Sample records for adjacent sea ice

  1. Variability and Trends in Sea Ice Extent and Ice Production in the Ross Sea

    NASA Technical Reports Server (NTRS)

    Comiso, Josefino; Kwok, Ronald; Martin, Seelye; Gordon, Arnold L.

    2011-01-01

    Salt release during sea ice formation in the Ross Sea coastal regions is regarded as a primary forcing for the regional generation of Antarctic Bottom Water. Passive microwave data from November 1978 through 2008 are used to examine the detailed seasonal and interannual characteristics of the sea ice cover of the Ross Sea and the adjacent Bellingshausen and Amundsen seas. For this period the sea ice extent in the Ross Sea shows the greatest increase of all the Antarctic seas. Variability in the ice cover in these regions is linked to changes in the Southern Annular Mode and secondarily to the Antarctic Circumpolar Wave. Over the Ross Sea shelf, analysis of sea ice drift data from 1992 to 2008 yields a positive rate of increase in the net ice export of about 30,000 sq km/yr. For a characteristic ice thickness of 0.6 m, this yields a volume transport of about 20 cu km/yr, which is almost identical, within error bars, to our estimate of the trend in ice production. The increase in brine rejection in the Ross Shelf Polynya associated with the estimated increase with the ice production, however, is not consistent with the reported Ross Sea salinity decrease. The locally generated sea ice enhancement of Ross Sea salinity may be offset by an increase of relatively low salinity of the water advected into the region from the Amundsen Sea, a consequence of increased precipitation and regional glacial ice melt.

  2. Sea ice and oceanic processes on the Ross Sea continental shelf

    NASA Technical Reports Server (NTRS)

    Jacobs, S. S.; Comiso, J. C.

    1989-01-01

    The spatial and temporal variability of Antarctic sea ice concentrations on the Ross Sea continental shelf have been investigated in relation to oceanic and atmospheric forcing. Sea ice data were derived from Nimbus 7 scanning multichannel microwave radiometer (SMMR) brightness temperatures from 1979-1986. Ice cover over the shelf was persistently lower than above the adjacent deep ocean, averaging 86 percent during winter with little month-to-month of interannual variability. The large spring Ross Sea polynya on the western shelf results in a longer period of summer insolation, greater surface layer heat storage, and later ice formation in that region the following autumn.

  3. Sea ice and oceanic processes on the Ross Sea continental shelf

    NASA Astrophysics Data System (ADS)

    Jacobs, S. S.; Comiso, J. C.

    1989-12-01

    We have investigated the spatial and temporal variability of Antarctic sea ice concentrations on the Ross Sea continental shelf, in relation to oceanic and atmospheric forcing. Sea ice data were derived from Nimbus 7 scanning multichannel microwave radiometer (SMMR) brightness temperatures from 1979-1986. Ice cover over the shelf was persistently lower than above the adjacent deep ocean, averaging 86% during winter with little month-to-month or interannual variability. The large spring Ross Sea polynya on the western shelf results in a longer period of summer insolation, greater surface layer heat storage, and later ice formation in that region the following autumn. Newly identified Pennell and Ross Passage polynyas near the continental shelf break appear to be maintained in part by divergence above a submarine bank and by upwelling of warmer water near the slope front. Warmer subsurface water enters the shelf region year-round and will retard ice growth and enhance heat flux to the atmosphere when entrained in the strong winter vertical circulation. Temperatures at 125-m depth on a mooring near the Ross Ice Shelf during July 1984 averaged 0.15°C above freezing, sufficient to support a vertical heat flux above 100 W/m2. Monthly average subsurface ocean temperatures along the Ross Ice Shelf lag the air temperature cycle and begin to rise several weeks before spring ice breakout. The coarse SMMR resolution and dynamic ice shelf coastlines can compromise the use of microwave sea ice data near continental boundaries.

  4. Ice Bridge Antarctic Sea Ice

    NASA Image and Video Library

    2009-10-21

    Sea ice is seen out the window of NASA's DC-8 research aircraft as it flies 2,000 feet above the Bellingshausen Sea in West Antarctica on Wednesday, Oct., 21, 2009. This was the fourth science flight of NASA’s Operation Ice Bridge airborne Earth science mission to study Antarctic ice sheets, sea ice, and ice shelves. Photo Credit: (NASA/Jane Peterson)

  5. Arctic and Antarctic Sea Ice Changes and Impacts (Invited)

    NASA Astrophysics Data System (ADS)

    Nghiem, S. V.

    2013-12-01

    The extent of springtime Arctic perennial sea ice, important to preconditioning summer melt and to polar sunrise photochemistry, continues its precipitous reduction in the last decade marked by a record low in 2012, as the Bromine, Ozone, and Mercury Experiment (BROMEX) was conducted around Barrow, Alaska, to investigate impacts of sea ice reduction on photochemical processes, transport, and distribution in the polar environment. In spring 2013, there was further loss of perennial sea ice, as it was not observed in the ocean region adjacent to the Alaskan north coast, where there was a stretch of perennial sea ice in 2012 in the Beaufort Sea and Chukchi Sea. In contrast to the rapid and extensive loss of sea ice in the Arctic, Antarctic sea ice has a trend of a slight increase in the past three decades. Given the significant variability in time and in space together with uncertainties in satellite observations, the increasing trend of Antarctic sea ice may arguably be considered as having a low confidence level; however, there was no overall reduction of Antarctic sea ice extent anywhere close to the decreasing rate of Arctic sea ice. There exist publications presenting various factors driving changes in Arctic and Antarctic sea ice. After a short review of these published factors, new observations and atmospheric, oceanic, hydrological, and geological mechanisms contributed to different behaviors of sea ice changes in the Arctic and Antarctic are presented. The contribution from of hydrologic factors may provide a linkage to and enhance thermal impacts from lower latitudes. While geological factors may affect the sensitivity of sea ice response to climate change, these factors can serve as the long-term memory in the system that should be exploited to improve future projections or predictions of sea ice changes. Furthermore, similarities and differences in chemical impacts of Arctic and Antarctic sea ice changes are discussed. Understanding sea ice changes and

  6. Sunlight, Sea Ice, and the Ice Albedo Feedback in a Changing Arctic Sea Ice Cover

    DTIC Science & Technology

    2013-09-30

    Sea Ice , and the Ice Albedo Feedback in a...COVERED 00-00-2013 to 00-00-2013 4. TITLE AND SUBTITLE Sunlight, Sea Ice , and the Ice Albedo Feedback in a Changing Arctic Sea Ice Cover 5a...during a period when incident solar irradiance is large increasing solar heat input to the ice . Seasonal sea ice typically has a smaller albedo

  7. Windows in Arctic sea ice: Light transmission and ice algae in a refrozen lead

    NASA Astrophysics Data System (ADS)

    Kauko, Hanna M.; Taskjelle, Torbjørn; Assmy, Philipp; Pavlov, Alexey K.; Mundy, C. J.; Duarte, Pedro; Fernández-Méndez, Mar; Olsen, Lasse M.; Hudson, Stephen R.; Johnsen, Geir; Elliott, Ashley; Wang, Feiyue; Granskog, Mats A.

    2017-06-01

    The Arctic Ocean is rapidly changing from thicker multiyear to thinner first-year ice cover, with significant consequences for radiative transfer through the ice pack and light availability for algal growth. A thinner, more dynamic ice cover will possibly result in more frequent leads, covered by newly formed ice with little snow cover. We studied a refrozen lead (≤0.27 m ice) in drifting pack ice north of Svalbard (80.5-81.8°N) in May-June 2015 during the Norwegian young sea ICE expedition (N-ICE2015). We measured downwelling incident and ice-transmitted spectral irradiance, and colored dissolved organic matter (CDOM), particle absorption, ultraviolet (UV)-protecting mycosporine-like amino acids (MAAs), and chlorophyll a (Chl a) in melted sea ice samples. We found occasionally very high MAA concentrations (up to 39 mg m-3, mean 4.5 ± 7.8 mg m-3) and MAA to Chl a ratios (up to 6.3, mean 1.2 ± 1.3). Disagreement in modeled and observed transmittance in the UV range let us conclude that MAA signatures in CDOM absorption spectra may be artifacts due to osmotic shock during ice melting. Although observed PAR (photosynthetically active radiation) transmittance through the thin ice was significantly higher than that of the adjacent thicker ice with deep snow cover, ice algal standing stocks were low (≤2.31 mg Chl a m-2) and similar to the adjacent ice. Ice algal accumulation in the lead was possibly delayed by the low inoculum and the time needed for photoacclimation to the high-light environment. However, leads are important for phytoplankton growth by acting like windows into the water column.

  8. Arctic Sea Ice Predictability and the Sea Ice Prediction Network

    NASA Astrophysics Data System (ADS)

    Wiggins, H. V.; Stroeve, J. C.

    2014-12-01

    Drastic reductions in Arctic sea ice cover have increased the demand for Arctic sea ice predictions by a range of stakeholders, including local communities, resource managers, industry and the public. The science of sea-ice prediction has been challenged to keep up with these developments. Efforts such as the SEARCH Sea Ice Outlook (SIO; http://www.arcus.org/sipn/sea-ice-outlook) and the Sea Ice for Walrus Outlook have provided a forum for the international sea-ice prediction and observing community to explore and compare different approaches. The SIO, originally organized by the Study of Environmental Change (SEARCH), is now managed by the new Sea Ice Prediction Network (SIPN), which is building a collaborative network of scientists and stakeholders to improve arctic sea ice prediction. The SIO synthesizes predictions from a variety of methods, including heuristic and from a statistical and/or dynamical model. In a recent study, SIO data from 2008 to 2013 were analyzed. The analysis revealed that in some years the predictions were very successful, in other years they were not. Years that were anomalous compared to the long-term trend have proven more difficult to predict, regardless of which method was employed. This year, in response to feedback from users and contributors to the SIO, several enhancements have been made to the SIO reports. One is to encourage contributors to provide spatial probability maps of sea ice cover in September and the first day each location becomes ice-free; these are an example of subseasonal to seasonal, local-scale predictions. Another enhancement is a separate analysis of the modeling contributions. In the June 2014 SIO report, 10 of 28 outlooks were produced from models that explicitly simulate sea ice from dynamic-thermodynamic sea ice models. Half of the models included fully-coupled (atmosphere, ice, and ocean) models that additionally employ data assimilation. Both of these subsets (models and coupled models with data

  9. Validation and Interpretation of a new sea ice GlobIce dataset using buoys and the CICE sea ice model

    NASA Astrophysics Data System (ADS)

    Flocco, D.; Laxon, S. W.; Feltham, D. L.; Haas, C.

    2012-04-01

    The GlobIce project has provided high resolution sea ice product datasets over the Arctic derived from SAR data in the ESA archive. The products are validated sea ice motion, deformation and fluxes through straits. GlobIce sea ice velocities, deformation data and sea ice concentration have been validated using buoy data provided by the International Arctic Buoy Program (IABP). Over 95% of the GlobIce and buoy data analysed fell within 5 km of each other. The GlobIce Eulerian image pair product showed a high correlation with buoy data. The sea ice concentration product was compared to SSM/I data. An evaluation of the validity of the GlobICE data will be presented in this work. GlobICE sea ice velocity and deformation were compared with runs of the CICE sea ice model: in particular the mass fluxes through the straits were used to investigate the correlation between the winter behaviour of sea ice and the sea ice state in the following summer.

  10. Sea ice ecosystems.

    PubMed

    Arrigo, Kevin R

    2014-01-01

    Polar sea ice is one of the largest ecosystems on Earth. The liquid brine fraction of the ice matrix is home to a diverse array of organisms, ranging from tiny archaea to larger fish and invertebrates. These organisms can tolerate high brine salinity and low temperature but do best when conditions are milder. Thriving ice algal communities, generally dominated by diatoms, live at the ice/water interface and in recently flooded surface and interior layers, especially during spring, when temperatures begin to rise. Although protists dominate the sea ice biomass, heterotrophic bacteria are also abundant. The sea ice ecosystem provides food for a host of animals, with crustaceans being the most conspicuous. Uneaten organic matter from the ice sinks through the water column and feeds benthic ecosystems. As sea ice extent declines, ice algae likely contribute a shrinking fraction of the total amount of organic matter produced in polar waters.

  11. The Formation each Winter of the Circumpolar Wave in the Sea Ice around Antarctica

    NASA Technical Reports Server (NTRS)

    Gloersen, Per; White, Warren B.

    1999-01-01

    Seeking to improve upon the visualization of the Antarctic Circumpolar Wave (ACW) , we compare a 16-year sequence of 6-month winter averages of Antarctic sea ice extents and concentrations with those of adjacent sea surface temperatures (SSTs). Here we follow SSTs around the globe along the maximum sea ice edge rather than in a zonal band equatorward of it. The results are similar to the earlier ones, but the ACWs do not propagate with equal amplitude or speed. Additionally in a sequence of 4 polar stereographic plots of these SSTs and sea ice concentrations, we find a remarkable correlation between SST minima and sea ice concentration maxima, even to the extent of matching contours across the ice-sea boundary, in the sector between 900E and the Palmer Peninsula. Based on these observations, we suggest that the memory of the ACW in the sea ice is carried from one Austral winter to the next by the neighboring SSTS, since the sea ice is nearly absent in the Austral summer.

  12. Ice Bridge Antarctic Sea Ice

    NASA Image and Video Library

    2009-10-21

    An iceberg is seen out the window of NASA's DC-8 research aircraft as it flies 2,000 feet above the Amundsen Sea in West Antarctica on Wednesday, Oct., 21, 2009. This was the fourth science flight of NASA’s Operation Ice Bridge airborne Earth science mission to study Antarctic ice sheets, sea ice, and ice shelves. Photo Credit: (NASA/Jane Peterson)

  13. Arctic Sea Ice Classification and Mapping for Surface Albedo Parameterization in Sea Ice Modeling

    NASA Astrophysics Data System (ADS)

    Nghiem, S. V.; Clemente-Colón, P.; Perovich, D. K.; Polashenski, C.; Simpson, W. R.; Rigor, I. G.; Woods, J. E.; Nguyen, D. T.; Neumann, G.

    2016-12-01

    A regime shift of Arctic sea ice from predominantly perennial sea ice (multi-year ice or MYI) to seasonal sea ice (first-year ice or FYI) has occurred in recent decades. This shift has profoundly altered the proportional composition of different sea ice classes and the surface albedo distribution pertaining to each sea ice class. Such changes impacts physical, chemical, and biological processes in the Arctic atmosphere-ice-ocean system. The drastic changes upset the traditional geophysical representation of surface albedo of the Arctic sea ice cover in current models. A critical science issue is that these profound changes must be rigorously and systematically observed and characterized to enable a transformative re-parameterization of key model inputs, such as ice surface albedo, to ice-ocean-atmosphere climate modeling in order to obtain re-analyses that accurately reproduce Arctic changes and also to improve sea ice and weather forecast models. Addressing this challenge is a strategy identified by the National Research Council study on "Seasonal to Decadal Predictions of Arctic Sea Ice - Challenges and Strategies" to replicate the new Arctic reality. We review results of albedo characteristics associated with different sea ice classes such as FYI and MYI. Then we demonstrate the capability for sea ice classification and mapping using algorithms developed by the Jet Propulsion Laboratory and by the U.S. National Ice Center for use with multi-sourced satellite radar data at L, C, and Ku bands. Results obtained with independent algorithms for different radar frequencies consistently identify sea ice classes and thereby cross-verify the sea ice classification methods. Moreover, field observations obtained from buoy webcams and along an extensive trek across Elson Lagoon and a sector of the Beaufort Sea during the BRomine, Ozone, and Mercury EXperiment (BROMEX) in March 2012 are used to validate satellite products of sea ice classes. This research enables the mapping

  14. Seafloor Control on Sea Ice

    NASA Technical Reports Server (NTRS)

    Nghiem, S. V.; Clemente-Colon, P.; Rigor, I. G.; Hall, D. K.; Neumann, G.

    2011-01-01

    The seafloor has a profound role in Arctic sea ice formation and seasonal evolution. Ocean bathymetry controls the distribution and mixing of warm and cold waters, which may originate from different sources, thereby dictating the pattern of sea ice on the ocean surface. Sea ice dynamics, forced by surface winds, are also guided by seafloor features in preferential directions. Here, satellite mapping of sea ice together with buoy measurements are used to reveal the bathymetric control on sea ice growth and dynamics. Bathymetric effects on sea ice formation are clearly observed in the conformation between sea ice patterns and bathymetric characteristics in the peripheral seas. Beyond local features, bathymetric control appears over extensive ice-prone regions across the Arctic Ocean. The large-scale conformation between bathymetry and patterns of different synoptic sea ice classes, including seasonal and perennial sea ice, is identified. An implication of the bathymetric influence is that the maximum extent of the total sea ice cover is relatively stable, as observed by scatterometer data in the decade of the 2000s, while the minimum ice extent has decreased drastically. Because of the geologic control, the sea ice cover can expand only as far as it reaches the seashore, the continental shelf break, or other pronounced bathymetric features in the peripheral seas. Since the seafloor does not change significantly for decades or centuries, sea ice patterns can be recurrent around certain bathymetric features, which, once identified, may help improve short-term forecast and seasonal outlook of the sea ice cover. Moreover, the seafloor can indirectly influence cloud cover by its control on sea ice distribution, which differentially modulates the latent heat flux through ice covered and open water areas.

  15. Effects of recent decreases in arctic sea ice on an ice-associated marine bird

    NASA Astrophysics Data System (ADS)

    Divoky, George J.; Lukacs, Paul M.; Druckenmiller, Matthew L.

    2015-08-01

    Recent major reductions in summer arctic sea ice extent could be expected to be affecting the distributions and life histories of arctic marine biota adapted to living adjacent to sea ice. Of major concern are the effects of ice reductions, and associated increasing SST, on the most abundant forage fish in the Arctic, Arctic cod (Boreogadus saida), the primary prey for the region's upper trophic level marine predators. The black guillemot (Cepphus grylle mandtii) is an ice-obligate diving seabird specializing in feeding on Arctic cod and has been studied annually since 1975 at a breeding colony in the western Beaufort Sea. The data set is one of the few allowing assessment of the response of an upper trophic marine predator to recent decadal changes in the region's cryosphere. Analysis of oceanographic conditions north of the colony from 1975 to 2012 for the annual period when parents provision young (mid-July to early September), found no major regime shifts in ice extent or SST until the late 1990s with major decreases in ice and increases in SST in the first decade of the 21st Century. We examined decadal variation in late summer oceanographic conditions, nestling diet and success, and overwinter adult survival, comparing a historical period (1975-1984) with a recent (2003-2012) one. In the historical period sea ice retreated an average of 1.8 km per day from 15 July to 1 September to an average distance of 95.8 km from the colony, while in the recent period ice retreat averaged 9.8 km per day to an average distance of 506.9 km for the same time period. SST adjacent to the island increased an average of 2.9 °C between the two periods. While Arctic cod comprised over 95% of the prey provided to nestlings in the historical period, in the recent period 80% of the years had seasonal decreases, with Arctic cod decreasing to <5% of the nestling diet, and nearshore demersals, primarily sculpin (Cottidae), comprising the majority of the diet. A five-fold increase in

  16. Sea ice in the Greenland Sea

    NASA Image and Video Library

    2017-12-08

    As the northern hemisphere experiences the heat of summer, ice moves and melts in the Arctic waters and the far northern lands surrounding it. The Moderate Resolution Imaging Spectroradiometer (MODIS) aboard NASA’s Aqua satellite captured this true-color image of sea ice off Greenland on July 16, 2015. Large chunks of melting sea ice can be seen in the sea ice off the coast, and to the south spirals of ice have been shaped by the winds and currents that move across the Greenland Sea. Along the Greenland coast, cold, fresh melt water from the glaciers flows out to the sea, as do newly calved icebergs. Frigid air from interior Greenland pushes the ice away from the shoreline, and the mixing of cold water and air allows some sea ice to be sustained even at the height of summer. According to observations from satellites, 2015 is on track to be another low year for arctic summer sea ice cover. The past ten years have included nine of the lowest ice extents on record. The annual minimum typically occurs in late August or early September. The amount of Arctic sea ice cover has been dropping as global temperatures rise. The Arctic is two to three times more sensitive to temperature changes as the Earth as a whole. Credit: NASA/GSFC/Jeff Schmaltz/MODIS Land Rapid Response Team NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

  17. Sea Ice Summer Camp: Bringing Together Arctic Sea Ice Modelers and Observers

    NASA Astrophysics Data System (ADS)

    Perovich, D. K.; Holland, M. M.

    2016-12-01

    The Arctic sea ice has undergone dramatic change and numerical models project this to continue for the foreseeable future. Understanding the mechanisms behind sea ice loss and its consequences for the larger Arctic and global systems is of critical importance if we are to anticipate and plan for the future. One impediment to progress is a disconnect between the observational and modeling communities. A sea ice summer camp was held in Barrow Alaska from 26 May to 1 June 2016 to overcome this impediment and better integrate the sea ice community. The 25 participants were a mix of modelers and observers from 13 different institutions at career stages from graduate student to senior scientist. The summer camp provided an accelerated program on sea ice observations and models and also fostered future collaborative interdisciplinary activities. Each morning was spent in the classroom with a daily lecture on an aspect of modeling or remote sensing followed by practical exercises. Topics included using models to assess sensitivity, to test hypotheses and to explore sources of uncertainty in future Arctic sea ice loss. The afternoons were spent on the ice making observations. There were four observational activities; albedo observations, ice thickness measurements, ice coring and physical properties, and ice morphology surveys. The last field day consisted of a grand challenge where the group formulated a hypothesis, developed an observational and modeling strategy to test the hypothesis, and then integrated the observations and model results. The impacts of changing sea ice are being felt today in Barrow Alaska. We opened a dialog with Barrow community members to further understand these changes. This included an evening discussion with two Barrow sea ice experts and a community presentation of our work in a public lecture at the Inupiat Heritage Center.

  18. Atmosphere-Ice-Ocean-Ecosystem Processes in a Thinner Arctic Sea Ice Regime: The Norwegian Young Sea ICE (N-ICE2015) Expedition

    NASA Astrophysics Data System (ADS)

    Granskog, Mats A.; Fer, Ilker; Rinke, Annette; Steen, Harald

    2018-03-01

    Arctic sea ice has been in rapid decline the last decade and the Norwegian young sea ICE (N-ICE2015) expedition sought to investigate key processes in a thin Arctic sea ice regime, with emphasis on atmosphere-snow-ice-ocean dynamics and sea ice associated ecosystem. The main findings from a half-year long campaign are collected into this special section spanning the Journal of Geophysical Research: Atmospheres, Journal of Geophysical Research: Oceans, and Journal of Geophysical Research: Biogeosciences and provide a basis for a better understanding of processes in a thin sea ice regime in the high Arctic. All data from the campaign are made freely available to the research community.

  19. Improved method for sea ice age computation based on combination of sea ice drift and concentration

    NASA Astrophysics Data System (ADS)

    Korosov, Anton; Rampal, Pierre; Lavergne, Thomas; Aaboe, Signe

    2017-04-01

    Sea Ice Age is one of the components of the Sea Ice ECV as defined by the Global Climate Observing System (GCOS) [WMO, 2015]. It is an important climate indicator describing the sea ice state in addition to sea ice concentration (SIC) and thickness (SIT). The amount of old/thick ice in the Arctic Ocean has been decreasing dramatically [Perovich et al. 2015]. Kwok et al. [2009] reported significant decline in the MYI share and consequent loss of thickness and therefore volume. Today, there is only one acknowledged sea ice age climate data record [Tschudi, et al. 2015], based on Maslanik et al. [2011] provided by National Snow and Ice Data Center (NSIDC) [http://nsidc.org/data/docs/daac/nsidc0611-sea-ice-age/]. The sea ice age algorithm [Fowler et al., 2004] is using satellite-derived ice drift for Lagrangian tracking of individual ice parcels (12-km grid cells) defined by areas of sea ice concentration > 15% [Maslanik et al., 2011], i.e. sea ice extent, according to the NASA Team algorithm [Cavalieri et al., 1984]. This approach has several drawbacks. (1) Using sea ice extent instead of sea ice concentration leads to overestimation of the amount of older ice. (2) The individual ice parcels are not advected uniformly over (long) time. This leads to undersampling in areas of consistent ice divergence. (3) The end product grid cells are assigned the age of the oldest ice parcel within that cell, and the frequency distribution of the ice age is not taken into account. In addition, the base sea ice drift product (https://nsidc.org/data/docs/daac/nsidc0116_icemotion.gd.html) is known to exhibit greatly reduced accuracy during the summer season [Sumata et al 2014, Szanyi, 2016] as it only relies on a combination of sea ice drifter trajectories and wind-driven "free-drift" motion during summer. This results in a significant overestimate of old-ice content, incorrect shape of the old-ice pack, and lack of information about the ice age distribution within the grid cells. We

  20. Processes driving sea ice variability in the Bering Sea in an eddying ocean/sea ice model: Mean seasonal cycle

    NASA Astrophysics Data System (ADS)

    Li, Linghan; McClean, Julie L.; Miller, Arthur J.; Eisenman, Ian; Hendershott, Myrl C.; Papadopoulos, Caroline A.

    2014-12-01

    The seasonal cycle of sea ice variability in the Bering Sea, together with the thermodynamic and dynamic processes that control it, are examined in a fine resolution (1/10°) global coupled ocean/sea-ice model configured in the Community Earth System Model (CESM) framework. The ocean/sea-ice model consists of the Los Alamos National Laboratory Parallel Ocean Program (POP) and the Los Alamos Sea Ice Model (CICE). The model was forced with time-varying reanalysis atmospheric forcing for the time period 1970-1989. This study focuses on the time period 1980-1989. The simulated seasonal-mean fields of sea ice concentration strongly resemble satellite-derived observations, as quantified by root-mean-square errors and pattern correlation coefficients. The sea ice energy budget reveals that the seasonal thermodynamic ice volume changes are dominated by the surface energy flux between the atmosphere and the ice in the northern region and by heat flux from the ocean to the ice along the southern ice edge, especially on the western side. The sea ice force balance analysis shows that sea ice motion is largely associated with wind stress. The force due to divergence of the internal ice stress tensor is large near the land boundaries in the north, and it is small in the central and southern ice-covered region. During winter, which dominates the annual mean, it is found that the simulated sea ice was mainly formed in the northern Bering Sea, with the maximum ice growth rate occurring along the coast due to cold air from northerly winds and ice motion away from the coast. South of St Lawrence Island, winds drive the model sea ice southwestward from the north to the southwestern part of the ice-covered region. Along the ice edge in the western Bering Sea, model sea ice is melted by warm ocean water, which is carried by the simulated Bering Slope Current flowing to the northwest, resulting in the S-shaped asymmetric ice edge. In spring and fall, similar thermodynamic and dynamic

  1. There goes the sea ice: following Arctic sea ice parcels and their properties.

    NASA Astrophysics Data System (ADS)

    Tschudi, M. A.; Tooth, M.; Meier, W.; Stewart, S.

    2017-12-01

    Arctic sea ice distribution has changed considerably over the last couple of decades. Sea ice extent record minimums have been observed in recent years, the distribution of ice age now heavily favors younger ice, and sea ice is likely thinning. This new state of the Arctic sea ice cover has several impacts, including effects on marine life, feedback on the warming of the ocean and atmosphere, and on the future evolution of the ice pack. The shift in the state of the ice cover, from a pack dominated by older ice, to the current state of a pack with mostly young ice, impacts specific properties of the ice pack, and consequently the pack's response to the changing Arctic climate. For example, younger ice typically contains more numerous melt ponds during the melt season, resulting in a lower albedo. First-year ice is typically thinner and more fragile than multi-year ice, making it more susceptible to dynamic and thermodynamic forcing. To investigate the response of the ice pack to climate forcing during summertime melt, we have developed a database that tracks individual Arctic sea ice parcels along with associated properties as these parcels advect during the summer. Our database tracks parcels in the Beaufort Sea, from 1985 - present, along with variables such as ice surface temperature, albedo, ice concentration, and convergence. We are using this database to deduce how these thousands of tracked parcels fare during summer melt, i.e. what fraction of the parcels advect through the Beaufort, and what fraction melts out? The tracked variables describe the thermodynamic and dynamic forcing on these parcels during their journey. This database will also be made available to all interested investigators, after it is published in the near future. The attached image shows the ice surface temperature of all parcels (right) that advected through the Beaufort Sea region (left) in 2014.

  2. Towards Improving Sea Ice Predictabiity: Evaluating Climate Models Against Satellite Sea Ice Observations

    NASA Astrophysics Data System (ADS)

    Stroeve, J. C.

    2014-12-01

    The last four decades have seen a remarkable decline in the spatial extent of the Arctic sea ice cover, presenting both challenges and opportunities to Arctic residents, government agencies and industry. After the record low extent in September 2007 effort has increased to improve seasonal, decadal-scale and longer-term predictions of the sea ice cover. Coupled global climate models (GCMs) consistently project that if greenhouse gas concentrations continue to rise, the eventual outcome will be a complete loss of the multiyear ice cover. However, confidence in these projections depends o HoHoweon the models ability to reproduce features of the present-day climate. Comparison between models participating in the World Climate Research Programme Coupled Model Intercomparison Project Phase 5 (CMIP5) and observations of sea ice extent and thickness show that (1) historical trends from 85% of the model ensemble members remain smaller than observed, and (2) spatial patterns of sea ice thickness are poorly represented in most models. Part of the explanation lies with a failure of models to represent details of the mean atmospheric circulation pattern that governs the transport and spatial distribution of sea ice. These results raise concerns regarding the ability of CMIP5 models to realistically represent the processes driving the decline of Arctic sea ice and to project the timing of when a seasonally ice-free Arctic may be realized. On shorter time-scales, seasonal sea ice prediction has been challenged to predict the sea ice extent from Arctic conditions a few months to a year in advance. Efforts such as the Sea Ice Outlook (SIO) project, originally organized through the Study of Environmental Change (SEARCH) and now managed by the Sea Ice Prediction Network project (SIPN) synthesize predictions of the September sea ice extent based on a variety of approaches, including heuristic, statistical and dynamical modeling. Analysis of SIO contributions reveals that when the

  3. Submesoscale sea ice-ocean interactions in marginal ice zones

    NASA Astrophysics Data System (ADS)

    Thompson, A. F.; Manucharyan, G.

    2017-12-01

    Signatures of ocean eddies, fronts and filaments are commonly observed within the marginal ice zones (MIZ) from satellite images of sea ice concentration, in situ observations via ice-tethered profilers or under-ice gliders. Localized and intermittent sea ice heating and advection by ocean eddies are currently not accounted for in climate models and may contribute to their biases and errors in sea ice forecasts. Here, we explore mechanical sea ice interactions with underlying submesoscale ocean turbulence via a suite of numerical simulations. We demonstrate that the release of potential energy stored in meltwater fronts can lead to energetic submesoscale motions along MIZs with sizes O(10 km) and Rossby numbers O(1). In low-wind conditions, cyclonic eddies and filaments efficiently trap the sea ice and advect it over warmer surface ocean waters where it can effectively melt. The horizontal eddy diffusivity of sea ice mass and heat across the MIZ can reach O(200 m2 s-1). Submesoscale ocean variability also induces large vertical velocities (order of 10 m day-1) that can bring relatively warm subsurface waters into the mixed layer. The ocean-sea ice heat fluxes are localized over cyclonic eddies and filaments reaching about 100 W m-2. We speculate that these submesoscale-driven intermittent fluxes of heat and sea ice can potentially contribute to the seasonal evolution of MIZs. With continuing global warming and sea ice thickness reduction in the Arctic Ocean, as well as the large expanse of thin sea ice in the Southern Ocean, submesoscale sea ice-ocean processes are expected to play a significant role in the climate system.

  4. Submesoscale Sea Ice-Ocean Interactions in Marginal Ice Zones

    NASA Astrophysics Data System (ADS)

    Manucharyan, Georgy E.; Thompson, Andrew F.

    2017-12-01

    Signatures of ocean eddies, fronts, and filaments are commonly observed within marginal ice zones (MIZs) from satellite images of sea ice concentration, and in situ observations via ice-tethered profilers or underice gliders. However, localized and intermittent sea ice heating and advection by ocean eddies are currently not accounted for in climate models and may contribute to their biases and errors in sea ice forecasts. Here, we explore mechanical sea ice interactions with underlying submesoscale ocean turbulence. We demonstrate that the release of potential energy stored in meltwater fronts can lead to energetic submesoscale motions along MIZs with spatial scales O(10 km) and Rossby numbers O(1). In low-wind conditions, cyclonic eddies and filaments efficiently trap the sea ice and advect it over warmer surface ocean waters where it can effectively melt. The horizontal eddy diffusivity of sea ice mass and heat across the MIZ can reach O(200 m2 s-1). Submesoscale ocean variability also induces large vertical velocities (order 10 m d-1) that can bring relatively warm subsurface waters into the mixed layer. The ocean-sea ice heat fluxes are localized over cyclonic eddies and filaments reaching about 100 W m-2. We speculate that these submesoscale-driven intermittent fluxes of heat and sea ice can contribute to the seasonal evolution of MIZs. With the continuing global warming and sea ice thickness reduction in the Arctic Ocean, submesoscale sea ice-ocean processes are expected to become increasingly prominent.

  5. Sea Ice

    NASA Technical Reports Server (NTRS)

    Perovich, D.; Gerland, S.; Hendricks, S.; Meier, Walter N.; Nicolaus, M.; Richter-Menge, J.; Tschudi, M.

    2013-01-01

    During 2013, Arctic sea ice extent remained well below normal, but the September 2013 minimum extent was substantially higher than the record-breaking minimum in 2012. Nonetheless, the minimum was still much lower than normal and the long-term trend Arctic September extent is -13.7 per decade relative to the 1981-2010 average. The less extreme conditions this year compared to 2012 were due to cooler temperatures and wind patterns that favored retention of ice through the summer. Sea ice thickness and volume remained near record-low levels, though indications are of slightly thicker ice compared to the record low of 2012.

  6. Variability and Trends in the Arctic Sea Ice Cover: Results from Different Techniques

    NASA Technical Reports Server (NTRS)

    Comiso, Josefino C.; Meier, Walter N.; Gersten, Robert

    2017-01-01

    Variability and trend studies of sea ice in the Arctic have been conducted using products derived from the same raw passive microwave data but by different groups using different algorithms. This study provides consistency assessment of four of the leading products, namely, Goddard Bootstrap (SB2), Goddard NASA Team (NT1), EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI-SAF 1.2), and Hadley HadISST 2.2 data in evaluating variability and trends in the Arctic sea ice cover. All four provide generally similar ice patterns but significant disagreements in ice concentration distributions especially in the marginal ice zone and adjacent regions in winter and meltponded areas in summer. The discrepancies are primarily due to different ways the four techniques account for occurrences of new ice and meltponding. However, results show that the different products generally provide consistent and similar representation of the state of the Arctic sea ice cover. Hadley and NT1 data usually provide the highest and lowest monthly ice extents, respectively. The Hadley data also show the lowest trends in ice extent and ice area at negative 3.88 percent decade and negative 4.37 percent decade, respectively, compared to an average of negative 4.36 percent decade and negative 4.57 percent decade for all four. Trend maps also show similar spatial distribution for all four with the largest negative trends occurring at the Kara/Barents Sea and Beaufort Sea regions, where sea ice has been retreating the fastest. The good agreement of the trends especially with updated data provides strong confidence in the quantification of the rate of decline in the Arctic sea ice cover.

  7. Stress and deformation characteristics of sea ice in a high resolution numerical sea ice model.

    NASA Astrophysics Data System (ADS)

    Heorton, Harry; Feltham, Daniel; Tsamados, Michel

    2017-04-01

    The drift and deformation of sea ice floating on the polar oceans is due to the applied wind and ocean currents. The deformations of sea ice over ocean basin length scales have observable patterns; cracks and leads in satellite images and within the velocity fields generated from floe tracking. In a climate sea ice model the deformation of sea ice over ocean basin length scales is modelled using a rheology that represents the relationship between stresses and deformation within the sea ice cover. Here we investigate the link between observable deformation characteristics and the underlying internal sea ice stresses and force balance using the Los Alamos numerical sea ice climate model. In order to mimic laboratory experiments on the deformation of small cubes of sea ice we have developed an idealised square domain that tests the model response at spatial resolutions of up to 500m. We use the Elastic Anisotropic Plastic and Elastic Viscous Plastic rheologies, comparing their stability over varying resolutions and time scales. Sea ice within the domain is forced by idealised winds in order to compare the confinement of wind stresses and internal sea ice stresses. We document the characteristic deformation patterns of convergent, divergent and rotating stress states.

  8. Early Student Support to Investigate the Role of Sea Ice-Albedo Feedback in Sea Ice Predictions

    DTIC Science & Technology

    2014-09-30

    Ice - Albedo Feedback in Sea Ice Predictions Cecilia M. Bitz Atmospheric Sciences MS351640 University of Washington Seattle, WA 98196-1640 phone...TERM GOALS The overarching goals of this project are to understand the role of sea ice - albedo feedback on sea ice predictability, to improve how... sea - ice albedo is modeled and how sea ice predictions are initialized, and then to evaluate how these improvements

  9. Sea-ice dynamics strongly promote Snowball Earth initiation and destabilize tropical sea-ice margins

    NASA Astrophysics Data System (ADS)

    Voigt, A.; Abbot, D. S.

    2012-12-01

    The Snowball Earth bifurcation, or runaway ice-albedo feedback, is defined for particular boundary conditions by a critical CO2 and a critical sea-ice cover (SI), both of which are essential for evaluating hypotheses related to Neoproterozoic glaciations. Previous work has shown that the Snowball Earth bifurcation, denoted as (CO2, SI)*, differs greatly among climate models. Here, we study the effect of bare sea-ice albedo, sea-ice dynamics and ocean heat transport on (CO2, SI)* in the atmosphere-ocean general circulation model ECHAM5/MPI-OM with Marinoan (~ 635 Ma) continents and solar insolation (94% of modern). In its standard setup, ECHAM5/MPI-OM initiates a~Snowball Earth much more easily than other climate models at (CO2, SI)* ≈ (500 ppm, 55%). Replacing the model's standard bare sea-ice albedo of 0.75 by a much lower value of 0.45, we find (CO2, SI)* ≈ (204 ppm, 70%). This is consistent with previous work and results from net evaporation and local melting near the sea-ice margin. When we additionally disable sea-ice dynamics, we find that the Snowball Earth bifurcation can be pushed even closer to the equator and occurs at a hundred times lower CO2: (CO2, SI)* ≈ (2 ppm, 85%). Therefore, the simulation of sea-ice dynamics in ECHAM5/MPI-OM is a dominant determinant of its high critical CO2 for Snowball initiation relative to other models. Ocean heat transport has no effect on the critical sea-ice cover and only slightly decreases the critical CO2. For disabled sea-ice dynamics, the state with 85% sea-ice cover is stabilized by the Jormungand mechanism and shares characteristics with the Jormungand climate states. However, there is no indication of the Jormungand bifurcation and hysteresis in ECHAM5/MPI-OM. The state with 85% sea-ice cover therefore is a soft Snowball state rather than a true Jormungand state. Overall, our results demonstrate that differences in sea-ice dynamics schemes can be at least as important as differences in sea-ice albedo for

  10. The application of ERTS imagery to monitoring Arctic sea ice. [mapping ice in Bering Sea, Beaufort Sea, Canadian Archipelago, and Greenland Sea

    NASA Technical Reports Server (NTRS)

    Barnes, J. C. (Principal Investigator); Bowley, C. J.

    1974-01-01

    The author has identified the following significant results. Because of the effect of sea ice on the heat balance of the Arctic and because of the expanding economic interest in arctic oil and minerals, extensive monitoring and further study of sea ice is required. The application of ERTS data for mapping ice is evaluated for several arctic areas, including the Bering Sea, the eastern Beaufort Sea, parts of the Canadian Archipelago, and the Greenland Sea. Interpretive techniques are discussed, and the scales and types of ice features that can be detected are described. For the Bering Sea, a sample of ERTS-1 imagery is compared with visual ice reports and aerial photography from the NASA CV-990 aircraft. The results of the investigation demonstrate that ERTS-1 imagery has substantial practical application for monitoring arctic sea ice. Ice features as small as 80-100 m in width can be detected, and the combined use of the visible and near-IR imagery is a powerful tool for identifying ice types. Sequential ERTS-1 observations at high latitudes enable ice deformations and movements to be mapped. Ice conditions in the Bering Sea during early March depicted in ERTS-1 images are in close agreement with aerial ice observations and photographs.

  11. A review of sea ice proxy information from polar ice cores

    NASA Astrophysics Data System (ADS)

    Abram, Nerilie J.; Wolff, Eric W.; Curran, Mark A. J.

    2013-11-01

    Sea ice plays an important role in Earth's climate system. The lack of direct indications of past sea ice coverage, however, means that there is limited knowledge of the sensitivity and rate at which sea ice dynamics are involved in amplifying climate changes. As such, there is a need to develop new proxy records for reconstructing past sea ice conditions. Here we review the advances that have been made in using chemical tracers preserved in ice cores to determine past changes in sea ice cover around Antarctica. Ice core records of sea salt concentration show promise for revealing patterns of sea ice extent particularly over glacial-interglacial time scales. In the coldest climates, however, the sea salt signal appears to lose sensitivity and further work is required to determine how this proxy can be developed into a quantitative sea ice indicator. Methane sulphonic acid (MSA) in near-coastal ice cores has been used to reconstruct quantified changes and interannual variability in sea ice extent over shorter time scales spanning the last ˜160 years, and has potential to be extended to produce records of Antarctic sea ice changes throughout the Holocene. However the MSA ice core proxy also requires careful site assessment and interpretation alongside other palaeoclimate indicators to ensure reconstructions are not biased by non-sea ice factors, and we summarise some recommended strategies for the further development of sea ice histories from ice core MSA. For both proxies the limited information about the production and transfer of chemical markers from the sea ice zone to the Antarctic ice sheets remains an issue that requires further multidisciplinary study. Despite some exploratory and statistical work, the application of either proxy as an indicator of sea ice change in the Arctic also remains largely unknown. As information about these new ice core proxies builds, so too does the potential to develop a more comprehensive understanding of past changes in sea

  12. The importance of sea ice for exchange of habitat-specific protist communities in the Central Arctic Ocean

    NASA Astrophysics Data System (ADS)

    Hardge, Kristin; Peeken, Ilka; Neuhaus, Stefan; Lange, Benjamin A.; Stock, Alexandra; Stoeck, Thorsten; Weinisch, Lea; Metfies, Katja

    2017-01-01

    Sea ice is one of the main features influencing the Arctic marine protist community composition and diversity in sea ice and sea water. We analyzed protist communities within sea ice, melt pond water, under-ice water and deep-chlorophyll maximum water at eight sea ice stations sampled during summer of the 2012 record sea ice minimum year. Using Illumina sequencing, we identified characteristic communities associated with specific habitats and investigated protist exchange between these habitats. The highest abundance and diversity of unique taxa were found in sea ice, particularly in multi-year ice (MYI), highlighting the importance of sea ice as a unique habitat for sea ice protists. Melting of sea ice was associated with increased exchange of communities between sea ice and the underlying water column. In contrast, sea ice formation was associated with increased exchange between all four habitats, suggesting that brine rejection from the ice is an important factor for species redistribution in the Central Arctic. Ubiquitous taxa (e.g. Gymnodinium) that occurred in all habitats still had habitat-preferences. This demonstrates a limited ability to survive in adjacent but different environments. Our results suggest that the continued reduction of sea ice extent, and particularly of MYI, will likely lead to diminished protist exchange and subsequently, could reduce species diversity in all habitats of the Central Arctic Ocean. An important component of the unique sea ice protist community could be endangered because specialized taxa restricted to this habitat may not be able to adapt to rapid environmental changes.

  13. Validation and Interpretation of a New Sea Ice Globice Dataset Using Buoys and the Cice Sea Ice Model

    NASA Astrophysics Data System (ADS)

    Flocco, D.; Laxon, S. W.; Feltham, D. L.; Haas, C.

    2011-12-01

    The GlobIce project has provided high resolution sea ice product datasets over the Arctic derived from SAR data in the ESA archive. The products are validated sea ice motion, deformation and fluxes through straits. GlobIce sea ice velocities, deformation data and sea ice concentration have been validated using buoy data provided by the International Arctic Buoy Program (IABP). Over 95% of the GlobIce and buoy data analysed fell within 5 km of each other. The GlobIce Eulerian image pair product showed a high correlation with buoy data. The sea ice concentration product was compared to SSM/I data. An evaluation of the validity of the GlobICE data will be presented in this work. GlobICE sea ice velocity and deformation were compared with runs of the CICE sea ice model: in particular the mass fluxes through the straits were used to investigate the correlation between the winter behaviour of sea ice and the sea ice state in the following summer.

  14. Quaternary Sea-ice history in the Arctic Ocean based on a new Ostracode sea-ice proxy

    USGS Publications Warehouse

    Cronin, T. M.; Gemery, L.; Briggs, W.M.; Jakobsson, M.; Polyak, L.; Brouwers, E.M.

    2010-01-01

    Paleo-sea-ice history in the Arctic Ocean was reconstructed using the sea-ice dwelling ostracode Acetabulastoma arcticum from late Quaternary sediments from the Mendeleyev, Lomonosov, and Gakkel Ridges, the Morris Jesup Rise and the Yermak Plateau. Results suggest intermittently high levels of perennial sea ice in the central Arctic Ocean during Marine Isotope Stage (MIS) 3 (25-45 ka), minimal sea ice during the last deglacial (16-11 ka) and early Holocene thermal maximum (11-5 ka) and increasing sea ice during the mid-to-late Holocene (5-0 ka). Sediment core records from the Iceland and Rockall Plateaus show that perennial sea ice existed in these regions only during glacial intervals MIS 2, 4, and 6. These results show that sea ice exhibits complex temporal and spatial variability during different climatic regimes and that the development of modern perennial sea ice may be a relatively recent phenomenon. ?? 2010.

  15. New Tools for Sea Ice Data Analysis and Visualization: NSIDC's Arctic Sea Ice News and Analysis

    NASA Astrophysics Data System (ADS)

    Vizcarra, N.; Stroeve, J.; Beam, K.; Beitler, J.; Brandt, M.; Kovarik, J.; Savoie, M. H.; Skaug, M.; Stafford, T.

    2017-12-01

    Arctic sea ice has long been recognized as a sensitive climate indicator and has undergone a dramatic decline over the past thirty years. Antarctic sea ice continues to be an intriguing and active field of research. The National Snow and Ice Data Center's Arctic Sea Ice News & Analysis (ASINA) offers researchers and the public a transparent view of sea ice data and analysis. We have released a new set of tools for sea ice analysis and visualization. In addition to Charctic, our interactive sea ice extent graph, the new Sea Ice Data and Analysis Tools page provides access to Arctic and Antarctic sea ice data organized in seven different data workbooks, updated daily or monthly. An interactive tool lets scientists, or the public, quickly compare changes in ice extent and location. Another tool allows users to map trends, anomalies, and means for user-defined time periods. Animations of September Arctic and Antarctic monthly average sea ice extent and concentration may also be accessed from this page. Our tools help the NSIDC scientists monitor and understand sea ice conditions in near real time. They also allow the public to easily interact with and explore sea ice data. Technical innovations in our data center helped NSIDC quickly build these tools and more easily maintain them. The tools were made publicly accessible to meet the desire from the public and members of the media to access the numbers and calculations that power our visualizations and analysis. This poster explores these tools and how other researchers, the media, and the general public are using them.

  16. NCEP MMAB Sea Ice Home Page

    Science.gov Websites

    NCEP MMAB Sea Ice Home Page The Polar and Great Lakes Ice group works on sea ice analysis from satellite, sea ice modeling, and ice-atmosphere-ocean coupling. Our work supports the Alaska Region of the @noaa.gov Last Modified 2 July 2012 Pages of Interest Analysis Daily Sea Ice Analyses Animations of the

  17. Calibration of sea ice dynamic parameters in an ocean-sea ice model using an ensemble Kalman filter

    NASA Astrophysics Data System (ADS)

    Massonnet, F.; Goosse, H.; Fichefet, T.; Counillon, F.

    2014-07-01

    The choice of parameter values is crucial in the course of sea ice model development, since parameters largely affect the modeled mean sea ice state. Manual tuning of parameters will soon become impractical, as sea ice models will likely include more parameters to calibrate, leading to an exponential increase of the number of possible combinations to test. Objective and automatic methods for parameter calibration are thus progressively called on to replace the traditional heuristic, "trial-and-error" recipes. Here a method for calibration of parameters based on the ensemble Kalman filter is implemented, tested and validated in the ocean-sea ice model NEMO-LIM3. Three dynamic parameters are calibrated: the ice strength parameter P*, the ocean-sea ice drag parameter Cw, and the atmosphere-sea ice drag parameter Ca. In twin, perfect-model experiments, the default parameter values are retrieved within 1 year of simulation. Using 2007-2012 real sea ice drift data, the calibration of the ice strength parameter P* and the oceanic drag parameter Cw improves clearly the Arctic sea ice drift properties. It is found that the estimation of the atmospheric drag Ca is not necessary if P* and Cw are already estimated. The large reduction in the sea ice speed bias with calibrated parameters comes with a slight overestimation of the winter sea ice areal export through Fram Strait and a slight improvement in the sea ice thickness distribution. Overall, the estimation of parameters with the ensemble Kalman filter represents an encouraging alternative to manual tuning for ocean-sea ice models.

  18. Do pelagic grazers benefit from sea ice? Insights from the Antarctic sea ice proxy IPSO25

    NASA Astrophysics Data System (ADS)

    Schmidt, Katrin; Brown, Thomas A.; Belt, Simon T.; Ireland, Louise C.; Taylor, Kyle W. R.; Thorpe, Sally E.; Ward, Peter; Atkinson, Angus

    2018-04-01

    Sea ice affects primary production in polar regions in multiple ways. It can dampen water column productivity by reducing light or nutrient supply, provide a habitat for ice algae and condition the marginal ice zone (MIZ) for phytoplankton blooms on its seasonal retreat. The relative importance of three different carbon sources (sea ice derived, sea ice conditioned, non-sea-ice associated) for the polar food web is not well understood, partly due to the lack of methods that enable their unambiguous distinction. Here we analysed two highly branched isoprenoid (HBI) biomarkers to trace sea-ice-derived and sea-ice-conditioned carbon in Antarctic krill (Euphausia superba) and relate their concentrations to the grazers' body reserves, growth and recruitment. During our sampling in January-February 2003, the proxy for sea ice diatoms (a di-unsaturated HBI termed IPSO25, δ13C = -12.5 ± 3.3 ‰) occurred in open waters of the western Scotia Sea, where seasonal ice retreat was slow. In suspended matter from surface waters, IPSO25 was present at a few stations close to the ice edge, but in krill the marker was widespread. Even at stations that had been ice-free for several weeks, IPSO25 was found in krill stomachs, suggesting that they gathered the ice-derived algae from below the upper mixed layer. Peak abundances of the proxy for MIZ diatoms (a tri-unsaturated HBI termed HBI III, δ13C = -42.2 ± 2.4 ‰) occurred in regions of fast sea ice retreat and persistent salinity-driven stratification in the eastern Scotia Sea. Krill sampled in the area defined by the ice edge bloom likewise contained high amounts of HBI III. As indicators for the grazer's performance we used the mass-length ratio, size of digestive gland and growth rate for krill, and recruitment for the biomass-dominant calanoid copepods Calanoides acutus and Calanus propinquus. These indices consistently point to blooms in the MIZ as an important feeding ground for pelagic grazers. Even though ice

  19. Sea ice roughness: the key for predicting Arctic summer ice albedo

    NASA Astrophysics Data System (ADS)

    Landy, J.; Ehn, J. K.; Tsamados, M.; Stroeve, J.; Barber, D. G.

    2017-12-01

    Although melt ponds on Arctic sea ice evolve in stages, ice with smoother surface topography typically allows the pond water to spread over a wider area, reducing the ice-albedo and accelerating further melt. Building on this theory, we simulated the distribution of meltwater on a range of statistically-derived topographies to develop a quantitative relationship between premelt sea ice surface roughness and summer ice albedo. Our method, previously applied to ICESat observations of the end-of-winter sea ice roughness, could account for 85% of the variance in AVHRR observations of the summer ice-albedo [Landy et al., 2015]. Consequently, an Arctic-wide reduction in sea ice roughness over the ICESat operational period (from 2003 to 2008) explained a drop in ice-albedo that resulted in a 16% increase in solar heat input to the sea ice cover. Here we will review this work and present new research linking pre-melt sea ice surface roughness observations from Cryosat-2 to summer sea ice albedo over the past six years, examining the potential of winter roughness as a significant new source of sea ice predictability. We will further evaluate the possibility for high-resolution (kilometre-scale) forecasts of summer sea ice albedo from waveform-level Cryosat-2 roughness data in the landfast sea ice zone of the Canadian Arctic. Landy, J. C., J. K. Ehn, and D. G. Barber (2015), Albedo feedback enhanced by smoother Arctic sea ice, Geophys. Res. Lett., 42, 10,714-10,720, doi:10.1002/2015GL066712.

  20. Estimates of ikaite export from sea ice to the underlying seawater in a sea ice-seawater mesocosm

    NASA Astrophysics Data System (ADS)

    Geilfus, Nicolas-Xavier; Galley, Ryan J.; Else, Brent G. T.; Campbell, Karley; Papakyriakou, Tim; Crabeck, Odile; Lemes, Marcos; Delille, Bruno; Rysgaard, Søren

    2016-09-01

    The precipitation of ikaite and its fate within sea ice is still poorly understood. We quantify temporal inorganic carbon dynamics in sea ice from initial formation to its melt in a sea ice-seawater mesocosm pool from 11 to 29 January 2013. Based on measurements of total alkalinity (TA) and total dissolved inorganic carbon (TCO2), the main processes affecting inorganic carbon dynamics within sea ice were ikaite precipitation and CO2 exchange with the atmosphere. In the underlying seawater, the dissolution of ikaite was the main process affecting inorganic carbon dynamics. Sea ice acted as an active layer, releasing CO2 to the atmosphere during the growth phase, taking up CO2 as it melted and exporting both ikaite and TCO2 into the underlying seawater during the whole experiment. Ikaite precipitation of up to 167 µmol kg-1 within sea ice was estimated, while its export and dissolution into the underlying seawater was responsible for a TA increase of 64-66 µmol kg-1 in the water column. The export of TCO2 from sea ice to the water column increased the underlying seawater TCO2 by 43.5 µmol kg-1, suggesting that almost all of the TCO2 that left the sea ice was exported to the underlying seawater. The export of ikaite from the ice to the underlying seawater was associated with brine rejection during sea ice growth, increased vertical connectivity in sea ice due to the upward percolation of seawater and meltwater flushing during sea ice melt. Based on the change in TA in the water column around the onset of sea ice melt, more than half of the total ikaite precipitated in the ice during sea ice growth was still contained in the ice when the sea ice began to melt. Ikaite crystal dissolution in the water column kept the seawater pCO2 undersaturated with respect to the atmosphere in spite of increased salinity, TA and TCO2 associated with sea ice growth. Results indicate that ikaite export from sea ice and its dissolution in the underlying seawater can potentially hamper

  1. Potential Arctic sea ice refuge for sustaining a remnant polar bear population (Invited)

    NASA Astrophysics Data System (ADS)

    Durner, G. M.; Amstrup, S. C.; Douglas, D. C.; Gautier, D. L.

    2010-12-01

    Polar bears depend on sea ice as a platform from which they capture seals. Sea ice availability must be spatially and temporally adequate for birth and weaning of seal pups, and to maximize seal hunting opportunities for polar bears. Projected declines in the spatial and temporal extent of summer and autumn sea ice could potentially limit the ability of polar bears to build up body stores sufficient to maintain reproductive fitness. General circulation models, however, suggest that summer and autumn sea ice may persist in the shelf waters of the Canadian Archipelago and northern Greenland adjacent to the Arctic basin. While winter-formed ice is important, a primary mechanism for sea ice accumulation in this region is by mechanical thickening of the sea ice facilitated by convergent forces from the Beaufort Gyre and the Transpolar Drift Stream. Collectively these areas could provide a polar bear refugium when other regions have lost the sea ice necessary to support viable populations. The potential for a polar bear refugium, however, must include other resource considerations. Projected declines of sea ice in the Northwest Passage may expose polar bears to hazards related to increase shipping and other commerce. Increasing global demands and limited opportunities elsewhere make the Arctic an increasingly attractive area for petroleum exploration. The Canadian Archipelago coincides with the Sverdrup basin, where petroleum accumulations have already been discovered but as yet are undeveloped. The Lincoln Sea Basin offshore of northern Greenland has the geological possibility of significant petroleum accumulations, and northeastern Greenland is one of the most prospective areas in the Arctic for undiscovered oil. Activities associated with commerce and petroleum development could reduce the potential viability of the region as a polar bear refugium. Hence, if the goal is a sustainable (albeit reduced) polar bear population, important considerations include commerce

  2. Sea-ice evaluation of NEMO-Nordic 1.0: a NEMO-LIM3.6-based ocean-sea-ice model setup for the North Sea and Baltic Sea

    NASA Astrophysics Data System (ADS)

    Pemberton, Per; Löptien, Ulrike; Hordoir, Robinson; Höglund, Anders; Schimanke, Semjon; Axell, Lars; Haapala, Jari

    2017-08-01

    The Baltic Sea is a seasonally ice-covered marginal sea in northern Europe with intense wintertime ship traffic and a sensitive ecosystem. Understanding and modeling the evolution of the sea-ice pack is important for climate effect studies and forecasting purposes. Here we present and evaluate the sea-ice component of a new NEMO-LIM3.6-based ocean-sea-ice setup for the North Sea and Baltic Sea region (NEMO-Nordic). The setup includes a new depth-based fast-ice parametrization for the Baltic Sea. The evaluation focuses on long-term statistics, from a 45-year long hindcast, although short-term daily performance is also briefly evaluated. We show that NEMO-Nordic is well suited for simulating the mean sea-ice extent, concentration, and thickness as compared to the best available observational data set. The variability of the annual maximum Baltic Sea ice extent is well in line with the observations, but the 1961-2006 trend is underestimated. Capturing the correct ice thickness distribution is more challenging. Based on the simulated ice thickness distribution we estimate the undeformed and deformed ice thickness and concentration in the Baltic Sea, which compares reasonably well with observations.

  3. Microwave emission characteristics of sea ice

    NASA Technical Reports Server (NTRS)

    Edgerton, A. T.; Poe, G.

    1972-01-01

    A general classification is presented for sea ice brightness temperatures with categories of high and low emission, corresponding to young and weathered sea ice, respectively. A sea ice emission model was developed which allows variations of ice salinity and temperature in directions perpendicular to the ice surface.

  4. Arctic sea ice decline: Projected changes in timing and extent of sea ice in the Bering and Chukchi Seas

    USGS Publications Warehouse

    Douglas, David C.

    2010-01-01

    The Arctic region is warming faster than most regions of the world due in part to increasing greenhouse gases and positive feedbacks associated with the loss of snow and ice cover. One consequence has been a rapid decline in Arctic sea ice over the past 3 decades?a decline that is projected to continue by state-of-the-art models. Many stakeholders are therefore interested in how global warming may change the timing and extent of sea ice Arctic-wide, and for specific regions. To inform the public and decision makers of anticipated environmental changes, scientists are striving to better understand how sea ice influences ecosystem structure, local weather, and global climate. Here, projected changes in the Bering and Chukchi Seas are examined because sea ice influences the presence of, or accessibility to, a variety of local resources of commercial and cultural value. In this study, 21st century sea ice conditions in the Bering and Chukchi Seas are based on projections by 18 general circulation models (GCMs) prepared for the fourth reporting period by the Intergovernmental Panel on Climate Change (IPCC) in 2007. Sea ice projections are analyzed for each of two IPCC greenhouse gas forcing scenarios: the A1B `business as usual? scenario and the A2 scenario that is somewhat more aggressive in its CO2 emissions during the second half of the century. A large spread of uncertainty among projections by all 18 models was constrained by creating model subsets that excluded GCMs that poorly simulated the 1979-2008 satellite record of ice extent and seasonality. At the end of the 21st century (2090-2099), median sea ice projections among all combinations of model ensemble and forcing scenario were qualitatively similar. June is projected to experience the least amount of sea ice loss among all months. For the Chukchi Sea, projections show extensive ice melt during July and ice-free conditions during August, September, and October by the end of the century, with high agreement

  5. Spatial patterns in the length of the sea ice season in the Southern Ocean, 1979-1986

    NASA Technical Reports Server (NTRS)

    Parkinson, Claire L.

    1994-01-01

    The length of the sea ice season summarizes in one number the ice coverage conditions for an individual location for an entire year. It becomes a particularly valuable variable when mapped spatially over a large area and examined for regional and interannual differences, as is done here for the Southern Ocean over the years 1979-1986, using the satellite passive microwave data of the Nimbus 7 scanning multichannel microwave radiometer. Three prominent geographic anomalies in ice season lengths occur consistently in each year of the data set, countering the general tendency toward shorter ice seasons from south to north: (1) in the Weddell Sea the tendency is toward shorter ice seasons from southwest to northeast, reflective of the cyclonic ice/atmosphere/ocean circulations in the Weddell Sea region. (2) Directly north of the Ross Ice Shelf anomalously short ice seasons occur, lasting only 245-270 days, in contrast to the perennial ice coverage at comparable latitudes in the southern Bellingshausen and Amundsen Seas and in the western Weddell Sea. The short ice season off the Ross Ice Shelf reflects the consistently early opening of the ice cover each spring, under the influence of upwelling along the continental slope and shelf and atmospheric forcing from winds blowing off the Antarctic continent. (3) In the southern Amundsen Sea, anomalously short ice seasons occur adjacent to the coast, owing to the frequent existence of coastal polynyas off the many small ice shelves bordering the sea. Least squares trends in the ice season lengths over the 1979-1986 period are highly coherent spatially, with overall trends toward shorter ice seasons in the northern Weddell and Bellingshausen seas and toward longer ice seasons in the Ross Sea, around much of East Antarctica, and in a portion of the south central Weddell Sea.

  6. Spatial patterns in the length of the sea ice season in the Southern Ocean, 1979-1986

    NASA Astrophysics Data System (ADS)

    Parkinson, Claire L.

    1994-08-01

    The length of the sea ice season summarizes in one number the ice coverage conditions for an individual location for an entire year. It becomes a particularly valuable variable when mapped spatially over a large area and examined for regional and interannual differences, as is done here for the Southern Ocean over the years 1979-1986, using the satellite passive microwave data of the Nimbus 7 scanning multichannel microwave radiometer. Three prominent geographic anomalies in ice season lengths occur consistently in each year of the data set, countering the general tendency toward shorter ice seasons from south to north: (1) In the Weddell Sea the tendency is toward shorter ice seasons from southwest to northeast, reflective of the cyclonic ice/atmosphere/ocean circulations in the Weddell Sea region. (2) Directly north of the Ross Ice Shelf anomalously short ice seasons occur, lasting only 245-270 days, in contrast to the perennial ice coverage at comparable latitudes in the southern Bellingshausen and Amundsen Seas and in the western Weddell Sea. The short ice season off the Ross Ice Shelf reflects the consistently early opening of the ice cover each spring, under the influence of upwelling along the continental slope and shelf and atmospheric forcing from winds blowing off the Antarctic continent. (3) In the southern Amundsen Sea, anomalously short ice seasons occur adjacent to the coast, owing to the frequent existence of coastal polynyas off the many small ice shelves bordering the sea. Least squares trends in the ice season lengths over the 1979-1986 period are highly coherent spatially, with overall trends toward shorter ice seasons in the northern Weddell and Bellingshausen seas and toward longer ice seasons in the Ross Sea, around much of East Antarctica, and in a portion of the south central Weddell Sea.

  7. The CMIP6 Sea-Ice Model Intercomparison Project (SIMIP): Understanding sea ice through climate-model simulations

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Notz, Dirk; Jahn, Alexandra; Holland, Marika

    A better understanding of the role of sea ice for the changing climate of our planet is the central aim of the diagnostic Coupled Model Intercomparison Project 6 (CMIP6)-endorsed Sea-Ice Model Intercomparison Project (SIMIP). To reach this aim, SIMIP requests sea-ice-related variables from climate-model simulations that allow for a better understanding and, ultimately, improvement of biases and errors in sea-ice simulations with large-scale climate models. This then allows us to better understand to what degree CMIP6 model simulations relate to reality, thus improving our confidence in answering sea-ice-related questions based on these simulations. Furthermore, the SIMIP protocol provides a standardmore » for sea-ice model output that will streamline and hence simplify the analysis of the simulated sea-ice evolution in research projects independent of CMIP. To reach its aims, SIMIP provides a structured list of model output that allows for an examination of the three main budgets that govern the evolution of sea ice, namely the heat budget, the momentum budget, and the mass budget. Furthermore, we explain the aims of SIMIP in more detail and outline how its design allows us to answer some of the most pressing questions that sea ice still poses to the international climate-research community.« less

  8. The CMIP6 Sea-Ice Model Intercomparison Project (SIMIP): Understanding sea ice through climate-model simulations

    DOE PAGES

    Notz, Dirk; Jahn, Alexandra; Holland, Marika; ...

    2016-09-23

    A better understanding of the role of sea ice for the changing climate of our planet is the central aim of the diagnostic Coupled Model Intercomparison Project 6 (CMIP6)-endorsed Sea-Ice Model Intercomparison Project (SIMIP). To reach this aim, SIMIP requests sea-ice-related variables from climate-model simulations that allow for a better understanding and, ultimately, improvement of biases and errors in sea-ice simulations with large-scale climate models. This then allows us to better understand to what degree CMIP6 model simulations relate to reality, thus improving our confidence in answering sea-ice-related questions based on these simulations. Furthermore, the SIMIP protocol provides a standardmore » for sea-ice model output that will streamline and hence simplify the analysis of the simulated sea-ice evolution in research projects independent of CMIP. To reach its aims, SIMIP provides a structured list of model output that allows for an examination of the three main budgets that govern the evolution of sea ice, namely the heat budget, the momentum budget, and the mass budget. Furthermore, we explain the aims of SIMIP in more detail and outline how its design allows us to answer some of the most pressing questions that sea ice still poses to the international climate-research community.« less

  9. Analysis of sea ice dynamics

    NASA Technical Reports Server (NTRS)

    Zwally, J.

    1988-01-01

    The ongoing work has established the basis for using multiyear sea ice concentrations from SMMR passive microwave for studies of largescale advection and convergence/divergence of the Arctic sea ice pack. Comparisons were made with numerical model simulations and buoy data showing qualitative agreement on daily to interannual time scales. Analysis of the 7-year SMMR data set shows significant interannual variations in the total area of multiyear ice. The scientific objective is to investigate the dynamics, mass balance, and interannual variability of the Arctic sea ice pack. The research emphasizes the direct application of sea ice parameters derived from passive microwave data (SMMR and SSMI) and collaborative studies using a sea ice dynamics model. The possible causes of observed interannual variations in the multiyear ice area are being examined. The relative effects of variations in the large scale advection and convergence/divergence within the ice pack on a regional and seasonal basis are investigated. The effects of anomolous atmospheric forcings are being examined, including the long-lived effects of synoptic events and monthly variations in the mean geostrophic winds. Estimates to be made will include the amount of new ice production within the ice pack during winter and the amount of ice exported from the pack.

  10. Arctic landfast sea ice

    NASA Astrophysics Data System (ADS)

    Konig, Christof S.

    Landfast ice is sea ice which forms and remains fixed along a coast, where it is attached either to the shore, or held between shoals or grounded icebergs. Landfast ice fundamentally modifies the momentum exchange between atmosphere and ocean, as compared to pack ice. It thus affects the heat and freshwater exchange between air and ocean and impacts on the location of ocean upwelling and downwelling zones. Further, the landfast ice edge is essential for numerous Arctic mammals and Inupiat who depend on them for their subsistence. The current generation of sea ice models is not capable of reproducing certain aspects of landfast ice formation, maintenance, and disintegration even when the spatial resolution would be sufficient to resolve such features. In my work I develop a new ice model that permits the existence of landfast sea ice even in the presence of offshore winds, as is observed in mature. Based on viscous-plastic as well as elastic-viscous-plastic ice dynamics I add tensile strength to the ice rheology and re-derive the equations as well as numerical methods to solve them. Through numerical experiments on simplified domains, the effects of those changes are demonstrated. It is found that the modifications enable landfast ice modeling, as desired. The elastic-viscous-plastic rheology leads to initial velocity fluctuations within the landfast ice that weaken the ice sheet and break it up much faster than theoretically predicted. Solving the viscous-plastic rheology using an implicit numerical method avoids those waves and comes much closer to theoretical predictions. Improvements in landfast ice modeling can only verified in comparison to observed data. I have extracted landfast sea ice data of several decades from several sources to create a landfast sea ice climatology that can be used for that purpose. Statistical analysis of the data shows several factors that significantly influence landfast ice distribution: distance from the coastline, ocean depth, as

  11. Mechanical sea-ice strength parameterized as a function of ice temperature

    NASA Astrophysics Data System (ADS)

    Hata, Yukie; Tremblay, Bruno

    2016-04-01

    Mechanical sea-ice strength is key for a better simulation of the timing of landlock ice onset and break-up in the Canadian Arctic Archipelago (CAA). We estimate the mechanical strength of sea ice in the CAA by analyzing the position record measured by the several buoys deployed in the CAA between 2008 and 2013, and wind data from the Canadian Meteorological Centre's Global Deterministic Prediction System (CMC_GDPS) REforecasts (CGRF). First, we calculate the total force acting on the ice using the wind data. Next, we estimate upper (lower) bounds on the sea-ice strength by identifying cases when the sea ice deforms (does not deform) under the action of a given total force. Results from this analysis show that the ice strength of landlock sea ice in the CAA is approximately 40 kN/m on the landfast ice onset (in ice growth season). Additionally, it becomes approximately 10 kN/m on the landfast ice break-up (in melting season). The ice strength decreases with ice temperature increase, which is in accord with results from Johnston [2006]. We also include this new parametrization of sea-ice strength as a function of ice temperature in a coupled slab ocean sea ice model. The results from the model with and without the new parametrization are compared with the buoy data from the International Arctic Buoy Program (IABP).

  12. Sea ice dynamics across the Mid-Pleistocene transition in the Bering Sea.

    PubMed

    Detlef, H; Belt, S T; Sosdian, S M; Smik, L; Lear, C H; Hall, I R; Cabedo-Sanz, P; Husum, K; Kender, S

    2018-03-05

    Sea ice and associated feedback mechanisms play an important role for both long- and short-term climate change. Our ability to predict future sea ice extent, however, hinges on a greater understanding of past sea ice dynamics. Here we investigate sea ice changes in the eastern Bering Sea prior to, across, and after the Mid-Pleistocene transition (MPT). The sea ice record, based on the Arctic sea ice biomarker IP 25 and related open water proxies from the International Ocean Discovery Program Site U1343, shows a substantial increase in sea ice extent across the MPT. The occurrence of late-glacial/deglacial sea ice maxima are consistent with sea ice/land ice hysteresis and land-glacier retreat via the temperature-precipitation feedback. We also identify interactions of sea ice with phytoplankton growth and ocean circulation patterns, which have important implications for glacial North Pacific Intermediate Water formation and potentially North Pacific abyssal carbon storage.

  13. Sea ice off western Alaska

    NASA Image and Video Library

    2015-02-20

    On February 4, 2014 the Moderate Resolution Imaging Spectroradiometer (MODIS) flying aboard NASA’s Aqua satellite captured a true-color image of sea ice off of western Alaska. In this true-color image, the snow and ice covered land appears bright white while the floating sea ice appears a duller grayish-white. Snow over the land is drier, and reflects more light back to the instrument, accounting for the very bright color. Ice overlying oceans contains more water, and increasing water decreases reflectivity of ice, resulting in duller colors. Thinner ice is also duller. The ocean waters are tinted with green, likely due to a combination of sediment and phytoplankton. Alaska lies to the east in this image, and Russia to the west. The Bering Strait, covered with ice, lies between to two. South of the Bering Strait, the waters are known as the Bering Sea. To the north lies the Chukchi Sea. The bright white island south of the Bering Strait is St. Lawrence Island. Home to just over 1200 people, the windswept island belongs to the United States, but sits closer to Russia than to Alaska. To the southeast of the island a dark area, loosely covered with floating sea ice, marks a persistent polynya – an area of open water surrounded by more frozen sea ice. Due to the prevailing winds, which blow the sea ice away from the coast in this location, the area rarely completely freezes. The ice-covered areas in this image, as well as the Beaufort Sea, to the north, are critical areas for the survival of the ringed seal, a threatened species. The seals use the sea ice, including ice caves, to rear their young, and use the free-floating sea ice for molting, raising the young and breeding. In December 2014, the National Oceanic and Atmospheric Administration (NOAA) proposed that much of this region be set aside as critical, protected habitat for the ringed seal. Credit: NASA/GSFC/Jeff Schmaltz/MODIS Land Rapid Response Team NASA image use policy. NASA Goddard Space Flight Center

  14. Sea Ice

    NASA Technical Reports Server (NTRS)

    Parkinson, Claire L.; Cavalieri, Donald J.

    2005-01-01

    Sea ice covers vast areas of the polar oceans, with ice extent in the Northern Hemisphere ranging from approximately 7 x 10(exp 6) sq km in September to approximately 15 x 10(exp 6) sq km in March and ice extent in the Southern Hemisphere ranging from approximately 3 x 10(exp 6) sq km in February to approximately 18 x 10(exp 6) sq km in September. These ice covers have major impacts on the atmosphere, oceans, and ecosystems of the polar regions, and so as changes occur in them there are potential widespread consequences. Satellite data reveal considerable interannual variability in both polar sea ice covers, and many studies suggest possible connections between the ice and various oscillations within the climate system, such as the Arctic Oscillation, North Atlantic Oscillation, and Antarctic Oscillation, or Southern Annular Mode. Nonetheless, statistically significant long-term trends are also apparent, including overall trends of decreased ice coverage in the Arctic and increased ice coverage in the Antarctic from late 1978 through the end of 2003, with the Antarctic ice increases following marked decreases in the Antarctic ice during the 1970s. For a detailed picture of the seasonally varying ice cover at the start of the 21st century, this chapter includes ice concentration maps for each month of 2001 for both the Arctic and the Antarctic, as well as an overview of what the satellite record has revealed about the two polar ice covers from the 1970s through 2003.

  15. Relative influences of the metocean forcings on the drifting ice pack and estimation of internal ice stress gradients in the Labrador Sea

    NASA Astrophysics Data System (ADS)

    Turnbull, I. D.; Torbati, R. Z.; Taylor, R. S.

    2017-07-01

    Understanding the relative influences of the metocean forcings on the drift of sea ice floes is a crucial component to the overall characterization of an ice environment and to developing an understanding of the factors controlling the ice dynamics. In addition, estimating the magnitude of the internal stress gradients on drifting sea ice floes generated by surrounding ice cover is important for modeling operations, informing the design of offshore structures and vessels in ice environments, and for the proper calibration of Discrete Element Models (DEM) of fields of drifting ice floes. In the spring of 2015 and 2016, four sea ice floes offshore Makkovik, Labrador were tagged with satellite-linked ice tracking buoys along with one satellite-linked weather station on each floe to transmit wind speed and direction. Twenty satellite-linked Lagrangian surface ocean current tracking buoys were also deployed in the open water adjacent to the targeted ice floes. In this paper, the dynamics of the four ice floes are explored in terms of the relative proportions which were forced by the wind, current, sea surface topography, Coriolis, and internal stress gradients. The internal ice stress gradients are calculated as residuals between the observed accelerations of the floes as measured by the tracking buoys and the sums of the other metocean forcings. Results show that internal ice stress gradients accounted for up to 50% of the observed forcing on the floes, and may have reached up to around 0.19 kPa.

  16. Sea Ice in the Bellingshausen Sea

    NASA Image and Video Library

    2017-12-08

    Antarctica—the continent at the southernmost reach of the planet—is fringed by cold, often frozen waters of the Southern Ocean. The extent of sea ice around the continent typically reaches a peak in September and a minimum in February. The photograph above shows Antarctic sea ice on November 5, 2014, during the annual cycle of melt. The image was acquired by the Digital Mapping System (DMS), a digital camera installed in the belly of research aircraft to capture images of terrain below. In this case, the system flew on the DC-8 during a flight as part of NASA’s Operation IceBridge. Most of the view shows first-year sea ice in the Bellingshausen Sea, as it appeared from an altitude of 328 meters (1,076 feet). The block of ice on the right side of the image is older, thicker, and was once attached to the Antarctic Ice Sheet. By the time this image was acquired, however, the ice had broken away to form an iceberg. Given its close proximity to the ice sheet, this could have been a relatively new berg. Read more: earthobservatory.nasa.gov/IOTD/view.php?id=86721 Credit: NASA/Goddard/IceBridge DMS L0 Raw Imagery courtesy of the Digital Mapping System (DMS) team and the NASA DAAC at the National Snow and Ice Data Center Credit: NASA Earth Observatory NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

  17. Sea-ice deformation in a coupled ocean-sea-ice model and in satellite remote sensing data

    NASA Astrophysics Data System (ADS)

    Spreen, Gunnar; Kwok, Ron; Menemenlis, Dimitris; Nguyen, An T.

    2017-07-01

    A realistic representation of sea-ice deformation in models is important for accurate simulation of the sea-ice mass balance. Simulated sea-ice deformation from numerical simulations with 4.5, 9, and 18 km horizontal grid spacing and a viscous-plastic (VP) sea-ice rheology are compared with synthetic aperture radar (SAR) satellite observations (RGPS, RADARSAT Geophysical Processor System) for the time period 1996-2008. All three simulations can reproduce the large-scale ice deformation patterns, but small-scale sea-ice deformations and linear kinematic features (LKFs) are not adequately reproduced. The mean sea-ice total deformation rate is about 40 % lower in all model solutions than in the satellite observations, especially in the seasonal sea-ice zone. A decrease in model grid spacing, however, produces a higher density and more localized ice deformation features. The 4.5 km simulation produces some linear kinematic features, but not with the right frequency. The dependence on length scale and probability density functions (PDFs) of absolute divergence and shear for all three model solutions show a power-law scaling behavior similar to RGPS observations, contrary to what was found in some previous studies. Overall, the 4.5 km simulation produces the most realistic divergence, vorticity, and shear when compared with RGPS data. This study provides an evaluation of high and coarse-resolution viscous-plastic sea-ice simulations based on spatial distribution, time series, and power-law scaling metrics.

  18. Operationally Monitoring Sea Ice at the Canadian Ice Service

    NASA Astrophysics Data System (ADS)

    de Abreu, R.; Flett, D.; Carrieres, T.; Falkingham, J.

    2004-05-01

    The Canadian Ice Service (CIS) of the Meteorological Service of Canada promotes safe and efficient maritime operations and protects Canada's environment by providing reliable and timely information about ice and iceberg conditions in Canadian waters. Daily and seasonal charts describing the extent, type and concentration of sea ice and icebergs are provided to support navigation and other activities (e.g. oil and gas) in coastal waters. The CIS relies on a suite of spaceborne visible, infrared and microwave sensors to operationally monitor ice conditions in Canadian coastal and inland waterways. These efforts are complemented by operational sea ice models that are customized and run at the CIS. The archive of these data represent a 35 year archive of ice conditions and have proven to be a valuable dataset for historical sea ice analysis. This presentation will describe the daily integration of remote sensing observations and modelled ice conditions used to produce ice and iceberg products. A review of the decadal evolution of this process will be presented, as well as a glimpse into the future of ice and iceberg monitoring. Examples of the utility of the CIS digital sea ice archive for climate studies will also be presented.

  19. Influences of sea ice on eastern Bering Sea phytoplankton

    NASA Astrophysics Data System (ADS)

    Zhou, Qianqian; Wang, Peng; Chen, Changping; Liang, Junrong; Li, Bingqian; Gao, Yahui

    2015-03-01

    The influence of sea ice on the species composition and cell density of phytoplankton was investigated in the eastern Bering Sea in spring 2008. Diatoms, particularly pennate diatoms, dominated the phytoplankton community. The dominant species were Grammonema islandica (Grunow in Van Heurck) Hasle, Fragilariopsis cylindrus (Grunow) Krieger, F. oceanica (Cleve) Hasle, Navicula vanhoeffenii Gran, Thalassiosira antarctica Comber, T. gravida Cleve, T. nordenskiöeldii Cleve, and T. rotula Meunier. Phytoplankton cell densities varied from 0.08×104 to 428.8×104 cells/L, with an average of 30.3×104 cells/L. Using cluster analysis, phytoplankton were grouped into three assemblages defined by ice-forming conditions: open water, ice edge, and sea ice assemblages. In spring, when the sea ice melts, the phytoplankton dispersed from the sea ice to the ice edge and even into open waters. Thus, these phytoplankton in the sea ice may serve as a "seed bank" for phytoplankton population succession in the subarctic ecosystem. Moreover, historical studies combined with these results suggest that the sizes of diatom species have become smaller, shifting from microplankton to nannoplankton-dominated communities.

  20. Sea-ice indicators of polar bear habitat

    NASA Astrophysics Data System (ADS)

    Stern, Harry L.; Laidre, Kristin L.

    2016-09-01

    Nineteen subpopulations of polar bears (Ursus maritimus) are found throughout the circumpolar Arctic, and in all regions they depend on sea ice as a platform for traveling, hunting, and breeding. Therefore polar bear phenology - the cycle of biological events - is linked to the timing of sea-ice retreat in spring and advance in fall. We analyzed the dates of sea-ice retreat and advance in all 19 polar bear subpopulation regions from 1979 to 2014, using daily sea-ice concentration data from satellite passive microwave instruments. We define the dates of sea-ice retreat and advance in a region as the dates when the area of sea ice drops below a certain threshold (retreat) on its way to the summer minimum or rises above the threshold (advance) on its way to the winter maximum. The threshold is chosen to be halfway between the historical (1979-2014) mean September and mean March sea-ice areas. In all 19 regions there is a trend toward earlier sea-ice retreat and later sea-ice advance. Trends generally range from -3 to -9 days decade-1 in spring and from +3 to +9 days decade-1 in fall, with larger trends in the Barents Sea and central Arctic Basin. The trends are not sensitive to the threshold. We also calculated the number of days per year that the sea-ice area exceeded the threshold (termed ice-covered days) and the average sea-ice concentration from 1 June through 31 October. The number of ice-covered days is declining in all regions at the rate of -7 to -19 days decade-1, with larger trends in the Barents Sea and central Arctic Basin. The June-October sea-ice concentration is declining in all regions at rates ranging from -1 to -9 percent decade-1. These sea-ice metrics (or indicators of habitat change) were designed to be useful for management agencies and for comparative purposes among subpopulations. We recommend that the National Climate Assessment include the timing of sea-ice retreat and advance in future reports.

  1. Variability and trends in the Arctic Sea ice cover: Results from different techniques

    NASA Astrophysics Data System (ADS)

    Comiso, Josefino C.; Meier, Walter N.; Gersten, Robert

    2017-08-01

    Variability and trend studies of sea ice in the Arctic have been conducted using products derived from the same raw passive microwave data but by different groups using different algorithms. This study provides consistency assessment of four of the leading products, namely, Goddard Bootstrap (SB2), Goddard NASA Team (NT1), EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI-SAF 1.2), and Hadley HadISST 2.2 data in evaluating variability and trends in the Arctic sea ice cover. All four provide generally similar ice patterns but significant disagreements in ice concentration distributions especially in the marginal ice zone and adjacent regions in winter and meltponded areas in summer. The discrepancies are primarily due to different ways the four techniques account for occurrences of new ice and meltponding. However, results show that the different products generally provide consistent and similar representation of the state of the Arctic sea ice cover. Hadley and NT1 data usually provide the highest and lowest monthly ice extents, respectively. The Hadley data also show the lowest trends in ice extent and ice area at -3.88%/decade and -4.37%/decade, respectively, compared to an average of -4.36%/decade and -4.57%/decade for all four. Trend maps also show similar spatial distribution for all four with the largest negative trends occurring at the Kara/Barents Sea and Beaufort Sea regions, where sea ice has been retreating the fastest. The good agreement of the trends especially with updated data provides strong confidence in the quantification of the rate of decline in the Arctic sea ice cover.Plain Language SummaryThe declining Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> cover, especially in the summer, has been the center of attention in recent years. Reports on the <span class="hlt">sea</span> <span class="hlt">ice</span> cover have been provided by different institutions using basically the same set of satellite data but different techniques for estimating key parameters such as <span class="hlt">ice</span></p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014TCry....8.2409L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014TCry....8.2409L"><span><span class="hlt">Ice</span> and AIS: ship speed data and <span class="hlt">sea</span> <span class="hlt">ice</span> forecasts in the Baltic <span class="hlt">Sea</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Löptien, U.; Axell, L.</p> <p>2014-12-01</p> <p>The Baltic <span class="hlt">Sea</span> is a seasonally <span class="hlt">ice</span>-covered marginal <span class="hlt">sea</span> located in a densely populated area in northern Europe. Severe <span class="hlt">sea</span> <span class="hlt">ice</span> conditions have the potential to hinder the intense ship traffic considerably. Thus, <span class="hlt">sea</span> <span class="hlt">ice</span> fore- and nowcasts are regularly provided by the national weather services. Typically, the forecast comprises several <span class="hlt">ice</span> properties that are distributed as prognostic variables, but their actual usefulness is difficult to measure, and the ship captains must determine their relative importance and relevance for optimal ship speed and safety ad hoc. The present study provides a more objective approach by comparing the ship speeds, obtained by the automatic identification system (AIS), with the respective forecasted <span class="hlt">ice</span> conditions. We find that, despite an unavoidable random component, this information is useful to constrain and rate fore- and nowcasts. More precisely, 62-67% of ship speed variations can be explained by the forecasted <span class="hlt">ice</span> properties when fitting a mixed-effect model. This statistical fit is based on a test region in the Bothnian <span class="hlt">Sea</span> during the severe winter 2011 and employs 15 to 25 min averages of ship speed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www1.ncdc.noaa.gov/pub/data/cmb/bams-sotc/climate-assessment-2004.pdf','USGSPUBS'); return false;" href="http://www1.ncdc.noaa.gov/pub/data/cmb/bams-sotc/climate-assessment-2004.pdf"><span>Polar Climate: Arctic <span class="hlt">sea</span> <span class="hlt">ice</span></span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Stone, R.S.; Douglas, David C.; Belchansky, G.I.; Drobot, S.D.</p> <p>2005-01-01</p> <p>Recent decreases in snow and <span class="hlt">sea</span> <span class="hlt">ice</span> cover in the high northern latitudes are among the most notable indicators of climate change. Northern Hemisphere <span class="hlt">sea</span> <span class="hlt">ice</span> extent for the year as a whole was the third lowest on record dating back to 1973, behind 1995 (lowest) and 1990 (second lowest; Hadley Center–NCEP). September <span class="hlt">sea</span> <span class="hlt">ice</span> extent, which is at the end of the summer melt season and is typically the month with the lowest <span class="hlt">sea</span> <span class="hlt">ice</span> extent of the year, has decreased by about 19% since the late 1970s (Fig. 5.2), with a record minimum observed in 2002 (Serreze et al. 2003). A record low extent also occurred in spring (Chapman 2005, personal communication), and 2004 marked the third consecutive year of anomalously extreme <span class="hlt">sea</span> <span class="hlt">ice</span> retreat in the Arctic (Stroeve et al. 2005). Some model simulations indicate that <span class="hlt">ice</span>-free summers will occur in the Arctic by the year 2070 (ACIA 2004).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C13C0831F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C13C0831F"><span>First Results from the ASIBIA (Arctic <span class="hlt">Sea-Ice</span>, snow, Biogeochemistry and Impacts on the Atmosphere) <span class="hlt">Sea-Ice</span> Chamber</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Frey, M. M.; France, J.; von Glasow, R.; Thomas, M.</p> <p>2015-12-01</p> <p>The ocean-<span class="hlt">ice</span>-atmosphere system is very complex, and there are numerous challenges with conducting fieldwork on <span class="hlt">sea-ice</span> including costs, safety, experimental controls and access. By creating a new coupled Ocean-<span class="hlt">Sea-Ice</span>-(Snow)-Atmosphere facility at the University of East Anglia, UK, we are able to perform controlled investigations in areas such as <span class="hlt">sea-ice</span> physics, physicochemical and biogeochemical processes in <span class="hlt">sea-ice</span>, and to quantify the bi-directional flux of gases in established, freezing and melting <span class="hlt">sea-ice</span>. The environmental chamber is capable of controlled programmable temperatures from -55°C to +30°C, allowing a full range of first year <span class="hlt">sea-ice</span> growing conditions in both the Arctic and Antarctic to be simulated. The <span class="hlt">sea-ice</span> tank within the chamber measures 2.4 m x 1.4 m x 1 m water depth, with an identically sized Teflon film atmosphere on top of the tank. The tank and atmosphere forms a coupled, isolated mesocosm. Above the atmosphere is a light bank with dimmable solar simulation LEDs, and UVA and UVB broadband fluorescent battens, providing light for a range of experiments such as under <span class="hlt">ice</span> biogeochemistry and photochemistry. <span class="hlt">Ice</span> growth in the tank will be ideally suited for studying first-year <span class="hlt">sea-ice</span> physical properties, with in-situ <span class="hlt">ice</span>-profile measurements of temperature, salinity, conductivity, pressure and spectral light transmission. Under water and above <span class="hlt">ice</span> cameras are installed to observe the physical development of the <span class="hlt">sea-ice</span>. The ASIBIA facility is also well equipped for gas exchange and diffusion studies through <span class="hlt">sea-ice</span> with a suite of climate relevant gas measuring instruments (CH4, CO2, O3, NOx, NOy permanently installed, further instruments available) able to measure either directly in the atmospheric component, or via a membrane for water side dissolved gases. Here, we present the first results from the ASIBIA <span class="hlt">sea-ice</span> chamber, focussing on the physical development of first-year <span class="hlt">sea-ice</span> and show the future plans for the facility over</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C32B..01T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C32B..01T"><span>Some Results on <span class="hlt">Sea</span> <span class="hlt">Ice</span> Rheology for the Seasonal <span class="hlt">Ice</span> Zone, Obtained from the Deformation Field of <span class="hlt">Sea</span> <span class="hlt">Ice</span> Drift Pattern</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Toyota, T.; Kimura, N.</p> <p>2017-12-01</p> <p><span class="hlt">Sea</span> <span class="hlt">ice</span> rheology which relates <span class="hlt">sea</span> <span class="hlt">ice</span> stress to the large-scale deformation of the <span class="hlt">ice</span> cover has been a big issue to numerical <span class="hlt">sea</span> <span class="hlt">ice</span> modelling. At present the treatment of internal stress within <span class="hlt">sea</span> <span class="hlt">ice</span> area is based mostly on the rheology formulated by Hibler (1979), where the whole <span class="hlt">sea</span> <span class="hlt">ice</span> area behaves like an isotropic and plastic matter under the ordinary stress with the yield curve given by an ellipse with an aspect ratio (e) of 2, irrespective of <span class="hlt">sea</span> <span class="hlt">ice</span> area and horizontal resolution of the model. However, this formulation was initially developed to reproduce the seasonal variation of the perennial <span class="hlt">ice</span> in the Arctic Ocean. As for its applicability to the seasonal <span class="hlt">ice</span> zones (SIZ), where various types of <span class="hlt">sea</span> <span class="hlt">ice</span> are present, it still needs validation from observational data. In this study, the validity of this rheology was examined for the <span class="hlt">Sea</span> of Okhotsk <span class="hlt">ice</span>, typical of the SIZ, based on the AMSR-derived <span class="hlt">ice</span> drift pattern in comparison with the result obtained for the Beaufort <span class="hlt">Sea</span>. To examine the dependence on a horizontal scale, the coastal radar data operated near the Hokkaido coast, Japan, were also used. <span class="hlt">Ice</span> drift pattern was obtained by a maximum cross-correlation method with grid spacings of 37.5 km from the 89 GHz brightness temperature of AMSR-E for the entire <span class="hlt">Sea</span> of Okhotsk and the Beaufort <span class="hlt">Sea</span> and 1.3 km from the coastal radar for the near-shore <span class="hlt">Sea</span> of Okhotsk. The validity of this rheology was investigated from a standpoint of work rate done by deformation field, following the theory of Rothrock (1975). In analysis, the relative rates of convergence were compared between theory and observation to check the shape of yield curve, and the strain ellipse at each grid cell was estimated to see the horizontal variation of deformation field. The result shows that the ellipse of e=1.7-2.0 as the yield curve represents the observed relative conversion rates well for all the <span class="hlt">ice</span> areas. Since this result corresponds with the yield criterion by Tresca and</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-GSFC_20171208_Archive_e001527.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-GSFC_20171208_Archive_e001527.html"><span>Blue Beaufort <span class="hlt">Sea</span> <span class="hlt">Ice</span> from Operation <span class="hlt">Ice</span>Bridge</span></a></p> <p><a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a></p> <p></p> <p>2017-12-08</p> <p>Mosaic image of <span class="hlt">sea</span> <span class="hlt">ice</span> in the Beaufort <span class="hlt">Sea</span> created by the Digital Mapping System (DMS) instrument aboard the <span class="hlt">Ice</span>Bridge P-3B. The dark area in the middle of the image is open water seen through a lead, or opening, in the <span class="hlt">ice</span>. Light blue areas are thick <span class="hlt">sea</span> <span class="hlt">ice</span> and dark blue areas are thinner <span class="hlt">ice</span> formed as water in the lead refreezes. Leads are formed when cracks develop in <span class="hlt">sea</span> <span class="hlt">ice</span> as it moves in response to wind and ocean currents. DMS uses a modified digital SLR camera that points down through a window in the underside of the plane, capturing roughly one frame per second. These images are then combined into an image mosaic using specialized computer software. Credit: NASA/DMS NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.C41E0448B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.C41E0448B"><span>The NRL 2011 Airborne <span class="hlt">Sea-Ice</span> Thickness Campaign</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Brozena, J. M.; Gardner, J. M.; Liang, R.; Ball, D.; Richter-Menge, J.</p> <p>2011-12-01</p> <p>In March of 2011, the US Naval Research Laboratory (NRL) performed a study focused on the estimation of <span class="hlt">sea-ice</span> thickness from airborne radar, laser and photogrammetric sensors. The study was funded by ONR to take advantage of the Navy's ICEX2011 <span class="hlt">ice</span>-camp /submarine exercise, and to serve as a lead-in year for NRL's five year basic research program on the measurement and modeling of <span class="hlt">sea-ice</span> scheduled to take place from 2012-2017. Researchers from the Army Cold Regions Research and Engineering Laboratory (CRREL) and NRL worked with the Navy Arctic Submarine Lab (ASL) to emplace a 9 km-long ground-truth line near the <span class="hlt">ice</span>-camp (see Richter-Menge et al., this session) along which <span class="hlt">ice</span> and snow thickness were directly measured. Additionally, US Navy submarines collected <span class="hlt">ice</span> draft measurements under the groundtruth line. Repeat passes directly over the ground-truth line were flown and a grid surrounding the line was also flown to collect altimeter, LiDAR and Photogrammetry data. Five CRYOSAT-2 satellite tracks were underflown, as well, coincident with satellite passage. Estimates of <span class="hlt">sea</span> <span class="hlt">ice</span> thickness are calculated assuming local hydrostatic balance, and require the densities of water, <span class="hlt">ice</span> and snow, snow depth, and freeboard (defined as the elevation of <span class="hlt">sea</span> <span class="hlt">ice</span>, plus accumulated snow, above local <span class="hlt">sea</span> level). Snow thickness is estimated from the difference between LiDAR and radar altimeter profiles, the latter of which is assumed to penetrate any snow cover. The concepts we used to estimate <span class="hlt">ice</span> thickness are similar to those employed in NASA ICEBRIDGE <span class="hlt">sea-ice</span> thickness estimation. Airborne sensors used for our experiment were a Reigl Q-560 scanning topographic LiDAR, a pulse-limited (2 nS), 10 GHz radar altimeter and an Applanix DSS-439 digital photogrammetric camera (for lead identification). Flights were conducted on a Twin Otter aircraft from Pt. Barrow, AK, and averaged ~ 5 hours in duration. It is challenging to directly compare results from the swath LiDAR with the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/20827996','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/20827996"><span>[Reflectance of <span class="hlt">sea</span> <span class="hlt">ice</span> in Liaodong Bay].</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Xu, Zhan-tang; Yang, Yue-zhong; Wang, Gui-fen; Cao, Wen-xi; Kong, Xiang-peng</p> <p>2010-07-01</p> <p>In the present study, the relationships between <span class="hlt">sea</span> <span class="hlt">ice</span> albedo and the bidirectional reflectance distribution in Liaodong Bay were investigated. The results indicate that: (1) <span class="hlt">sea</span> <span class="hlt">ice</span> albedo alpha(lambda) is closely related to the components of <span class="hlt">sea</span> <span class="hlt">ice</span>, the higher the particulate concentration in <span class="hlt">sea</span> <span class="hlt">ice</span> surface is, the lower the <span class="hlt">sea</span> <span class="hlt">ice</span> albedo alpha(lambda) is. On the contrary, the higher the bubble concentration in <span class="hlt">sea</span> <span class="hlt">ice</span> is, the higher <span class="hlt">sea</span> <span class="hlt">ice</span> albedo alpha(lambda) is. (2) <span class="hlt">Sea</span> <span class="hlt">ice</span> albedo alpha(lambda) is similar to the bidirectional reflectance factor R(f) when the probe locates at nadir. The R(f) would increase with the increase in detector zenith theta, and the correlation between R(f) and the detector azimuth would gradually increase. When the theta is located at solar zenith 63 degrees, the R(f) would reach the maximum, and the strongest correlation is also shown between the R(f) and the detector azimuth. (3) Different types of <span class="hlt">sea</span> <span class="hlt">ice</span> would have the different anisotropic reflectance factors.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..1511292F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..1511292F"><span><span class="hlt">Ice</span>2<span class="hlt">sea</span> - Estimating the future contribution of continental <span class="hlt">ice</span> to <span class="hlt">sea</span>-level rise - project summary</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ford, Elaina; Vaughan, David</p> <p>2013-04-01</p> <p><span class="hlt">Ice</span>2<span class="hlt">sea</span> brings together the EU's scientific and operational expertise from 24 leading institutions across Europe and beyond. Improved projections of the contribution of <span class="hlt">ice</span> to <span class="hlt">sea</span>-level rise produced by this major European-funded programme will inform the fifth IPCC report (due in September 2013). In 2007, the fourth Intergovernmental Panel on Climate Change (IPCC) report highlighted <span class="hlt">ice</span>-sheets as the most significant remaining uncertainty in projections of <span class="hlt">sea</span>-level rise. Understanding about the crucial <span class="hlt">ice</span>-sheet effects was "too limited to assess their likelihood or provide a best estimate of an upper bound for <span class="hlt">sea</span>-level rise". <span class="hlt">Ice</span>2<span class="hlt">sea</span> was created to address these issues - the project started in 2009 and is now drawing to a close, with our final symposium in May 2013, and final publicity activities around the IPCC report release in autumn 2013. Here we present a summary of the overall and key outputs of the <span class="hlt">ice</span>2<span class="hlt">sea</span> project.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23908231','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23908231"><span>Ecological consequences of <span class="hlt">sea-ice</span> decline.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Post, Eric; Bhatt, Uma S; Bitz, Cecilia M; Brodie, Jedediah F; Fulton, Tara L; Hebblewhite, Mark; Kerby, Jeffrey; Kutz, Susan J; Stirling, Ian; Walker, Donald A</p> <p>2013-08-02</p> <p>After a decade with nine of the lowest arctic <span class="hlt">sea-ice</span> minima on record, including the historically low minimum in 2012, we synthesize recent developments in the study of ecological responses to <span class="hlt">sea-ice</span> decline. <span class="hlt">Sea-ice</span> loss emerges as an important driver of marine and terrestrial ecological dynamics, influencing productivity, species interactions, population mixing, gene flow, and pathogen and disease transmission. Major challenges in the near future include assigning clearer attribution to <span class="hlt">sea</span> <span class="hlt">ice</span> as a primary driver of such dynamics, especially in terrestrial systems, and addressing pressures arising from human use of arctic coastal and near-shore areas as <span class="hlt">sea</span> <span class="hlt">ice</span> diminishes.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFM.C43E0592P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFM.C43E0592P"><span>The Last Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> Refuge</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Pfirman, S. L.; Tremblay, B.; Newton, R.; Fowler, C.</p> <p>2010-12-01</p> <p>Summer <span class="hlt">sea</span> <span class="hlt">ice</span> may persist along the northern flank of Canada and Greenland for decades longer than the rest of the Arctic, raising the possibility of a naturally formed refugium for <span class="hlt">ice</span>-associated species. Observations and models indicate that some <span class="hlt">ice</span> in this region forms locally, while some is transported to the area by winds and ocean currents. Depending on future changes in melt patterns and <span class="hlt">sea</span> <span class="hlt">ice</span> transport rates, both the central Arctic and Siberian shelf <span class="hlt">seas</span> may be sources of <span class="hlt">ice</span> to the region. An international system of monitoring and management of the <span class="hlt">sea</span> <span class="hlt">ice</span> refuge, along with the <span class="hlt">ice</span> source regions, has the potential to maintain viable habitat for <span class="hlt">ice</span>-associated species, including polar bears, for decades into the future. Issues to consider in developing a strategy include: + the likely duration and extent of summer <span class="hlt">sea</span> <span class="hlt">ice</span> in this region based on observations, models and paleoenvironmental information + the extent and characteristics of the “<span class="hlt">ice</span> shed” contributing <span class="hlt">sea</span> <span class="hlt">ice</span> to the refuge, including its dynamics, physical and biological characteristics as well as potential for contamination from local or long-range sources + likely assemblages of <span class="hlt">ice</span>-associated species and their habitats + potential stressors such as transportation, tourism, resource extraction, contamination + policy, governance, and development issues including management strategies that could maintain the viability of the refuge.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JGRC..122.1497K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JGRC..122.1497K"><span><span class="hlt">Sea-ice</span> thickness from field measurements in the northwestern Barents <span class="hlt">Sea</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>King, Jennifer; Spreen, Gunnar; Gerland, Sebastian; Haas, Christian; Hendricks, Stefan; Kaleschke, Lars; Wang, Caixin</p> <p>2017-02-01</p> <p>The Barents <span class="hlt">Sea</span> is one of the fastest changing regions of the Arctic, and has experienced the strongest decline in winter-time <span class="hlt">sea-ice</span> area in the Arctic, at -23±4% decade-1. <span class="hlt">Sea-ice</span> thickness in the Barents <span class="hlt">Sea</span> is not well studied. We present two previously unpublished helicopter-borne electromagnetic (HEM) <span class="hlt">ice</span> thickness measurements from the northwestern Barents <span class="hlt">Sea</span> acquired in March 2003 and 2014. The HEM data are compared to <span class="hlt">ice</span> thickness calculated from <span class="hlt">ice</span> draft measured by ULS deployed between 1994 and 1996. These data show that <span class="hlt">ice</span> thickness varies greatly from year to year; influenced by the thermodynamic and dynamic processes that govern local formation vs long-range advection. In a year with a large inflow of <span class="hlt">sea-ice</span> from the Arctic Basin, the Barents <span class="hlt">Sea</span> <span class="hlt">ice</span> cover is dominated by thick multiyear <span class="hlt">ice</span>; as was the case in 2003 and 1995. In a year with an <span class="hlt">ice</span> cover that was mainly grown in situ, the <span class="hlt">ice</span> will be thin and mechanically unstable; as was the case in 2014. The HEM data allow us to explore the spatial and temporal variability in <span class="hlt">ice</span> thickness. In 2003 the dominant <span class="hlt">ice</span> class was more than 2 years old; and modal <span class="hlt">sea-ice</span> thickness varied regionally from 0.6 to 1.4 m, with the thinner <span class="hlt">ice</span> being either first-year <span class="hlt">ice</span>, or multiyear <span class="hlt">ice</span> which had come into contact with warm Atlantic water. In 2014 the <span class="hlt">ice</span> cover was predominantly locally grown <span class="hlt">ice</span> less than 1 month old (regional modes of 0.5-0.8 m). These two situations represent two extremes of a range of possible <span class="hlt">ice</span> thickness distributions that can present very different conditions for shipping traffic; or have a different impact on heat transport from ocean to atmosphere.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C11C0923F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C11C0923F"><span>Improving Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> Observations and Data Access to Support Advances in <span class="hlt">Sea</span> <span class="hlt">Ice</span> Forecasting</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Farrell, S. L.</p> <p>2017-12-01</p> <p>The economic and strategic importance of the Arctic region is becoming apparent. One of the most striking and widely publicized changes underway is the declining <span class="hlt">sea</span> <span class="hlt">ice</span> cover. Since <span class="hlt">sea</span> <span class="hlt">ice</span> is a key component of the climate system, its ongoing loss has serious, and wide-ranging, socio-economic implications. Increasing year-to-year variability in the geographic location, concentration, and thickness of the Arctic <span class="hlt">ice</span> cover will pose both challenges and opportunities. The <span class="hlt">sea</span> <span class="hlt">ice</span> research community must be engaged in sustained Arctic Observing Network (AON) initiatives so as to deliver fit-for-purpose remote sensing data products to a variety of stakeholders including Arctic communities, the weather forecasting and climate modeling communities, industry, local, regional and national governments, and policy makers. An example of engagement is the work currently underway to improve research collaborations between scientists engaged in obtaining and assessing <span class="hlt">sea</span> <span class="hlt">ice</span> observational data and those conducting numerical modeling studies and forecasting <span class="hlt">ice</span> conditions. As part of the US AON, in collaboration with the Interagency Arctic Research Policy Committee (IARPC), we are developing a strategic framework within which observers and modelers can work towards the common goal of improved <span class="hlt">sea</span> <span class="hlt">ice</span> forecasting. Here, we focus on <span class="hlt">sea</span> <span class="hlt">ice</span> thickness, a key varaible of the Arctic <span class="hlt">ice</span> cover. We describe multi-sensor, and blended, <span class="hlt">sea</span> <span class="hlt">ice</span> thickness data products under development that can be leveraged to improve model initialization and validation, as well as support data assimilation exercises. We will also present the new PolarWatch initiative (polarwatch.noaa.gov) and discuss efforts to advance access to remote sensing satellite observations and improve communication with Arctic stakeholders, so as to deliver data products that best address societal needs.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC44B..03T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC44B..03T"><span>Multi-decadal Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> roughness.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tsamados, M.; Stroeve, J.; Kharbouche, S.; Muller, J. P., , Prof; Nolin, A. W.; Petty, A.; Haas, C.; Girard-Ardhuin, F.; Landy, J.</p> <p>2017-12-01</p> <p>The transformation of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> from mainly perennial, multi-year <span class="hlt">ice</span> to a seasonal, first-year <span class="hlt">ice</span> is believed to have been accompanied by a reduction of the roughness of the <span class="hlt">ice</span> cover surface. This smoothening effect has been shown to (i) modify the momentum and heat transfer between the atmosphere and ocean, (ii) to alter the <span class="hlt">ice</span> thickness distribution which in turn controls the snow and melt pond repartition over the <span class="hlt">ice</span> cover, and (iii) to bias airborne and satellite remote sensing measurements that depend on the scattering and reflective characteristics over the <span class="hlt">sea</span> <span class="hlt">ice</span> surface topography. We will review existing and novel remote sensing methodologies proposed to estimate <span class="hlt">sea</span> <span class="hlt">ice</span> roughness, ranging from airborne LIDAR measurement (ie Operation <span class="hlt">Ice</span>Bridge), to backscatter coefficients from scatterometers (ASCAT, QUICKSCAT), to multi angle maging spectroradiometer (MISR), and to laser (Icesat) and radar altimeters (Envisat, Cryosat, Altika, Sentinel-3). We will show that by comparing and cross-calibrating these different products we can offer a consistent multi-mission, multi-decadal view of the declining <span class="hlt">sea</span> <span class="hlt">ice</span> roughness. Implications for <span class="hlt">sea</span> <span class="hlt">ice</span> physics, climate and remote sensing will also be discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19740022688&hterms=oil+monitoring&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Doil%2Bmonitoring','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19740022688&hterms=oil+monitoring&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Doil%2Bmonitoring"><span>Monitoring Arctic <span class="hlt">Sea</span> <span class="hlt">ice</span> using ERTS imagery. [Bering <span class="hlt">Sea</span>, Beaufort <span class="hlt">Sea</span>, Canadian Archipelago, and Greenland <span class="hlt">Sea</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Barnes, J. C.; Bowley, C. J.</p> <p>1974-01-01</p> <p>Because of the effect of <span class="hlt">sea</span> <span class="hlt">ice</span> on the heat balance of the Arctic and because of the expanding economic interest in arctic oil and other minerals, extensive monitoring and further study of <span class="hlt">sea</span> <span class="hlt">ice</span> is required. The application of ERTS data for mapping <span class="hlt">ice</span> is evaluated for several arctic areas, including the Bering <span class="hlt">Sea</span>, the eastern Beaufort <span class="hlt">Sea</span>, parts of the Canadian Archipelago, and the Greenland <span class="hlt">Sea</span>. Interpretive techniques are discussed, and the scales and types of <span class="hlt">ice</span> features that can be detected are described. For the Bering <span class="hlt">Sea</span>, a sample of ERTS imagery is compared with visual <span class="hlt">ice</span> reports and aerial photography from the NASA CV-990 aircraft.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014TCD.....8.3811L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014TCD.....8.3811L"><span><span class="hlt">Ice</span> and AIS: ship speed data and <span class="hlt">sea</span> <span class="hlt">ice</span> forecasts in the Baltic <span class="hlt">Sea</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Löptien, U.; Axell, L.</p> <p>2014-07-01</p> <p>The Baltic <span class="hlt">Sea</span> is a seasonally <span class="hlt">ice</span> covered marginal <span class="hlt">sea</span> located in a densely populated area in northern Europe. Severe <span class="hlt">sea</span> <span class="hlt">ice</span> conditions have the potential to hinder the intense ship traffic considerably. Thus, <span class="hlt">sea</span> <span class="hlt">ice</span> fore- and nowcasts are regularly provided by the national weather services. Typically, several <span class="hlt">ice</span> properties are allocated, but their actual usefulness is difficult to measure and the ship captains must determine their relative importance and relevance for optimal ship speed and safety ad hoc. The present study provides a more objective approach by comparing the ship speeds, obtained by the Automatic Identification System (AIS), with the respective forecasted <span class="hlt">ice</span> conditions. We find that, despite an unavoidable random component, this information is useful to constrain and rate fore- and nowcasts. More precisely, 62-67% of ship speed variations can be explained by the forecasted <span class="hlt">ice</span> properties when fitting a mixed effect model. This statistical fit is based on a test region in the Bothnian Bay during the severe winter 2011 and employes 15 to 25 min averages of ship speed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://eric.ed.gov/?q=sea&pg=5&id=EJ827417','ERIC'); return false;" href="https://eric.ed.gov/?q=sea&pg=5&id=EJ827417"><span>SIPEX--Exploring the Antarctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> Zone</span></a></p> <p><a target="_blank" href="http://www.eric.ed.gov/ERICWebPortal/search/extended.jsp?_pageLabel=advanced">ERIC Educational Resources Information Center</a></p> <p>Zicus, Sandra; Dobson, Jane; Worby, Anthony</p> <p>2008-01-01</p> <p><span class="hlt">Sea</span> <span class="hlt">ice</span> in the polar regions plays a key role in both regulating global climate and maintaining marine ecosystems. The international <span class="hlt">Sea</span> <span class="hlt">Ice</span> Physics and Ecosystem eXperiment (SIPEX) explored the <span class="hlt">sea</span> <span class="hlt">ice</span> zone around Antarctica in September and October 2007, investigating relationships between the physical <span class="hlt">sea</span> <span class="hlt">ice</span> environment and the structure of…</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C33B1187W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C33B1187W"><span><span class="hlt">Sea</span> <span class="hlt">Ice</span> in the NCEP Seasonal Forecast System</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wu, X.; Saha, S.; Grumbine, R. W.; Bailey, D. A.; Carton, J.; Penny, S. G.</p> <p>2017-12-01</p> <p><span class="hlt">Sea</span> <span class="hlt">ice</span> is known to play a significant role in the global climate system. For a weather or climate forecast system (CFS), it is important that the realistic distribution of <span class="hlt">sea</span> <span class="hlt">ice</span> is represented. <span class="hlt">Sea</span> <span class="hlt">ice</span> prediction is challenging; <span class="hlt">sea</span> <span class="hlt">ice</span> can form or melt, it can move with wind and/or ocean current; <span class="hlt">sea</span> <span class="hlt">ice</span> interacts with both the air above and ocean underneath, it influences by, and has impact on the air and ocean conditions. NCEP has developed coupled CFS (version 2, CFSv2) and also carried out CFS reanalysis (CFSR), which includes a coupled model with the NCEP global forecast system, a land model, an ocean model (GFDL MOM4), and a <span class="hlt">sea</span> <span class="hlt">ice</span> model. In this work, we present the NCEP coupled model, the CFSv2 <span class="hlt">sea</span> <span class="hlt">ice</span> component that includes a dynamic thermodynamic <span class="hlt">sea</span> <span class="hlt">ice</span> model and a simple "assimilation" scheme, how <span class="hlt">sea</span> <span class="hlt">ice</span> has been assimilated in CFSR, the characteristics of the <span class="hlt">sea</span> <span class="hlt">ice</span> from CFSR and CFSv2, and the improvements of <span class="hlt">sea</span> <span class="hlt">ice</span> needed for future seasonal prediction system, part of the Unified Global Coupled System (UGCS), which is being developed and under testing, including <span class="hlt">sea</span> <span class="hlt">ice</span> data assimilation with the Local Ensemble Transform Kalman Filter (LETKF). Preliminary results from the UGCS testing will also be presented.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-GSFC_20171208_Archive_e001605.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-GSFC_20171208_Archive_e001605.html"><span>Iceberg in <span class="hlt">sea</span> <span class="hlt">ice</span></span></a></p> <p><a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a></p> <p></p> <p>2017-12-08</p> <p>An iceberg embedded in <span class="hlt">sea</span> <span class="hlt">ice</span> as seen from the <span class="hlt">Ice</span>Bridge DC-8 over the Bellingshausen <span class="hlt">Sea</span> on Oct. 19, 2012. Credit: NASA / James Yungel NASA's Operation <span class="hlt">Ice</span>Bridge is an airborne science mission to study Earth's polar <span class="hlt">ice</span>. For more information about <span class="hlt">Ice</span>Bridge, visit: www.nasa.gov/icebridge NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMPA13A1975T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMPA13A1975T"><span>Guide to <span class="hlt">Sea</span> <span class="hlt">Ice</span> Information and <span class="hlt">Sea</span> <span class="hlt">Ice</span> Data Online - the <span class="hlt">Sea</span> <span class="hlt">Ice</span> Knowledge and Data Platform www.meereisportal.de and www.seaiceportal.de</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Treffeisen, R. E.; Nicolaus, M.; Bartsch, A.; Fritzsch, B.; Grosfeld, K.; Haas, C.; Hendricks, S.; Heygster, G.; Hiller, W.; Krumpen, T.; Melsheimer, C.; Ricker, R.; Weigelt, M.</p> <p>2016-12-01</p> <p>The combination of multi-disciplinary <span class="hlt">sea</span> <span class="hlt">ice</span> science and the rising demand of society for up-to-date information and user customized products places emphasis on creating new ways of communication between science and society. The new knowledge platform is a contribution to the cross-linking of scientifically qualified information on climate change, and focuses on the theme: `<span class="hlt">sea</span> <span class="hlt">ice</span>' in both Polar Regions. With this platform, the science opens to these changing societal demands. It is the first comprehensive German speaking knowledge platform on <span class="hlt">sea</span> <span class="hlt">ice</span>; the platform went online in 2013. The web site delivers popularized information for the general public as well as scientific data meant primarily for the more expert readers and scientists. It also provides various tools allowing for visitor interaction. The demand for the web site indicates a high level of interest from both the general public and experts. It communicates science-based information to improve awareness and understanding of <span class="hlt">sea</span> <span class="hlt">ice</span> related research. The principle concept of the new knowledge platform is based on three pillars: (1) <span class="hlt">sea</span> <span class="hlt">ice</span> knowledge and background information, (2) data portal with visualizations, and (3) expert knowledge, latest research results and press releases. Since then, the content and selection of data sets increased and the data portal received increasing attention, also from the international science community. Meanwhile, we are providing near-real time and archived data of many key parameters of <span class="hlt">sea</span> <span class="hlt">ice</span> and its snow cover. The data sets result from measurements acquired by various platforms as well as numerical simulations. Satellite observations (e.g., AMSR2, CryoSat-2 and SMOS) of <span class="hlt">sea</span> <span class="hlt">ice</span> concentration, freeboard, thickness and drift are available as gridded data sets. <span class="hlt">Sea</span> <span class="hlt">ice</span> and snow temperatures and thickness as well as atmospheric parameters are available from autonomous <span class="hlt">ice</span>-tethered platforms (buoys). Additional ship observations, <span class="hlt">ice</span> station measurements, and</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_2");'>2</a></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li class="active"><span>4</span></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_4 --> <div id="page_5" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li class="active"><span>5</span></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="81"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/14749827','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/14749827"><span>Enhanced <span class="hlt">ice</span> sheet growth in Eurasia owing to <span class="hlt">adjacent</span> <span class="hlt">ice</span>-dammed lakes.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Krinner, G; Mangerud, J; Jakobsson, M; Crucifix, M; Ritz, C; Svendsen, J I</p> <p>2004-01-29</p> <p>Large proglacial lakes cool regional summer climate because of their large heat capacity, and have been shown to modify precipitation through mesoscale atmospheric feedbacks, as in the case of Lake Agassiz. Several large <span class="hlt">ice</span>-dammed lakes, with a combined area twice that of the Caspian <span class="hlt">Sea</span>, were formed in northern Eurasia about 90,000 years ago, during the last glacial period when an <span class="hlt">ice</span> sheet centred over the Barents and Kara <span class="hlt">seas</span> blocked the large northbound Russian rivers. Here we present high-resolution simulations with an atmospheric general circulation model that explicitly simulates the surface mass balance of the <span class="hlt">ice</span> sheet. We show that the main influence of the Eurasian proglacial lakes was a significant reduction of <span class="hlt">ice</span> sheet melting at the southern margin of the Barents-Kara <span class="hlt">ice</span> sheet through strong regional summer cooling over large parts of Russia. In our simulations, the summer melt reduction clearly outweighs lake-induced decreases in moisture and hence snowfall, such as has been reported earlier for Lake Agassiz. We conclude that the summer cooling mechanism from proglacial lakes accelerated <span class="hlt">ice</span> sheet growth and delayed <span class="hlt">ice</span> sheet decay in Eurasia and probably also in North America.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C21E..02I','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C21E..02I"><span>Measurements of <span class="hlt">sea</span> <span class="hlt">ice</span> mass redistribution during <span class="hlt">ice</span> deformation event in Arctic winter</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Itkin, P.; Spreen, G.; King, J.; Rösel, A.; Skourup, H.; Munk Hvidegaard, S.; Wilkinson, J.; Oikkonen, A.; Granskog, M. A.; Gerland, S.</p> <p>2016-12-01</p> <p><span class="hlt">Sea-ice</span> growth during high winter is governed by <span class="hlt">ice</span> dynamics. The highest growth rates are found in leads that open under divergent conditions, where exposure to the cold atmosphere promotes thermodynamic growth. Additionally <span class="hlt">ice</span> thickens dynamically, where convergence causes rafting and ridging. We present a local study of <span class="hlt">sea-ice</span> growth and mass redistribution between two consecutive airborne measurements, on 19 and 24 April 2015, during the N-<span class="hlt">ICE</span>2015 expedition in the area north of Svalbard. Between the two overflights an <span class="hlt">ice</span> deformation event was observed. Airborne laser scanner (ALS) measurements revisited the same <span class="hlt">sea-ice</span> area of approximately 3x3 km. By identifying the <span class="hlt">sea</span> surface within the ALS measurements as a reference the <span class="hlt">sea</span> <span class="hlt">ice</span> plus snow freeboard was obtained with a spatial resolution of 5 m. By assuming isostatic equilibrium of level floes, the freeboard heights can be converted to <span class="hlt">ice</span> thickness. The snow depth is estimated from in-situ measurements. <span class="hlt">Sea</span> <span class="hlt">ice</span> thickness measurements were made in the same area as the ALS measurements by electromagnetic sounding from a helicopter (HEM), and with a ground-based device (EM31), which allows for cross-validation of the <span class="hlt">sea-ice</span> thickness estimated from all 3 procedures. Comparison of the ALS snow freeboard distributions between the first and second overflight shows a decrease in the thin <span class="hlt">ice</span> classes and an increase of the thick <span class="hlt">ice</span> classes. While there was no observable snowfall and a very low <span class="hlt">sea-ice</span> growth of older level <span class="hlt">ice</span> during this period, an autonomous buoy array deployed in the surroundings of the area measured by the ALS shows first divergence followed by convergence associated with shear. To quantify and link the <span class="hlt">sea</span> <span class="hlt">ice</span> deformation with the associated <span class="hlt">sea-ice</span> thickness change and mass redistribution we identify over 100 virtual buoys in the ALS data from both overflights. We triangulate the area between the buoys and calculate the strain rates and freeboard change for each individual triangle</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C11C0929S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C11C0929S"><span>Collaborations for Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> Information and Tools</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sheffield Guy, L.; Wiggins, H. V.; Turner-Bogren, E. J.; Rich, R. H.</p> <p>2017-12-01</p> <p>The dramatic and rapid changes in Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> require collaboration across boundaries, including between disciplines, sectors, institutions, and between scientists and decision-makers. This poster will highlight several projects that provide knowledge to advance the development and use of <span class="hlt">sea</span> <span class="hlt">ice</span> knowledge. <span class="hlt">Sea</span> <span class="hlt">Ice</span> for Walrus Outlook (SIWO: https://www.arcus.org/search-program/siwo) - SIWO is a resource for Alaskan Native subsistence hunters and other interested stakeholders. SIWO provides weekly reports, during April-June, of <span class="hlt">sea</span> <span class="hlt">ice</span> conditions relevant to walrus in the northern Bering and southern Chukchi <span class="hlt">seas</span>. Collaboration among scientists, Alaskan Native <span class="hlt">sea-ice</span> experts, and the Eskimo Walrus Commission is fundamental to this project's success. <span class="hlt">Sea</span> <span class="hlt">Ice</span> Prediction Network (SIPN: https://www.arcus.org/sipn) - A collaborative, multi-agency-funded project focused on seasonal Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> predictions. The goals of SIPN include: coordinate and evaluate Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> predictions; integrate, assess, and guide observations; synthesize predictions and observations; and disseminate predictions and engage key stakeholders. The <span class="hlt">Sea</span> <span class="hlt">Ice</span> Outlook—a key activity of SIPN—is an open process to share and synthesize predictions of the September minimum Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> extent and other variables. Other SIPN activities include workshops, webinars, and communications across the network. Directory of <span class="hlt">Sea</span> <span class="hlt">Ice</span> Experts (https://www.arcus.org/researchers) - ARCUS has undertaken a pilot project to develop a web-based directory of <span class="hlt">sea</span> <span class="hlt">ice</span> experts across institutions, countries, and sectors. The goal of the project is to catalyze networking between individual investigators, institutions, funding agencies, and other stakeholders interested in Arctic <span class="hlt">sea</span> <span class="hlt">ice</span>. Study of Environmental Arctic Change (SEARCH: https://www.arcus.org/search-program) - SEARCH is a collaborative program that advances research, synthesizes research findings, and broadly communicates the results to support</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012TCD.....6..505F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012TCD.....6..505F"><span>Quantification of ikaite in Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Fischer, M.; Thomas, D. N.; Krell, A.; Nehrke, G.; Göttlicher, J.; Norman, L.; Riaux-Gobin, C.; Dieckmann, G. S.</p> <p>2012-02-01</p> <p>Calcium carbonate precipitation in <span class="hlt">sea</span> <span class="hlt">ice</span> can increase pCO2 during precipitation in winter and decrease pCO2 during dissolution in spring. CaCO3 precipitation in <span class="hlt">sea</span> <span class="hlt">ice</span> is thought to potentially drive significant CO2 uptake by the ocean. However, little is known about the quantitative spatial and temporal distribution of CaCO3 within <span class="hlt">sea</span> <span class="hlt">ice</span>. This is the first quantitative study of hydrous calcium carbonate, as ikaite, in <span class="hlt">sea</span> <span class="hlt">ice</span> and discusses its potential significance for the carbon cycle in polar oceans. <span class="hlt">Ice</span> cores and brine samples were collected from pack and land fast <span class="hlt">sea</span> <span class="hlt">ice</span> between September and December 2007 during an expedition in the East Antarctic and another off Terre Adélie, Antarctica. Samples were analysed for CaCO3, Salinity, DOC, DON, Phosphate, and total alkalinity. A relationship between the measured parameters and CaCO3 precipitation could not be observed. We found calcium carbonate, as ikaite, mostly in the top layer of <span class="hlt">sea</span> <span class="hlt">ice</span> with values up to 126 mg ikaite per liter melted <span class="hlt">sea</span> <span class="hlt">ice</span>. This potentially represents a contribution between 0.12 and 9 Tg C to the annual carbon flux in polar oceans. The horizontal distribution of ikaite in <span class="hlt">sea</span> <span class="hlt">ice</span> was heterogenous. We also found the precipitate in the snow on top of the <span class="hlt">sea</span> <span class="hlt">ice</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ERL....13c4008Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ERL....13c4008Z"><span>Wind-<span class="hlt">sea</span> surface temperature-<span class="hlt">sea</span> <span class="hlt">ice</span> relationship in the Chukchi-Beaufort <span class="hlt">Seas</span> during autumn</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhang, Jing; Stegall, Steve T.; Zhang, Xiangdong</p> <p>2018-03-01</p> <p>Dramatic climate changes, especially the largest <span class="hlt">sea</span> <span class="hlt">ice</span> retreat during September and October, in the Chukchi-Beaufort <span class="hlt">Seas</span> could be a consequence of, and further enhance, complex air-<span class="hlt">ice-sea</span> interactions. To detect these interaction signals, statistical relationships between surface wind speed, <span class="hlt">sea</span> surface temperature (SST), and <span class="hlt">sea</span> <span class="hlt">ice</span> concentration (SIC) were analyzed. The results show a negative correlation between wind speed and SIC. The relationships between wind speed and SST are complicated by the presence of <span class="hlt">sea</span> <span class="hlt">ice</span>, with a negative correlation over open water but a positive correlation in <span class="hlt">sea</span> <span class="hlt">ice</span> dominated areas. The examination of spatial structures indicates that wind speed tends to increase when approaching the <span class="hlt">ice</span> edge from open water and the area fully covered by <span class="hlt">sea</span> <span class="hlt">ice</span>. The anomalous downward radiation and thermal advection, as well as their regional distribution, play important roles in shaping these relationships, though wind-driven sub-grid scale boundary layer processes may also have contributions. Considering the feedback loop involved in the wind-SST-SIC relationships, climate model experiments would be required to further untangle the underlying complex physical processes.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27650478','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27650478"><span>Canadian Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> reconstructed from bromine in the Greenland NEEM <span class="hlt">ice</span> core.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Spolaor, Andrea; Vallelonga, Paul; Turetta, Clara; Maffezzoli, Niccolò; Cozzi, Giulio; Gabrieli, Jacopo; Barbante, Carlo; Goto-Azuma, Kumiko; Saiz-Lopez, Alfonso; Cuevas, Carlos A; Dahl-Jensen, Dorthe</p> <p>2016-09-21</p> <p>Reconstructing the past variability of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> provides an essential context for recent multi-year <span class="hlt">sea</span> <span class="hlt">ice</span> decline, although few quantitative reconstructions cover the Holocene period prior to the earliest historical records 1,200 years ago. Photochemical recycling of bromine is observed over first-year, or seasonal, <span class="hlt">sea</span> <span class="hlt">ice</span> in so-called "bromine explosions" and we employ a 1-D chemistry transport model to quantify processes of bromine enrichment over first-year <span class="hlt">sea</span> <span class="hlt">ice</span> and depositional transport over multi-year <span class="hlt">sea</span> <span class="hlt">ice</span> and land <span class="hlt">ice</span>. We report bromine enrichment in the Northwest Greenland Eemian NEEM <span class="hlt">ice</span> core since the end of the Eemian interglacial 120,000 years ago, finding the maximum extension of first-year <span class="hlt">sea</span> <span class="hlt">ice</span> occurred approximately 9,000 years ago during the Holocene climate optimum, when Greenland temperatures were 2 to 3 °C above present values. First-year <span class="hlt">sea</span> <span class="hlt">ice</span> extent was lowest during the glacial stadials suggesting complete coverage of the Arctic Ocean by multi-year <span class="hlt">sea</span> <span class="hlt">ice</span>. These findings demonstrate a clear relationship between temperature and first-year <span class="hlt">sea</span> <span class="hlt">ice</span> extent in the Arctic and suggest multi-year <span class="hlt">sea</span> <span class="hlt">ice</span> will continue to decline as polar amplification drives Arctic temperatures beyond the 2 °C global average warming target of the recent COP21 Paris climate agreement.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1811086D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1811086D"><span>Atmospheric forcing of <span class="hlt">sea</span> <span class="hlt">ice</span> anomalies in the Ross <span class="hlt">Sea</span> Polynya region</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dale, Ethan; McDonald, Adrian; Rack, Wolfgang</p> <p>2016-04-01</p> <p>Despite warming trends in global temperatures, <span class="hlt">sea</span> <span class="hlt">ice</span> extent in the southern hemisphere has shown an increasing trend over recent decades. Wind-driven <span class="hlt">sea</span> <span class="hlt">ice</span> export from coastal polynyas is an important source of <span class="hlt">sea</span> <span class="hlt">ice</span> production. Areas of major polynyas in the Ross <span class="hlt">Sea</span>, the region with largest increase in <span class="hlt">sea</span> <span class="hlt">ice</span> extent, have been suggested to produce the vast amount of the <span class="hlt">sea</span> <span class="hlt">ice</span> in the region. We investigate the impacts of strong wind events on polynyas and the subsequent <span class="hlt">sea</span> <span class="hlt">ice</span> production. We utilize Bootstrap <span class="hlt">sea</span> <span class="hlt">ice</span> concentration (SIC) measurements derived from satellite based, Special Sensor Microwave Imager (SSM/I) brightness temperature images. These are compared with surface wind measurements made by automatic weather stations of the University of Wisconsin-Madison Antarctic Meteorology Program. Our analysis focusses on the winter period defined as 1st April to 1st November in this study. Wind data was used to classify each day into characteristic regimes based on the change of wind speed. For each regime, a composite of SIC anomaly was formed for the Ross <span class="hlt">Sea</span> region. We found that persistent weak winds near the edge of the Ross <span class="hlt">Ice</span> Shelf are generally associated with positive SIC anomalies in the Ross <span class="hlt">Sea</span> polynya area (RSP). Conversely we found negative SIC anomalies in this area during persistent strong winds. By analyzing <span class="hlt">sea</span> <span class="hlt">ice</span> motion vectors derived from SSM/I brightness temperatures, we find significant <span class="hlt">sea</span> <span class="hlt">ice</span> motion anomalies throughout the Ross <span class="hlt">Sea</span> during strong wind events. These anomalies persist for several days after the strong wing event. Strong, negative correlations are found between SIC within the RSP and wind speed indicating that strong winds cause significant advection of <span class="hlt">sea</span> <span class="hlt">ice</span> in the RSP. This rapid decrease in SIC is followed by a more gradual recovery in SIC. This increase occurs on a time scale greater than the average persistence of strong wind events and the resulting <span class="hlt">Sea</span> <span class="hlt">ice</span> motion anomalies, highlighting the production</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/21141043','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/21141043"><span>Loss of <span class="hlt">sea</span> <span class="hlt">ice</span> in the Arctic.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Perovich, Donald K; Richter-Menge, Jacqueline A</p> <p>2009-01-01</p> <p>The Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> cover is in decline. The areal extent of the <span class="hlt">ice</span> cover has been decreasing for the past few decades at an accelerating rate. Evidence also points to a decrease in <span class="hlt">sea</span> <span class="hlt">ice</span> thickness and a reduction in the amount of thicker perennial <span class="hlt">sea</span> <span class="hlt">ice</span>. A general global warming trend has made the <span class="hlt">ice</span> cover more vulnerable to natural fluctuations in atmospheric and oceanic forcing. The observed reduction in Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> is a consequence of both thermodynamic and dynamic processes, including such factors as preconditioning of the <span class="hlt">ice</span> cover, overall warming trends, changes in cloud coverage, shifts in atmospheric circulation patterns, increased export of older <span class="hlt">ice</span> out of the Arctic, advection of ocean heat from the Pacific and North Atlantic, enhanced solar heating of the ocean, and the <span class="hlt">ice</span>-albedo feedback. The diminishing Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> is creating social, political, economic, and ecological challenges.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009EGUGA..11.4734V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009EGUGA..11.4734V"><span><span class="hlt">Ice</span>2<span class="hlt">sea</span> - the future glacial contribution to <span class="hlt">sea</span>-level rise</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Vaughan, D. G.; Ice2sea Consortium</p> <p>2009-04-01</p> <p>The melting of continental <span class="hlt">ice</span> (glaciers, <span class="hlt">ice</span> caps and <span class="hlt">ice</span> sheets) is a substantial source of current <span class="hlt">sea</span>-level rise, and one that is accelerating more rapidly than was predicted even a few years ago. Indeed, the most recent report from Intergovernmental Panel on Climate Change highlighted that the uncertainty in projections of future <span class="hlt">sea</span>-level rise is dominated by uncertainty concerning continental <span class="hlt">ice</span>, and that understanding of the key processes that will lead to loss of continental <span class="hlt">ice</span> must be improved before reliable projections of <span class="hlt">sea</span>-level rise can be produced. Such projections are urgently required for effective <span class="hlt">sea</span>-defence management and coastal adaptation planning. <span class="hlt">Ice</span>2<span class="hlt">sea</span> is a consortium of European institutes and international partners seeking European funding to support an integrated scientific programme to improve understanding concerning the future glacial contribution to <span class="hlt">sea</span>-level rise. This includes improving understanding of the processes that control, past, current and future <span class="hlt">sea</span>-level rise, and generation of improved estimates of the contribution of glacial components to <span class="hlt">sea</span>-level rise over the next 200 years. The programme will include targeted studies of key processes in mountain glacier systems and <span class="hlt">ice</span> caps (e.g. Svalbard), and in <span class="hlt">ice</span> sheets in both polar regions (Greenland and Antarctica) to improve understanding of how these systems will respond to future climate change. It will include fieldwork and remote sensing studies, and develop a suite of new, cross-validated glacier and <span class="hlt">ice</span>-sheet model. <span class="hlt">Ice</span>2<span class="hlt">sea</span> will deliver these results in forms accessible to scientists, policy-makers and the general public, which will include clear presentations of the sources of uncertainty. Our aim is both, to provide improved projections of the glacial contribution to <span class="hlt">sea</span>-level rise, and to leave a legacy of improved tools and techniques that will form the basis of ongoing refinements in <span class="hlt">sea</span>-level projection. <span class="hlt">Ice</span>2<span class="hlt">sea</span> will provide exciting opportunities for many</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20040171197','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20040171197"><span>MODIS Snow and <span class="hlt">Sea</span> <span class="hlt">Ice</span> Products</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hall, Dorothy K.; Riggs, George A.; Salomonson, Vincent V.</p> <p>2004-01-01</p> <p>In this chapter, we describe the suite of Earth Observing System (EOS) Moderate-Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua snow and <span class="hlt">sea</span> <span class="hlt">ice</span> products. Global, daily products, developed at Goddard Space Flight Center, are archived and distributed through the National Snow and <span class="hlt">Ice</span> Data Center at various resolutions and on different grids useful for different communities Snow products include binary snow cover, snow albedo, and in the near future, fraction of snow in a 5OO-m pixel. <span class="hlt">Sea</span> <span class="hlt">ice</span> products include <span class="hlt">ice</span> extent determined with two different algorithms, and <span class="hlt">sea</span> <span class="hlt">ice</span> surface temperature. The algorithms used to develop these products are described. Both the snow and <span class="hlt">sea</span> <span class="hlt">ice</span> products, available since February 24,2000, are useful for modelers. Validation of the products is also discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=GL-2002-002288&hterms=moderating&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dmoderating','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=GL-2002-002288&hterms=moderating&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dmoderating"><span><span class="hlt">Ice</span> in Caspian <span class="hlt">Sea</span> and Aral <span class="hlt">Sea</span>, Kazakhstan</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p></p> <p>2002-01-01</p> <p>In this MODIS image from December 3, 2001, winter <span class="hlt">sea</span> <span class="hlt">ice</span> can be seen forming in the shallow waters of the northern Caspian (left) and Aral (upper right) <span class="hlt">Seas</span>. Despite the inflow of the Volga River (upper left), the northern portion of the Caspian <span class="hlt">Sea</span> averages only 17 ft in depth, and responds to the region's continental climate, which is cold in winter and hot and dry in the summer. The southern part of the <span class="hlt">Sea</span> is deeper and remains <span class="hlt">ice</span>-free throughout the winter. The dirty appearance of the <span class="hlt">ice</span> may be due to sediment in the water, but may also be due to wind-driven dust. The wind in the region can blow at hurricane-force strength and can cause the <span class="hlt">ice</span> to pile up in hummocks that are anchored to the <span class="hlt">sea</span> bottom. The eastern portion of the Aral <span class="hlt">Sea</span> is also beginning to freeze. At least two characteristics of the Aral <span class="hlt">Sea</span> 'compete' in determining whether its waters will freeze. The <span class="hlt">Sea</span> is shallow, which increases the likelihood of freezing, but it is also very salty, which means that lower temperatures are required to freeze it than would be required for fresh water. With average December temperatures of 18o F, it's clearly cold enough to allow <span class="hlt">ice</span> to form. As the waters that feed the Aral <span class="hlt">Sea</span> continue to be diverted for agriculture, the <span class="hlt">Sea</span> becomes shallower and the regional climate becomes even more continental. This is because large bodies of water absorb and retain heat, moderating seasonal changes in temperature. Credit: Jacques Descloitres, MODIS Land Rapid Response Team, NASA/GSFC</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-GSFC_20171208_Archive_e001599.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-GSFC_20171208_Archive_e001599.html"><span>Clouds Over <span class="hlt">Sea</span> <span class="hlt">Ice</span></span></a></p> <p><a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a></p> <p></p> <p>2012-11-01</p> <p>Low-lying clouds over <span class="hlt">sea</span> <span class="hlt">ice</span> on the Bellingshausen <span class="hlt">Sea</span>. Credit: NASA / Maria-Jose Vinas NASA's Operation <span class="hlt">Ice</span>Bridge is an airborne science mission to study Earth's polar <span class="hlt">ice</span>. For more information about <span class="hlt">Ice</span>Bridge, visit: www.nasa.gov/icebridge NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20010037604','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20010037604"><span>Satellite Remote Sensing: Passive-Microwave Measurements of <span class="hlt">Sea</span> <span class="hlt">Ice</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Parkinson, Claire L.; Zukor, Dorothy J. (Technical Monitor)</p> <p>2001-01-01</p> <p>Satellite passive-microwave measurements of <span class="hlt">sea</span> <span class="hlt">ice</span> have provided global or near-global <span class="hlt">sea</span> <span class="hlt">ice</span> data for most of the period since the launch of the Nimbus 5 satellite in December 1972, and have done so with horizontal resolutions on the order of 25-50 km and a frequency of every few days. These data have been used to calculate <span class="hlt">sea</span> <span class="hlt">ice</span> concentrations (percent areal coverages), <span class="hlt">sea</span> <span class="hlt">ice</span> extents, the length of the <span class="hlt">sea</span> <span class="hlt">ice</span> season, <span class="hlt">sea</span> <span class="hlt">ice</span> temperatures, and <span class="hlt">sea</span> <span class="hlt">ice</span> velocities, and to determine the timing of the seasonal onset of melt as well as aspects of the <span class="hlt">ice</span>-type composition of the <span class="hlt">sea</span> <span class="hlt">ice</span> cover. In each case, the calculations are based on the microwave emission characteristics of <span class="hlt">sea</span> <span class="hlt">ice</span> and the important contrasts between the microwave emissions of <span class="hlt">sea</span> <span class="hlt">ice</span> and those of the surrounding liquid-water medium.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017DyAtO..79...10S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017DyAtO..79...10S"><span>Sensitivity of open-water <span class="hlt">ice</span> growth and <span class="hlt">ice</span> concentration evolution in a coupled atmosphere-ocean-<span class="hlt">sea</span> <span class="hlt">ice</span> model</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Shi, Xiaoxu; Lohmann, Gerrit</p> <p>2017-09-01</p> <p>A coupled atmosphere-ocean-<span class="hlt">sea</span> <span class="hlt">ice</span> model is applied to investigate to what degree the area-thickness distribution of new <span class="hlt">ice</span> formed in open water affects the <span class="hlt">ice</span> and ocean properties. Two sensitivity experiments are performed which modify the horizontal-to-vertical aspect ratio of open-water <span class="hlt">ice</span> growth. The resulting changes in the Arctic <span class="hlt">sea-ice</span> concentration strongly affect the surface albedo, the ocean heat release to the atmosphere, and the <span class="hlt">sea-ice</span> production. The changes are further amplified through a positive feedback mechanism among the Arctic <span class="hlt">sea</span> <span class="hlt">ice</span>, the Atlantic Meridional Overturning Circulation (AMOC), and the surface air temperature in the Arctic, as the Fram Strait <span class="hlt">sea</span> <span class="hlt">ice</span> import influences the freshwater budget in the North Atlantic Ocean. Anomalies in <span class="hlt">sea-ice</span> transport lead to changes in <span class="hlt">sea</span> surface properties of the North Atlantic and the strength of AMOC. For the Southern Ocean, the most pronounced change is a warming along the Antarctic Circumpolar Current (ACC), owing to the interhemispheric bipolar seasaw linked to AMOC weakening. Another insight of this study lies on the improvement of our climate model. The ocean component FESOM is a newly developed ocean-<span class="hlt">sea</span> <span class="hlt">ice</span> model with an unstructured mesh and multi-resolution. We find that the subpolar <span class="hlt">sea-ice</span> boundary in the Northern Hemisphere can be improved by tuning the process of open-water <span class="hlt">ice</span> growth, which strongly influences the <span class="hlt">sea</span> <span class="hlt">ice</span> concentration in the marginal <span class="hlt">ice</span> zone, the North Atlantic circulation, salinity and Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> volume. Since the distribution of new <span class="hlt">ice</span> on open water relies on many uncertain parameters and the knowledge of the detailed processes is currently too crude, it is a challenge to implement the processes realistically into models. Based on our sensitivity experiments, we conclude a pronounced uncertainty related to open-water <span class="hlt">sea</span> <span class="hlt">ice</span> growth which could significantly affect the climate system sensitivity.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMOS43B2035W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMOS43B2035W"><span>Biogeochemical Coupling between Ocean and <span class="hlt">Sea</span> <span class="hlt">Ice</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wang, S.; Jeffery, N.; Maltrud, M. E.; Elliott, S.; Wolfe, J.</p> <p>2016-12-01</p> <p>Biogeochemical processes in ocean and <span class="hlt">sea</span> <span class="hlt">ice</span> are tightly coupled at high latitudes. Ongoing changes in Arctic and Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> domain likely influence the coupled system, not only through physical fields but also biogeochemical properties. Investigating the system and its changes requires representation of ocean and <span class="hlt">sea</span> <span class="hlt">ice</span> biogeochemical cycles, as well as their coupling in Earth System Models. Our work is based on ACME-HiLAT, a new offshoot of the Community Earth System Model (CESM), including a comprehensive representation of marine ecosystems in the form of the Biogeochemical Elemental Cycling Module (BEC). A full vertical column <span class="hlt">sea</span> <span class="hlt">ice</span> biogeochemical module has recently been incorporated into the <span class="hlt">sea</span> <span class="hlt">ice</span> component. We have further introduced code modifications to couple key growth-limiting nutrients (N, Si, Fe), dissolved and particulate organic matter, and phytoplankton classes that are important in polar regions between ocean and <span class="hlt">sea</span> <span class="hlt">ice</span>. The coupling of ocean and <span class="hlt">sea</span> <span class="hlt">ice</span> biology-chemistry will enable representation of key processes such as the release of important climate active constituents or seeding algae from melting <span class="hlt">sea</span> <span class="hlt">ice</span> into surface waters. Sensitivity tests suggest <span class="hlt">sea</span> <span class="hlt">ice</span> and ocean biogeochemical coupling influences phytoplankton competition, biological production, and the CO2 flux. <span class="hlt">Sea</span> <span class="hlt">ice</span> algal seeding plays an important role in determining phytoplankton composition of Arctic early spring blooms, since different groups show various responses to the seeding biomass. Iron coupling leads to increased phytoplankton biomass in the Southern Ocean, which also affects carbon uptake via the biological pump. The coupling of macronutrients and organic matter may have weaker influences on the marine ecosystem. Our developments will allow climate scientists to investigate the fully coupled responses of the <span class="hlt">sea</span> <span class="hlt">ice</span>-ocean BGC system to physical changes in polar climate.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1248935','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1248935"><span>Norwegian Young <span class="hlt">Sea</span> <span class="hlt">Ice</span> Experiment (N-<span class="hlt">ICE</span>) Field Campaign Report</span></a></p> <p><a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Walden, V. P.; Hudson, S. R.; Cohen, L.</p> <p></p> <p>The Norwegian Young <span class="hlt">Sea</span> <span class="hlt">Ice</span> (N-<span class="hlt">ICE</span>) experiment was conducted aboard the R/V Lance research vessel from January through June 2015. The primary purpose of the experiment was to better understand thin, first-year <span class="hlt">sea</span> <span class="hlt">ice</span>. This includes understanding of how different components of the Arctic system affect <span class="hlt">sea</span> <span class="hlt">ice</span>, but also how changing <span class="hlt">sea</span> <span class="hlt">ice</span> affects the system. A major part of this effort is to characterize the atmospheric conditions throughout the experiment. A micropulse lidar (MPL) (S/N: 108) was deployed from the U.S. Department of Energy’s (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility as part of the atmospheric suitemore » of instruments. The MPL operated successfully throughout the entire experiment, acquiring data from 21 January 2015 through 23 June 2015. The MPL was the essential instrument for determining the phase (water, <span class="hlt">ice</span> or mixed) of the lower-level clouds over the <span class="hlt">sea</span> <span class="hlt">ice</span>. Data obtained from the MPL during the N-<span class="hlt">ICE</span> experiment show large cloud fractions over young, thin Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> from January through June 2015 (north of Svalbard). The winter season was characterized by frequent synoptic storms and large fluctuations in the near-surface temperature. There was much less synoptic activity in spring and summer as the near-surface temperature rose to 0 C. The cloud fraction was lower in winter (60%) than in the spring and summer (80%). Supercooled liquid clouds were observed for most of the deployment, appearing first in mid-February. Spring and summer clouds were characterized by low, thick, uniform clouds.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20010100393','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20010100393"><span>Variability of Antarctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> 1979-1998</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Zwally, H. Jay; Comiso, Josefino C.; Parkinson, Claire L.; Cavalieri, Donald J.; Gloersen, Per; Koblinsky, Chester J. (Technical Monitor)</p> <p>2001-01-01</p> <p>The principal characteristics of the variability of Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> cover as previously described from satellite passive-microwave observations are also evident in a systematically-calibrated and analyzed data set for 20.2 years (1979-1998). The total Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> extent (concentration > 15 %) increased by 13,440 +/- 4180 sq km/year (+1.18 +/- 0.37%/decade). The area of <span class="hlt">sea</span> <span class="hlt">ice</span> within the extent boundary increased by 16,960 +/- 3,840 sq km/year (+1.96 +/- 0.44%/decade). Regionally, the trends in extent are positive in the Weddell <span class="hlt">Sea</span> (1.5 +/- 0.9%/decade), Pacific Ocean (2.4 +/- 1.4%/decade), and Ross (6.9 +/- 1.1 %/decade) sectors, slightly negative in the Indian Ocean (-1.5 +/- 1.8%/decade, and strongly negative in the Bellingshausen-Amundsen <span class="hlt">Seas</span> sector (-9.5 +/- 1.5%/decade). For the entire <span class="hlt">ice</span> pack, small <span class="hlt">ice</span> increases occur in all seasons with the largest increase during autumn. On a regional basis, the trends differ season to season. During summer and fall, the trends are positive or near zero in all sectors except the Bellingshausen-Amundsen <span class="hlt">Seas</span> sector. During winter and spring, the trends are negative or near zero in all sectors except the Ross <span class="hlt">Sea</span>, which has positive trends in all seasons. Components of interannual variability with periods of about 3 to 5 years are regionally large, but tend to counterbalance each other in the total <span class="hlt">ice</span> pack. The interannual variability of the annual mean <span class="hlt">sea-ice</span> extent is only 1.6% overall, compared to 5% to 9% in each of five regional sectors. Analysis of the relation between regional <span class="hlt">sea</span> <span class="hlt">ice</span> extents and spatially-averaged surface temperatures over the <span class="hlt">ice</span> pack gives an overall sensitivity between winter <span class="hlt">ice</span> cover and temperature of -0.7% change in <span class="hlt">sea</span> <span class="hlt">ice</span> extent per K. For summer, some regional <span class="hlt">ice</span> extents vary positively with temperature and others negatively. The observed increase in Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> cover is counter to the observed decreases in the Arctic. It is also qualitatively consistent with the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016ClDy...47.3301J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016ClDy...47.3301J"><span>The interaction between <span class="hlt">sea</span> <span class="hlt">ice</span> and salinity-dominated ocean circulation: implications for halocline stability and rapid changes of <span class="hlt">sea</span> <span class="hlt">ice</span> cover</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Jensen, Mari F.; Nilsson, Johan; Nisancioglu, Kerim H.</p> <p>2016-11-01</p> <p>Changes in the <span class="hlt">sea</span> <span class="hlt">ice</span> cover of the Nordic <span class="hlt">Seas</span> have been proposed to play a key role for the dramatic temperature excursions associated with the Dansgaard-Oeschger events during the last glacial. In this study, we develop a simple conceptual model to examine how interactions between <span class="hlt">sea</span> <span class="hlt">ice</span> and oceanic heat and freshwater transports affect the stability of an upper-ocean halocline in a semi-enclosed basin. The model represents a <span class="hlt">sea</span> <span class="hlt">ice</span> covered and salinity stratified Nordic <span class="hlt">Seas</span>, and consists of a <span class="hlt">sea</span> <span class="hlt">ice</span> component and a two-layer ocean. The <span class="hlt">sea</span> <span class="hlt">ice</span> thickness depends on the atmospheric energy fluxes as well as the ocean heat flux. We introduce a thickness-dependent <span class="hlt">sea</span> <span class="hlt">ice</span> export. Whether <span class="hlt">sea</span> <span class="hlt">ice</span> stabilizes or destabilizes against a freshwater perturbation is shown to depend on the representation of the diapycnal flow. In a system where the diapycnal flow increases with density differences, the <span class="hlt">sea</span> <span class="hlt">ice</span> acts as a positive feedback on a freshwater perturbation. If the diapycnal flow decreases with density differences, the <span class="hlt">sea</span> <span class="hlt">ice</span> acts as a negative feedback. However, both representations lead to a circulation that breaks down when the freshwater input at the surface is small. As a consequence, we get rapid changes in <span class="hlt">sea</span> <span class="hlt">ice</span>. In addition to low freshwater forcing, increasing deep-ocean temperatures promote instability and the disappearance of <span class="hlt">sea</span> <span class="hlt">ice</span>. Generally, the unstable state is reached before the vertical density difference disappears, and the temperature of the deep ocean do not need to increase as much as previously thought to provoke abrupt changes in <span class="hlt">sea</span> <span class="hlt">ice</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C53B0776L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C53B0776L"><span>Dynamics of landfast <span class="hlt">sea</span> <span class="hlt">ice</span> near Jangbogo Antarctic Research Station observed by SAR interferometry</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lee, H.; Han, H.</p> <p>2015-12-01</p> <p>Landfast <span class="hlt">sea</span> <span class="hlt">ice</span> is a type of <span class="hlt">sea</span> <span class="hlt">ice</span> <span class="hlt">adjacent</span> to the coast and immobile for a certain period of time. It is important to analyze the temporal and spatial variation of landfast <span class="hlt">ice</span> because it has significant influences on marine ecosystem and the safe operation of icebreaker vessels. However, it has been a difficult task for both remote sensing and in situ observation to discriminate landfast <span class="hlt">ice</span> from other types of <span class="hlt">sea</span> <span class="hlt">ice</span>, such as pack <span class="hlt">ice</span>, and also to understand the dynamics and internal strss-strain of fast <span class="hlt">ice</span>. In this study, we identify landfast <span class="hlt">ice</span> and its annual variation in Terra Nova Bay (74° 37' 4"S, 164° 13' 7"E), East Antarctica, where Jangbogo Antarctic Research Station has recently been constructed in 2014, by using Interferometric Synthetic Aperture Radar (InSAR) technology. We generated 38 interferograms having temporal baselines of 1-9 days out of 62 COSMO-SkyMed SAR images over Terra Nova Bay obtained from December 2010 to January 2012. Landfast <span class="hlt">ice</span> began to melt in November 2011 when air temperature raised above freezing point but lasted more than two month to the end of the study period in January 2012. No meaningful relationship was found between <span class="hlt">sea</span> <span class="hlt">ice</span> extent and wind and current. Glacial strain (~67cm/day) is similar to tidal strain (~40 cm) so that they appear similar in one-day InSAR. As glacial stress is cumulative while tidal stress is oscillatory, InSAR images with weekly temporal baseline (7~9 days) revealed that a consistent motion of Campbell Glacier Tongue (CGT) is pushing the <span class="hlt">sea</span> <span class="hlt">ice</span> continuously to make interferometric fringes parallel to the glacier-<span class="hlt">sea</span> <span class="hlt">ice</span> contacts. Glacial interferometric fringe is parallel to the glacier-<span class="hlt">sea</span> <span class="hlt">ice</span> contact lines while tidal strain should be parallel to the coastlines defined by <span class="hlt">sea</span> shore and glacier tongue. DDInSAR operation removed the consistent glacial strain leaving tidal strain alone so that the response of fast <span class="hlt">ice</span> to tide can be used to deduce physical properties of <span class="hlt">sea</span> <span class="hlt">ice</span> in various</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C51A0965H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C51A0965H"><span><span class="hlt">Sea</span> <span class="hlt">Ice</span> Mass Reconciliation Exercise (SIMRE) for altimetry derived <span class="hlt">sea</span> <span class="hlt">ice</span> thickness data sets</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hendricks, S.; Haas, C.; Tsamados, M.; Kwok, R.; Kurtz, N. T.; Rinne, E. J.; Uotila, P.; Stroeve, J.</p> <p>2017-12-01</p> <p>Satellite altimetry is the primary remote sensing data source for retrieval of Arctic <span class="hlt">sea-ice</span> thickness. Observational data sets are available from current and previous missions, namely ESA's Envisat and CryoSat as well as NASA ICESat. In addition, freeboard results have been published from the earlier ESA ERS missions and candidates for new data products are the Sentinel-3 constellation, the CNES AltiKa mission and NASA laser altimeter successor ICESat-2. With all the different aspects of sensor type and orbit configuration, all missions have unique properties. In addition, thickness retrieval algorithms have evolved over time and data centers have developed different strategies. These strategies may vary in choice of auxiliary data sets, algorithm parts and product resolution and masking. The <span class="hlt">Sea</span> <span class="hlt">Ice</span> Mass Reconciliation Exercise (SIMRE) is a project by the <span class="hlt">sea-ice</span> radar altimetry community to bridge the challenges of comparing data sets across missions and algorithms. The ESA Arctic+ research program facilitates this project with the objective to collect existing data sets and to derive a reconciled estimate of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> mass balance. Starting with CryoSat-2 products, we compare results from different data centers (UCL, AWI, NASA JPL & NASA GSFC) at full resolution along selected orbits with independent <span class="hlt">ice</span> thickness estimates. Three regions representative of first-year <span class="hlt">ice</span>, multiyear <span class="hlt">ice</span> and mixed <span class="hlt">ice</span> conditions are used to compare the difference in thickness and thickness change between products over the seasonal cycle. We present first results and provide an outline for the further development of SIMRE activities. The methodology for comparing data sets is designed to be extendible and the project is open to contributions by interested groups. Model results of <span class="hlt">sea</span> <span class="hlt">ice</span> thickness will be added in a later phase of the project to extend the scope of SIMRE beyond EO products.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li class="active"><span>5</span></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_5 --> <div id="page_6" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li class="active"><span>6</span></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="101"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016TCry...10.2275T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016TCry...10.2275T"><span>The EUMETSAT <span class="hlt">sea</span> <span class="hlt">ice</span> concentration climate data record</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tonboe, Rasmus T.; Eastwood, Steinar; Lavergne, Thomas; Sørensen, Atle M.; Rathmann, Nicholas; Dybkjær, Gorm; Toudal Pedersen, Leif; Høyer, Jacob L.; Kern, Stefan</p> <p>2016-09-01</p> <p>An Arctic and Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> area and extent dataset has been generated by EUMETSAT's Ocean and <span class="hlt">Sea</span> <span class="hlt">Ice</span> Satellite Application Facility (OSISAF) using the record of microwave radiometer data from NASA's Nimbus 7 Scanning Multichannel Microwave radiometer (SMMR) and the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) and Special Sensor Microwave Imager and Sounder (SSMIS) satellite sensors. The dataset covers the period from October 1978 to April 2015 and updates and further developments are planned for the next phase of the project. The methodology for computing the <span class="hlt">sea</span> <span class="hlt">ice</span> concentration uses (1) numerical weather prediction (NWP) data input to a radiative transfer model for reduction of the impact of weather conditions on the measured brightness temperatures; (2) dynamical algorithm tie points to mitigate trends in residual atmospheric, <span class="hlt">sea</span> <span class="hlt">ice</span>, and water emission characteristics and inter-sensor differences/biases; and (3) a hybrid <span class="hlt">sea</span> <span class="hlt">ice</span> concentration algorithm using the Bristol algorithm over <span class="hlt">ice</span> and the Bootstrap algorithm in frequency mode over open water. A new <span class="hlt">sea</span> <span class="hlt">ice</span> concentration uncertainty algorithm has been developed to estimate the spatial and temporal variability in <span class="hlt">sea</span> <span class="hlt">ice</span> concentration retrieval accuracy. A comparison to US National <span class="hlt">Ice</span> Center <span class="hlt">sea</span> <span class="hlt">ice</span> charts from the Arctic and the Antarctic shows that <span class="hlt">ice</span> concentrations are higher in the <span class="hlt">ice</span> charts than estimated from the radiometer data at intermediate <span class="hlt">sea</span> <span class="hlt">ice</span> concentrations between open water and 100 % <span class="hlt">ice</span>. The <span class="hlt">sea</span> <span class="hlt">ice</span> concentration climate data record is available for download at <a href=" http://www.osi-saf.org"target="_blank">www.osi-saf.org</a>, including documentation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120009528','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120009528"><span>Antarctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> Variability and Trends, 1979-2010</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Parkinson, C. L.; Cavalieri, D. J.</p> <p>2012-01-01</p> <p>In sharp contrast to the decreasing <span class="hlt">sea</span> <span class="hlt">ice</span> coverage of the Arctic, in the Antarctic the <span class="hlt">sea</span> <span class="hlt">ice</span> cover has, on average, expanded since the late 1970s. More specifically, satellite passive-microwave data for the period November 1978 - December 2010 reveal an overall positive trend in <span class="hlt">ice</span> extents of 17,100 +/- 2,300 square km/yr. Much of the increase, at 13,700 +/- 1,500 square km/yr, has occurred in the region of the Ross <span class="hlt">Sea</span>, with lesser contributions from the Weddell <span class="hlt">Sea</span> and Indian Ocean. One region, that of the Bellingshausen/Amundsen <span class="hlt">Seas</span>, has, like the Arctic, instead experienced significant <span class="hlt">sea</span> <span class="hlt">ice</span> decreases, with an overall <span class="hlt">ice</span> extent trend of -8,200 +/- 1,200 square km/yr. When examined through the annual cycle over the 32-year period 1979-2010, the Southern Hemisphere <span class="hlt">sea</span> <span class="hlt">ice</span> cover as a whole experienced positive <span class="hlt">ice</span> extent trends in every month, ranging in magnitude from a low of 9,100 +/- 6,300 square km/yr in February to a high of 24,700 +/- 10,000 square km/yr in May. The Ross <span class="hlt">Sea</span> and Indian Ocean also had positive trends in each month, while the Bellingshausen/Amundsen <span class="hlt">Seas</span> had negative trends in each month, and the Weddell <span class="hlt">Sea</span> and Western Pacific Ocean had a mixture of positive and negative trends. Comparing <span class="hlt">ice</span>-area results to <span class="hlt">ice</span>-extent results, in each case the <span class="hlt">ice</span>-area trend has the same sign as the <span class="hlt">ice</span>-extent trend, but differences in the magnitudes of the two trends identify regions with overall increasing <span class="hlt">ice</span> concentrations and others with overall decreasing <span class="hlt">ice</span> concentrations. The strong pattern of decreasing <span class="hlt">ice</span> coverage in the Bellingshausen/Amundsen <span class="hlt">Seas</span> region and increasing <span class="hlt">ice</span> coverage in the Ross <span class="hlt">Sea</span> region is suggestive of changes in atmospheric circulation. This is a key topic for future research.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUOSHE54B1584J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUOSHE54B1584J"><span>The interaction between <span class="hlt">sea</span> <span class="hlt">ice</span> and salinity-dominated ocean circulation: implications for halocline stability and rapid changes of <span class="hlt">sea-ice</span> cover</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Jensen, M. F.; Nilsson, J.; Nisancioglu, K. H.</p> <p>2016-02-01</p> <p>In this study, we develop a simple conceptual model to examine how interactions between <span class="hlt">sea</span> <span class="hlt">ice</span> and oceanic heat and freshwater transports affect the stability of an upper-ocean halocline in a semi-enclosed basin. The model represents a <span class="hlt">sea-ice</span> covered and salinity stratified ocean, and consists of a <span class="hlt">sea-ice</span> component and a two-layer ocean; a cold, fresh surface layer above a warmer, more saline layer. The <span class="hlt">sea-ice</span> thickness depends on the atmospheric energy fluxes as well as the ocean heat flux. We introduce a thickness-dependent <span class="hlt">sea-ice</span> export. Whether <span class="hlt">sea</span> <span class="hlt">ice</span> stabilizes or destabilizes against a freshwater perturbation is shown to depend on the representation of the vertical mixing. In a system where the vertical diffusivity is constant, the <span class="hlt">sea</span> <span class="hlt">ice</span> acts as a positive feedback on a freshwater perturbation. If the vertical diffusivity is derived from a constant mixing energy constraint, the <span class="hlt">sea</span> <span class="hlt">ice</span> acts as a negative feedback. However, both representations lead to a circulation that breaks down when the freshwater input at the surface is small. As a consequence, we get rapid changes in <span class="hlt">sea</span> <span class="hlt">ice</span>. In addition to low freshwater forcing, increasing deep-ocean temperatures promote instability and the disappearance of <span class="hlt">sea</span> <span class="hlt">ice</span>. Generally, the unstable state is reached before the vertical density difference disappears, and small changes in temperature and freshwater inputs can provoke abrupt changes in <span class="hlt">sea</span> <span class="hlt">ice</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3934902','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3934902"><span><span class="hlt">Sea</span> <span class="hlt">Ice</span> Biogeochemistry: A Guide for Modellers</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Tedesco, Letizia; Vichi, Marcello</p> <p>2014-01-01</p> <p><span class="hlt">Sea</span> <span class="hlt">ice</span> is a fundamental component of the climate system and plays a key role in polar trophic food webs. Nonetheless <span class="hlt">sea</span> <span class="hlt">ice</span> biogeochemical dynamics at large temporal and spatial scales are still rarely described. Numerical models may potentially contribute integrating among sparse observations, but available models of <span class="hlt">sea</span> <span class="hlt">ice</span> biogeochemistry are still scarce, whether their relevance for properly describing the current and future state of the polar oceans has been recently addressed. A general methodology to develop a <span class="hlt">sea</span> <span class="hlt">ice</span> biogeochemical model is presented, deriving it from an existing validated model application by extension of generic pelagic biogeochemistry model parameterizations. The described methodology is flexible and considers different levels of ecosystem complexity and vertical representation, while adopting a strategy of coupling that ensures mass conservation. We show how to apply this methodology step by step by building an intermediate complexity model from a published realistic application and applying it to analyze theoretically a typical season of first-year <span class="hlt">sea</span> <span class="hlt">ice</span> in the Arctic, the one currently needing the most urgent understanding. The aim is to (1) introduce <span class="hlt">sea</span> <span class="hlt">ice</span> biogeochemistry and address its relevance to ocean modelers of polar regions, supporting them in adding a new <span class="hlt">sea</span> <span class="hlt">ice</span> component to their modelling framework for a more adequate representation of the <span class="hlt">sea</span> <span class="hlt">ice</span>-covered ocean ecosystem as a whole, and (2) extend our knowledge on the relevant controlling factors of <span class="hlt">sea</span> <span class="hlt">ice</span> algal production, showing that beyond the light and nutrient availability, the duration of the <span class="hlt">sea</span> <span class="hlt">ice</span> season may play a key-role shaping the algal production during the on going and upcoming projected changes. PMID:24586604</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017CliPa..13...39M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017CliPa..13...39M"><span><span class="hlt">Sea</span> <span class="hlt">ice</span> and pollution-modulated changes in Greenland <span class="hlt">ice</span> core methanesulfonate and bromine</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Maselli, Olivia J.; Chellman, Nathan J.; Grieman, Mackenzie; Layman, Lawrence; McConnell, Joseph R.; Pasteris, Daniel; Rhodes, Rachael H.; Saltzman, Eric; Sigl, Michael</p> <p>2017-01-01</p> <p>Reconstruction of past changes in Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> extent may be critical for understanding its future evolution. Methanesulfonate (MSA) and bromine concentrations preserved in <span class="hlt">ice</span> cores have both been proposed as indicators of past <span class="hlt">sea</span> <span class="hlt">ice</span> conditions. In this study, two <span class="hlt">ice</span> cores from central and north-eastern Greenland were analysed at sub-annual resolution for MSA (CH3SO3H) and bromine, covering the time period 1750-2010. We examine correlations between <span class="hlt">ice</span> core MSA and the HadISST1 <span class="hlt">ICE</span> <span class="hlt">sea</span> <span class="hlt">ice</span> dataset and consult back trajectories to infer the likely source regions. A strong correlation between the low-frequency MSA and bromine records during pre-industrial times indicates that both chemical species are likely linked to processes occurring on or near <span class="hlt">sea</span> <span class="hlt">ice</span> in the same source regions. The positive correlation between <span class="hlt">ice</span> core MSA and bromine persists until the mid-20th century, when the acidity of Greenland <span class="hlt">ice</span> begins to increase markedly due to increased fossil fuel emissions. After that time, MSA levels decrease as a result of declining <span class="hlt">sea</span> <span class="hlt">ice</span> extent but bromine levels increase. We consider several possible explanations and ultimately suggest that increased acidity, specifically nitric acid, of snow on <span class="hlt">sea</span> <span class="hlt">ice</span> stimulates the release of reactive Br from <span class="hlt">sea</span> <span class="hlt">ice</span>, resulting in increased transport and deposition on the Greenland <span class="hlt">ice</span> sheet.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C23E..01R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C23E..01R"><span>Variational Ridging in <span class="hlt">Sea</span> <span class="hlt">Ice</span> Models</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Roberts, A.; Hunke, E. C.; Lipscomb, W. H.; Maslowski, W.; Kamal, S.</p> <p>2017-12-01</p> <p>This work presents the results of a new development to make basin-scale <span class="hlt">sea</span> <span class="hlt">ice</span> models aware of the shape, porosity and extent of individual ridges within the pack. We have derived an analytic solution for the Euler-Lagrange equation of individual ridges that accounts for non-conservative forces, and therefore the compressive strength of individual ridges. Because a region of the pack is simply a collection of paths of individual ridges, we are able to solve the Euler-Lagrange equation for a large-scale <span class="hlt">sea</span> <span class="hlt">ice</span> field also, and therefore the compressive strength of a region of the pack that explicitly accounts for the macro-porosity of ridged debris. We make a number of assumptions that have simplified the problem, such as treating <span class="hlt">sea</span> <span class="hlt">ice</span> as a granular material in ridges, and assuming that bending moments associated with ridging are perturbations around an isostatic state. Regardless of these simplifications, the ridge model is remarkably predictive of macro-porosity and ridge shape, and, because our equations are analytic, they do not require costly computations to solve the Euler-Lagrange equation of ridges on the large scale. The new ridge model is therefore applicable to large-scale <span class="hlt">sea</span> <span class="hlt">ice</span> models. We present results from this theoretical development, as well as plans to apply it to the Regional Arctic System Model and a community <span class="hlt">sea</span> <span class="hlt">ice</span> code. Most importantly, the new ridging model is particularly useful for pinpointing gaps in our observational record of <span class="hlt">sea</span> <span class="hlt">ice</span> ridges, and points to the need for improved measurements of the evolution of porosity of deformed <span class="hlt">ice</span> in the Arctic and Antarctic. Such knowledge is not only useful for improving models, but also for improving estimates of <span class="hlt">sea</span> <span class="hlt">ice</span> volume derived from altimetric measurements of <span class="hlt">sea</span> <span class="hlt">ice</span> freeboard.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-GSFC_20171208_Archive_e000266.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-GSFC_20171208_Archive_e000266.html"><span>NASA Science Flights Target Melting Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span></span></a></p> <p><a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a></p> <p></p> <p>2017-12-08</p> <p>This summer, with <span class="hlt">sea</span> <span class="hlt">ice</span> across the Arctic Ocean shrinking to below-average levels, a NASA airborne survey of polar <span class="hlt">ice</span> just completed its first flights. Its target: aquamarine pools of melt water on the <span class="hlt">ice</span> surface that may be accelerating the overall <span class="hlt">sea</span> <span class="hlt">ice</span> retreat. NASA’s Operation <span class="hlt">Ice</span>Bridge completed the first research flight of its new 2016 Arctic summer campaign on July 13. The science flights, which continue through July 25, are collecting data on <span class="hlt">sea</span> <span class="hlt">ice</span> in a year following a record-warm winter in the Arctic. Read more: go.nasa.gov/29T6mxc Caption: A large pool of melt water over <span class="hlt">sea</span> <span class="hlt">ice</span>, as seen from an Operation <span class="hlt">Ice</span>Bridge flight over the Beaufort <span class="hlt">Sea</span> on July 14, 2016. During this summer campaign, <span class="hlt">Ice</span>Bridge will map the extent, frequency and depth of melt ponds like these to help scientists forecast the Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> yearly minimum extent in September. Credit: NASA/Operation <span class="hlt">Ice</span>Bridge</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014GeoRL..41.2411S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014GeoRL..41.2411S"><span>Predicting September <span class="hlt">sea</span> <span class="hlt">ice</span>: Ensemble skill of the SEARCH <span class="hlt">Sea</span> <span class="hlt">Ice</span> Outlook 2008-2013</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Stroeve, Julienne; Hamilton, Lawrence C.; Bitz, Cecilia M.; Blanchard-Wrigglesworth, Edward</p> <p>2014-04-01</p> <p>Since 2008, the Study of Environmental Arctic Change <span class="hlt">Sea</span> <span class="hlt">Ice</span> Outlook has solicited predictions of September <span class="hlt">sea-ice</span> extent from the Arctic research community. Individuals and teams employ a variety of modeling, statistical, and heuristic approaches to make these predictions. Viewed as monthly ensembles each with one or two dozen individual predictions, they display a bimodal pattern of success. In years when observed <span class="hlt">ice</span> extent is near its trend, the median predictions tend to be accurate. In years when the observed extent is anomalous, the median and most individual predictions are less accurate. Statistical analysis suggests that year-to-year variability, rather than methods, dominate the variation in ensemble prediction success. Furthermore, ensemble predictions do not improve as the season evolves. We consider the role of initial <span class="hlt">ice</span>, atmosphere and ocean conditions, and summer storms and weather in contributing to the challenge of <span class="hlt">sea-ice</span> prediction.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA601522','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA601522"><span>Multiscale Models of Melting Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span></span></a></p> <p><a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>2013-09-30</p> <p>September 29, 2013 LONG-TERM GOALS <span class="hlt">Sea</span> <span class="hlt">ice</span> reflectance or albedo , a key parameter in climate modeling, is primarily determined by melt pond...and <span class="hlt">ice</span> floe configurations. <span class="hlt">Ice</span> - albedo feedback has played a major role in the recent declines of the summer Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> pack. However...understanding the evolution of melt ponds and <span class="hlt">sea</span> <span class="hlt">ice</span> albedo remains a significant challenge to improving climate models. Our research is focused on</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28011294','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28011294"><span><span class="hlt">Sea-ice</span> eukaryotes of the Gulf of Finland, Baltic <span class="hlt">Sea</span>, and evidence for herbivory on weakly shade-adapted <span class="hlt">ice</span> algae.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Majaneva, Markus; Blomster, Jaanika; Müller, Susann; Autio, Riitta; Majaneva, Sanna; Hyytiäinen, Kirsi; Nagai, Satoshi; Rintala, Janne-Markus</p> <p>2017-02-01</p> <p>To determine community composition and physiological status of early spring <span class="hlt">sea-ice</span> organisms, we collected <span class="hlt">sea-ice</span>, slush and under-<span class="hlt">ice</span> water samples from the Baltic <span class="hlt">Sea</span>. We combined light microscopy, HPLC pigment analysis and pyrosequencing, and related the biomass and physiological status of <span class="hlt">sea-ice</span> algae with the protistan community composition in a new way in the area. In terms of biomass, centric diatoms including a distinct Melosira arctica bloom in the upper intermediate section of the fast <span class="hlt">ice</span>, dinoflagellates, euglenoids and the cyanobacterium Aphanizomenon sp. predominated in the <span class="hlt">sea-ice</span> sections and unidentified flagellates in the slush. Based on pigment analyses, the <span class="hlt">ice</span>-algal communities showed no adjusted photosynthetic pigment pools throughout the <span class="hlt">sea</span> <span class="hlt">ice</span>, and the bottom-<span class="hlt">ice</span> communities were not shade-adapted. The <span class="hlt">sea</span> <span class="hlt">ice</span> included more characteristic phototrophic taxa (49%) than did slush (18%) and under-<span class="hlt">ice</span> water (37%). Cercozoans and ciliates were the richest taxon groups, and the differences among the communities arose mainly from the various phagotrophic protistan taxa inhabiting the communities. The presence of pheophytin a coincided with an elevated ciliate biomass and read abundance in the drift <span class="hlt">ice</span> and with a high Eurytemora affinis read abundance in the pack <span class="hlt">ice</span>, indicating that ciliates and Eurytemora affinis were grazing on algae. Copyright © 2016 Elsevier GmbH. All rights reserved.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-PIA02456.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-PIA02456.html"><span><span class="hlt">Sea</span>Winds Wind-<span class="hlt">Ice</span> Interaction</span></a></p> <p><a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a></p> <p></p> <p>2000-05-07</p> <p>The figure demonstrates of the capability of the <span class="hlt">Sea</span>Winds instrument on NASA QuikScat satellite in monitoring both <span class="hlt">sea</span> <span class="hlt">ice</span> and ocean surface wind, thus helping to further our knowledge in wind-<span class="hlt">ice</span> interaction and its effect on climate change.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19980021232','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19980021232"><span><span class="hlt">Sea</span> <span class="hlt">Ice</span> on the Southern Ocean</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Jacobs, Stanley S.</p> <p>1998-01-01</p> <p>Year-round satellite records of <span class="hlt">sea</span> <span class="hlt">ice</span> distribution now extend over more than two decades, providing a valuable tool to investigate related characteristics and circulations in the Southern Ocean. We have studied a variety of features indicative of oceanic and atmospheric interactions with Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span>. In the Amundsen & Bellingshausen <span class="hlt">Seas</span>, <span class="hlt">sea</span> <span class="hlt">ice</span> extent was found to have decreased by approximately 20% from 1973 through the early 1990's. This change coincided with and probably contributed to recently warmer surface conditions on the west side of the Antarctic Peninsula, where air temperatures have increased by approximately 0.5 C/decade since the mid-1940's. The <span class="hlt">sea</span> <span class="hlt">ice</span> decline included multiyear cycles of several years in length superimposed on high interannual variability. The retreat was strongest in summer, and would have lowered the regional mean <span class="hlt">ice</span> thickness, with attendant impacts upon vertical heat flux and the formation of snow <span class="hlt">ice</span> and brine. The cause of the regional warming and loss of <span class="hlt">sea</span> <span class="hlt">ice</span> is believed to be linked to large-scale circulation changes in the atmosphere and ocean. At the eastern end of the Weddell Gyre, the Cosmonaut Polyna revealed greater activity since 1986, a recurrence pattern during recent winters and two possible modes of formation. Persistence in polynya location was noted off Cape Ann, where the coastal current can interact more strongly with the Antarctic Circumpolar Current. As a result of vorticity conservation, locally enhanced upwelling brings warmer deep water into the mixed layer, causing divergence and melting. In the Ross <span class="hlt">Sea</span>, <span class="hlt">ice</span> extent fluctuates over periods of several years, with summer minima and winter maxima roughly in phase. This leads to large interannual cycles of <span class="hlt">sea</span> <span class="hlt">ice</span> range, which correlate positively with meridinal winds, regional air temperatures and subsequent shelf water salinities. Deep shelf waters display considerable interannual variability, but have freshened by approximately 0.03/decade</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2002AGUFMOS21B0197M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2002AGUFMOS21B0197M"><span>Biologically-Oriented Processes in the Coastal <span class="hlt">Sea</span> <span class="hlt">Ice</span> Zone of the White <span class="hlt">Sea</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Melnikov, I. A.</p> <p>2002-12-01</p> <p>The annual advance and retreat of <span class="hlt">sea</span> <span class="hlt">ice</span> is a major physical determinant of spatial and temporal changes in the structure and function of marine coastal biological communities. <span class="hlt">Sea</span> <span class="hlt">ice</span> biological data obtained in the tidal zone of Kandalaksha Gulf (White <span class="hlt">Sea</span>) during 1996-2001 period will be presented. Previous observations in this area were mainly conducted during the <span class="hlt">ice</span>-free summer season. However, there is little information on the <span class="hlt">ice</span>-covered winter season (6-7 months duration), and, especially, on the <span class="hlt">sea-ice</span> biology in the coastal zone within tidal regimes. During the January-May period time-series observations were conducted on transects along shorelines with coastal and fast <span class="hlt">ice</span>. Trends in the annual extent of <span class="hlt">sea</span> <span class="hlt">ice</span> showed significant impacts on <span class="hlt">ice</span>-associated biological communities. Three types of <span class="hlt">sea</span> <span class="hlt">ice</span> impact on kelps, balanoides, littorinas and amphipods are distinguished: (i) positive, when <span class="hlt">sea</span> <span class="hlt">ice</span> protects these populations from grinding (ii) negative, when <span class="hlt">ice</span> grinds both fauna and flora, and (iii) a combined effect, when fast <span class="hlt">ice</span> protects, but anchored <span class="hlt">ice</span> grinds plant and animals. To understand the full spectrum of ecological problems caused by pollution on the coastal zone, as well as the problems of <span class="hlt">sea</span> <span class="hlt">ice</span> melting caused by global warming, an integrated, long-term study of the physical, chemical, and biological processes is needed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/20601510','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/20601510"><span>Proteorhodopsin-bearing bacteria in Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span>.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Koh, Eileen Y; Atamna-Ismaeel, Nof; Martin, Andrew; Cowie, Rebecca O M; Beja, Oded; Davy, Simon K; Maas, Elizabeth W; Ryan, Ken G</p> <p>2010-09-01</p> <p>Proteorhodopsins (PRs) are widespread bacterial integral membrane proteins that function as light-driven proton pumps. Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> supports a complex community of autotrophic algae, heterotrophic bacteria, viruses, and protists that are an important food source for higher trophic levels in <span class="hlt">ice</span>-covered regions of the Southern Ocean. Here, we present the first report of PR-bearing bacteria, both dormant and active, in Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> from a series of sites in the Ross <span class="hlt">Sea</span> using gene-specific primers. Positive PR sequences were generated from genomic DNA at all depths in <span class="hlt">sea</span> <span class="hlt">ice</span>, and these sequences aligned with the classes Alphaproteobacteria, Gammaproteobacteria, and Flavobacteria. The sequences showed some similarity to previously reported PR sequences, although most of the sequences were generally distinct. Positive PR sequences were also observed from cDNA reverse transcribed from RNA isolated from <span class="hlt">sea</span> <span class="hlt">ice</span> samples. This finding indicates that these sequences were generated from metabolically active cells and suggests that the PR gene is functional within <span class="hlt">sea</span> <span class="hlt">ice</span>. Both blue-absorbing and green-absorbing forms of PRs were detected, and only a limited number of blue-absorbing forms were found and were in the midsection of the <span class="hlt">sea</span> <span class="hlt">ice</span> profile in this study. Questions still remain regarding the protein's ecological functions, and ultimately, field experiments will be needed to establish the ecological and functional role of PRs in the <span class="hlt">sea</span> <span class="hlt">ice</span> ecosystem.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70175240','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70175240"><span>Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> decline contributes to thinning lake <span class="hlt">ice</span> trend in northern Alaska</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Alexeev, Vladimir; Arp, Christopher D.; Jones, Benjamin M.; Cai, Lei</p> <p>2016-01-01</p> <p>Field measurements, satellite observations, and models document a thinning trend in seasonal Arctic lake <span class="hlt">ice</span> growth, causing a shift from bedfast to floating <span class="hlt">ice</span> conditions. September <span class="hlt">sea</span> <span class="hlt">ice</span> concentrations in the Arctic Ocean since 1991 correlate well (r = +0.69,p < 0.001) to this lake regime shift. To understand how and to what extent <span class="hlt">sea</span> <span class="hlt">ice</span> affects lakes, we conducted model experiments to simulate winters with years of high (1991/92) and low (2007/08) <span class="hlt">sea</span> <span class="hlt">ice</span> extent for which we also had field measurements and satellite imagery characterizing lake <span class="hlt">ice</span> conditions. A lake <span class="hlt">ice</span> growth model forced with Weather Research and Forecasting model output produced a 7% decrease in lake <span class="hlt">ice</span> growth when 2007/08 <span class="hlt">sea</span> <span class="hlt">ice</span> was imposed on 1991/92 climatology and a 9% increase in lake <span class="hlt">ice</span> growth for the opposing experiment. Here, we clearly link early winter 'ocean-effect' snowfall and warming to reduced lake <span class="hlt">ice</span> growth. Future reductions in <span class="hlt">sea</span> <span class="hlt">ice</span> extent will alter hydrological, biogeochemical, and habitat functioning of Arctic lakes and cause sub-lake permafrost thaw.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19850017731&hterms=climate+exchange&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dclimate%2Bexchange','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19850017731&hterms=climate+exchange&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dclimate%2Bexchange"><span><span class="hlt">Sea</span> <span class="hlt">Ice</span>, Climate and Fram Strait</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hunkins, K.</p> <p>1984-01-01</p> <p>When <span class="hlt">sea</span> <span class="hlt">ice</span> is formed the albedo of the ocean surface increases from its open water value of about 0.1 to a value as high as 0.8. This albedo change effects the radiation balance and thus has the potential to alter climate. <span class="hlt">Sea</span> <span class="hlt">ice</span> also partially seals off the ocean from the atmosphere, reducing the exchange of gases such as carbon dioxide. This is another possible mechanism by which climate might be affected. The Marginal <span class="hlt">Ice</span> Zone Experiment (MIZEX 83 to 84) is an international, multidisciplinary study of processes controlling the edge of the <span class="hlt">ice</span> pack in that area including the interactions between <span class="hlt">sea</span>, air and <span class="hlt">ice</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/19884496','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/19884496"><span>The future of <span class="hlt">ice</span> sheets and <span class="hlt">sea</span> <span class="hlt">ice</span>: between reversible retreat and unstoppable loss.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Notz, Dirk</p> <p>2009-12-08</p> <p>We discuss the existence of cryospheric "tipping points" in the Earth's climate system. Such critical thresholds have been suggested to exist for the disappearance of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> and the retreat of <span class="hlt">ice</span> sheets: Once these <span class="hlt">ice</span> masses have shrunk below an anticipated critical extent, the <span class="hlt">ice</span>-albedo feedback might lead to the irreversible and unstoppable loss of the remaining <span class="hlt">ice</span>. We here give an overview of our current understanding of such threshold behavior. By using conceptual arguments, we review the recent findings that such a tipping point probably does not exist for the loss of Arctic summer <span class="hlt">sea</span> <span class="hlt">ice</span>. Hence, in a cooler climate, <span class="hlt">sea</span> <span class="hlt">ice</span> could recover rapidly from the loss it has experienced in recent years. In addition, we discuss why this recent rapid retreat of Arctic summer <span class="hlt">sea</span> <span class="hlt">ice</span> might largely be a consequence of a slow shift in <span class="hlt">ice</span>-thickness distribution, which will lead to strongly increased year-to-year variability of the Arctic summer <span class="hlt">sea-ice</span> extent. This variability will render seasonal forecasts of the Arctic summer <span class="hlt">sea-ice</span> extent increasingly difficult. We also discuss why, in contrast to Arctic summer <span class="hlt">sea</span> <span class="hlt">ice</span>, a tipping point is more likely to exist for the loss of the Greenland <span class="hlt">ice</span> sheet and the West Antarctic <span class="hlt">ice</span> sheet.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19970009603','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19970009603"><span>Polarimetric Signatures of <span class="hlt">Sea</span> <span class="hlt">Ice</span>. Part 1; Theoretical Model</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Nghiem, S. V.; Kwok, R.; Yueh, S. H.; Drinkwater, M. R.</p> <p>1995-01-01</p> <p>Physical, structural, and electromagnetic properties and interrelating processes in <span class="hlt">sea</span> <span class="hlt">ice</span> are used to develop a composite model for polarimetric backscattering signatures of <span class="hlt">sea</span> <span class="hlt">ice</span>. Physical properties of <span class="hlt">sea</span> <span class="hlt">ice</span> constituents such as <span class="hlt">ice</span>, brine, air, and salt are presented in terms of their effects on electromagnetic wave interactions. <span class="hlt">Sea</span> <span class="hlt">ice</span> structure and geometry of scatterers are related to wave propagation, attenuation, and scattering. Temperature and salinity, which are determining factors for the thermodynamic phase distribution in <span class="hlt">sea</span> <span class="hlt">ice</span>, are consistently used to derive both effective permittivities and polarimetric scattering coefficients. Polarimetric signatures of <span class="hlt">sea</span> <span class="hlt">ice</span> depend on crystal sizes and brine volumes, which are affected by <span class="hlt">ice</span> growth rates. Desalination by brine expulsion, drainage, or other mechanisms modifies wave penetration and scattering. <span class="hlt">Sea</span> <span class="hlt">ice</span> signatures are further complicated by surface conditions such as rough interfaces, hummocks, snow cover, brine skim, or slush layer. Based on the same set of geophysical parameters characterizing <span class="hlt">sea</span> <span class="hlt">ice</span>, a composite model is developed to calculate effective permittivities and backscattering covariance matrices at microwave frequencies for interpretation of <span class="hlt">sea</span> <span class="hlt">ice</span> polarimetric signatures.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1990JGR....9513393W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1990JGR....9513393W"><span>Satellite observations of the <span class="hlt">ice</span> cover of the Kuril Basin Region of the Okhotsk <span class="hlt">Sea</span> and its relation to the regional oceanography</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wakatsuchi, Masaaki; Martin, Seelye</p> <p>1990-08-01</p> <p>For the period 1978-1982, this paper examines the nature of the <span class="hlt">sea</span> <span class="hlt">ice</span> which forms over the Kuril Basin of the Okhotsk <span class="hlt">Sea</span> and describes the impact of this <span class="hlt">ice</span> on the regional oceanography. The paper compares the oceanographic behavior during the heavy <span class="hlt">ice</span> season associated with the cold 1979 winter with the behavior during the lighter <span class="hlt">ice</span> years of 1980 and 1982. Examination of the oceanography in the Okhotsk and the <span class="hlt">adjacent</span> Pacific shows that the early summer water column structure depends on the heat loss from the Okhotsk during the preceding <span class="hlt">ice</span> season, the total amount of Okhotsk <span class="hlt">ice</span> formation, and specifically the amount of <span class="hlt">ice</span> formation in the Kuril Basin. Following the 1979 <span class="hlt">ice</span> season, the upper 200-300 m of the Kuril Basin waters were cooler, less saline, and richer in oxygen than for the other years. This modification appears to be a process local to the Kuril Basin, driven by eddy-induced mixing, local cooling, and <span class="hlt">ice</span> melting. In the depths 300-1200 m, the water modification is caused by the advection of water from the northern Okhotsk. For 1979, this deeper water is also less saline, colder, and richer in oxygen than for the lighter <span class="hlt">ice</span> years. The water modified in the Okhotsk enters the <span class="hlt">adjacent</span> North Pacific through the Bussol' Strait, where for 1979 the <span class="hlt">adjacent</span> waters are also cooler, less saline, and richer in oxygen down to a depth of 1000 m than for the lighter <span class="hlt">ice</span> years.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017PrOce.156...17L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017PrOce.156...17L"><span>Under the <span class="hlt">sea</span> <span class="hlt">ice</span>: Exploring the relationship between <span class="hlt">sea</span> <span class="hlt">ice</span> and the foraging behaviour of southern elephant seals in East Antarctica</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Labrousse, Sara; Sallée, Jean-Baptiste; Fraser, Alexander D.; Massom, Robert A.; Reid, Phillip; Sumner, Michael; Guinet, Christophe; Harcourt, Robert; McMahon, Clive; Bailleul, Frédéric; Hindell, Mark A.; Charrassin, Jean-Benoit</p> <p>2017-08-01</p> <p>Investigating ecological relationships between predators and their environment is essential to understand the response of marine ecosystems to climate variability and change. This is particularly true in polar regions, where <span class="hlt">sea</span> <span class="hlt">ice</span> (a sensitive climate variable) plays a crucial yet highly dynamic and variable role in how it influences the whole marine ecosystem, from phytoplankton to top predators. For mesopredators such as seals, <span class="hlt">sea</span> <span class="hlt">ice</span> both supports a rich (under-<span class="hlt">ice</span>) food resource, access to which depends on local to regional coverage and conditions. Here, we investigate sex-specific relationships between the foraging strategies of southern elephant seals (Mirounga leonina) in winter and spatio-temporal variability in <span class="hlt">sea</span> <span class="hlt">ice</span> concentration (SIC) and coverage in East Antarctica. We satellite-tracked 46 individuals undertaking post-moult trips in winter from Kerguelen Islands to the peri-Antarctic shelf between 2004 and 2014. These data indicate distinct general patterns of <span class="hlt">sea</span> <span class="hlt">ice</span> usage: while females tended to follow the <span class="hlt">sea</span> <span class="hlt">ice</span> edge as it extended northward, the males remained on the continental shelf despite increasing <span class="hlt">sea</span> <span class="hlt">ice</span>. Seal hunting time, a proxy of foraging activity inferred from the diving behaviour, was longer for females in late autumn in the outer part of the pack <span class="hlt">ice</span>, ∼150-370 km south of the <span class="hlt">ice</span> edge. Within persistent regions of compact <span class="hlt">sea</span> <span class="hlt">ice</span>, females had a longer foraging activity (i) in the highest <span class="hlt">sea</span> <span class="hlt">ice</span> concentration at their position, but (ii) their foraging activity was longer when there were more patches of low concentration <span class="hlt">sea</span> <span class="hlt">ice</span> around their position (either in time or in space; 30 days & 50 km). The high spatio-temporal variability of <span class="hlt">sea</span> <span class="hlt">ice</span> around female positions is probably a key factor allowing them to exploit these concentrated patches. Despite lack of information on prey availability, females may exploit mesopelagic finfishes and squids that concentrate near the <span class="hlt">ice</span>-water interface or within the water column (from</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li class="active"><span>6</span></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_6 --> <div id="page_7" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li class="active"><span>7</span></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="121"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016GeoRL..43.1642G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016GeoRL..43.1642G"><span>Predictability of the Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> edge</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Goessling, H. F.; Tietsche, S.; Day, J. J.; Hawkins, E.; Jung, T.</p> <p>2016-02-01</p> <p>Skillful <span class="hlt">sea</span> <span class="hlt">ice</span> forecasts from days to years ahead are becoming increasingly important for the operation and planning of human activities in the Arctic. Here we analyze the potential predictability of the Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> edge in six climate models. We introduce the integrated <span class="hlt">ice</span>-edge error (IIEE), a user-relevant verification metric defined as the area where the forecast and the "truth" disagree on the <span class="hlt">ice</span> concentration being above or below 15%. The IIEE lends itself to decomposition into an absolute extent error, corresponding to the common <span class="hlt">sea</span> <span class="hlt">ice</span> extent error, and a misplacement error. We find that the often-neglected misplacement error makes up more than half of the climatological IIEE. In idealized forecast ensembles initialized on 1 July, the IIEE grows faster than the absolute extent error. This means that the Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> edge is less predictable than <span class="hlt">sea</span> <span class="hlt">ice</span> extent, particularly in September, with implications for the potential skill of end-user relevant forecasts.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ISPAr42.3.2419Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ISPAr42.3.2419Z"><span><span class="hlt">Sea</span> <span class="hlt">Ice</span> Drift Monitoring in the Bohai <span class="hlt">Sea</span> Based on GF4 Satellite</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhao, Y.; Wei, P.; Zhu, H.; Xing, B.</p> <p>2018-04-01</p> <p>The Bohai <span class="hlt">Sea</span> is the inland <span class="hlt">sea</span> with the highest latitude in China. In winter, the phenomenon of freezing occurs in the Bohai <span class="hlt">Sea</span> due to frequent cold wave influx. According to historical records, there have been three serious <span class="hlt">ice</span> packs in the Bohai <span class="hlt">Sea</span> in the past 50 years which caused heavy losses to our economy. Therefore, it is of great significance to monitor the drift of <span class="hlt">sea</span> <span class="hlt">ice</span> and <span class="hlt">sea</span> <span class="hlt">ice</span> in the Bohai <span class="hlt">Sea</span>. The GF4 image has the advantages of short imaging time and high spatial resolution. Based on the GF4 satellite images, the three methods of SIFT (Scale invariant feature - the transform and Scale invariant feature transform), MCC (maximum cross-correlation method) and sift combined with MCC are used to monitor <span class="hlt">sea</span> <span class="hlt">ice</span> drift and calculate the speed and direction of <span class="hlt">sea</span> <span class="hlt">ice</span> drift, the three calculation results are compared and analyzed by using expert interpretation and historical statistical data to carry out remote sensing monitoring of <span class="hlt">sea</span> <span class="hlt">ice</span> drift results. The experimental results show that the experimental results of the three methods are in accordance with expert interpretation and historical statistics. Therefore, the GF4 remote sensing satellite images have the ability to monitor <span class="hlt">sea</span> <span class="hlt">ice</span> drift and can be used for drift monitoring of <span class="hlt">sea</span> <span class="hlt">ice</span> in the Bohai <span class="hlt">Sea</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28025300','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28025300"><span>Linking scales in <span class="hlt">sea</span> <span class="hlt">ice</span> mechanics.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Weiss, Jérôme; Dansereau, Véronique</p> <p>2017-02-13</p> <p>Mechanics plays a key role in the evolution of the <span class="hlt">sea</span> <span class="hlt">ice</span> cover through its control on drift, on momentum and thermal energy exchanges between the polar oceans and the atmosphere along cracks and faults, and on <span class="hlt">ice</span> thickness distribution through opening and ridging processes. At the local scale, a significant variability of the mechanical strength is associated with the microstructural heterogeneity of saline <span class="hlt">ice</span>, however characterized by a small correlation length, below the <span class="hlt">ice</span> thickness scale. Conversely, the <span class="hlt">sea</span> <span class="hlt">ice</span> mechanical fields (velocity, strain and stress) are characterized by long-ranged (more than 1000 km) and long-lasting (approx. few months) correlations. The associated space and time scaling laws are the signature of the brittle character of <span class="hlt">sea</span> <span class="hlt">ice</span> mechanics, with deformation resulting from a multi-scale accumulation of episodic fracturing and faulting events. To translate the short-range-correlated disorder on strength into long-range-correlated mechanical fields, several key ingredients are identified: long-ranged elastic interactions, slow driving conditions, a slow viscous-like relaxation of elastic stresses and a restoring/healing mechanism. These ingredients constrained the development of a new continuum mechanics modelling framework for the <span class="hlt">sea</span> <span class="hlt">ice</span> cover, called Maxwell-elasto-brittle. Idealized simulations without advection demonstrate that this rheological framework reproduces the main characteristics of <span class="hlt">sea</span> <span class="hlt">ice</span> mechanics, including anisotropy, spatial localization and intermittency, as well as the associated scaling laws.This article is part of the themed issue 'Microdynamics of <span class="hlt">ice</span>'. © 2016 The Author(s).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017RSPTA.37550352W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017RSPTA.37550352W"><span>Linking scales in <span class="hlt">sea</span> <span class="hlt">ice</span> mechanics</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Weiss, Jérôme; Dansereau, Véronique</p> <p>2017-02-01</p> <p>Mechanics plays a key role in the evolution of the <span class="hlt">sea</span> <span class="hlt">ice</span> cover through its control on drift, on momentum and thermal energy exchanges between the polar oceans and the atmosphere along cracks and faults, and on <span class="hlt">ice</span> thickness distribution through opening and ridging processes. At the local scale, a significant variability of the mechanical strength is associated with the microstructural heterogeneity of saline <span class="hlt">ice</span>, however characterized by a small correlation length, below the <span class="hlt">ice</span> thickness scale. Conversely, the <span class="hlt">sea</span> <span class="hlt">ice</span> mechanical fields (velocity, strain and stress) are characterized by long-ranged (more than 1000 km) and long-lasting (approx. few months) correlations. The associated space and time scaling laws are the signature of the brittle character of <span class="hlt">sea</span> <span class="hlt">ice</span> mechanics, with deformation resulting from a multi-scale accumulation of episodic fracturing and faulting events. To translate the short-range-correlated disorder on strength into long-range-correlated mechanical fields, several key ingredients are identified: long-ranged elastic interactions, slow driving conditions, a slow viscous-like relaxation of elastic stresses and a restoring/healing mechanism. These ingredients constrained the development of a new continuum mechanics modelling framework for the <span class="hlt">sea</span> <span class="hlt">ice</span> cover, called Maxwell-elasto-brittle. Idealized simulations without advection demonstrate that this rheological framework reproduces the main characteristics of <span class="hlt">sea</span> <span class="hlt">ice</span> mechanics, including anisotropy, spatial localization and intermittency, as well as the associated scaling laws. This article is part of the themed issue 'Microdynamics of <span class="hlt">ice</span>'.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2791593','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2791593"><span>The future of <span class="hlt">ice</span> sheets and <span class="hlt">sea</span> <span class="hlt">ice</span>: Between reversible retreat and unstoppable loss</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Notz, Dirk</p> <p>2009-01-01</p> <p>We discuss the existence of cryospheric “tipping points” in the Earth's climate system. Such critical thresholds have been suggested to exist for the disappearance of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> and the retreat of <span class="hlt">ice</span> sheets: Once these <span class="hlt">ice</span> masses have shrunk below an anticipated critical extent, the ice–albedo feedback might lead to the irreversible and unstoppable loss of the remaining <span class="hlt">ice</span>. We here give an overview of our current understanding of such threshold behavior. By using conceptual arguments, we review the recent findings that such a tipping point probably does not exist for the loss of Arctic summer <span class="hlt">sea</span> <span class="hlt">ice</span>. Hence, in a cooler climate, <span class="hlt">sea</span> <span class="hlt">ice</span> could recover rapidly from the loss it has experienced in recent years. In addition, we discuss why this recent rapid retreat of Arctic summer <span class="hlt">sea</span> <span class="hlt">ice</span> might largely be a consequence of a slow shift in <span class="hlt">ice</span>-thickness distribution, which will lead to strongly increased year-to-year variability of the Arctic summer <span class="hlt">sea-ice</span> extent. This variability will render seasonal forecasts of the Arctic summer <span class="hlt">sea-ice</span> extent increasingly difficult. We also discuss why, in contrast to Arctic summer <span class="hlt">sea</span> <span class="hlt">ice</span>, a tipping point is more likely to exist for the loss of the Greenland <span class="hlt">ice</span> sheet and the West Antarctic <span class="hlt">ice</span> sheet. PMID:19884496</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20170003145','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20170003145"><span>Antarctic <span class="hlt">Sea-Ice</span> Freeboard and Estimated Thickness from NASA's ICESat and <span class="hlt">Ice</span>Bridge Observations</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Yi, Donghui; Kurtz, Nathan; Harbeck, Jeremy; Manizade, Serdar; Hofton, Michelle; Cornejo, Helen G.; Zwally, H. Jay; Robbins, John</p> <p>2016-01-01</p> <p>ICESat completed 18 observational campaigns during its lifetime from 2003 to 2009. Data from all of the 18 campaign periods are used in this study. Most of the operational periods were between 34 and 38 days long. Because of laser failure and orbit transition from 8-day to 91-day orbit, there were four periods lasting 57, 16, 23, and 12 days. <span class="hlt">Ice</span>Bridge data from 2009, 2010, and 2011 are used in this study. Since 2009, there are 19 Airborne Topographic Mapper (ATM) campaigns, and eight Land, Vegetation, and <span class="hlt">Ice</span> Sensor (LVIS) campaigns over the Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span>. Freeboard heights are derived from ICESat, ATM and LVIS elevation and waveform data. With nominal densities of snow, water, and <span class="hlt">sea</span> <span class="hlt">ice</span>, combined with snow depth data from AMSR-E/AMSR2 passive microwave observation over the southern ocean, <span class="hlt">sea-ice</span> thickness is derived from the freeboard. Combined with AMSR-E/AMSR2 <span class="hlt">ice</span> concentration, <span class="hlt">sea-ice</span> area and volume are also calculated. During the 2003-2009 period, <span class="hlt">sea-ice</span> freeboard and thickness distributions show clear seasonal variations that reflect the yearly cycle of the growth and decay of the Antarctic pack <span class="hlt">ice</span>. We found no significant trend of thickness or area for the Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> during the ICESat period. <span class="hlt">Ice</span>Bridge <span class="hlt">sea</span> <span class="hlt">ice</span> freeboard and thickness data from 2009 to 2011 over the Weddell <span class="hlt">Sea</span> and Amundsen and Bellingshausen <span class="hlt">Seas</span> are compared with the ICESat results.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27670112','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27670112"><span>Microbial mercury methylation in Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span>.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Gionfriddo, Caitlin M; Tate, Michael T; Wick, Ryan R; Schultz, Mark B; Zemla, Adam; Thelen, Michael P; Schofield, Robyn; Krabbenhoft, David P; Holt, Kathryn E; Moreau, John W</p> <p>2016-08-01</p> <p>Atmospheric deposition of mercury onto <span class="hlt">sea</span> <span class="hlt">ice</span> and circumpolar <span class="hlt">sea</span> water provides mercury for microbial methylation, and contributes to the bioaccumulation of the potent neurotoxin methylmercury in the marine food web. Little is known about the abiotic and biotic controls on microbial mercury methylation in polar marine systems. However, mercury methylation is known to occur alongside photochemical and microbial mercury reduction and subsequent volatilization. Here, we combine mercury speciation measurements of total and methylated mercury with metagenomic analysis of whole-community microbial DNA from Antarctic snow, brine, <span class="hlt">sea</span> <span class="hlt">ice</span> and <span class="hlt">sea</span> water to elucidate potential microbially mediated mercury methylation and volatilization pathways in polar marine environments. Our results identify the marine microaerophilic bacterium Nitrospina as a potential mercury methylator within <span class="hlt">sea</span> <span class="hlt">ice</span>. Anaerobic bacteria known to methylate mercury were notably absent from <span class="hlt">sea-ice</span> metagenomes. We propose that Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> can harbour a microbial source of methylmercury in the Southern Ocean.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.C31A0622S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.C31A0622S"><span>Probabilistic Forecasting of Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> Extent</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Slater, A. G.</p> <p>2013-12-01</p> <p><span class="hlt">Sea</span> <span class="hlt">ice</span> in the Arctic is changing rapidly. Most noticeable has been the series of record, or near-record, annual minimums in <span class="hlt">sea</span> <span class="hlt">ice</span> extent in the past six years. The changing regime of <span class="hlt">sea</span> <span class="hlt">ice</span> has prompted much interest in seasonal prediction of <span class="hlt">sea</span> <span class="hlt">ice</span> extent, particularly as opportunities for Arctic shipping and resource exploration or extraction increase. This study presents a daily <span class="hlt">sea</span> <span class="hlt">ice</span> extent probabilistic forecast method with a 50-day lead time. A base projection is made from historical data and near-real-time <span class="hlt">sea</span> <span class="hlt">ice</span> concentration is assimilated on the issue date of the forecast. When considering the September mean <span class="hlt">ice</span> extent for the period 1995-2012, the performance of the 50-day lead time forecast is very good: correlation=0.94, Bias = 0.14 ×106 km^2 and RMSE = 0.36 ×106 km^2. Forecasts for the daily minimum contains equal skill levels. The system is highly competitive with any of the SEARCH <span class="hlt">Sea</span> <span class="hlt">Ice</span> Outlook estimates. The primary finding of this study is that large amounts of forecast skill can be gained from knowledge of the initial conditions of concentration (perhaps more than previously thought). Given the simplicity of the forecast model, improved skill should be available from system refinement and with suitable proxies for large scale atmosphere and ocean circulation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/biblio/5599042-airborne-gravity-measurement-over-sea-ice-western-weddel-sea','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/5599042-airborne-gravity-measurement-over-sea-ice-western-weddel-sea"><span>Airborne gravity measurement over <span class="hlt">sea-ice</span>: The western Weddel <span class="hlt">Sea</span></span></a></p> <p><a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Brozena, J.; Peters, M.; LaBrecque, J.</p> <p>1990-10-01</p> <p>An airborne gravity study of the western Weddel <span class="hlt">Sea</span>, east of the Antarctic Peninsula, has shown that floating pack-<span class="hlt">ice</span> provides a useful radar altimetric reference surface for altitude and vertical acceleration corrections surface for alititude and vertical acceleration corrections to airborne gravimetry. Airborne gravimetry provides an important alternative to satellite altimetry for the <span class="hlt">sea-ice</span> covered regions of the world since satellite alimeters are not designed or intended to provide accurate geoidal heights in areas where significant <span class="hlt">sea-ice</span> is present within the radar footprint. Errors in radar corrected airborne gravimetry are primarily sensitive to the variations in the second derivative ofmore » the <span class="hlt">sea-ice</span> reference surface in the frequency pass-band of interest. With the exception of imbedded icebergs the second derivative of the pack-<span class="hlt">ice</span> surface closely approximates that of the mean <span class="hlt">sea</span>-level surface at wavelengths > 10-20 km. With the airborne method the percentage of <span class="hlt">ice</span> coverage, the mixture of first and multi-year <span class="hlt">ice</span> and the existence of leads and pressure ridges prove to be unimportant in determining gravity anomalies at scales of geophysical and geodetic interest, provided that the <span class="hlt">ice</span> is floating and not grounded. In the Weddell study an analysis of 85 crosstrack miss-ties distributed over 25 data tracks yields an rms error of 2.2 mGals. Significant structural anomalies including the continental shelf and offsets and lineations interpreted as fracture zones recording the early spreading directions within the Weddell <span class="hlt">Sea</span> are observed in the gravity map.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C21G1192Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C21G1192Z"><span>Under <span class="hlt">Sea</span> <span class="hlt">Ice</span> phytoplankton bloom detection and contamination in Antarctica</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zeng, C.; Zeng, T.; Xu, H.</p> <p>2017-12-01</p> <p>Previous researches reported compelling <span class="hlt">sea</span> <span class="hlt">ice</span> phytoplankton bloom in Arctic, while seldom reports studied about Antarctic. Here, lab experiment showed <span class="hlt">sea</span> <span class="hlt">ice</span> increased the visible light albedo of the water leaving radiance. Even a new formed <span class="hlt">sea</span> <span class="hlt">ice</span> of 10cm thickness increased water leaving radiance up to 4 times of its original bare water. Given that phytoplankton preferred growing and accumulating under the <span class="hlt">sea</span> <span class="hlt">ice</span> with thickness of 10cm-1m, our results showed that the changing rate of OC4 estimated [Chl-a] varied from 0.01-0.5mg/m3 to 0.2-0.3mg/m3, if the water covered by 10cm <span class="hlt">sea</span> <span class="hlt">ice</span>. Going further, varying thickness of <span class="hlt">sea</span> <span class="hlt">ice</span> modulated the changing rate of estimating [Chl-a] non-linearly, thus current routine OC4 model cannot estimate under <span class="hlt">sea</span> <span class="hlt">ice</span> [Chl-a] appropriately. Besides, marginal <span class="hlt">sea</span> <span class="hlt">ice</span> zone has a large amount of mixture regions containing <span class="hlt">sea</span> <span class="hlt">ice</span>, water and snow, where is favorable for phytoplankton. We applied 6S model to estimate the <span class="hlt">sea</span> <span class="hlt">ice</span>/snow contamination on sub-pixel water leaving radiance of 4.25km spatial resolution ocean color products. Results showed that <span class="hlt">sea</span> <span class="hlt">ice</span>/snow scale effectiveness overestimated [Chl-a] concentration based on routine band ratio OC4 model, which contamination increased with the rising fraction of <span class="hlt">sea</span> <span class="hlt">ice</span>/snow within one pixel. Finally, we analyzed the under <span class="hlt">sea</span> <span class="hlt">ice</span> bloom in Antarctica based on the [Chl-a] concentration trends during 21 days after <span class="hlt">sea</span> <span class="hlt">ice</span> retreating. Regardless of those overestimation caused by <span class="hlt">sea</span> <span class="hlt">ice</span>/snow sub scale contamination, we still did not see significant under <span class="hlt">sea</span> <span class="hlt">ice</span> blooms in Antarctica in 2012-2017 compared with Arctic. This research found that Southern Ocean is not favorable for under <span class="hlt">sea</span> <span class="hlt">ice</span> blooms and the phytoplankton bloom preferred to occur in at least 3 weeks after <span class="hlt">sea</span> <span class="hlt">ice</span> retreating.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C21E..06L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C21E..06L"><span>Atmospheric forcing of <span class="hlt">sea</span> <span class="hlt">ice</span> leads in the Beaufort <span class="hlt">Sea</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lewis, B. J.; Hutchings, J.; Mahoney, A. R.; Shapiro, L. H.</p> <p>2016-12-01</p> <p>Leads in <span class="hlt">sea</span> <span class="hlt">ice</span> play an important role in the polar marine environment where they allow heat and moisture transfer between the oceans and atmosphere and act as travel pathways for both marine mammals and ships. Examining AVHRR thermal imagery of the Beaufort <span class="hlt">Sea</span>, collected between 1994 and 2010, <span class="hlt">sea</span> <span class="hlt">ice</span> leads appear in repeating patterns and locations (Eicken et al 2005). The leads, resolved by AVHRR, are at least 250m wide (Mahoney et al 2012), thus the patterns described are for lead systems that extend up to hundreds of kilometers across the Beaufort <span class="hlt">Sea</span>. We describe how these patterns are associated with the location of weather systems relative to the coastline. Mean <span class="hlt">sea</span> level pressure and 10m wind fields from ECMWF ERA-Interim reanalysis are used to identify if particular lead patterns can be uniquely forecast based on the location of weather systems. <span class="hlt">Ice</span> drift data from the NSIDC's Polar Pathfinder Daily 25km EASE-Grid <span class="hlt">Sea</span> <span class="hlt">Ice</span> Motion Vectors indicates the role shear along leads has on the motion of <span class="hlt">ice</span> in the Beaufort Gyre. Lead formation is driven by 4 main factors: (i) coastal features such as promontories and islands influence the origin of leads by concentrating stresses within the <span class="hlt">ice</span> pack; (ii) direction of the wind forcing on the <span class="hlt">ice</span> pack determines the type of fracture, (iii) the location of the anticyclone (or cyclone) center determines the length of the fracture for certain patterns; and (iv) duration of weather conditions affects the width of the <span class="hlt">ice</span> fracture zones. Movement of the <span class="hlt">ice</span> pack on the leeward side of leads originating at promontories and islands increases, creating shear zones that control <span class="hlt">ice</span> transport along the Alaska coast in winter. . Understanding how atmospheric conditions influence the large-scale motion of the <span class="hlt">ice</span> pack is needed to design models that predict variability of the gyre and export of multi-year <span class="hlt">ice</span> to lower latitudes.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014ESSD....6..367L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014ESSD....6..367L"><span><span class="hlt">Sea</span> <span class="hlt">ice</span> in the Baltic <span class="hlt">Sea</span> - revisiting BASIS <span class="hlt">ice</span>, a historical data set covering the period 1960/1961-1978/1979</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Löptien, U.; Dietze, H.</p> <p>2014-12-01</p> <p>The Baltic <span class="hlt">Sea</span> is a seasonally <span class="hlt">ice</span>-covered, marginal <span class="hlt">sea</span> in central northern Europe. It is an essential waterway connecting highly industrialised countries. Because ship traffic is intermittently hindered by <span class="hlt">sea</span> <span class="hlt">ice</span>, the local weather services have been monitoring <span class="hlt">sea</span> <span class="hlt">ice</span> conditions for decades. In the present study we revisit a historical monitoring data set, covering the winters 1960/1961 to 1978/1979. This data set, dubbed Data Bank for Baltic <span class="hlt">Sea</span> <span class="hlt">Ice</span> and <span class="hlt">Sea</span> Surface Temperatures (BASIS) <span class="hlt">ice</span>, is based on hand-drawn maps that were collected and then digitised in 1981 in a joint project of the Finnish Institute of Marine Research (today the Finnish Meteorological Institute (FMI)) and the Swedish Meteorological and Hydrological Institute (SMHI). BASIS <span class="hlt">ice</span> was designed for storage on punch cards and all <span class="hlt">ice</span> information is encoded by five digits. This makes the data hard to access. Here we present a post-processed product based on the original five-digit code. Specifically, we convert to standard <span class="hlt">ice</span> quantities (including information on <span class="hlt">ice</span> types), which we distribute in the current and free Network Common Data Format (NetCDF). Our post-processed data set will help to assess numerical <span class="hlt">ice</span> models and provide easy-to-access unique historical reference material for <span class="hlt">sea</span> <span class="hlt">ice</span> in the Baltic <span class="hlt">Sea</span>. In addition we provide statistics showcasing the data quality. The website http://www.baltic-ocean.org hosts the post-processed data and the conversion code. The data are also archived at the Data Publisher for Earth & Environmental Science, PANGAEA (doi:10.1594/PANGAEA.832353).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-GSFC_20171208_Archive_e000837.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-GSFC_20171208_Archive_e000837.html"><span><span class="hlt">Sea</span> <span class="hlt">ice</span> around Ostrov Sakhalin, eastern Russia</span></a></p> <p><a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a></p> <p></p> <p>2017-12-08</p> <p>Located off the east coast of Russia, the <span class="hlt">Sea</span> of Okhotsk stretches down to 45 degrees North latitude, and <span class="hlt">sea</span> <span class="hlt">ice</span> forms regularly in the basin. In fact, it is the lowest latitude for seasonal <span class="hlt">sea</span> <span class="hlt">ice</span> formation in the world. On January 4, 2015, the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite captured this true-color image of the <span class="hlt">ice</span>-covered <span class="hlt">Sea</span> of Okhotsk. Every winter, winds from East Siberia, frigid air temperatures, and a large amount of freshwater flowing out from rivers promote the formation of <span class="hlt">sea</span> <span class="hlt">ice</span> in the region. Much of the freshwater comes from the Amur River, one of the ten longest rivers in the world. From year to year, variations in temperature and wind speed can cause large fluctuations in <span class="hlt">sea</span> <span class="hlt">ice</span> extent. The <span class="hlt">sea</span> spans more than 1,500,000 square kilometers (600,000 square miles), and <span class="hlt">ice</span> cover can spread across 50 to 90 percent of it at its annual peak. On average, that <span class="hlt">ice</span> persists for 180 days. According to research published in 2014, the region's <span class="hlt">sea</span> <span class="hlt">ice</span> has been decreasing over a 34-year period. Annual <span class="hlt">ice</span> production in the <span class="hlt">Sea</span> of Okhotsk dropped by more than 11 percent from 1974 to 2008. The researchers suggest that this decline has, at least in part, "led to weakening of the overturning in the North Pacific." Water with less <span class="hlt">sea</span> <span class="hlt">ice</span> is fresher, less dense, and unable to sink and circulate as well as salty, dense water. A weakened circulation in the North Pacific has implications for the supply of nutrients, such as iron, that affect biological productivity. Credit: NASA/GSFC/Jeff Schmaltz/MODIS Land Rapid Response Team NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20170005812&hterms=sea&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dsea','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20170005812&hterms=sea&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dsea"><span>Bellingshausen <span class="hlt">Sea</span> <span class="hlt">Ice</span> Extent Recorded in an Antarctic Peninsula <span class="hlt">Ice</span> Core</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Porter, Stacy E.; Parkinson, Claire L.; Mosley-Thompson, Ellen</p> <p>2016-01-01</p> <p>Annual net accumulation (A(sub n)) from the Bruce Plateau (BP) <span class="hlt">ice</span> core retrieved from the Antarctic Peninsula exhibits a notable relationship with <span class="hlt">sea</span> <span class="hlt">ice</span> extent (SIE) in the Bellingshausen <span class="hlt">Sea</span>. Over the satellite era, both BP A(sub n) and Bellingshausen SIE are influenced by large-scale climatic factors such as the Amundsen <span class="hlt">Sea</span> Low, Southern Annular Mode, and Southern Oscillation. In addition to the direct response of BP A(sub n) to Bellingshausen SIE (e.g., more open water as a moisture source), these large-scale climate phenomena also link the BP and the Bellingshausen <span class="hlt">Sea</span> indirectly such that they exhibit similar responses (e.g., northerly wind anomalies advect warm, moist air to the Antarctic Peninsula and neighboring Bellingshausen <span class="hlt">Sea</span>, which reduces SIE and increases A(sub n)). Comparison with a time series of fast <span class="hlt">ice</span> at South Orkney Islands reveals a relationship between BP A(sub n) and <span class="hlt">sea</span> <span class="hlt">ice</span> in the northern Weddell <span class="hlt">Sea</span> that is relatively consistent over the twentieth century, except when it is modulated by atmospheric wave patterns described by the Trans-Polar Index. The trend of increasing accumulation on the Bruce Plateau since approximately 1970 agrees with other climate records and reconstructions in the region and suggests that the current rate of <span class="hlt">sea</span> <span class="hlt">ice</span> loss in the Bellingshausen <span class="hlt">Sea</span> is unrivaled in the twentieth century.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017TCry...11..267D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017TCry...11..267D"><span>Atmospheric forcing of <span class="hlt">sea</span> <span class="hlt">ice</span> anomalies in the Ross <span class="hlt">Sea</span> polynya region</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dale, Ethan R.; McDonald, Adrian J.; Coggins, Jack H. J.; Rack, Wolfgang</p> <p>2017-01-01</p> <p>We investigate the impacts of strong wind events on the <span class="hlt">sea</span> <span class="hlt">ice</span> concentration within the Ross <span class="hlt">Sea</span> polynya (RSP), which may have consequences on <span class="hlt">sea</span> <span class="hlt">ice</span> formation. Bootstrap <span class="hlt">sea</span> <span class="hlt">ice</span> concentration (SIC) measurements derived from satellite SSM/I brightness temperatures are correlated with surface winds and temperatures from Ross <span class="hlt">Ice</span> Shelf automatic weather stations (AWSs) and weather models (ERA-Interim). Daily data in the austral winter period were used to classify characteristic weather regimes based on the percentiles of wind speed. For each regime a composite of a SIC anomaly was formed for the entire Ross <span class="hlt">Sea</span> region and we found that persistent weak winds near the edge of the Ross <span class="hlt">Ice</span> Shelf are generally associated with positive SIC anomalies in the Ross <span class="hlt">Sea</span> polynya and vice versa. By analyzing <span class="hlt">sea</span> <span class="hlt">ice</span> motion vectors derived from the SSM/I brightness temperatures we find significant <span class="hlt">sea</span> <span class="hlt">ice</span> motion anomalies throughout the Ross <span class="hlt">Sea</span> during strong wind events, which persist for several days after a strong wind event has ended. Strong, negative correlations are found between SIC and AWS wind speed within the RSP indicating that strong winds cause significant advection of <span class="hlt">sea</span> <span class="hlt">ice</span> in the region. We were able to partially recreate these correlations using colocated, modeled ERA-Interim wind speeds. However, large AWS and model differences are observed in the vicinity of Ross Island, where ERA-Interim underestimates wind speeds by a factor of 1.7 resulting in a significant misrepresentation of RSP processes in this area based on model data. Thus, the cross-correlation functions produced by compositing based on ERA-Interim wind speeds differed significantly from those produced with AWS wind speeds. In general the rapid decrease in SIC during a strong wind event is followed by a more gradual recovery in SIC. The SIC recovery continues over a time period greater than the average persistence of strong wind events and <span class="hlt">sea</span> <span class="hlt">ice</span> motion anomalies. This suggests that <span class="hlt">sea</span> <span class="hlt">ice</span></p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C41B0701R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C41B0701R"><span>The Relationship Between Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> Albedo and the Geophysical Parameters of the <span class="hlt">Ice</span> Cover</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Riihelä, A.</p> <p>2015-12-01</p> <p>The Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> cover is thinning and retreating. Remote sensing observations have also shown that the mean albedo of the remaining <span class="hlt">ice</span> cover is decreasing on decadal time scales, albeit with significant annual variability (Riihelä et al., 2013, Pistone et al., 2014). Attribution of the albedo decrease between its different drivers, such as decreasing <span class="hlt">ice</span> concentration and enhanced surface melt of the <span class="hlt">ice</span>, remains an important research question for the forecasting of future conditions of the <span class="hlt">ice</span> cover. A necessary step towards this goal is understanding the relationships between Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> albedo and the geophysical parameters of the <span class="hlt">ice</span> cover. Particularly the question of the relationship between <span class="hlt">sea</span> <span class="hlt">ice</span> albedo and <span class="hlt">ice</span> age is both interesting and not widely studied. The recent changes in the Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> zone have led to a substantial decrease of its multi-year <span class="hlt">sea</span> <span class="hlt">ice</span>, as old <span class="hlt">ice</span> melts and is replaced by first-year <span class="hlt">ice</span> during the next freezing season. It is generally known that younger <span class="hlt">sea</span> <span class="hlt">ice</span> tends to have a lower albedo than older <span class="hlt">ice</span> because of several reasons, such as wetter snow cover and enhanced melt ponding. However, the quantitative correlation between <span class="hlt">sea</span> <span class="hlt">ice</span> age and <span class="hlt">sea</span> <span class="hlt">ice</span> albedo has not been extensively studied to date, excepting in-situ measurement based studies which are, by necessity, focused on a limited area of the Arctic Ocean (Perovich and Polashenski, 2012).In this study, I analyze the dependencies of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> albedo relative to the geophysical parameters of the <span class="hlt">ice</span> field. I use remote sensing datasets such as the CM SAF CLARA-A1 (Karlsson et al., 2013) and the NASA MeaSUREs (Anderson et al., 2014) as data sources for the analysis. The studied period is 1982-2009. The datasets are spatiotemporally collocated and analysed. The changes in <span class="hlt">sea</span> <span class="hlt">ice</span> albedo as a function of <span class="hlt">sea</span> <span class="hlt">ice</span> age are presented for the whole Arctic Ocean and for potentially interesting marginal <span class="hlt">sea</span> cases. This allows us to see if the the albedo of the older <span class="hlt">sea</span></p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008GeoRL..35.8501D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008GeoRL..35.8501D"><span>Calcium carbonate as ikaite crystals in Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dieckmann, Gerhard S.; Nehrke, Gernot; Papadimitriou, Stathys; Göttlicher, Jörg; Steininger, Ralph; Kennedy, Hilary; Wolf-Gladrow, Dieter; Thomas, David N.</p> <p>2008-04-01</p> <p>We report on the discovery of the mineral ikaite (CaCO3.6H2O) in <span class="hlt">sea-ice</span> from the Southern Ocean. The precipitation of CaCO3 during the freezing of seawater has previously been predicted from thermodynamic modelling, indirect measurements, and has been documented in artificial <span class="hlt">sea</span> <span class="hlt">ice</span> during laboratory experiments but has not been reported for natural <span class="hlt">sea-ice</span>. It is assumed that CaCO3 formation in <span class="hlt">sea</span> <span class="hlt">ice</span> may be important for a <span class="hlt">sea</span> <span class="hlt">ice</span>-driven carbon pump in <span class="hlt">ice</span>-covered oceanic waters. Without direct evidence of CaCO3 precipitation in <span class="hlt">sea</span> <span class="hlt">ice</span>, its role in this and other processes has remained speculative. The discovery of CaCO3.6H2O crystals in natural <span class="hlt">sea</span> <span class="hlt">ice</span> provides the necessary evidence for the evaluation of previous assumptions and lays the foundation for further studies to help elucidate the role of ikaite in the carbon cycle of the seasonally <span class="hlt">sea</span> <span class="hlt">ice</span>-covered regions</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19940026115','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19940026115"><span>The role of <span class="hlt">sea</span> <span class="hlt">ice</span> dynamics in global climate change</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hibler, William D., III</p> <p>1992-01-01</p> <p>The topics covered include the following: general characteristics of <span class="hlt">sea</span> <span class="hlt">ice</span> drift; <span class="hlt">sea</span> <span class="hlt">ice</span> rheology; <span class="hlt">ice</span> thickness distribution; <span class="hlt">sea</span> <span class="hlt">ice</span> thermodynamic models; equilibrium thermodynamic models; effect of internal brine pockets and snow cover; model simulations of Arctic <span class="hlt">Sea</span> <span class="hlt">ice</span>; and sensitivity of <span class="hlt">sea</span> <span class="hlt">ice</span> models to climate change.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009EGUGA..11.4193S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009EGUGA..11.4193S"><span>Trend analysis of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> extent</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Silva, M. E.; Barbosa, S. M.; Antunes, Luís; Rocha, Conceição</p> <p>2009-04-01</p> <p>The extent of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> is a fundamental parameter of Arctic climate variability. In the context of climate change, the area covered by <span class="hlt">ice</span> in the Arctic is a particularly useful indicator of recent changes in the Arctic environment. Climate models are in near universal agreement that Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> extent will decline through the 21st century as a consequence of global warming and many studies predict a <span class="hlt">ice</span> free Arctic as soon as 2012. Time series of satellite passive microwave observations allow to assess the temporal changes in the extent of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span>. Much of the analysis of the <span class="hlt">ice</span> extent time series, as in most climate studies from observational data, have been focussed on the computation of deterministic linear trends by ordinary least squares. However, many different processes, including deterministic, unit root and long-range dependent processes can engender trend like features in a time series. Several parametric tests have been developed, mainly in econometrics, to discriminate between stationarity (no trend), deterministic trend and stochastic trends. Here, these tests are applied in the trend analysis of the <span class="hlt">sea</span> <span class="hlt">ice</span> extent time series available at National Snow and <span class="hlt">Ice</span> Data Center. The parametric stationary tests, Augmented Dickey-Fuller (ADF), Phillips-Perron (PP) and the KPSS, do not support an overall deterministic trend in the time series of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> extent. Therefore, alternative parametrizations such as long-range dependence should be considered for characterising long-term Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> variability.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C43B0754M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C43B0754M"><span>Coordinated Mapping of <span class="hlt">Sea</span> <span class="hlt">Ice</span> Deformation Features with Autonomous Vehicles</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Maksym, T.; Williams, G. D.; Singh, H.; Weissling, B.; Anderson, J.; Maki, T.; Ackley, S. F.</p> <p>2016-12-01</p> <p>Decreases in summer <span class="hlt">sea</span> <span class="hlt">ice</span> extent in the Beaufort and Chukchi <span class="hlt">Seas</span> has lead to a transition from a largely perennial <span class="hlt">ice</span> cover, to a seasonal <span class="hlt">ice</span> cover. This drives shifts in <span class="hlt">sea</span> <span class="hlt">ice</span> production, dynamics, <span class="hlt">ice</span> types, and thickness distribution. To examine how the processes driving <span class="hlt">ice</span> advance might also impact the morphology of the <span class="hlt">ice</span> cover, a coordinated <span class="hlt">ice</span> mapping effort was undertaken during a field campaign in the Beaufort <span class="hlt">Sea</span> in October, 2015. Here, we present observations of <span class="hlt">sea</span> <span class="hlt">ice</span> draft topography from six missions of an Autonomous Underwater Vehicle run under different <span class="hlt">ice</span> types and deformation features observed during autumn freeze-up. <span class="hlt">Ice</span> surface features were also mapped during coordinated drone photogrammetric missions over each site. We present preliminary results of a comparison between <span class="hlt">sea</span> <span class="hlt">ice</span> surface topography and <span class="hlt">ice</span> underside morphology for a range of sample <span class="hlt">ice</span> types, including hummocked multiyear <span class="hlt">ice</span>, rubble fields, young <span class="hlt">ice</span> ridges and rafts, and consolidated pancake <span class="hlt">ice</span>. These data are compared to prior observations of <span class="hlt">ice</span> morphological features from deformed Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span>. Such data will be useful for improving parameterizations of <span class="hlt">sea</span> <span class="hlt">ice</span> redistribution during deformation, and for better constraining estimates of airborne or satellite <span class="hlt">sea</span> <span class="hlt">ice</span> thickness.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li class="active"><span>7</span></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_7 --> <div id="page_8" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li class="active"><span>8</span></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="141"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C53D..01N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C53D..01N"><span>Examining Differences in Arctic and Antarctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> Change</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Nghiem, S. V.; Rigor, I. G.; Clemente-Colon, P.; Neumann, G.; Li, P.</p> <p>2015-12-01</p> <p>The paradox of the rapid reduction of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> versus the stability (or slight increase) of Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> remains a challenge in the cryospheric science research community. Here we start by reviewing a number of explanations that have been suggested by different researchers and authors. One suggestion is that stratospheric ozone depletion may affect atmospheric circulation and wind patterns such as the Southern Annular Mode, and thereby sustaining the Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> cover. The reduction of salinity and density in the near-surface layer may weaken the convective mixing of cold and warmer waters, and thus maintaining regions of no warming around the Antarctic. A decrease in <span class="hlt">sea</span> <span class="hlt">ice</span> growth may reduce salt rejection and upper-ocean density to enhance thermohalocline stratification, and thus supporting Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> production. Melt water from Antarctic <span class="hlt">ice</span> shelves collects in a cool and fresh surface layer to shield the surface ocean from the warmer deeper waters, and thus leading to an expansion of Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span>. Also, wind effects may positively contribute to Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> growth. Moreover, Antarctica lacks of additional heat sources such as warm river discharge to melt <span class="hlt">sea</span> <span class="hlt">ice</span> as opposed to the case in the Arctic. Despite of these suggested explanations, factors that can consistently and persistently maintains the stability of <span class="hlt">sea</span> <span class="hlt">ice</span> still need to be identified for the Antarctic, which are opposed to factors that help accelerate <span class="hlt">sea</span> <span class="hlt">ice</span> loss in the Arctic. In this respect, using decadal observations from multiple satellite datasets, we examine differences in <span class="hlt">sea</span> <span class="hlt">ice</span> properties and distributions, together with dynamic and thermodynamic processes and interactions with land, ocean, and atmosphere, causing differences in Arctic and Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> change to contribute to resolving the Arctic-Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> paradox.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C21B1124W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C21B1124W"><span>Synthesis of User Needs for Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> Predictions</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wiggins, H. V.; Turner-Bogren, E. J.; Sheffield Guy, L.</p> <p>2017-12-01</p> <p>Forecasting Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> on sub-seasonal to seasonal scales in a changing Arctic is of interest to a diverse range of stakeholders. However, <span class="hlt">sea</span> <span class="hlt">ice</span> forecasting is still challenging due to high variability in weather and ocean conditions and limits to prediction capabilities; the science needs for observations and modeling are extensive. At a time of challenged science funding, one way to prioritize <span class="hlt">sea</span> <span class="hlt">ice</span> prediction efforts is to examine the information needs of various stakeholder groups. This poster will present a summary and synthesis of existing surveys, reports, and other literature that examines user needs for <span class="hlt">sea</span> <span class="hlt">ice</span> predictions. The synthesis will include lessons learned from the <span class="hlt">Sea</span> <span class="hlt">Ice</span> Prediction Network (a collaborative, multi-agency-funded project focused on seasonal Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> predictions), the <span class="hlt">Sea</span> <span class="hlt">Ice</span> for Walrus Outlook (a resource for Alaska Native subsistence hunters and coastal communities, that provides reports on weather and <span class="hlt">sea</span> <span class="hlt">ice</span> conditions), and other efforts. The poster will specifically compare the scales and variables of <span class="hlt">sea</span> <span class="hlt">ice</span> forecasts currently available, as compared to what information is requested by various user groups.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5179961','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5179961"><span>Linking scales in <span class="hlt">sea</span> <span class="hlt">ice</span> mechanics</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Weiss, Jérôme; Dansereau, Véronique</p> <p>2017-01-01</p> <p>Mechanics plays a key role in the evolution of the <span class="hlt">sea</span> <span class="hlt">ice</span> cover through its control on drift, on momentum and thermal energy exchanges between the polar oceans and the atmosphere along cracks and faults, and on <span class="hlt">ice</span> thickness distribution through opening and ridging processes. At the local scale, a significant variability of the mechanical strength is associated with the microstructural heterogeneity of saline <span class="hlt">ice</span>, however characterized by a small correlation length, below the <span class="hlt">ice</span> thickness scale. Conversely, the <span class="hlt">sea</span> <span class="hlt">ice</span> mechanical fields (velocity, strain and stress) are characterized by long-ranged (more than 1000 km) and long-lasting (approx. few months) correlations. The associated space and time scaling laws are the signature of the brittle character of <span class="hlt">sea</span> <span class="hlt">ice</span> mechanics, with deformation resulting from a multi-scale accumulation of episodic fracturing and faulting events. To translate the short-range-correlated disorder on strength into long-range-correlated mechanical fields, several key ingredients are identified: long-ranged elastic interactions, slow driving conditions, a slow viscous-like relaxation of elastic stresses and a restoring/healing mechanism. These ingredients constrained the development of a new continuum mechanics modelling framework for the <span class="hlt">sea</span> <span class="hlt">ice</span> cover, called Maxwell–elasto-brittle. Idealized simulations without advection demonstrate that this rheological framework reproduces the main characteristics of <span class="hlt">sea</span> <span class="hlt">ice</span> mechanics, including anisotropy, spatial localization and intermittency, as well as the associated scaling laws. This article is part of the themed issue ‘Microdynamics of ice’. PMID:28025300</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://eric.ed.gov/?q=kelp&id=EJ335092','ERIC'); return false;" href="https://eric.ed.gov/?q=kelp&id=EJ335092"><span><span class="hlt">Sea</span> <span class="hlt">Ice</span> and Oceanographic Conditions.</span></a></p> <p><a target="_blank" href="http://www.eric.ed.gov/ERICWebPortal/search/extended.jsp?_pageLabel=advanced">ERIC Educational Resources Information Center</a></p> <p>Oceanus, 1986</p> <p>1986-01-01</p> <p>The coastal waters of the Beaufort <span class="hlt">Sea</span> are covered with <span class="hlt">ice</span> three-fourths of the year. These waters (during winter) are discussed by considering: consolidation of coastal <span class="hlt">ice</span>; under-<span class="hlt">ice</span> water; brine circulation; biological energy; life under the <span class="hlt">ice</span> (including kelp and larger animals); food chains; and <span class="hlt">ice</span> break-up. (JN)</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016PolSc..10..323Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016PolSc..10..323Y"><span>Mapping of the air-<span class="hlt">sea</span> CO2 flux in the Arctic Ocean and its <span class="hlt">adjacent</span> <span class="hlt">seas</span>: Basin-wide distribution and seasonal to interannual variability</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Yasunaka, Sayaka; Murata, Akihiko; Watanabe, Eiji; Chierici, Melissa; Fransson, Agneta; van Heuven, Steven; Hoppema, Mario; Ishii, Masao; Johannessen, Truls; Kosugi, Naohiro; Lauvset, Siv K.; Mathis, Jeremy T.; Nishino, Shigeto; Omar, Abdirahman M.; Olsen, Are; Sasano, Daisuke; Takahashi, Taro; Wanninkhof, Rik</p> <p>2016-09-01</p> <p>We produced 204 monthly maps of the air-<span class="hlt">sea</span> CO2 flux in the Arctic north of 60°N, including the Arctic Ocean and its <span class="hlt">adjacent</span> <span class="hlt">seas</span>, from January 1997 to December 2013 by using a self-organizing map technique. The partial pressure of CO2 (pCO2) in surface water data were obtained by shipboard underway measurements or calculated from alkalinity and total inorganic carbon of surface water samples. Subsequently, we investigated the basin-wide distribution and seasonal to interannual variability of the CO2 fluxes. The 17-year annual mean CO2 flux shows that all areas of the Arctic Ocean and its <span class="hlt">adjacent</span> <span class="hlt">seas</span> were net CO2 sinks. The estimated annual CO2 uptake by the Arctic Ocean was 180 TgC yr-1. The CO2 influx was strongest in winter in the Greenland/Norwegian <span class="hlt">Seas</span> (>15 mmol m-2 day-1) and the Barents <span class="hlt">Sea</span> (>12 mmol m-2 day-1) because of strong winds, and strongest in summer in the Chukchi <span class="hlt">Sea</span> (∼10 mmol m-2 day-1) because of the <span class="hlt">sea-ice</span> retreat. In recent years, the CO2 uptake has increased in the Greenland/Norwegian <span class="hlt">Sea</span> and decreased in the southern Barents <span class="hlt">Sea</span>, owing to increased and decreased air-<span class="hlt">sea</span> pCO2 differences, respectively.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUFM.U13C0068D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUFM.U13C0068D"><span>Reemergence of <span class="hlt">sea</span> <span class="hlt">ice</span> cover anomalies and the role of the <span class="hlt">sea</span> <span class="hlt">ice</span>-albedo feedback in CCSM simulations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Deweaver, E. T.</p> <p>2008-12-01</p> <p>The dramatic <span class="hlt">sea</span> <span class="hlt">ice</span> decline of 2007 and lack of recovery in 2008 raise the question of a "tipping point" for Arctic <span class="hlt">sea</span> <span class="hlt">ice</span>, beyond which the transition to a seasonal <span class="hlt">sea</span> <span class="hlt">ice</span> state becomes abrupt and irreversible. The tipping point is essentially a "memory catastrophe", in which a dramatic loss of <span class="hlt">sea</span> <span class="hlt">ice</span> in one summer is "remembered" in reduced <span class="hlt">ice</span> thickness over the winter season and leads to a comparably dramatic loss the following summer. The dominant contributor to this memory is presumably the <span class="hlt">sea</span> <span class="hlt">ice</span> - albedo feedback (SIAF), in which excess insolation absorbed due to low summer <span class="hlt">ice</span> cover leads to a shorter <span class="hlt">ice</span> growth season and hence thinner <span class="hlt">ice</span>. While these dynamics are clearly important, they are difficult to quantify given the lack of long-term observations in the Arctic and the suddenness of the recent loss. Alternatively, we attempt to quantify the contribution of the SIAF to the year-to-year memory of <span class="hlt">sea</span> <span class="hlt">ice</span> cover anomalies in simulations of the NCAR Community Climate System Model (CCSM) under 20th century conditions. Lagged autocorrelation plots of <span class="hlt">sea</span> <span class="hlt">ice</span> area anomalies show that anomalies in one year tend to "reemerge" in the following year. Further experiments using a slab ocean model (SOM) are used to assess the contribution of oceanic processes to the year-to-year reemergence. This contribution is substantial, particularly in the winter season, and includes memory due to the standard mixed layer reemergence mechanism and low-frequency ocean heat transport anomalies. The contribution of the SIAF to persistence in the SOM experiment is determined through additional experiments in which the SIAF is disabled by fixing surface albedo to its climatological value regardless of <span class="hlt">sea</span> <span class="hlt">ice</span> concentration anomalies. SIAF causes a 50% increase in the magnitude of the anomalies but a relatively small increase in their persistence. Persistence is not dramatically increased because the enhancement of shortwave flux anomalies by SIAF is compensated by stronger</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-GSFC_20171208_Archive_e001600.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-GSFC_20171208_Archive_e001600.html"><span>Iceberg trapped in <span class="hlt">sea</span> <span class="hlt">ice</span></span></a></p> <p><a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a></p> <p></p> <p>2012-11-01</p> <p>An iceberg trapped in <span class="hlt">sea</span> <span class="hlt">ice</span> in the Amundsen <span class="hlt">Sea</span>, seen from the <span class="hlt">Ice</span>Bridge DC-8 during the Getz 07 mission on Oct. 27. Credit: NASA / Maria-Jose Vinas NASA's Operation <span class="hlt">Ice</span>Bridge is an airborne science mission to study Earth's polar <span class="hlt">ice</span>. For more information about <span class="hlt">Ice</span>Bridge, visit: www.nasa.gov/icebridge NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.C11B..03P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.C11B..03P"><span>Airborne radar surveys of snow depth over Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> during Operation <span class="hlt">Ice</span>Bridge</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Panzer, B.; Gomez-Garcia, D.; Leuschen, C.; Paden, J. D.; Gogineni, P. S.</p> <p>2012-12-01</p> <p>Over the last decade, multiple satellite-based laser and radar altimeters, optimized for polar observations, have been launched with one of the major objectives being the determination of global <span class="hlt">sea</span> <span class="hlt">ice</span> thickness and distribution [5, 6]. Estimation of <span class="hlt">sea-ice</span> thickness from these altimeters relies on freeboard measurements and the presence of snow cover on <span class="hlt">sea</span> <span class="hlt">ice</span> affects this estimate. Current means of estimating the snow depth rely on daily precipitation products and/or data from passive microwave sensors [2, 7]. Even a small uncertainty in the snow depth leads to a large uncertainty in the <span class="hlt">sea-ice</span> thickness estimate. To improve the accuracy of the <span class="hlt">sea-ice</span> thickness estimates and provide validation for measurements from satellite-based sensors, the Center for Remote Sensing of <span class="hlt">Ice</span> Sheets deploys the Snow Radar as a part of NASA Operation <span class="hlt">Ice</span>Bridge. The Snow Radar is an ultra-wideband, frequency-modulated, continuous-wave radar capable of resolving snow depth on <span class="hlt">sea</span> <span class="hlt">ice</span> from 5 cm to more than 2 meters from long-range, airborne platforms [4]. This paper will discuss the algorithm used to directly extract snow depth estimates exclusively using the Snow Radar data set by tracking both the air-snow and snow-<span class="hlt">ice</span> interfaces. Prior work in this regard used data from a laser altimeter for tracking the air-snow interface or worked under the assumption that the return from the snow-<span class="hlt">ice</span> interface was greater than that from the air-snow interface due to a larger dielectric contrast, which is not true for thick or higher loss snow cover [1, 3]. This paper will also present snow depth estimates from Snow Radar data during the NASA Operation <span class="hlt">Ice</span>Bridge 2010-2011 Antarctic campaigns. In 2010, three <span class="hlt">sea</span> <span class="hlt">ice</span> flights were flown, two in the Weddell <span class="hlt">Sea</span> and one in the Amundsen and Bellingshausen <span class="hlt">Seas</span>. All three flight lines were repeated in 2011, allowing an annual comparison of snow depth. In 2011, a repeat pass of an earlier flight in the Weddell <span class="hlt">Sea</span> was flown, allowing for a</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014ESSDD...7..419L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014ESSDD...7..419L"><span><span class="hlt">Sea</span> <span class="hlt">ice</span> in the Baltic <span class="hlt">Sea</span> - revisiting BASIS <span class="hlt">ice</span>, a~historical data set covering the period 1960/1961-1978/1979</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Löptien, U.; Dietze, H.</p> <p>2014-06-01</p> <p>The Baltic <span class="hlt">Sea</span> is a seasonally <span class="hlt">ice</span>-covered, marginal <span class="hlt">sea</span>, situated in central northern Europe. It is an essential waterway connecting highly industrialised countries. Because ship traffic is intermittently hindered by <span class="hlt">sea</span> <span class="hlt">ice</span>, the local weather services have been monitoring <span class="hlt">sea</span> <span class="hlt">ice</span> conditions for decades. In the present study we revisit a historical monitoring data set, covering the winters 1960/1961. This data set, dubbed Data Bank for Baltic <span class="hlt">Sea</span> <span class="hlt">Ice</span> and <span class="hlt">Sea</span> Surface Temperatures (BASIS) <span class="hlt">ice</span>, is based on hand-drawn maps that were collected and then digitised 1981 in a joint project of the Finnish Institute of Marine Research (today Finish Meteorological Institute (FMI)) and the Swedish Meteorological and Hydrological Institute (SMHI). BASIS <span class="hlt">ice</span> was designed for storage on punch cards and all <span class="hlt">ice</span> information is encoded by five digits. This makes the data hard to access. Here we present a post-processed product based on the original five-digit code. Specifically, we convert to standard <span class="hlt">ice</span> quantities (including information on <span class="hlt">ice</span> types), which we distribute in the current and free Network Common Data Format (NetCDF). Our post-processed data set will help to assess numerical <span class="hlt">ice</span> models and provide easy-to-access unique historical reference material for <span class="hlt">sea</span> <span class="hlt">ice</span> in the Baltic <span class="hlt">Sea</span>. In addition we provide statistics showcasing the data quality. The website <a href="www.baltic-ocean.org"target="_blank">www.baltic-ocean.org<a/> hosts the post-prossed data and the conversion code. The data are also archived at the Data Publisher for Earth & Environmental Science PANGEA (<a href="http://dx.doi.org/"target="_blank">doi:10.1594/PANGEA.832353<a/>).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/22715789','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/22715789"><span>[Spectral features analysis of <span class="hlt">sea</span> <span class="hlt">ice</span> in the Arctic Ocean].</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Ke, Chang-qing; Xie, Hong-jie; Lei, Rui-bo; Li, Qun; Sun, Bo</p> <p>2012-04-01</p> <p><span class="hlt">Sea</span> <span class="hlt">ice</span> in the Arctic Ocean plays an important role in the global climate change, and its quick change and impact are the scientists' focus all over the world. The spectra of different kinds of <span class="hlt">sea</span> <span class="hlt">ice</span> were measured with portable ASD FieldSpec 3 spectrometer during the long-term <span class="hlt">ice</span> station of the 4th Chinese national Arctic Expedition in 2010, and the spectral features were analyzed systematically. The results indicated that the reflectance of <span class="hlt">sea</span> <span class="hlt">ice</span> covered by snow is the highest one, naked <span class="hlt">sea</span> <span class="hlt">ice</span> the second, and melted <span class="hlt">sea</span> <span class="hlt">ice</span> the lowest. Peak and valley characteristics of spectrum curves of <span class="hlt">sea</span> <span class="hlt">ice</span> covered by thick snow, thin snow, wet snow and snow crystal are very significant, and the reflectance basically decreases with the wavelength increasing. The rules of reflectance change with wavelength of natural <span class="hlt">sea</span> <span class="hlt">ice</span>, white <span class="hlt">ice</span> and blue <span class="hlt">ice</span> are basically same, the reflectance of them is medium, and that of grey <span class="hlt">ice</span> is far lower than natural <span class="hlt">sea</span> <span class="hlt">ice</span>, white <span class="hlt">ice</span> and blue <span class="hlt">ice</span>. It is very significant for scientific research to analyze the spectral features of <span class="hlt">sea</span> <span class="hlt">ice</span> in the Arctic Ocean and to implement the quantitative remote sensing of <span class="hlt">sea</span> <span class="hlt">ice</span>, and to further analyze its response to the global warming.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.C41D0434C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.C41D0434C"><span><span class="hlt">Ice</span> Sheet and <span class="hlt">Sea</span> <span class="hlt">Ice</span> Observations from Unmanned Aircraft Systems</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Crocker, R. I.; Maslanik, J. A.</p> <p>2011-12-01</p> <p>A suite of sensors has been assembled to map <span class="hlt">ice</span> sheet and <span class="hlt">sea</span> <span class="hlt">ice</span> surface topography with fine-resolution from small unmanned aircraft systems (UAS). This payload is optimized to provide coincident surface elevation and imagery data, and with its low cost and ease of reproduction, it has the potential to become a widely-distributed observational resource to complement polar manned-aircraft and satellite missions. To date, it has been deployed to map <span class="hlt">ice</span> sheet elevations near Jakobshavn Isbræ in Greenland, and to measure <span class="hlt">sea</span> <span class="hlt">ice</span> freeboard and roughness in Fram Strait off the coast of Svalbard. Data collected during these campaigns have facilitate a detailed assessment of the system's surface elevation measurement accuracy, and provide a glimpse of the summer 2009 Fram Strait <span class="hlt">sea</span> <span class="hlt">ice</span> conditions. These findings are presented, along with a brief overview of our future Arctic UAS operations.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016ESASP.739E..42Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016ESASP.739E..42Z"><span>Techniques for <span class="hlt">Sea</span> <span class="hlt">Ice</span> Characteristics Extraction and <span class="hlt">Sea</span> <span class="hlt">Ice</span> Monitoring Using Multi-Sensor Satellite Data in the Bohai <span class="hlt">Sea</span>-Dragon 3 Programme Final Report (2012-2016)</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhang, Xi; Zhang, Jie; Meng, Junmin</p> <p>2016-08-01</p> <p>The objectives of Dragon-3 programme (ID: 10501) are to develop methods for classification <span class="hlt">sea</span> <span class="hlt">ice</span> types and retrieving <span class="hlt">ice</span> thickness based on multi-sensor data. In this final results paper, we give a briefly introduction for our research work and mainly results. Key words: the Bohai <span class="hlt">Sea</span> <span class="hlt">ice</span>, <span class="hlt">Sea</span> <span class="hlt">ice</span>, optical and</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110015207','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110015207"><span>Regional Changes in the <span class="hlt">Sea</span> <span class="hlt">Ice</span> Cover and <span class="hlt">Ice</span> Production in the Antarctic</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Comiso, Josefino C.</p> <p>2011-01-01</p> <p>Coastal polynyas around the Antarctic continent have been regarded as <span class="hlt">sea</span> <span class="hlt">ice</span> factories because of high <span class="hlt">ice</span> production rates in these regions. The observation of a positive trend in the extent of Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> during the satellite era has been intriguing in light of the observed rapid decline of the <span class="hlt">ice</span> extent in the Arctic. The results of analysis of the time series of passive microwave data indicate large regional variability with the trends being strongly positive in the Ross <span class="hlt">Sea</span>, strongly negative in the Bellingshausen/Amundsen <span class="hlt">Seas</span> and close to zero in the other regions. The atmospheric circulation in the Antarctic is controlled mainly by the Southern Annular Mode (SAM) and the marginal <span class="hlt">ice</span> zone around the continent shows an alternating pattern of advance and retreat suggesting the presence of a propagating wave (called Antarctic Circumpolar Wave) around the circumpolar region. The results of analysis of the passive microwave data suggest that the positive trend in the Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> cover could be caused primarily by enhanced <span class="hlt">ice</span> production in the Ross <span class="hlt">Sea</span> that may be associated with more persistent and larger coastal polynyas in the region. Over the Ross <span class="hlt">Sea</span> shelf, analysis of <span class="hlt">sea</span> <span class="hlt">ice</span> drift data from 1992 to 2008 yields a positive rate-of-increase in the net <span class="hlt">ice</span> export of about 30,000 km2 per year. For a characteristic <span class="hlt">ice</span> thickness of 0.6 m, this yields a volume transport of about 20 km3/year, which is almost identical, within error bars, to our estimate of the trend in <span class="hlt">ice</span> production. In addition to the possibility of changes in SAM, modeling studies have also indicated that the ozone hole may have a role in that it causes the deepening of the lows in the western Antarctic region thereby causing strong winds to occur offthe Ross-<span class="hlt">ice</span> shelf.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015JGRC..120..647F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015JGRC..120..647F"><span>The refreezing of melt ponds on Arctic <span class="hlt">sea</span> <span class="hlt">ice</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Flocco, Daniela; Feltham, Daniel L.; Bailey, Eleanor; Schroeder, David</p> <p>2015-02-01</p> <p>The presence of melt ponds on the surface of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> significantly reduces its albedo, inducing a positive feedback leading to <span class="hlt">sea</span> <span class="hlt">ice</span> thinning. While the role of melt ponds in enhancing the summer melt of <span class="hlt">sea</span> <span class="hlt">ice</span> is well known, their impact on suppressing winter freezing of <span class="hlt">sea</span> <span class="hlt">ice</span> has, hitherto, received less attention. Melt ponds freeze by forming an <span class="hlt">ice</span> lid at the upper surface, which insulates them from the atmosphere and traps pond water between the underlying <span class="hlt">sea</span> <span class="hlt">ice</span> and the <span class="hlt">ice</span> lid. The pond water is a store of latent heat, which is released during refreezing. Until a pond freezes completely, there can be minimal <span class="hlt">ice</span> growth at the base of the underlying <span class="hlt">sea</span> <span class="hlt">ice</span>. In this work, we present a model of the refreezing of a melt pond that includes the heat and salt balances in the <span class="hlt">ice</span> lid, trapped pond, and underlying <span class="hlt">sea</span> <span class="hlt">ice</span>. The model uses a two-stream radiation model to account for radiative scattering at phase boundaries. Simulations and related sensitivity studies suggest that trapped pond water may survive for over a month. We focus on the role that pond salinity has on delaying the refreezing process and retarding basal <span class="hlt">sea</span> <span class="hlt">ice</span> growth. We estimate that for a typical <span class="hlt">sea</span> <span class="hlt">ice</span> pond coverage in autumn, excluding the impact of trapped ponds in models overestimates <span class="hlt">ice</span> growth by up to 265 million km3, an overestimate of 26%.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008GMS...180.....D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008GMS...180.....D"><span>Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> Decline: Observations, Projections, Mechanisms, and Implications</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>DeWeaver, Eric T.; Bitz, Cecilia M.; Tremblay, L.-Bruno</p> <p></p> <p>This volume addresses the rapid decline of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span>, placing recent <span class="hlt">sea</span> <span class="hlt">ice</span> decline in the context of past observations, climate model simulations and projections, and simple models of the climate sensitivity of <span class="hlt">sea</span> <span class="hlt">ice</span>. Highlights of the work presented here include • An appraisal of the role played by wind forcing in driving the decline; • A reconstruction of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> conditions prior to human observations, based on proxy data from sediments; • A modeling approach for assessing the impact of <span class="hlt">sea</span> <span class="hlt">ice</span> decline on polar bears, used as input to the U.S. Fish and Wildlife Service's decision to list the polar bear as a threatened species under the Endangered Species Act; • Contrasting studies on the existence of a "tipping point," beyond which Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> decline will become (or has already become) irreversible, including an examination of the role of the small <span class="hlt">ice</span> cap instability in global warming simulations; • A significant summertime atmospheric response to <span class="hlt">sea</span> <span class="hlt">ice</span> reduction in an atmospheric general circulation model, suggesting a positive feedback and the potential for short-term climate prediction. The book will be of interest to researchers attempting to understand the recent behavior of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span>, model projections of future <span class="hlt">sea</span> <span class="hlt">ice</span> loss, and the consequences of <span class="hlt">sea</span> <span class="hlt">ice</span> loss for the natural and human systems of the Arctic.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24832800','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24832800"><span><span class="hlt">Sea</span> <span class="hlt">ice</span> microorganisms: environmental constraints and extracellular responses.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Ewert, Marcela; Deming, Jody W</p> <p>2013-03-28</p> <p>Inherent to <span class="hlt">sea</span> <span class="hlt">ice</span>, like other high latitude environments, is the strong seasonality driven by changes in insolation throughout the year. <span class="hlt">Sea-ice</span> organisms are exposed to shifting, sometimes limiting, conditions of temperature and salinity. An array of adaptations to survive these and other challenges has been acquired by those organisms that inhabit the <span class="hlt">ice</span>. One key adaptive response is the production of extracellular polymeric substances (EPS), which play multiple roles in the entrapment, retention and survival of microorganisms in <span class="hlt">sea</span> <span class="hlt">ice</span>. In this concept paper we consider two main areas of <span class="hlt">sea-ice</span> microbiology: the physico-chemical properties that define <span class="hlt">sea</span> <span class="hlt">ice</span> as a microbial habitat, imparting particular advantages and limits; and extracellular responses elicited in microbial inhabitants as they exploit or survive these conditions. Emphasis is placed on protective strategies used in the face of fluctuating and extreme environmental conditions in <span class="hlt">sea</span> <span class="hlt">ice</span>. Gaps in knowledge and testable hypotheses are identified for future research.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3960889','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3960889"><span><span class="hlt">Sea</span> <span class="hlt">Ice</span> Microorganisms: Environmental Constraints and Extracellular Responses</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Ewert, Marcela; Deming, Jody W.</p> <p>2013-01-01</p> <p>Inherent to <span class="hlt">sea</span> <span class="hlt">ice</span>, like other high latitude environments, is the strong seasonality driven by changes in insolation throughout the year. <span class="hlt">Sea-ice</span> organisms are exposed to shifting, sometimes limiting, conditions of temperature and salinity. An array of adaptations to survive these and other challenges has been acquired by those organisms that inhabit the <span class="hlt">ice</span>. One key adaptive response is the production of extracellular polymeric substances (EPS), which play multiple roles in the entrapment, retention and survival of microorganisms in <span class="hlt">sea</span> <span class="hlt">ice</span>. In this concept paper we consider two main areas of <span class="hlt">sea-ice</span> microbiology: the physico-chemical properties that define <span class="hlt">sea</span> <span class="hlt">ice</span> as a microbial habitat, imparting particular advantages and limits; and extracellular responses elicited in microbial inhabitants as they exploit or survive these conditions. Emphasis is placed on protective strategies used in the face of fluctuating and extreme environmental conditions in <span class="hlt">sea</span> <span class="hlt">ice</span>. Gaps in knowledge and testable hypotheses are identified for future research. PMID:24832800</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014TCry....8.1469R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014TCry....8.1469R"><span>Temporal dynamics of ikaite in experimental <span class="hlt">sea</span> <span class="hlt">ice</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Rysgaard, S.; Wang, F.; Galley, R. J.; Grimm, R.; Notz, D.; Lemes, M.; Geilfus, N.-X.; Chaulk, A.; Hare, A. A.; Crabeck, O.; Else, B. G. T.; Campbell, K.; Sørensen, L. L.; Sievers, J.; Papakyriakou, T.</p> <p>2014-08-01</p> <p>Ikaite (CaCO3 · 6H2O) is a metastable phase of calcium carbonate that normally forms in a cold environment and/or under high pressure. Recently, ikaite crystals have been found in <span class="hlt">sea</span> <span class="hlt">ice</span>, and it has been suggested that their precipitation may play an important role in air-<span class="hlt">sea</span> CO2 exchange in <span class="hlt">ice</span>-covered <span class="hlt">seas</span>. Little is known, however, of the spatial and temporal dynamics of ikaite in <span class="hlt">sea</span> <span class="hlt">ice</span>. Here we present evidence for highly dynamic ikaite precipitation and dissolution in <span class="hlt">sea</span> <span class="hlt">ice</span> grown at an outdoor pool of the <span class="hlt">Sea-ice</span> Environmental Research Facility (SERF) in Manitoba, Canada. During the experiment, ikaite precipitated in <span class="hlt">sea</span> <span class="hlt">ice</span> when temperatures were below -4 °C, creating three distinct zones of ikaite concentrations: (1) a millimeter-to-centimeter-thin surface layer containing frost flowers and brine skim with bulk ikaite concentrations of >2000 μmol kg-1, (2) an internal layer with ikaite concentrations of 200-400 μmol kg-1, and (3) a bottom layer with ikaite concentrations of <100 μmol kg-1. Snowfall events caused the <span class="hlt">sea</span> <span class="hlt">ice</span> to warm and ikaite crystals to dissolve. Manual removal of the snow cover allowed the <span class="hlt">sea</span> <span class="hlt">ice</span> to cool and brine salinities to increase, resulting in rapid ikaite precipitation. The observed ikaite concentrations were on the same order of magnitude as modeled by FREZCHEM, which further supports the notion that ikaite concentration in <span class="hlt">sea</span> <span class="hlt">ice</span> increases with decreasing temperature. Thus, varying snow conditions may play a key role in ikaite precipitation and dissolution in <span class="hlt">sea</span> <span class="hlt">ice</span>. This could have a major implication for CO2 exchange with the atmosphere and ocean that has not been accounted for previously.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/biblio/638276-sea-ice-polar-climate-ncar-csm','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/638276-sea-ice-polar-climate-ncar-csm"><span><span class="hlt">Sea</span> <span class="hlt">ice</span> and polar climate in the NCAR CSM</span></a></p> <p><a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Weatherly, J.W.; Briegleb, B.P.; Large, W.G.</p> <p></p> <p>The Climate System Model (CSM) consists of atmosphere, ocean, land, and <span class="hlt">sea-ice</span> components linked by a flux coupler, which computes fluxes of energy and momentum between components. The <span class="hlt">sea-ice</span> component consists of a thermodynamic formulation for <span class="hlt">ice</span>, snow, and leads within the <span class="hlt">ice</span> pack, and <span class="hlt">ice</span> dynamics using the cavitating-fluid <span class="hlt">ice</span> rheology, which allows for the compressive strength of <span class="hlt">ice</span> but ignores shear viscosity. The results of a 300-yr climate simulation are presented, with the focus on <span class="hlt">sea</span> <span class="hlt">ice</span> and the atmospheric forcing over <span class="hlt">sea</span> <span class="hlt">ice</span> in the polar regions. The atmospheric model results are compared to analyses from themore » European Centre for Medium-Range Weather Forecasts and other observational sources. The <span class="hlt">sea-ice</span> concentrations and velocities are compared to satellite observational data. The atmospheric <span class="hlt">sea</span> level pressure (SLP) in CSM exhibits a high in the central Arctic displaced poleward from the observed Beaufort high. The Southern Hemisphere SLP over <span class="hlt">sea</span> <span class="hlt">ice</span> is generally 5 mb lower than observed. Air temperatures over <span class="hlt">sea</span> <span class="hlt">ice</span> in both hemispheres exhibit cold biases of 2--4 K. The precipitation-minus-evaporation fields in both hemispheres are greatly improved over those from earlier versions of the atmospheric GCM.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFM.C31A0435M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFM.C31A0435M"><span>Help, I don’t know which <span class="hlt">sea</span> <span class="hlt">ice</span> algorithm to use?!: Developing an authoritative <span class="hlt">sea</span> <span class="hlt">ice</span> climate data record</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Meier, W.; Stroeve, J.; Duerr, R. E.; Fetterer, F. M.</p> <p>2009-12-01</p> <p>The declining Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> is one of the most dramatic indicators of climate change and is being recognized as a key factor in future climate impacts on biology, human activities, and global climate change. As such, the audience for <span class="hlt">sea</span> <span class="hlt">ice</span> data is expanding well beyond the <span class="hlt">sea</span> <span class="hlt">ice</span> community. The most comprehensive <span class="hlt">sea</span> <span class="hlt">ice</span> data are from a series of satellite-borne passive microwave sensors. They provide a near-complete daily timeseries of <span class="hlt">sea</span> <span class="hlt">ice</span> concentration and extent since late-1978. However, there are many complicating issues in using such data, particularly for novice users. First, there is not one single, definitive algorithm, but several. And even for a given algorithm, different processing and quality-control methods may be used, depending on the source. Second, for all algorithms, there are uncertainties in any retrieved value. In general, these limitations are well-known: low spatial-resolution results in an imprecise <span class="hlt">ice</span> edge determination and lack of small-scale detail (e.g., lead detection) within the <span class="hlt">ice</span> pack; surface melt depresses concentration values during summer; thin <span class="hlt">ice</span> is underestimated in some algorithms; some algorithms are sensitive to physical surface temperature; other surface features (e.g., snow) can influence retrieved data. While general error estimates are available for concentration values, currently the products do not carry grid-cell level or even granule level data quality information. Finally, metadata and data provenance information are limited, both of which are essential for future reprocessing. Here we describe the progress to date toward development of <span class="hlt">sea</span> <span class="hlt">ice</span> concentration products and outline the future steps needed to complete a <span class="hlt">sea</span> <span class="hlt">ice</span> climate data record.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li class="active"><span>8</span></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_8 --> <div id="page_9" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li class="active"><span>9</span></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="161"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19850017730&hterms=Parkinsons+circulation&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3DParkinsons%2Bcirculation','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19850017730&hterms=Parkinsons+circulation&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3DParkinsons%2Bcirculation"><span>Possible <span class="hlt">Sea</span> <span class="hlt">Ice</span> Impacts on Oceanic Deep Convection</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Parkinson, C. L.</p> <p>1984-01-01</p> <p>Many regions of the world ocean known or suspected to have deep convection are <span class="hlt">sea-ice</span> covered for at least a portion of the annual cycle. As this suggests that <span class="hlt">sea</span> <span class="hlt">ice</span> might have some impact on generating or maintaining this phenomenon, several mechanisms by which <span class="hlt">sea</span> <span class="hlt">ice</span> could exert an influence are presented in the following paragraphs. <span class="hlt">Sea</span> <span class="hlt">ice</span> formation could be a direct causal factor in deep convection by providing the surface density increase necessary to initiate the convective overturning. As <span class="hlt">sea</span> <span class="hlt">ice</span> forms, either by <span class="hlt">ice</span> accretion or by in situ <span class="hlt">ice</span> formation in open water or in lead areas between <span class="hlt">ice</span> floes, salt is rejected to the underlying water. This increases the water salinity, thereby increasing water density in the mixed layer under the <span class="hlt">ice</span>. A sufficient increase in density will lead to mixing with deeper waters, and perhaps to deep convection or even bottom water formation. Observations are needed to establish whether this process is actually occurring; it is most likely in regions with extensive <span class="hlt">ice</span> formation and a relatively unstable oceanic density structure.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70012715','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70012715"><span>Time-dependence of <span class="hlt">sea-ice</span> concentration and multiyear <span class="hlt">ice</span> fraction in the Arctic Basin</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Gloersen, P.; Zwally, H.J.; Chang, A.T.C.; Hall, D.K.; Campbell, W.J.; Ramseier, R.O.</p> <p>1978-01-01</p> <p>The time variation of the <span class="hlt">sea-ice</span> concentration and multiyear <span class="hlt">ice</span> fraction within the pack <span class="hlt">ice</span> in the Arctic Basin is examined, using microwave images of <span class="hlt">sea</span> <span class="hlt">ice</span> recently acquired by the Nimbus-5 spacecraft and the NASA CV-990 airborne laboratory. The images used for these studies were constructed from data acquired from the Electrically Scanned Microwave Radiometer (ESMR) which records radiation from earth and its atmosphere at a wavelength of 1.55 cm. Data are analyzed for four seasons during 1973-1975 to illustrate some basic differences in the properties of the <span class="hlt">sea</span> <span class="hlt">ice</span> during those times. Spacecraft data are compared with corresponding NASA CV-990 airborne laboratory data obtained over wide areas in the Arctic Basin during the Main Arctic <span class="hlt">Ice</span> Dynamics Joint Experiment (1975) to illustrate the applicability of passive-microwave remote sensing for monitoring the time dependence of <span class="hlt">sea-ice</span> concentration (divergence). These observations indicate significant variations in the <span class="hlt">sea-ice</span> concentration in the spring, late fall and early winter. In addition, deep in the interior of the Arctic polar <span class="hlt">sea-ice</span> pack, heretofore unobserved large areas, several hundred kilometers in extent, of <span class="hlt">sea-ice</span> concentrations as low as 50% are indicated. ?? 1978 D. Reidel Publishing Company.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19950045752&hterms=Parkinsons&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3DParkinsons','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19950045752&hterms=Parkinsons&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3DParkinsons"><span>The role of <span class="hlt">sea</span> <span class="hlt">ice</span> in 2 x CO2 climate model sensitivity. Part 1: The total influence of <span class="hlt">sea</span> <span class="hlt">ice</span> thickness and extent</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Rind, D.; Healy, R.; Parkinson, C.; Martinson, D.</p> <p>1995-01-01</p> <p>As a first step in investigating the effects of <span class="hlt">sea</span> <span class="hlt">ice</span> changes on the climate sensitivity to doubled atmospheric CO2, the authors use a standard simple <span class="hlt">sea</span> <span class="hlt">ice</span> model while varying the <span class="hlt">sea</span> <span class="hlt">ice</span> distributions and thicknesses in the control run. Thinner <span class="hlt">ice</span> amplifies the atmospheric temperature senstivity in these experiments by about 15% (to a warming of 4.8 C), because it is easier for the thinner <span class="hlt">ice</span> to be removed as the climate warms. Thus, its impact on sensitivity is similar to that of greater <span class="hlt">sea</span> <span class="hlt">ice</span> extent in the control run, which provides more opportunity for <span class="hlt">sea</span> <span class="hlt">ice</span> reduction. An experiment with <span class="hlt">sea</span> <span class="hlt">ice</span> not allowed to change between the control and doubled CO2 simulations illustrates that the total effect of <span class="hlt">sea</span> <span class="hlt">ice</span> on surface air temperature changes, including cloud cover and water vapor feedbacks that arise in response to <span class="hlt">sea</span> <span class="hlt">ice</span> variations, amounts to 37% of the temperature sensitivity to the CO2 doubling, accounting for 1.56 C of the 4.17 C global warming. This is about four times larger than the <span class="hlt">sea</span> <span class="hlt">ice</span> impact when no feedbacks are allowed. The different experiments produce a range of results for southern high latitudes with the hydrologic budget over Antarctica implying <span class="hlt">sea</span> level increases of varying magnitude or no change. These results highlight the importance of properly constraining the <span class="hlt">sea</span> <span class="hlt">ice</span> response to climate perturbations, necessitating the use of more realistic <span class="hlt">sea</span> <span class="hlt">ice</span> and ocean models.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFM.C41C0478A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFM.C41C0478A"><span>Controls on Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> from first-year and multi-year <span class="hlt">ice</span> survival rates</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Armour, K.; Bitz, C. M.; Hunke, E. C.; Thompson, L.</p> <p>2009-12-01</p> <p>The recent decrease in Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> cover has transpired with a significant loss of multi-year (MY) <span class="hlt">ice</span>. The transition to an Arctic that is populated by thinner first-year (FY) <span class="hlt">sea</span> <span class="hlt">ice</span> has important implications for future trends in area and volume. We develop a reduced model for Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> with which we investigate how the survivability of FY and MY <span class="hlt">ice</span> control various aspects of the <span class="hlt">sea-ice</span> system. We demonstrate that Arctic <span class="hlt">sea-ice</span> area and volume behave approximately as first-order autoregressive processes, which allows for a simple interpretation of September <span class="hlt">sea-ice</span> in which its mean state, variability, and sensitivity to climate forcing can be described naturally in terms of the average survival rates of FY and MY <span class="hlt">ice</span>. This model, used in concert with a <span class="hlt">sea-ice</span> simulation that traces FY and MY <span class="hlt">ice</span> areas to estimate the survival rates, reveals that small trends in the <span class="hlt">ice</span> survival rates explain the decline in total Arctic <span class="hlt">ice</span> area, and the relatively larger loss of MY <span class="hlt">ice</span> area, over the period 1979-2006. Additionally, our model allows for a calculation of the persistence time scales of September area and volume anomalies. A relatively short memory time scale for <span class="hlt">ice</span> area (~ 1 year) implies that Arctic <span class="hlt">ice</span> area is nearly in equilibrium with long-term climate forcing at all times, and therefore observed trends in area are a clear indication of a changing climate. A longer memory time scale for <span class="hlt">ice</span> volume (~ 5 years) suggests that volume can be out of equilibrium with climate forcing for long periods of time, and therefore trends in <span class="hlt">ice</span> volume are difficult to distinguish from its natural variability. With our reduced model, we demonstrate the connection between memory time scale and sensitivity to climate forcing, and discuss the implications that a changing memory time scale has on the trajectory of <span class="hlt">ice</span> area and volume in a warming climate. Our findings indicate that it is unlikely that a “tipping point” in September <span class="hlt">ice</span> area and volume will be</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29621173','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29621173"><span>Statistical Analysis of SSMIS <span class="hlt">Sea</span> <span class="hlt">Ice</span> Concentration Threshold at the Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> Edge during Summer Based on MODIS and Ship-Based Observational Data.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Ji, Qing; Li, Fei; Pang, Xiaoping; Luo, Cong</p> <p>2018-04-05</p> <p>The threshold of <span class="hlt">sea</span> <span class="hlt">ice</span> concentration (SIC) is the basis for accurately calculating <span class="hlt">sea</span> <span class="hlt">ice</span> extent based on passive microwave (PM) remote sensing data. However, the PM SIC threshold at the <span class="hlt">sea</span> <span class="hlt">ice</span> edge used in previous studies and released <span class="hlt">sea</span> <span class="hlt">ice</span> products has not always been consistent. To explore the representable value of the PM SIC threshold corresponding on average to the position of the Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> edge during summer in recent years, we extracted <span class="hlt">sea</span> <span class="hlt">ice</span> edge boundaries from the Moderate-resolution Imaging Spectroradiometer (MODIS) <span class="hlt">sea</span> <span class="hlt">ice</span> product (MOD29 with a spatial resolution of 1 km), MODIS images (250 m), and <span class="hlt">sea</span> <span class="hlt">ice</span> ship-based observation points (1 km) during the fifth (CHINARE-2012) and sixth (CHINARE-2014) Chinese National Arctic Research Expeditions, and made an overlay and comparison analysis with PM SIC derived from Special Sensor Microwave Imager Sounder (SSMIS, with a spatial resolution of 25 km) in the summer of 2012 and 2014. Results showed that the average SSMIS SIC threshold at the Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> edge based on <span class="hlt">ice</span>-water boundary lines extracted from MOD29 was 33%, which was higher than that of the commonly used 15% discriminant threshold. The average SIC threshold at <span class="hlt">sea</span> <span class="hlt">ice</span> edge based on <span class="hlt">ice</span>-water boundary lines extracted by visual interpretation from four scenes of the MODIS image was 35% when compared to the average value of 36% from the MOD29 extracted <span class="hlt">ice</span> edge pixels for the same days. The average SIC of 31% at the <span class="hlt">sea</span> <span class="hlt">ice</span> edge points extracted from ship-based observations also confirmed that choosing around 30% as the SIC threshold during summer is recommended for <span class="hlt">sea</span> <span class="hlt">ice</span> extent calculations based on SSMIS PM data. These results can provide a reference for further studying the variation of <span class="hlt">sea</span> <span class="hlt">ice</span> under the rapidly changing Arctic.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUOSME12B..03L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUOSME12B..03L"><span>Under the <span class="hlt">Sea</span> <span class="hlt">Ice</span>: Exploration of the Relationships Between <span class="hlt">Sea</span> <span class="hlt">Ice</span> Patterns and Foraging Movements of a Marine Predator in East Antarctica.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Labrousse, S.; Sallee, J. B.; Fraser, A. D.; Massom, R. A.; Reid, P.; Sumner, M.; Guinet, C.; Harcourt, R.; Bailleul, F.; Hindell, M.; Charrassin, J. B.</p> <p>2016-02-01</p> <p>Investigating ecological relationships between top predators and their environment is essential to understand the response of marine ecosystems to climate variability. Specifically, variability and changes in <span class="hlt">sea</span> <span class="hlt">ice</span>, which is known as an important habitat for marine ecosystems, presents complex patterns in East Antarctic. The impact for ecosystems of such changes of their habitat is however still unknown. Acting as an ecological double-edged sword, <span class="hlt">sea</span> <span class="hlt">ice</span> can impede access to marine resources while harboring a rich ecosystem during winter. Here, we investigated which type of <span class="hlt">sea</span> <span class="hlt">ice</span> habitat is used by male and female southern elephant seals during winter and examine if and how the spatio-temporal variability of <span class="hlt">sea</span> <span class="hlt">ice</span> concentration (SIC) influence their foraging strategies. We also examined over a 10 years time-series the impact of SIC and <span class="hlt">sea</span> <span class="hlt">ice</span> advance anomaly on foraging activity. To do this, we studied 46 individuals equipped with Satellite linked data recorders between 2004 and 2014, undertaking post-moult trips in winter from Kerguelen to the peri-Antarctic shelf. The general patterns of <span class="hlt">sea</span> <span class="hlt">ice</span> use by males and females are clearly distinct; while females tended to follow the <span class="hlt">sea</span> <span class="hlt">ice</span> edge as it extended northward, males remained on the continental shelf. Female foraging activity was higher in late autumn in the outer part of the pack <span class="hlt">ice</span> in concentrated SIC and spatially stable. They remained in areas of variable SIC over time and low persistence. The seal hunting time, a proxy of foraging activity inferred from the diving behaviour, was much higher during earlier advance of <span class="hlt">sea</span> <span class="hlt">ice</span> over female time-series. The females were possibly taking advantage of the <span class="hlt">ice</span> algal autumn bloom sustaining krill and an under <span class="hlt">ice</span> ecosystem without being trapped in <span class="hlt">sea</span> <span class="hlt">ice</span>. Males foraging activity increased when they remained deep inside <span class="hlt">sea</span> <span class="hlt">ice</span> over the shelf using variable SIC in time and space, presumably in polynyas or flaw leads between fast and pack <span class="hlt">ice</span>. This strategy</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19940026121','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19940026121"><span>A toy model of <span class="hlt">sea</span> <span class="hlt">ice</span> growth</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Thorndike, Alan S.</p> <p>1992-01-01</p> <p>My purpose here is to present a simplified treatment of the growth of <span class="hlt">sea</span> <span class="hlt">ice</span>. By ignoring many details, it is possible to obtain several results that help to clarify the ways in which the <span class="hlt">sea</span> <span class="hlt">ice</span> cover will respond to climate change. Three models are discussed. The first deals with the growth of <span class="hlt">sea</span> <span class="hlt">ice</span> during the cold season. The second describes the cycle of growth and melting for perennial <span class="hlt">ice</span>. The third model extends the second to account for the possibility that the <span class="hlt">ice</span> melts away entirely in the summer. In each case, the objective is to understand what physical processes are most important, what <span class="hlt">ice</span> properties determine the <span class="hlt">ice</span> behavior, and to which climate variables the system is most sensitive.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.C21E..08S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.C21E..08S"><span>Rate and state dependent processes in <span class="hlt">sea</span> <span class="hlt">ice</span> deformation</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sammonds, P. R.; Scourfield, S.; Lishman, B.</p> <p>2014-12-01</p> <p>Realistic models of <span class="hlt">sea</span> <span class="hlt">ice</span> processes and properties are needed to assess <span class="hlt">sea</span> <span class="hlt">ice</span> thickness, extent and concentration and, when run within GCMs, provide prediction of climate change. The deformation of <span class="hlt">sea</span> <span class="hlt">ice</span> is a key control on the Arctic Ocean dynamics. But the deformation of <span class="hlt">sea</span> <span class="hlt">ice</span> is dependent not only on the rate of the processes involved but also the state of the <span class="hlt">sea</span> <span class="hlt">ice</span> and particular in terms of its evolution with time and temperature. Shear deformation is a dominant mechanism from the scale of basin-scale shear lineaments, through floe-floe interaction to block sliding in <span class="hlt">ice</span> ridges. The shear deformation will not only depend on the speed of movement of <span class="hlt">ice</span> surfaces but also the degree that the surfaces have bonded during thermal consolidation and compaction. Frictional resistance to sliding can vary by more than two orders of magnitude depending on the state of the interface. But this in turn is dependent upon both imposed conditions and <span class="hlt">sea</span> <span class="hlt">ice</span> properties such as size distribution of interfacial broken <span class="hlt">ice</span>, angularity, porosity, salinity, etc. We review experimental results in <span class="hlt">sea</span> <span class="hlt">ice</span> mechanics from mid-scale experiments, conducted in the Hamburg model ship <span class="hlt">ice</span> tank, simulating <span class="hlt">sea</span> <span class="hlt">ice</span> floe motion and interaction and compare these with laboratory experiments on <span class="hlt">ice</span> friction done in direct shear from which a rate and state constitutive relation for shear deformation is derived. Finally we apply this to field measurement of <span class="hlt">sea</span> <span class="hlt">ice</span> friction made during experiments in the Barents <span class="hlt">Sea</span> to assess the other environmental factors, the state terms, that need to be modelled in order to up-scale to Arctic Ocean-scale dynamics.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70040743','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70040743"><span>Walrus areas of use in the Chukchi <span class="hlt">Sea</span> during sparse <span class="hlt">sea</span> <span class="hlt">ice</span> cover</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Jay, Chadwick V.; Fischbach, Anthony S.; Kochnev, Anatoly A.</p> <p>2012-01-01</p> <p>The Pacific walrus Odobenus rosmarus divergens feeds on benthic invertebrates on the continental shelf of the Chukchi and Bering <span class="hlt">Seas</span> and rests on <span class="hlt">sea</span> <span class="hlt">ice</span> between foraging trips. With climate warming, <span class="hlt">ice</span>-free periods in the Chukchi <span class="hlt">Sea</span> have increased and are projected to increase further in frequency and duration. We radio-tracked walruses to estimate areas of walrus foraging and occupancy in the Chukchi <span class="hlt">Sea</span> from June to November of 2008 to 2011, years when <span class="hlt">sea</span> <span class="hlt">ice</span> was sparse over the continental shelf in comparison to historical records. The earlier and more extensive <span class="hlt">sea</span> <span class="hlt">ice</span> retreat in June to September, and delayed freeze-up of <span class="hlt">sea</span> <span class="hlt">ice</span> in October to November, created conditions for walruses to arrive earlier and stay later in the Chukchi <span class="hlt">Sea</span> than in the past. The lack of <span class="hlt">sea</span> <span class="hlt">ice</span> over the continental shelf from September to October caused walruses to forage in nearshore areas instead of offshore areas as in the past. Walruses did not frequent the deep waters of the Arctic Basin when <span class="hlt">sea</span> <span class="hlt">ice</span> retreated off the shelf. Walruses foraged in most areas they occupied, and areas of concentrated foraging generally corresponded to regions of high benthic biomass, such as in the northeastern (Hanna Shoal) and southwestern Chukchi <span class="hlt">Sea</span>. A notable exception was the occurrence of concentrated foraging in a nearshore area of northwestern Alaska that is apparently depauperate in walrus prey. With increasing <span class="hlt">sea</span> <span class="hlt">ice</span> loss, it is likely that walruses will increase their use of coastal haul-outs and nearshore foraging areas, with consequences to the population that are yet to be understood.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C43B0753X','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C43B0753X"><span><span class="hlt">Sea</span> <span class="hlt">Ice</span> Freeboard and Thickness from the 2013 <span class="hlt">Ice</span>Bridge ATM and DMS Data in Ross <span class="hlt">Sea</span>, Antarctica</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Xie, H.; Tian, L.; Tang, J.; Ackley, S. F.</p> <p>2016-12-01</p> <p>In November (20, 21, 27, and 28) 2013, NASA's <span class="hlt">Ice</span>Bridge mission flew over the Ross <span class="hlt">Sea</span>, Antarctica and collected important <span class="hlt">sea</span> <span class="hlt">ice</span> data with the ATM and DMS for the first time. We will present our methods to derive the local <span class="hlt">sea</span> level and total freeboard for <span class="hlt">ice</span> thickness retrieval from these two datasets. The methods include (1) leads classification from DMS data using an automated lead detection method, (2) potential leads from the reflectance of less than 0.25 from the ATM laser shots of L1B data, (3) local <span class="hlt">sea</span> level retrieval based on these qualified ATM laser shots (L1B) within the DMS-derived leads (after outliers removal from the mean ± 2 standard deviation of these ATM elevations), (4) establishment of an empirical equation of local <span class="hlt">sea</span> level as a function of distance from the starting point of each <span class="hlt">Ice</span>Bridge flight, (5) total freeboard retrieval from the ATM L2 elevations by subtracting the local <span class="hlt">sea</span> level derived from the empirical equation, and (6) <span class="hlt">ice</span> thickness retrieval. The <span class="hlt">ice</span> thickness derived from this method will be analyzed and compared with ICESat data (2003-2009) and other available data for the same region at the similar time period. Possible change and potential reasons will be identified and discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUOSHE44C1528D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUOSHE44C1528D"><span>The Effect of Recent Decreases in <span class="hlt">Sea</span> <span class="hlt">Ice</span> Extent and Increases in SST on the Seasonal Availability of Arctic Cod (Boreogadus saida) to Seabirds in the Beaufort <span class="hlt">Sea</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Divoky, G.; Druckenmiller, M. L.</p> <p>2016-02-01</p> <p>With major decreases in pan-Arctic summer <span class="hlt">sea</span> <span class="hlt">ice</span> extent steadily underway, the Beaufort <span class="hlt">Sea</span> has been nearly <span class="hlt">ice</span>-free in five of the last eight summers. This loss of a critical arctic marine habitat and the concurrent warming of the recently <span class="hlt">ice</span>-free waters could potentially cause major changes in the biological oceanography of the Beaufort <span class="hlt">Sea</span> and alter the distribution, abundance and condition of the region's upper trophic level predators that formerly relied on prey associated with <span class="hlt">sea</span> <span class="hlt">ice</span> or cold (<2°C) surface waters. Arctic cod (Boreogadus saida), the primary forage fish for seabirds in the Beaufort <span class="hlt">Sea</span>, is part of the cryopelagic fauna associated with <span class="hlt">sea</span> <span class="hlt">ice</span> and is also found in <span class="hlt">adjacent</span> <span class="hlt">ice</span>-free waters. In the extreme western Beaufort <span class="hlt">Sea</span> near Cooper Island, Arctic cod availability to breeding Black Guillemots (Cepphus grylle), a diving seabird, has declined since 2002. Guillemots are a good indicator of Arctic cod availability in surface waters and the upper water column as they feed at depths of 1-20m. Currently, when <span class="hlt">sea</span> <span class="hlt">ice</span> is absent from the nearshore and SST exceeds 4°C, guillemots are observed to seasonally shift from Arctic cod to nearshore demersal prey, with a resulting decrease in nestling survival and quality. Arctic cod is the primary prey for many of the seabirds utilizing the Beaufort <span class="hlt">Sea</span> as a post-breeding staging area and migratory corridor in late summer and early fall. The loss of approximately 200-300 thousand sq km of summer <span class="hlt">sea</span> <span class="hlt">ice</span> habitat in recent years could be expected to affect the distribution, abundance, and movements of these species as there are few alternative fish resources in the region. We examine temporal and spatial variation in August <span class="hlt">sea</span> <span class="hlt">ice</span> extent and SST in the Beaufort <span class="hlt">Sea</span> to determine the regions, periods and bird species that are potentially most affected as the Beaufort <span class="hlt">Sea</span> transitions to becoming regularly <span class="hlt">ice</span>-free in late summer.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20080018456&hterms=Secret&qs=N%3D0%26Ntk%3DTitle%26Ntx%3Dmode%2Bmatchall%26Ntt%3DThe%2BSecret','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20080018456&hterms=Secret&qs=N%3D0%26Ntk%3DTitle%26Ntx%3Dmode%2Bmatchall%26Ntt%3DThe%2BSecret"><span>The Secret of the Svalbard <span class="hlt">Sea</span> <span class="hlt">Ice</span> Barrier</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Nghiem, Son V.; Van Woert, Michael L.; Neumann, Gregory</p> <p>2004-01-01</p> <p>An elongated <span class="hlt">sea</span> <span class="hlt">ice</span> feature called the Svalbard <span class="hlt">sea</span> <span class="hlt">ice</span> barrier rapidly formed over an area in the Barents <span class="hlt">Sea</span> to the east of Svalbard posing navigation hazards. The secret of its formation lies in the bottom bathymetry that governs the distribution of cold Arctic waters masses, which impacts <span class="hlt">sea</span> <span class="hlt">ice</span> growth on the water surface.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70017680','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70017680"><span>Contrasts in Arctic shelf <span class="hlt">sea-ice</span> regimes and some implications: Beaufort <span class="hlt">Sea</span> versus Laptev <span class="hlt">Sea</span></span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Reimnitz, E.; Dethleff, D.; Nurnberg, D.</p> <p>1994-01-01</p> <p>The winter <span class="hlt">ice</span>-regime of the 500 km) from the mainland than in the Beaufort <span class="hlt">Sea</span>. As a result, the annual freeze-up does not incorporate old, deep-draft <span class="hlt">ice</span>, and with a lack of compression, such deep-draft <span class="hlt">ice</span> is not generated in situ, as on the Beaufort <span class="hlt">Sea</span> shelf. The Laptev <span class="hlt">Sea</span> has as much as 1000 km of fetch at the end of summer, when freezing storms move in and large (6 m) waves can form. Also, for the first three winter months, the polynya lies inshore at a water depth of only 10 m. Turbulence and freezing are excellent conditions for sediment entrainment by frazil and anchor <span class="hlt">ice</span>, when compared to conditions in the short-fetched Beaufort <span class="hlt">Sea</span>. We expect entrainment to occur yearly. Different from the intensely <span class="hlt">ice</span>-gouged Beaufort <span class="hlt">Sea</span> shelf, hydraulic bedforms probably dominate in the Laptev <span class="hlt">Sea</span>. Corresponding with the large volume of <span class="hlt">ice</span> produced, more dense water is generated in the Laptev <span class="hlt">Sea</span>, possibly accompanied by downslope sediment transport. Thermohaline convection at the midshelf polynya, together with the reduced rate of bottom disruption by <span class="hlt">ice</span> keels, may enhance benthic productivity and permit establishment of open-shelf benthic communities which in the Beaufort <span class="hlt">Sea</span> can thrive only in the protection of barrier islands. Indirect evidence for high benthic productivity is found in the presence of walrus, who also require year-round open water. By contrast, lack of a suitable environment restricts walrus from the Beaufort <span class="hlt">Sea</span>, although over 700 km farther to the south. We could speculate on other consequences of the different <span class="hlt">ice</span> regimes in the Beaufort and Laptev <span class="hlt">Seas</span>, but these few examples serve to point out the dangers of exptrapolating from knowledge gained in the North American Arctic to other shallow Arctic shelf settings. ?? 1994.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70190395','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70190395"><span>Polar bears and <span class="hlt">sea</span> <span class="hlt">ice</span> habitat change</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Durner, George M.; Atwood, Todd C.; Butterworth, Andy</p> <p>2017-01-01</p> <p>The polar bear (Ursus maritimus) is an obligate apex predator of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> and as such can be affected by climate warming-induced changes in the extent and composition of pack <span class="hlt">ice</span> and its impacts on their seal prey. <span class="hlt">Sea</span> <span class="hlt">ice</span> declines have negatively impacted some polar bear subpopulations through reduced energy input because of loss of hunting habitats, higher energy costs due to greater <span class="hlt">ice</span> drift, <span class="hlt">ice</span> fracturing and open water, and ultimately greater challenges to recruit young. Projections made from the output of global climate models suggest that polar bears in peripheral Arctic and sub-Arctic <span class="hlt">seas</span> will be reduced in numbers or become extirpated by the end of the twenty-first century if the rate of climate warming continues on its present trajectory. The same projections also suggest that polar bears may persist in the high-latitude Arctic where heavy multiyear <span class="hlt">sea</span> <span class="hlt">ice</span> that has been typical in that region is being replaced by thinner annual <span class="hlt">ice</span>. Underlying physical and biological oceanography provides clues as to why polar bear in some regions are negatively impacted, while bears in other regions have shown no apparent changes. However, continued declines in <span class="hlt">sea</span> <span class="hlt">ice</span> will eventually challenge the survival of polar bears and efforts to conserve them in all regions of the Arctic.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140010420','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140010420"><span><span class="hlt">Sea</span> <span class="hlt">Ice</span> Thickness, Freeboard, and Snow Depth products from Operation <span class="hlt">Ice</span>Bridge Airborne Data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Kurtz, N. T.; Farrell, S. L.; Studinger, M.; Galin, N.; Harbeck, J. P.; Lindsay, R.; Onana, V. D.; Panzer, B.; Sonntag, J. G.</p> <p>2013-01-01</p> <p>The study of <span class="hlt">sea</span> <span class="hlt">ice</span> using airborne remote sensing platforms provides unique capabilities to measure a wide variety of <span class="hlt">sea</span> <span class="hlt">ice</span> properties. These measurements are useful for a variety of topics including model evaluation and improvement, assessment of satellite retrievals, and incorporation into climate data records for analysis of interannual variability and long-term trends in <span class="hlt">sea</span> <span class="hlt">ice</span> properties. In this paper we describe methods for the retrieval of <span class="hlt">sea</span> <span class="hlt">ice</span> thickness, freeboard, and snow depth using data from a multisensor suite of instruments on NASA's Operation <span class="hlt">Ice</span>Bridge airborne campaign. We assess the consistency of the results through comparison with independent data sets that demonstrate that the <span class="hlt">Ice</span>Bridge products are capable of providing a reliable record of snow depth and <span class="hlt">sea</span> <span class="hlt">ice</span> thickness. We explore the impact of inter-campaign instrument changes and associated algorithm adaptations as well as the applicability of the adapted algorithms to the ongoing <span class="hlt">Ice</span>Bridge mission. The uncertainties associated with the retrieval methods are determined and placed in the context of their impact on the retrieved <span class="hlt">sea</span> <span class="hlt">ice</span> thickness. Lastly, we present results for the 2009 and 2010 <span class="hlt">Ice</span>Bridge campaigns, which are currently available in product form via the National Snow and <span class="hlt">Ice</span> Data Center</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.int-res.com/abstracts/meps/v407/p293-302/','USGSPUBS'); return false;" href="http://www.int-res.com/abstracts/meps/v407/p293-302/"><span>Divergent movements of walrus and <span class="hlt">sea</span> <span class="hlt">ice</span> in the Nothern Bering <span class="hlt">Sea</span></span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Jay, Chadwick V.; Udevitz, Mark S.; Kwok, Ron; Fischbach, Anthony S.; Douglas, David C.</p> <p>2010-01-01</p> <p>The Pacific walrus Odobenus rosmarus divergens is a large Arctic pinniped of the Chukchi and Bering <span class="hlt">Seas</span>. Reductions of <span class="hlt">sea</span> <span class="hlt">ice</span> projected to occur in the Arctic by mid-century raise concerns for conservation of the Pacific walrus. To understand the significance of <span class="hlt">sea</span> <span class="hlt">ice</span> loss to the viability of walruses, it would be useful to better understand the spatial associations between the movements of <span class="hlt">sea</span> <span class="hlt">ice</span> and walruses. We investigated whether local-scale (~1 to 100 km) walrus movements correspond to movements of <span class="hlt">sea</span> <span class="hlt">ice</span> in the Bering <span class="hlt">Sea</span> in early spring, using locations from radio-tracked walruses and measures of <span class="hlt">ice</span> floe movements from processed synthetic aperture radar satellite imagery. We used generalized linear mixed-effects models to analyze the angle between walrus and <span class="hlt">ice</span> floe movement vectors and the distance between the final geographic position of walruses and their associated <span class="hlt">ice</span> floes (displacement), as functions of observation duration, proportion of time the walrus was in water, and geographic region. Analyses were based on 121 walrus-<span class="hlt">ice</span> vector pairs and observations lasting 12 to 36 h. Angles and displacements increased with observation duration, proportion of time the walrus spent in the water, and varied among regions (regional mean angles ranged from 40° to 81° and mean displacements ranged from 15 to 35 km). Our results indicated a lack of correspondence between walruses and their initially associated <span class="hlt">ice</span> floes, suggesting that local areas of walrus activities were independent of the movement of <span class="hlt">ice</span> floes.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014JGRC..119.2327A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014JGRC..119.2327A"><span>Implications of fractured Arctic perennial <span class="hlt">ice</span> cover on thermodynamic and dynamic <span class="hlt">sea</span> <span class="hlt">ice</span> processes</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Asplin, Matthew G.; Scharien, Randall; Else, Brent; Howell, Stephen; Barber, David G.; Papakyriakou, Tim; Prinsenberg, Simon</p> <p>2014-04-01</p> <p>Decline of the Arctic summer minimum <span class="hlt">sea</span> <span class="hlt">ice</span> extent is characterized by large expanses of open water in the Siberian, Laptev, Chukchi, and Beaufort <span class="hlt">Seas</span>, and introduces large fetch distances in the Arctic Ocean. Long waves can propagate deep into the pack <span class="hlt">ice</span>, thereby causing flexural swell and failure of the <span class="hlt">sea</span> <span class="hlt">ice</span>. This process shifts the floe size diameter distribution smaller, increases floe surface area, and thereby affects <span class="hlt">sea</span> <span class="hlt">ice</span> dynamic and thermodynamic processes. The results of Radarsat-2 imagery analysis show that a flexural fracture event which occurred in the Beaufort <span class="hlt">Sea</span> region on 6 September 2009 affected ˜40,000 km2. Open water fractional area in the area affected initially decreased from 3.7% to 2.7%, but later increased to ˜20% following wind-forced divergence of the <span class="hlt">ice</span> pack. Energy available for lateral melting was assessed by estimating the change in energy entrainment from longwave and shortwave radiation in the mixed-layer of the ocean following flexural fracture. 11.54 MJ m-2 of additional energy for lateral melting of <span class="hlt">ice</span> floes was identified in affected areas. The impact of this process in future Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> melt seasons was assessed using estimations of earlier occurrences of fracture during the melt season, and is discussed in context with ocean heat fluxes, atmospheric mixing of the ocean mixed layer, and declining <span class="hlt">sea</span> <span class="hlt">ice</span> cover. We conclude that this process is an important positive feedback to Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> loss, and timing of initiation is critical in how it affects <span class="hlt">sea</span> <span class="hlt">ice</span> thermodynamic and dynamic processes.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.8068J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.8068J"><span><span class="hlt">Sea-ice</span> cover in the Nordic <span class="hlt">Seas</span> and the sensitivity to Atlantic water temperatures</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Jensen, Mari F.; Nisancioglu, Kerim H.; Spall, Michael A.</p> <p>2017-04-01</p> <p>Changes in the <span class="hlt">sea-ice</span> cover of the Nordic <span class="hlt">Seas</span> have been proposed to play a key role for the dramatic temperature excursions associated with the Dansgaard-Oeschger events during the last glacial. However, with its proximity to the warm Atlantic water, how a <span class="hlt">sea-ice</span> cover can persist in the Nordic <span class="hlt">Seas</span> is not well understood. In this study, we apply an eddy-resolving configuration of the Massachusetts Institute of Technology general circulation model with an idealized topography to study the presence of <span class="hlt">sea</span> <span class="hlt">ice</span> in a Nordic <span class="hlt">Seas</span>-like domain. We assume an infinite amount of warm Atlantic water present in the south by restoring the southern area to constant temperatures. The <span class="hlt">sea</span>-surface temperatures are restored toward cold, atmospheric temperatures, and as a result, <span class="hlt">sea</span> <span class="hlt">ice</span> is present in the interior of the domain. However, the <span class="hlt">sea-ice</span> cover in the margins of the Nordic <span class="hlt">Seas</span>, an area with a warm, cyclonic boundary current, is sensitive to the amount of heat entering the domain, i.e., the restoring temperature in the south. When the temperature of the warm, cyclonic boundary current is high, the margins are free of <span class="hlt">sea</span> <span class="hlt">ice</span> and heat is released to the atmosphere. We show that with a small reduction in the temperature of the incoming Atlantic water, the Nordic <span class="hlt">Seas</span>-like domain is fully covered in <span class="hlt">sea</span> <span class="hlt">ice</span>. Warm water is still entering the Nordic <span class="hlt">Seas</span>, however, this happens at depths below a cold, fresh surface layer produced by melted <span class="hlt">sea</span> <span class="hlt">ice</span>. Consequently, the heat release to the atmosphere is reduced along with the eddy heat fluxes. Results suggest a threshold value in the amount of heat entering the Nordic <span class="hlt">Seas</span> before the <span class="hlt">sea-ice</span> cover disappears in the margins. We study the sensitivity of this threshold to changes in atmospheric temperatures and vertical diffusivity.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C31A1151B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C31A1151B"><span>Influence of <span class="hlt">sea</span> <span class="hlt">ice</span> on Arctic coasts</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Barnhart, K. R.; Kay, J. E.; Overeem, I.; Anderson, R. S.</p> <p>2017-12-01</p> <p>Coasts form the dynamic interface between the terrestrial and oceanic systems. In the Arctic, and in much of the world, the coast is a focal point for population, infrastructure, biodiversity, and ecosystem services. A key difference between Arctic and temperate coasts is the presence of <span class="hlt">sea</span> <span class="hlt">ice</span>. Changes in <span class="hlt">sea</span> <span class="hlt">ice</span> cover can influence the coast because (1) the length of the <span class="hlt">sea</span> <span class="hlt">ice</span>-free season controls the time over which nearshore water can interact with the land, and (2) the location of the <span class="hlt">sea</span> <span class="hlt">ice</span> edge controls the fetch over which storm winds can interact with open ocean water, which in turn governs nearshore water level and wave field. We first focus on the interaction of <span class="hlt">sea</span> <span class="hlt">ice</span> and <span class="hlt">ice</span>-rich coasts. We combine satellite records of <span class="hlt">sea</span> <span class="hlt">ice</span> with a model for wind-driven storm surge and waves to estimate how changes in the <span class="hlt">sea</span> <span class="hlt">ice</span>-free season have impacted the nearshore hydrodynamic environment along Alaska's Beaufort <span class="hlt">Sea</span> Coast for the period 1979-2012. This region has experienced some of the greatest changes in both <span class="hlt">sea</span> <span class="hlt">ice</span> cover and coastal erosion rates in the Arctic: the median length of the open-water season has expanded by 90 percent, while coastal erosion rates have more than doubled from 8.7 to 19 m yr-1. At Drew Point, NW winds increase shoreline water levels that control the incision of a submarine notch, the rate-limiting step of coastal retreat. The maximum water-level setup at Drew Point has increased consistently with increasing fetch. We extend our analysis to the entire Arctic using both satellite-based observations and global coupled climate model output from the Community Earth System Model Large Ensemble (CESM-LE) project. This 30-member ensemble employs a 1-degree version of the CESM-CAM5 historical forcing for the period 1920-2005, and RCP 8.5 forcing from 2005-2100. A control model run with constant pre-industrial (1850) forcing characterizes internal variability in a constant climate. Finally, we compare observations and model results to</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/AD1013710','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/AD1013710"><span>Mass Balance of Multiyear <span class="hlt">Sea</span> <span class="hlt">Ice</span> in the Southern Beaufort <span class="hlt">Sea</span></span></a></p> <p><a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>2015-09-30</p> <p>1) Determination of the net growth and melt of multiyear (MY) <span class="hlt">sea</span> <span class="hlt">ice</span> during its transit through the southern Beaufort <span class="hlt">Sea</span> 2) Identification of...which we refer to as the FGIV dataset. Analysis of melt processes from <span class="hlt">ice</span> core and IMB data (Eicken) Through stratigraphic analysis of <span class="hlt">sea</span> <span class="hlt">ice</span>...samples that are brought back to shore were melted and used to determine profiles of salinity and stable isotope ratios. These data allow us to identify</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li class="active"><span>9</span></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_9 --> <div id="page_10" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li class="active"><span>10</span></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="181"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1364126','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1364126"><span>CICE, The Los Alamos <span class="hlt">Sea</span> <span class="hlt">Ice</span> Model</span></a></p> <p><a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Hunke, Elizabeth; Lipscomb, William; Jones, Philip</p> <p></p> <p>The Los Alamos <span class="hlt">sea</span> <span class="hlt">ice</span> model (CICE) is the result of an effort to develop a computationally efficient <span class="hlt">sea</span> <span class="hlt">ice</span> component for a fully coupled atmosphere–land–ocean–<span class="hlt">ice</span> global climate model. It was originally designed to be compatible with the Parallel Ocean Program (POP), an ocean circulation model developed at Los Alamos National Laboratory for use on massively parallel computers. CICE has several interacting components: a vertical thermodynamic model that computes local growth rates of snow and <span class="hlt">ice</span> due to vertical conductive, radiative and turbulent fluxes, along with snowfall; an elastic-viscous-plastic model of <span class="hlt">ice</span> dynamics, which predicts the velocity field of themore » <span class="hlt">ice</span> pack based on a model of the material strength of the <span class="hlt">ice</span>; an incremental remapping transport model that describes horizontal advection of the areal concentration, <span class="hlt">ice</span> and snow volume and other state variables; and a ridging parameterization that transfers <span class="hlt">ice</span> among thickness categories based on energetic balances and rates of strain. It also includes a biogeochemical model that describes evolution of the <span class="hlt">ice</span> ecosystem. The CICE <span class="hlt">sea</span> <span class="hlt">ice</span> model is used for climate research as one component of complex global earth system models that include atmosphere, land, ocean and biogeochemistry components. It is also used for operational <span class="hlt">sea</span> <span class="hlt">ice</span> forecasting in the polar regions and in numerical weather prediction models.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20170003146','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20170003146"><span>Characterizing Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> Topography Using High-Resolution <span class="hlt">Ice</span>Bridge Data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Petty, Alek; Tsamados, Michel; Kurtz, Nathan; Farrell, Sinead; Newman, Thomas; Harbeck, Jeremy; Feltham, Daniel; Richter-Menge, Jackie</p> <p>2016-01-01</p> <p>We present an analysis of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> topography using high resolution, three-dimensional, surface elevation data from the Airborne Topographic Mapper, flown as part of NASA's Operation <span class="hlt">Ice</span>Bridge mission. Surface features in the <span class="hlt">sea</span> <span class="hlt">ice</span> cover are detected using a newly developed surface feature picking algorithm. We derive information regarding the height, volume and geometry of surface features from 2009-2014 within the Beaufort/Chukchi and Central Arctic regions. The results are delineated by <span class="hlt">ice</span> type to estimate the topographic variability across first-year and multi-year <span class="hlt">ice</span> regimes.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27660738','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27660738"><span>Influence of <span class="hlt">ice</span> thickness and surface properties on light transmission through Arctic <span class="hlt">sea</span> <span class="hlt">ice</span>.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Katlein, Christian; Arndt, Stefanie; Nicolaus, Marcel; Perovich, Donald K; Jakuba, Michael V; Suman, Stefano; Elliott, Stephen; Whitcomb, Louis L; McFarland, Christopher J; Gerdes, Rüdiger; Boetius, Antje; German, Christopher R</p> <p>2015-09-01</p> <p>The observed changes in physical properties of <span class="hlt">sea</span> <span class="hlt">ice</span> such as decreased thickness and increased melt pond cover severely impact the energy budget of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span>. Increased light transmission leads to increased deposition of solar energy in the upper ocean and thus plays a crucial role for amount and timing of <span class="hlt">sea-ice</span>-melt and under-<span class="hlt">ice</span> primary production. Recent developments in underwater technology provide new opportunities to study light transmission below the largely inaccessible underside of <span class="hlt">sea</span> <span class="hlt">ice</span>. We measured spectral under-<span class="hlt">ice</span> radiance and irradiance using the new Nereid Under-<span class="hlt">Ice</span> (NUI) underwater robotic vehicle, during a cruise of the R/V Polarstern to 83°N 6°W in the Arctic Ocean in July 2014. NUI is a next generation hybrid remotely operated vehicle (H-ROV) designed for both remotely piloted and autonomous surveys underneath land-fast and moving <span class="hlt">sea</span> <span class="hlt">ice</span>. Here we present results from one of the first comprehensive scientific dives of NUI employing its interdisciplinary sensor suite. We combine under-<span class="hlt">ice</span> optical measurements with three dimensional under-<span class="hlt">ice</span> topography (multibeam sonar) and aerial images of the surface conditions. We investigate the influence of spatially varying <span class="hlt">ice</span>-thickness and surface properties on the spatial variability of light transmittance during summer. Our results show that surface properties such as melt ponds dominate the spatial distribution of the under-<span class="hlt">ice</span> light field on small scales (<1000 m 2 ), while <span class="hlt">sea</span> <span class="hlt">ice</span>-thickness is the most important predictor for light transmission on larger scales. In addition, we propose the use of an algorithm to obtain histograms of light transmission from distributions of <span class="hlt">sea</span> <span class="hlt">ice</span> thickness and surface albedo.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-GSFC_20171208_Archive_e000638.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-GSFC_20171208_Archive_e000638.html"><span>Warming <span class="hlt">Seas</span> and Melting <span class="hlt">Ice</span> Sheets</span></a></p> <p><a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a></p> <p></p> <p>2017-12-08</p> <p><span class="hlt">Sea</span> level rise is a natural consequence of the warming of our planet. We know this from basic physics. When water heats up, it expands. So when the ocean warms, <span class="hlt">sea</span> level rises. When <span class="hlt">ice</span> is exposed to heat, it melts. And when <span class="hlt">ice</span> on land melts and water runs into the ocean, <span class="hlt">sea</span> level rises. For thousands of years, <span class="hlt">sea</span> level has remained relatively stable and human communities have settled along the planet’s coastlines. But now Earth’s <span class="hlt">seas</span> are rising. Globally, <span class="hlt">sea</span> level has risen about eight inches since the beginning of the 20th century and more than two inches in the last 20 years alone. All signs suggest that this rise is accelerating. Read more: go.nasa.gov/1heZn29 Caption: An iceberg floats in Disko Bay, near Ilulissat, Greenland, on July 24, 2015. The massive Greenland <span class="hlt">ice</span> sheet is shedding about 300 gigatons of <span class="hlt">ice</span> a year into the ocean, making it the single largest source of <span class="hlt">sea</span> level rise from melting <span class="hlt">ice</span>. Credits: NASA/Saskia Madlener NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19790049956&hterms=navigation+sea+past&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dnavigation%2Bsea%2Bpast','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19790049956&hterms=navigation+sea+past&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dnavigation%2Bsea%2Bpast"><span>Mapping of <span class="hlt">sea</span> <span class="hlt">ice</span> and measurement of its drift using aircraft synthetic aperture radar images</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Leberl, F.; Bryan, M. L.; Elachi, C.; Farr, T.; Campbell, W.</p> <p>1979-01-01</p> <p>Side-looking radar images of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> were obtained as part of the Arctic <span class="hlt">Ice</span> Dynamics Joint Experiment. Repetitive coverages of a test site in the Arctic were used to measure <span class="hlt">sea</span> <span class="hlt">ice</span> drift, employing single images and blocks of overlapping radar image strips; the images were used in conjunction with data from the aircraft inertial navigation and altimeter. Also, independently measured, accurate positions of a number of ground control points were available. Initial tests of the method were carried out with repeated coverages of a land area on the Alaska coast (Prudhoe). Absolute accuracies achieved were essentially limited by the accuracy of the inertial navigation data. Errors of drift measurements were found to be about + or - 2.5 km. Relative accuracy is higher; its limits are set by the radar image geometry and the definition of identical features in sequential images. The drift of <span class="hlt">adjacent</span> <span class="hlt">ice</span> features with respect to one another could be determined with errors of less than + or - 0.2 km.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19990064613&hterms=Parkinsons&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3DParkinsons','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19990064613&hterms=Parkinsons&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3DParkinsons"><span>Variability of Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> as Determined from Satellite Observations</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Parkinson, Claire L.</p> <p>1999-01-01</p> <p>The compiled, quality-controlled satellite multichannel passive-microwave record of polar <span class="hlt">sea</span> <span class="hlt">ice</span> now spans over 18 years, from November 1978 through December 1996, and is revealing considerable information about the Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> cover and its variability. The information includes data on <span class="hlt">ice</span> concentrations (percent areal coverages of <span class="hlt">ice</span>), <span class="hlt">ice</span> extents, <span class="hlt">ice</span> melt, <span class="hlt">ice</span> velocities, the seasonal cycle of the <span class="hlt">ice</span>, the interannual variability of the <span class="hlt">ice</span>, the frequency of <span class="hlt">ice</span> coverage, and the length of the <span class="hlt">sea</span> <span class="hlt">ice</span> season. The data reveal marked regional and interannual variabilities, as well as some statistically significant trends. For the north polar <span class="hlt">ice</span> cover as a whole, maximum <span class="hlt">ice</span> extents varied over a range of 14,700,000 - 15,900,000 sq km, while individual regions experienced much greater percent variations, for instance, with the Greenland <span class="hlt">Sea</span> having a range of 740,000 - 1,110,000 sq km in its yearly maximum <span class="hlt">ice</span> coverage. In spite of the large variations from year to year and region to region, overall the Arctic <span class="hlt">ice</span> extents showed a statistically significant, 2.80% / decade negative trend over the 18.2-year period. <span class="hlt">Ice</span> season lengths, which vary from only a few weeks near the <span class="hlt">ice</span> margins to the full year in the large region of perennial <span class="hlt">ice</span> coverage, also experienced interannual variability, along with spatially coherent overall trends. Linear least squares trends show the <span class="hlt">sea</span> <span class="hlt">ice</span> season to have lengthened in much of the Bering <span class="hlt">Sea</span>, Baffin Bay, the Davis Strait, and the Labrador <span class="hlt">Sea</span>, but to have shortened over a much larger area, including the <span class="hlt">Sea</span> of Okhotsk, the Greenland <span class="hlt">Sea</span>, the Barents <span class="hlt">Sea</span>, and the southeastern Arctic.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4711856','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4711856"><span>Influence of <span class="hlt">sea</span> <span class="hlt">ice</span> on Arctic precipitation</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Kopec, Ben G.; Feng, Xiahong; Michel, Fred A.; Posmentier, Eric S.</p> <p>2016-01-01</p> <p>Global climate is influenced by the Arctic hydrologic cycle, which is, in part, regulated by <span class="hlt">sea</span> <span class="hlt">ice</span> through its control on evaporation and precipitation. However, the quantitative link between precipitation and <span class="hlt">sea</span> <span class="hlt">ice</span> extent is poorly constrained. Here we present observational evidence for the response of precipitation to <span class="hlt">sea</span> <span class="hlt">ice</span> reduction and assess the sensitivity of the response. Changes in the proportion of moisture sourced from the Arctic with <span class="hlt">sea</span> <span class="hlt">ice</span> change in the Canadian Arctic and Greenland <span class="hlt">Sea</span> regions over the past two decades are inferred from annually averaged deuterium excess (d-excess) measurements from six sites. Other influences on the Arctic hydrologic cycle, such as the strength of meridional transport, are assessed using the North Atlantic Oscillation index. We find that the independent, direct effect of <span class="hlt">sea</span> <span class="hlt">ice</span> on the increase of the percentage of Arctic sourced moisture (or Arctic moisture proportion, AMP) is 18.2 ± 4.6% and 10.8 ± 3.6%/100,000 km2 <span class="hlt">sea</span> <span class="hlt">ice</span> lost for each region, respectively, corresponding to increases of 10.9 ± 2.8% and 2.7 ± 1.1%/1 °C of warming in the vapor source regions. The moisture source changes likely result in increases of precipitation and changes in energy balance, creating significant uncertainty for climate predictions. PMID:26699509</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20070016598&hterms=sea+ice+albedo&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dsea%2Bice%2Balbedo','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20070016598&hterms=sea+ice+albedo&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dsea%2Bice%2Balbedo"><span>Observational Evidence of a Hemispheric-wide <span class="hlt">Ice</span>-ocean Albedo Feedback Effect on Antarctic <span class="hlt">Sea-ice</span> Decay</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Nihashi, Sohey; Cavalieri, Donald J.</p> <p>2007-01-01</p> <p>The effect of <span class="hlt">ice</span>-ocean albedo feedback (a kind of <span class="hlt">ice</span>-albedo feedback) on <span class="hlt">sea-ice</span> decay is demonstrated over the Antarctic <span class="hlt">sea-ice</span> zone from an analysis of satellite-derived hemispheric <span class="hlt">sea</span> <span class="hlt">ice</span> concentration and European Centre for Medium-Range Weather Forecasts (ERA-40) atmospheric data for the period 1979-2001. <span class="hlt">Sea</span> <span class="hlt">ice</span> concentration in December (time of most active melt) correlates better with the meridional component of the wind-forced <span class="hlt">ice</span> drift (MID) in November (beginning of the melt season) than the MID in December. This 1 month lagged correlation is observed in most of the Antarctic <span class="hlt">sea-ice</span> covered ocean. Daily time series of <span class="hlt">ice</span> , concentration show that the <span class="hlt">ice</span> concentration anomaly increases toward the time of maximum <span class="hlt">sea-ice</span> melt. These findings can be explained by the following positive feedback effect: once <span class="hlt">ice</span> concentration decreases (increases) at the beginning of the melt season, solar heating of the upper ocean through the increased (decreased) open water fraction is enhanced (reduced), leading to (suppressing) a further decrease in <span class="hlt">ice</span> concentration by the oceanic heat. Results obtained fi-om a simple <span class="hlt">ice</span>-ocean coupled model also support our interpretation of the observational results. This positive feedback mechanism explains in part the large interannual variability of the <span class="hlt">sea-ice</span> cover in summer.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUFMOS31C1297H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUFMOS31C1297H"><span>Transient sensitivities of <span class="hlt">sea</span> <span class="hlt">ice</span> export through the Canadian Arctic Archipelago inferred from a coupled ocean/<span class="hlt">sea-ice</span> adjoint model</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Heimbach, P.; Losch, M.; Menemenlis, D.; Campin, J.; Hill, C.</p> <p>2008-12-01</p> <p>The sensitivity of <span class="hlt">sea-ice</span> export through the Canadian Arctic Archipelago (CAA), measured in terms of its solid freshwater export through Lancaster Sound, to changes in various elements of the ocean and <span class="hlt">sea-ice</span> state, and to elements of the atmospheric forcing fields through time and space is assessed by means of a coupled ocean/<span class="hlt">sea-ice</span> adjoint model. The adjoint model furnishes full spatial sensitivity maps (also known as Lagrange multipliers) of the export metric to a variety of model variables at any chosen point in time, providing the unique capability to quantify major drivers of <span class="hlt">sea-ice</span> export variability. The underlying model is the MIT ocean general circulation model (MITgcm), which is coupled to a Hibler-type dynamic/thermodynamic <span class="hlt">sea-ice</span> model. The configuration is based on the Arctic face of the ECCO3 high-resolution cubed-sphere model, but coarsened to 36-km horizontal grid spacing. The adjoint of the coupled system has been derived by means of automatic differentiation using the software tool TAF. Finite perturbation simulations are performed to check the information provided by the adjoint. The <span class="hlt">sea-ice</span> model's performance in the presence of narrow straits is assessed with different <span class="hlt">sea-ice</span> lateral boundary conditions. The adjoint sensitivity clearly exposes the role of the model trajectory and the transient nature of the problem. The complex interplay between forcing, dynamics, and boundary condition is demonstrated in the comparison between the different calculations. The study is a step towards fully coupled adjoint-based ocean/<span class="hlt">sea-ice</span> state estimation at basin to global scales as part of the ECCO efforts.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFMEP54B..05O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFMEP54B..05O"><span>The Impact of <span class="hlt">Sea</span> <span class="hlt">Ice</span> Loss on Wave Dynamics and Coastal Erosion Along the Arctic Coast</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Overeem, I.; Anderson, R. S.; Wobus, C. W.; Matell, N.; Urban, F. E.; Clow, G. D.; Stanton, T. P.</p> <p>2010-12-01</p> <p>The extent of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> has been shrinking rapidly over the past few decades, and attendant acceleration of erosion is now occurring along the Arctic coast. This both brings coastal infrastructure into harm’s way and promotes a complex response of the <span class="hlt">adjacent</span> landscape to global change. We quantify the effects of declining <span class="hlt">sea</span> <span class="hlt">ice</span> extent on coastal erosion rates along a 75-km stretch of coastal permafrost bluffs <span class="hlt">adjacent</span> to the Beaufort <span class="hlt">Sea</span>, Alaska, where present-day erosion rates are among the highest in the world at ~14 m yr-1. Our own observations reinforce those of others, and suggest that the rate-limiting process is thermal erosion at the base of the several-meter tall bluffs. Here we focus on the interaction between the nearshore <span class="hlt">sea</span> <span class="hlt">ice</span> concentration, the location of the <span class="hlt">sea</span> <span class="hlt">ice</span> margin, and the fetch-limited, shallow water wave field, since these parameters ultimately control both <span class="hlt">sea</span> surface temperatures and the height to which these waters can bathe the frozen bluffs. Thirty years of daily or bi-daily passive microwave data from Nimbus-7 SMMR and DMSP SSM/I satellites reveal that the nearshore open water season lengthened ~54 days over 1979-2009. The open water season, centered in August, expands more rapidly into the fall (September and October~0.92 day yr-1) than into the early summer (July~0.71 days yr-1). Average fetch, defined for our purposes as the distance from the <span class="hlt">sea</span> <span class="hlt">ice</span> margin to the coast over which the wind is blowing, increased by a factor 1.7 over the same time-span. Given these time series, we modeled daily nearshore wave heights during the open water season for each year, which we integrated to provide a quantitative metric for the annual exposure of the coastal bluffs to thermal erosion. This “annual wave exposure” increased by 250% during 1979-2009. In the same interval, coastal erosion rates reconstructed from satellite and aerial photo records show less acceleration. We attribute this to a disproportionate extension of the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AcMSn..31....1Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AcMSn..31....1Z"><span>Modeling ocean wave propagation under <span class="hlt">sea</span> <span class="hlt">ice</span> covers</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhao, Xin; Shen, Hayley H.; Cheng, Sukun</p> <p>2015-02-01</p> <p>Operational ocean wave models need to work globally, yet current ocean wave models can only treat <span class="hlt">ice</span>-covered regions crudely. The purpose of this paper is to provide a brief overview of <span class="hlt">ice</span> effects on wave propagation and different research methodology used in studying these effects. Based on its proximity to land or <span class="hlt">sea</span>, <span class="hlt">sea</span> <span class="hlt">ice</span> can be classified as: landfast <span class="hlt">ice</span> zone, shear zone, and the marginal <span class="hlt">ice</span> zone. All <span class="hlt">ice</span> covers attenuate wave energy. Only long swells can penetrate deep into an <span class="hlt">ice</span> cover. Being closest to open water, wave propagation in the marginal <span class="hlt">ice</span> zone is the most complex to model. The physical appearance of <span class="hlt">sea</span> <span class="hlt">ice</span> in the marginal <span class="hlt">ice</span> zone varies. Grease <span class="hlt">ice</span>, pancake <span class="hlt">ice</span>, brash <span class="hlt">ice</span>, floe aggregates, and continuous <span class="hlt">ice</span> sheet may be found in this zone at different times and locations. These types of <span class="hlt">ice</span> are formed under different thermal-mechanical forcing. There are three classic models that describe wave propagation through an idealized <span class="hlt">ice</span> cover: mass loading, thin elastic plate, and viscous layer models. From physical arguments we may conjecture that mass loading model is suitable for disjoint aggregates of <span class="hlt">ice</span> floes much smaller than the wavelength, thin elastic plate model is suitable for a continuous <span class="hlt">ice</span> sheet, and the viscous layer model is suitable for grease <span class="hlt">ice</span>. For different <span class="hlt">sea</span> <span class="hlt">ice</span> types we may need different wave <span class="hlt">ice</span> interaction models. A recently proposed viscoelastic model is able to synthesize all three classic models into one. Under suitable limiting conditions it converges to the three previous models. The complete theoretical framework for evaluating wave propagation through various <span class="hlt">ice</span> covers need to be implemented in the operational ocean wave models. In this review, we introduce the <span class="hlt">sea</span> <span class="hlt">ice</span> types, previous wave <span class="hlt">ice</span> interaction models, wave attenuation mechanisms, the methods to calculate wave reflection and transmission between different <span class="hlt">ice</span> covers, and the effect of <span class="hlt">ice</span> floe breaking on shaping the <span class="hlt">sea</span> <span class="hlt">ice</span> morphology</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017GeCoA.213...17B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017GeCoA.213...17B"><span>Gypsum and hydrohalite dynamics in <span class="hlt">sea</span> <span class="hlt">ice</span> brines</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Butler, Benjamin M.; Papadimitriou, Stathys; Day, Sarah J.; Kennedy, Hilary</p> <p>2017-09-01</p> <p>Mineral authigenesis from their dissolved <span class="hlt">sea</span> salt matrix is an emergent feature of <span class="hlt">sea</span> <span class="hlt">ice</span> brines, fuelled by dramatic equilibrium solubility changes in the large sub-zero temperature range of this cryospheric system on the surface of high latitude oceans. The multi-electrolyte composition of seawater results in the potential for several minerals to precipitate in <span class="hlt">sea</span> <span class="hlt">ice</span>, each affecting the in-situ geochemical properties of the <span class="hlt">sea</span> <span class="hlt">ice</span> brine system, the habitat of sympagic biota. The solubility of two of these minerals, gypsum (CaSO4 ·2H2O) and hydrohalite (NaCl · 2H2O), was investigated in high ionic strength multi-electrolyte solutions at below-zero temperatures to examine their dissolution-precipitation dynamics in the <span class="hlt">sea</span> <span class="hlt">ice</span> brine system. The gypsum dynamics in <span class="hlt">sea</span> <span class="hlt">ice</span> were found to be highly dependent on the solubilities of mirabilite and hydrohalite between 0.2 and - 25.0 ° C. The hydrohalite solubility between - 14.3 and - 25.0 ° C exhibits a sharp change between undersaturated and supersaturated conditions, and, thus, distinct temperature fields of precipitation and dissolution in <span class="hlt">sea</span> <span class="hlt">ice</span>, with saturation occurring at - 22.9 ° C. The sharp changes in hydrohalite solubility at temperatures ⩽-22.9 °C result from the formation of an <span class="hlt">ice</span>-hydrohalite aggregate, which alters the structural properties of brine inclusions in cold <span class="hlt">sea</span> <span class="hlt">ice</span>. Favourable conditions for gypsum precipitation in <span class="hlt">sea</span> <span class="hlt">ice</span> were determined to occur in the region of hydrohalite precipitation below - 22.9 ° C and in conditions of metastable mirabilite supersaturation above - 22.9 ° C (investigated at - 7.1 and - 8.2 ° C here) but gypsum is unlikely to persist once mirabilite forms at these warmer (>-22.9 °C) temperatures. The dynamics of hydrohalite in <span class="hlt">sea</span> <span class="hlt">ice</span> brines based on its experimental solubility were consistent with that derived from thermodynamic modelling (FREZCHEM code) but the gypsum dynamics derived from the code were inconsistent with that indicated by its</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=PIA04300&hterms=sea+world&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dsea%2Bworld','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=PIA04300&hterms=sea+world&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dsea%2Bworld"><span><span class="hlt">Ice</span> Types in the Beaufort <span class="hlt">Sea</span>, Alaska</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p></p> <p>2003-01-01</p> <p><p/> Determining the amount and type of <span class="hlt">sea</span> <span class="hlt">ice</span> in the polar oceans is crucial to improving our knowledge and understanding of polar weather and long term climate fluctuations. These views from two satellite remote sensing instruments; the synthetic aperture radar (SAR) on board the RADARSAT satellite and the Multi-angle Imaging SpectroRadiometer (MISR), illustrate different methods that may be used to assess <span class="hlt">sea</span> <span class="hlt">ice</span> type. <span class="hlt">Sea</span> <span class="hlt">ice</span> in the Beaufort <span class="hlt">Sea</span> off the north coast of Alaska was classified and mapped in these concurrent images acquired March 19, 2001 and mapped to the same geographic area.<p/>To identify <span class="hlt">sea</span> <span class="hlt">ice</span> types, the National Oceanic and Atmospheric Administration (NOAA) National <span class="hlt">Ice</span> Center constructs <span class="hlt">ice</span> charts using several data sources including RADARSAT SAR images such as the one shown at left. SAR classifies <span class="hlt">sea</span> <span class="hlt">ice</span> types primarily by how the surface and subsurface roughness influence radar backscatter. In the SAR image, white lines delineate different <span class="hlt">sea</span> <span class="hlt">ice</span> zones as identified by the National <span class="hlt">Ice</span> Center. Regions of mostly multi-year <span class="hlt">ice</span> (A) are separated from regions with large amounts of first year and younger <span class="hlt">ice</span> (B-D), and the dashed white line at bottom marks the coastline. In general, <span class="hlt">sea</span> <span class="hlt">ice</span> types that exhibit increased radar backscatter appear bright in SAR and are identified as rougher, older <span class="hlt">ice</span> types. Younger, smoother <span class="hlt">ice</span> types appear dark to SAR. Near the top of the SAR image, however, red arrows point to bright areas in which large, crystalline 'frost flowers' have formed on young, thin <span class="hlt">ice</span>, causing this young <span class="hlt">ice</span> type to exhibit an increased radar backscatter. Frost flowers are strongly backscattering at radar wavelengths (cm) due to both surface roughness and the high salinity of frost flowers, which causes them to be highly reflective to radar energy.<p/>Surface roughness is also registered by MISR, although the roughness observed is at a different spatial scale. Older, rougher <span class="hlt">ice</span> areas are predominantly backward scattering to</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26347538','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26347538"><span>Processes controlling surface, bottom and lateral melt of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> in a state of the art <span class="hlt">sea</span> <span class="hlt">ice</span> model.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Tsamados, Michel; Feltham, Daniel; Petty, Alek; Schroeder, David; Flocco, Daniela</p> <p>2015-10-13</p> <p>We present a modelling study of processes controlling the summer melt of the Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> cover. We perform a sensitivity study and focus our interest on the thermodynamics at the <span class="hlt">ice</span>-atmosphere and <span class="hlt">ice</span>-ocean interfaces. We use the Los Alamos community <span class="hlt">sea</span> <span class="hlt">ice</span> model CICE, and additionally implement and test three new parametrization schemes: (i) a prognostic mixed layer; (ii) a three equation boundary condition for the salt and heat flux at the <span class="hlt">ice</span>-ocean interface; and (iii) a new lateral melt parametrization. Recent additions to the CICE model are also tested, including explicit melt ponds, a form drag parametrization and a halodynamic brine drainage scheme. The various <span class="hlt">sea</span> <span class="hlt">ice</span> parametrizations tested in this sensitivity study introduce a wide spread in the simulated <span class="hlt">sea</span> <span class="hlt">ice</span> characteristics. For each simulation, the total melt is decomposed into its surface, bottom and lateral melt components to assess the processes driving melt and how this varies regionally and temporally. Because this study quantifies the relative importance of several processes in driving the summer melt of <span class="hlt">sea</span> <span class="hlt">ice</span>, this work can serve as a guide for future research priorities. © 2015 The Author(s).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JGRD..12210820G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JGRD..12210820G"><span>Spring snow conditions on Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> north of Svalbard, during the Norwegian Young <span class="hlt">Sea</span> <span class="hlt">ICE</span> (N-<span class="hlt">ICE</span>2015) expedition</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gallet, Jean-Charles; Merkouriadi, Ioanna; Liston, Glen E.; Polashenski, Chris; Hudson, Stephen; Rösel, Anja; Gerland, Sebastian</p> <p>2017-10-01</p> <p>Snow is crucial over <span class="hlt">sea</span> <span class="hlt">ice</span> due to its conflicting role in reflecting the incoming solar energy and reducing the heat transfer so that its temporal and spatial variability are important to estimate. During the Norwegian Young <span class="hlt">Sea</span> <span class="hlt">ICE</span> (N-<span class="hlt">ICE</span>2015) campaign, snow physical properties and variability were examined, and results from April until mid-June 2015 are presented here. Overall, the snow thickness was about 20 cm higher than the climatology for second-year <span class="hlt">ice</span>, with an average of 55 ± 27 cm and 32 ± 20 cm on first-year <span class="hlt">ice</span>. The average density was 350-400 kg m-3 in spring, with higher values in June due to melting. Due to flooding in March, larger variability in snow water equivalent was observed. However, the snow structure was quite homogeneous in spring due to warmer weather and lower amount of storms passing over the field camp. The snow was mostly consisted of wind slab, faceted, and depth hoar type crystals with occasional fresh snow. These observations highlight the more dynamic character of evolution of snow properties over <span class="hlt">sea</span> <span class="hlt">ice</span> compared to previous observations, due to more variable <span class="hlt">sea</span> <span class="hlt">ice</span> and weather conditions in this area. The snowpack was isothermal as early as 10 June with the first onset of melt clearly identified in early June. Based on our observations, we estimate than snow could be accurately represented by a three to four layers modeling approach, in order to better consider the high variability of snow thickness and density together with the rapid metamorphose of the snow in springtime.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006AGUFMED43A0925B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006AGUFMED43A0925B"><span>Visualizing Glaciers and <span class="hlt">Sea</span> <span class="hlt">Ice</span> via Google Earth</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ballagh, L. M.; Fetterer, F.; Haran, T. M.; Pharris, K.</p> <p>2006-12-01</p> <p>The NOAA team at NSIDC manages over 60 distinct cryospheric and related data products. With an emphasis on data rescue and in situ data, these products hold value for both the scientific and non-scientific user communities. The overarching goal of this presentation is to promote products from two components of the cryosphere (glaciers and <span class="hlt">sea</span> <span class="hlt">ice</span>). Our Online Glacier Photograph Database contains approximately 3,000 photographs taken over many decades, exemplifying change in the glacier terminus over time. The <span class="hlt">sea</span> <span class="hlt">ice</span> product shows <span class="hlt">sea</span> <span class="hlt">ice</span> extent and concentration along with anomalies and trends. This <span class="hlt">Sea</span> <span class="hlt">Ice</span> Index product, which starts in 1979 and is updated monthly, provides visuals of the current state of <span class="hlt">sea</span> <span class="hlt">ice</span> in both hemispheres with trends and anomalies. The long time period covered by the data set means that many of the trends in <span class="hlt">ice</span> extent and concentration shown in this product are statistically significant despite the large natural variability in <span class="hlt">sea</span> <span class="hlt">ice</span>. The minimum arctic <span class="hlt">sea</span> <span class="hlt">ice</span> extent has been a record low in September 2002 and 2005, contributing to an accelerated trend in <span class="hlt">sea</span> <span class="hlt">ice</span> reduction. With increasing world-wide interest in indicators of global climate change, and the upcoming International Polar Year, these data products are of interest to a broad audience. To further extend the impact of these data, we have made them viewable through Google Earth via the Keyhole Markup Language (KML). This presents an opportunity to branch out to a more diverse audience by using a new and innovative tool that allows spatial representation of data of significant scientific and educational interest.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20040015192&hterms=Parkinsons&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3DParkinsons','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20040015192&hterms=Parkinsons&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3DParkinsons"><span>Observed and Modeled Trends in Southern Ocean <span class="hlt">Sea</span> <span class="hlt">Ice</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Parkinson, Claire L.</p> <p>2003-01-01</p> <p>Conceptual models and global climate model (GCM) simulations have both indicated the likelihood of an enhanced sensitivity to climate change in the polar regions, derived from the positive feedbacks brought about by the polar abundance of snow and <span class="hlt">ice</span> surfaces. Some models further indicate that the changes in the polar regions can have a significant impact globally. For instance, 37% of the temperature sensitivity to a doubling of atmospheric CO2 in simulations with the GCM of the Goddard Institute for Space Studies (GISS) is attributable exclusively to inclusion of <span class="hlt">sea</span> <span class="hlt">ice</span> variations in the model calculations. Both <span class="hlt">sea</span> <span class="hlt">ice</span> thickness and <span class="hlt">sea</span> <span class="hlt">ice</span> extent decrease markedly in the doubled CO, case, thereby allowing the <span class="hlt">ice</span> feedbacks to occur. Stand-alone <span class="hlt">sea</span> <span class="hlt">ice</span> models have shown Southern Ocean hemispherically averaged winter <span class="hlt">ice</span>-edge retreats of 1.4 deg latitude for each 1 K increase in atmospheric temperatures. Observations, however, show a much more varied Southern Ocean <span class="hlt">ice</span> cover, both spatially and temporally, than many of the modeled expectations. In fact, the satellite passive-microwave record of Southern Ocean <span class="hlt">sea</span> <span class="hlt">ice</span> since late 1978 has revealed overall increases rather than decreases in <span class="hlt">ice</span> extents, with <span class="hlt">ice</span> extent trends on the order of 11,000 sq km/year. When broken down spatially, the positive trends are strongest in the Ross <span class="hlt">Sea</span>, while the trends are negative in the Bellingshausen/Amundsen <span class="hlt">Seas</span>. Greater spatial detail can be obtained by examining trends in the length of the <span class="hlt">sea</span> <span class="hlt">ice</span> season, and those trends show a coherent picture of shortening <span class="hlt">sea</span> <span class="hlt">ice</span> seasons throughout almost the entire Bellingshausen and Amundsen <span class="hlt">Seas</span> to the west of the Antarctic Peninsula and in the far western Weddell <span class="hlt">Sea</span> immediately to the east of the Peninsula, with lengthening <span class="hlt">sea</span> <span class="hlt">ice</span> seasons around much of the rest of the continent. This pattern corresponds well with the spatial pattern of temperature trends, as the Peninsula region is the one region in the Antarctic with a strong</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018JGRC..123.1406T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018JGRC..123.1406T"><span>An Examination of the <span class="hlt">Sea</span> <span class="hlt">Ice</span> Rheology for Seasonal <span class="hlt">Ice</span> Zones Based on <span class="hlt">Ice</span> Drift and Thickness Observations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Toyota, Takenobu; Kimura, Noriaki</p> <p>2018-02-01</p> <p>The validity of the <span class="hlt">sea</span> <span class="hlt">ice</span> rheological model formulated by Hibler (1979), which is widely used in present numerical <span class="hlt">sea</span> <span class="hlt">ice</span> models, is examined for the <span class="hlt">Sea</span> of Okhotsk as an example of the seasonal <span class="hlt">ice</span> zone (SIZ), based on satellite-derived <span class="hlt">sea</span> <span class="hlt">ice</span> velocity, concentration and thickness. Our focus was the formulation of the yield curve, the shape of which can be estimated from <span class="hlt">ice</span> drift pattern based on the energy equation of deformation, while the strength of the <span class="hlt">ice</span> cover that determines its magnitude was evaluated using <span class="hlt">ice</span> concentration and thickness data. <span class="hlt">Ice</span> drift was obtained with a grid spacing of 37.5 km from the AMSR-E 89 GHz brightness temperature using a maximum cross-correlation method. The <span class="hlt">ice</span> thickness was obtained with a spatial resolution of 100 m from a regression of the PALSAR backscatter coefficients with <span class="hlt">ice</span> thickness. To assess scale dependence, the <span class="hlt">ice</span> drift data derived from a coastal radar covering a 70 km range in the southernmost <span class="hlt">Sea</span> of Okhotsk were similarly analyzed. The results obtained were mostly consistent with Hibler's formulation that was based on the Arctic Ocean on both scales with no dependence on a time scale, and justify the treatment of <span class="hlt">sea</span> <span class="hlt">ice</span> as a plastic material, with an elliptical shaped yield curve to some extent. However, it also highlights the difficulty in parameterizing sub-grid scale ridging in the model because grid scale <span class="hlt">ice</span> velocities reduce the deformation magnitude by half due to the large variation of the deformation field in the SIZ.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20030056665&hterms=Parkinsons&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3DParkinsons','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20030056665&hterms=Parkinsons&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3DParkinsons"><span>30-Year Satellite Record Reveals Accelerated Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> Loss, Antarctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> Trend Reversal</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Cavalieri, Donald J.; Parkinson, C. L.; Vinnikov, K. Y.</p> <p>2003-01-01</p> <p>Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> extent decreased by 0.30 plus or minus 0.03 x 10(exp 6) square kilometers per decade from 1972 through 2002, but decreased by 0.36 plus or minus 0.05 x 10(exp 6) square kilometers per decade from 1979 through 2002, indicating an acceleration of 20% in the rate of decrease. In contrast to the Arctic, the Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> extent decreased dramatically over the period 1973-1977, then gradually increased, with an overall 30-year trend of -0.15 plus or minus 0.08 x 10(exp 6) square kilometers per 10yr. The trend reversal is attributed to a large positive anomaly in Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> extent observed in the early 1970's.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19870007787&hterms=marginal&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dmarginal','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19870007787&hterms=marginal&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dmarginal"><span>Microwave properties of <span class="hlt">sea</span> <span class="hlt">ice</span> in the marginal <span class="hlt">ice</span> zone</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Onstott, R. G.; Larson, R. W.</p> <p>1986-01-01</p> <p>Active microwave properties of summer <span class="hlt">sea</span> <span class="hlt">ice</span> were measured. Backscatter data were acquired at frequencies from 1 to 17 GHz, at angles from 0 to 70 deg from vertical, and with like and cross antenna polarizations. Results show that melt-water, snow thickness, snowpack morphology, snow surface roughness, <span class="hlt">ice</span> surface roughness, and deformation characteristics are the fundamental scene parameters which govern the summer <span class="hlt">sea</span> <span class="hlt">ice</span> backscatter response. A thick, wet snow cover dominates the backscatter response and masks any <span class="hlt">ice</span> sheet features below. However, snow and melt-water are not distributed uniformly and the stage of melt may also be quite variable. These nonuniformities related to <span class="hlt">ice</span> type are not necessarily well understood and produce unique microwave signature characteristics.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li class="active"><span>10</span></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_10 --> <div id="page_11" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li class="active"><span>11</span></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="201"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018E%26PSL.481...61C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018E%26PSL.481...61C"><span>Seasonal <span class="hlt">sea</span> <span class="hlt">ice</span> cover during the warm Pliocene: Evidence from the Iceland <span class="hlt">Sea</span> (ODP Site 907)</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Clotten, Caroline; Stein, Ruediger; Fahl, Kirsten; De Schepper, Stijn</p> <p>2018-01-01</p> <p><span class="hlt">Sea</span> <span class="hlt">ice</span> is a critical component in the Arctic and global climate system, yet little is known about its extent and variability during past warm intervals, such as the Pliocene (5.33-2.58 Ma). Here, we present the first multi-proxy (IP25, sterols, alkenones, palynology) <span class="hlt">sea</span> <span class="hlt">ice</span> reconstructions for the Late Pliocene Iceland <span class="hlt">Sea</span> (ODP Site 907). Our interpretation of a seasonal <span class="hlt">sea</span> <span class="hlt">ice</span> cover with occasional <span class="hlt">ice</span>-free intervals between 3.50-3.00 Ma is supported by reconstructed alkenone-based summer <span class="hlt">sea</span> surface temperatures. As evidenced from brassicasterol and dinosterol, primary productivity was low between 3.50 and 3.00 Ma and the site experienced generally oligotrophic conditions. The East Greenland Current (and East Icelandic Current) may have transported <span class="hlt">sea</span> <span class="hlt">ice</span> into the Iceland <span class="hlt">Sea</span> and/or brought cooler and fresher waters favoring local <span class="hlt">sea</span> <span class="hlt">ice</span> formation. Between 3.00 and 2.40 Ma, the Iceland <span class="hlt">Sea</span> is mainly <span class="hlt">sea</span> <span class="hlt">ice</span>-free, but seasonal <span class="hlt">sea</span> <span class="hlt">ice</span> occurred between 2.81 and 2.74 Ma. <span class="hlt">Sea</span> <span class="hlt">ice</span> extending into the Iceland <span class="hlt">Sea</span> at this time may have acted as a positive feedback for the build-up of the Greenland <span class="hlt">Ice</span> Sheet (GIS), which underwent a major expansion ∼2.75 Ma. Thereafter, most likely a stable <span class="hlt">sea</span> <span class="hlt">ice</span> edge developed close to Greenland, possibly changing together with the expansion and retreat of the GIS and affecting the productivity in the Iceland <span class="hlt">Sea</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..17.9654S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..17.9654S"><span>Micromechanics of <span class="hlt">sea</span> <span class="hlt">ice</span> gouge in shear zones</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sammonds, Peter; Scourfield, Sally; Lishman, Ben</p> <p>2015-04-01</p> <p>The deformation of <span class="hlt">sea</span> <span class="hlt">ice</span> is a key control on the Arctic Ocean dynamics. Shear displacement on all scales is an important deformation process in the <span class="hlt">sea</span> cover. Shear deformation is a dominant mechanism from the scale of basin-scale shear lineaments, through floe-floe interaction and block sliding in <span class="hlt">ice</span> ridges through to the micro-scale mechanics. Shear deformation will not only depend on the speed of movement of <span class="hlt">ice</span> surfaces but also the degree that the surfaces have bonded during thermal consolidation and compaction. Recent observations made during fieldwork in the Barents <span class="hlt">Sea</span> show that shear produces a gouge similar to a fault gouge in a shear zone in the crust. A range of sizes of gouge are exhibited. The consolidation of these fragments has a profound influence on the shear strength and the rate of the processes involved. We review experimental results in <span class="hlt">sea</span> <span class="hlt">ice</span> mechanics from mid-scale experiments, conducted in the Hamburg model ship <span class="hlt">ice</span> tank, simulating <span class="hlt">sea</span> <span class="hlt">ice</span> floe motion and interaction and compare these with laboratory experiments on <span class="hlt">ice</span> friction done in direct shear, and upscale to field measurement of <span class="hlt">sea</span> <span class="hlt">ice</span> friction and gouge deformation made during experiments off Svalbard. We find that consolidation, fragmentation and bridging play important roles in the overall dynamics and fit the model of Sammis and Ben-Zion, developed for understanding the micro-mechanics of rock fault gouge, to the <span class="hlt">sea</span> <span class="hlt">ice</span> problem.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMPP54A..03P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMPP54A..03P"><span>Late Holocene <span class="hlt">sea</span> <span class="hlt">ice</span> conditions in Herald Canyon, Chukchi <span class="hlt">Sea</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Pearce, C.; O'Regan, M.; Rattray, J. E.; Hutchinson, D. K.; Cronin, T. M.; Gemery, L.; Barrientos, N.; Coxall, H.; Smittenberg, R.; Semiletov, I. P.; Jakobsson, M.</p> <p>2017-12-01</p> <p><span class="hlt">Sea</span> <span class="hlt">ice</span> in the Arctic Ocean has been in steady decline in recent decades and, based on satellite data, the retreat is most pronounced in the Chukchi and Beaufort <span class="hlt">seas</span>. Historical observations suggest that the recent changes were unprecedented during the last 150 years, but for a longer time perspective, we rely on the geological record. For this study, we analyzed sediment samples from two piston cores from Herald Canyon in the Chukchi <span class="hlt">Sea</span>, collected during the 2014 SWERUS-C3 Arctic Ocean Expedition. The Herald Canyon is a local depression across the Chukchi Shelf, and acts as one of the main pathways for Pacific Water to the Arctic Ocean after entering through the narrow and shallow Bering Strait. The study site lies at the modern-day seasonal <span class="hlt">sea</span> <span class="hlt">ice</span> minimum edge, and is thus an ideal location for the reconstruction of past <span class="hlt">sea</span> <span class="hlt">ice</span> variability. Both sediment cores contain late Holocene deposits characterized by high sediment accumulation rates (100-300 cm/kyr). Core 2-PC1 from the shallow canyon flank (57 m water depth) is 8 meter long and extends back to 4200 cal yrs BP, while the upper 3 meters of Core 4-PC1 from the central canyon (120 mwd) cover the last 3000 years. The chronologies of the cores are based on radiocarbon dates and the 3.6 ka Aniakchak CFE II tephra, which is used as an absolute age marker to calculate the marine radiocarbon reservoir age. Analysis of biomarkers for <span class="hlt">sea</span> <span class="hlt">ice</span> and surface water productivity indicate stable <span class="hlt">sea</span> <span class="hlt">ice</span> conditions throughout the entire late Holocene, ending with an abrupt increase of phytoplankton sterols in the very top of both sediment sequences. The shift is accompanied by a sudden increase in coarse sediments (> 125 µm) and a minor change in δ13Corg. We interpret this transition in the top sediments as a community turnover in primary producers from <span class="hlt">sea</span> <span class="hlt">ice</span> to open water biota. Most importantly, our results indicate that the ongoing rapid <span class="hlt">ice</span> retreat in the Chukchi <span class="hlt">Sea</span> of recent decades was unprecedented during the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..17.9552K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..17.9552K"><span>Palaeo-<span class="hlt">ice</span> stream pathways in the easternmost Amundsen <span class="hlt">Sea</span> Embayment, West Antarctica</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Klages, Johann P.; Kuhn, Gerhard; Graham, Alastair G. C.; Smith, James A.; Hillenbrand, Claus-Dieter; Nitsche, Frank O.; Larter, Rob D.; Gohl, Karsten</p> <p>2015-04-01</p> <p>Multibeam swath bathymetry datasets collected over the past two decades have been compiled to identify palaeo-<span class="hlt">ice</span> stream pathways in the easternmost Amundsen <span class="hlt">Sea</span> Embayment. We mapped 3010 glacial landforms to reconstruct palaeo-<span class="hlt">ice</span> flow in the ~250 km-long Abbot Glacial Trough that was occupied by a large palaeo-<span class="hlt">ice</span> stream, fed by two tributaries (Cosgrove and Abbot) that reached the continental shelf edge during the last maximum <span class="hlt">ice</span>-sheet advance. The mapping has enabled a clear differentiation between glacial landforms interpreted as indicative of wet- (e.g. mega-scale glacial lineations) and cold-based <span class="hlt">ice</span> (e.g. hill-hole pairs) during the last glaciation of the continental shelf. Both the regions of fast palaeo-<span class="hlt">ice</span> flow within the palaeo-<span class="hlt">ice</span> stream troughs, and the regions of slow palaeo-<span class="hlt">ice</span> flow on <span class="hlt">adjacent</span> seafloor highs (referred to as inter-<span class="hlt">ice</span> stream ridges) additionally record glacial landforms such as grounding-zone wedges and recessional moraines that indicate grounding line stillstands of the <span class="hlt">ice</span> sheet during the last deglaciation from the shelf. As the palaeo-<span class="hlt">ice</span> stream flowed along a trough with variable geometry and variable subglacial substrate, it appears that trough sections characterized by constrictions and outcropping hard substrate that changes the bed gradient, led the pace of grounding-line retreat to slow and subsequently pause, resulting in the deposition of grounding-zone wedges. The stepped retreat recorded within the Abbot Glacial Trough corresponds well to post-glacial stepped retreat interpreted for the neighbouring Pine Island-Thwaites Palaeo-<span class="hlt">Ice</span> Stream trough, thus suggesting a uniform pattern of episodic retreat across the eastern Amundsen <span class="hlt">Sea</span> Embayment. The correlation of episodic retreat features with geological boundaries further emphasises the significance of subglacial geology in steering <span class="hlt">ice</span> stream flow. Our new geomorphological map of the easternmost Amundsen <span class="hlt">Sea</span> Embayment resolves the pathways of palaeo-<span class="hlt">ice</span> streams that</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014SPIE.9299E..03J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014SPIE.9299E..03J"><span>Development of <span class="hlt">sea</span> <span class="hlt">ice</span> monitoring with aerial remote sensing technology</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Jiang, Xuhui; Han, Lei; Dong, Liang; Cui, Lulu; Bie, Jun; Fan, Xuewei</p> <p>2014-11-01</p> <p>In the north China <span class="hlt">Sea</span> district, <span class="hlt">sea</span> <span class="hlt">ice</span> disaster is very serious every winter, which brings a lot of adverse effects to shipping transportation, offshore oil exploitation, and coastal engineering. In recent years, along with the changing of global climate, the <span class="hlt">sea</span> <span class="hlt">ice</span> situation becomes too critical. The monitoring of <span class="hlt">sea</span> <span class="hlt">ice</span> is playing a very important role in keeping human life and properties in safety, and undertaking of marine scientific research. The methods to monitor <span class="hlt">sea</span> <span class="hlt">ice</span> mainly include: first, shore observation; second, icebreaker monitoring; third, satellite remote sensing; and then aerial remote sensing monitoring. The marine station staffs use relevant equipments to monitor the <span class="hlt">sea</span> <span class="hlt">ice</span> in the shore observation. The icebreaker monitoring means: the workers complete the test of the properties of <span class="hlt">sea</span> <span class="hlt">ice</span>, such as density, salinity and mechanical properties. MODIS data and NOAA data are processed to get <span class="hlt">sea</span> <span class="hlt">ice</span> charts in the satellite remote sensing means. Besides, artificial visual monitoring method and some airborne remote sensors are adopted in the aerial remote sensing to monitor <span class="hlt">sea</span> <span class="hlt">ice</span>. Aerial remote sensing is an important means in <span class="hlt">sea</span> <span class="hlt">ice</span> monitoring because of its strong maneuverability, wide watching scale, and high resolution. In this paper, several methods in the <span class="hlt">sea</span> <span class="hlt">ice</span> monitoring using aerial remote sensing technology are discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19760039698&hterms=1103&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3D%2526%25231103','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19760039698&hterms=1103&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3D%2526%25231103"><span>Beaufort <span class="hlt">Sea</span> <span class="hlt">ice</span> zones as delineated by microwave imagery</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Campbell, W. J.; Gloersen, P.; Webster, W. J.; Wilheit, T. T.; Ramseier, R. O.</p> <p>1976-01-01</p> <p>Microwave and infrared data were obtained from a research aircraft over the Beaufort <span class="hlt">Sea</span> <span class="hlt">ice</span> from the shoreline of Harrison Bay northward to a latitude of almost 81 deg N. The data acquired were compared with microwave data obtained on the surface at an approximate position of 75 deg N, 150 deg W. Over this north-south transect of the polar <span class="hlt">ice</span> canopy it was discovered that the <span class="hlt">sea</span> <span class="hlt">ice</span> could be divided into five distinct zones. The shorefast <span class="hlt">sea</span> <span class="hlt">ice</span> was found to consist uniformly of first-year <span class="hlt">sea</span> <span class="hlt">ice</span>. The second zone was found to be a mixture of first-year <span class="hlt">sea</span> <span class="hlt">ice</span>, medium size multiyear floes, and many recently refrozen leads, polynyas, and open water; considerable shearing activity was evident in this zone. The third zone was a mixture of first-year and multiyear <span class="hlt">sea</span> <span class="hlt">ice</span> which had a uniform microwave signature. The fourth zone was found to be a mixture of first-year <span class="hlt">sea</span> <span class="hlt">ice</span> and medium-to-large size multiyear floes which was similar in composition to the second zone. The fifth zone was almost exclusively multiyear <span class="hlt">ice</span> extending to the North Pole.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014TCD.....8.1517K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014TCD.....8.1517K"><span>About uncertainties in <span class="hlt">sea</span> <span class="hlt">ice</span> thickness retrieval from satellite radar altimetry: results from the ESA-CCI <span class="hlt">Sea</span> <span class="hlt">Ice</span> ECV Project Round Robin Exercise</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kern, S.; Khvorostovsky, K.; Skourup, H.; Rinne, E.; Parsakhoo, Z. S.; Djepa, V.; Wadhams, P.; Sandven, S.</p> <p>2014-03-01</p> <p>One goal of the European Space Agency Climate Change Initiative <span class="hlt">sea</span> <span class="hlt">ice</span> Essential Climate Variable project is to provide a quality controlled 20 year long data set of Arctic Ocean winter-time <span class="hlt">sea</span> <span class="hlt">ice</span> thickness distribution. An important step to achieve this goal is to assess the accuracy of <span class="hlt">sea</span> <span class="hlt">ice</span> thickness retrieval based on satellite radar altimetry. For this purpose a data base is created comprising <span class="hlt">sea</span> <span class="hlt">ice</span> freeboard derived from satellite radar altimetry between 1993 and 2012 and collocated observations of snow and <span class="hlt">sea</span> <span class="hlt">ice</span> freeboard from Operation <span class="hlt">Ice</span> Bridge (OIB) and CryoSat Validation Experiment (CryoVEx) air-borne campaigns, of <span class="hlt">sea</span> <span class="hlt">ice</span> draft from moored and submarine Upward Looking Sonar (ULS), and of snow depth from OIB campaigns, Advanced Microwave Scanning Radiometer aboard EOS (AMSR-E) and the Warren Climatology (Warren et al., 1999). An inter-comparison of the snow depth data sets stresses the limited usefulness of Warren climatology snow depth for freeboard-to-thickness conversion under current Arctic Ocean conditions reported in other studies. This is confirmed by a comparison of snow freeboard measured during OIB and CryoVEx and snow freeboard computed from radar altimetry. For first-year <span class="hlt">ice</span> the agreement between OIB and AMSR-E snow depth within 0.02 m suggests AMSR-E snow depth as an appropriate alternative. Different freeboard-to-thickness and freeboard-to-draft conversion approaches are realized. The mean observed ULS <span class="hlt">sea</span> <span class="hlt">ice</span> draft agrees with the mean <span class="hlt">sea</span> <span class="hlt">ice</span> draft computed from radar altimetry within the uncertainty bounds of the data sets involved. However, none of the realized approaches is able to reproduce the seasonal cycle in <span class="hlt">sea</span> <span class="hlt">ice</span> draft observed by moored ULS satisfactorily. A sensitivity analysis of the freeboard-to-thickness conversion suggests: in order to obtain <span class="hlt">sea</span> <span class="hlt">ice</span> thickness as accurate as 0.5 m from radar altimetry, besides a freeboard estimate with centimetre accuracy, an <span class="hlt">ice</span>-type dependent <span class="hlt">sea</span> <span class="hlt">ice</span> density is as mandatory</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1991JGR....9618411L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1991JGR....9618411L"><span><span class="hlt">Sea</span> <span class="hlt">ice</span> ridging in the eastern Weddell <span class="hlt">Sea</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lytle, V. I.; Ackley, S. F.</p> <p>1991-10-01</p> <p>In August 1986, <span class="hlt">sea</span> <span class="hlt">ice</span> ridge heights and spatial frequency in the eastern Weddell <span class="hlt">Sea</span> were measured using a ship-based acoustical sounder. Using a minimum ridge sail height of 0.75 m, a total of 933 ridges were measured along a track length of 415 km. The ridge frequency varied from 0.4 to 10.5 ridges km-1. The mean height of the ridges was found to be about 1.1 m regardless of the ridge frequency. These results are compared to other ridging statistics from the Ross <span class="hlt">Sea</span> and found to be similar. Comparison with Arctic data, however, indicates that the height and frequency of the ridges are considerably less in the Weddell <span class="hlt">Sea</span> than in the Arctic. Whereas in the Arctic the mean ridge height tends to increase with the ridge frequency, we found that this was not the case in the Weddell <span class="hlt">Sea</span>, where the mean ridge height remained constant irrespective of the ridge frequency. Estimates of the contribution of deformed <span class="hlt">ice</span> to the total <span class="hlt">ice</span> thickness are generally low except for a single 53-km section where the ridge frequency increased by an order of magnitude. This resulted in an increase in the equivalent mean <span class="hlt">ice</span> thickness due to ridging from 0.04 m in the less deformed areas to 0.45 m in the highly deformed section. These values were found to be consistent with values obtained from drilled profile lines during the same cruise.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70193618','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70193618"><span>Holocene <span class="hlt">sea</span> surface temperature and <span class="hlt">sea</span> <span class="hlt">ice</span> extent in the Okhotsk and Bering <span class="hlt">Seas</span></span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Harada, Naomi; Katsuki, Kota; Nakagawa, Mitsuhiro; Matsumoto, Akiko; Seki, Osamu; Addison, Jason A.; Finney, Bruce P.; Sato, Miyako</p> <p>2014-01-01</p> <p>Accurate prediction of future climate requires an understanding of the mechanisms of the Holocene climate; however, the driving forces, mechanisms, and processes of climate change in the Holocene associated with different time scales remain unclear. We investigated the drivers of Holocene <span class="hlt">sea</span> surface temperature (SST) and <span class="hlt">sea</span> <span class="hlt">ice</span> extent in the North Pacific Ocean, and the Okhotsk and Bering <span class="hlt">Seas</span>, as inferred from sediment core records, by using the alkenone unsaturation index as a biomarker of SST and abundances of <span class="hlt">sea</span> <span class="hlt">ice</span>-related diatoms (F. cylindrus and F. oceanica) as an indicator of <span class="hlt">sea</span> <span class="hlt">ice</span> extent to explore controlling mechanisms in the high-latitude Pacific. Temporal changes in alkenone content suggest that alkenone production was relatively high during the middle Holocene in the Okhotsk <span class="hlt">Sea</span> and the western North Pacific, but highest in the late Holocene in the eastern Bering <span class="hlt">Sea</span> and the eastern North Pacific. The Holocene variations of alkenone-SSTs at sites near Kamchatka in the Northwest Pacific, as well as in the western and eastern regions of the Bering <span class="hlt">Sea</span>, and in the eastern North Pacific track the changes of Holocene summer insolation at 50°N, but at other sites in the western North Pacific, in the southern Okhotsk <span class="hlt">Sea</span>, and the eastern Bering <span class="hlt">Sea</span> they do not. In addition to insolation, other atmosphere and ocean climate drivers, such as <span class="hlt">sea</span> <span class="hlt">ice</span> distribution and changes in the position and activity of the Aleutian Low, may have systematically influenced the timing and magnitude of warming and cooling during the Holocene within the subarctic North Pacific. Periods of high <span class="hlt">sea</span> <span class="hlt">ice</span> extent in both the Okhotsk and Bering <span class="hlt">Seas</span> may correspond to some periods of frequent or strong winter–spring dust storms in the Mongolian Gobi Desert, particularly one centered at ∼4–3 thousand years before present (kyr BP). Variation in storm activity in the Mongolian Gobi Desert region may reflect changes in the strength and positions of the Aleutian Low and Siberian</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C32B..05B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C32B..05B"><span>Expanding Antarctic <span class="hlt">Sea</span> <span class="hlt">Ice</span>: Anthropogenic or Natural Variability?</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bitz, C. M.</p> <p>2016-12-01</p> <p>Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> extent has increased over the last 36 years according to the satellite record. Concurrent with Antarctic <span class="hlt">sea-ice</span> expansion has been broad cooling of the Southern Ocean <span class="hlt">sea</span>-surface temperature. Not only are Southern Ocean <span class="hlt">sea</span> <span class="hlt">ice</span> and SST trends at odds with expectations from greenhouse gas-induced warming, the trend patterns are not reproduced in historical simulations with comprehensive global climate models. While a variety of different factors may have contributed to the observed trends in recent decades, we propose that it is atmospheric circulation changes - and the changes in ocean circulation they induce - that have emerged as the most likely cause of the observed Southern Ocean <span class="hlt">sea</span> <span class="hlt">ice</span> and SST trends. I will discuss deficiencies in models that could explain their incorrect response. In addition, I will present results from a series of experiments where the Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> and ocean are forced by atmospheric perturbations imposed within a coupled climate model. Figure caption: Linear trends of annual-mean SST (left) and annual-mean <span class="hlt">sea-ice</span> concentration (right) over 1980-2014. SST is from NOAA's Optimum Interpolation SST dataset (version 2; Reynolds et al. 2002). <span class="hlt">Sea-ice</span> concentration is from passive microwave observations using the NASA Team algorithm. Only the annual means are shown here for brevity and because the signal to noise is greater than in the seasonal means. Figure from Armour and Bitz (2015).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA123762','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA123762"><span>The Growth, Structure, and Properties of <span class="hlt">Sea</span> <span class="hlt">Ice</span>,</span></a></p> <p><a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>1982-11-01</p> <p>First, the natural range of temperatures at which <span class="hlt">sea</span> <span class="hlt">ice</span> exists is just a few degrees off its melting point. In fact, <span class="hlt">sea</span> <span class="hlt">ice</span> normally is only...surface of lakes and <span class="hlt">seas</span>. If <span class="hlt">ice</span> sank into its melt, as do most solids, there would be a tendency for natural water bodies to freeze completely to...I I I -c 1 I II I I 02 b . Figure 1. Structure of <span class="hlt">ice</span> I. The fact that ordinary <span class="hlt">ice</span> is such an open, low density solid also suggests that</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C21A0652H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C21A0652H"><span>NWS Alaska <span class="hlt">Sea</span> <span class="hlt">Ice</span> Program: Operations, Customer Support & Challenges</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Heim, R.; Schreck, M. B.</p> <p>2016-12-01</p> <p>The National Weather Service's Alaska <span class="hlt">Sea</span> <span class="hlt">Ice</span> Program is designed to service customers and partners operating and planning operations within Alaska waters. The Alaska <span class="hlt">Sea</span> <span class="hlt">Ice</span> Program offers daily <span class="hlt">sea</span> <span class="hlt">ice</span> and <span class="hlt">sea</span> surface temperature analysis products. The program also delivers a five day <span class="hlt">sea</span> <span class="hlt">ice</span> forecast 3 times each week, provides a 3 month <span class="hlt">sea</span> <span class="hlt">ice</span> outlook at the end of each month, and has staff available to respond to <span class="hlt">sea</span> <span class="hlt">ice</span> related information inquiries. These analysis and forecast products are utilized by many entities around the state of Alaska and nationally for safety of navigation and community strategic planning. The list of current customers stem from academia and research institutions, to local state and federal agencies, to resupply barges, to coastal subsistence hunters, to gold dredgers, to fisheries, to the general public. Due to a longer <span class="hlt">sea</span> <span class="hlt">ice</span> free season over recent years, activity in the waters around Alaska has increased. This has led to a rise in decision support services from the Alaska <span class="hlt">Sea</span> <span class="hlt">Ice</span> Program. The ASIP is in constant contact with the National <span class="hlt">Ice</span> Center as well as the United States Coast Guard (USCG) for safety of navigation. In the past, the ASIP provided briefings to the USCG when in support of search and rescue efforts. Currently, not only does that support remain, but our team is also briefing on <span class="hlt">sea</span> <span class="hlt">ice</span> outlooks into the next few months. As traffic in the Arctic increases, the ASIP will be called upon to provide more and more services on varying time scales to meet customer needs. This talk will address the many facets of the current Alaska <span class="hlt">Sea</span> <span class="hlt">Ice</span> Program as well as delve into what we see as the future of the ASIP.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFMOS13H..02E','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFMOS13H..02E"><span><span class="hlt">Sea-ice</span> information co-management: Planning for sustainable multiple uses of <span class="hlt">ice</span>-covered <span class="hlt">seas</span> in a rapidly changing Arctic</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Eicken, H.; Lovecraft, A. L.</p> <p>2012-12-01</p> <p>A thinner, less extensive and more mobile summer <span class="hlt">sea-ice</span> cover is a major element and driver of Arctic Ocean change. Declining summer <span class="hlt">sea</span> <span class="hlt">ice</span> presents Arctic stakeholders with substantial challenges and opportunities from the perspective of sustainable ocean use and derivation of <span class="hlt">sea-ice</span> or ecosystem services. <span class="hlt">Sea-ice</span> use by people and wildlife as well as its role as a major environmental hazard focuses the interests and concerns of indigenous hunters and Arctic coastal communities, resource managers and the maritime industry. In particular, rapid <span class="hlt">sea-ice</span> change and intensifying offshore industrial activities have raised fundamental questions as to how best to plan for and manage multiple and increasingly overlapping ocean and <span class="hlt">sea</span> <span class="hlt">ice</span> uses. The western North American Arctic - a region that has seen some of the greatest changes in <span class="hlt">ice</span> and ocean conditions in the past three decades anywhere in the North - is the focus of our study. Specifically, we examine the important role that relevant and actionable <span class="hlt">sea-ice</span> information can play in allowing stakeholders to evaluate risks and reconcile overlapping and potentially competing interests. Our work in coastal Alaska suggests that important prerequisites to address such challenges are common values, complementary bodies of expertise (e.g., local or indigenous knowledge, engineering expertise, environmental science) and a forum for the implementation and evaluation of a <span class="hlt">sea-ice</span> data and information framework. Alongside the International Polar Year 2007-08 and an associated boost in Arctic Ocean observation programs and platforms, there has been a movement towards new governance bodies that have these qualities and can play a central role in guiding the design and optimization of Arctic observing systems. To help further the development of such forums an evaluation of the density and spatial distribution of institutions, i.e., rule sets that govern ocean use, as well as the use of scenario planning and analysis can serve as</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014GeoRL..41.7566D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014GeoRL..41.7566D"><span>Will Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> thickness initialization improve seasonal forecast skill?</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Day, J. J.; Hawkins, E.; Tietsche, S.</p> <p>2014-11-01</p> <p>Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> thickness is thought to be an important predictor of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> extent. However, coupled seasonal forecast systems do not generally use <span class="hlt">sea</span> <span class="hlt">ice</span> thickness observations in their initialization and are therefore missing a potentially important source of additional skill. To investigate how large this source is, a set of ensemble potential predictability experiments with a global climate model, initialized with and without knowledge of the <span class="hlt">sea</span> <span class="hlt">ice</span> thickness initial state, have been run. These experiments show that accurate knowledge of the <span class="hlt">sea</span> <span class="hlt">ice</span> thickness field is crucially important for <span class="hlt">sea</span> <span class="hlt">ice</span> concentration and extent forecasts up to 8 months ahead, especially in summer. Perturbing <span class="hlt">sea</span> <span class="hlt">ice</span> thickness also has a significant impact on the forecast error in Arctic 2 m temperature a few months ahead. These results suggest that advancing capabilities to observe and assimilate <span class="hlt">sea</span> <span class="hlt">ice</span> thickness into coupled forecast systems could significantly increase skill.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C13E..07L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C13E..07L"><span>EM Bias-Correction for <span class="hlt">Ice</span> Thickness and Surface Roughness Retrievals over Rough Deformed <span class="hlt">Sea</span> <span class="hlt">Ice</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Li, L.; Gaiser, P. W.; Allard, R.; Posey, P. G.; Hebert, D. A.; Richter-Menge, J.; Polashenski, C. M.</p> <p>2016-12-01</p> <p>The very rough ridge <span class="hlt">sea</span> <span class="hlt">ice</span> accounts for significant percentage of total <span class="hlt">ice</span> areas and even larger percentage of total volume. The commonly used Radar altimeter surface detection techniques are empirical in nature and work well only over level/smooth <span class="hlt">sea</span> <span class="hlt">ice</span>. Rough <span class="hlt">sea</span> <span class="hlt">ice</span> surfaces can modify the return waveforms, resulting in significant Electromagnetic (EM) bias in the estimated surface elevations, and thus large errors in the <span class="hlt">ice</span> thickness retrievals. To understand and quantify such <span class="hlt">sea</span> <span class="hlt">ice</span> surface roughness effects, a combined EM rough surface and volume scattering model was developed to simulate radar returns from the rough <span class="hlt">sea</span> <span class="hlt">ice</span> `layer cake' structure. A waveform matching technique was also developed to fit observed waveforms to a physically-based waveform model and subsequently correct the roughness induced EM bias in the estimated freeboard. This new EM Bias Corrected (EMBC) algorithm was able to better retrieve surface elevations and estimate the surface roughness parameter simultaneously. In situ data from multi-instrument airborne and ground campaigns were used to validate the <span class="hlt">ice</span> thickness and surface roughness retrievals. For the surface roughness retrievals, we applied this EMBC algorithm to co-incident LiDAR/Radar measurements collected during a Cryosat-2 under-flight by the NASA <span class="hlt">Ice</span>Bridge missions. Results show that not only does the waveform model fit very well to the measured radar waveform, but also the roughness parameters derived independently from the LiDAR and radar data agree very well for both level and deformed <span class="hlt">sea</span> <span class="hlt">ice</span>. For <span class="hlt">sea</span> <span class="hlt">ice</span> thickness retrievals, validation based on in-situ data from the coordinated CRREL/NRL field campaign demonstrates that the physically-based EMBC algorithm performs fundamentally better than the empirical algorithm over very rough deformed <span class="hlt">sea</span> <span class="hlt">ice</span>, suggesting that <span class="hlt">sea</span> <span class="hlt">ice</span> surface roughness effects can be modeled and corrected based solely on the radar return waveforms.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA617029','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA617029"><span>Radar Remote Sensing of <span class="hlt">Ice</span> and <span class="hlt">Sea</span> State and Air-<span class="hlt">Sea</span> Interaction in the Marginal <span class="hlt">Ice</span> Zone</span></a></p> <p><a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>2014-09-30</p> <p>1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Radar Remote Sensing of <span class="hlt">Ice</span> and <span class="hlt">Sea</span> State and Air-<span class="hlt">Sea</span>...Interaction in the Marginal <span class="hlt">Ice</span> Zone Hans C. Graber RSMAS – Department of Ocean Sciences Center for Southeastern Tropical Advanced Remote Sensing...scattering and attenuation process of ocean waves interacting with <span class="hlt">ice</span> . A nautical X-band radar on a vessel dedicated to science would be used to follow the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20150004436','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20150004436"><span><span class="hlt">Sea-Ice</span> Freeboard Retrieval Using Digital Photon-Counting Laser Altimetry</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Farrell, Sinead L.; Brunt, Kelly M.; Ruth, Julia M.; Kuhn, John M.; Connor, Laurence N.; Walsh, Kaitlin M.</p> <p>2015-01-01</p> <p>Airborne and spaceborne altimeters provide measurements of <span class="hlt">sea-ice</span> elevation, from which <span class="hlt">sea-ice</span> freeboard and thickness may be derived. Observations of the Arctic <span class="hlt">ice</span> pack by satellite altimeters indicate a significant decline in <span class="hlt">ice</span> thickness, and volume, over the last decade. NASA's <span class="hlt">Ice</span>, Cloud and land Elevation Satellite-2 (ICESat-2) is a next-generation laser altimeter designed to continue key <span class="hlt">sea-ice</span> observations through the end of this decade. An airborne simulator for ICESat-2, the Multiple Altimeter Beam Experimental Lidar (MABEL), has been deployed to gather pre-launch data for mission development. We present an analysis of MABEL data gathered over <span class="hlt">sea</span> <span class="hlt">ice</span> in the Greenland <span class="hlt">Sea</span> and assess the capabilities of photon-counting techniques for <span class="hlt">sea-ice</span> freeboard retrieval. We compare freeboard estimates in the marginal <span class="hlt">ice</span> zone derived from MABEL photon-counting data with coincident data collected by a conventional airborne laser altimeter. We find that freeboard estimates agree to within 0.03m in the areas where <span class="hlt">sea-ice</span> floes were interspersed with wide leads, and to within 0.07m elsewhere. MABEL data may also be used to infer <span class="hlt">sea-ice</span> thickness, and when compared with coincident but independent <span class="hlt">ice</span> thickness estimates, MABEL <span class="hlt">ice</span> thicknesses agreed to within 0.65m or better.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-GSFC_20171208_Archive_e002001.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-GSFC_20171208_Archive_e002001.html"><span><span class="hlt">Sea</span> <span class="hlt">Ice</span> in McClure Strait</span></a></p> <p><a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a></p> <p></p> <p>2017-12-08</p> <p>NASA image acquired August 17, 2010 In mid-August 2010, the Northwest Passage was almost—but not quite—free of <span class="hlt">ice</span>. The <span class="hlt">ice</span> content in the northern route through the passage (through the Western Parry Channel) was very light, but <span class="hlt">ice</span> remained in McClure (or M’Clure) Strait. The Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite captured this natural-color image on August 17, 2010. Although most of McClure Strait looks perfectly <span class="hlt">ice</span>-free, immediately west of Prince Patrick Island, a band of <span class="hlt">sea</span> <span class="hlt">ice</span> stretches southward across the strait (left edge of the image). The National Snow and <span class="hlt">Ice</span> Data Center <span class="hlt">Sea</span> <span class="hlt">Ice</span> News and Analysis blog reported that even more <span class="hlt">ice</span> remained in the southern route (through Amundsen’s Passage) of the Northwest Passage in mid-August 2010. Nevertheless, the <span class="hlt">ice</span> content in the northern route was not only well below the 1968–2000 average, but also nearly a month ahead of the clearing observed in 2007, when Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> set a record low. As of mid-August 2010, however, overall <span class="hlt">sea</span> <span class="hlt">ice</span> extent was higher than it had been at the same time of year in 2007. Credit: NASA/GSFC/Jeff Schmaltz/MODIS Land Rapid Response Team Caption by Michon Scott. To learn more go to: earthobservatory.nasa.gov/NaturalHazards/view.php?id=45333 Instrument: Terra - MODIS NASA Goddard Space Flight Center is home to the nation's largest organization of combined scientists, engineers and technologists that build spacecraft, instruments and new technology to study the Earth, the sun, our solar system, and the universe. Follow us on Twitter Join us on Facebook Click here to see more images from NASA Goddard’s Earth Observatory</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19990064090&hterms=Parkinsons&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3DParkinsons','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19990064090&hterms=Parkinsons&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3DParkinsons"><span>Variability of Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> as Viewed from Space</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Parkinson, Claire L.</p> <p>1998-01-01</p> <p>Over the past 20 years, satellite passive-microwave radiometry has provided a marvelous means for obtaining information about the variability of the Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> cover and particularly about <span class="hlt">sea</span> <span class="hlt">ice</span> concentrations (% areal coverages) and from them <span class="hlt">ice</span> extents and the lengths of the <span class="hlt">sea</span> <span class="hlt">ice</span> season. This ability derives from the sharp contrast between the microwave emissions of <span class="hlt">sea</span> <span class="hlt">ice</span> versus liquid water and allows routine monitoring of the vast Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> cover, which typically varies in extent from a minimum of about 8,000,000 sq km in September to a maximum of about 15,000,000 sq km in March, the latter value being over 1.5 times the area of either the United States or Canada. The vast Arctic <span class="hlt">ice</span> cover has many impacts, including hindering heat, mass, and y momentum exchanges between the oceans and the atmosphere, reducing the amount of solar radiation absorbed at the Earth's surface, affecting freshwater transports and ocean circulation, and serving as a vital surface for many species of polar animals. These direct impacts also lead to indirect impacts, including effects on local and perhaps global atmospheric temperatures, effects that are being examined in general circulation modeling studies, where preliminary results indicate that changes on the order of a few percent <span class="hlt">sea</span> <span class="hlt">ice</span> concentration can lead to temperature changes of 1 K or greater even in local areas outside of the <span class="hlt">sea</span> <span class="hlt">ice</span> region. Satellite passive-microwave data for November 1978 through December 1996 reveal marked regional and interannual variabilities in both the <span class="hlt">ice</span> extents and the lengths of the <span class="hlt">sea</span> <span class="hlt">ice</span> season, as well as some statistically significant trends. For the north polar <span class="hlt">ice</span> cover as a whole, maximum <span class="hlt">ice</span> extents varied over a range of 14,700,000 - 15,900,000 km(2), while individual regions showed much greater percentage variations, e.g., with the Greenland <span class="hlt">Sea</span> experiencing a range of 740,000 - 1,1110,000 km(2) in its yearly maximum <span class="hlt">ice</span> coverage. Although variations from year to</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29704449','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29704449"><span>Contribution of <span class="hlt">sea</span> <span class="hlt">ice</span> microbial production to Antarctic benthic communities is driven by <span class="hlt">sea</span> <span class="hlt">ice</span> dynamics and composition of functional guilds.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Wing, Stephen R; Leichter, James J; Wing, Lucy C; Stokes, Dale; Genovese, Sal J; McMullin, Rebecca M; Shatova, Olya A</p> <p>2018-04-28</p> <p>Organic matter produced by the <span class="hlt">sea</span> <span class="hlt">ice</span> microbial community (SIMCo) is an important link between <span class="hlt">sea</span> <span class="hlt">ice</span> dynamics and secondary production in near-shore food webs of Antarctica. <span class="hlt">Sea</span> <span class="hlt">ice</span> conditions in McMurdo Sound were quantified from time series of MODIS satellite images for Sept. 1 through Feb. 28 of 2007-2015. A predictable <span class="hlt">sea</span> <span class="hlt">ice</span> persistence gradient along the length of the Sound and evidence for a distinct change in <span class="hlt">sea</span> <span class="hlt">ice</span> dynamics in 2011 were observed. We used stable isotope analysis (δ 13 C and δ 15 N) of SIMCo, suspended particulate organic matter (SPOM) and shallow water (10-20 m) macroinvertebrates to reveal patterns in trophic structure of, and incorporation of organic matter from SIMCo into, benthic communities at eight sites distributed along the <span class="hlt">sea</span> <span class="hlt">ice</span> persistence gradient. Mass-balance analysis revealed distinct trophic architecture among communities and large fluxes of SIMCo into the near-shore food web, with the estimates ranging from 2 to 84% of organic matter derived from SIMCo for individual species. Analysis of patterns in density, and biomass of macroinvertebrate communities among sites allowed us to model net incorporation of organic matter from SIMCo, in terms of biomass per unit area (g/m 2 ), into benthic communities. Here, organic matter derived from SIMCo supported 39 to 71 per cent of total biomass. Furthermore, for six species, we observed declines in contribution of SIMCo between years with persistent <span class="hlt">sea</span> <span class="hlt">ice</span> (2008-2009) and years with extensive <span class="hlt">sea</span> <span class="hlt">ice</span> breakout (2012-2015). Our data demonstrate the vital role of SIMCo in ecosystem function in Antarctica and strong linkages between <span class="hlt">sea</span> <span class="hlt">ice</span> dynamics and near-shore secondary productivity. These results have important implications for our understanding of how benthic communities will respond to changes in <span class="hlt">sea</span> <span class="hlt">ice</span> dynamics associated with climate change and highlight the important role of shallow water macroinvertebrate communities as sentinels of change for the Antarctic marine</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li class="active"><span>11</span></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_11 --> <div id="page_12" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li class="active"><span>12</span></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="221"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=PIA02971&hterms=sea+world&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dsea%2Bworld','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=PIA02971&hterms=sea+world&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dsea%2Bworld"><span>Comparative Views of Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> Growth</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p></p> <p>2000-01-01</p> <p>NASA researchers have new insights into the mysteries of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span>, thanks to the unique abilities of Canada's Radarsat satellite. The Arctic is the smallest of the world's four oceans, but it may play a large role in helping scientists monitor Earth's climate shifts.<p/>Using Radarsat's special sensors to take images at night and to peer through clouds, NASA researchers can now see the complete <span class="hlt">ice</span> cover of the Arctic. This allows tracking of any shifts and changes, in unprecedented detail, over the course of an entire winter. The radar-generated, high-resolution images are up to 100 times better than those taken by previous satellites.<p/>The two images above are separated by nine days (earlier image on the left). Both images represent an area (approximately 96 by 128 kilometers; 60 by 80 miles)located in the Baufort <span class="hlt">Sea</span>, north of the Alaskan coast. The brighter features are older thicker <span class="hlt">ice</span> and the darker areas show young, recently formed <span class="hlt">ice</span>. Within the nine-day span, large and extensive cracks in the <span class="hlt">ice</span> cover have formed due to <span class="hlt">ice</span> movement. These cracks expose the open ocean to the cold, frigid atmosphere where <span class="hlt">sea</span> <span class="hlt">ice</span> grows rapidly and thickens.<p/>Using this new information, scientists at NASA's Jet Propulsion Laboratory (JPL), Pasadena, Calif., can generate comprehensive maps of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> thickness for the first time. 'Before we knew only the extent of the <span class="hlt">ice</span> cover,' said Dr. Ronald Kwok, JPL principal investigator of a project called <span class="hlt">Sea</span> <span class="hlt">Ice</span> Thickness Derived From High Resolution Radar Imagery. 'We also knew that the <span class="hlt">sea</span> <span class="hlt">ice</span> extent had decreased over the last 20 years, but we knew very little about <span class="hlt">ice</span> thickness.'<p/>'Since <span class="hlt">sea</span> <span class="hlt">ice</span> is very thin, about 3 meters (10 feet) or less,'Kwok explained, 'it is very sensitive to climate change.'<p/>Until now, observations of polar <span class="hlt">sea</span> <span class="hlt">ice</span> thickness have been available for specific areas, but not for the entire polar region.<p/>The new radar mapping technique has also given scientists a close look at</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20100033640','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20100033640"><span>The Satellite Passive-Microwave Record of <span class="hlt">Sea</span> <span class="hlt">Ice</span> in the Ross <span class="hlt">Sea</span> Since Late 1978</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Parkinson, Claire L.</p> <p>2009-01-01</p> <p>Satellites have provided us with a remarkable ability to monitor many aspects of the globe day-in and day-out and <span class="hlt">sea</span> <span class="hlt">ice</span> is one of numerous variables that by now have quite substantial satellite records. Passive-microwave data have been particularly valuable in <span class="hlt">sea</span> <span class="hlt">ice</span> monitoring, with a record that extends back to August 1987 on daily basis (for most of the period), to November 1970 on a less complete basis (again for most of the period), and to December 1972 on a less complete basis. For the period since November 1970, Ross <span class="hlt">Sea</span> <span class="hlt">sea</span> <span class="hlt">ice</span> imagery is available at spatial resolution of approximately 25 km. This allows good depictions of the seasonal advance and retreat of the <span class="hlt">ice</span> cover each year, along with its marked interannual variability. The Ross <span class="hlt">Sea</span> <span class="hlt">ice</span> extent typically reaches a minimum of approximately 0.7 x 10(exp 6) square kilometers in February, rising to a maximum of approximately 4.0 x 10(exp 6) square kilometers in September, with much variability among years for both those numbers. The Ross <span class="hlt">Sea</span> images show clearly the day-by-day activity greatly from year to year. Animations of the data help to highlight the dynamic nature of the Ross <span class="hlt">Sea</span> <span class="hlt">ice</span> cover. The satellite data also allow calculation of trends in the <span class="hlt">ice</span> cover over the period of the satellite record. Using linear least-squares fits, the Ross <span class="hlt">Sea</span> <span class="hlt">ice</span> extent increased at an average rate of 12,600 plus or minus 1,800 square kilometers per year between November 1978 and December 2007, with every month exhibiting increased <span class="hlt">ice</span> extent and the rates of increase ranging from a low of 7,500 plus or minus 5,000 square kilometers per year for the February <span class="hlt">ice</span> extents to a high of 20,300 plus or minus 6,100 kilometers per year for the October <span class="hlt">ice</span> extents. On a yearly average basis, for 1979-2007 the Ross <span class="hlt">Sea</span> <span class="hlt">ice</span> extent increased at a rate of 4.8 plus or minus 1.6 % per decade. Placing the Ross <span class="hlt">Sea</span> in the context of the Southern Ocean as a whole, over the November 1978-December 2007 period the Ross <span class="hlt">Sea</span> had</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4653624','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4653624"><span>Additional Arctic observations improve weather and <span class="hlt">sea-ice</span> forecasts for the Northern <span class="hlt">Sea</span> Route</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Inoue, Jun; Yamazaki, Akira; Ono, Jun; Dethloff, Klaus; Maturilli, Marion; Neuber, Roland; Edwards, Patti; Yamaguchi, Hajime</p> <p>2015-01-01</p> <p>During <span class="hlt">ice</span>-free periods, the Northern <span class="hlt">Sea</span> Route (NSR) could be an attractive shipping route. The decline in Arctic <span class="hlt">sea-ice</span> extent, however, could be associated with an increase in the frequency of the causes of severe weather phenomena, and high wind-driven waves and the advection of <span class="hlt">sea</span> <span class="hlt">ice</span> could make ship navigation along the NSR difficult. Accurate forecasts of weather and <span class="hlt">sea</span> <span class="hlt">ice</span> are desirable for safe navigation, but large uncertainties exist in current forecasts, partly owing to the sparse observational network over the Arctic Ocean. Here, we show that the incorporation of additional Arctic observations improves the initial analysis and enhances the skill of weather and <span class="hlt">sea-ice</span> forecasts, the application of which has socioeconomic benefits. Comparison of 63-member ensemble atmospheric forecasts, using different initial data sets, revealed that additional Arctic radiosonde observations were useful for predicting a persistent strong wind event. The <span class="hlt">sea-ice</span> forecast, initialised by the wind fields that included the effects of the observations, skilfully predicted rapid wind-driven <span class="hlt">sea-ice</span> advection along the NSR. PMID:26585690</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C41A0644M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C41A0644M"><span>Modelling of <span class="hlt">Sea</span> <span class="hlt">Ice</span> Thermodynamics and Biogeochemistry during the N-<span class="hlt">ICE</span>2015 Expedition in the Arctic Ocean</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Meyer, A.; Duarte, P.; Mork Olsen, L.; Kauko, H.; Assmy, P.; Rösel, A.; Itkin, P.; Hudson, S. R.; Granskog, M. A.; Gerland, S.; Sundfjord, A.; Steen, H.; Jeffery, N.; Hunke, E. C.; Elliott, S.; Turner, A. K.</p> <p>2016-12-01</p> <p>Changes in the <span class="hlt">sea</span> <span class="hlt">ice</span> regime of the Arctic Ocean over the last decades from a thick perennial multiyear <span class="hlt">ice</span> to a first year <span class="hlt">ice</span> have been well documented. These changes in the <span class="hlt">sea</span> <span class="hlt">ice</span> regime will affect feedback mechanisms between the <span class="hlt">sea</span> <span class="hlt">ice</span>, atmosphere and ocean. Here we evaluate the performance of the Los Alamos <span class="hlt">Sea</span> <span class="hlt">Ice</span> Model (CICE), a state of the art <span class="hlt">sea</span> <span class="hlt">ice</span> model, to predict <span class="hlt">sea</span> <span class="hlt">ice</span> physical and biogeochemical properties at time scales of a few weeks. We also identify the most problematic prognostic variables and what is necessary to improve their forecast. The availability of a complete data set of forcing collected during the Norwegian Young <span class="hlt">sea</span> <span class="hlt">Ice</span> (N-<span class="hlt">ICE</span>-2015) expedition north of Svalbard opens the possibility to properly test CICE. Oceanographic, atmospheric, <span class="hlt">sea</span> <span class="hlt">ice</span>, snow, and biological data were collected above, on, and below the <span class="hlt">ice</span> using R/V Lance as the base for the <span class="hlt">ice</span> camps that were drifting south towards the Fram Strait. Over six months, four different drifts took place, from the Nansen Basin, through the marginal <span class="hlt">ice</span> zone, to the open ocean. Obtained results from the model show a good performance regarding <span class="hlt">ice</span> thickness, salinity and temperature. Nutrients and <span class="hlt">sea</span> <span class="hlt">ice</span> algae are however not modelled as accurately. We hypothesize that improvements in biogeochemical modeling may be achieved by complementing brine drainage with a diffusion parameterization and biogeochemical modeling with the introduction of an explicit formulation to forecast chlorophyll and regulate photosynthetic efficiency.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140011036','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140011036"><span>Improving Surface Mass Balance Over <span class="hlt">Ice</span> Sheets and Snow Depth on <span class="hlt">Sea</span> <span class="hlt">Ice</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Koenig, Lora Suzanne; Box, Jason; Kurtz, Nathan</p> <p>2013-01-01</p> <p>Surface mass balance (SMB) over <span class="hlt">ice</span> sheets and snow on <span class="hlt">sea</span> <span class="hlt">ice</span> (SOSI) are important components of the cryosphere. Large knowledge gaps remain in scientists' abilities to monitor SMB and SOSI, including insufficient measurements and difficulties with satellite retrievals. On <span class="hlt">ice</span> sheets, snow accumulation is the sole mass gain to SMB, and meltwater runoff can be the dominant single loss factor in extremely warm years such as 2012. SOSI affects the growth and melt cycle of the Earth's polar <span class="hlt">sea</span> <span class="hlt">ice</span> cover. The summer of 2012 saw the largest satellite-recorded melt area over the Greenland <span class="hlt">ice</span> sheet and the smallest satellite-recorded Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> extent, making this meeting both timely and relevant.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA549401','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA549401"><span>Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span>: Using Airborne Topographic Mapper Measurements (ATM) to Determine <span class="hlt">Sea</span> <span class="hlt">Ice</span> Thickness</span></a></p> <p><a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>2011-05-10</p> <p>Track Distance (Km) E le v a ti o n ( m ) ATM Elevation Profile Elevation 18 Figure 13: Geoid shape of earth’s equipotential surface , which is...inferred for the region between successive leads. Therefore, flying over a lead in the <span class="hlt">ice</span> is very important for determining the exact <span class="hlt">sea</span> surface elevation...inferred for the region between successive leads. Therefore, flying over a lead in the <span class="hlt">ice</span> is very important for determining the exact <span class="hlt">sea</span> surface</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.6676H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.6676H"><span>Scaling properties of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> deformation in high-resolution viscous-plastic <span class="hlt">sea</span> <span class="hlt">ice</span> models and satellite observations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hutter, Nils; Losch, Martin; Menemenlis, Dimitris</p> <p>2017-04-01</p> <p><span class="hlt">Sea</span> <span class="hlt">ice</span> models with the traditional viscous-plastic (VP) rheology and very high grid resolution can resolve leads and deformation rates that are localised along Linear Kinematic Features (LKF). In a 1-km pan-Arctic <span class="hlt">sea</span> <span class="hlt">ice</span>-ocean simulation, the small scale <span class="hlt">sea-ice</span> deformations in the Central Arctic are evaluated with a scaling analysis in relation to satellite observations of the Envisat Geophysical Processor System (EGPS). A new coupled scaling analysis for data on Eulerian grids determines the spatial and the temporal scaling as well as the coupling between temporal and spatial scales. The spatial scaling of the modelled <span class="hlt">sea</span> <span class="hlt">ice</span> deformation implies multi-fractality. The spatial scaling is also coupled to temporal scales and varies realistically by region and season. The agreement of the spatial scaling and its coupling to temporal scales with satellite observations and models with the modern elasto-brittle rheology challenges previous results with VP models at coarse resolution where no such scaling was found. The temporal scaling analysis, however, shows that the VP model does not fully resolve the intermittency of <span class="hlt">sea</span> <span class="hlt">ice</span> deformation that is observed in satellite data.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013JGRF..118.1533D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013JGRF..118.1533D"><span>The Greenland <span class="hlt">Ice</span> Sheet's surface mass balance in a seasonally <span class="hlt">sea</span> <span class="hlt">ice</span>-free Arctic</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Day, J. J.; Bamber, J. L.; Valdes, P. J.</p> <p>2013-09-01</p> <p>General circulation models predict a rapid decrease in <span class="hlt">sea</span> <span class="hlt">ice</span> extent with concurrent increases in near-surface air temperature and precipitation in the Arctic over the 21st century. This has led to suggestions that some Arctic land <span class="hlt">ice</span> masses may experience an increase in accumulation due to enhanced evaporation from a seasonally <span class="hlt">sea</span> <span class="hlt">ice</span>-free Arctic Ocean. To investigate the impact of this phenomenon on Greenland <span class="hlt">Ice</span> Sheet climate and surface mass balance (SMB), a regional climate model, HadRM3, was used to force an insolation-temperature melt SMB model. A set of experiments designed to investigate the role of <span class="hlt">sea</span> <span class="hlt">ice</span> independently from <span class="hlt">sea</span> surface temperature (SST) forcing are described. In the warmer and wetter SI + SST simulation, Greenland experiences a 23% increase in winter SMB but 65% reduced summer SMB, resulting in a net decrease in the annual value. This study shows that <span class="hlt">sea</span> <span class="hlt">ice</span> decline contributes to the increased winter balance, causing 25% of the increase in winter accumulation; this is largest in eastern Greenland as the result of increased evaporation in the Greenland <span class="hlt">Sea</span>. These results indicate that the seasonal cycle of Greenland's SMB will increase dramatically as global temperatures increase, with the largest changes in temperature and precipitation occurring in winter. This demonstrates that the accurate prediction of changes in <span class="hlt">sea</span> <span class="hlt">ice</span> cover is important for predicting Greenland SMB and <span class="hlt">ice</span> sheet evolution.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C23D..01R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C23D..01R"><span><span class="hlt">Ice</span> sheet systems and <span class="hlt">sea</span> level change.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Rignot, E. J.</p> <p>2015-12-01</p> <p>Modern views of <span class="hlt">ice</span> sheets provided by satellites, airborne surveys, in situ data and paleoclimate records while transformative of glaciology have not fundamentally changed concerns about <span class="hlt">ice</span> sheet stability and collapse that emerged in the 1970's. Motivated by the desire to learn more about <span class="hlt">ice</span> sheets using new technologies, we stumbled on an unexplored field of science and witnessed surprising changes before realizing that most were coming too fast, soon and large. <span class="hlt">Ice</span> sheets are integrant part of the Earth system; they interact vigorously with the atmosphere and the oceans, yet most of this interaction is not part of current global climate models. Since we have never witnessed the collapse of a marine <span class="hlt">ice</span> sheet, observations and exploration remain critical sentinels. At present, these observations suggest that Antarctica and Greenland have been launched into a path of multi-meter <span class="hlt">sea</span> level rise caused by rapid climate warming. While the current loss of <span class="hlt">ice</span> sheet mass to the ocean remains a trickle, every mm of <span class="hlt">sea</span> level change will take centuries of climate reversal to get back, several major marine-terminating sectors have been pushed out of equilibrium, and <span class="hlt">ice</span> shelves are irremediably being lost. As glaciers retreat from their salty, warm, oceanic margins, they will melt away and retreat slower, but concerns remain about <span class="hlt">sea</span> level change from vastly marine-based sectors: 2-m <span class="hlt">sea</span> level equivalent in Greenland and 23-m in Antarctica. Significant changes affect 2/4 marine-based sectors in Greenland - Jakobshavn Isb. and the northeast stream - with Petermann Gl. not far behind. Major changes have affected the Amundsen <span class="hlt">Sea</span> sector of West Antarctica since the 1980s. Smaller yet significant changes affect the marine-based Wilkes Land sector of East Antarctica, a reminder that not all marine-based <span class="hlt">ice</span> is in West Antarctica. Major advances in reducing uncertainties in <span class="hlt">sea</span> level projections will require massive, interdisciplinary efforts that are not currently in place</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20150021896&hterms=sea&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dsea','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20150021896&hterms=sea&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dsea"><span>Is <span class="hlt">Ice</span>-Rafted Sediment in a North Pole Marine Record Evidence for Perennial <span class="hlt">Sea-ice</span> Cover?</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Tremblay, L.B.; Schmidt, G.A.; Pfirman, S.; Newton, R.; DeRepentigny, P.</p> <p>2015-01-01</p> <p><span class="hlt">Ice</span>-rafted sediments of Eurasian and North American origin are found consistently in the upper part (13 Ma BP to present) of the Arctic Coring Expedition (ACEX) ocean core from the Lomonosov Ridge, near the North Pole (approximately 88 degrees N). Based on modern <span class="hlt">sea-ice</span> drift trajectories and speeds, this has been taken as evidence of the presence of a perennial <span class="hlt">sea-ice</span> cover in the Arctic Ocean from the middle Miocene onwards. However, other high latitude land and marine records indicate a long-term trend towards cooling broken by periods of extensive warming suggestive of a seasonally <span class="hlt">ice</span>-free Arctic between the Miocene and the present. We use a coupled <span class="hlt">sea-ice</span> slab-ocean model including sediment transport tracers to map the spatial distribution of <span class="hlt">ice</span>-rafted deposits in the Arctic Ocean. We use 6 hourly wind forcing and surface heat fluxes for two different climates: one with a perennial <span class="hlt">sea-ice</span> cover similar to that of the present day and one with seasonally <span class="hlt">ice</span>-free conditions, similar to that simulated in future projections. Model results confirm that in the present-day climate, <span class="hlt">sea</span> <span class="hlt">ice</span> takes more than 1 year to transport sediment from all its peripheral <span class="hlt">seas</span> to the North Pole. However, in a warmer climate, <span class="hlt">sea-ice</span> speeds are significantly faster (for the same wind forcing) and can deposit sediments of Laptev, East Siberian and perhaps also Beaufort <span class="hlt">Sea</span> origin at the North Pole. This is primarily because of the fact that <span class="hlt">sea-ice</span> interactions are much weaker with a thinner <span class="hlt">ice</span> cover and there is less resistance to drift. We conclude that the presence of <span class="hlt">ice</span>-rafted sediment of Eurasian and North American origin at the North Pole does not imply a perennial <span class="hlt">sea-ice</span> cover in the Arctic Ocean, reconciling the ACEX ocean core data with other land and marine records.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009EGUGA..11.6008T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009EGUGA..11.6008T"><span>Influences of Ocean Thermohaline Stratification on Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Toole, J. M.; Timmermans, M.-L.; Perovich, D. K.; Krishfield, R. A.; Proshutinsky, A.; Richter-Menge, J. A.</p> <p>2009-04-01</p> <p>The Arctic Ocean's surface mixed layer constitutes the dynamical and thermodynamical link between the <span class="hlt">sea</span> <span class="hlt">ice</span> and the underlying waters. Wind stress, acting directly on the surface mixed layer or via wind-forced <span class="hlt">ice</span> motion, produce surface currents that can in turn drive deep ocean flow. Mixed layer temperature is intimately related to basal <span class="hlt">sea</span> <span class="hlt">ice</span> growth and melting. Heat fluxes into or out of the surface mixed layer can occur at both its upper and lower interfaces: the former via air-<span class="hlt">sea</span> exchange at leads and conduction through the <span class="hlt">ice</span>, the latter via turbulent mixing and entrainment at the layer base. Variations in Arctic Ocean mixed layer properties are documented based on more than 16,000 temperature and salinity profiles acquired by <span class="hlt">Ice</span>-Tethered Profilers since summer 2004 and analyzed in conjunction with <span class="hlt">sea</span> <span class="hlt">ice</span> observations from <span class="hlt">Ice</span> Mass Balance Buoys and atmospheric heat flux estimates. Guidance interpreting the observations is provided by a one-dimensional ocean mixed layer model. The study focuses attention on the very strong density stratification about the mixed layer base in the Arctic that, in regions of <span class="hlt">sea</span> <span class="hlt">ice</span> melting, is increasing with time. The intense stratification greatly impedes mixed layer deepening by vertical convection and shear mixing, and thus limits the flux of deep ocean heat to the surface that could influence <span class="hlt">sea</span> <span class="hlt">ice</span> growth/decay. Consistent with previous work, this study demonstrates that the Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> is most sensitive to changes in ocean mixed layer heat resulting from fluxes across its upper (air-<span class="hlt">sea</span> and/or <span class="hlt">ice</span>-water) interface.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19900037500&hterms=classification+passive&qs=N%3D0%26Ntk%3DTitle%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dclassification%2Bpassive','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19900037500&hterms=classification+passive&qs=N%3D0%26Ntk%3DTitle%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dclassification%2Bpassive"><span>A multisensor approach to <span class="hlt">sea</span> <span class="hlt">ice</span> classification for the validation of DMSP-SSM/I passive microwave derived <span class="hlt">sea</span> <span class="hlt">ice</span> products</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Steffen, K.; Schweiger, A. J.</p> <p>1990-01-01</p> <p>The validation of <span class="hlt">sea</span> <span class="hlt">ice</span> products derived from the Special Sensor Microwave Imager (SSM/I) on board a DMSP platform is examined using data from the Landsat MSS and NOAA-AVHRR sensors. Image processing techniques for retrieving <span class="hlt">ice</span> concentrations from each type of imagery are developed and results are intercompared to determine the <span class="hlt">ice</span> parameter retrieval accuracy of the SSM/I NASA-Team algorithm. For case studies in the Beaufort <span class="hlt">Sea</span> and East Greenland <span class="hlt">Sea</span>, average retrieval errors of the SSM/I algorithm are between 1.7 percent for spring conditions and 4.3 percent during freeze up in comparison with Landsat derived <span class="hlt">ice</span> concentrations. For a case study in the East Greenland <span class="hlt">Sea</span>, SSM/I derived <span class="hlt">ice</span> concentration in comparison with AVHRR imagery display a mean error of 9.6 percent.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19840002650','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19840002650"><span>Antartic <span class="hlt">sea</span> <span class="hlt">ice</span>, 1973 - 1976: Satellite passive-microwave observations</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Zwally, H. J.; Comiso, J. C.; Parkinson, C. L.; Campbell, W. J.; Carsey, F. D.; Gloersen, P.</p> <p>1983-01-01</p> <p>Data from the Electrically Scanning Microwave Radiometer (ESMR) on the Nimbus 5 satellite are used to determine the extent and distribution of Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span>. The characteristics of the southern ocean, the mathematical formulas used to obtain quantitative <span class="hlt">sea</span> <span class="hlt">ice</span> concentrations, the general characteristics of the seasonal <span class="hlt">sea</span> <span class="hlt">ice</span> growth/decay cycle and regional differences, and the observed seasonal growth/decay cycle for individual years and interannual variations of the <span class="hlt">ice</span> cover are discussed. The <span class="hlt">sea</span> <span class="hlt">ice</span> data from the ESMR are presented in the form of color-coded maps of the Antarctic and the southern oceans. The maps show brightness temperatures and concentrations of pack <span class="hlt">ice</span> averaged for each month, 4-year monthly averages, and month-to-month changes. Graphs summarizing the results, such as areas of <span class="hlt">sea</span> <span class="hlt">ice</span> as a function of time in the various sectors of the southern ocean are included. The images demonstrate that satellite microwave data provide unique information on large-scale <span class="hlt">sea</span> <span class="hlt">ice</span> conditions for determining climatic conditions in polar regions and possible global climatic changes.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20070021400&hterms=relationships&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DTitle%26N%3D0%26No%3D50%26Ntt%3Drelationships','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20070021400&hterms=relationships&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DTitle%26N%3D0%26No%3D50%26Ntt%3Drelationships"><span>Spatial Variability of Barrow-Area Shore-Fast <span class="hlt">Sea</span> <span class="hlt">Ice</span> and Its Relationships to Passive Microwave Emissivity</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Maslanik, J. A.; Rivas, M. Belmonte; Holmgren, J.; Gasiewski, A. J.; Heinrichs, J. F.; Stroeve, J. C.; Klein, M.; Markus, T.; Perovich, D. K.; Sonntag, J. G.; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_20070021400'); toggleEditAbsImage('author_20070021400_show'); toggleEditAbsImage('author_20070021400_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_20070021400_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_20070021400_hide"></p> <p>2006-01-01</p> <p>Aircraft-acquired passive microwave data, laser radar height observations, RADARSAT synthetic aperture radar imagery, and in situ measurements obtained during the AMSR-<span class="hlt">Ice</span>03 experiment are used to investigate relationships between microwave emission and <span class="hlt">ice</span> characteristics over several space scales. The data fusion allows delineation of the shore-fast <span class="hlt">ice</span> and pack <span class="hlt">ice</span> in the Barrow area, AK, into several <span class="hlt">ice</span> classes. Results show good agreement between observed and Polarimetric Scanning Radiometer (PSR)-derived snow depths over relatively smooth <span class="hlt">ice</span>, with larger differences over ridged and rubbled <span class="hlt">ice</span>. The PSR results are consistent with the effects on snow depth of the spatial distribution and nature of <span class="hlt">ice</span> roughness, ridging, and other factors such as <span class="hlt">ice</span> age. Apparent relationships exist between <span class="hlt">ice</span> roughness and the degree of depolarization of emission at 10,19, and 37 GHz. This depolarization .would yield overestimates of total <span class="hlt">ice</span> concentration using polarization-based algorithms, with indications of this seen when the NT-2 algorithm is applied to the PSR data. Other characteristics of the microwave data, such as effects of grounding of <span class="hlt">sea</span> <span class="hlt">ice</span> and large contrast between <span class="hlt">sea</span> <span class="hlt">ice</span> and <span class="hlt">adjacent</span> land, are also apparent in the PSR data. Overall, the results further demonstrate the importance of macroscale <span class="hlt">ice</span> roughness conditions such as ridging and rubbling on snow depth and microwave emissivity.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70017033','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70017033"><span>Sediments in Arctic <span class="hlt">sea</span> <span class="hlt">ice</span>: Implications for entrainment, transport and release</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Nurnberg, D.; Wollenburg, I.; Dethleff, D.; Eicken, H.; Kassens, H.; Letzig, T.; Reimnitz, E.; Thiede, Jorn</p> <p>1994-01-01</p> <p>Despite the Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> cover's recognized sensitivity to environmental change, the role of sediment inclusions in lowering <span class="hlt">ice</span> albedo and affecting <span class="hlt">ice</span> ablation is poorly understood. <span class="hlt">Sea</span> <span class="hlt">ice</span> sediment inclusions were studied in the central Arctic Ocean during the Arctic 91 expedition and in the Laptev <span class="hlt">Sea</span> (East Siberian Arctic Region Expedition 1992). Results from these investigations are here combined with previous studies performed in major areas of <span class="hlt">ice</span> ablation and the southern central Arctic Ocean. This study documents the regional distribution and composition of particle-laden <span class="hlt">ice</span>, investigates and evaluates processes by which sediment is incorporated into the <span class="hlt">ice</span> cover, and identifies transport paths and probable depositional centers for the released sediment. In April 1992, <span class="hlt">sea</span> <span class="hlt">ice</span> in the Laptev <span class="hlt">Sea</span> was relatively clean. The sediment occasionally observed was distributed diffusely over the entire <span class="hlt">ice</span> column, forming turbid <span class="hlt">ice</span>. Observations indicate that frazil and anchor <span class="hlt">ice</span> formation occurring in a large coastal polynya provide a main mechanism for sediment entrainment. In the central Arctic Ocean sediments are concentrated in layers within or at the surface of <span class="hlt">ice</span> floes due to melting and refreezing processes. The surface sediment accumulation in central Arctic multi-year <span class="hlt">sea</span> <span class="hlt">ice</span> exceeds by far the amounts observed in first-year <span class="hlt">ice</span> from the Laptev <span class="hlt">Sea</span> in April 1992. <span class="hlt">Sea</span> <span class="hlt">ice</span> sediments are generally fine grained, although coarse sediments and stones up to 5 cm in diameter are observed. Component analysis indicates that quartz and clay minerals are the main terrigenous sediment particles. The biogenous components, namely shells of pelecypods and benthic foraminiferal tests, point to a shallow, benthic, marine source area. Apparently, sediment inclusions were resuspended from shelf areas before and incorporated into the <span class="hlt">sea</span> <span class="hlt">ice</span> by suspension freezing. Clay mineralogy of <span class="hlt">ice</span>-rafted sediments provides information on potential source areas. A smectite</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C31D..01S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C31D..01S"><span>The <span class="hlt">Sea-Ice</span> Floe Size Distribution</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Stern, H. L., III; Schweiger, A. J. B.; Zhang, J.; Steele, M.</p> <p>2017-12-01</p> <p>The size distribution of <span class="hlt">ice</span> floes in the polar <span class="hlt">seas</span> affects the dynamics and thermodynamics of the <span class="hlt">ice</span> cover and its interaction with the ocean and atmosphere. <span class="hlt">Ice</span>-ocean models are now beginning to include the floe size distribution (FSD) in their simulations. In order to characterize seasonal changes of the FSD and provide validation data for our <span class="hlt">ice</span>-ocean model, we calculated the FSD in the Beaufort and Chukchi <span class="hlt">seas</span> over two spring-summer-fall seasons (2013 and 2014) using more than 250 cloud-free visible-band scenes from the MODIS sensors on NASA's Terra and Aqua satellites, identifying nearly 250,000 <span class="hlt">ice</span> floes between 2 and 30 km in diameter. We found that the FSD follows a power-law distribution at all locations, with a seasonally varying exponent that reflects floe break-up in spring, loss of smaller floes in summer, and the return of larger floes after fall freeze-up. We extended the results to floe sizes from 10 m to 2 km at selected time/space locations using more than 50 high-resolution radar and visible-band satellite images. Our analysis used more data and applied greater statistical rigor than any previous study of the FSD. The incorporation of the FSD into our <span class="hlt">ice</span>-ocean model resulted in reduced <span class="hlt">sea-ice</span> thickness, mainly in the marginal <span class="hlt">ice</span> zone, which improved the simulation of <span class="hlt">sea-ice</span> extent and yielded an earlier <span class="hlt">ice</span> retreat. We also examined results from 17 previous studies of the FSD, most of which report power-law FSDs but with widely varying exponents. It is difficult to reconcile the range of results due to different study areas, seasons, and methods of analysis. We review the power-law representation of the FSD in these studies and discuss some mathematical details that are important to consider in any future analysis.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19820009687','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19820009687"><span>An optical model for the microwave properties of <span class="hlt">sea</span> <span class="hlt">ice</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Gloersen, P.; Larabee, J. K.</p> <p>1981-01-01</p> <p>The complex refractive index of <span class="hlt">sea</span> <span class="hlt">ice</span> is modeled and used to predict the microwave signatures of various <span class="hlt">sea</span> <span class="hlt">ice</span> types. Results are shown to correspond well with the observed values of the complex index inferred from dielectic constant and dielectric loss measurements performed in the field, and with observed microwave signatures of <span class="hlt">sea</span> <span class="hlt">ice</span>. The success of this modeling procedure vis a vis modeling of the dielectric properties of <span class="hlt">sea</span> <span class="hlt">ice</span> constituents used earlier by several others is explained. Multiple layer radiative transfer calculations are used to predict the microwave properties of first-year <span class="hlt">sea</span> <span class="hlt">ice</span> with and without snow, and multiyear <span class="hlt">sea</span> <span class="hlt">ice</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2000JGR...10511299K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2000JGR...10511299K"><span>Results of the <span class="hlt">Sea</span> <span class="hlt">Ice</span> Model Intercomparison Project: Evaluation of <span class="hlt">sea</span> <span class="hlt">ice</span> rheology schemes for use in climate simulations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kreyscher, Martin; Harder, Markus; Lemke, Peter; Flato, Gregory M.</p> <p>2000-05-01</p> <p>A hierarchy of <span class="hlt">sea</span> <span class="hlt">ice</span> rheologies is evaluated on the basis of a comprehensive set of observational data. The investigations are part of the <span class="hlt">Sea</span> <span class="hlt">Ice</span> Model Intercomparison Project (SIMIP). Four different <span class="hlt">sea</span> <span class="hlt">ice</span> rheology schemes are compared: a viscous-plastic rheology, a cavitating-fluid model, a compressible Newtonian fluid, and a simple free drift approach with velocity correction. The same grid, land boundaries, and forcing fields are applied to all models. As verification data, there are (1) <span class="hlt">ice</span> thickness data from upward looking sonars (ULS), (2) <span class="hlt">ice</span> concentration data from the passive microwave radiometers SMMR and SSM/I, (3) daily buoy drift data obtained by the International Arctic Buoy Program (IABP), and (4) satellite-derived <span class="hlt">ice</span> drift fields based on the 85 GHz channel of SSM/I. All models are optimized individually with respect to mean drift speed and daily drift speed statistics. The impact of <span class="hlt">ice</span> strength on the <span class="hlt">ice</span> cover is best revealed by the spatial pattern of <span class="hlt">ice</span> thickness, <span class="hlt">ice</span> drift on different timescales, daily drift speed statistics, and the drift velocities in Fram Strait. Overall, the viscous-plastic rheology yields the most realistic simulation. In contrast, the results of the very simple free-drift model with velocity correction clearly show large errors in simulated <span class="hlt">ice</span> drift as well as in <span class="hlt">ice</span> thicknesses and <span class="hlt">ice</span> export through Fram Strait compared to observation. The compressible Newtonian fluid cannot prevent excessive <span class="hlt">ice</span> thickness buildup in the central Arctic and overestimates the internal forces in Fram Strait. Because of the lack of shear strength, the cavitating-fluid model shows marked differences to the statistics of observed <span class="hlt">ice</span> drift and the observed spatial pattern of <span class="hlt">ice</span> thickness. Comparison of required computer resources demonstrates that the additional cost for the viscous-plastic <span class="hlt">sea</span> <span class="hlt">ice</span> rheology is minor compared with the atmospheric and oceanic model components in global climate simulations.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMNG31A1833A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMNG31A1833A"><span>The statistical properties of <span class="hlt">sea</span> <span class="hlt">ice</span> velocity fields</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Agarwal, S.; Wettlaufer, J. S.</p> <p>2016-12-01</p> <p>Thorndike and Colony (1982) showed that more than 70% of the variance of the <span class="hlt">ice</span> motion can be explained by the geostrophic winds. This conclusion was reached by analyzing only 2 years of data. Due to the importance of <span class="hlt">ice</span> motion in Arctic climate we ask how persistent is such a prediction. In so doing, we study and develop a stochastic model for the Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> velocity fields based on the observed <span class="hlt">sea</span> <span class="hlt">ice</span> velocity fields from satellites and buoys for the period 1978 - 2012. Having previously found that the Arctic <span class="hlt">Sea</span> Equivalent <span class="hlt">Ice</span> Extent (EIE) has a white noise structure on annual to bi-annual time scales (Agarwal et. al. 2012), we assess the connection to <span class="hlt">ice</span> motion. We divide the Arctic into dynamic and thermodynamic components, with focus on the dynamic part i.e. the velocity fields of <span class="hlt">sea</span> <span class="hlt">ice</span> driven by the geostrophic winds over the Arctic. We show (1) the stationarity of the spatial correlation structure of the velocity fields, and (2) the robustness of white noise structure present in the velocity fields on annual to bi-annual time scales, which combine to explain the white noise characteristics of the EIE on these time scales. S. Agarwal, W. Moon and J.S. Wettlaufer, Trends, noise and reentrant long-term persistence in Arctic <span class="hlt">sea</span> <span class="hlt">ice</span>, Proc. R. Soc. A, 468, 2416 (2012). A.S. Thorndike and R. Colony, <span class="hlt">Sea</span> <span class="hlt">ice</span> motion in response to geostrophic winds, J. Geophys. Res. 87, 5845 (1982).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.5067M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.5067M"><span>Satellite altimetry in <span class="hlt">sea</span> <span class="hlt">ice</span> regions - detecting open water for estimating <span class="hlt">sea</span> surface heights</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Müller, Felix L.; Dettmering, Denise; Bosch, Wolfgang</p> <p>2017-04-01</p> <p>The Greenland <span class="hlt">Sea</span> and the Farm Strait are transporting <span class="hlt">sea</span> <span class="hlt">ice</span> from the central Arctic ocean southwards. They are covered by a dynamic changing <span class="hlt">sea</span> <span class="hlt">ice</span> layer with significant influences on the Earth climate system. Between the <span class="hlt">sea</span> <span class="hlt">ice</span> there exist various sized open water areas known as leads, straight lined open water areas, and polynyas exhibiting a circular shape. Identifying these leads by satellite altimetry enables the extraction of <span class="hlt">sea</span> surface height information. Analyzing the radar echoes, also called waveforms, provides information on the surface backscatter characteristics. For example waveforms reflected by calm water have a very narrow and single-peaked shape. Waveforms reflected by <span class="hlt">sea</span> <span class="hlt">ice</span> show more variability due to diffuse scattering. Here we analyze altimeter waveforms from different conventional pulse-limited satellite altimeters to separate open water and <span class="hlt">sea</span> <span class="hlt">ice</span> waveforms. An unsupervised classification approach employing partitional clustering algorithms such as K-medoids and memory-based classification methods such as K-nearest neighbor is used. The classification is based on six parameters derived from the waveform's shape, for example the maximum power or the peak's width. The open-water detection is quantitatively compared to SAR images processed while accounting for <span class="hlt">sea</span> <span class="hlt">ice</span> motion. The classification results are used to derive information about the temporal evolution of <span class="hlt">sea</span> <span class="hlt">ice</span> extent and <span class="hlt">sea</span> surface heights. They allow to provide evidence on climate change relevant influences as for example Arctic <span class="hlt">sea</span> level rise due to enhanced melting rates of Greenland's glaciers and an increasing fresh water influx into the Arctic ocean. Additionally, the <span class="hlt">sea</span> <span class="hlt">ice</span> cover extent analyzed over a long-time period provides an important indicator for a globally changing climate system.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li class="active"><span>12</span></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_12 --> <div id="page_13" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li class="active"><span>13</span></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="241"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1916606M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1916606M"><span>Modelling <span class="hlt">sea</span> <span class="hlt">ice</span> dynamics</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Murawski, Jens; Kleine, Eckhard</p> <p>2017-04-01</p> <p><span class="hlt">Sea</span> <span class="hlt">ice</span> remains one of the frontiers of ocean modelling and is of vital importance for the correct forecasts of the northern oceans. At large scale, it is commonly considered a continuous medium whose dynamics is modelled in terms of continuum mechanics. Its specifics are a matter of constitutive behaviour which may be characterised as rigid-plastic. The new developed <span class="hlt">sea</span> <span class="hlt">ice</span> dynamic module bases on general principles and follows a systematic approach to the problem. Both drift field and stress field are modelled by a variational property. Rigidity is treated by Lagrangian relaxation. Thus one is led to a sensible numerical method. Modelling fast <span class="hlt">ice</span> remains to be a challenge. It is understood that ridging and the formation of grounded <span class="hlt">ice</span> keels plays a role in the process. The <span class="hlt">ice</span> dynamic model includes a parameterisation of the stress associated with grounded <span class="hlt">ice</span> keels. Shear against the grounded bottom contact might lead to plastic deformation and the loss of integrity. The numerical scheme involves a potentially large system of linear equations which is solved by pre-conditioned iteration. The entire algorithm consists of several components which result from decomposing the problem. The algorithm has been implemented and tested in practice.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012EGUGA..1413439B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012EGUGA..1413439B"><span>Changes in the seasonality of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> and temperature</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bintanja, R.</p> <p>2012-04-01</p> <p>Observations show that the Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> cover is currently declining as a result of climate warming. According to climate models, this retreat will continue and possibly accelerate in the near-future. However, the magnitude of this decline is not the same throughout the year. With temperatures near or above the freezing point, summertime Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> will quickly diminish. However, at temperatures well below freezing, the <span class="hlt">sea</span> <span class="hlt">ice</span> cover during winter will exhibit a much weaker decline. In the future, the <span class="hlt">sea</span> <span class="hlt">ice</span> seasonal cycle will be no <span class="hlt">ice</span> in summer, and thin one-year <span class="hlt">ice</span> in winter. Hence, the seasonal cycle in <span class="hlt">sea</span> <span class="hlt">ice</span> cover will increase with ongoing climate warming. This in itself leads to an increased summer-winter contrast in surface air temperature, because changes in <span class="hlt">sea</span> <span class="hlt">ice</span> have a dominant influence on Arctic temperature and its seasonality. Currently, the annual amplitude in air temperature is decreasing, however, because winters warm faster than summer. With ongoing summer <span class="hlt">sea</span> <span class="hlt">ice</span> reductions there will come a time when the annual temperature amplitude will increase again because of the large seasonal changes in <span class="hlt">sea</span> <span class="hlt">ice</span>. This suggests that changes in the seasonal cycle in Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> and temperature are closely, and intricately, connected. Future changes in Arctic seasonality (will) have an profound effect on flora, fauna, humans and economic activities.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24204642','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24204642"><span>Floating <span class="hlt">ice</span>-algal aggregates below melting arctic <span class="hlt">sea</span> <span class="hlt">ice</span>.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Assmy, Philipp; Ehn, Jens K; Fernández-Méndez, Mar; Hop, Haakon; Katlein, Christian; Sundfjord, Arild; Bluhm, Katrin; Daase, Malin; Engel, Anja; Fransson, Agneta; Granskog, Mats A; Hudson, Stephen R; Kristiansen, Svein; Nicolaus, Marcel; Peeken, Ilka; Renner, Angelika H H; Spreen, Gunnar; Tatarek, Agnieszka; Wiktor, Jozef</p> <p>2013-01-01</p> <p>During two consecutive cruises to the Eastern Central Arctic in late summer 2012, we observed floating algal aggregates in the melt-water layer below and between melting <span class="hlt">ice</span> floes of first-year pack <span class="hlt">ice</span>. The macroscopic (1-15 cm in diameter) aggregates had a mucous consistency and were dominated by typical <span class="hlt">ice</span>-associated pennate diatoms embedded within the mucous matrix. Aggregates maintained buoyancy and accumulated just above a strong pycnocline that separated meltwater and seawater layers. We were able, for the first time, to obtain quantitative abundance and biomass estimates of these aggregates. Although their biomass and production on a square metre basis was small compared to <span class="hlt">ice</span>-algal blooms, the floating <span class="hlt">ice</span>-algal aggregates supported high levels of biological activity on the scale of the individual aggregate. In addition they constituted a food source for the <span class="hlt">ice</span>-associated fauna as revealed by pigments indicative of zooplankton grazing, high abundance of naked ciliates, and <span class="hlt">ice</span> amphipods associated with them. During the Arctic melt season, these floating aggregates likely play an important ecological role in an otherwise impoverished near-surface <span class="hlt">sea</span> <span class="hlt">ice</span> environment. Our findings provide important observations and measurements of a unique aggregate-based habitat during the 2012 record <span class="hlt">sea</span> <span class="hlt">ice</span> minimum year.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3804104','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3804104"><span>Floating <span class="hlt">Ice</span>-Algal Aggregates below Melting Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span></span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Assmy, Philipp; Ehn, Jens K.; Fernández-Méndez, Mar; Hop, Haakon; Katlein, Christian; Sundfjord, Arild; Bluhm, Katrin; Daase, Malin; Engel, Anja; Fransson, Agneta; Granskog, Mats A.; Hudson, Stephen R.; Kristiansen, Svein; Nicolaus, Marcel; Peeken, Ilka; Renner, Angelika H. H.; Spreen, Gunnar; Tatarek, Agnieszka; Wiktor, Jozef</p> <p>2013-01-01</p> <p>During two consecutive cruises to the Eastern Central Arctic in late summer 2012, we observed floating algal aggregates in the melt-water layer below and between melting <span class="hlt">ice</span> floes of first-year pack <span class="hlt">ice</span>. The macroscopic (1-15 cm in diameter) aggregates had a mucous consistency and were dominated by typical <span class="hlt">ice</span>-associated pennate diatoms embedded within the mucous matrix. Aggregates maintained buoyancy and accumulated just above a strong pycnocline that separated meltwater and seawater layers. We were able, for the first time, to obtain quantitative abundance and biomass estimates of these aggregates. Although their biomass and production on a square metre basis was small compared to <span class="hlt">ice</span>-algal blooms, the floating <span class="hlt">ice</span>-algal aggregates supported high levels of biological activity on the scale of the individual aggregate. In addition they constituted a food source for the <span class="hlt">ice</span>-associated fauna as revealed by pigments indicative of zooplankton grazing, high abundance of naked ciliates, and <span class="hlt">ice</span> amphipods associated with them. During the Arctic melt season, these floating aggregates likely play an important ecological role in an otherwise impoverished near-surface <span class="hlt">sea</span> <span class="hlt">ice</span> environment. Our findings provide important observations and measurements of a unique aggregate-based habitat during the 2012 record <span class="hlt">sea</span> <span class="hlt">ice</span> minimum year. PMID:24204642</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C33B1183H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C33B1183H"><span>Multi-method Quantification of <span class="hlt">Sea-ice</span> Production in Weddell <span class="hlt">Sea</span> Polynyas (Antarctica)</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Heinemann, G.; Zentek, R.; Stulic, L.; Paul, S.; Preusser, A.; Timmermann, R.</p> <p>2017-12-01</p> <p>Coastal polynyas occur frequently during winter in the Weddell <span class="hlt">Sea</span>, which leads to strong <span class="hlt">sea</span> <span class="hlt">ice</span> production and to the formation of a highly saline water mass which is considered to be a major source of bottom water and one of the main drivers of the circulation beneath the Filchner-Ronne <span class="hlt">Ice</span> Shelf. Thus the quantification of <span class="hlt">sea</span> <span class="hlt">ice</span> production in Weddell <span class="hlt">Sea</span> polynyas is of vital interest for understanding water mass modification in this region. We use a multi-method approach to quantify <span class="hlt">sea</span> <span class="hlt">ice</span> production. Method 1) is based on the energy balance simulated by the regional climate model COSMO-CLM (CCLM) with 15 / 5 km resolution for the period 2002-2015 (nested in ERA-Interim data). Daily <span class="hlt">sea</span> <span class="hlt">ice</span> concentrations were taken from microwave satellite measurements. Method 2) is based on remote sensing using MODIS thermal infrared data at a resolution of 1-2km and a surface energy balance model taking atmospheric data from different reanalyses (ERA-Interim, JRA55, NCEP2) as well as data of CCLM. Method 3) relies on simulations using the Finite Element <span class="hlt">Sea</span> <span class="hlt">ice</span>-Ocean Model (FESOM). FESOM is run on a global grid with a resolution of about 5 km along the coast of the Weddell <span class="hlt">Sea</span> using atmospheric forcing from reanalyses (ERA-Interim (80km) and CFSR (38km)) as well as from CCLM. In addition, an experiment with assimilation of MODIS thin <span class="hlt">ice</span> retrievals was conducted. Estimates of polynya area (POLA) and <span class="hlt">sea</span> <span class="hlt">ice</span> production (IP) from the different methods are presented. The MODIS-based method with ERA-Interim shows the largest POLA as well as the largest IP for the Ronne polynya (RO, POLA / IP = 2800 km² / 29 km³/a) and for the polynya off Brunt <span class="hlt">Ice</span> Shelf (BR, 3400 km² / 30 km³/a). Sensitivity to the choice of atmosphere data is high. In particular, too low temperatures in JRA55 cause very large <span class="hlt">ice</span> production events and a strong overestimation of IP rates. Estimates based on CCLM simulations agree generally well with MODIS/ERA-Interim. FESOM yields a generally larger <span class="hlt">ice</span></p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ClDy..tmp.2399R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ClDy..tmp.2399R"><span>Links between the Amundsen <span class="hlt">Sea</span> Low and <span class="hlt">sea</span> <span class="hlt">ice</span> in the Ross <span class="hlt">Sea</span>: seasonal and interannual relationships</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Raphael, Marilyn N.; Holland, Marika M.; Landrum, Laura; Hobbs, William R.</p> <p>2018-05-01</p> <p>Previous studies have shown that <span class="hlt">sea</span> <span class="hlt">ice</span> extent in the Southern Ocean is influenced by the intensity and location of the Amundsen <span class="hlt">Sea</span> Low (ASL), through their effect on the meridional winds. However, the inhomogeneous nature of the influence of the ASL on <span class="hlt">sea</span> <span class="hlt">ice</span> as well as its influence during critical periods of the <span class="hlt">sea</span> <span class="hlt">ice</span> annual cycle is not clear. In this study, we do a spatio-temporal analysis of links between the ASL and the <span class="hlt">sea</span> <span class="hlt">ice</span> during the advance and retreat periods of the <span class="hlt">ice</span> over the period 1979-2013 focusing on the role of the meridional and zonal winds. We use the ERA-Interim monthly-averaged 500 mb geopotential height and 10 m wind data along with monthly Passive Microwave <span class="hlt">Sea</span> <span class="hlt">Ice</span> Concentrations (SIC) to examine the seasonal and interannual relationships between the ASL and SIC in the Ross-Amundsen <span class="hlt">sea</span> <span class="hlt">ice</span> sector. To characterize the state of the ASL we use indices that describe its location and its intensity. We show that the ASL has preferred locations and intensities during <span class="hlt">ice</span> advance and retreat seasons. The strength and direction of the influence of the ASL are not spatially homogeneous and can change from advance to retreat season and there are strong significant relationships between the characteristics of the ASL and SIC, within and across seasons and interannually.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUOSHE24A1423M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUOSHE24A1423M"><span>Aircraft Surveys of the Beaufort <span class="hlt">Sea</span> Seasonal <span class="hlt">Ice</span> Zone</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Morison, J.</p> <p>2016-02-01</p> <p>The Seasonal <span class="hlt">Ice</span> Zone Reconnaissance Surveys (SIZRS) is a program of repeated ocean, <span class="hlt">ice</span>, and atmospheric measurements across the Beaufort-Chukchi <span class="hlt">sea</span> seasonal <span class="hlt">sea</span> <span class="hlt">ice</span> zone (SIZ) utilizing US Coast Guard Arctic Domain Awareness (ADA) flights of opportunity. The SIZ is the region between maximum winter <span class="hlt">sea</span> <span class="hlt">ice</span> extent and minimum summer <span class="hlt">sea</span> <span class="hlt">ice</span> extent. As such, it contains the full range of positions of the marginal <span class="hlt">ice</span> zone (MIZ) where <span class="hlt">sea</span> <span class="hlt">ice</span> interacts with open water. The increasing size and changing air-<span class="hlt">ice</span>-ocean properties of the SIZ are central to recent reductions in Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> extent. The changes in the interplay among the atmosphere, <span class="hlt">ice</span>, and ocean require a systematic SIZ observational effort of coordinated atmosphere, <span class="hlt">ice</span>, and ocean observations covering up to interannual time-scales, Therefore, every year beginning in late Spring and continuing to early Fall, SIZRS makes monthly flights across the Beaufort <span class="hlt">Sea</span> SIZ aboard Coast Guard C-130H aircraft from USCG Air Station Kodiak dropping Aircraft eXpendable CTDs (AXCTD) and Aircraft eXpendable Current Profilers (AXCP) for profiles of ocean temperature, salinity and shear, dropsondes for atmospheric temperature, humidity, and velocity profiles, and buoys for atmosphere and upper ocean time series. Enroute measurements include IR imaging, radiometer and lidar measurements of the <span class="hlt">sea</span> surface and cloud tops. SIZRS also cooperates with the International Arctic Buoy Program for buoy deployments and with the NOAA Earth System Research Laboratory atmospheric chemistry sampling program on board the aircraft. Since 2012, SIZRS has found that even as SIZ extent, <span class="hlt">ice</span> character, and atmospheric forcing varies year-to-year, the pattern of ocean freshening and radiative warming south of the <span class="hlt">ice</span> edge is consistent. The experimental approach, observations and extensions to other projects will be discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AHEEM..64..115S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AHEEM..64..115S"><span>SPH Modelling of <span class="hlt">Sea-ice</span> Pack Dynamics</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Staroszczyk, Ryszard</p> <p>2017-12-01</p> <p>The paper is concerned with the problem of <span class="hlt">sea-ice</span> pack motion and deformation under the action of wind and water currents. Differential equations describing the dynamics of <span class="hlt">ice</span>, with its very distinct mateFfigrial responses in converging and diverging flows, express the mass and linear momentum balances on the horizontal plane (the free surface of the ocean). These equations are solved by the fully Lagrangian method of smoothed particle hydrodynamics (SPH). Assuming that the <span class="hlt">ice</span> behaviour can be approximated by a non-linearly viscous rheology, the proposed SPH model has been used to simulate the evolution of a <span class="hlt">sea-ice</span> pack driven by wind drag stresses. The results of numerical simulations illustrate the evolution of an <span class="hlt">ice</span> pack, including variations in <span class="hlt">ice</span> thickness and <span class="hlt">ice</span> area fraction in space and time. The effects of different initial <span class="hlt">ice</span> pack configurations and of different conditions assumed at the coast-<span class="hlt">ice</span> interface are examined. In particular, the SPH model is applied to a pack flow driven by a vortex wind to demonstrate how well the Lagrangian formulation can capture large deformations and displacements of <span class="hlt">sea</span> <span class="hlt">ice</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009EGUGA..1113752H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009EGUGA..1113752H"><span>L-band radiometry for <span class="hlt">sea</span> <span class="hlt">ice</span> applications</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Heygster, G.; Hedricks, S.; Mills, P.; Kaleschke, L.; Stammer, D.; Tonboe, R.</p> <p>2009-04-01</p> <p>Although <span class="hlt">sea</span> <span class="hlt">ice</span> remote sensing has reached the level of operational exploitation with well established retrieval methods, several important tasks are still unsolved. In particular during freezing and melting periods with mixed <span class="hlt">ice</span> and water surfaces, estimates of <span class="hlt">ice</span> concentration with passive and active microwave sensors remain challenging. Newly formed thin <span class="hlt">ice</span> is also hard to distinguish from open water with radiometers for frequencies above 8 GHz. The SMOS configuration (planned launch 2009) with a radiometer at 1.4 GHz is a promising technique to complement observations at higher microwave frequencies. ESA has initiated a project to investigate the possibilities for an additional Level-2 <span class="hlt">sea</span> <span class="hlt">ice</span> data product based on SMOS. In detail, the project objectives are (1) to model the L band emission of <span class="hlt">sea</span> <span class="hlt">ice</span>, and to assess the potential (2) to retrieve <span class="hlt">sea</span> <span class="hlt">ice</span> parameters, especially concentration and thickness, and (3) to use cold water regions for an external calibration of SMOS. Modelling of L band emission: Several models have are investigated. All of them work on the same basic principles and have a vertically-layered, plane-parallel geometry. They are comprised of three basic components: (1) effective permittivities are calculated for each layer based on <span class="hlt">ice</span> bulk and micro-structural properties; (2) these are integrated across the total depth to derive emitted brightness temperature; (3) scattering terms can also be added because of the granular structure of <span class="hlt">ice</span> and snow. MEMLS (Microwave Emission Model of Layered Snowpacks (Wiesmann and Matzler 1999)) is one such model that contains all three elements in a single Matlab program. In the absence of knowledge about the internal structure of the <span class="hlt">sea</span> <span class="hlt">ice</span>, three-layer (air, <span class="hlt">ice</span> and water) dielectric slab models which take as input a single effective permittivity for the <span class="hlt">ice</span> layer are appropriate. By ignoring scattering effects one can derive a simple analytic expression for a dielectric slab as shown by Apinis and</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C11D..05H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C11D..05H"><span>An Investigation of the Radiative Effects and Climate Feedbacks of <span class="hlt">Sea</span> <span class="hlt">Ice</span> Sources of <span class="hlt">Sea</span> Salt Aerosol</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Horowitz, H. M.; Alexander, B.; Bitz, C. M.; Jaegle, L.; Burrows, S. M.</p> <p>2017-12-01</p> <p>In polar regions, <span class="hlt">sea</span> <span class="hlt">ice</span> is a major source of <span class="hlt">sea</span> salt aerosol through lofting of saline frost flowers or blowing saline snow from the <span class="hlt">sea</span> <span class="hlt">ice</span> surface. Under continued climate warming, an <span class="hlt">ice</span>-free Arctic in summer with only first-year, more saline <span class="hlt">sea</span> <span class="hlt">ice</span> in winter is likely. Previous work has focused on climate impacts in summer from increasing open ocean <span class="hlt">sea</span> salt aerosol emissions following complete <span class="hlt">sea</span> <span class="hlt">ice</span> loss in the Arctic, with conflicting results suggesting no net radiative effect or a negative climate feedback resulting from a strong first aerosol indirect effect. However, the radiative forcing from changes to the <span class="hlt">sea</span> <span class="hlt">ice</span> sources of <span class="hlt">sea</span> salt aerosol in a future, warmer climate has not previously been explored. Understanding how <span class="hlt">sea</span> <span class="hlt">ice</span> loss affects the Arctic climate system requires investigating both open-ocean and <span class="hlt">sea</span> <span class="hlt">ice</span> sources of <span class="hlt">sea</span>-salt aerosol and their potential interactions. Here, we implement a blowing snow source of <span class="hlt">sea</span> salt aerosol into the Community Earth System Model (CESM) dynamically coupled to the latest version of the Los Alamos <span class="hlt">sea</span> <span class="hlt">ice</span> model (CICE5). Snow salinity is a key parameter affecting blowing snow <span class="hlt">sea</span> salt emissions and previous work has assumed constant regional snow salinity over <span class="hlt">sea</span> <span class="hlt">ice</span>. We develop a parameterization for dynamic snow salinity in the <span class="hlt">sea</span> <span class="hlt">ice</span> model and examine how its spatial and temporal variability impacts the production of <span class="hlt">sea</span> salt from blowing snow. We evaluate and constrain the snow salinity parameterization using available observations. Present-day coupled CESM-CICE5 simulations of <span class="hlt">sea</span> salt aerosol concentrations including <span class="hlt">sea</span> <span class="hlt">ice</span> sources are evaluated against in situ and satellite (CALIOP) observations in polar regions. We then quantify the present-day radiative forcing from the addition of blowing snow <span class="hlt">sea</span> salt aerosol with respect to aerosol-radiation and aerosol-cloud interactions. The relative contributions of <span class="hlt">sea</span> <span class="hlt">ice</span> vs. open ocean sources of <span class="hlt">sea</span> salt aerosol to radiative forcing in polar regions is</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA572179','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA572179"><span>Mass Balance of Multiyear <span class="hlt">Sea</span> <span class="hlt">Ice</span> in the Southern Beaufort <span class="hlt">Sea</span></span></a></p> <p><a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>2012-09-30</p> <p>datasets. Table 1 lists the primary data sources to be used. To determine sources and sinks of MY <span class="hlt">ice</span>, we use a simple model of MY <span class="hlt">ice</span> circulation, which is...shown in Figure 1. In this model , we consider the Beaufort <span class="hlt">Sea</span> to consist of four zones defined by mean drift of <span class="hlt">sea</span> <span class="hlt">ice</span> in summer and winter, such...Healy/Louis S. St. Laurant cruises 1 Seasonal <span class="hlt">Ice</span> Zone Observing Network 2 Polar Airborne Measurements and Arctic Regional Climate Model</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUOSHE14B1411P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUOSHE14B1411P"><span>Atmospheric form drag over Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> derived from high-resolution <span class="hlt">Ice</span>Bridge elevation data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Petty, A.; Tsamados, M.; Kurtz, N. T.</p> <p>2016-02-01</p> <p>Here we present a detailed analysis of atmospheric form drag over Arctic <span class="hlt">sea</span> <span class="hlt">ice</span>, using high resolution, three-dimensional surface elevation data from the NASA Operation <span class="hlt">Ice</span>Bridge Airborne Topographic Mapper (ATM) laser altimeter. Surface features in the <span class="hlt">sea</span> <span class="hlt">ice</span> cover are detected using a novel feature-picking algorithm. We derive information regarding the height, spacing and orientation of unique surface features from 2009-2014 across both first-year and multiyear <span class="hlt">ice</span> regimes. The topography results are used to explicitly calculate atmospheric form drag coefficients; utilizing existing form drag parameterizations. The atmospheric form drag coefficients show strong regional variability, mainly due to variability in <span class="hlt">ice</span> type/age. The transition from a perennial to a seasonal <span class="hlt">ice</span> cover therefore suggest a decrease in the atmospheric form drag coefficients over Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> in recent decades. These results are also being used to calibrate a recent form drag parameterization scheme included in the <span class="hlt">sea</span> <span class="hlt">ice</span> model CICE, to improve the representation of form drag over Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> in global climate models.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/AD1013711','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/AD1013711"><span>Operationally Merged Satellite Visible/IR and Passive Microwave <span class="hlt">Sea</span> <span class="hlt">Ice</span> Information for Improved <span class="hlt">Sea</span> <span class="hlt">Ice</span> Forecasts and Ship Routing</span></a></p> <p><a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>2015-09-30</p> <p>microwave <span class="hlt">sea</span> <span class="hlt">ice</span> information for improved <span class="hlt">sea</span> <span class="hlt">ice</span> forecasts and ship routing W. Meier NASA Goddard Space Flight Center, Cryospheric Sciences Laboratory...updating the initial <span class="hlt">ice</span> concentration analysis fields along the <span class="hlt">ice</span> edge. In the past year, NASA Goddard and NRL have generated a merged 4 km AMSR-E...collaborations of three groups: NASA Goddard Space Flight Center ( NASA /GSFC) in Greenbelt, MD, NRL/Oceanography Division located at Stennis Space Center (SSC</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19990084033&hterms=divergent+series&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Ddivergent%2Bseries','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19990084033&hterms=divergent+series&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Ddivergent%2Bseries"><span>C-Band Backscatter Measurements of Winter <span class="hlt">Sea-Ice</span> in the Weddell <span class="hlt">Sea</span>, Antarctica</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Drinkwater, M. R.; Hosseinmostafa, R.; Gogineni, P.</p> <p>1995-01-01</p> <p>During the 1992 Winter Weddell Gyre Study, a C-band scatterometer was used from the German <span class="hlt">ice</span>-breaker R/V Polarstern to obtain detailed shipborne measurement scans of Antarctic <span class="hlt">sea-ice</span>. The frequency-modulated continuous-wave (FM-CW) radar operated at 4-3 GHz and acquired like- (VV) and cross polarization (HV) data at a variety of incidence angles (10-75 deg). Calibrated backscatter data were recorded for several <span class="hlt">ice</span> types as the icebreaker crossed the Weddell <span class="hlt">Sea</span> and detailed measurements were made of corresponding snow and <span class="hlt">sea-ice</span> characteristics at each measurement site, together with meteorological information, radiation budget and oceanographic data. The primary scattering contributions under cold winter conditions arise from the air/snow and snow/<span class="hlt">ice</span> interfaces. Observations indicate so e similarities with Arctic <span class="hlt">sea-ice</span> scattering signatures, although the main difference is generally lower mean backscattering coefficients in the Weddell <span class="hlt">Sea</span>. This is due to the younger mean <span class="hlt">ice</span> age and thickness, and correspondingly higher mean salinities. In particular, smooth white <span class="hlt">ice</span> found in 1992 in divergent areas within the Weddell Gyre <span class="hlt">ice</span> pack was generally extremely smooth and undeformed. Comparisons of field scatterometer data with calibrated 20-26 deg incidence ERS-1 radar image data show close correspondence, and indicate that rough Antarctic first-year and older second-year <span class="hlt">ice</span> forms do not produce as distinctively different scattering signatures as observed in the Arctic. Thick deformed first-year and second-year <span class="hlt">ice</span> on the other hand are clearly discriminated from younger undeformed <span class="hlt">ice</span>. thereby allowing successful separation of thick and thin <span class="hlt">ice</span>. Time-series data also indicate that C-band is sensitive to changes in snow and <span class="hlt">ice</span> conditions resulting from atmospheric and oceanographic forcing and the local heat flux environment. Variations of several dB in 45 deg incidence backscatter occur in response to a combination of thermally-regulated parameters</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19810011207','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19810011207"><span>Oceanographic influences on the <span class="hlt">sea</span> <span class="hlt">ice</span> cover in the <span class="hlt">Sea</span> of Okhotsk</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Gratz, A. J.; Parkinson, C. L.</p> <p>1981-01-01</p> <p><span class="hlt">Sea</span> <span class="hlt">ice</span> conditions in the <span class="hlt">Sea</span> of Okhotsk, as determined by satellite images from the electrically scanning microwave radiometer on board Nimbus 5, were analyzed in conjunction with the known oceanography. In particular, the <span class="hlt">sea</span> <span class="hlt">ice</span> coverage was compared with the bottom bathymetry and the surface currents, water temperatures, and salinity. It is found that <span class="hlt">ice</span> forms first in cold, shallow, low salinity waters. Once formed, the <span class="hlt">ice</span> seems to drift in a direction approximating the Okhotsk-Kuril current system. Two basic patterns of <span class="hlt">ice</span> edge positioning which persist for significant periods were identified as a rectangular structure and a wedge structure. Each of these is strongly correlated with the bathymetry of the region and with the known current system, suggesting that convective depth and ocean currents play an important role in determining <span class="hlt">ice</span> patterns.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA617621','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA617621"><span>Wave-<span class="hlt">Ice</span> and Air-<span class="hlt">Ice</span>-Ocean Interaction During the Chukchi <span class="hlt">Sea</span> <span class="hlt">Ice</span> Edge Advance</span></a></p> <p><a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>2014-09-30</p> <p>During cruise CU-B UAF UW Airborne expendable <span class="hlt">Ice</span> Buoy (AXIB) Ahead, at and inside <span class="hlt">ice</span> edge Surface meteorology T, SLP ~1 year CU-B UW...Balance (IMB) buoys Inside <span class="hlt">ice</span> edge w/ >50cm thickness <span class="hlt">Ice</span> mass balance T in snow-<span class="hlt">ice</span>-ocean, T, SLP at surface ~1 year WHOI CRREL (<span class="hlt">Sea</span>State DRI</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2003AGUFM.C41C0992L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2003AGUFM.C41C0992L"><span>The Role of Laboratory-Based Studies of the Physical and Biological Properties of <span class="hlt">Sea</span> <span class="hlt">Ice</span> in Supporting the Observation and Modeling of <span class="hlt">Ice</span> Covered <span class="hlt">Seas</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Light, B.; Krembs, C.</p> <p>2003-12-01</p> <p>Laboratory-based studies of the physical and biological properties of <span class="hlt">sea</span> <span class="hlt">ice</span> are an essential link between high latitude field observations and existing numerical models. Such studies promote improved understanding of climatic variability and its impact on <span class="hlt">sea</span> <span class="hlt">ice</span> and the structure of <span class="hlt">ice</span>-dependent marine ecosystems. Controlled laboratory experiments can help identify feedback mechanisms between physical and biological processes and their response to climate fluctuations. Climatically sensitive processes occurring between <span class="hlt">sea</span> <span class="hlt">ice</span> and the atmosphere and <span class="hlt">sea</span> <span class="hlt">ice</span> and the ocean determine surface radiative energy fluxes and the transfer of nutrients and mass across these boundaries. High temporally and spatially resolved analyses of <span class="hlt">sea</span> <span class="hlt">ice</span> under controlled environmental conditions lend insight to the physics that drive these transfer processes. Techniques such as optical probing, thin section photography, and microscopy can be used to conduct experiments on natural <span class="hlt">sea</span> <span class="hlt">ice</span> core samples and laboratory-grown <span class="hlt">ice</span>. Such experiments yield insight on small scale processes from the microscopic to the meter scale and can be powerful interdisciplinary tools for education and model parameterization development. Examples of laboratory investigations by the authors include observation of the response of <span class="hlt">sea</span> <span class="hlt">ice</span> microstructure to changes in temperature, assessment of the relationships between <span class="hlt">ice</span> structure and the partitioning of solar radiation by first-year <span class="hlt">sea</span> <span class="hlt">ice</span> covers, observation of pore evolution and interfacial structure, and quantification of the production and impact of microbial metabolic products on the mechanical, optical, and textural characteristics of <span class="hlt">sea</span> <span class="hlt">ice</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.C24B..08B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.C24B..08B"><span>Airborne Grid <span class="hlt">Sea-Ice</span> Surveys for Comparison with CryoSat-2</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Brozena, J. M.; Gardner, J. M.; Liang, R.; Hagen, R. A.; Ball, D.</p> <p>2014-12-01</p> <p>The U.S. Naval Research Laboratory is engaged in a study of the changing Arctic with a particular focus on <span class="hlt">ice</span> thickness and distribution variability. The purpose is to optimize computer models used to predict <span class="hlt">sea</span> <span class="hlt">ice</span> changes. An important part of our study is to calibrate/validate CryoSat-2 <span class="hlt">ice</span> thickness data prior to its incorporation into new <span class="hlt">ice</span> forecast models. The large footprint of the CryoSat-2 altimeter over <span class="hlt">sea-ice</span> is a significant issue in any attempt to ground-truth the data. Along-track footprints are reduced to ~ 300 m by SAR processing of the returns. However, the cross-track footprint is determined by the topography of the surface. Further, the actual return is the sum of the returns from individual reflectors within the footprint making it difficult to interpret the return, and optimize the waveform tracker. We therefore collected a series of grids of airborne scanning lidar and nadir pointing radar on sub-satellite tracks over <span class="hlt">sea-ice</span> that would extend far enough cross-track to capture the illuminated area. One difficulty in the collection of grids comprised of <span class="hlt">adjacent</span> overlapping tracks is that the <span class="hlt">ice</span> moves as much as 300 m over the duration of a single track (~ 10 min). With a typical lidar swath width of 500m we needed to adjust the survey tracks in near real-time for the <span class="hlt">ice</span> motion. This was accomplished by a photogrammetric method of <span class="hlt">ice</span> velocity determination (RTIME) reported in another presentation. Post-processing refinements resulted in typical track-to-track miss-ties of ~ 1-2 m, much of which could be attributed to <span class="hlt">ice</span> deformation over the period of the survey. An important factor is that we were able to reconstruct the <span class="hlt">ice</span> configuration at the time of the satellite overflight, resulting in an accurate representation of the surface illuminated by CryoSat-2. Our intention is to develop a model of the <span class="hlt">ice</span> surface using the lidar grid which includes both snow and <span class="hlt">ice</span> using radar profiles to determine snow thickness. In 2013 a set of 6</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.C31B0652O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.C31B0652O"><span>Observing Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> from Bow to Screen: Introducing <span class="hlt">Ice</span> Watch, the Data Network of Near Real-Time and Historic Observations from the Arctic Shipborne <span class="hlt">Sea</span> <span class="hlt">Ice</span> Standardization Tool (ASSIST)</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Orlich, A.; Hutchings, J. K.; Green, T. M.</p> <p>2013-12-01</p> <p>The <span class="hlt">Ice</span> Watch Program is an open source forum to access in situ Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> conditions. It provides the research community and additional stakeholders a convenient resource to monitor <span class="hlt">sea</span> <span class="hlt">ice</span> and its role in understanding the Arctic as a system by implementing a standardized observation protocol and hosting a multi-service data portal. International vessels use the Arctic Shipborne <span class="hlt">Sea</span> <span class="hlt">Ice</span> Standardization Tool (ASSIST) software to report near-real time <span class="hlt">sea</span> <span class="hlt">ice</span> conditions while underway. Essential observations of total <span class="hlt">ice</span> concentration, distribution of multi-year <span class="hlt">ice</span> and other <span class="hlt">ice</span> types, as well as their respective stage of melt are reported. These current and historic <span class="hlt">sea</span> <span class="hlt">ice</span> conditions are visualized on interactive maps and in a variety of statistical analyses, and with all data sets available to download for further investigation. The summer of 2012 was the debut of the ASSIST software and the <span class="hlt">Ice</span> Watch campaign, with research vessels from six nations reporting from a wide spatio-temporal scale spanning from the Beaufort <span class="hlt">Sea</span>, across the North Pole and Arctic Basin, the coast of Greenland and into the Kara and Barents <span class="hlt">Seas</span> during mid-season melt and into the first stages of freeze-up. The 2013 summer field season sustained the observation and data archiving record, with participation from some of the same cruises as well as other geographic and seasonal realms covered by new users. These results are presented to illustrate the evolution of the program, increased participation and critical statistics of <span class="hlt">ice</span> regime change and record of melt and freeze processes revealed by the data. As an ongoing effort, <span class="hlt">Ice</span> Watch/ASSIST aims to standardize observations of Arctic-specific <span class="hlt">sea</span> <span class="hlt">ice</span> features and conditions while utilizing nomenclature and coding based on the World Meteorological Organization (WMO) standards and the Antarctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> and Processes & Climate (ASPeCt) protocol. Instigated by members of the CliC <span class="hlt">Sea</span> <span class="hlt">Ice</span> Working Group, the program has evolved with</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C53B0782B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C53B0782B"><span>Airborne Grid <span class="hlt">Sea-Ice</span> Surveys for Comparison with Cryosat-2</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Brozena, J. M.; Gardner, J. M.; Liang, R.; Hagen, R. A.; Ball, D.; Newman, T.</p> <p>2015-12-01</p> <p>The Naval Research Laboratory is studying of the changing Arctic with a focus on <span class="hlt">ice</span> thickness and distribution variability. The goal is optimization of computer models used to predict <span class="hlt">sea</span> <span class="hlt">ice</span> changes. An important part of our study is to calibrate/validate Cryosat-2 <span class="hlt">ice</span> thickness data prior to its incorporation into new <span class="hlt">ice</span> forecast models. The footprint of the altimeter over <span class="hlt">sea-ice</span> is a significant issue in any attempt to ground-truth the data. Along-track footprints are reduced to ~ 300 m by SAR processing of the returns. However, the cross-track footprint is determined by the topography of the surface. Further, the actual return is the sum of the returns from individual reflectors within the footprint making it difficult to interpret the return, and optimize the waveform tracker. We therefore collected a series of grids of scanning LiDAR and radar on sub-satellite tracks over <span class="hlt">sea-ice</span> that would extend far enough cross-track to capture the illuminated area. The difficulty in the collection of such grids, which are comprised of <span class="hlt">adjacent</span> overlapping tracks is <span class="hlt">ice</span> motion of as much as 300 m over the duration of a single flight track (~ 20 km) of data collection. With a typical LiDAR swath width of < 500m adjustment of the survey tracks in near real-time for the <span class="hlt">ice</span> motion is necessary for a coherent data set. This was accomplished by a an NRL devised photogrammetric method of <span class="hlt">ice</span> velocity determination. Post-processing refinements resulted in typical track-to-track miss-ties of ~ 1-2 m, much of which could be attributed to <span class="hlt">ice</span> deformation over the period of the survey. This allows us to reconstruct the <span class="hlt">ice</span> configuration to the time of the satellite overflight, resulting in a good picture of the surface actually illuminated by the radar. The detailed 2-d LiDAR image is the snow surface, not the underlying <span class="hlt">ice</span> presumably illuminated by the radar. Our hope is that the 1-D radar profiles collected along the LiDAR swath centerlines will be sufficient to correct the</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li class="active"><span>13</span></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_13 --> <div id="page_14" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li class="active"><span>14</span></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="261"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C21A0658Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C21A0658Z"><span>Changes in Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> Thickness and Floe Size</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhang, J.; Schweiger, A. J. B.; Stern, H. L., III; Steele, M.</p> <p>2016-12-01</p> <p>A thickness, floe size, and enthalpy distribution <span class="hlt">sea</span> <span class="hlt">ice</span> model was implemented into the Pan-arctic <span class="hlt">Ice</span>-Ocean Modeling and Assimilation System (PIOMAS) by coupling the Zhang et al. [2015] <span class="hlt">sea</span> <span class="hlt">ice</span> floe size distribution (FSD) theory with the Thorndike et al. [1975] <span class="hlt">ice</span> thickness distribution (ITD) theory in order to explicitly simulate multicategory FSD and ITD simultaneously. A range of <span class="hlt">ice</span> thickness and floe size observations were used for model calibration and validation. The expanded, validated PIOMAS was used to study <span class="hlt">sea</span> <span class="hlt">ice</span> response to atmospheric and oceanic changes in the Arctic, focusing on the interannual variability and trends of <span class="hlt">ice</span> thickness and floe size over the period 1979-2015. It is found that over the study period both <span class="hlt">ice</span> thickness and floe size have been decreasing steadily in the Arctic. The simulated <span class="hlt">ice</span> thickness shows considerable spatiotemporal variability in recent years. As the <span class="hlt">ice</span> cover becomes thinner and weaker, the model simulates an increasing number of small floes (at the low end of the FSD), which affects <span class="hlt">sea</span> <span class="hlt">ice</span> properties, particularly in the marginal <span class="hlt">ice</span> zone.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C43B0761S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C43B0761S"><span>Current Status and Future Plan of Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> monitoring in South Korea</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Shin, J.; Park, J.</p> <p>2016-12-01</p> <p>Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> is one of the most important parameters in climate. For monitoring of <span class="hlt">sea</span> <span class="hlt">ice</span> changes, the National Meteorological Satellite Center (NMSC) of Korea Metrological Administration has developed the "Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> monitoring system" to retrieve the <span class="hlt">sea</span> <span class="hlt">ice</span> extent and surface roughness using microwave sensor data, and statistical prediction model for Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> extent. This system has been implemented to the web site for real-time public service. The <span class="hlt">sea</span> <span class="hlt">ice</span> information can be retrieved using the spaceborne microwave sensor-Special Sensor Microwave Imager/Sounder (SSMI/S). The <span class="hlt">sea</span> <span class="hlt">ice</span> information like <span class="hlt">sea</span> <span class="hlt">ice</span> extent, <span class="hlt">sea</span> <span class="hlt">ice</span> surface roughness, and predictive <span class="hlt">sea</span> <span class="hlt">ice</span> extent are produced weekly base since 2007. We also publish the "Analysis report of the Arctic <span class="hlt">sea</span> <span class="hlt">ice</span>" twice a year. We are trying to add more <span class="hlt">sea</span> <span class="hlt">ice</span> information into this system. Details of current status and future plan of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> monitoring and the methodology of the <span class="hlt">sea</span> <span class="hlt">ice</span> information retrievals will be presented in the meeting.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUSM.C24A..01S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUSM.C24A..01S"><span><span class="hlt">Sea</span> <span class="hlt">Ice</span> Formation Rate and Temporal Variation of Temperature and Salinity at the Vicinity of Wilkins <span class="hlt">Ice</span> Shelf from Data Collected by Southern Elephant Seals in 2008</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Santini, M. F.; Souza, R.; Wainer, I.; Muelbert, M.; Hindell, M.</p> <p>2013-05-01</p> <p>The use of marine mammals as autonomous platforms for collecting oceanographic data has revolutionized the understanding of physical properties of low or non-sampled regions of the polar oceans. The use of these animals became possible due to advancements in the development of electronic devices, sensors and batteries carried by them. Oceanographic data collected by two southern elephant seals (Mirounga leonina) during the Fall of 2008 were used to infer the <span class="hlt">sea-ice</span> formation rate in the region <span class="hlt">adjacent</span> to the Wilkins <span class="hlt">Ice</span> Shelf, west of the Antarctic Peninsula at that period. The <span class="hlt">sea-ice</span> formation rate was estimated from the salt balance equation for the upper (100 m) ocean at a daily frequency for the period between 13 February and 20 June 2008. The oceanographic data collected by the animals were also used to present the temporal variation of the water temperature and salinity from surface to 300 m depth in the study area. <span class="hlt">Sea</span> <span class="hlt">ice</span> formation rate ranged between 0,087 m/day in early April and 0,008 m/day in late June. Temperature and salinity ranged from -1.84°C to 1.60°C and 32.85 to 34.85, respectively, for the upper 300 m of the water column in the analyzed period. The <span class="hlt">sea-ice</span> formation rate estimations do not consider water advection, only temporal changes of the vertical profile of salinity. This may cause underestimates of the real <span class="hlt">sea-ice</span> formation rate. The intense reduction of <span class="hlt">sea</span> <span class="hlt">ice</span> rate formation from April to June 2008 may be related to the intrusion of the Circumpolar Depth Water (CDW) into the study region. As a consequence of that we believe that this process can be partly responsible for the disintegration of the Wilkins <span class="hlt">Ice</span> Shelf during the winter of 2008. The data presented here are considered a new frontier in physical and biological oceanography, providing a new approach for monitoring <span class="hlt">sea</span> <span class="hlt">ice</span> changes and oceanographic conditions in polar oceans. This is especially valid for regions covered by <span class="hlt">sea</span> <span class="hlt">ice</span> where traditional instruments deployed by</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1997JCli...10..593W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1997JCli...10..593W"><span>Modeling of Antarctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> in a General Circulation Model.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wu, Xingren; Simmonds, Ian; Budd, W. F.</p> <p>1997-04-01</p> <p>A dynamic-thermodynamic <span class="hlt">sea</span> <span class="hlt">ice</span> model is developed and coupled with the Melbourne University general circulation model to simulate the seasonal cycle of the Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> distribution. The model is efficient, rapid to compute, and useful for a range of climate studies. The thermodynamic part of the <span class="hlt">sea</span> <span class="hlt">ice</span> model is similar to that developed by Parkinson and Washington, the dynamics contain a simplified <span class="hlt">ice</span> rheology that resists compression. The thermodynamics is based on energy conservation at the top surface of the <span class="hlt">ice</span>/snow, the <span class="hlt">ice</span>/water interface, and the open water area to determine the <span class="hlt">ice</span> formation, accretion, and ablation. A lead parameterization is introduced with an effective partitioning scheme for freezing between and under the <span class="hlt">ice</span> floes. The dynamic calculation determines the motion of <span class="hlt">ice</span>, which is forced with the atmospheric wind, taking account of <span class="hlt">ice</span> resistance and rafting. The simulated <span class="hlt">sea</span> <span class="hlt">ice</span> distribution compares reasonably well with observations. The seasonal cycle of <span class="hlt">ice</span> extent is well simulated in phase as well as in magnitude. Simulated <span class="hlt">sea</span> <span class="hlt">ice</span> thickness and concentration are also in good agreement with observations over most regions and serve to indicate the importance of advection and ocean drift in the determination of the <span class="hlt">sea</span> <span class="hlt">ice</span> distribution.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/biblio/484365-modeling-antarctic-sea-ice-general-circulation-model','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/484365-modeling-antarctic-sea-ice-general-circulation-model"><span>Modeling of Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> in a general circulation model</span></a></p> <p><a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Wu, Xingren; Budd, W.F.; Simmonds, I.</p> <p>1997-04-01</p> <p>A dynamic-thermodynamic <span class="hlt">sea</span> <span class="hlt">ice</span> model is developed and coupled with the Melbourne University general circulation model to simulate the seasonal cycle of the Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> distributions The model is efficient, rapid to compute, and useful for a range of climate studies. The thermodynamic part of the <span class="hlt">sea</span> <span class="hlt">ice</span> model is similar to that developed by Parkinson and Washington, the dynamics contain a simplified <span class="hlt">ice</span> rheology that resists compression. The thermodynamics is based on energy conservation at the top surface of the <span class="hlt">ice</span>/snow, the <span class="hlt">ice</span>/water interface, and the open water area to determine the <span class="hlt">ice</span> formation, accretion, and ablation. Amore » lead parameterization is introduced with an effective partitioning scheme for freezing between and under the <span class="hlt">ice</span> floes. The dynamic calculation determines the motion of <span class="hlt">ice</span>, which is forced with the atmospheric wind, taking account of <span class="hlt">ice</span> resistance and rafting. The simulated <span class="hlt">sea</span> <span class="hlt">ice</span> distribution compares reasonably well with observations. The seasonal cycle of <span class="hlt">ice</span> extent is well simulated in phase as well as in magnitude. Simulated <span class="hlt">sea</span> <span class="hlt">ice</span> thickness and concentration are also in good agreement with observations over most regions and serve to indicate the importance of advection and ocean drift in the determination of the <span class="hlt">sea</span> <span class="hlt">ice</span> distribution. 64 refs., 15 figs., 2 tabs.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ERL....12h4011A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ERL....12h4011A"><span>Warming in the Nordic <span class="hlt">Seas</span>, North Atlantic storms and thinning Arctic <span class="hlt">sea</span> <span class="hlt">ice</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Alexeev, Vladimir A.; Walsh, John E.; Ivanov, Vladimir V.; Semenov, Vladimir A.; Smirnov, Alexander V.</p> <p>2017-08-01</p> <p>Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> over the last few decades has experienced a significant decline in coverage both in summer and winter. The currently warming Atlantic Water layer has a pronounced impact on <span class="hlt">sea</span> <span class="hlt">ice</span> in the Nordic <span class="hlt">Seas</span> (including the Barents <span class="hlt">Sea</span>). More open water combined with the prevailing atmospheric pattern of airflow from the southeast, and persistent North Atlantic storms such as the recent extremely strong Storm Frank in December 2015, lead to increased energy transport to the high Arctic. Each of these storms brings sizeable anomalies of heat to the high Arctic, resulting in significant warming and slowing down of <span class="hlt">sea</span> <span class="hlt">ice</span> growth or even melting. Our analysis indicates that the recently observed <span class="hlt">sea</span> <span class="hlt">ice</span> decline in the Nordic <span class="hlt">Seas</span> during the cold season around Svalbard, Franz Joseph Land and Novaya Zemlya, and the associated heat release from open water into the atmosphere, contributed significantly to the increase in the downward longwave radiation throughout the entire Arctic. Added to other changes in the surface energy budget, this increase since the 1960s to the present is estimated to be at least 10 W m-2, which can result in thinner (up to at least 15-20 cm) Arctic <span class="hlt">ice</span> at the end of the winter. This change in the surface budget is an important contributing factor accelerating the thinning of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70012473','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70012473"><span>Arctic continental shelf morphology related to <span class="hlt">sea-ice</span> zonation, Beaufort <span class="hlt">Sea</span>, Alaska</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Reimnitz, E.; Toimil, L.; Barnes, P.</p> <p>1978-01-01</p> <p>Landsat-1 and NOAA satellite imagery for the winter 1972-1973, and a variety of <span class="hlt">ice</span> and <span class="hlt">sea</span>-floor data were used to study <span class="hlt">sea-ice</span> zonation and dynamics and their relation to bottom morphology and geology on the Beaufort <span class="hlt">Sea</span> continental shelf of arctic Alaska. In early winter the location of the boundary between undeformed fast <span class="hlt">ice</span> and westward-drifting pack <span class="hlt">ice</span> of the Pacific Gyre is controlled by major coastal promontories. Pronounced linear pressure- and shear-ridges, as well as hummock fields, form along this boundary and are stabilized by grounding, generally between the 10- and 20-m isobaths. Slippage along this boundary occurs intermittently at or seaward of the grounded ridges, forming new grounded ridges in a widening zone, the stamukhi zone, which by late winter extends out to the 40-m isobath. Between intermittent events along the stamukhi zone, pack-<span class="hlt">ice</span> drift and slippage is continuous along the shelf edge, at average rates of 3-10 km/day. Whether slippage occurs along the stamukhi zone or along the shelf edge, it is restricted to a zone several hundred meters wide, and <span class="hlt">ice</span> seaward of the slip face moves at uniform rates without discernible drag effects. A causal relationship is seen between the spatial distribution of major <span class="hlt">ice</span>-ridge systems and offshore shoals downdrift of major coastal promontories. The shoals appear to have migrated shoreward under the influence of <span class="hlt">ice</span> up to 400 m in the last 25 years. The <span class="hlt">sea</span> floor seaward of these shoals within the stamukhi zone shows high <span class="hlt">ice</span>-gouge density, large incision depths, and a high degree of disruption of internal sedimentary structures. The concentration of large <span class="hlt">ice</span> ridges and our <span class="hlt">sea</span> floor data in the stamukhi zone indicate that much of the available marine energy is expended here, while the inner shelf and coast, where the relatively undeformed fast <span class="hlt">ice</span> grows, are sheltered. There is evidence that anomalies in the overall arctic shelf profile are related to <span class="hlt">sea-ice</span> zonation, <span class="hlt">ice</span> dynamics, and bottom</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ISPAr42.3..485H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ISPAr42.3..485H"><span>Thin <span class="hlt">Ice</span> Area Extraction in the Seasonal <span class="hlt">Sea</span> <span class="hlt">Ice</span> Zones of the Northern Hemisphere Using Modis Data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hayashi, K.; Naoki, K.; Cho, K.</p> <p>2018-04-01</p> <p><span class="hlt">Sea</span> <span class="hlt">ice</span> has an important role of reflecting the solar radiation back into space. However, once the <span class="hlt">sea</span> <span class="hlt">ice</span> area melts, the area starts to absorb the solar radiation which accelerates the global warming. This means that the trend of global warming is likely to be enhanced in <span class="hlt">sea</span> <span class="hlt">ice</span> areas. In this study, the authors have developed a method to extract thin <span class="hlt">ice</span> area using reflectance data of MODIS onboard Terra and Aqua satellites of NASA. The reflectance of thin <span class="hlt">sea</span> <span class="hlt">ice</span> in the visible region is rather low. Moreover, since the surface of thin <span class="hlt">sea</span> <span class="hlt">ice</span> is likely to be wet, the reflectance of thin <span class="hlt">sea</span> <span class="hlt">ice</span> in the near infrared region is much lower than that of visible region. Considering these characteristics, the authors have developed a method to extract thin <span class="hlt">sea</span> <span class="hlt">ice</span> areas by using the reflectance data of MODIS (NASA MYD09 product, 2017) derived from MODIS L1B. By using the scatter plots of the reflectance of Band 1 (620 nm-670 nm) and Band 2 (841 nm-876 nm)) of MODIS, equations for extracting thin <span class="hlt">ice</span> area were derived. By using those equations, most of the thin <span class="hlt">ice</span> areas which could be recognized from MODIS images were well extracted in the seasonal <span class="hlt">sea</span> <span class="hlt">ice</span> zones in the Northern Hemisphere, namely the <span class="hlt">Sea</span> of Okhotsk, the Bering <span class="hlt">Sea</span> and the Gulf of Saint Lawrence. For some limited areas, Landsat-8 OLI images were also used for validation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C54A..08S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C54A..08S"><span>Tropical pacing of Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> increase</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Schneider, D. P.</p> <p>2015-12-01</p> <p>One reason why coupled climate model simulations generally do not reproduce the observed increase in Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> extent may be that their internally generated climate variability does not sync with the observed phases of phenomena like the Pacific Decadal Oscillation (PDO) and ENSO. For example, it is unlikely for a free-running coupled model simulation to capture the shift of the PDO from its positive to negative phase during 1998, and the subsequent ~15 year duration of the negative PDO phase. In previously presented work based on atmospheric models forced by observed tropical SSTs and stratospheric ozone, we demonstrated that tropical variability is key to explaining the wind trends over the Southern Ocean during the past ~35 years, particularly in the Ross, Amundsen and Bellingshausen <span class="hlt">Seas</span>, the regions of the largest trends in <span class="hlt">sea</span> <span class="hlt">ice</span> extent and <span class="hlt">ice</span> season duration. Here, we extend this idea to coupled model simulations with the Community Earth System Model (CESM) in which the evolution of SST anomalies in the central and eastern tropical Pacific is constrained to match the observations. This ensemble of 10 "tropical pacemaker" simulations shows a more realistic evolution of Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> anomalies than does its unconstrained counterpart, the CESM Large Ensemble (both sets of runs include stratospheric ozone depletion and other time-dependent radiative forcings). In particular, the pacemaker runs show that increased <span class="hlt">sea</span> <span class="hlt">ice</span> in the eastern Ross <span class="hlt">Sea</span> is associated with a deeper Amundsen <span class="hlt">Sea</span> Low (ASL) and stronger westerlies over the south Pacific. These circulation patterns in turn are linked with the negative phase of the PDO, characterized by negative SST anomalies in the central and eastern Pacific. The timing of tropical decadal variability with respect to ozone depletion further suggests a strong role for tropical variability in the recent acceleration of the Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> trend, as ozone depletion stabilized by late 1990s, prior to the most</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C32B..02S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C32B..02S"><span>Structural Uncertainty in Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> simulations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Schneider, D. P.</p> <p>2016-12-01</p> <p>The inability of the vast majority of historical climate model simulations to reproduce the observed increase in Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> has motivated many studies about the quality of the observational record, the role of natural variability versus forced changes, and the possibility of missing or inadequate forcings in the models (such as freshwater discharge from thinning <span class="hlt">ice</span> shelves or an inadequate magnitude of stratospheric ozone depletion). In this presentation I will highlight another source of uncertainty that has received comparatively little attention: Structural uncertainty, that is, the systematic uncertainty in simulated <span class="hlt">sea</span> <span class="hlt">ice</span> trends that arises from model physics and mean-state biases. Using two large ensembles of experiments from the Community Earth System Model (CESM), I will show that the model is predisposed towards producing negative Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> trends during 1979-present, and that this outcome is not simply because the model's decadal variability is out-of-synch with that in nature. In the "Tropical Pacific Pacemaker" ensemble, in which observed tropical Pacific SST anomalies are prescribed, the model produces very realistic atmospheric circulation trends over the Southern Ocean, yet the <span class="hlt">sea</span> <span class="hlt">ice</span> trend is negative in every ensemble member. However, if the ensemble-mean trend (commonly interpreted as the forced response) is removed, some ensemble members show a <span class="hlt">sea</span> <span class="hlt">ice</span> increase that is very similar to the observed. While this results does confirm the important role of natural variability, it also suggests a strong bias in the forced response. I will discuss the reasons for this systematic bias and explore possible remedies. This an important problem to solve because projections of 21st -Century changes in the Antarctic climate system (including <span class="hlt">ice</span> sheet surface mass balance changes and related changes in the <span class="hlt">sea</span> level budget) have a strong dependence on the mean state of and changes in the Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> cover. This problem is not unique to</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5016760','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5016760"><span>Influence of <span class="hlt">ice</span> thickness and surface properties on light transmission through Arctic <span class="hlt">sea</span> <span class="hlt">ice</span></span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Arndt, Stefanie; Nicolaus, Marcel; Perovich, Donald K.; Jakuba, Michael V.; Suman, Stefano; Elliott, Stephen; Whitcomb, Louis L.; McFarland, Christopher J.; Gerdes, Rüdiger; Boetius, Antje; German, Christopher R.</p> <p>2015-01-01</p> <p>Abstract The observed changes in physical properties of <span class="hlt">sea</span> <span class="hlt">ice</span> such as decreased thickness and increased melt pond cover severely impact the energy budget of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span>. Increased light transmission leads to increased deposition of solar energy in the upper ocean and thus plays a crucial role for amount and timing of sea‐ice‐melt and under‐<span class="hlt">ice</span> primary production. Recent developments in underwater technology provide new opportunities to study light transmission below the largely inaccessible underside of <span class="hlt">sea</span> <span class="hlt">ice</span>. We measured spectral under‐<span class="hlt">ice</span> radiance and irradiance using the new Nereid Under‐<span class="hlt">Ice</span> (NUI) underwater robotic vehicle, during a cruise of the R/V Polarstern to 83°N 6°W in the Arctic Ocean in July 2014. NUI is a next generation hybrid remotely operated vehicle (H‐ROV) designed for both remotely piloted and autonomous surveys underneath land‐fast and moving <span class="hlt">sea</span> <span class="hlt">ice</span>. Here we present results from one of the first comprehensive scientific dives of NUI employing its interdisciplinary sensor suite. We combine under‐<span class="hlt">ice</span> optical measurements with three dimensional under‐<span class="hlt">ice</span> topography (multibeam sonar) and aerial images of the surface conditions. We investigate the influence of spatially varying ice‐thickness and surface properties on the spatial variability of light transmittance during summer. Our results show that surface properties such as melt ponds dominate the spatial distribution of the under‐<span class="hlt">ice</span> light field on small scales (<1000 m2), while <span class="hlt">sea</span> ice‐thickness is the most important predictor for light transmission on larger scales. In addition, we propose the use of an algorithm to obtain histograms of light transmission from distributions of <span class="hlt">sea</span> <span class="hlt">ice</span> thickness and surface albedo. PMID:27660738</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFM.C43E0586E','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFM.C43E0586E"><span>Carbon Dioxide Transfer Through <span class="hlt">Sea</span> <span class="hlt">Ice</span>: Modelling Flux in Brine Channels</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Edwards, L.; Mitchelson-Jacob, G.; Hardman-Mountford, N.</p> <p>2010-12-01</p> <p>For many years <span class="hlt">sea</span> <span class="hlt">ice</span> was thought to act as a barrier to the flux of CO2 between the ocean and atmosphere. However, laboratory-based and in-situ observations suggest that while <span class="hlt">sea</span> <span class="hlt">ice</span> may in some circumstances reduce or prevent transfer (e.g. in regions of thick, superimposed multi-year <span class="hlt">ice</span>), it may also be highly permeable (e.g. thin, first year <span class="hlt">ice</span>) with some studies observing significant fluxes of CO2. <span class="hlt">Sea</span> <span class="hlt">ice</span> covered regions have been observed to act both as a sink and a source of atmospheric CO2 with the permeability of <span class="hlt">sea</span> <span class="hlt">ice</span> and direction of flux related to <span class="hlt">sea</span> <span class="hlt">ice</span> temperature and the presence of brine channels in the <span class="hlt">ice</span>, as well as seasonal processes such as whether the <span class="hlt">ice</span> is freezing or thawing. Brine channels concentrate dissolved inorganic carbon (DIC) as well as salinity and as these dense waters descend through both the <span class="hlt">sea</span> <span class="hlt">ice</span> and the surface ocean waters, they create a sink for CO2. Calcium carbonate (ikaite) precipitation in the <span class="hlt">sea</span> <span class="hlt">ice</span> is thought to enhance this process. Micro-organisms present within the <span class="hlt">sea</span> <span class="hlt">ice</span> will also contribute to the CO2 flux dynamics. Recent evidence of decreasing <span class="hlt">sea</span> <span class="hlt">ice</span> extent and the associated change from a multi-year <span class="hlt">ice</span> to first-year <span class="hlt">ice</span> dominated system suggest the potential for increased CO2 flux through regions of thinner, more porous <span class="hlt">sea</span> <span class="hlt">ice</span>. A full understanding of the processes and feedbacks controlling the flux in these regions is needed to determine their possible contribution to global CO2 levels in a future warming climate scenario. Despite the significance of these regions, the air-<span class="hlt">sea</span> CO2 flux in <span class="hlt">sea</span> <span class="hlt">ice</span> covered regions is not currently included in global climate models. Incorporating this carbon flux system into Earth System models requires the development of a well-parameterised <span class="hlt">sea</span> <span class="hlt">ice</span>-air flux model. In our work we use the Los Alamos <span class="hlt">sea</span> <span class="hlt">ice</span> model, CICE, with a modification to incorporate the movement of CO2 through brine channels including the addition of DIC processes and <span class="hlt">ice</span> algae production to</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/10583952','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/10583952"><span>Global Warming and Northern Hemisphere <span class="hlt">Sea</span> <span class="hlt">Ice</span> Extent.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Vinnikov; Robock; Stouffer; Walsh; Parkinson; Cavalieri; Mitchell; Garrett; Zakharov</p> <p>1999-12-03</p> <p>Surface and satellite-based observations show a decrease in Northern Hemisphere <span class="hlt">sea</span> <span class="hlt">ice</span> extent during the past 46 years. A comparison of these trends to control and transient integrations (forced by observed greenhouse gases and tropospheric sulfate aerosols) from the Geophysical Fluid Dynamics Laboratory and Hadley Centre climate models reveals that the observed decrease in Northern Hemisphere <span class="hlt">sea</span> <span class="hlt">ice</span> extent agrees with the transient simulations, and both trends are much larger than would be expected from natural climate variations. From long-term control runs of climate models, it was found that the probability of the observed trends resulting from natural climate variability, assuming that the models' natural variability is similar to that found in nature, is less than 2 percent for the 1978-98 <span class="hlt">sea</span> <span class="hlt">ice</span> trends and less than 0.1 percent for the 1953-98 <span class="hlt">sea</span> <span class="hlt">ice</span> trends. Both models used here project continued decreases in <span class="hlt">sea</span> <span class="hlt">ice</span> thickness and extent throughout the next century.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFMIN11C1538S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFMIN11C1538S"><span>The Timing of Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> Advance and Retreat as an Indicator of <span class="hlt">Ice</span>-Dependent Marine Mammal Habitat</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Stern, H. L.; Laidre, K. L.</p> <p>2013-12-01</p> <p>The Arctic is widely recognized as the front line of climate change. Arctic air temperature is rising at twice the global average rate, and the <span class="hlt">sea-ice</span> cover is shrinking and thinning, with total disappearance of summer <span class="hlt">sea</span> <span class="hlt">ice</span> projected to occur in a matter of decades. Arctic marine mammals such as polar bears, seals, walruses, belugas, narwhals, and bowhead whales depend on the <span class="hlt">sea-ice</span> cover as an integral part of their existence. While the downward trend in <span class="hlt">sea-ice</span> extent in a given month is an often-used metric for quantifying physical changes in the <span class="hlt">ice</span> cover, it is not the most relevant measure for characterizing changes in the <span class="hlt">sea-ice</span> habitat of marine mammals. Species that depend on <span class="hlt">sea</span> <span class="hlt">ice</span> are behaviorally tied to the annual retreat of <span class="hlt">sea</span> <span class="hlt">ice</span> in the spring and advance in the fall. Changes in the timing of the spring retreat and the fall advance are more relevant to Arctic marine species than changes in the areal <span class="hlt">sea-ice</span> coverage in a particular month of the year. Many ecologically important regions of the Arctic are essentially <span class="hlt">ice</span>-covered in winter and <span class="hlt">ice</span>-free in summer, and will probably remain so for a long time into the future. But the dates of <span class="hlt">sea-ice</span> retreat in spring and advance in fall are key indicators of climate change for <span class="hlt">ice</span>-dependent marine mammals. We use daily <span class="hlt">sea-ice</span> concentration data derived from satellite passive microwave sensors to calculate the dates of <span class="hlt">sea-ice</span> retreat in spring and advance in fall in 12 regions of the Arctic for each year from 1979 through 2013. The regions include the peripheral <span class="hlt">seas</span> around the Arctic Ocean (Beaufort, Chukchi, East Siberian, Laptev, Kara, Barents), the Canadian Arctic Archipelago, and the marginal <span class="hlt">seas</span> (Okhotsk, Bering, East Greenland, Baffin Bay, Hudson Bay). We find that in 11 of the 12 regions (all except the Bering <span class="hlt">Sea</span>), <span class="hlt">sea</span> <span class="hlt">ice</span> is retreating earlier in spring and advancing later in fall. Rates of spring retreat range from -5 to -8 days/decade, and rates of fall advance range from +5 to +9</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4024236','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4024236"><span>Influence of stochastic <span class="hlt">sea</span> <span class="hlt">ice</span> parametrization on climate and the role of atmosphere–<span class="hlt">sea</span> ice–ocean interaction</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Juricke, Stephan; Jung, Thomas</p> <p>2014-01-01</p> <p>The influence of a stochastic <span class="hlt">sea</span> <span class="hlt">ice</span> strength parametrization on the mean climate is investigated in a coupled atmosphere–<span class="hlt">sea</span> ice–ocean model. The results are compared with an uncoupled simulation with a prescribed atmosphere. It is found that the stochastic <span class="hlt">sea</span> <span class="hlt">ice</span> parametrization causes an effective weakening of the <span class="hlt">sea</span> <span class="hlt">ice</span>. In the uncoupled model this leads to an Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> volume increase of about 10–20% after an accumulation period of approximately 20–30 years. In the coupled model, no such increase is found. Rather, the stochastic perturbations lead to a spatial redistribution of the Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> thickness field. A mechanism involving a slightly negative atmospheric feedback is proposed that can explain the different responses in the coupled and uncoupled system. Changes in integrated Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> quantities caused by the stochastic parametrization are generally small, as memory is lost during the melting season because of an almost complete loss of <span class="hlt">sea</span> <span class="hlt">ice</span>. However, stochastic <span class="hlt">sea</span> <span class="hlt">ice</span> perturbations affect regional <span class="hlt">sea</span> <span class="hlt">ice</span> characteristics in the Southern Hemisphere, both in the uncoupled and coupled model. Remote impacts of the stochastic <span class="hlt">sea</span> <span class="hlt">ice</span> parametrization on the mean climate of non-polar regions were found to be small. PMID:24842027</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20040171250','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20040171250"><span>ICESat Observations of Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span>: A First Look</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Kwok, Ron; Zwally, H. Jay; Yi, Dong-Hui</p> <p>2004-01-01</p> <p>Analysis of near-coincident ICESat and RADARSAT imagery shows that the retrieved elevations from the laser altimeter are sensitive to new openings (containing thin <span class="hlt">ice</span> or open water) in the <span class="hlt">sea</span> <span class="hlt">ice</span> cover as well as to surface relief of old and first-year <span class="hlt">ice</span>. The precision of the elevation estimates, measured over relatively flat <span class="hlt">sea</span> <span class="hlt">ice</span>, is approx. 2 cm Using the thickness of thin-<span class="hlt">ice</span> in recent openings to estimate <span class="hlt">sea</span> level references, we obtain the <span class="hlt">sea-ice</span> free-board along the altimeter tracks. This step is necessitated by the large uncertainties in the time-varying <span class="hlt">sea</span> surface topography compared to that required for accurate determination of free-board. Unknown snow depth introduces the largest uncertainty in the conversion of free-board to <span class="hlt">ice</span> thickness. Surface roughness is also derived, for the first time, from the variability of successive elevation estimates along the altimeter track Overall, these ICESat measurements provide an unprecedented view of the Arctic Ocean <span class="hlt">ice</span> cover at length scales at and above the spatial dimension of the altimeter footprint.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1916800R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1916800R"><span>Impact of wave mixing on the <span class="hlt">sea</span> <span class="hlt">ice</span> cover</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Rynders, Stefanie; Aksenov, Yevgeny; Madec, Gurvan; Nurser, George; Feltham, Daniel</p> <p>2017-04-01</p> <p>As information on surface waves in <span class="hlt">ice</span>-covered regions becomes available in <span class="hlt">ice</span>-ocean models, there is an opportunity to model wave-related processes more accurate. Breaking waves cause mixing of the upper water column and present mixing schemes in ocean models take this into account through surface roughness. A commonly used approach is to calculate surface roughness from significant wave height, parameterised from wind speed. We present results from simulations using modelled significant wave height instead, which accounts for the presence of <span class="hlt">sea</span> <span class="hlt">ice</span> and the effect of swell. The simulations use the NEMO ocean model coupled to the CICE <span class="hlt">sea</span> <span class="hlt">ice</span> model, with wave information from the ECWAM model of the European Centre for Medium-Range Weather Forecasts (ECMWF). The new waves-in-<span class="hlt">ice</span> module allows waves to propagate in <span class="hlt">sea</span> <span class="hlt">ice</span> and attenuates waves according to multiple scattering and non-elastic losses. It is found that in the simulations with wave mixing the mixed layer depth (MLD) under <span class="hlt">ice</span> cover is reduced, since the parameterisation from wind speed overestimates wave height in the <span class="hlt">ice</span>-covered regions. The MLD change, in turn, affects <span class="hlt">sea</span> <span class="hlt">ice</span> concentration and <span class="hlt">ice</span> thickness. In the Arctic, reduced MLD in winter translates into increased <span class="hlt">ice</span> thicknesses overall, with higher increases in the Western Arctic and decreases along the Siberian coast. In summer, shallowing of the mixed layer results in more heat accumulating in the surface ocean, increasing <span class="hlt">ice</span> melting. In the Southern Ocean the meridional gradient in <span class="hlt">ice</span> thickness and concentration is increased. We argue that coupling waves with <span class="hlt">sea</span> <span class="hlt">ice</span> - ocean models can reduce negative biases in <span class="hlt">sea</span> <span class="hlt">ice</span> cover, affecting the distribution of nutrients and, thus, biological productivity and ecosystems. This coupling will become more important in the future, when wave heights in a large part of the Arctic are expected to increase due to <span class="hlt">sea</span> <span class="hlt">ice</span> retreat and a larger wave fetch. Therefore, wave mixing constitutes a possible</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/AD1013753','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/AD1013753"><span>Forecasting Future <span class="hlt">Sea</span> <span class="hlt">Ice</span> Conditions: A Lagrangian Approach</span></a></p> <p><a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>2015-09-30</p> <p>1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Forecasting Future <span class="hlt">Sea</span> <span class="hlt">Ice</span> Conditions: A Lagrangian ...GCMs participating in IPCC AR5 agree with observed source region patterns from the satellite- derived dataset. 4- Compare Lagrangian <span class="hlt">ice</span>... Lagrangian <span class="hlt">sea-ice</span> back trajectories to estimate thermodynamic and dynamic (advection) <span class="hlt">ice</span> loss. APPROACH We use a Lagrangian trajectory model to</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018TCry...12.1157M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018TCry...12.1157M"><span>Canadian snow and <span class="hlt">sea</span> <span class="hlt">ice</span>: historical trends and projections</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mudryk, Lawrence R.; Derksen, Chris; Howell, Stephen; Laliberté, Fred; Thackeray, Chad; Sospedra-Alfonso, Reinel; Vionnet, Vincent; Kushner, Paul J.; Brown, Ross</p> <p>2018-04-01</p> <p>The Canadian <span class="hlt">Sea</span> <span class="hlt">Ice</span> and Snow Evolution (CanSISE) Network is a climate research network focused on developing and applying state of the art observational data to advance dynamical prediction, projections, and understanding of seasonal snow cover and <span class="hlt">sea</span> <span class="hlt">ice</span> in Canada and the circumpolar Arctic. Here, we present an assessment from the CanSISE Network on trends in the historical record of snow cover (fraction, water equivalent) and <span class="hlt">sea</span> <span class="hlt">ice</span> (area, concentration, type, and thickness) across Canada. We also assess projected changes in snow cover and <span class="hlt">sea</span> <span class="hlt">ice</span> likely to occur by mid-century, as simulated by the Coupled Model Intercomparison Project Phase 5 (CMIP5) suite of Earth system models. The historical datasets show that the fraction of Canadian land and marine areas covered by snow and <span class="hlt">ice</span> is decreasing over time, with seasonal and regional variability in the trends consistent with regional differences in surface temperature trends. In particular, summer <span class="hlt">sea</span> <span class="hlt">ice</span> cover has decreased significantly across nearly all Canadian marine regions, and the rate of multi-year <span class="hlt">ice</span> loss in the Beaufort <span class="hlt">Sea</span> and Canadian Arctic Archipelago has nearly doubled over the last 8 years. The multi-model consensus over the 2020-2050 period shows reductions in fall and spring snow cover fraction and <span class="hlt">sea</span> <span class="hlt">ice</span> concentration of 5-10 % per decade (or 15-30 % in total), with similar reductions in winter <span class="hlt">sea</span> <span class="hlt">ice</span> concentration in both Hudson Bay and eastern Canadian waters. Peak pre-melt terrestrial snow water equivalent reductions of up to 10 % per decade (30 % in total) are projected across southern Canada.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018JGRC..123..672H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018JGRC..123..672H"><span>Scaling Properties of Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> Deformation in a High-Resolution Viscous-Plastic <span class="hlt">Sea</span> <span class="hlt">Ice</span> Model and in Satellite Observations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hutter, Nils; Losch, Martin; Menemenlis, Dimitris</p> <p>2018-01-01</p> <p><span class="hlt">Sea</span> <span class="hlt">ice</span> models with the traditional viscous-plastic (VP) rheology and very small horizontal grid spacing can resolve leads and deformation rates localized along Linear Kinematic Features (LKF). In a 1 km pan-Arctic <span class="hlt">sea</span> <span class="hlt">ice</span>-ocean simulation, the small-scale <span class="hlt">sea</span> <span class="hlt">ice</span> deformations are evaluated with a scaling analysis in relation to satellite observations of the Envisat Geophysical Processor System (EGPS) in the Central Arctic. A new coupled scaling analysis for data on Eulerian grids is used to determine the spatial and temporal scaling and the coupling between temporal and spatial scales. The spatial scaling of the modeled <span class="hlt">sea</span> <span class="hlt">ice</span> deformation implies multifractality. It is also coupled to temporal scales and varies realistically by region and season. The agreement of the spatial scaling with satellite observations challenges previous results with VP models at coarser resolution, which did not reproduce the observed scaling. The temporal scaling analysis shows that the VP model, as configured in this 1 km simulation, does not fully resolve the intermittency of <span class="hlt">sea</span> <span class="hlt">ice</span> deformation that is observed in satellite data.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li class="active"><span>14</span></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_14 --> <div id="page_15" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li class="active"><span>15</span></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="281"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29576996','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29576996"><span>Scaling Properties of Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> Deformation in a High-Resolution Viscous-Plastic <span class="hlt">Sea</span> <span class="hlt">Ice</span> Model and in Satellite Observations.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Hutter, Nils; Losch, Martin; Menemenlis, Dimitris</p> <p>2018-01-01</p> <p><span class="hlt">Sea</span> <span class="hlt">ice</span> models with the traditional viscous-plastic (VP) rheology and very small horizontal grid spacing can resolve leads and deformation rates localized along Linear Kinematic Features (LKF). In a 1 km pan-Arctic <span class="hlt">sea</span> <span class="hlt">ice</span>-ocean simulation, the small-scale <span class="hlt">sea</span> <span class="hlt">ice</span> deformations are evaluated with a scaling analysis in relation to satellite observations of the Envisat Geophysical Processor System (EGPS) in the Central Arctic. A new coupled scaling analysis for data on Eulerian grids is used to determine the spatial and temporal scaling and the coupling between temporal and spatial scales. The spatial scaling of the modeled <span class="hlt">sea</span> <span class="hlt">ice</span> deformation implies multifractality. It is also coupled to temporal scales and varies realistically by region and season. The agreement of the spatial scaling with satellite observations challenges previous results with VP models at coarser resolution, which did not reproduce the observed scaling. The temporal scaling analysis shows that the VP model, as configured in this 1 km simulation, does not fully resolve the intermittency of <span class="hlt">sea</span> <span class="hlt">ice</span> deformation that is observed in satellite data.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19840059709&hterms=Thorndike&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DThorndike','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19840059709&hterms=Thorndike&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DThorndike"><span>Measuring the <span class="hlt">sea</span> <span class="hlt">ice</span> floe size distribution</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Rothrock, D. A.; Thorndike, A. S.</p> <p>1984-01-01</p> <p>The <span class="hlt">sea</span> <span class="hlt">ice</span> covering the Arctic Ocean is broken into distinct pieces,called floes. In the summer, these floes, which have diameters ranging up to 100 km, are separated from each other by a region of open water. In the winter, floes still exist, but they are less easily identified. An understanding of the geometry of the <span class="hlt">ice</span> pack is of interest for a number of practical applications associated with transportation in <span class="hlt">ice</span>-covered <span class="hlt">seas</span> and with the design of offshore structures intended to survive in the presence of <span class="hlt">ice</span>. The present investigation has the objective to clarify ideas about floe sizes and to propose techniques for measuring them. Measurements are presented with the primary aim to illustrate points of technique or approach. A preliminary discussion of the floe size distribution of <span class="hlt">sea</span> <span class="hlt">ice</span> is devoted to questions of definition and of measurement.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C53C..02R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C53C..02R"><span><span class="hlt">Sea</span> <span class="hlt">ice</span> thickness derived from radar altimetry: achievements and future plans</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ricker, R.; Hendricks, S.; Paul, S.; Kaleschke, L.; Tian-Kunze, X.</p> <p>2017-12-01</p> <p>The retrieval of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> thickness is one of the major objectives of the European CryoSat-2 radar altimeter mission and the 7-year long period of operation has produced an unprecedented record of monthly <span class="hlt">sea</span> <span class="hlt">ice</span> thickness information. We present CryoSat-2 results that show changes and variability of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> from the winter season 2010/2011 until fall 2017. CryoSat-2, however, was designed to observe thick perennial <span class="hlt">sea</span> <span class="hlt">ice</span>, while an accurate retrieval of thin seasonal <span class="hlt">sea</span> <span class="hlt">ice</span> is more challenging. We have therefore developed a method of completing and improving Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> thickness information within the ESA SMOS+ <span class="hlt">Sea</span> <span class="hlt">Ice</span> project by merging CryoSat-2 and SMOS <span class="hlt">sea</span> <span class="hlt">ice</span> thickness retrievals. Using these satellite missions together overcomes several issues of single-mission retrievals and provides a more accurate and comprehensive view on the state of Arctic <span class="hlt">sea-ice</span> thickness at higher temporal resolution. However, stand-alone CryoSat-2 observations can be used as reference data for the exploitation of older pulse-limited radar altimetry data sets over <span class="hlt">sea</span> <span class="hlt">ice</span>. In order to observe trends in <span class="hlt">sea</span> <span class="hlt">ice</span> thickness, it is required to minimize inter-mission biases between subsequent satellite missions. Within the ESA Climate Change Initiative (CCI) on <span class="hlt">Sea</span> <span class="hlt">Ice</span>, a climate data record of <span class="hlt">sea</span> <span class="hlt">ice</span> thickness derived from satellite radar altimetry has been developed for both hemispheres, based on the 15-year (2002-2017) monthly retrievals from Envisat and CryoSat-2 and calibrated in the 2010-2012 overlap period. The next step in promoting the utilization of <span class="hlt">sea</span> <span class="hlt">ice</span> thickness information from radar altimetry is to provide products by a service that meets the requirements for climate applications and operational systems. This task will be pursued within a Copernicus Climate Change Service project (C3S). This framework also aims to include additional sensors such as onboard Sentinel-3 and we will show first results of Sentinel-3 Arctic <span class="hlt">sea-ice</span> thickness. These</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018FrEaS...6...22J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018FrEaS...6...22J"><span>Organic matter controls of iron incorporation in growing <span class="hlt">sea</span> <span class="hlt">ice</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Janssens, Julie; Meiners, Klaus M.; Townsend, Ashley T.; Lannuzel, Delphine</p> <p>2018-03-01</p> <p>This study presents the first laboratory-controlled <span class="hlt">sea-ice</span> growth experiment conducted under trace metal clean conditions. The role played by organic matter, in the incorporation of iron (Fe) into <span class="hlt">sea</span> <span class="hlt">ice</span> was investigated by means of laboratory <span class="hlt">ice</span>-growth experiments using a titanium cold-finger apparatus. Experiments were also conducted to understand the role of extracellular polymeric substances (EPS) in the enrichment of ammonium in <span class="hlt">sea</span> <span class="hlt">ice</span>. <span class="hlt">Sea</span> <span class="hlt">ice</span> was grown from several seawater solutions containing different quantities and qualities of particulate Fe (PFe), dissolved Fe (DFe) and organic matter. <span class="hlt">Sea</span> <span class="hlt">ice</span> and seawater were analyzed for particulate organic carbon and nitrogen, macro-nutrients, extracellular EPS, PFe and DFe, and particulate aluminium. The experiments showed that biogenic PFe is preferentially incorporated into <span class="hlt">sea</span> <span class="hlt">ice</span> compared to lithogenic PFe. Furthermore, <span class="hlt">sea</span> <span class="hlt">ice</span> grown from ultra-violet (UV) and non-UV treated seawaters exhibits contrasting incorporation rates of organic matter and Fe. Whereas the effects of UV-treatments were not always significant, we do find indications that the type or organic matter controls the enrichment of Fe in forming <span class="hlt">sea</span> <span class="hlt">ice</span>.. Specifically, we come to the conclusion that the incorporation of DFe is favored by the presence of organic ligands in the source solution.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20060044030&hterms=SLP&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3DSLP','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20060044030&hterms=SLP&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3DSLP"><span>Ross <span class="hlt">sea</span> <span class="hlt">ice</span> motion, area flux, and deformation</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>kwok, Ron</p> <p>2005-01-01</p> <p>The <span class="hlt">sea</span> <span class="hlt">ice</span> motion, area export, and deformation of the Ross <span class="hlt">Sea</span> <span class="hlt">ice</span> cover are examined with satellite passive microwave and RADARSAT observations. The record of high-resolution synthetic aperture radar (SAR) data, from 1998 and 2000, allows the estimation of the variability of <span class="hlt">ice</span> deformation at the small scale (10 km) and to assess the quality of the longer record of passive microwave <span class="hlt">ice</span> motion. Daily and subdaily deformation fields and RADARSAT imagery highlight the variability of motion and deformation in the Ross <span class="hlt">Sea</span>. With the passive microwave <span class="hlt">ice</span> motion, the area export at a flux gate positioned between Cape Adare and Land Bay is estimated. Between 1992 and 2003, a positive trend can be seen in the winter (March-November) <span class="hlt">ice</span> area flux that has a mean of 990 x 103 km2 and ranges from a low of 600 x 103 km2 in 1992 to a peak of 1600 x 103 km2 in 2001. In the mean, the southern Ross <span class="hlt">Sea</span> produces almost twice its own area of <span class="hlt">sea</span> <span class="hlt">ice</span> during the winter. Cross-gate <span class="hlt">sea</span> level pressure (SLP) gradients explain 60% of the variance in the <span class="hlt">ice</span> area flux. A positive trend in this gradient, from reanalysis products, suggests a 'spinup' of the Ross <span class="hlt">Sea</span> Gyre over the past 12 yr. In both the NCEP-NCAR and ERA-40 surface pressure fields, longer-term trends in this gradient and mean SLP between 1979 and 2002 are explored along with positive anomalies in the monthly cross-gate SLP gradient associated with the positive phase of the Southern Hemisphere annular mode and the extrapolar Southern Oscillation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20170010244&hterms=sea&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dsea','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20170010244&hterms=sea&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dsea"><span>Improvements in <span class="hlt">Ice</span>-Sheet <span class="hlt">Sea</span>-Level Projections</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Shepherd, Andrew; Nowicki, Sophie</p> <p>2017-01-01</p> <p><span class="hlt">Ice</span> losses from Antarctica and Greenland are the largest uncertainty in <span class="hlt">sea</span>-level projections. Nevertheless, improvements in <span class="hlt">ice</span>-sheet models over recent decades have led to closer agreement with satellite observations, keeping track with their increasing contribution to global <span class="hlt">sea</span>-level rise.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.8163M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.8163M"><span>How <span class="hlt">sea</span> <span class="hlt">ice</span> could be the cold beating heart of European weather</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Margrethe Ringgaard, Ida; Yang, Shuting; Hesselbjerg Christensen, Jens; Kaas, Eigil</p> <p>2017-04-01</p> <p>The possibility that the ongoing rapid demise of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> may instigate abrupt changes is, however, not tackled by current research in general. <span class="hlt">Ice</span> cores from the Greenland <span class="hlt">Ice</span> Sheet (GIS) show clear evidence of past abrupt warm events with up to 15 degrees warming in less than a decade, most likely triggered by rapid disappearance of Nordic <span class="hlt">Seas</span> <span class="hlt">sea</span> <span class="hlt">ice</span>. At present, both Arctic <span class="hlt">Sea</span> <span class="hlt">ice</span> and the GIS are in strong transformation: Arctic <span class="hlt">sea-ice</span> cover has been retreating during most of the satellite era and in recent years, Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> experienced a dramatic reduction and the summer extent was in 2012 and 2016 only half of the 1979-2000 average. With such dramatic change in the current <span class="hlt">sea</span> <span class="hlt">ice</span> coverage as a point of departure, several studies have linked reduction in wintertime <span class="hlt">sea</span> <span class="hlt">ice</span> in the Barents-Kara <span class="hlt">seas</span> to cold weather anomalies over Europe and through large scale tele-connections to regional warming elsewhere. Here we aim to investigate if, and how, Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> impacts European weather, i.e. if the Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> works as the 'cold heart' of European weather. To understand the effects of the <span class="hlt">sea</span> <span class="hlt">ice</span> reduction on the full climate system, a fully-coupled global climate model, EC-Earth, is used. A new energy-conserving method for assimilating <span class="hlt">sea</span> <span class="hlt">ice</span> using the sensible heat flux is implemented in the coupled climate model and compared to the traditional, non-conserving, method of assimilating <span class="hlt">sea</span> <span class="hlt">ice</span>. Using this new method, experiments are performed with reduced <span class="hlt">sea</span> <span class="hlt">ice</span> cover in the Barents-Kara <span class="hlt">seas</span> under both warm and cold conditions in Europe. These experiments are used to evaluate how the Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> modulates European winter weather under present climate conditions with a view towards favouring both relatively cold and warm conditions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.C31D0341K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.C31D0341K"><span><span class="hlt">Sea</span> <span class="hlt">Ice</span> Characteristics and the Open-Linked Data World</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Khalsa, S. J. S.; McGuinness, D. L.; Duerr, R.; Pulsifer, P. L.; Fox, P. A.; Thompson, C.; Yan, R.</p> <p>2014-12-01</p> <p>The audience for <span class="hlt">sea</span> <span class="hlt">ice</span> data sets has broadened dramatically over the past several decades. Initially the National Snow and <span class="hlt">Ice</span> Data Center (NSIDC) <span class="hlt">sea</span> <span class="hlt">ice</span> products were used primarily by <span class="hlt">sea</span> <span class="hlt">ice</span> specialists. However, now they are in demand by researchers in many different domains and some are used by the public. This growth in the number and type of users has presented challenges to content providers aimed particularly at supporting interdisciplinary and multidisciplinary data use. In our experience, it is generally insufficient to simply make the data available as originally formatted. New audiences typically need data in different forms; forms that meet their needs, that work with their specific tools. Moreover, simple data reformatting is rarely enough. The data needs to be aggregated, transformed or otherwise converted into forms that better serve the needs of the new audience. The Semantic <span class="hlt">Sea</span> <span class="hlt">Ice</span> Interoperability Initiative (SSIII) is an NSF-funded research project aimed at making <span class="hlt">sea</span> <span class="hlt">ice</span> data more useful to more people using semantic technologies. The team includes domain and science data experts as well as knowledge representation and linked data experts. Beginning with a series of workshops involving members of the operations, <span class="hlt">sea</span> <span class="hlt">ice</span> research and modeling communities, as well as members of local communities in Alaska, a suite of ontologies describing the physical characteristics of <span class="hlt">sea</span> <span class="hlt">ice</span> have been developed and used to provide one of NSIDC's data sets, the operational Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> charts obtained from the Canadian <span class="hlt">Ice</span> Center, as open-linked data. These data extend nearly a decade into the past and can now be queried either directly through a publicly available SPARQL end point (for those who are familiar with open-linked data) or through a simple Open Geospatial Consortium (OGC) standards map-based query tool. Questions like "What were the characteristics (i.e., <span class="hlt">sea</span> <span class="hlt">ice</span> concentration, form and stage of development) of the <span class="hlt">sea</span> <span class="hlt">ice</span> in the region</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5892929','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5892929"><span>Microalgal photophysiology and macronutrient distribution in summer <span class="hlt">sea</span> <span class="hlt">ice</span> in the Amundsen and Ross <span class="hlt">Seas</span>, Antarctica</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Fransson, Agneta; Currie, Kim; Wulff, Angela; Chierici, Melissa</p> <p>2018-01-01</p> <p>Our study addresses how environmental variables, such as macronutrients concentrations, snow cover, carbonate chemistry and salinity affect the photophysiology and biomass of Antarctic <span class="hlt">sea-ice</span> algae. We have measured vertical profiles of inorganic macronutrients (phosphate, nitrite + nitrate and silicic acid) in summer <span class="hlt">sea</span> <span class="hlt">ice</span> and photophysiology of <span class="hlt">ice</span> algal assemblages in the poorly studied Amundsen and Ross <span class="hlt">Seas</span> sectors of the Southern Ocean. Brine-scaled bacterial abundance, chl a and macronutrient concentrations were often high in the <span class="hlt">ice</span> and positively correlated with each other. Analysis of photosystem II rapid light curves showed that microalgal cells in samples with high phosphate and nitrite + nitrate concentrations had reduced maximum relative electron transport rate and photosynthetic efficiency. We also observed strong couplings of PSII parameters to snow depth, <span class="hlt">ice</span> thickness and brine salinity, which highlights a wide range of photoacclimation in Antarctic pack-<span class="hlt">ice</span> algae. It is likely that the pack <span class="hlt">ice</span> was in a post-bloom situation during the late <span class="hlt">sea-ice</span> season, with low photosynthetic efficiency and a high degree of nutrient accumulation occurring in the <span class="hlt">ice</span>. In order to predict how key biogeochemical processes are affected by future changes in <span class="hlt">sea</span> <span class="hlt">ice</span> cover, such as in situ photosynthesis and nutrient cycling, we need to understand how physicochemical properties of <span class="hlt">sea</span> <span class="hlt">ice</span> affect the microbial community. Our results support existing hypothesis about <span class="hlt">sea-ice</span> algal photophysiology, and provide additional observations on high nutrient concentrations in <span class="hlt">sea</span> <span class="hlt">ice</span> that could influence the planktonic communities as the <span class="hlt">ice</span> is retreating. PMID:29634756</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C41D0761S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C41D0761S"><span>NWS Alaska <span class="hlt">Sea</span> <span class="hlt">Ice</span> Program: Operations and Decision Support Services</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Schreck, M. B.; Nelson, J. A., Jr.; Heim, R.</p> <p>2015-12-01</p> <p>The National Weather Service's Alaska <span class="hlt">Sea</span> <span class="hlt">Ice</span> Program is designed to service customers and partners operating and planning operations within Alaska waters. The Alaska <span class="hlt">Sea</span> <span class="hlt">Ice</span> Program offers daily <span class="hlt">sea</span> <span class="hlt">ice</span> and <span class="hlt">sea</span> surface temperature analysis products. The program also delivers a five day <span class="hlt">sea</span> <span class="hlt">ice</span> forecast 3 times each week, provides a 3 month <span class="hlt">sea</span> <span class="hlt">ice</span> outlook at the end of each month, and has staff available to respond to <span class="hlt">sea</span> <span class="hlt">ice</span> related information inquiries. These analysis and forecast products are utilized by many entities around the state of Alaska and nationally for safety of navigation and community strategic planning. The list of current customers stem from academia and research institutions, to local state and federal agencies, to resupply barges, to coastal subsistence hunters, to gold dredgers, to fisheries, to the general public. Due to a longer <span class="hlt">sea</span> <span class="hlt">ice</span> free season over recent years, activity in the waters around Alaska has increased. This has led to a rise in decision support services from the Alaska <span class="hlt">Sea</span> <span class="hlt">Ice</span> Program. The ASIP is in constant contact with the National <span class="hlt">Ice</span> Center as well as the United States Coast Guard (USCG) for safety of navigation. In the past, the ASIP provided briefings to the USCG when in support of search and rescue efforts. Currently, not only does that support remain, but our team is also briefing on <span class="hlt">sea</span> <span class="hlt">ice</span> outlooks into the next few months. As traffic in the Arctic increases, the ASIP will be called upon to provide more and more services on varying time scales to meet customer needs. This talk will address the many facets of the current Alaska <span class="hlt">Sea</span> <span class="hlt">Ice</span> Program as well as delve into what we see as the future of the ASIP.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMPP13A2057L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMPP13A2057L"><span><span class="hlt">Sea</span> <span class="hlt">ice</span> variations in the central Okhotsk <span class="hlt">Sea</span> during the last two glacial-interglacial cycles</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lo, L.; Cabedo-Sanz, P.; Lattaud, J.; Belt, S. T.; Schouten, S.; Huang, J. J.; Timmermann, A.; Zeeden, C.; Wei, K. Y.; Shen, C. C.; Hodell, D. A.; Elderfield, H.</p> <p>2016-12-01</p> <p><span class="hlt">Sea</span> <span class="hlt">ice</span> system as one of the critical and sensitive climate components in the Earth's climate system has experienced dramatically declination for the past few decades. Little knowledge, however, about the <span class="hlt">sea</span> <span class="hlt">ice</span> variations in the past orbital timescales has been obtained by paleoclimatic studies due to the lack of reliable <span class="hlt">sea</span> <span class="hlt">ice</span> proxy and age model constrain in the high productivity subpolar to polar regions. Here we present continuous 180,000 years subarctic northwestern Pacific <span class="hlt">sea</span> <span class="hlt">ice</span> and surface temperature (SST) records in the center Okhotsk <span class="hlt">Sea</span>, the southernmost of seasonal <span class="hlt">sea</span> <span class="hlt">ice</span> fomration region in the Northern Hemisphere by using by using novel organic and non-destructive geochemical proxies from Site MD01-2414 (53oN, 149oE, water depth 1123 m). High resolution X-ray fluoresces scanning biogenic/terrestrial (Ba/Ti) elemental ratio represent clear glacial-interglacial cycles. Organic geochemical proxies (IP25 and TEX86) derived <span class="hlt">sea</span> <span class="hlt">ice</span> and SST changes in the same time resolution reveal the seasonality in the center Okhotsk <span class="hlt">Sea</span>. <span class="hlt">Sea</span> <span class="hlt">ice</span> shows strong 23-kyr precession cycle control with modulation of 100-kyr eccentricity cycle during the peak interglacial periods (Marine Isotope Stage 5e and Holocene). On the other hand, SST represent global background climate change of 100-kyr cycle with very strong obliquity changes. According to the timeseries analyses, we argue that the <span class="hlt">sea</span> <span class="hlt">ice</span> minimum in the center of Okhotsk <span class="hlt">Sea</span> has mainly been controlled by the local autumn insolation. SST represent annual insolation increasing due to local summer insolation and the obliquity pacing. This study firstly demonstrated clear seasonality in the same site. Further study of the relationship between <span class="hlt">sea</span> <span class="hlt">ice</span> and seawater thermal hisotries on the orbital timescale in the subarctic Pacific is crucial in the understanding of past major climate event, e.g. Middle Pleistocene Transition and Middle Brunhes Event.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC53A0867D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC53A0867D"><span>Impacts of 1, 1.5, and 2 Degree Warming on Arctic Terrestrial Snow and <span class="hlt">Sea</span> <span class="hlt">Ice</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Derksen, C.; Mudryk, L.; Howell, S.; Flato, G. M.; Fyfe, J. C.; Gillett, N. P.; Sigmond, M.; Kushner, P. J.; Dawson, J.; Zwiers, F. W.; Lemmen, D.; Duguay, C. R.; Zhang, X.; Fletcher, C. G.; Dery, S. J.</p> <p>2017-12-01</p> <p>The 2015 Paris Agreement of the United Nations Framework Convention on Climate Change (UNFCCC) established the global temperature goal of "holding the increase in the global average temperature to below 2°C above pre-industrial levels and pursuing efforts to limit the temperature increase to 1.5°C above pre-industrial levels." In this study, we utilize multiple gridded snow and <span class="hlt">sea</span> <span class="hlt">ice</span> products (satellite retrievals; assimilation systems; physical models driven by reanalyses) and ensembles of climate model simulations to determine the impacts of observed warming, and project the relative impacts of the UNFCC future warming targets on Arctic seasonal terrestrial snow and <span class="hlt">sea</span> <span class="hlt">ice</span> cover. Observed changes during the satellite era represent the response to approximately 1°C of global warming. Consistent with other studies, analysis of the observational record (1970's to present) identifies changes including a shorter snow cover duration (due to later snow onset and earlier snow melt), significant reductions in spring snow cover and summer <span class="hlt">sea</span> <span class="hlt">ice</span> extent, and the loss of a large proportion of multi-year <span class="hlt">sea</span> <span class="hlt">ice</span>. The spatial patterns of observed snow and <span class="hlt">sea</span> <span class="hlt">ice</span> loss are coherent across <span class="hlt">adjacent</span> terrestrial/marine regions. There are strong pattern correlations between snow and temperature trends, with weaker association between <span class="hlt">sea</span> <span class="hlt">ice</span> and temperature due to the additional influence of dynamical effects such wind-driven redistribution of <span class="hlt">sea</span> <span class="hlt">ice</span>. Climate model simulations from the Coupled Model Inter-comparison Project Phase 5(CMIP-5) multi-model ensemble, large initial condition ensembles of the Community Earth System Model (CESM) and Canadian Earth System Model (CanESM2) , and warming stabilization simulations from CESM were used to identify changes in snow and <span class="hlt">ice</span> under further increases to 1.5°C and 2°C warming. The model projections indicate these levels of warming will be reached over the coming 2-4 decades. Warming to 1.5°C results in an increase in the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFM.C43D0577F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFM.C43D0577F"><span><span class="hlt">Sea</span> <span class="hlt">Ice</span> and Hydrographic Variability in the Northwest North Atlantic</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Fenty, I. G.; Heimbach, P.; Wunsch, C. I.</p> <p>2010-12-01</p> <p><span class="hlt">Sea</span> <span class="hlt">ice</span> anomalies in the Northwest North Atlantic's Labrador <span class="hlt">Sea</span> are of climatic interest because of known and hypothesized feedbacks with hydrographic anomalies, deep convection/mode water formation, and Northern Hemisphere atmospheric patterns. As greenhouse gas concentrations increase, hydrographic anomalies formed in the Arctic Ocean associated with warming will propagate into the Labrador <span class="hlt">Sea</span> via the Fram Strait/West Greenland Current and the Canadian Archipelago/Baffin Island Current. Therefore, understanding the dynamical response of <span class="hlt">sea</span> <span class="hlt">ice</span> in the basin to hydrographic anomalies is essential for the prediction and interpretation of future high-latitude climate change. Historically, efforts to quantify the link between the observed <span class="hlt">sea</span> <span class="hlt">ice</span> and hydrographic variability in the region has been limited due to in situ observation paucity and technical challenges associated with synthesizing ocean and <span class="hlt">sea</span> <span class="hlt">ice</span> observations with numerical models. To elaborate the relationship between <span class="hlt">sea</span> <span class="hlt">ice</span> and ocean variability, we create three one-year (1992-1993, 1996-1997, 2003-2004) three-dimensional time-varying reconstructions of the ocean and <span class="hlt">sea</span> <span class="hlt">ice</span> state in Labrador <span class="hlt">Sea</span> and Baffin Bay. The reconstructions are syntheses of a regional coupled 32 km ocean-<span class="hlt">sea</span> <span class="hlt">ice</span> model with a suite of contemporary in situ and satellite hydrographic and <span class="hlt">ice</span> data using the adjoint method. The model and data are made consistent, in a least-squares sense, by iteratively adjusting several model control variables (e.g., ocean initial and lateral boundary conditions and the atmospheric state) to minimize an uncertainty-weighted model-data misfit cost function. The reconstructions reveal that the <span class="hlt">ice</span> pack attains a state of quasi-equilibrium in mid-March (the annual <span class="hlt">sea</span> <span class="hlt">ice</span> maximum) in which the total <span class="hlt">ice</span>-covered area reaches a steady state -<span class="hlt">ice</span> production and dynamical divergence along the coasts balances dynamical convergence and melt along the pack’s seaward edge. <span class="hlt">Sea</span> <span class="hlt">ice</span> advected to the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013GeoRL..40.6362G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013GeoRL..40.6362G"><span>Gypsum crystals observed in experimental and natural <span class="hlt">sea</span> <span class="hlt">ice</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Geilfus, N.-X.; Galley, R. J.; Cooper, M.; Halden, N.; Hare, A.; Wang, F.; Søgaard, D. H.; Rysgaard, S.</p> <p>2013-12-01</p> <p>gypsum has been predicted to precipitate in <span class="hlt">sea</span> <span class="hlt">ice</span>, it has never been observed. Here we provide the first report on gypsum precipitation in both experimental and natural <span class="hlt">sea</span> <span class="hlt">ice</span>. Crystals were identified by X-ray diffraction analysis. Based on their apparent distinguishing characteristics, the gypsum crystals were identified as being authigenic. The FREeZing CHEMistry (FREZCHEM) model results support our observations of both gypsum and ikaite precipitation at typical in situ <span class="hlt">sea</span> <span class="hlt">ice</span> temperatures and confirms the "Gitterman pathway" where gypsum is predicted to precipitate. The occurrence of authigenic gypsum in <span class="hlt">sea</span> <span class="hlt">ice</span> during its formation represents a new observation of precipitate formation and potential marine deposition in polar <span class="hlt">seas</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C52A..03P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C52A..03P"><span>Characterizing Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> topography and atmospheric form drag using high-resolution <span class="hlt">Ice</span>Bridge data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Petty, A.; Tsamados, M.; Kurtz, N. T.; Farrell, S. L.; Newman, T.; Harbeck, J.; Feltham, D. L.; Richter-Menge, J.</p> <p>2015-12-01</p> <p>Here we present a detailed analysis of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> topography using high resolution, three-dimensional surface elevation data from the NASA Operation <span class="hlt">Ice</span>Bridge Airborne Topographic Mapper (ATM) laser altimeter. We derive novel <span class="hlt">ice</span> topography statistics from 2009-2014 across both first-year and multiyear <span class="hlt">ice</span> regimes - including the height, area coverage, orientation and spacing of distinct surface features. The <span class="hlt">sea</span> <span class="hlt">ice</span> topography exhibits strong spatial variability, including increased surface feature (e.g. pressure ridge) height and area coverage within the multi-year <span class="hlt">ice</span> regions. The <span class="hlt">ice</span> topography also shows a strong coastal dependency, with the feature height and area coverage increasing as a function of proximity to the nearest coastline, especially north of Greenland and the Canadian Archipelago. The <span class="hlt">ice</span> topography data have also been used to explicitly calculate atmospheric drag coefficients over Arctic <span class="hlt">sea</span> <span class="hlt">ice</span>; utilizing existing relationships regarding ridge geometry and their impact on form drag. The results are being used to calibrate the recent drag parameterization scheme included in the <span class="hlt">sea</span> <span class="hlt">ice</span> model CICE.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA601787','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA601787"><span>Mass Balance of Multiyear <span class="hlt">Sea</span> <span class="hlt">Ice</span> in the Southern Beaufort <span class="hlt">Sea</span></span></a></p> <p><a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>2013-09-30</p> <p>model of MY <span class="hlt">ice</span> circulation, which is shown in Figure 1. In this model , we consider the Beaufort <span class="hlt">Sea</span> to consist of four zones defined by mean drift...Arctic Regional Climate Model Simulation Project 3 International Arctic Buoy Program 4 <span class="hlt">Sea</span> <span class="hlt">ice</span> Experiment - Dynamic Nature of the Arctic 5Cold...2 Table 2: Datasets compiled to date Geophysical data type Source Time period acquired Buoy tracks IABP 12 hrly position data 1978-2012 <span class="hlt">Ice</span></p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ClDy..tmp..892C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ClDy..tmp..892C"><span>Mechanisms of interannual- to decadal-scale winter Labrador <span class="hlt">Sea</span> <span class="hlt">ice</span> variability</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Close, S.; Herbaut, C.; Houssais, M.-N.; Blaizot, A.-C.</p> <p>2017-12-01</p> <p>The variability of the winter <span class="hlt">sea</span> <span class="hlt">ice</span> cover of the Labrador <span class="hlt">Sea</span> region and its links to atmospheric and oceanic forcing are investigated using observational data, a coupled ocean-<span class="hlt">sea</span> <span class="hlt">ice</span> model and a fully-coupled model simulation drawn from the CMIP5 archive. A consistent series of mechanisms associated with high <span class="hlt">sea</span> <span class="hlt">ice</span> cover are found amongst the various data sets. The highest values of <span class="hlt">sea</span> <span class="hlt">ice</span> area occur when the northern Labrador <span class="hlt">Sea</span> is <span class="hlt">ice</span> covered. This region is found to be primarily thermodynamically forced, contrasting with the dominance of mechanical forcing along the eastern coast of Baffin Island and Labrador, and the growth of <span class="hlt">sea</span> <span class="hlt">ice</span> is associated with anomalously fresh local ocean surface conditions. Positive fresh water anomalies are found to propagate to the region from a source area off the southeast Greenland coast with a 1 month transit time. These anomalies are associated with <span class="hlt">sea</span> <span class="hlt">ice</span> melt, driven by the enhanced offshore transport of <span class="hlt">sea</span> <span class="hlt">ice</span> in the source region, and its subsequent westward transport in the Irminger Current system. By combining <span class="hlt">sea</span> <span class="hlt">ice</span> transport through the Denmark Strait in the preceding autumn with the Greenland Blocking Index and the Atlantic Multidecadal Oscillation Index, strong correlation with the Labrador <span class="hlt">Sea</span> <span class="hlt">ice</span> area of the following winter is obtained. This relationship represents a dependence on the availability of <span class="hlt">sea</span> <span class="hlt">ice</span> to be melted in the source region, the necessary atmospheric forcing to transport this offshore, and a further multidecadal-scale link with the large-scale <span class="hlt">sea</span> surface temperature conditions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C33B1185F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C33B1185F"><span>The role of feedbacks in Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> change</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Feltham, D. L.; Frew, R. C.; Holland, P.</p> <p>2017-12-01</p> <p>The changes in Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> over the last thirty years have a strong seasonal dependence, and the way these changes grow in spring and decay in autumn suggests that feedbacks are strongly involved. The changes may ultimately be caused by atmospheric warming, the winds, snowfall changes, etc., but we cannot understand these forcings without first untangling the feedbacks. A highly simplified coupled <span class="hlt">sea</span> <span class="hlt">ice</span> -mixed layer model has been developed to investigate the importance of feedbacks on the evolution of <span class="hlt">sea</span> <span class="hlt">ice</span> in two contrasting regions in the Southern Ocean; the Amundsen <span class="hlt">Sea</span> where <span class="hlt">sea</span> <span class="hlt">ice</span> extent has been decreasing, and the Weddell <span class="hlt">Sea</span> where it has been expanding. The change in mixed layer depth in response to changes in the atmosphere to ocean energy flux is implicit in a strong negative feedback on <span class="hlt">ice</span> cover changes in the Amundsen <span class="hlt">Sea</span>, with atmospheric cooling leading to a deeper mixed layer resulting in greater entrainment of warm Circumpolar Deep Water, causing increased basal melting of <span class="hlt">sea</span> <span class="hlt">ice</span>. This strong negative feedback produces counter intuitive responses to changes in forcings in the Amundsen <span class="hlt">Sea</span>. This feedback is absent in the Weddell due to the complete destratification and strong water column cooling that occurs each winter in simulations. The impact of other feedbacks, including the albedo feedback, changes in insulation due to <span class="hlt">ice</span> thickness and changes in the freezing temperature of the mixed layer, were found to be of secondary importance compared to changes in the mixed layer depth.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140010778','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140010778"><span>Changes in Arctic Melt Season and Implications for <span class="hlt">Sea</span> <span class="hlt">Ice</span> Loss</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Stroeve, J. C.; Markus, T.; Boisvert, L.; Miller, J.; Barrett, A.</p> <p>2014-01-01</p> <p>The Arctic-wide melt season has lengthened at a rate of 5 days dec-1 from 1979 to 2013, dominated by later autumn freeze-up within the Kara, Laptev, East Siberian, Chukchi and Beaufort <span class="hlt">seas</span> between 6 and 11 days dec(exp -1). While melt onset trends are generally smaller, the timing of melt onset has a large influence on the total amount of solar energy absorbed during summer. The additional heat stored in the upper ocean of approximately 752MJ m(exp -2) during the last decade, increases <span class="hlt">sea</span> surface temperatures by 0.5 to 1.5 C and largely explains the observed delays in autumn freeze-up within the Arctic Ocean's <span class="hlt">adjacent</span> <span class="hlt">seas</span>. Cumulative anomalies in total absorbed solar radiation from May through September for the most recent pentad locally exceed 300-400 MJ m(exp -2) in the Beaufort, Chukchi and East Siberian <span class="hlt">seas</span>. This extra solar energy is equivalent to melting 0.97 to 1.3 m of <span class="hlt">ice</span> during the summer.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19890018776','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19890018776"><span>Arctic <span class="hlt">Sea</span> <span class="hlt">ice</span> studies with passive microwave satellite observations</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Cavalieri, D. J.</p> <p>1988-01-01</p> <p>The objectives of this research are: (1) to improve <span class="hlt">sea</span> <span class="hlt">ice</span> concentration determinations from passive microwave space observations; (2) to study the role of Arctic polynyas in the production of <span class="hlt">sea</span> <span class="hlt">ice</span> and the associated salinization of Arctic shelf water; and (3) to study large scale <span class="hlt">sea</span> <span class="hlt">ice</span> variability in the polar oceans. The strategy is to analyze existing data sets and data acquired from both the DMSP SSM/I and recently completed aircraft underflights. Special attention will be given the high resolution 85.5 GHz SSM/I channels for application to thin <span class="hlt">ice</span> algorithms and processes studies. Analysis of aircraft and satellite data sets is expected to provide a basis for determining the potential of the SSM/I high frequency channels for improving <span class="hlt">sea</span> <span class="hlt">ice</span> algorithms and for investigating oceanic processes. Improved <span class="hlt">sea</span> <span class="hlt">ice</span> algorithms will aid the study of Arctic coastal polynyas which in turn will provide a better understanding of the role of these polynyas in maintaining the Arctic watermass structure. Analysis of satellite and archived meteorological data sets will provide improved estimates of annual, seasonal and shorter-term <span class="hlt">sea</span> <span class="hlt">ice</span> variability.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li class="active"><span>15</span></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_15 --> <div id="page_16" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li class="active"><span>16</span></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="301"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JGRD..12210837M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JGRD..12210837M"><span>Winter snow conditions on Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> north of Svalbard during the Norwegian young <span class="hlt">sea</span> <span class="hlt">ICE</span> (N-<span class="hlt">ICE</span>2015) expedition</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Merkouriadi, Ioanna; Gallet, Jean-Charles; Graham, Robert M.; Liston, Glen E.; Polashenski, Chris; Rösel, Anja; Gerland, Sebastian</p> <p>2017-10-01</p> <p>Snow is a crucial component of the Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> system. Its thickness and thermal properties control heat conduction and radiative fluxes across the ocean, <span class="hlt">ice</span>, and atmosphere interfaces. Hence, observations of the evolution of snow depth, density, thermal conductivity, and stratigraphy are crucial for the development of detailed snow numerical models predicting energy transfer through the snow pack. Snow depth is also a major uncertainty in predicting <span class="hlt">ice</span> thickness using remote sensing algorithms. Here we examine the winter spatial and temporal evolution of snow physical properties on first-year (FYI) and second-year <span class="hlt">ice</span> (SYI) in the Atlantic sector of the Arctic Ocean, during the Norwegian young <span class="hlt">sea</span> <span class="hlt">ICE</span> (N-<span class="hlt">ICE</span>2015) expedition (January to March 2015). During N-<span class="hlt">ICE</span>2015, the snow pack consisted of faceted grains (47%), depth hoar (28%), and wind slab (13%), indicating very different snow stratigraphy compared to what was observed in the Pacific sector of the Arctic Ocean during the SHEBA campaign (1997-1998). Average snow bulk density was 345 kg m-3 and it varied with <span class="hlt">ice</span> type. Snow depth was 41 ± 19 cm in January and 56 ± 17 cm in February, which is significantly greater than earlier suggestions for this region. The snow water equivalent was 14.5 ± 5.3 cm over first-year <span class="hlt">ice</span> and 19 ± 5.4 cm over second-year <span class="hlt">ice</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C31A..01G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C31A..01G"><span>Seasonal Changes of Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> Physical Properties Observed During N-<span class="hlt">ICE</span>2015: An Overview</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gerland, S.; Spreen, G.; Granskog, M. A.; Divine, D.; Ehn, J. K.; Eltoft, T.; Gallet, J. C.; Haapala, J. J.; Hudson, S. R.; Hughes, N. E.; Itkin, P.; King, J.; Krumpen, T.; Kustov, V. Y.; Liston, G. E.; Mundy, C. J.; Nicolaus, M.; Pavlov, A.; Polashenski, C.; Provost, C.; Richter-Menge, J.; Rösel, A.; Sennechael, N.; Shestov, A.; Taskjelle, T.; Wilkinson, J.; Steen, H.</p> <p>2015-12-01</p> <p>Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> is changing, and for improving the understanding of the cryosphere, data is needed to describe the status and processes controlling current seasonal <span class="hlt">sea</span> <span class="hlt">ice</span> growth, change and decay. We present preliminary results from in-situ observations on <span class="hlt">sea</span> <span class="hlt">ice</span> in the Arctic Basin north of Svalbard from January to June 2015. Over that time, the Norwegian research vessel «Lance» was moored to in total four <span class="hlt">ice</span> floes, drifting with the <span class="hlt">sea</span> <span class="hlt">ice</span> and allowing an international group of scientists to conduct detailed research. Each drift lasted until the ship reached the marginal <span class="hlt">ice</span> zone and <span class="hlt">ice</span> started to break up, before moving further north and starting the next drift. The ship stayed within the area approximately 80°-83° N and 5°-25° E. While the expedition covered measurements in the atmosphere, the snow and <span class="hlt">sea</span> <span class="hlt">ice</span> system, and in the ocean, as well as biological studies, in this presentation we focus on physics of snow and <span class="hlt">sea</span> <span class="hlt">ice</span>. Different <span class="hlt">ice</span> types could be investigated: young <span class="hlt">ice</span> in refrozen leads, first year <span class="hlt">ice</span>, and old <span class="hlt">ice</span>. Snow surveys included regular snow pits with standardized measurements of physical properties and sampling. Snow and <span class="hlt">ice</span> thickness were measured at stake fields, along transects with electromagnetics, and in drillholes. For quantifying <span class="hlt">ice</span> physical properties and texture, <span class="hlt">ice</span> cores were obtained regularly and analyzed. Optical properties of snow and <span class="hlt">ice</span> were measured both with fixed installed radiometers, and from mobile systems, a sledge and an ROV. For six weeks, the surface topography was scanned with a ground LIDAR system. Spatial scales of surveys ranged from spot measurements to regional surveys from helicopter (<span class="hlt">ice</span> thickness, photography) during two months of the expedition, and by means of an array of autonomous buoys in the region. Other regional information was obtained from SAR satellite imagery and from satellite based radar altimetry. The analysis of the data collected has started, and first results will be</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018JGRC..123..324B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018JGRC..123..324B"><span>Multiphase Reactive Transport and Platelet <span class="hlt">Ice</span> Accretion in the <span class="hlt">Sea</span> <span class="hlt">Ice</span> of McMurdo Sound, Antarctica</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Buffo, J. J.; Schmidt, B. E.; Huber, C.</p> <p>2018-01-01</p> <p><span class="hlt">Sea</span> <span class="hlt">ice</span> seasonally to interannually forms a thermal, chemical, and physical boundary between the atmosphere and hydrosphere over tens of millions of square kilometers of ocean. Its presence affects both local and global climate and ocean dynamics, <span class="hlt">ice</span> shelf processes, and biological communities. Accurate incorporation of <span class="hlt">sea</span> <span class="hlt">ice</span> growth and decay, and its associated thermal and physiochemical processes, is underrepresented in large-scale models due to the complex physics that dictate oceanic <span class="hlt">ice</span> formation and evolution. Two phenomena complicate <span class="hlt">sea</span> <span class="hlt">ice</span> simulation, particularly in the Antarctic: the multiphase physics of reactive transport brought about by the inhomogeneous solidification of seawater, and the buoyancy driven accretion of platelet <span class="hlt">ice</span> formed by supercooled <span class="hlt">ice</span> shelf water onto the basal surface of the overlying <span class="hlt">ice</span>. Here a one-dimensional finite difference model capable of simulating both processes is developed and tested against <span class="hlt">ice</span> core data. Temperature, salinity, liquid fraction, fluid velocity, total salt content, and <span class="hlt">ice</span> structure are computed during model runs. The model results agree well with empirical observations and simulations highlight the effect platelet <span class="hlt">ice</span> accretion has on overall <span class="hlt">ice</span> thickness and characteristics. Results from sensitivity studies emphasize the need to further constrain <span class="hlt">sea</span> <span class="hlt">ice</span> microstructure and the associated physics, particularly permeability-porosity relationships, if a complete model of <span class="hlt">sea</span> <span class="hlt">ice</span> evolution is to be obtained. Additionally, implications for terrestrial <span class="hlt">ice</span> shelves and icy moons in the solar system are discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26347534','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26347534"><span>Is <span class="hlt">ice</span>-rafted sediment in a North Pole marine record evidence for perennial <span class="hlt">sea-ice</span> cover?</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Tremblay, L B; Schmidt, G A; Pfirman, S; Newton, R; DeRepentigny, P</p> <p>2015-10-13</p> <p><span class="hlt">Ice</span>-rafted sediments of Eurasian and North American origin are found consistently in the upper part (13 Ma BP to present) of the Arctic Coring Expedition (ACEX) ocean core from the Lomonosov Ridge, near the North Pole (≈88° N). Based on modern <span class="hlt">sea-ice</span> drift trajectories and speeds, this has been taken as evidence of the presence of a perennial <span class="hlt">sea-ice</span> cover in the Arctic Ocean from the middle Miocene onwards (Krylov et al. 2008 Paleoceanography 23, PA1S06. (doi:10.1029/2007PA001497); Darby 2008 Paleoceanography 23, PA1S07. (doi:10.1029/2007PA001479)). However, other high latitude land and marine records indicate a long-term trend towards cooling broken by periods of extensive warming suggestive of a seasonally <span class="hlt">ice</span>-free Arctic between the Miocene and the present (Polyak et al. 2010 Quaternary Science Reviews 29, 1757-1778. (doi:10.1016/j.quascirev.2010.02.010)). We use a coupled <span class="hlt">sea-ice</span> slab-ocean model including sediment transport tracers to map the spatial distribution of <span class="hlt">ice</span>-rafted deposits in the Arctic Ocean. We use 6 hourly wind forcing and surface heat fluxes for two different climates: one with a perennial <span class="hlt">sea-ice</span> cover similar to that of the present day and one with seasonally <span class="hlt">ice</span>-free conditions, similar to that simulated in future projections. Model results confirm that in the present-day climate, <span class="hlt">sea</span> <span class="hlt">ice</span> takes more than 1 year to transport sediment from all its peripheral <span class="hlt">seas</span> to the North Pole. However, in a warmer climate, <span class="hlt">sea-ice</span> speeds are significantly faster (for the same wind forcing) and can deposit sediments of Laptev, East Siberian and perhaps also Beaufort <span class="hlt">Sea</span> origin at the North Pole. This is primarily because of the fact that <span class="hlt">sea-ice</span> interactions are much weaker with a thinner <span class="hlt">ice</span> cover and there is less resistance to drift. We conclude that the presence of <span class="hlt">ice</span>-rafted sediment of Eurasian and North American origin at the North Pole does not imply a perennial <span class="hlt">sea-ice</span> cover in the Arctic Ocean, reconciling the ACEX ocean core data with</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140013006','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140013006"><span>Effects of Mackenzie River Discharge and Bathymetry on <span class="hlt">Sea</span> <span class="hlt">Ice</span> in the Beaufort <span class="hlt">Sea</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Nghiem, S. V.; Hall, D. K.; Rigor, I. G; Li, P.; Neumann, G.</p> <p>2014-01-01</p> <p>Mackenzie River discharge and bathymetry effects on <span class="hlt">sea</span> <span class="hlt">ice</span> in the Beaufort <span class="hlt">Sea</span> are examined in 2012 when Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> extent hit a record low. Satellite-derived <span class="hlt">sea</span> surface temperature revealed warmer waters closer to river mouths. By 5 July 2012, Mackenzie warm waters occupied most of an open water area about 316,000 sq km. Surface temperature in a common open water area increased by 6.5 C between 14 June and 5 July 2012, before and after the river waters broke through a recurrent landfast <span class="hlt">ice</span> barrier formed over the shallow seafloor offshore the Mackenzie Delta. In 2012, melting by warm river waters was especially effective when the strong Beaufort Gyre fragmented <span class="hlt">sea</span> <span class="hlt">ice</span> into unconsolidated floes. The Mackenzie and other large rivers can transport an enormous amount of heat across immense continental watersheds into the Arctic Ocean, constituting a stark contrast to the Antarctic that has no such rivers to affect <span class="hlt">sea</span> <span class="hlt">ice</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018TCry...12.1681P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018TCry...12.1681P"><span>Variability of <span class="hlt">sea</span> salts in <span class="hlt">ice</span> and firn cores from Fimbul <span class="hlt">Ice</span> Shelf, Dronning Maud Land, Antarctica</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Paulina Vega, Carmen; Isaksson, Elisabeth; Schlosser, Elisabeth; Divine, Dmitry; Martma, Tõnu; Mulvaney, Robert; Eichler, Anja; Schwikowski-Gigar, Margit</p> <p>2018-05-01</p> <p>Major ions were analysed in firn and <span class="hlt">ice</span> cores located at Fimbul <span class="hlt">Ice</span> Shelf (FIS), Dronning Maud Land - DML, Antarctica. FIS is the largest <span class="hlt">ice</span> shelf in the Haakon VII <span class="hlt">Sea</span>, with an extent of approximately 36 500 km2. Three shallow firn cores (about 20 m deep) were retrieved in different <span class="hlt">ice</span> rises, Kupol Ciolkovskogo (KC), Kupol Moskovskij (KM), and Blåskimen Island (BI), while a 100 m long core (S100) was drilled near the FIS edge. These sites are distributed over the entire FIS area so that they provide a variety of elevation (50-400 m a.s.l.) and distance (3-42 km) to the <span class="hlt">sea</span>. <span class="hlt">Sea</span>-salt species (mainly Na+ and Cl-) generally dominate the precipitation chemistry in the study region. We associate a significant sixfold increase in median <span class="hlt">sea</span>-salt concentrations, observed in the S100 core after the 1950s, to an enhanced exposure of the S100 site to primary <span class="hlt">sea</span>-salt aerosol due to a shorter distance from the S100 site to the <span class="hlt">ice</span> front, and to enhanced <span class="hlt">sea</span>-salt aerosol production from blowing salty snow over <span class="hlt">sea</span> <span class="hlt">ice</span>, most likely related to the calving of Trolltunga occurred during the 1960s. This increase in <span class="hlt">sea</span>-salt concentrations is synchronous with a shift in non-<span class="hlt">sea</span>-salt sulfate (nssSO42-) toward negative values, suggesting a possible contribution of fractionated aerosol to the <span class="hlt">sea</span>-salt load in the S100 core most likely originating from salty snow found on <span class="hlt">sea</span> <span class="hlt">ice</span>. In contrast, there is no evidence of a significant contribution of fractionated <span class="hlt">sea</span> salt to the <span class="hlt">ice</span>-rises sites, where the signal would be most likely masked by the large inputs of biogenic sulfate estimated for these sites. In summary, these results suggest that the S100 core contains a <span class="hlt">sea</span>-salt record dominated by the proximity of the site to the ocean, and processes of <span class="hlt">sea</span> <span class="hlt">ice</span> formation in the neighbouring waters. In contrast, the <span class="hlt">ice</span>-rises firn cores register a larger-scale signal of atmospheric flow conditions and a less efficient transport of <span class="hlt">sea</span>-salt aerosols to these sites. These findings are a</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014PhDT........69M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014PhDT........69M"><span>Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span>: Trends, Stability and Variability</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Moon, Woosok</p> <p></p> <p>A stochastic Arctic <span class="hlt">sea-ice</span> model is derived and analyzed in detail to interpret the recent decay and associated variability of Arctic <span class="hlt">sea-ice</span> under changes in greenhouse gas forcing widely referred to as global warming. The approach begins from a deterministic model of the heat flux balance through the air/<span class="hlt">sea/ice</span> system, which uses observed monthly-averaged heat fluxes to drive a time evolution of <span class="hlt">sea-ice</span> thickness. This model reproduces the observed seasonal cycle of the <span class="hlt">ice</span> cover and it is to this that stochastic noise---representing high frequency variability---is introduced. The model takes the form of a single periodic non-autonomous stochastic ordinary differential equation. Following an introductory chapter, the two that follow focus principally on the properties of the deterministic model in order to identify the main properties governing the stability of the <span class="hlt">ice</span> cover. In chapter 2 the underlying time-dependent solutions to the deterministic model are analyzed for their stability. It is found that the response time-scale of the system to perturbations is dominated by the destabilizing <span class="hlt">sea-ice</span> albedo feedback, which is operative in the summer, and the stabilizing long wave radiative cooling of the <span class="hlt">ice</span> surface, which is operative in the winter. This basic competition is found throughout the thesis to define the governing dynamics of the system. In particular, as greenhouse gas forcing increases, the <span class="hlt">sea-ice</span> albedo feedback becomes more effective at destabilizing the system. Thus, any projections of the future state of Arctic <span class="hlt">sea-ice</span> will depend sensitively on the treatment of the <span class="hlt">ice</span>-albedo feedback. This in turn implies that the treatment a fractional <span class="hlt">ice</span> cover as the <span class="hlt">ice</span> areal extent changes rapidly, must be handled with the utmost care. In chapter 3, the idea of a two-season model, with just winter and summer, is revisited. By breaking the seasonal cycle up in this manner one can simplify the interpretation of the basic dynamics. Whereas in the fully</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.7879K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.7879K"><span>Tropospheric characteristics over <span class="hlt">sea</span> <span class="hlt">ice</span> during N-<span class="hlt">ICE</span>2015</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kayser, Markus; Maturilli, Marion; Graham, Robert; Hudson, Stephen; Cohen, Lana; Rinke, Annette; Kim, Joo-Hong; Park, Sang-Jong; Moon, Woosok; Granskog, Mats</p> <p>2017-04-01</p> <p>Over recent years, the Arctic Ocean region has shifted towards a younger and thinner <span class="hlt">sea-ice</span> regime. The Norwegian young <span class="hlt">sea</span> <span class="hlt">ICE</span> (N-<span class="hlt">ICE</span>2015) expedition was designed to investigate the atmosphere-snow-<span class="hlt">ice</span>-ocean interactions in this new <span class="hlt">ice</span> regime north of Svalbard. Here we analyze upper-air measurements made by radiosondes launched twice daily together with surface meteorology observations during N-<span class="hlt">ICE</span>2015 from January to June 2015. We study the multiple cyclonic events observed during N-<span class="hlt">ICE</span>2015 with respect to changes in the vertical thermodynamic structure, sudden increases in moisture content and temperature, temperature inversions and boundary layer dynamics. The influence of synoptic cyclones is strongest under polar night conditions, when radiative cooling is most effective and the moisture content is low. We find that transitions between the radiatively clear and opaque state are the largest drivers of changes to temperature inversion and stability characteristics in the boundary layer during winter. In spring radiative fluxes warm the surface leading to lifted temperature inversions and a statically unstable boundary layer. The unique N-<span class="hlt">ICE</span>2015 dataset is used for case studies investigating changes in the vertical structure of the atmosphere under varying synoptic conditions. The goal is to deepen our understanding of synoptic interactions within the Arctic climate system, to improve model performance, as well as to identify gaps in instrumentation, which precludes further investigations.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-GSFC_20171208_Archive_e000751.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-GSFC_20171208_Archive_e000751.html"><span><span class="hlt">Sea</span> <span class="hlt">Ice</span> off the Princess Astrid Coast</span></a></p> <p><a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a></p> <p></p> <p>2015-04-08</p> <p>On April 5, 2015, the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite acquired this natural-color image of <span class="hlt">sea</span> <span class="hlt">ice</span> off the coast of East Antarctica’s Princess Astrid Coast. White areas close to the continent are <span class="hlt">sea</span> <span class="hlt">ice</span>, while white areas in the northeast corner of the image are clouds. One way to better distinguish <span class="hlt">ice</span> from clouds is with false-color imagery. In the false-color view of the scene here, <span class="hlt">ice</span> is blue and clouds are white. The image was acquired after Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> had passed its annual minimum extent (reached on February 20, 2015), and had resumed expansion toward its maximum extent (usually reached in September). Credit: NASA image by Jeff Schmaltz, LANCE/EOSDIS Rapid Response. Caption by Kathryn Hansen via NASA's Earth Observatory Read more: www.nasa.gov/content/<span class="hlt">sea-ice</span>-off-east-antarcticas-princes... NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19900060081&hterms=oceanography&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Doceanography','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19900060081&hterms=oceanography&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Doceanography"><span>Satellite observations of the <span class="hlt">ice</span> cover of the Kuril Basin region of the Okhotsk <span class="hlt">Sea</span> and its relation to the regional oceanography</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wakatsuchi, Masaaki; Martin, Seelye</p> <p>1990-01-01</p> <p>For the period 1978-1982, this paper examines the nature of the <span class="hlt">sea</span> <span class="hlt">ice</span> which forms over the Kuril Basin of the Okhotsk <span class="hlt">Sea</span> and describes the impact of this <span class="hlt">ice</span> on the regional oceanography. The oceanographic behavior during the heavy <span class="hlt">ice</span> season associated with the cold 1979 winter is compared with the behavior during the lighter <span class="hlt">ice</span> years of 1980 and 1982. Examination of the oceanography in the Okhotsk and the <span class="hlt">adjacent</span> Pacific shows that the early summer water column structure depends on the heat loss from the Okhotsk during the preceding <span class="hlt">ice</span> season, the total amount of Okhotsk <span class="hlt">ice</span> formation, and, specifically, the amount of the <span class="hlt">ice</span> formation in the Kuril Basin. Following the 1979 <span class="hlt">ice</span> season, the upper 200-300 m of the Kuril Basin waters were cooler, less saline, and richer in oxygen than for the other years. This modification appears to be a process local to the Kuril Basin, driven by eddy-induced mixing, local cooling, and <span class="hlt">ice</span> melting.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20160004954&hterms=sea&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dsea','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20160004954&hterms=sea&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dsea"><span>Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> Simulation in the PlioMIP Ensemble</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Howell, Fergus W.; Haywood, Alan M.; Otto-Bliesner, Bette L.; Bragg, Fran; Chan, Wing-Le; Chandler, Mark A.; Contoux, Camille; Kamae, Youichi; Abe-Ouchi, Ayako; Rosenbloom, Nan A.; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_20160004954'); toggleEditAbsImage('author_20160004954_show'); toggleEditAbsImage('author_20160004954_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_20160004954_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_20160004954_hide"></p> <p>2016-01-01</p> <p>Eight general circulation models have simulated the mid-Pliocene warm period (mid-Pliocene, 3.264 to 3.025 Ma) as part of the Pliocene Modelling Intercomparison Project (PlioMIP). Here, we analyse and compare their simulation of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> for both the pre-industrial period and the mid-Pliocene. Mid-Pliocene <span class="hlt">sea</span> <span class="hlt">ice</span> thickness and extent is reduced, and the model spread of extent is more than twice the pre-industrial spread in some summer months. Half of the PlioMIP models simulate <span class="hlt">ice</span>-free conditions in the mid-Pliocene. This spread amongst the ensemble is in line with the uncertainties amongst proxy reconstructions for mid-Pliocene <span class="hlt">sea</span> <span class="hlt">ice</span> extent. Correlations between mid-Pliocene Arctic temperatures and <span class="hlt">sea</span> <span class="hlt">ice</span> extents are almost twice as strong as the equivalent correlations for the pre-industrial simulations. The need for more comprehensive <span class="hlt">sea</span> <span class="hlt">ice</span> proxy data is highlighted, in order to better compare model performances.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120010403','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120010403"><span>Satellite Observations of Antarctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> Thickness and Volume</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Kurtz, Nathan; Markus, Thorsten</p> <p>2012-01-01</p> <p>We utilize satellite laser altimetry data from ICESat combined with passive microwave measurements to analyze basin-wide changes in Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> thickness and volume over a 5 year period from 2003-2008. <span class="hlt">Sea</span> <span class="hlt">ice</span> thickness exhibits a small negative trend while area increases in the summer and fall balanced losses in thickness leading to small overall volume changes. Using a five year time-series, we show that only small <span class="hlt">ice</span> thickness changes of less than -0.03 m/yr and volume changes of -266 cu km/yr and 160 cu km/yr occurred for the spring and summer periods, respectively. The calculated thickness and volume trends are small compared to the observational time period and interannual variability which masks the determination of long-term trend or cyclical variability in the <span class="hlt">sea</span> <span class="hlt">ice</span> cover. These results are in stark contrast to the much greater observed losses in Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> volume and illustrate the different hemispheric changes of the polar <span class="hlt">sea</span> <span class="hlt">ice</span> covers in recent years.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28694490','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28694490"><span><span class="hlt">Sea</span> <span class="hlt">ice</span> breakup and marine melt of a retreating tidewater outlet glacier in northeast Greenland (81°N).</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Bendtsen, Jørgen; Mortensen, John; Lennert, Kunuk; K Ehn, Jens; Boone, Wieter; Galindo, Virginie; Hu, Yu-Bin; Dmitrenko, Igor A; Kirillov, Sergei A; Kjeldsen, Kristian K; Kristoffersen, Yngve; G Barber, David; Rysgaard, Søren</p> <p>2017-07-10</p> <p>Rising temperatures in the Arctic cause accelerated mass loss from the Greenland <span class="hlt">Ice</span> Sheet and reduced <span class="hlt">sea</span> <span class="hlt">ice</span> cover. Tidewater outlet glaciers represent direct connections between glaciers and the ocean where melt rates at the <span class="hlt">ice</span>-ocean interface are influenced by ocean temperature and circulation. However, few measurements exist near outlet glaciers from the northern coast towards the Arctic Ocean that has remained nearly permanently <span class="hlt">ice</span> covered. Here we present hydrographic measurements along the terminus of a major retreating tidewater outlet glacier from Flade Isblink <span class="hlt">Ice</span> Cap. We show that the region is characterized by a relatively large change of the seasonal freshwater content, corresponding to ~2 m of freshwater, and that solar heating during the short open water period results in surface layer temperatures above 1 °C. Observations of temperature and salinity supported that the outlet glacier is a floating <span class="hlt">ice</span> shelf with near-glacial subsurface temperatures at the freezing point. Melting from the surface layer significantly influenced the <span class="hlt">ice</span> foot morphology of the glacier terminus. Hence, melting of the tidewater outlet glacier was found to be critically dependent on the retreat of <span class="hlt">sea</span> <span class="hlt">ice</span> <span class="hlt">adjacent</span> to the terminus and the duration of open water.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20010026440','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20010026440"><span>Observation of <span class="hlt">Sea</span> <span class="hlt">Ice</span> Surface Thermal States Under Cloud Cover</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Nghiem, S. V.; Perovich, D. K.; Gow, A. J.; Kwok, R.; Barber, D. G.; Comiso, J. C.; Zukor, Dorothy J. (Technical Monitor)</p> <p>2001-01-01</p> <p>Clouds interfere with the distribution of short-wave and long-wave radiations over <span class="hlt">sea</span> <span class="hlt">ice</span>, and thereby strongly affect the surface energy balance in polar regions. To evaluate the overall effects of clouds on climatic feedback processes in the atmosphere-<span class="hlt">ice</span>-ocean system, the challenge is to observe <span class="hlt">sea</span> <span class="hlt">ice</span> surface thermal states under both clear sky and cloudy conditions. From laboratory experiments, we show that C-band radar (transparent to clouds) backscatter is very sensitive to the surface temperature of first-year <span class="hlt">sea</span> <span class="hlt">ice</span>. The effect of <span class="hlt">sea</span> <span class="hlt">ice</span> surface temperature on the magnitude of backscatter change depends on the thermal regimes of <span class="hlt">sea</span> <span class="hlt">ice</span> thermodynamic states. For the temperature range above the mirabilite (Na2SO4.10H20) crystallization point (-8.2 C), C-band data show <span class="hlt">sea</span> <span class="hlt">ice</span> backscatter changes by 8-10 dB for incident angles from 20 to 35 deg at both horizontal and vertical polarizations. For temperatures below the mirabilite point but above the crystallization point of MgCl2.8H2O (-18.0 C), relatively strong backwater changes between 4-6 dB are observed. These backscatter changes correspond to approximately 8 C change in temperature for both cases. The backscattering mechanism is related to the temperature which determines the thermodynamic distribution of brine volume in the <span class="hlt">sea</span> <span class="hlt">ice</span> surface layer. The backscatter is positively correlated to temperature and the process is reversible with thermodynamic variations such as diurnal insolation effects. From two different dates in May 1993 with clear and overcast conditions determined by the Advanced Very High Resolution Radiometer (AVHRR), concurrent Earth Resources Satellite 1 (ERS-1) C-band <span class="hlt">ice</span> observed with increases in backscatter over first-year <span class="hlt">sea</span> <span class="hlt">ice</span>, and verified by increases in in-situ <span class="hlt">sea</span> <span class="hlt">ice</span> surface temperatures measured at the Collaborative-Interdisciplinary Cryosphere Experiment (C-<span class="hlt">ICE</span>) site.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFMOS11B1654B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFMOS11B1654B"><span>Skin Temperature Processes in the Presence of <span class="hlt">Sea</span> <span class="hlt">Ice</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Brumer, S. E.; Zappa, C. J.; Brown, S.; McGillis, W. R.; Loose, B.</p> <p>2013-12-01</p> <p>Monitoring the <span class="hlt">sea-ice</span> margins of polar oceans and understanding the physical processes at play at the <span class="hlt">ice</span>-ocean-air interface is essential in the perspective of a changing climate in which we face an accelerated decline of <span class="hlt">ice</span> caps and <span class="hlt">sea</span> <span class="hlt">ice</span>. Remote sensing and in particular InfraRed (IR) imaging offer a unique opportunity not only to observe physical processes at <span class="hlt">sea-ice</span> margins, but also to measure air-<span class="hlt">sea</span> exchanges near <span class="hlt">ice</span>. It permits monitoring <span class="hlt">ice</span> and ocean temperature variability, and can be used for derivation of surface flow field allowing investigating turbulence and shearing at the <span class="hlt">ice</span>-ocean interface as well as ocean-atmosphere gas transfer. Here we present experiments conducted with the aim of gaining an insight on how the presence of <span class="hlt">sea</span> <span class="hlt">ice</span> affects the momentum exchange between the atmosphere and ocean and investigate turbulence production in the interplay of <span class="hlt">ice</span>-water shear, convection, waves and wind. A set of over 200 high resolution IR imagery records was taken at the US Army Cold Regions Research and Engineering Laboratory (CRREL, Hanover NH) under varying <span class="hlt">ice</span> coverage, fan and pump settings. In situ instruments provided air and water temperature, salinity, subsurface currents and wave height. Air side profiling provided environmental parameters such as wind speed, humidity and heat fluxes. The study aims to investigate what can be gained from small-scale high-resolution IR imaging of the <span class="hlt">ice</span>-ocean-air interface; in particular how <span class="hlt">sea</span> <span class="hlt">ice</span> modulates local physics and gas transfer. The relationship between water and <span class="hlt">ice</span> temperatures with current and wind will be addressed looking at the ocean and <span class="hlt">ice</span> temperature variance. Various skin temperature and gas transfer parameterizations will be evaluated at <span class="hlt">ice</span> margins under varying environmental conditions. Furthermore the accuracy of various techniques used to determine surface flow will be assessed from which turbulence statistics will be determined. This will give an insight on how <span class="hlt">ice</span> presence</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011PhDT.......110D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011PhDT.......110D"><span>Alaska shorefast <span class="hlt">ice</span>: Interfacing geophysics with local <span class="hlt">sea</span> <span class="hlt">ice</span> knowledge and use</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Druckenmiller, Matthew L.</p> <p></p> <p>This thesis interfaces geophysical techniques with local and traditional knowledge (LTK) of indigenous <span class="hlt">ice</span> experts to track and evaluate coastal <span class="hlt">sea</span> <span class="hlt">ice</span> conditions over annual and inter-annual timescales. A novel approach is presented for consulting LTK alongside a systematic study of where, when, and how the community of Barrow, Alaska uses the <span class="hlt">ice</span> cover. The goal of this research is to improve our understanding of and abilities to monitor the processes that govern the state and dynamics of shorefast <span class="hlt">sea</span> <span class="hlt">ice</span> in the Chukchi <span class="hlt">Sea</span> and use of <span class="hlt">ice</span> by the community. Shorefast <span class="hlt">ice</span> stability and community strategies for safe hunting provide a framework for data collection and knowledge sharing that reveals how nuanced observations by Inupiat <span class="hlt">ice</span> experts relate to identifying hazards. In particular, shorefast <span class="hlt">ice</span> break-out events represent a significant threat to the lives of hunters. Fault tree analysis (FTA) is used to combine local and time-specific observations of <span class="hlt">ice</span> conditions by both geophysical instruments and local experts, and to evaluate how <span class="hlt">ice</span> features, atmospheric and oceanic forces, and local to regional processes interact to cause break-out events. Each year, the Barrow community builds trails across shorefast <span class="hlt">ice</span> for use during the spring whaling season. In collaboration with hunters, a systematic multi-year survey (2007--2011) was performed to map these trails and measure <span class="hlt">ice</span> thickness along them. Relationships between <span class="hlt">ice</span> conditions and hunter strategies that guide trail placement and risk assessment are explored. In addition, trail surveys provide a meaningful and consistent approach to monitoring the thickness distribution of shorefast <span class="hlt">ice</span>, while establishing a baseline for assessing future environmental change and potential impacts to the community. Coastal communities in the region have proven highly adaptive in their ability to safely and successfully hunt from <span class="hlt">sea</span> <span class="hlt">ice</span> over the last 30 years as significant changes have been observed in the <span class="hlt">ice</span> zone</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C43D..01R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C43D..01R"><span>NASA <span class="hlt">Ice</span>Bridge: Scientific Insights from Airborne Surveys of the Polar <span class="hlt">Sea</span> <span class="hlt">Ice</span> Covers</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Richter-Menge, J.; Farrell, S. L.</p> <p>2015-12-01</p> <p>The NASA Operation <span class="hlt">Ice</span>Bridge (OIB) airborne <span class="hlt">sea</span> <span class="hlt">ice</span> surveys are designed to continue a valuable series of <span class="hlt">sea</span> <span class="hlt">ice</span> thickness measurements by bridging the gap between NASA's <span class="hlt">Ice</span>, Cloud and Land Elevation Satellite (ICESat), which operated from 2003 to 2009, and ICESat-2, which is scheduled for launch in 2017. Initiated in 2009, OIB has conducted campaigns over the western Arctic Ocean (March/April) and Southern Oceans (October/November) on an annual basis when the thickness of <span class="hlt">sea</span> <span class="hlt">ice</span> cover is nearing its maximum. More recently, a series of Arctic surveys have also collected observations in the late summer, at the end of the melt season. The Airborne Topographic Mapper (ATM) laser altimeter is one of OIB's primary sensors, in combination with the Digital Mapping System digital camera, a Ku-band radar altimeter, a frequency-modulated continuous-wave (FMCW) snow radar, and a KT-19 infrared radiation pyrometer. Data from the campaigns are available to the research community at: http://nsidc.org/data/icebridge/. This presentation will summarize the spatial and temporal extent of the OIB campaigns and their complementary role in linking in situ and satellite measurements, advancing observations of <span class="hlt">sea</span> <span class="hlt">ice</span> processes across all length scales. Key scientific insights gained on the state of the <span class="hlt">sea</span> <span class="hlt">ice</span> cover will be highlighted, including snow depth, <span class="hlt">ice</span> thickness, surface roughness and morphology, and melt pond evolution.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2005AGUFM.A12B..01M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2005AGUFM.A12B..01M"><span>Overview of <span class="hlt">Sea-Ice</span> Properties, Distribution and Temporal Variations, for Application to <span class="hlt">Ice</span>-Atmosphere Chemical Processes.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Moritz, R. E.</p> <p>2005-12-01</p> <p>The properties, distribution and temporal variation of <span class="hlt">sea-ice</span> are reviewed for application to problems of <span class="hlt">ice</span>-atmosphere chemical processes. Typical vertical structure of <span class="hlt">sea-ice</span> is presented for different <span class="hlt">ice</span> types, including young <span class="hlt">ice</span>, first-year <span class="hlt">ice</span> and multi-year <span class="hlt">ice</span>, emphasizing factors relevant to surface chemistry and gas exchange. Time average annual cycles of large scale variables are presented, including <span class="hlt">ice</span> concentration, <span class="hlt">ice</span> extent, <span class="hlt">ice</span> thickness and <span class="hlt">ice</span> age. Spatial and temporal variability of these large scale quantities is considered on time scales of 1-50 years, emphasizing recent and projected changes in the Arctic pack <span class="hlt">ice</span>. The amount and time evolution of open water and thin <span class="hlt">ice</span> are important factors that influence ocean-<span class="hlt">ice</span>-atmosphere chemical processes. Observations and modeling of the <span class="hlt">sea-ice</span> thickness distribution function are presented to characterize the range of variability in open water and thin <span class="hlt">ice</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMPP13C..01S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMPP13C..01S"><span>Coherent <span class="hlt">Sea</span> <span class="hlt">Ice</span> Variations in the Nordic <span class="hlt">Seas</span> and Abrupt Greenland Climate Changes over Dansgaard-Oeschger Cycles</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sadatzki, H.; Berben, S.; Dokken, T.; Stein, R.; Fahl, K.; Jansen, E.</p> <p>2016-12-01</p> <p>Rapid changes in <span class="hlt">sea</span> <span class="hlt">ice</span> extent in the Nordic <span class="hlt">Seas</span> may have played a crucial role in controlling the abruptness of ocean circulation and climate changes associated with Dansgaard-Oeschger (D-O) cycles during the last glacial (Li et al., 2010; Dokken et al., 2013). To investigate the role of <span class="hlt">sea</span> <span class="hlt">ice</span> for abrupt climate changes, we produced a <span class="hlt">sea</span> <span class="hlt">ice</span> record from the Norwegian <span class="hlt">Sea</span> Core MD99-2284 at a temporal resolution approaching that of <span class="hlt">ice</span> core records, covering four D-O cycles at ca. 32-41 ka. This record is based on the <span class="hlt">sea</span> <span class="hlt">ice</span> diatom biomarker IP25, open-water phytoplankton biomarker dinosterol and semi-quantitative phytoplankton-IP25 (PIP25) estimates. A detailed tephrochronology of MD99-2284 corroborates the tuning-based age model and independently constrains the GS9/GIS8 transition, allowing for direct comparison between our sediment and <span class="hlt">ice</span> core records. For cold stadials we find extremely low fluxes of total organic carbon, dinosterol and IP25, which points to a general absence of open-water phytoplankton and <span class="hlt">ice</span> algae production under a near-permanent <span class="hlt">sea</span> <span class="hlt">ice</span> cover. For the interstadials, in turn, all biomarker fluxes are strongly enhanced, reflecting a highly productive <span class="hlt">sea</span> <span class="hlt">ice</span> edge situation and implying largely open ocean conditions for the eastern Nordic <span class="hlt">Seas</span>. As constrained by three tephra layers, we observe that the stadial-interstadial <span class="hlt">sea</span> <span class="hlt">ice</span> decline was rapid and may have induced a coeval abrupt northward shift in the Greenland precipitation moisture source as recorded in <span class="hlt">ice</span> cores. The <span class="hlt">sea</span> <span class="hlt">ice</span> retreat also facilitated a massive heat release through deep convection in the previously stratified Nordic <span class="hlt">Seas</span>, generating atmospheric warming of the D-O events. We thus conclude that rapid changes in <span class="hlt">sea</span> <span class="hlt">ice</span> extent in the Nordic <span class="hlt">Seas</span> amplified oceanic reorganizations and were a key factor in controlling abrupt Greenland climate changes over D-O cycles. Dokken, T.M. et al., 2013. Paleoceanography 28, 491-502 Li, C. et al., 2010. Journ. Clim. 23, 5457-5475</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20050185661','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20050185661"><span><span class="hlt">Sea</span> <span class="hlt">Ice</span> Kinematics and Thickness from RGPS: Observations and Theory</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Stern, Harry; Lindsay, Ron; Yu, Yan-Ling; Moritz, Richard; Rothrock, Drew</p> <p>2005-01-01</p> <p>The RADARSAT Geophysical Processor System (RGPS) has produced a wealth of data on Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> motion, deformation, and thickness with broad geographical coverage and good temporal resolution. These data provide unprecedented spatial detail of the structure and evolution of the <span class="hlt">sea</span> <span class="hlt">ice</span> cover. The broad purpose of this study was to take advantage of the strengths of the RGPS data set to investigate <span class="hlt">sea</span> <span class="hlt">ice</span> kinematics and thickness, which affect the climate through their influence on <span class="hlt">ice</span> production, ridging, and transport (i.e. mass balance); heat flux to the atmosphere; and structure of the upper ocean mixed layer. The objectives of this study were to: (1) Explain the relationship between the discontinuous motion of the <span class="hlt">ice</span> cover and the large-scale, smooth wind field that drives the <span class="hlt">ice</span>; (2) Characterize the <span class="hlt">sea</span> <span class="hlt">ice</span> deformation in the Arctic at different temporal and spatial scales, and compare it with deformation predicted by a state-of-theart <span class="hlt">ice</span>/ocean model; and (3) Compare RGPS-derived <span class="hlt">sea</span> <span class="hlt">ice</span> thickness with other data, and investigate the thinning of the Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> cover as seen in ULS data obtained by U.S. Navy submarines. We briefly review the results of our work below, separated into the topics of <span class="hlt">sea</span> <span class="hlt">ice</span> deformation and <span class="hlt">sea</span> <span class="hlt">ice</span> thickness. This is followed by a list of publications, meetings and presentations, and other activities supported under this grant. We are attaching to this report copies of all the listed publications. Finally, we would like to point out our community service to NASA through our involvement with the ASF User Working Group and the RGPS Science Working Group, as evidenced in the list of meetings and presentations below.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li class="active"><span>16</span></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_16 --> <div id="page_17" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li class="active"><span>17</span></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="321"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-PIA18034.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-PIA18034.html"><span>Warm Rivers Play Role in Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> Melt</span></a></p> <p><a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a></p> <p></p> <p>2014-03-05</p> <p>Beaufort <span class="hlt">Sea</span> surface temperatures where Canada Mackenzie River discharges into the Arctic Ocean, measured by NASA MODIS instrument; warm river waters had broken through a shoreline <span class="hlt">sea</span> <span class="hlt">ice</span> barrier to enhance <span class="hlt">sea</span> <span class="hlt">ice</span> melt.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1993EOSTr..74..121I','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1993EOSTr..74..121I"><span>Weddell <span class="hlt">Sea</span> exploration from <span class="hlt">ice</span> station</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ice Station Weddell Group of Principal Investigators; Chief Scientists; Gordon, Arnold L.</p> <p></p> <p>On January 18, 1915, the Endurance and Sir Ernest Shackleton and his crew were stranded in the <span class="hlt">ice</span> of the Weddell <span class="hlt">Sea</span> and began one of the most famous drifts in polar exploration. Shackleton turned a failure into a triumph by leading all of his team to safety [Shackleton, 1919]. The drift track of the Endurance and the <span class="hlt">ice</span> floe occupied by her stranded crew after the ship was lost on November 21, 1915, at 68°38.5‧S and 52°26.5‧W, carried the group along the western rim of the Weddell Gyre, representing a rare human presence in this region of perennial <span class="hlt">sea-ice</span> cover.Seventy-seven years later, in 1992, the first intentional scientific Southern Ocean <span class="hlt">ice</span> drift station, <span class="hlt">Ice</span> Station Weddell-1 (ISW-1), was established in the western Weddell <span class="hlt">Sea</span> by a joint effort of the United States and Russia. ISW-1 followed the track of the Endurance closely (Figure 1) and gathered an impressive array of data in this largely unexplored corner of the Southern Ocean, the western edge of the Weddell Gyre.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.C21C0622M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.C21C0622M"><span>Meteorological conditions influencing the formation of level <span class="hlt">ice</span> within the Baltic <span class="hlt">Sea</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mazur, A. K.; Krezel, A.</p> <p>2012-12-01</p> <p>The Baltic <span class="hlt">Sea</span> is covered by <span class="hlt">ice</span> every winter and on average, the <span class="hlt">ice</span>-covered area is 45% of the total area of the Baltic <span class="hlt">Sea</span>. The beginning of <span class="hlt">ice</span> season usually starts in the end of November, <span class="hlt">ice</span> extent is the largest between mid-February and mid-March and <span class="hlt">sea</span> <span class="hlt">ice</span> disappears completely in May. The <span class="hlt">ice</span> covered areas during a typical winter are the Gulf of Bothnia, the Gulf of Finland and the Gulf of Riga. The studies of <span class="hlt">sea</span> <span class="hlt">ice</span> in the Baltic <span class="hlt">Sea</span> are related to two aspects: climate and marine transport. Depending on the local weather conditions during the winter different types of <span class="hlt">sea</span> <span class="hlt">ice</span> can be formed. From the point of winter shipping it is important to locate level and deformed <span class="hlt">ice</span> areas (rafted <span class="hlt">ice</span>, ridged <span class="hlt">ice</span>, and hummocked <span class="hlt">ice</span>). Because of cloud and daylight independency as well as good spatial resolution, SAR data seems to be the most suitable source of data for <span class="hlt">sea</span> <span class="hlt">ice</span> observation in the comparatively small area of the Baltic <span class="hlt">Sea</span>. We used ASAR Wide Swath Mode data with spatial resolution 150 m. We analyzed data from the three winter seasons which were examples of severe, typical and mild winters. To remove the speckle effect the data were resampled to 250 m pixel size and filtred using Frost filter 5x5. To detect edges we used Sobel filter. The data were also converted into grayscale. <span class="hlt">Sea</span> <span class="hlt">ice</span> classification was based on Object-Based Image Analysis (OBIA). Object-based methods are not a common tool in <span class="hlt">sea</span> <span class="hlt">ice</span> studies but they seem to accurately separate level <span class="hlt">ice</span> within the <span class="hlt">ice</span> pack. The data were segmented and classified using eCognition Developer software. Level <span class="hlt">ice</span> were classified based on texture features defined by Haralick (Grey Level Co-Occurrence Matrix homogeneity, GLCM contrast, GLCM entropy and GLCM correlation). The long-term changes of the Baltic <span class="hlt">Sea</span> <span class="hlt">ice</span> conditions have been already studied. They include date of freezing, date of break-up, <span class="hlt">sea</span> <span class="hlt">ice</span> extent and some of work also <span class="hlt">ice</span> thickness. There is a little knowledge about the relationship of</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70186594','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70186594"><span>Diminishing <span class="hlt">sea</span> <span class="hlt">ice</span> in the western Arctic Ocean</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Stone, R.S.; Belchansky, G.I.; Drobot, Sheldon; Douglas, David C.; Levinson, D.H.; Waple, A.M.</p> <p>2004-01-01</p> <p>Since the advent of satellite passive microwave radiometry (1978), variations in <span class="hlt">sea</span> <span class="hlt">ice</span> extent and concentration have been carefully monitored from space. An estimated 7.4% decrease in <span class="hlt">sea</span> <span class="hlt">ice</span> extent has occurred in the last 25 yr (Johannessen et al. 2004), with recent record minima (e.g., Maslanik et al. 1999; Serreze et al. 2003) accounting for much of the decline. Comparisons between the time series of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> melt dynamics and snowmelt dates at the NOAA–CMDL Barrow Observatory (BRW) reveal intriguing correlations.Melt-onset dates over <span class="hlt">sea</span> <span class="hlt">ice</span> (Drobot and Anderson 2001) were cross correlated with the melt-date time series from BRW, and a prominent region of high correlation between snowmelt onset over <span class="hlt">sea</span> <span class="hlt">ice</span> and the BRW record of melt dates was approximately aligned with the climatological center of the Beaufort <span class="hlt">Sea</span> Anticyclone (BSA). The BSA induces anticyclonic <span class="hlt">ice</span> motion in the region, effectively forcing the Beaufort gyre. A weak gyre caused by a breakdown of the BSA diminishes transport of multiyear <span class="hlt">ice</span> into this region (Drobot and Maslanik 2003). Similarly, the annual snow cycle at BRW varies with the position and intensity of the BSA (Stone et al. 2002, their Fig. 6). Thus, variations in the BSA appear to have far-reaching effects on the annual accumulation and subsequent melt of snow over a large region of the western Arctic.A dramatic increase in melt season duration (Belchansky et al. 2004) was also observed within the same region of high correlation between onset of melt over the <span class="hlt">ice</span> pack and snowmelt at BRW (Fig. 5.7). By inference, this suggests linkages between factors that modulate the annual cycle of snow on land and processes that influence melting of snow and <span class="hlt">ice</span> in the western Arctic Ocean.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/19109440','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/19109440"><span>Nonlinear threshold behavior during the loss of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span>.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Eisenman, I; Wettlaufer, J S</p> <p>2009-01-06</p> <p>In light of the rapid recent retreat of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span>, a number of studies have discussed the possibility of a critical threshold (or "tipping point") beyond which the <span class="hlt">ice</span>-albedo feedback causes the <span class="hlt">ice</span> cover to melt away in an irreversible process. The focus has typically been centered on the annual minimum (September) <span class="hlt">ice</span> cover, which is often seen as particularly susceptible to destabilization by the <span class="hlt">ice</span>-albedo feedback. Here, we examine the central physical processes associated with the transition from <span class="hlt">ice</span>-covered to <span class="hlt">ice</span>-free Arctic Ocean conditions. We show that although the <span class="hlt">ice</span>-albedo feedback promotes the existence of multiple <span class="hlt">ice</span>-cover states, the stabilizing thermodynamic effects of <span class="hlt">sea</span> <span class="hlt">ice</span> mitigate this when the Arctic Ocean is <span class="hlt">ice</span> covered during a sufficiently large fraction of the year. These results suggest that critical threshold behavior is unlikely during the approach from current perennial <span class="hlt">sea-ice</span> conditions to seasonally <span class="hlt">ice</span>-free conditions. In a further warmed climate, however, we find that a critical threshold associated with the sudden loss of the remaining wintertime-only <span class="hlt">sea</span> <span class="hlt">ice</span> cover may be likely.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26580809','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26580809"><span>Increased Land Use by Chukchi <span class="hlt">Sea</span> Polar Bears in Relation to Changing <span class="hlt">Sea</span> <span class="hlt">Ice</span> Conditions.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Rode, Karyn D; Wilson, Ryan R; Regehr, Eric V; St Martin, Michelle; Douglas, David C; Olson, Jay</p> <p>2015-01-01</p> <p>Recent observations suggest that polar bears (Ursus maritimus) are increasingly using land habitats in some parts of their range, where they have minimal access to their preferred prey, likely in response to loss of their <span class="hlt">sea</span> <span class="hlt">ice</span> habitat associated with climatic warming. We used location data from female polar bears fit with satellite radio collars to compare land use patterns in the Chukchi <span class="hlt">Sea</span> between two periods (1986-1995 and 2008-2013) when substantial summer <span class="hlt">sea-ice</span> loss occurred. In both time periods, polar bears predominantly occupied <span class="hlt">sea-ice</span>, although land was used during the summer <span class="hlt">sea-ice</span> retreat and during the winter for maternal denning. However, the proportion of bears on land for > 7 days between August and October increased between the two periods from 20.0% to 38.9%, and the average duration on land increased by 30 days. The majority of bears that used land in the summer and for denning came to Wrangel and Herald Islands (Russia), highlighting the importance of these northernmost land habitats to Chukchi <span class="hlt">Sea</span> polar bears. Where bears summered and denned, and how long they spent there, was related to the timing and duration of <span class="hlt">sea</span> <span class="hlt">ice</span> retreat. Our results are consistent with other studies supporting increased land use as a common response of polar bears to <span class="hlt">sea-ice</span> loss. Implications of increased land use for Chukchi <span class="hlt">Sea</span> polar bears are unclear, because a recent study observed no change in body condition or reproductive indices between the two periods considered here. This result suggests that the ecology of this region may provide a degree of resilience to <span class="hlt">sea</span> <span class="hlt">ice</span> loss. However, projections of continued <span class="hlt">sea</span> <span class="hlt">ice</span> loss suggest that polar bears in the Chukchi <span class="hlt">Sea</span> and other parts of the Arctic may increasingly use land habitats in the future, which has the potential to increase nutritional stress and human-polar bear interactions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015GeoRL..42.5442L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015GeoRL..42.5442L"><span>Observed platelet <span class="hlt">ice</span> distributions in Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span>: An index for ocean-<span class="hlt">ice</span> shelf heat flux</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Langhorne, P. J.; Hughes, K. G.; Gough, A. J.; Smith, I. J.; Williams, M. J. M.; Robinson, N. J.; Stevens, C. L.; Rack, W.; Price, D.; Leonard, G. H.; Mahoney, A. R.; Haas, C.; Haskell, T. G.</p> <p>2015-07-01</p> <p>Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> that has been affected by supercooled <span class="hlt">Ice</span> Shelf Water (ISW) has a unique crystallographic structure and is called platelet <span class="hlt">ice</span>. In this paper we synthesize platelet <span class="hlt">ice</span> observations to construct a continent-wide map of the winter presence of ISW at the ocean surface. The observations demonstrate that, in some regions of coastal Antarctica, supercooled ISW drives a negative oceanic heat flux of -30 Wm-2 that persists for several months during winter, significantly affecting <span class="hlt">sea</span> <span class="hlt">ice</span> thickness. In other regions, particularly where the thinning of <span class="hlt">ice</span> shelves is believed to be greatest, platelet <span class="hlt">ice</span> is not observed. Our new data set includes the longest <span class="hlt">ice</span>-ocean record for Antarctica, which dates back to 1902 near the McMurdo <span class="hlt">Ice</span> Shelf. These historical data indicate that, over the past 100 years, any change in the volume of very cold surface outflow from this <span class="hlt">ice</span> shelf is less than the uncertainties in the measurements.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFMED33B..03E','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFMED33B..03E"><span>Indigenous Knowledge and <span class="hlt">Sea</span> <span class="hlt">Ice</span> Science: What Can We Learn from Indigenous <span class="hlt">Ice</span> Users?</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Eicken, H.</p> <p>2010-12-01</p> <p>Drawing on examples mostly from Iñupiaq and Yup’ik <span class="hlt">sea-ice</span> expertise in coastal Alaska, this contribution examines how local, indigenous knowledge (LIK) can inform and guide geophysical and biological <span class="hlt">sea-ice</span> research. Part of the relevance of LIK derives from its linkage to <span class="hlt">sea-ice</span> use and the services coastal communities derive from the <span class="hlt">ice</span> cover. As a result, indigenous experts keep track of a broad range of <span class="hlt">sea-ice</span> variables at a particular location. These observations are embedded into a broader worldview that speaks to both long-term variability or change and to the system of values associated with <span class="hlt">ice</span> use. The contribution examines eight different contexts in which LIK in study site selection and assessment of a sampling campaign in the context of inter annual variability, the identification of rare or inconspicuous phenomena or events, the contribution by indigenous experts to hazard assessment and emergency response, the record of past and present climate embedded in LIK, and the value of holistic <span class="hlt">sea-ice</span> knowledge in detecting subtle, intertwined patterns of environmental change. The relevance of local, indigenous <span class="hlt">sea-ice</span> expertise in helping advance adaptation and responses to climate change as well as its potential role in guiding research questions and hypotheses are also examined. The challenges that may have to be overcome in creating an interface for exchange between indigenous experts and seaice researchers are considered. Promising approaches to overcome these challenges include cross-cultural, interdisciplinary education, and the fostering of Communities of Practice.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A21Q..08F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A21Q..08F"><span>Response of Antarctic <span class="hlt">sea</span> surface temperature and <span class="hlt">sea</span> <span class="hlt">ice</span> to ozone depletion</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ferreira, D.; Gnanadesikan, A.; Kostov, Y.; Marshall, J.; Seviour, W.; Waugh, D.</p> <p>2017-12-01</p> <p>The influence of the Antarctic ozone hole extends all the way from the stratosphere through the troposphere down to the surface, with clear signatures on surface winds, and SST during summer. In this talk we discuss the impact of these changes on the ocean circulation and <span class="hlt">sea</span> <span class="hlt">ice</span> state. We are notably motivated by the observed cooling of the surface Southern Ocean and associated increase in Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> extent since the 1970s. These trends are not reproduced by CMIP5 climate models, and the underlying mechanism at work in nature and the models remain unexplained. Did the ozone hole contribute to the observed trends?Here, we review recent advances toward answering these issues using "abrupt ozone depletion" experiments. The ocean and <span class="hlt">sea</span> <span class="hlt">ice</span> response is rather complex, comprising two timescales: a fast ( 1-2y) cooling of the surface ocean and <span class="hlt">sea</span> <span class="hlt">ice</span> cover increase, followed by a slower warming trend, which, depending on models, flip the sign of the SST and <span class="hlt">sea</span> <span class="hlt">ice</span> responses on decadal timescale. Although the basic mechanism seems robust, comparison across climate models reveal large uncertainties in the timescales and amplitude of the response to the extent that even the sign of the ocean and <span class="hlt">sea</span> <span class="hlt">ice</span> response to ozone hole and recovery remains unconstrained. After briefly describing the dynamics and thermodynamics behind the two-timescale response, we will discuss the main sources of uncertainties in the modeled response, namely cloud effects and air-<span class="hlt">sea</span> heat exchanges, surface wind stress response and ocean eddy transports. Finally, we will consider the implications of our results on the ability of coupled climate models to reproduce observed Southern Ocean changes.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1811971I','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1811971I"><span>Relating Regional Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> and climate extremes over Europe</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ionita-Scholz, Monica; Grosfeld, Klaus; Lohmann, Gerrit; Scholz, Patrick</p> <p>2016-04-01</p> <p>The potential increase of temperature extremes under climate change is a major threat to society, as temperature extremes have a deep impact on environment, hydrology, agriculture, society and economy. Hence, the analysis of the mechanisms underlying their occurrence, including their relationships with the large-scale atmospheric circulation and <span class="hlt">sea</span> <span class="hlt">ice</span> concentration, is of major importance. At the same time, the decline in Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> cover during the last 30 years has been widely documented and it is clear that this change is having profound impacts at regional as well as planetary scale. As such, this study aims to investigate the relation between the autumn regional <span class="hlt">sea</span> <span class="hlt">ice</span> concentration variability and cold winters in Europe, as identified by the numbers of cold nights (TN10p), cold days (TX10p), <span class="hlt">ice</span> days (ID) and consecutive frost days (CFD). We analyze the relationship between Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> variation in autumn (September-October-November) averaged over eight different Arctic regions (Barents/Kara <span class="hlt">Seas</span>, Beaufort <span class="hlt">Sea</span>, Chukchi/Bering <span class="hlt">Seas</span>, Central Arctic, Greenland <span class="hlt">Sea</span>, Labrador <span class="hlt">Sea</span>/Baffin Bay, Laptev/East Siberian <span class="hlt">Seas</span> and Northern Hemisphere) and variations in atmospheric circulation and climate extreme indices in the following winter season over Europe using composite map analysis. Based on the composite map analysis it is shown that the response of the winter extreme temperatures over Europe is highly correlated/connected to changes in Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> variability. However, this signal is not symmetrical for the case of high and low <span class="hlt">sea</span> <span class="hlt">ice</span> years. Moreover, the response of temperatures extreme over Europe to <span class="hlt">sea</span> <span class="hlt">ice</span> variability over the different Arctic regions differs substantially. The regions which have the strongest impact on the extreme winter temperature over Europe are: Barents/Kara <span class="hlt">Seas</span>, Beaufort <span class="hlt">Sea</span>, Central Arctic and the Northern Hemisphere. For the years of high <span class="hlt">sea</span> <span class="hlt">ice</span> concentration in the Barents/Kara <span class="hlt">Seas</span> there is a reduction in the number</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/11809961','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/11809961"><span>Antarctic <span class="hlt">Sea</span> <span class="hlt">ice</span>--a habitat for extremophiles.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Thomas, D N; Dieckmann, G S</p> <p>2002-01-25</p> <p>The pack <span class="hlt">ice</span> of Earth's polar oceans appears to be frozen white desert, devoid of life. However, beneath the snow lies a unique habitat for a group of bacteria and microscopic plants and animals that are encased in an <span class="hlt">ice</span> matrix at low temperatures and light levels, with the only liquid being pockets of concentrated brines. Survival in these conditions requires a complex suite of physiological and metabolic adaptations, but <span class="hlt">sea-ice</span> organisms thrive in the <span class="hlt">ice</span>, and their prolific growth ensures they play a fundamental role in polar ecosystems. Apart from their ecological importance, the bacterial and algae species found in <span class="hlt">sea</span> <span class="hlt">ice</span> have become the focus for novel biotechnology, as well as being considered proxies for possible life forms on <span class="hlt">ice</span>-covered extraterrestrial bodies.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMPP44C..03D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMPP44C..03D"><span>Biogeochemical Cycling and <span class="hlt">Sea</span> <span class="hlt">Ice</span> Dynamics in the Bering <span class="hlt">Sea</span> across the Mid-Pleistocene Transition</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Detlef, H.; Sosdian, S. M.; Belt, S. T.; Smik, L.; Lear, C. H.; Hall, I. R.; Kender, S.; Leng, M. J.; Husum, K.; Cabedo-Sanz, P.</p> <p>2017-12-01</p> <p>Today the Bering <span class="hlt">Sea</span> is characterized by high primary productivity (PP) along the eastern shelf, maintained by CO2 and nutrient rich upwelled deep waters and nutrient release during spring <span class="hlt">sea</span> <span class="hlt">ice</span> melting. As such, low oxygen concentrations are pervasive in mid-depth waters. Changes in ventilation and export productivity in the past have been shown to impact this oxygen minimum zone. On glacial/interglacial (G/IG) timescales <span class="hlt">sea</span> <span class="hlt">ice</span> formation plays a pivotal role on intermediate water ventilation with evidence pointing to the formation of North Pacific Intermediate Water (NPIW) in the Bering <span class="hlt">Sea</span> during Pleistocene glacial intervals. In addition, <span class="hlt">sea</span> <span class="hlt">ice</span> plays a significant role in both long- and short-term climate change via associated feedback mechanisms. Thus, records of <span class="hlt">sea</span> <span class="hlt">ice</span> dynamics and biogeochemical cycling in the Bering <span class="hlt">Sea</span> are necessary to fully understand the interaction between PP, circulation patterns, and past G/IG climates with potential implications for the North Pacific carbon cycle. Here we use a multi-proxy approach to study <span class="hlt">sea</span> <span class="hlt">ice</span> dynamics and bottom water oxygenation, across three intervals prior to, across, and after the Mid-Pleistocene Transition (MPT, 1.2-0.7 Ma) from International Ocean Discovery Program Site U1343. The MPT, most likely driven by internal climate mechanisms, is ideal to study changes in <span class="hlt">sea</span> <span class="hlt">ice</span> dynamics and sedimentary redox conditions on orbital timescales and to investigate the implications for associated feedback mechanisms. The <span class="hlt">sea</span> <span class="hlt">ice</span> record, based on various biomarkers, including IP25, shows substantial increase in <span class="hlt">sea</span> <span class="hlt">ice</span> extent across the MPT and the occurrence of a late-glacial/deglacial <span class="hlt">sea</span> <span class="hlt">ice</span> spike, with consequences for glacial NPIW formation and land glacier retreat via the temperature-precipitation feedback. U/Mn of foraminiferal authigenic coatings, a novel proxy for bottom water oxygenation, also shows distinct variability on G/IG timescales across the MPT, most likely a result of PP and water mass</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/AD1013732','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/AD1013732"><span>Wave-<span class="hlt">Ice</span> and Air-<span class="hlt">Ice</span>-Ocean Interaction During the Chukchi <span class="hlt">Sea</span> <span class="hlt">Ice</span> Edge Advance</span></a></p> <p><a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>2015-09-30</p> <p>1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Wave -<span class="hlt">Ice</span> and Air-<span class="hlt">Ice</span>-Ocean Interaction During the...Chukchi <span class="hlt">Sea</span> in the late summer have potentially changed the impact of fall storms by creating wave fields in the vicinity of the advancing <span class="hlt">ice</span> edge. A...first) wave -<span class="hlt">ice</span> interaction field experiment that adequately documents the relationship of a growing pancake <span class="hlt">ice</span> cover with a time and space varying</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014ESD.....5..271L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014ESD.....5..271L"><span>Projecting Antarctic <span class="hlt">ice</span> discharge using response functions from <span class="hlt">Sea</span>RISE <span class="hlt">ice</span>-sheet models</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Levermann, A.; Winkelmann, R.; Nowicki, S.; Fastook, J. L.; Frieler, K.; Greve, R.; Hellmer, H. H.; Martin, M. A.; Meinshausen, M.; Mengel, M.; Payne, A. J.; Pollard, D.; Sato, T.; Timmermann, R.; Wang, W. L.; Bindschadler, R. A.</p> <p>2014-08-01</p> <p>The largest uncertainty in projections of future <span class="hlt">sea</span>-level change results from the potentially changing dynamical <span class="hlt">ice</span> discharge from Antarctica. Basal <span class="hlt">ice</span>-shelf melting induced by a warming ocean has been identified as a major cause for additional <span class="hlt">ice</span> flow across the grounding line. Here we attempt to estimate the uncertainty range of future <span class="hlt">ice</span> discharge from Antarctica by combining uncertainty in the climatic forcing, the oceanic response and the <span class="hlt">ice</span>-sheet model response. The uncertainty in the global mean temperature increase is obtained from historically constrained emulations with the MAGICC-6.0 (Model for the Assessment of Greenhouse gas Induced Climate Change) model. The oceanic forcing is derived from scaling of the subsurface with the atmospheric warming from 19 comprehensive climate models of the Coupled Model Intercomparison Project (CMIP-5) and two ocean models from the EU-project <span class="hlt">Ice</span>2<span class="hlt">Sea</span>. The dynamic <span class="hlt">ice</span>-sheet response is derived from linear response functions for basal <span class="hlt">ice</span>-shelf melting for four different Antarctic drainage regions using experiments from the <span class="hlt">Sea</span>-level Response to <span class="hlt">Ice</span> Sheet Evolution (<span class="hlt">Sea</span>RISE) intercomparison project with five different Antarctic <span class="hlt">ice</span>-sheet models. The resulting uncertainty range for the historic Antarctic contribution to global <span class="hlt">sea</span>-level rise from 1992 to 2011 agrees with the observed contribution for this period if we use the three <span class="hlt">ice</span>-sheet models with an explicit representation of <span class="hlt">ice</span>-shelf dynamics and account for the time-delayed warming of the oceanic subsurface compared to the surface air temperature. The median of the additional <span class="hlt">ice</span> loss for the 21st century is computed to 0.07 m (66% range: 0.02-0.14 m; 90% range: 0.0-0.23 m) of global <span class="hlt">sea</span>-level equivalent for the low-emission RCP-2.6 (Representative Concentration Pathway) scenario and 0.09 m (66% range: 0.04-0.21 m; 90% range: 0.01-0.37 m) for the strongest RCP-8.5. Assuming no time delay between the atmospheric warming and the oceanic subsurface, these</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1917155B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1917155B"><span><span class="hlt">Sea</span> <span class="hlt">ice</span> type dynamics in the Arctic based on Sentinel-1 Data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Babiker, Mohamed; Korosov, Anton; Park, Jeong-Won</p> <p>2017-04-01</p> <p><span class="hlt">Sea</span> <span class="hlt">ice</span> observation from satellites has been carried out for more than four decades and is one of the most important applications of EO data in operational monitoring as well as in climate change studies. Several sensors and retrieval methods have been developed and successfully utilized to measure <span class="hlt">sea</span> <span class="hlt">ice</span> area, concentration, drift, type, thickness, etc [e.g. Breivik et al., 2009]. Today operational <span class="hlt">sea</span> <span class="hlt">ice</span> monitoring and analysis is fully dependent on use of satellite data. However, new and improved satellite systems, such as multi-polarisation Synthetic Apperture Radar (SAR), require further studies to develop more advanced and automated <span class="hlt">sea</span> <span class="hlt">ice</span> monitoring methods. In addition, the unprecedented volume of data available from recently launched Sentinel missions provides both challenges and opportunities for studying <span class="hlt">sea</span> <span class="hlt">ice</span> dynamics. In this study we investigate <span class="hlt">sea</span> <span class="hlt">ice</span> type dynamics in the Fram strait based on Sentinel-1 A, B SAR data. Series of images for the winter season are classified into 4 <span class="hlt">ice</span> types (young <span class="hlt">ice</span>, first year <span class="hlt">ice</span>, multiyear <span class="hlt">ice</span> and leads) using the new algorithm developed by us for <span class="hlt">sea</span> <span class="hlt">ice</span> classification, which is based on segmentation, GLCM calculation, Haralick texture feature extraction, unsupervised and supervised classifications and Support Vector Machine (SVM) [Zakhvatkina et al., 2016; Korosov et al., 2016]. This algorithm is further improved by applying thermal and scalloping noise removal [Park et al. 2016]. <span class="hlt">Sea</span> <span class="hlt">ice</span> drift is retrieved from the same series of Sentinel-1 images using the newly developed algorithm based on combination of feature tracking and pattern matching [Mukenhuber et al., 2016]. Time series of these two products (<span class="hlt">sea</span> <span class="hlt">ice</span> type and <span class="hlt">sea</span> <span class="hlt">ice</span> drift) are combined in order to study <span class="hlt">sea</span> <span class="hlt">ice</span> deformation processes at small scales. Zones of <span class="hlt">sea</span> <span class="hlt">ice</span> convergence and divergence identified from <span class="hlt">sea</span> <span class="hlt">ice</span> drift are compared with ridges and leads identified from texture features. That allows more specific interpretation of SAR</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012EGUGA..1410179W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012EGUGA..1410179W"><span>Results from a lab study of melting <span class="hlt">sea</span> <span class="hlt">ice</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wiese, M.; Griewank, P.; Notz, D.</p> <p>2012-04-01</p> <p><span class="hlt">Sea-ice</span> melting is a complex process which is not fully understood yet. In order to study <span class="hlt">sea-ice</span> melt in detail we perform lab experiments in an approximately 2x0.7x1.2 m large tank in a cold room. We grow <span class="hlt">sea</span> <span class="hlt">ice</span> with different salinities at least 10 cm thick. Then we let the <span class="hlt">ice</span> melt at different air temperatures and oceanic heat fluxes. During the melt period, we measure the evolution of <span class="hlt">ice</span> thickness, internal temperature, salinity and surface temperature. We will present results from roughly five months of experiments. Topics will include the influence of bulk salinity on melt rates and the surface temperature. The effects of flushing on the salinity evolution and detailed thermal profiles will also be included. To investigate these processes we focus on the energy budget and the salinity evolution. These topics are linked since the thermodynamic properties of <span class="hlt">sea</span> <span class="hlt">ice</span> (heat capacity, heat conductivity and latent heat of fusion) are very sensitive to salinity variations. For example the heat capacity of <span class="hlt">sea</span> <span class="hlt">ice</span> increases greatly as the temperature approaches the melting point. This increase results in non-linear temperature profiles and enhances heat conduction into the <span class="hlt">ice</span>. The salinity evolution during the growth phase has been investigated and measured in multiple studies over the last decades. In contrast there are no detailed lab measurements of melting <span class="hlt">ice</span> available to quantify the effects of flushing melt water and ponding. This is partially due to the fact that the heterogeneity of melting <span class="hlt">sea</span> <span class="hlt">ice</span> makes it much more difficult to measure representative values.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..15.5747D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..15.5747D"><span><span class="hlt">ICE</span> stereocamera system - photogrammetric setup for retrieval and analysis of small scale <span class="hlt">sea</span> <span class="hlt">ice</span> topography</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Divine, Dmitry; Pedersen, Christina; Karlsen, Tor Ivan; Aas, Harald; Granskog, Mats; Renner, Angelika; Spreen, Gunnar; Gerland, Sebastian</p> <p>2013-04-01</p> <p>A new thin-<span class="hlt">ice</span> Arctic paradigm requires reconsideration of the set of parameterizations of mass and energy exchange within the ocean-<span class="hlt">sea-ice</span>-atmosphere system used in modern CGCMs. Such a reassessment would require a comprehensive collection of measurements made specifically on first-year pack <span class="hlt">ice</span> with a focus on summer melt season when the difference from typical conditions for the earlier multi-year Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> cover becomes most pronounced. Previous in situ studies have demonstrated a crucial importance of smaller (i.e. less than 10 m) scale surface topography features for the seasonal evolution of pack <span class="hlt">ice</span>. During 2011-2012 NPI developed a helicopter borne <span class="hlt">ICE</span> stereocamera system intended for mapping the <span class="hlt">sea</span> <span class="hlt">ice</span> surface topography and aerial photography. The hardware component of the system comprises two Canon 5D Mark II cameras, combined GPS/INS unit by "Novatel" and a laser altimeter mounted in a single enclosure outside the helicopter. The unit is controlled by a PXI chassis mounted inside the helicopter cabin. The <span class="hlt">ICE</span> stereocamera system was deployed for the first time during the 2012 summer field season. The hardware setup has proven to be highly reliable and was used in about 30 helicopter flights over Arctic <span class="hlt">sea-ice</span> during July-September. Being highly automated it required a minimal human supervision during in-flight operation. The deployment of the camera system was mostly done in combination with the EM-bird, which measures <span class="hlt">sea-ice</span> thickness, and this combination provides an integrated view of <span class="hlt">sea</span> <span class="hlt">ice</span> cover along the flight track. During the flight the cameras shot sequentially with a time interval of 1 second each to ensure sufficient overlap between subsequent images. Some 35000 images of <span class="hlt">sea</span> <span class="hlt">ice</span>/water surface captured per camera sums into 6 Tb of data collected during its first field season. The reconstruction of the digital elevation model of <span class="hlt">sea</span> <span class="hlt">ice</span> surface will be done using SOCET SET commercial software. Refraction at water/air interface can</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C21C0715L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C21C0715L"><span>Wind-driven <span class="hlt">Sea-Ice</span> Changes Intensify Subsurface Warm Water Intrusion into the West Antarctic Land <span class="hlt">Ice</span> Front</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Li, X.; Gille, S. T.; shang-Ping, X.; Xie, S. P.; Holland, D. M.; Holland, M. M.</p> <p>2016-12-01</p> <p>The climate change observed around Antarctica in recent decades is characterized by distinct zonally asymmetric patterns, with the strongest changes over West Antarctica. These changes are marked by strong land <span class="hlt">ice</span> melting and <span class="hlt">sea</span> <span class="hlt">ice</span> redistribution around West Antarctica. This is associated with temperature and circulation anomalies in the ocean and atmosphere around the same area. In this study, we comprehensively examine the coherency between these changes using a combination of observations and numerical simulations. Results show that the atmospheric circulation changes distinctly drive the changes in ocean circulation and <span class="hlt">sea</span> <span class="hlt">ice</span> distribution. In addition, the atmospheric circulation induced <span class="hlt">sea</span> <span class="hlt">ice</span> changes play an important role in lifting the subsurface ocean temperature and salinity around the West Antarctica. During recent decades, the Amundsen <span class="hlt">Sea</span> Low (ASL) has deepened, especially in austral autumn and winter. This deepened ASL has intensified the offshore wind near the coastal regions of the Ross <span class="hlt">Sea</span>. Driven by these atmospheric changes, more <span class="hlt">sea</span> <span class="hlt">ice</span> has formed near West Antarctica in winter. In contrast, more <span class="hlt">sea</span> <span class="hlt">ice</span> melts during the summer. This strengthened <span class="hlt">sea</span> <span class="hlt">ice</span> seasonality has been observed and successfully reproduced in the model simulation. The wind-driven <span class="hlt">sea</span> <span class="hlt">ice</span> changes causes a surface freshening over the Ross and Amundsen <span class="hlt">Seas</span>, with a subsurface salinity increase over the Ross <span class="hlt">Sea</span>. The additional fresh/salt water fluxes thus further change the vertical distribution of salinity and strengthen the stratification in the Ross and Amundsen <span class="hlt">Seas</span>. As a result of the above <span class="hlt">ice</span>-ocean process, the mixed-layer depth around the Ross and Amundsen <span class="hlt">Seas</span> shallows. By weakening the vertical heat transport near the surface layer, and inducing an upward movement of the circumpolar deep water (CDW), this process freshened and cooled the surface layer, while the salinity and temperature in the sub-surface ocean are increased, extending from 150 meters to >700</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018TCry...12.1013L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018TCry...12.1013L"><span>A network model for characterizing brine channels in <span class="hlt">sea</span> <span class="hlt">ice</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lieblappen, Ross M.; Kumar, Deip D.; Pauls, Scott D.; Obbard, Rachel W.</p> <p>2018-03-01</p> <p>The brine pore space in <span class="hlt">sea</span> <span class="hlt">ice</span> can form complex connected structures whose geometry is critical in the governance of important physical transport processes between the ocean, <span class="hlt">sea</span> <span class="hlt">ice</span>, and surface. Recent advances in three-dimensional imaging using X-ray micro-computed tomography have enabled the visualization and quantification of the brine network morphology and variability. Using imaging of first-year <span class="hlt">sea</span> <span class="hlt">ice</span> samples at in situ temperatures, we create a new mathematical network model to characterize the topology and connectivity of the brine channels. This model provides a statistical framework where we can characterize the pore networks via two parameters, depth and temperature, for use in dynamical <span class="hlt">sea</span> <span class="hlt">ice</span> models. Our approach advances the quantification of brine connectivity in <span class="hlt">sea</span> <span class="hlt">ice</span>, which can help investigations of bulk physical properties, such as fluid permeability, that are key in both global and regional <span class="hlt">sea</span> <span class="hlt">ice</span> models.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28835469','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28835469"><span><span class="hlt">Sea-ice</span> induced growth decline in Arctic shrubs.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Forchhammer, Mads</p> <p>2017-08-01</p> <p>Measures of increased tundra plant productivity have been associated with the accelerating retreat of the Arctic <span class="hlt">sea-ice</span>. Emerging studies document opposite effects, advocating for a more complex relationship between the shrinking <span class="hlt">sea-ice</span> and terrestrial plant productivity. I introduce an autoregressive plant growth model integrating effects of biological and climatic conditions for analysing individual ring-width growth time series. Using 128 specimens of Salix arctica , S. glauca and Betula nana sampled across Greenland to Svalbard, an overall negative effect of the retreating June <span class="hlt">sea-ice</span> extent was found on the annual growth. The negative effect of the retreating June <span class="hlt">sea-ice</span> was observed for younger individuals with large annual growth allocations and with little or no trade-off between previous and current year's growth. © 2017 The Author(s).</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li class="active"><span>17</span></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_17 --> <div id="page_18" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li class="active"><span>18</span></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="341"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADP023555','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADP023555"><span>High Resolution Simulations of Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span>, 1979-1993</span></a></p> <p><a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>2003-01-01</p> <p>William H. Lipscomb * PO[ARISSP To evaluate improvements in modelling Arctic <span class="hlt">sea</span> <span class="hlt">ice</span>, we compare results from two regional models at 1/120 horizontal...resolution. The first is a coupled <span class="hlt">ice</span>-ocean model of the Arctic Ocean, consisting of an ocean model (adapted from the Parallel Ocean Program, Los...Alamos National Laboratory [LANL]) and the "old" <span class="hlt">sea</span> <span class="hlt">ice</span> model . The second model uses the same grid but consists of an improved "new" <span class="hlt">sea</span> <span class="hlt">ice</span> model (LANL</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C21D1156T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C21D1156T"><span>Seasonal regional forecast of the minimum <span class="hlt">sea</span> <span class="hlt">ice</span> extent in the LapteV <span class="hlt">Sea</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tremblay, B.; Brunette, C.; Newton, R.</p> <p>2017-12-01</p> <p>Late winter anomaly of <span class="hlt">sea</span> <span class="hlt">ice</span> export from the peripheral <span class="hlt">seas</span> of the Atctic Ocean was found to be a useful predictor for the minimum <span class="hlt">sea</span> <span class="hlt">ice</span> extent (SIE) in the Arctic Ocean (Williams et al., 2017). In the following, we present a proof of concept for a regional seasonal forecast of the min SIE for the Laptev <span class="hlt">Sea</span> based on late winter coastal divergence quantified using a Lagrangian <span class="hlt">Ice</span> Tracking System (LITS) forced with satellite derived <span class="hlt">sea-ice</span> drifts from the Polar Pathfinder. Following Nikolaeva and Sesterikov (1970), we track an imaginary line just offshore of coastal polynyas in the Laptev <span class="hlt">Sea</span> from December of the previous year to May 1 of the following year using LITS. Results show that coastal divergence in the Laptev <span class="hlt">Sea</span> between February 1st and May 1st is best correlated (r = -0.61) with the following September minimum SIE in accord with previous results from Krumpen et al. (2013, for the Laptev <span class="hlt">Sea</span>) and Williams et a. (2017, for the pan-Arctic). This gives a maximum seasonal predictability of Laptev <span class="hlt">Sea</span> min SIE anomalies from observations of approximately 40%. Coastal <span class="hlt">ice</span> divergence leads to formation of thinner <span class="hlt">ice</span> that melts earlier in early summer, hence creating areas of open water that have a lower albedo and trigger an <span class="hlt">ice</span>-albedo feedback. In the Laptev <span class="hlt">Sea</span>, we find that anomalies of coastal divergence in late winter are amplified threefold to result in the September SIE. We also find a correlation coefficient r = 0.49 between February-March-April (FMA) anomalies of coastal divergence with the FMA averaged AO index. Interestingly, the correlation is stronger, r = 0.61, when comparing the FMA coastal divergence anomalies to the DJFMA averaged AO index. It is hypothesized that the AO index at the beginning of the winter (and the associated anomalous <span class="hlt">sea</span> <span class="hlt">ice</span> export) also contains information that impact the magnitude of coastal divergence opening later in the winter. Our approach differs from previous approaches (e.g. Krumpen et al and Williams et al</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015JGRC..120.7657L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015JGRC..120.7657L"><span>Optical properties of melting first-year Arctic <span class="hlt">sea</span> <span class="hlt">ice</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Light, Bonnie; Perovich, Donald K.; Webster, Melinda A.; Polashenski, Christopher; Dadic, Ruzica</p> <p>2015-11-01</p> <p>The albedo and transmittance of melting, first-year Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> were measured during two cruises of the Impacts of Climate on the Eco-Systems and Chemistry of the Arctic Pacific Environment (ICESCAPE) project during the summers of 2010 and 2011. Spectral measurements were made for both bare and ponded <span class="hlt">ice</span> types at a total of 19 <span class="hlt">ice</span> stations in the Chukchi and Beaufort <span class="hlt">Seas</span>. These data, along with irradiance profiles taken within boreholes, laboratory measurements of the optical properties of core samples, <span class="hlt">ice</span> physical property observations, and radiative transfer model simulations are employed to describe representative optical properties for melting first-year Arctic <span class="hlt">sea</span> <span class="hlt">ice</span>. Ponded <span class="hlt">ice</span> was found to transmit roughly 4.4 times more total energy into the ocean, relative to nearby bare <span class="hlt">ice</span>. The ubiquitous surface-scattering layer and drained layer present on bare, melting <span class="hlt">sea</span> <span class="hlt">ice</span> are responsible for its relatively high albedo and relatively low transmittance. Light transmittance through ponded <span class="hlt">ice</span> depends on the physical thickness of the <span class="hlt">ice</span> and the magnitude of the scattering coefficient in the <span class="hlt">ice</span> interior. Bare <span class="hlt">ice</span> reflects nearly three-quarters of the incident sunlight, enhancing its resiliency to absorption by solar insolation. In contrast, ponded <span class="hlt">ice</span> absorbs or transmits to the ocean more than three-quarters of the incident sunlight. Characterization of the heat balance of a summertime <span class="hlt">ice</span> cover is largely dictated by its pond coverage, and light transmittance through ponded <span class="hlt">ice</span> shows strong contrast between first-year and multiyear Arctic <span class="hlt">ice</span> covers.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20040040106','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20040040106"><span>The Effects of Snow Depth Forcing on Southern Ocean <span class="hlt">Sea</span> <span class="hlt">Ice</span> Simulations</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Powel, Dylan C.; Markus, Thorsten; Stoessel, Achim</p> <p>2003-01-01</p> <p>The spatial and temporal distribution of snow on <span class="hlt">sea</span> <span class="hlt">ice</span> is an important factor for <span class="hlt">sea</span> <span class="hlt">ice</span> and climate models. First, it acts as an efficient insulator between the ocean and the atmosphere, and second, snow is a source of fresh water for altering the already weak Southern Ocean stratification. For the Antarctic, where the <span class="hlt">ice</span> thickness is relatively thin, snow can impact the <span class="hlt">ice</span> thickness in two ways: a) As mentioned above snow on <span class="hlt">sea</span> <span class="hlt">ice</span> reduces the ocean-atmosphere heat flux and thus reduces freezing at the base of the <span class="hlt">ice</span> flows; b) a heavy snow load can suppress the <span class="hlt">ice</span> below <span class="hlt">sea</span> level which causes flooding and, with subsequent freezing, a thickening of the <span class="hlt">sea</span> <span class="hlt">ice</span> (snow-to-<span class="hlt">ice</span> conversion). In this paper, we compare different snow fall paramterizations (incl. the incorporation of satellite-derived snow depth) and study the effect on the <span class="hlt">sea</span> <span class="hlt">ice</span> using a <span class="hlt">sea</span> <span class="hlt">ice</span> model.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.1399D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.1399D"><span>Nudging the Arctic Ocean to quantify Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> feedbacks</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dekker, Evelien; Severijns, Camiel; Bintanja, Richard</p> <p>2017-04-01</p> <p>It is well-established that the Arctic is warming 2 to 3 time faster than rest of the planet. One of the great uncertainties in climate research is related to what extent <span class="hlt">sea</span> <span class="hlt">ice</span> feedbacks amplify this (seasonally varying) Arctic warming. Earlier studies have analyzed existing climate model output using correlations and energy budget considerations in order to quantify <span class="hlt">sea</span> <span class="hlt">ice</span> feedbacks through indirect methods. From these analyses it is regularly inferred that <span class="hlt">sea</span> <span class="hlt">ice</span> likely plays an important role, but details remain obscure. Here we will take a different and a more direct approach: we will keep the <span class="hlt">sea</span> <span class="hlt">ice</span> constant in a sensitivity simulation, using a state-of -the-art climate model (EC-Earth), applying a technique that has never been attempted before. This experimental technique involves nudging the temperature and salinity of the ocean surface (and possibly some layers below to maintain the vertical structure and mixing) to a predefined prescribed state. When strongly nudged to existing (seasonally-varying) <span class="hlt">sea</span> surface temperatures, ocean salinity and temperature, we force the <span class="hlt">sea</span> <span class="hlt">ice</span> to remain in regions/seasons where it is located in the prescribed state, despite the changing climate. Once we obtain fixed' <span class="hlt">sea</span> <span class="hlt">ice</span>, we will run a future scenario, for instance 2 x CO2 with and without prescribed <span class="hlt">sea</span> <span class="hlt">ice</span>, with the difference between these runs providing a measure as to what extent <span class="hlt">sea</span> <span class="hlt">ice</span> contributes to Arctic warming, including the seasonal and geographical imprint of the effects.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.C21B0343L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.C21B0343L"><span>Estimation of Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> Freeboard and Thickness Using CryoSat-2</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lee, S.; Im, J.; Kim, J. W.; Kim, M.; Shin, M.</p> <p>2014-12-01</p> <p>Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> is one of the significant components of the global climate system as it plays a significant role in driving global ocean circulation. <span class="hlt">Sea</span> <span class="hlt">ice</span> extent has constantly declined since 1980s. Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> thickness has also been diminishing along with the decreasing <span class="hlt">sea</span> <span class="hlt">ice</span> extent. Because extent and thickness, two main characteristics of <span class="hlt">sea</span> <span class="hlt">ice</span>, are important indicators of the polar response to on-going climate change. <span class="hlt">Sea</span> <span class="hlt">ice</span> thickness has been measured with numerous field techniques such as surface drilling and deploying buoys. These techniques provide sparse and discontinuous data in spatiotemporal domain. Spaceborne radar and laser altimeters can overcome these limitations and have been used to estimate <span class="hlt">sea</span> <span class="hlt">ice</span> thickness. <span class="hlt">Ice</span> Cloud and land Elevation Satellite (ICEsat), a laser altimeter provided data to detect polar area elevation change between 2003 and 2009. CryoSat-2 launched with Synthetic Aperture Radar (SAR)/Interferometric Radar Altimeter (SIRAL) in April 2010 can provide data to estimate time-series of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> thickness. In this study, Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> freeboard and thickness between 2011 and 2014 were estimated using CryoSat-2 SAR and SARIn mode data that have <span class="hlt">sea</span> <span class="hlt">ice</span> surface height relative to the reference ellipsoid WGS84. In order to estimate <span class="hlt">sea</span> <span class="hlt">ice</span> thickness, freeboard, i.e., elevation difference between the top of <span class="hlt">sea</span> <span class="hlt">ice</span> surface should be calculated. Freeboard can be estimated through detecting leads. We proposed a novel lead detection approach. CryoSat-2 profiles such as pulse peakiness, backscatter sigma-0, stack standard deviation, skewness and kurtosis were examined to distinguish leads from <span class="hlt">sea</span> <span class="hlt">ice</span>. Near-real time cloud-free MODIS images corresponding to CryoSat-2 data measured were used to visually identify leads. Rule-based machine learning approaches such as See5.0 and random forest were used to identify leads. The proposed lead detection approach better distinguished leads from <span class="hlt">sea</span> <span class="hlt">ice</span> than the existing approaches</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120013478','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120013478"><span>Variability and Anomalous Trends in the Global <span class="hlt">Sea</span> <span class="hlt">Ice</span> Cover</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Comiso, Josefino C.</p> <p>2012-01-01</p> <p>The advent of satellite data came fortuitously at a time when the global <span class="hlt">sea</span> <span class="hlt">ice</span> cover has been changing rapidly and new techniques are needed to accurately assess the true state and characteristics of the global <span class="hlt">sea</span> <span class="hlt">ice</span> cover. The extent of the <span class="hlt">sea</span> <span class="hlt">ice</span> in the Northern Hemisphere has been declining by about -4% per decade for the period 1979 to 2011 but for the period from 1996 to 2010, the rate of decline became even more negative at -8% per decade, indicating an acceleration in the decline. More intriguing is the drastically declining perennial <span class="hlt">sea</span> <span class="hlt">ice</span> area, which is the <span class="hlt">ice</span> that survives the summer melt and observed to be retreating at the rate of -14% per decade during the 1979 to 2012 period. Although a slight recovery occurred in the last three years from an abrupt decline in 2007, the perennial <span class="hlt">ice</span> extent was almost as low as in 2007 in 2011. The multiyear <span class="hlt">ice</span>, which is the thick component of the perennial <span class="hlt">ice</span> and regarded as the mainstay of the Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> cover is declining at an even higher rate of -19% per decade. The more rapid decline of the extent of this thicker <span class="hlt">ice</span> type means that the volume of the <span class="hlt">ice</span> is also declining making the survival of the Arctic <span class="hlt">ice</span> in summer highly questionable. The slight recovery in 2008, 2009 and 2010 for the perennial <span class="hlt">ice</span> in summer was likely associated with an apparent cycle in the time series with a period of about 8 years. Results of analysis of concurrent MODIS and AMSR-E data in summer also provide some evidence of more extensive summer melt and meltponding in 2007 and 2011 than in other years. Meanwhile, the Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> cover, as observed by the same set of satellite data, is showing an unexpected and counter intuitive increase of about 1 % per decade over the same period. Although a strong decline in <span class="hlt">ice</span> extent is apparent in the Bellingshausen/ Amundsen <span class="hlt">Seas</span> region, such decline is more than compensated by increases in the extent of the <span class="hlt">sea</span> <span class="hlt">ice</span> cover in the Ross <span class="hlt">Sea</span> region. The results of analysis of</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA617899','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA617899"><span>An Innovative Network to Improve <span class="hlt">Sea</span> <span class="hlt">Ice</span> Prediction in a Changing Arctic</span></a></p> <p><a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>2014-09-30</p> <p><span class="hlt">sea</span> <span class="hlt">ice</span> volume. The EXP ensemble is initialized with 1/5 of CNTL snow depths, thus resulting in a reduced snow cover and lower summer albedo ... <span class="hlt">Sea</span> <span class="hlt">Ice</span> - Albedo Feedback in <span class="hlt">Sea</span> <span class="hlt">Ice</span> Predictions is also about understanding <span class="hlt">sea</span> <span class="hlt">ice</span> predictability. REFERENCES Blanchard-Wrigglesworth, E., K...1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. An Innovative Network to Improve <span class="hlt">Sea</span> <span class="hlt">Ice</span> Prediction</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EaFut...2..315O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EaFut...2..315O"><span>Global warming releases microplastic legacy frozen in Arctic <span class="hlt">Sea</span> <span class="hlt">ice</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Obbard, Rachel W.; Sadri, Saeed; Wong, Ying Qi; Khitun, Alexandra A.; Baker, Ian; Thompson, Richard C.</p> <p>2014-06-01</p> <p>When <span class="hlt">sea</span> <span class="hlt">ice</span> forms it scavenges and concentrates particulates from the water column, which then become trapped until the <span class="hlt">ice</span> melts. In recent years, melting has led to record lows in Arctic <span class="hlt">Sea</span> <span class="hlt">ice</span> extent, the most recent in September 2012. Global climate models, such as that of Gregory et al. (2002), suggest that the decline in Arctic <span class="hlt">Sea</span> <span class="hlt">ice</span> volume (3.4% per decade) will actually exceed the decline in <span class="hlt">sea</span> <span class="hlt">ice</span> extent, something that Laxon et al. (2013) have shown supported by satellite data. The extent to which melting <span class="hlt">ice</span> could release anthropogenic particulates back to the open ocean has not yet been examined. Here we show that Arctic <span class="hlt">Sea</span> <span class="hlt">ice</span> from remote locations contains concentrations of microplastics at least two orders of magnitude greater than those that have been previously reported in highly contaminated surface waters, such as those of the Pacific Gyre. Our findings indicate that microplastics have accumulated far from population centers and that polar <span class="hlt">sea</span> <span class="hlt">ice</span> represents a major historic global sink of man-made particulates. The potential for substantial quantities of legacy microplastic contamination to be released to the ocean as the <span class="hlt">ice</span> melts therefore needs to be evaluated, as do the physical and toxicological effects of plastics on marine life.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..16.5885L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..16.5885L"><span>Estimation of Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> Freeboard and Thickness Using CryoSat-2</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lee, Sanggyun; Im, Jungho; yoon, Hyeonjin; Shin, Minso; Kim, Miae</p> <p>2014-05-01</p> <p>Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> is one of the significant components of the global climate system as it plays a significant role in driving global ocean circulation, provides a continuous insulating layer at air-<span class="hlt">sea</span> interface, and reflects a large portion of the incoming solar radiation in Polar Regions. <span class="hlt">Sea</span> <span class="hlt">ice</span> extent has constantly declined since 1980s. Its area was the lowest ever recorded on 16 September 2012 since the satellite record began in 1979. Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> thickness has also been diminishing along with the decreasing <span class="hlt">sea</span> <span class="hlt">ice</span> extent. Because extent and thickness, two main characteristics of <span class="hlt">sea</span> <span class="hlt">ice</span>, are important indicators of the polar response to on-going climate change, there has been a great effort to quantify them using various approaches. <span class="hlt">Sea</span> <span class="hlt">ice</span> thickness has been measured with numerous field techniques such as surface drilling and deploying buoys. These techniques provide sparse and discontinuous data in spatiotemporal domain. Spaceborne radar and laser altimeters can overcome these limitations and have been used to estimate <span class="hlt">sea</span> <span class="hlt">ice</span> thickness. <span class="hlt">Ice</span> Cloud and land Elevation Satellite (ICEsat), a laser altimeter from National Aeronautics and Space Administration (NASA), provided data to detect polar area elevation change between 2003 and 2009. CryoSat-2 launched with Synthetic Aperture Radar (SAR)/Interferometric Radar Altimeter (SIRAL) on April 2010 can provide data to estimate time-series of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> thickness. In this study, Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> freeboard and thickness in 2012 and 2013 were estimated using CryoSat-2 SAR mode data that has <span class="hlt">sea</span> <span class="hlt">ice</span> surface height relative to the reference ellipsoid WGS84. In order to estimate <span class="hlt">sea</span> <span class="hlt">ice</span> thickness, freeboard height, elevation difference between the top of <span class="hlt">sea</span> <span class="hlt">ice</span> surface and leads should be calculated. CryoSat-2 profiles such as pulse peakiness, backscatter sigma-0, number of echoes, and significant wave height were examined to distinguish leads from <span class="hlt">sea</span> <span class="hlt">ice</span>. Several near-real time cloud-free MODIS images as CryoSat-2</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19950047903&hterms=low+emissivity&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dlow%2Bemissivity','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19950047903&hterms=low+emissivity&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dlow%2Bemissivity"><span>Low-frequency passive-microwave observations of <span class="hlt">sea</span> <span class="hlt">ice</span> in the Weddell <span class="hlt">Sea</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Menashi, James D.; St. Germain, Karen M.; Swift, Calvin T.; Comiso, Josefino C.; Lohanick, Alan W.</p> <p>1993-01-01</p> <p>The microwave emission properties of first-year <span class="hlt">sea</span> <span class="hlt">ice</span> were investigated from the R/V Polarstern during the Antarctic Winter Weddell Gyre Project in 1989. Radiometer measurements were made at 611 MHz and 10 GHz and were accompanied by video and visual observations. Using the theory of radiometric emission from a layered medium, a method for deriving <span class="hlt">sea</span> <span class="hlt">ice</span> thickness from radiometer data is developed and tested. The model is based on an incoherent reflection process and predicts that the emissivity of saline <span class="hlt">ice</span> increases monotonically with increasing <span class="hlt">ice</span> thickness until saturation occurs.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1919277B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1919277B"><span>Quantifying model uncertainty in seasonal Arctic <span class="hlt">sea-ice</span> forecasts</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Blanchard-Wrigglesworth, Edward; Barthélemy, Antoine; Chevallier, Matthieu; Cullather, Richard; Fučkar, Neven; Massonnet, François; Posey, Pamela; Wang, Wanqiu; Zhang, Jinlun; Ardilouze, Constantin; Bitz, Cecilia; Vernieres, Guillaume; Wallcraft, Alan; Wang, Muyin</p> <p>2017-04-01</p> <p>Dynamical model forecasts in the <span class="hlt">Sea</span> <span class="hlt">Ice</span> Outlook (SIO) of September Arctic <span class="hlt">sea-ice</span> extent over the last decade have shown lower skill than that found in both idealized model experiments and hindcasts of previous decades. Additionally, it is unclear how different model physics, initial conditions or post-processing techniques contribute to SIO forecast uncertainty. In this work, we have produced a seasonal forecast of 2015 Arctic summer <span class="hlt">sea</span> <span class="hlt">ice</span> using SIO dynamical models initialized with identical <span class="hlt">sea-ice</span> thickness in the central Arctic. Our goals are to calculate the relative contribution of model uncertainty and irreducible error growth to forecast uncertainty and assess the importance of post-processing, and to contrast pan-Arctic forecast uncertainty with regional forecast uncertainty. We find that prior to forecast post-processing, model uncertainty is the main contributor to forecast uncertainty, whereas after forecast post-processing forecast uncertainty is reduced overall, model uncertainty is reduced by an order of magnitude, and irreducible error growth becomes the main contributor to forecast uncertainty. While all models generally agree in their post-processed forecasts of September <span class="hlt">sea-ice</span> volume and extent, this is not the case for <span class="hlt">sea-ice</span> concentration. Additionally, forecast uncertainty of <span class="hlt">sea-ice</span> thickness grows at a much higher rate along Arctic coastlines relative to the central Arctic ocean. Potential ways of offering spatial forecast information based on the timescale over which the forecast signal beats the noise are also explored.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011EOSTr..92....1W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011EOSTr..92....1W"><span>Tradition and Technology: <span class="hlt">Sea</span> <span class="hlt">Ice</span> Science on Inuit Sleds</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wilkinson, Jeremy P.; Hanson, Susanne; Hughes, Nick E.; James, Alistair; Jones, Bryn; MacKinnon, Rory; Rysgaard, Søren; Toudal, Leif</p> <p>2011-01-01</p> <p>The Arctic is home to a circumpolar community of native people whose culture and traditions have enabled them to thrive in what most would perceive as a totally inhospitable and untenable environment. In many ways, <span class="hlt">sea</span> <span class="hlt">ice</span> can be viewed as the glue that binds these northern communities together; it is utilized in all aspects of their daily life. <span class="hlt">Sea</span> <span class="hlt">ice</span> acts as highways of the north; indeed, one can travel on these highways with dogsleds and snowmobiles. These travels over the frozen ocean occur at all periods of the <span class="hlt">sea</span> <span class="hlt">ice</span> cycle and over different <span class="hlt">ice</span> types and ages. Excursions may be hunting trips to remote regions or social visits to nearby villages. Furthermore, hunting on the <span class="hlt">sea</span> <span class="hlt">ice</span> contributes to the health, culture, and commercial income of a community.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5856068','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5856068"><span>Scaling Properties of Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> Deformation in a High‐Resolution Viscous‐Plastic <span class="hlt">Sea</span> <span class="hlt">Ice</span> Model and in Satellite Observations</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Losch, Martin; Menemenlis, Dimitris</p> <p>2018-01-01</p> <p>Abstract <span class="hlt">Sea</span> <span class="hlt">ice</span> models with the traditional viscous‐plastic (VP) rheology and very small horizontal grid spacing can resolve leads and deformation rates localized along Linear Kinematic Features (LKF). In a 1 km pan‐Arctic <span class="hlt">sea</span> ice‐ocean simulation, the small‐scale <span class="hlt">sea</span> <span class="hlt">ice</span> deformations are evaluated with a scaling analysis in relation to satellite observations of the Envisat Geophysical Processor System (EGPS) in the Central Arctic. A new coupled scaling analysis for data on Eulerian grids is used to determine the spatial and temporal scaling and the coupling between temporal and spatial scales. The spatial scaling of the modeled <span class="hlt">sea</span> <span class="hlt">ice</span> deformation implies multifractality. It is also coupled to temporal scales and varies realistically by region and season. The agreement of the spatial scaling with satellite observations challenges previous results with VP models at coarser resolution, which did not reproduce the observed scaling. The temporal scaling analysis shows that the VP model, as configured in this 1 km simulation, does not fully resolve the intermittency of <span class="hlt">sea</span> <span class="hlt">ice</span> deformation that is observed in satellite data. PMID:29576996</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C22A..02N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C22A..02N"><span>Snow depth evolution on <span class="hlt">sea</span> <span class="hlt">ice</span> from Snow Buoy measurement</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Nicolaus, M.; Arndt, S.; Hendricks, S.; Hoppmann, M.; Katlein, C.; König-Langlo, G.; Nicolaus, A.; Rossmann, H. L.; Schiller, M.; Schwegmann, S.; Langevin, D.</p> <p>2016-12-01</p> <p>Snow cover is an Essential Climate Variable. On <span class="hlt">sea</span> <span class="hlt">ice</span>, snow dominates the energy and momentum exchanges across the atmosphere-<span class="hlt">ice</span>-ocean interfaces, and actively contributes to <span class="hlt">sea</span> <span class="hlt">ice</span> mass balance. Yet, snow depth on <span class="hlt">sea</span> <span class="hlt">ice</span> is one of the least known and most difficult to observe parameters of the Arctic and Antarctic; mainly due to its exceptionally high spatial and temporal variability. In this study; we present a unique time series dataset of snow depth and air temperature evolution on Arctic and Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> recorded by autonomous instruments. Snow Buoys record snow depth with four independent ultrasonic sensors, increasing the reliability of the measurements and allowing for additional analyses. Auxiliary measurements include surface and air temperature, barometric pressure and GPS position. 39 deployments of such Snow Buoys were achieved over the last three years either on drifting pack <span class="hlt">ice</span>, on landfast <span class="hlt">sea</span> <span class="hlt">ice</span> or on an <span class="hlt">ice</span> shelf. Here we highlight results from two pairs of Snow Buoys installed on drifting pack <span class="hlt">ice</span> in the Weddell <span class="hlt">Sea</span>. The data reveals large regional differences in the annual cycle of snow depth. Almost no reduction in snow depth (snow melt) was observed in the inner and southern part of the Weddell <span class="hlt">Sea</span>, allowing a net snow accumulation of 0.2 to 0.9 m per year. In contrast, summer snow melt close to the <span class="hlt">ice</span> edge resulted in a decrease of about 0.5 m during the summer 2015/16. Another array of eight Snow Buoys was installed on central Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> in September 2015. Their air temperature record revealed exceptionally high air temperatures in the subsequent winter, even exceeding the melting point but with almost no impact on snow depth at that time. Future applications of Snow Buoys on Arctic and Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> will allow additional inter-annual studies of snow depth and snow processes, e.g. to support the development of snow depth data products from airborne and satellite data or though assimilation in numerical models.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C43A0738Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C43A0738Z"><span>High resolution <span class="hlt">sea</span> <span class="hlt">ice</span> modeling for the region of Baffin Bay and the Labrador <span class="hlt">Sea</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zakharov, I.; Prasad, S.; McGuire, P.</p> <p>2016-12-01</p> <p>A multi-category numerical <span class="hlt">sea</span> <span class="hlt">ice</span> model (CICE) with a data assimilation module was implemented to derive <span class="hlt">sea</span> <span class="hlt">ice</span> parameters in the region of Baffin Bay and the Labrador <span class="hlt">Sea</span> with resolution higher than 10 km. The model derived <span class="hlt">ice</span> parameters include concentration, ridge keel measurement, thickness and freeboard. The module for assimilation of <span class="hlt">ice</span> concentration uses data from the Advance Microwave Scanning Radiometer (AMSR-E) and OSI SAF data. The <span class="hlt">sea</span> surface temperature (SST) data from AMSRE-AVHRR and Operational SST and <span class="hlt">Sea</span> <span class="hlt">Ice</span> Analysis (OSTIA) system were used to correct the SST computed by a mixed layer slab ocean model that is used to determine the growth and melt of <span class="hlt">sea</span> <span class="hlt">ice</span>. The <span class="hlt">ice</span> thickness parameter from the model was compared with the measurements from Soil Moisture Ocean Salinity - Microwave Imaging Radiometer using Aperture Synthesis (SMOS-MIRAS). The freeboard measures where compared with the Cryosat-2 measurements. A spatial root mean square error computed for freeboard measures was found to be within the uncertainty limits of the observation. The model was also used to estimate the correlation parameter between the ridge and the ridge keel measurements in the region of Makkovik Bank. Also, the level <span class="hlt">ice</span> draft estimated from the model was in good agreement with the <span class="hlt">ice</span> draft derived from the upward looking sonar (ULS) instrument deployed in the Makkovik bank. The model corrected with <span class="hlt">ice</span> concentration and SST from remote sensing data demonstrated significant improvements in accuracy of the estimated <span class="hlt">ice</span> parameters. The model can be used for operational forecast and climate research.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-GSFC_20171208_Archive_e000613.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-GSFC_20171208_Archive_e000613.html"><span>Approaching the 2015 Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> Minimum</span></a></p> <p><a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a></p> <p></p> <p>2017-12-08</p> <p>As the sun sets over the Arctic, the end of this year’s melt season is quickly approaching and the <span class="hlt">sea</span> <span class="hlt">ice</span> cover has already shrunk to the fourth lowest in the satellite record. With possibly some days of melting left, the <span class="hlt">sea</span> <span class="hlt">ice</span> extent could still drop to the second or third lowest on record. Arctic <span class="hlt">sea</span> <span class="hlt">ice</span>, which regulates the planet’s temperature by bouncing solar energy back to space, has been on a steep decline for the last two decades. This animation shows the evolution of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> in 2015, from its annual maximum wintertime extent, reached on February 25, to September 6. Credit: NASA Scientific Visualization Studio DOWNLOAD THIS VIDEO HERE: svs.gsfc.nasa.gov/cgi-bin/details.cgi?aid=11999 NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.C42B..02D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.C42B..02D"><span>Will <span class="hlt">sea</span> <span class="hlt">ice</span> thickness initialisation improve Arctic seasonal-to-interannual forecast skill?</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Day, J. J.; Hawkins, E.; Tietsche, S.</p> <p>2014-12-01</p> <p>A number of recent studies have suggested that Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> thickness is an important predictor of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> extent. However, coupled forecast systems do not currently use <span class="hlt">sea</span> <span class="hlt">ice</span> thickness observations in their initialization and are therefore missing a potentially important source of additional skill. A set of ensemble potential predictability experiments, with a global climate model, initialized with and without knowledge of the <span class="hlt">sea</span> <span class="hlt">ice</span> thickness initial state, have been run to investigate this. These experiments show that accurate knowledge of the <span class="hlt">sea</span> <span class="hlt">ice</span> thickness field is crucially important for <span class="hlt">sea</span> <span class="hlt">ice</span> concentration and extent forecasts up to eight months ahead. Perturbing <span class="hlt">sea</span> <span class="hlt">ice</span> thickness also has a significant impact on the forecast error in the 2m temperature and surface pressure fields a few months ahead. These results show that advancing capabilities to observe and assimilate <span class="hlt">sea</span> <span class="hlt">ice</span> thickness into coupled forecast systems could significantly increase skill.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.gpo.gov/fdsys/pkg/FR-2011-12-22/pdf/2011-32809.pdf','FEDREG'); return false;" href="https://www.gpo.gov/fdsys/pkg/FR-2011-12-22/pdf/2011-32809.pdf"><span>76 FR 79764 - Use of Foreign-Flag Anchor Handling Vessels in the Beaufort <span class="hlt">Sea</span> or Chukchi <span class="hlt">Sea</span> <span class="hlt">Adjacent</span> to Alaska</span></a></p> <p><a target="_blank" href="http://www.gpo.gov/fdsys/browse/collection.action?collectionCode=FR">Federal Register 2010, 2011, 2012, 2013, 2014</a></p> <p></p> <p>2011-12-22</p> <p>... DEPARTMENT OF TRANSPORTATION Maritime Administration [Docket Number MARAD-2011-0163] Use of Foreign-Flag Anchor Handling Vessels in the Beaufort <span class="hlt">Sea</span> or Chukchi <span class="hlt">Sea</span> <span class="hlt">Adjacent</span> to Alaska AGENCY... 9199622) would operate in the Beaufort <span class="hlt">Sea</span> or Chukchi <span class="hlt">Sea</span> <span class="hlt">adjacent</span> to Alaska, under certain conditions...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.gpo.gov/fdsys/pkg/FR-2010-03-22/pdf/2010-6144.pdf','FEDREG'); return false;" href="https://www.gpo.gov/fdsys/pkg/FR-2010-03-22/pdf/2010-6144.pdf"><span>75 FR 13654 - Use of Foreign-Flag Anchor Handling Vessels in the Beaufort <span class="hlt">Sea</span> or Chukchi <span class="hlt">Sea</span> <span class="hlt">Adjacent</span> to Alaska</span></a></p> <p><a target="_blank" href="http://www.gpo.gov/fdsys/browse/collection.action?collectionCode=FR">Federal Register 2010, 2011, 2012, 2013, 2014</a></p> <p></p> <p>2010-03-22</p> <p>... DEPARTMENT OF TRANSPORTATION Maritime Administration [Docket Number MARAD 2010-0031] Use of Foreign-Flag Anchor Handling Vessels in the Beaufort <span class="hlt">Sea</span> or Chukchi <span class="hlt">Sea</span> <span class="hlt">Adjacent</span> to Alaska AGENCY... 9199622) would operate in the Beaufort <span class="hlt">Sea</span> or Chukchi <span class="hlt">Sea</span> <span class="hlt">adjacent</span> to Alaska, under certain conditions...</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li class="active"><span>18</span></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_18 --> <div id="page_19" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li class="active"><span>19</span></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="361"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27812435','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27812435"><span>Loitering of the retreating <span class="hlt">sea</span> <span class="hlt">ice</span> edge in the Arctic <span class="hlt">Seas</span>.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Steele, Michael; Ermold, Wendy</p> <p>2015-12-01</p> <p>Each year, the arctic <span class="hlt">sea</span> <span class="hlt">ice</span> edge retreats from its winter maximum extent through the Seasonal <span class="hlt">Ice</span> Zone (SIZ) to its summer minimum extent. On some days, this retreat happens at a rapid pace, while on other days, parts of the pan-arctic <span class="hlt">ice</span> edge hardly move for periods of days up to 1.5 weeks. We term this stationary behavior "<span class="hlt">ice</span> edge loitering," and identify areas that are more prone to loitering than others. Generally, about 20-25% of the SIZ area experiences loitering, most often only one time at any one location during the retreat season, but sometimes two or more times. The main mechanism controlling loitering is an interaction between surface winds and warm <span class="hlt">sea</span> surface temperatures in areas from which the <span class="hlt">ice</span> has already retreated. When retreat happens early enough to allow atmospheric warming of this open water, winds that force <span class="hlt">ice</span> floes into this water cause melting. Thus, while individual <span class="hlt">ice</span> floes are moving, the <span class="hlt">ice</span> edge as a whole appears to loiter. The time scale of loitering is then naturally tied to the synoptic time scale of wind forcing. Perhaps surprisingly, the area of loitering in the arctic <span class="hlt">seas</span> has not changed over the past 25 years, even as the SIZ area has grown. This is because rapid <span class="hlt">ice</span> retreat happens most commonly late in the summer, when atmospheric warming of open water is weak. We speculate that loitering may have profound effects on both physical and biological conditions at the <span class="hlt">ice</span> edge during the retreat season.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20170008477','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20170008477"><span>Improving Our Understanding of Antarctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> with NASA's Operation <span class="hlt">Ice</span>Bridge and the Upcoming ICESat-2 Mission</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Petty, Alek A.; Markus, Thorsten; Kurtz, Nathan T.</p> <p>2017-01-01</p> <p>Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> is a crucial component of the global climate system. Rapid <span class="hlt">sea</span> <span class="hlt">ice</span> production regimes around Antarctica feed the lower branch of the Southern Ocean overturning circulation through intense brine rejection and the formation of Antarctic Bottom Water (e.g., Orsi et al. 1999; Jacobs 2004), while the northward transport and subsequent melt of Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> drives the upper branch of the overturning circulation through freshwater input (Abernathy et al. 2016). Wind-driven trends in Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> (Holland Kwok 2012) have likely increased the transport of freshwater away from the Antarctic coastline, significantly altering the salinity distribution of the Southern Ocean (Haumann et al. 2016). Conversely, weaker <span class="hlt">sea</span> <span class="hlt">ice</span> production and the lack of shelf water formation over the Amundsen and Bellingshausen shelf <span class="hlt">seas</span> promote intrusion of warm Circumpolar Deep Water onto the continental shelf and the ocean-driven melting of several <span class="hlt">ice</span> shelves fringing the West Antarctic <span class="hlt">Ice</span> Sheet (e.g., Jacobs et al. 2011; Pritchard et al. 2012; Dutrieux et al. 2014). <span class="hlt">Sea</span> <span class="hlt">ice</span> conditions around Antarctica are also increasingly considered an important factor impacting local atmospheric conditions and the surface melting of Antarctic <span class="hlt">ice</span> shelves (e.g., Scambos et al. 2017). <span class="hlt">Sea</span> <span class="hlt">ice</span> formation around Antarctica is responsive to the strong regional variability in atmospheric forcing present around Antarctica, driving this bimodal variability in the behavior and properties of the underlying shelf <span class="hlt">seas</span> (e.g., Petty et al. 2012; Petty et al. 2014).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://polar.ncep.noaa.gov/seaice/Analyses.shtml','SCIGOVWS'); return false;" href="http://polar.ncep.noaa.gov/seaice/Analyses.shtml"><span>MMAB <span class="hlt">Sea</span> <span class="hlt">Ice</span> Analysis Page</span></a></p> <p><a target="_blank" href="http://www.science.gov/aboutsearch.html">Science.gov Websites</a></p> <p></p> <p></p> <p>. Consequently we produce <em>two</em> sorts of field. One is suitable for use by models, the global field. And the other <em>color</em> bar gif of the Alaska Region map Previous Alaska Region Maps NCEP MMAB Interactive <span class="hlt">Sea</span> <span class="hlt">Ice</span> Image Generation Animation Alaska Region <span class="hlt">Sea</span> of Okhotsk and <span class="hlt">Sea</span> of Japan - current figure concentration <em>color</em> bar</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JGRC..121..267B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JGRC..121..267B"><span>Physical processes contributing to an <span class="hlt">ice</span> free Beaufort <span class="hlt">Sea</span> during September 2012</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Babb, D. G.; Galley, R. J.; Barber, D. G.; Rysgaard, S.</p> <p>2016-01-01</p> <p>During the record September 2012 <span class="hlt">sea</span> <span class="hlt">ice</span> minimum, the Beaufort <span class="hlt">Sea</span> became <span class="hlt">ice</span> free for the first time during the observational record. Increased dynamic activity during late winter enabled increased open water and seasonal <span class="hlt">ice</span> coverage that contributed to negative <span class="hlt">sea</span> <span class="hlt">ice</span> anomalies and positive solar absorption anomalies which drove rapid bottom melt and <span class="hlt">sea</span> <span class="hlt">ice</span> loss. As had happened in the Beaufort <span class="hlt">Sea</span> during previous years of exceptionally low September <span class="hlt">sea</span> <span class="hlt">ice</span> extent, anomalous solar absorption developed during May, increased during June, peaked during July, and persisted into October. However in situ observations from a single floe reveal less than 78% of the energy required for bottom melt during 2012 was available from solar absorption. We show that the 2012 <span class="hlt">sea</span> <span class="hlt">ice</span> minimum in the Beaufort was the result of anomalously large solar absorption that was compounded by an arctic cyclone and other sources of heat such as solar transmission, oceanic upwelling, and riverine inputs, but was ultimately made possible through years of preconditioning toward a younger, thinner <span class="hlt">ice</span> pack. Significant negative trends in <span class="hlt">sea</span> <span class="hlt">ice</span> concentration between 1979 and 2012 from June to October, coupled with a tendency toward earlier <span class="hlt">sea</span> <span class="hlt">ice</span> reductions have fostered a significant trend of +12.9 MJ m-2 yr-1 in cumulative solar absorption, sufficient to melt an additional 4.3 cm m-2 yr-1. Overall through preconditioning toward a younger, thinner <span class="hlt">ice</span> pack the Beaufort <span class="hlt">Sea</span> has become increasingly susceptible to increased <span class="hlt">sea</span> <span class="hlt">ice</span> loss that may render it <span class="hlt">ice</span> free more frequently in coming years.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C43B0748B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C43B0748B"><span>Physical Processes contributing to an <span class="hlt">ice</span> free Beaufort <span class="hlt">Sea</span> during September 2012</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Babb, D.; Galley, R.; Barber, D. G.; Rysgaard, S.</p> <p>2016-12-01</p> <p>During the record September 2012 <span class="hlt">sea</span> <span class="hlt">ice</span> minimum the Beaufort <span class="hlt">Sea</span> became <span class="hlt">ice</span> free for the first time during the observational record. Increased dynamic activity during late winter enabled increased open water and seasonal <span class="hlt">ice</span> coverage that contributed to negative <span class="hlt">sea</span> <span class="hlt">ice</span> anomalies and positive solar absorption anomalies which drove rapid bottom melt and <span class="hlt">sea</span> <span class="hlt">ice</span> loss. As had happened in the Beaufort <span class="hlt">Sea</span> during previous years of exceptionally low September <span class="hlt">sea</span> <span class="hlt">ice</span> extent, anomalous solar absorption developed during May, increased during June, peaked during July and persisted into October. However in situ observations from a single floe reveal less than 78% of the energy required for bottom melt during 2012 was available from solar absorption. We show that the 2012 <span class="hlt">sea</span> <span class="hlt">ice</span> minimum in the Beaufort was the result of anomalously large solar absorption that was compounded by an arctic cyclone and other sources of heat such as solar transmission, oceanic upwelling and riverine inputs, but was ultimately made possible through years of preconditioning towards a younger, thinner <span class="hlt">ice</span> pack. Significant negative trends in <span class="hlt">sea</span> <span class="hlt">ice</span> concentration between 1979 and 2012 from June to October, coupled with a tendency towards earlier <span class="hlt">sea</span> <span class="hlt">ice</span> reductions have fostered a significant trend of +12.9 MJ m-2 year-1 in cumulative solar absorption, sufficient to melt an additional 4.3 cm m-2 year-1. Overall through preconditioning towards a younger, thinner <span class="hlt">ice</span> pack the Beaufort <span class="hlt">Sea</span> has become increasingly susceptible to increased <span class="hlt">sea</span> <span class="hlt">ice</span> loss that may render it <span class="hlt">ice</span> free more frequently in coming years.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.C21D0685B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.C21D0685B"><span>Influence of the <span class="hlt">sea-ice</span> edge on the Arctic nearshore environment</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Barnhart, K. R.; Overeem, I.; Anderson, R. S.</p> <p>2013-12-01</p> <p>Coasts form the dynamic interface of the terrestrial and oceanic systems. In the Arctic, and in much of the world, the coast is a zone of relatively high population, infrastructure, biodiversity, and ecosystem services. A significant difference between Arctic and temperate coasts is the presence of <span class="hlt">sea</span> <span class="hlt">ice</span>. <span class="hlt">Sea</span> <span class="hlt">ice</span> influences Arctic coasts in two main ways: (1) the length of the <span class="hlt">sea</span> <span class="hlt">ice</span>-free season controls the length of time over which nearshore water can interact with the land, and (2) the <span class="hlt">sea</span> <span class="hlt">ice</span> edge controls the fetch over which storm winds can blow over open water, resulting in changes in nearshore water level and wave field. The resulting nearshore hydrodynamic environment impacts all aspects of the coastal system. Here, we use satellite records of <span class="hlt">sea</span> <span class="hlt">ice</span> along with a simple model for wind-driven storm surge and waves to document how changes in the length and character of the <span class="hlt">sea</span> <span class="hlt">ice</span>-free season have impacted the nearshore hydrodynamic environment. For our <span class="hlt">sea</span> <span class="hlt">ice</span> analysis we primarily use the Bootstrap <span class="hlt">Sea</span> <span class="hlt">Ice</span> Concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS. We make whole-Arctic maps of <span class="hlt">sea</span> <span class="hlt">ice</span> change in the coastal zone. In addition to evaluating changes in length of the <span class="hlt">sea</span> <span class="hlt">ice</span>-free season at the coast, we look at changes segmented by azimuth. This allows us to consider changes in the <span class="hlt">sea</span> <span class="hlt">ice</span> in the context of the wind field. For our storm surge and wave field analysis we focus on the Beaufort <span class="hlt">Sea</span> region. This region has experienced some of the greatest changes in both <span class="hlt">sea</span> <span class="hlt">ice</span> cover and coastal erosion rates in the Arctic and is anticipated to experience significant change in the future. In addition, the NOAA ESRL GMD has observed the wind field at Barrow since extends to 1977. In our past work on the rapid and accelerating coastal erosion, we have shown that one may model storm surge with a 2D numerical bathystrophic model, and that waves are well represented by the Shore Protection Manual methods for shallow-water fetch-limited waves. We use</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C21C0714O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C21C0714O"><span>Global mapping of <span class="hlt">sea-ice</span> production from the satellite microwaves</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ohshima, K. I.; Nihashi, S.; Iwamoto, K.; Tamaru, N.; Nakata, K.; Tamura, T.</p> <p>2016-12-01</p> <p>Global overturning circulation is driven by density differences. Saline water rejected by <span class="hlt">sea-ice</span> production in coastal polynyas is the main source of dense water, and thus <span class="hlt">sea-ice</span> production is a key factor in the overturning circulation. However, until recently <span class="hlt">sea-ice</span> production and its interannual variability have not been well understood due to difficulties of in situ observation. The most effective means of detection of thin-<span class="hlt">ice</span> area and estimation of <span class="hlt">sea-ice</span> production on large scales is satellite remote sensing using passive microwave sensors, specifically the Special Sensor Microwave/Imager and Advanced Microwave Scanning Radiometer. This is based upon their ability to gain complete polar coverage on a daily basis irrespective of clouds and darkness. We have estimated <span class="hlt">sea-ice</span> production globally based on heat flux calculations using the satellite-derived thin <span class="hlt">ice</span> thickness data. The mapping demonstrates that <span class="hlt">ice</span> production rate is high in Antarctic coastal polynyas, in contrast to Arctic coastal polynyas. This is consistent with the formation of Antarctic Bottom Water (AABW). The Ross <span class="hlt">Ice</span> Shelf polynya has by far the highest <span class="hlt">ice</span> production in the Southern Hemisphere. The mapping has revealed that the Cape Darnley polynya is the second highest production area, leading to the discovery of the missing (fourth) source of AABW in this region. In the region off the Mertz Glacier Tongue, <span class="hlt">sea-ice</span> production decreased by as much as 40 %, due to the glacier calving in early 2010, resulting in a significant decrease in AABW production. The Okhotsk Northwestern polynya exhibits the highest <span class="hlt">ice</span> production in the Northern Hemisphere, and the resultant dense water formation leads to overturning in the North Pacific. Estimates of its <span class="hlt">ice</span> production show a significant decrease over the past 30-50 years, likely causing the weakening of the North Pacific overturning. The mapping also provides surface boundary conditions and validation data of heat- and salt-flux associated</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/1013155','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/1013155"><span>Seasonal comparisons of <span class="hlt">sea</span> <span class="hlt">ice</span> concentration estimates derived from SSM/I, OKEAN, and RADARSAT data</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Belchansky, Gennady I.; Douglas, David C.</p> <p>2002-01-01</p> <p>The Special Sensor Microwave Imager (SSM/I) microwave satellite radiometer and its predecessor SMMR are primary sources of information for global <span class="hlt">sea</span> <span class="hlt">ice</span> and climate studies. However, comparisons of SSM/I, Landsat, AVHRR, and ERS-1 synthetic aperture radar (SAR) have shown substantial seasonal and regional differences in their estimates of <span class="hlt">sea</span> <span class="hlt">ice</span> concentration. To evaluate these differences, we compared SSM/I estimates of <span class="hlt">sea</span> <span class="hlt">ice</span> coverage derived with the NASA Team and Bootstrap algorithms to estimates made using RADARSAT, and OKEAN-01 satellite sensor data. The study area included the Barents <span class="hlt">Sea</span>, Kara <span class="hlt">Sea</span>, Laptev <span class="hlt">Sea</span>, and <span class="hlt">adjacent</span> parts of the Arctic Ocean, during October 1995 through October 1999. <span class="hlt">Ice</span> concentration estimates from spatially and temporally near-coincident imagery were calculated using independent algorithms for each sensor type. The OKEAN algorithm implemented the satellite's two-channel active (radar) and passive microwave data in a linear mixture model based on the measured values of brightness temperature and radar backscatter. The RADARSAT algorithm utilized a segmentation approach of the measured radar backscatter, and the SSM/I <span class="hlt">ice</span> concentrations were derived at National Snow and <span class="hlt">Ice</span> Data Center (NSIDC) using the NASA Team and Bootstrap algorithms. Seasonal and monthly differences between SSM/I, OKEAN, and RADARSAT <span class="hlt">ice</span> concentrations were calculated and compared. Overall, total <span class="hlt">sea</span> <span class="hlt">ice</span> concentration estimates derived independently from near-coincident RADARSAT, OKEAN-01, and SSM/I satellite imagery demonstrated mean differences of less than 5.5% (S.D.<9.5%) during the winter period. Differences between the SSM/I NASA Team and the SSM/I Bootstrap concentrations were no more than 3.1% (S.D.<5.4%) during this period. RADARSAT and OKEAN-01 data both yielded higher total <span class="hlt">ice</span> concentrations than the NASA Team and the Bootstrap algorithms. The Bootstrap algorithm yielded higher total <span class="hlt">ice</span> concentrations than the NASA Team algorithm. Total <span class="hlt">ice</span></p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19..688R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19..688R"><span>Sensitivity Analysis of a Lagrangian <span class="hlt">Sea</span> <span class="hlt">Ice</span> Model</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Rabatel, Matthias; Rampal, Pierre; Bertino, Laurent; Carrassi, Alberto; Jones, Christopher K. R. T.</p> <p>2017-04-01</p> <p>Large changes in the Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> have been observed in the last decades in terms of the <span class="hlt">ice</span> thickness, extension and drift. Understanding the mechanisms behind these changes is of paramount importance to enhance our modeling and forecasting capabilities. For 40 years, models have been developed to describe the non-linear dynamical response of the <span class="hlt">sea</span> <span class="hlt">ice</span> to a number of external and internal factors. Nevertheless, there still exists large deviations between predictions and observations. There are related to incorrect descriptions of the <span class="hlt">sea</span> <span class="hlt">ice</span> response and/or to the uncertainties about the different sources of information: parameters, initial and boundary conditions and external forcing. Data assimilation (DA) methods are used to combine observations with models, and there is nowadays an increasing interest of DA for <span class="hlt">sea-ice</span> models and observations. We consider here the state-of-the art <span class="hlt">sea-ice</span> model, neXtSIM te{Rampal2016a}, which is based on a time-varying Lagrangian mesh and makes use of the Elasto-Brittle rheology. Our ultimate goal is designing appropriate DA scheme for such a modelling facility. This contribution reports about the first milestone along this line: a sensitivity analysis in order to quantify forecast error to guide model development and to set basis for further Lagrangian DA methods. Specific features of the <span class="hlt">sea-ice</span> dynamics in relation to the wind are thus analysed. Virtual buoys are deployed across the Arctic domain and their trajectories of motion are analysed. The simulated trajectories are also compared to real buoys trajectories observed. The model response is also compared with that one from a model version not including internal forcing to highlight the role of the rheology. Conclusions and perspectives for the general DA implementation are also discussed. \\bibitem{Rampal2016a} P. Rampal, S. Bouillon, E. Ólason, and M. Morlighem. ne{X}t{SIM}: a new {L}agrangian <span class="hlt">sea</span> <span class="hlt">ice</span> model. The Cryosphere, 10 (3): 1055-1073, 2016.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1993JGR....98.2561H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1993JGR....98.2561H"><span>Sensitivity study of a dynamic thermodynamic <span class="hlt">sea</span> <span class="hlt">ice</span> model</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Holland, David M.; Mysak, Lawrence A.; Manak, Davinder K.; Oberhuber, Josef M.</p> <p>1993-02-01</p> <p>A numerical simulation of the seasonal <span class="hlt">sea</span> <span class="hlt">ice</span> cover in the Arctic Ocean and the Greenland, Iceland, and Norwegian <span class="hlt">seas</span> is presented. The <span class="hlt">sea</span> <span class="hlt">ice</span> model is extracted from Oberhuber's (1990) coupled <span class="hlt">sea</span> <span class="hlt">ice</span>-mixed layer-isopycnal general circulation model and is written in spherical coordinates. The advantage of such a model over previous <span class="hlt">sea</span> <span class="hlt">ice</span> models is that it can be easily coupled to either global atmospheric or ocean general circulation models written in spherical coordinates. In this model, the thermodynamics are a modification of that of Parkinson and Washington (1979), while the dynamics use the full Hibler (1979) viscous-plastic rheology. Monthly thermodynamic and dynamic forcing fields for the atmosphere and ocean are specified. The simulations of the seasonal cycle of <span class="hlt">ice</span> thickness, compactness, and velocity, for a control set of parameters, compare favorably with the known seasonal characteristics of these fields. A sensitivity study of the control simulation of the seasonal <span class="hlt">sea</span> <span class="hlt">ice</span> cover is presented. The sensitivity runs are carried out under three different themes, namely, numerical conditions, parameter values, and physical processes. This last theme refers to experiments in which physical processes are either newly added or completely removed from the model. Approximately 80 sensitivity runs have been performed in which a change from the control run environment has been implemented. Comparisons have been made between the control run and a particular sensitivity run based on time series of the seasonal cycle of the domain-averaged <span class="hlt">ice</span> thickness, compactness, areal coverage, and kinetic energy. In addition, spatially varying fields of <span class="hlt">ice</span> thickness, compactness, velocity, and surface temperature for each season are presented for selected experiments. A brief description and discussion of the more interesting experiments are presented. The simulation of the seasonal cycle of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> cover is shown to be robust.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017BGeo...14.3927M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017BGeo...14.3927M"><span>Reviews and syntheses: <span class="hlt">Ice</span> acidification, the effects of ocean acidification on <span class="hlt">sea</span> <span class="hlt">ice</span> microbial communities</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>McMinn, Andrew</p> <p>2017-09-01</p> <p><span class="hlt">Sea</span> <span class="hlt">ice</span> algae, like some coastal and estuarine phytoplankton, are naturally exposed to a wider range of pH and CO2 concentrations than those in open marine <span class="hlt">seas</span>. While climate change and ocean acidification (OA) will impact pelagic communities, their effects on <span class="hlt">sea</span> <span class="hlt">ice</span> microbial communities remain unclear. <span class="hlt">Sea</span> <span class="hlt">ice</span> contains several distinct microbial communities, which are exposed to differing environmental conditions depending on their depth within the <span class="hlt">ice</span>. Bottom communities mostly experience relatively benign bulk ocean properties, while interior brine and surface (infiltration) communities experience much greater extremes. Most OA studies have examined the impacts on single <span class="hlt">sea</span> <span class="hlt">ice</span> algae species in culture. Although some studies examined the effects of OA alone, most examined the effects of OA and either light, nutrients or temperature. With few exceptions, increased CO2 concentration caused either no change or an increase in growth and/or photosynthesis. In situ studies on brine and surface algae also demonstrated a wide tolerance to increased and decreased pH and showed increased growth at higher CO2 concentrations. The short time period of most experiments (< 10 days), together with limited genetic diversity (i.e. use of only a single strain), however, has been identified as a limitation to a broader interpretation of the results. While there have been few studies on the effects of OA on the growth of marine bacterial communities in general, impacts appear to be minimal. In <span class="hlt">sea</span> <span class="hlt">ice</span> also, the few reports available suggest no negative impacts on bacterial growth or community richness. <span class="hlt">Sea</span> <span class="hlt">ice</span> ecosystems are ephemeral, melting and re-forming each year. Thus, for some part of each year organisms inhabiting the <span class="hlt">ice</span> must also survive outside of the <span class="hlt">ice</span>, either as part of the phytoplankton or as resting spores on the bottom. During these times, they will be exposed to the full range of co-stressors that pelagic organisms experience. Their ability to continue to make</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ClDy...49..775T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ClDy...49..775T"><span>Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> in the global eddy-permitting ocean reanalysis ORAP5</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tietsche, Steffen; Balmaseda, Magdalena A.; Zuo, Hao; Mogensen, Kristian</p> <p>2017-08-01</p> <p>We discuss the state of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> in the global eddy-permitting ocean reanalysis Ocean ReAnalysis Pilot 5 (ORAP5). Among other innovations, ORAP5 now assimilates observations of <span class="hlt">sea</span> <span class="hlt">ice</span> concentration using a univariate 3DVar-FGAT scheme. We focus on the period 1993-2012 and emphasize the evaluation of model performance with respect to recent observations of <span class="hlt">sea</span> <span class="hlt">ice</span> thickness. We find that <span class="hlt">sea</span> <span class="hlt">ice</span> concentration in ORAP5 is close to assimilated observations, with root mean square analysis residuals of less than 5 % in most regions. However, larger discrepancies exist for the Labrador <span class="hlt">Sea</span> and east of Greenland during winter owing to biases in the free-running model. <span class="hlt">Sea</span> <span class="hlt">ice</span> thickness is evaluated against three different observational data sets that have sufficient spatial and temporal coverage: ICESat, <span class="hlt">Ice</span>Bridge and SMOSIce. Large-scale features like the gradient between the thickest <span class="hlt">ice</span> in the Canadian Arctic and thinner <span class="hlt">ice</span> in the Siberian Arctic are simulated well by ORAP5. However, some biases remain. Of special note is the model's tendency to accumulate too thick <span class="hlt">ice</span> in the Beaufort Gyre. The root mean square error of ORAP5 <span class="hlt">sea</span> <span class="hlt">ice</span> thickness with respect to ICESat observations is 1.0 m, which is on par with the well-established PIOMAS model <span class="hlt">sea</span> <span class="hlt">ice</span> reconstruction. Interannual variability and trend of <span class="hlt">sea</span> <span class="hlt">ice</span> volume in ORAP5 also compare well with PIOMAS and ICESat estimates. We conclude that, notwithstanding a relatively simple <span class="hlt">sea</span> <span class="hlt">ice</span> data assimilation scheme, the overall state of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> in ORAP5 is in good agreement with observations and will provide useful initial conditions for predictions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20010037608','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20010037608"><span>Trends in the Length of the Southern Ocean <span class="hlt">Sea</span> <span class="hlt">Ice</span> Season: 1979-1999</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Parkinson, Claire L.; Zukor, Dorothy J. (Technical Monitor)</p> <p>2001-01-01</p> <p>Satellite data can be used to observe the <span class="hlt">sea</span> <span class="hlt">ice</span> distribution around the continent of Antarctica on a daily basis and hence to determine how many days a year have <span class="hlt">sea</span> <span class="hlt">ice</span> at each location. This has been done for each of the 21 years 1979-1999. Mapping the trends in these data over the 21-year period reveals a detailed pattern of changes in the length of the <span class="hlt">sea</span> <span class="hlt">ice</span> season around Antarctica. Most of the Ross <span class="hlt">Sea</span> <span class="hlt">ice</span> cover has undergone a lengthening of the <span class="hlt">sea</span> <span class="hlt">ice</span> season, whereas most of the Amundsen <span class="hlt">Sea</span> <span class="hlt">ice</span> cover and almost the entire Bellingshausen <span class="hlt">Sea</span> <span class="hlt">ice</span> cover have undergone a shortening of the <span class="hlt">sea</span> <span class="hlt">ice</span> season. Results around the rest of the continent, including in the Weddell <span class="hlt">Sea</span>, are more mixed, but overall, more of the Southern Ocean experienced a lengthening of the <span class="hlt">sea</span> <span class="hlt">ice</span> season than a shortening. For instance, the area experiencing a lengthening of the <span class="hlt">sea</span> <span class="hlt">ice</span> season by at least 1 day per year is 5.8 x 10(exp 6) sq km, whereas the area experiencing a shortening of the <span class="hlt">sea</span> <span class="hlt">ice</span> season by at least 1 day per year is less than half that, at 2.8 x 10(exp 6) sq km. This contrasts sharply with what is happened over the same period in the Arctic, where, overall, there has been some depletion of the <span class="hlt">ice</span> cover, including shortened <span class="hlt">sea</span> <span class="hlt">ice</span> seasons and decreased <span class="hlt">ice</span> extents.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.C51A0486G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.C51A0486G"><span>The 2013 Arctic Field Season of the NRL <span class="hlt">Sea-Ice</span> Measurement Program</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gardner, J. M.; Brozena, J. M.; Ball, D.; Hagen, R. A.; Liang, R.; Stoudt, C.</p> <p>2013-12-01</p> <p>The U.S. Naval Research Laboratory (NRL) is conducting a five year study of the changing Arctic with a particular focus on <span class="hlt">ice</span> thickness and distribution variability with the intent of optimizing state-of-the-art computer models which are currently used to predict <span class="hlt">sea</span> <span class="hlt">ice</span> changes. An important part of our study is to calibrate/validate CryoSat2 <span class="hlt">ice</span> thickness data prior to its incorporation into new <span class="hlt">ice</span> forecast models. NRL Code 7420 collected coincident data with the CryoSat2 satellite in 2011 and 2012 using a LiDAR (Riegl Q560) to measure combined snow and <span class="hlt">ice</span> thickness and a 10 GHz pulse-limited precision radar altimeter to measure <span class="hlt">sea-ice</span> freeboard. This field season, LiDAR data was collected using the Riegl Q680 which permitted higher density operation and data collection. Concident radar data was collected using an improved version of the NRL 10 GHz pulse limited radar that was used for the 2012 fieldwork. 8 coincident tracks of CryoSat2 satellite data were collected. Additionally a series of grids (7 total) of <span class="hlt">adjacent</span> tracks were flown coincident with Cryosat2 satellite overpass. These grids cover the approximate satellite footprint of the satellite on the <span class="hlt">ice</span> as it passes overhead. Data from these grids are shown here and will be used to examine the relationship of the tracked satellite waveform data to the actual surface across the footprint. We also coordinated with the Seasonal <span class="hlt">Ice</span> Zone Observing Network (SIZONet) group who conducted surface based <span class="hlt">ice</span> thickness surveys using a Geonics EM-31 along hunter trails on the landfast <span class="hlt">ice</span> near Barrow as well as on drifting <span class="hlt">ice</span> offshore during helicopter landings. On two sorties, a twin otter carrying the NRL LiDAR and radar altimeter flew in tandem with the helicopter carrying the EM-31 to achieve synchronous data acquisition. Data from these flights are shown here along with a digital elevation map.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.7840N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.7840N"><span>Online <span class="hlt">sea</span> <span class="hlt">ice</span> data platform: www.seaiceportal.de</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Nicolaus, Marcel; Asseng, Jölund; Bartsch, Annekathrin; Bräuer, Benny; Fritzsch, Bernadette; Grosfeld, Klaus; Hendricks, Stefan; Hiller, Wolfgang; Heygster, Georg; Krumpen, Thomas; Melsheimer, Christian; Ricker, Robert; Treffeisen, Renate; Weigelt, Marietta; Nicolaus, Anja; Lemke, Peter</p> <p>2016-04-01</p> <p>There is an increasing public interest in <span class="hlt">sea</span> <span class="hlt">ice</span> information from both Polar Regions, which requires up-to-date background information and data sets at different levels for various target groups. In order to serve this interest and need, seaiceportal.de (originally: meereisportal.de) was developed as a comprehensive German knowledge platform on <span class="hlt">sea</span> <span class="hlt">ice</span> and its snow cover in the Arctic and Antarctic. It was launched in April 2013. Since then, the content and selection of data sets increased and the data portal received increasing attention, also from the international science community. Meanwhile, we are providing near-real time and archive data of many key parameters of <span class="hlt">sea</span> <span class="hlt">ice</span> and its snow cover. The data sets result from measurements acquired by various platforms as well as numerical simulations. Satellite observations of <span class="hlt">sea</span> <span class="hlt">ice</span> concentration, freeboard, thickness and drift are available as gridded data sets. <span class="hlt">Sea</span> <span class="hlt">ice</span> and snow temperatures and thickness as well as atmospheric parameters are available from autonomous platforms (buoys). Additional ship observations, <span class="hlt">ice</span> station measurements, and mooring time series are compiled as data collections over the last decade. In parallel, we are continuously extending our meta-data and uncertainty information for all data sets. In addition to the data portal, seaiceportal.de provides general comprehensive background information on <span class="hlt">sea</span> <span class="hlt">ice</span> and snow as well as expert statements on recent observations and developments. This content is mostly in German in order to complement the various existing international sites for the German speaking public. We will present the portal, its content and function, but we are also asking for direct user feedback.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4651550','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4651550"><span>Increased Land Use by Chukchi <span class="hlt">Sea</span> Polar Bears in Relation to Changing <span class="hlt">Sea</span> <span class="hlt">Ice</span> Conditions</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Rode, Karyn D.; Wilson, Ryan R.; Regehr, Eric V.; St. Martin, Michelle; Douglas, David C.; Olson, Jay</p> <p>2015-01-01</p> <p>Recent observations suggest that polar bears (Ursus maritimus) are increasingly using land habitats in some parts of their range, where they have minimal access to their preferred prey, likely in response to loss of their <span class="hlt">sea</span> <span class="hlt">ice</span> habitat associated with climatic warming. We used location data from female polar bears fit with satellite radio collars to compare land use patterns in the Chukchi <span class="hlt">Sea</span> between two periods (1986–1995 and 2008–2013) when substantial summer <span class="hlt">sea-ice</span> loss occurred. In both time periods, polar bears predominantly occupied <span class="hlt">sea-ice</span>, although land was used during the summer <span class="hlt">sea-ice</span> retreat and during the winter for maternal denning. However, the proportion of bears on land for > 7 days between August and October increased between the two periods from 20.0% to 38.9%, and the average duration on land increased by 30 days. The majority of bears that used land in the summer and for denning came to Wrangel and Herald Islands (Russia), highlighting the importance of these northernmost land habitats to Chukchi <span class="hlt">Sea</span> polar bears. Where bears summered and denned, and how long they spent there, was related to the timing and duration of <span class="hlt">sea</span> <span class="hlt">ice</span> retreat. Our results are consistent with other studies supporting increased land use as a common response of polar bears to <span class="hlt">sea-ice</span> loss. Implications of increased land use for Chukchi <span class="hlt">Sea</span> polar bears are unclear, because a recent study observed no change in body condition or reproductive indices between the two periods considered here. This result suggests that the ecology of this region may provide a degree of resilience to <span class="hlt">sea</span> <span class="hlt">ice</span> loss. However, projections of continued <span class="hlt">sea</span> <span class="hlt">ice</span> loss suggest that polar bears in the Chukchi <span class="hlt">Sea</span> and other parts of the Arctic may increasingly use land habitats in the future, which has the potential to increase nutritional stress and human-polar bear interactions. PMID:26580809</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70159860','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70159860"><span>Increased land use by Chukchi <span class="hlt">Sea</span> polar bears in relation to changing <span class="hlt">sea</span> <span class="hlt">ice</span> conditions</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Rode, Karyn D.; Wilson, Ryan R.; Regehr, Eric V.; St. Martin, Michelle; Douglas, David C.; Olson, Jay</p> <p>2015-01-01</p> <p>Recent observations suggest that polar bears (Ursus maritimus) are increasingly using land habitats in some parts of their range, where they have minimal access to their preferred prey, likely in response to loss of their <span class="hlt">sea</span> <span class="hlt">ice</span> habitat associated with climatic warming. We used location data from female polar bears fit with satellite radio collars to compare land use patterns in the Chukchi <span class="hlt">Sea</span> between two periods (1986–1995 and 2008–2013) when substantial summer <span class="hlt">sea-ice</span> loss occurred. In both time periods, polar bears predominantly occupied <span class="hlt">sea-ice</span>, although land was used during the summer <span class="hlt">sea-ice</span> retreat and during the winter for maternal denning. However, the proportion of bears on land for > 7 days between August and October increased between the two periods from 20.0% to 38.9%, and the average duration on land increased by 30 days. The majority of bears that used land in the summer and for denning came to Wrangel and Herald Islands (Russia), highlighting the importance of these northernmost land habitats to Chukchi <span class="hlt">Sea</span> polar bears. Where bears summered and denned, and how long they spent there, was related to the timing and duration of <span class="hlt">sea</span> <span class="hlt">ice</span> retreat. Our results are consistent with other studies supporting increased land use as a common response of polar bears to <span class="hlt">sea-ice</span> loss. Implications of increased land use for Chukchi <span class="hlt">Sea</span> polar bears are unclear, because a recent study observed no change in body condition or reproductive indices between the two periods considered here. This result suggests that the ecology of this region may provide a degree of resilience to <span class="hlt">sea</span> <span class="hlt">ice</span> loss. However, projections of continued <span class="hlt">sea</span> <span class="hlt">ice</span> loss suggest that polar bears in the Chukchi <span class="hlt">Sea</span> and other parts of the Arctic may increasingly use land habitats in the future, which has the potential to increase nutritional stress and human-polar bear interactions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20000039366&hterms=Parkinsons&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3DParkinsons','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20000039366&hterms=Parkinsons&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3DParkinsons"><span>Changes in the Areal Extent of Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span>: Observations from Satellites</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Parkinson, Claire L.</p> <p>2000-01-01</p> <p>Wintertime <span class="hlt">sea</span> <span class="hlt">ice</span> covers 15 million square kilometers of the north polar region, an area exceeding one and a half times the area of the U. S. Even at the end of the summer melt season, <span class="hlt">sea</span> <span class="hlt">ice</span> still covers 7 million square kilometers. This vast <span class="hlt">ice</span> cover is an integral component of the climate system, being moved around by winds and waves, restricting heat and other exchanges between the ocean and atmosphere, reflecting most of the solar radiation incident on it, transporting cold, relatively fresh water equatorward, and affecting the overturning of ocean waters underneath, with impacts that can be felt worldwide. <span class="hlt">Sea</span> <span class="hlt">ice</span> also is a major factor in the Arctic ecosystem, affecting life forms ranging from minute organisms living within the <span class="hlt">ice</span>, sometimes to the tune of millions in a single <span class="hlt">ice</span> floe, to large marine mammals like walruses that rely on <span class="hlt">sea</span> <span class="hlt">ice</span> as a platform for resting, foraging, social interaction, and breeding. Since 1978, satellite technology has allowed the monitoring of the vast Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> cover on a routine basis. The satellite observations reveal that, overall, the areal extent of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> has been decreasing since 1978, at an average rate of 2.7% per decade through the end of 1998. Through 1998, the greatest rates of decrease occurred in the <span class="hlt">Seas</span> of Okhotsk and Japan and the Kara and Barents <span class="hlt">Seas</span>, with most other regions of the Arctic also experiencing <span class="hlt">ice</span> extent decreases. The two regions experiencing <span class="hlt">ice</span> extent increases over this time period were the Bering <span class="hlt">Sea</span> and the Gulf of St. Lawrence. Furthermore, the satellite data reveal that the <span class="hlt">sea</span> <span class="hlt">ice</span> season shortened by over 25 days per decade in the central <span class="hlt">Sea</span> of Okhotsk and the eastern Barents <span class="hlt">Sea</span>, and by lesser amounts throughout much of the rest of the Arctic seasonal <span class="hlt">sea</span> <span class="hlt">ice</span> region, although not in the Bering <span class="hlt">Sea</span> or the Gulf of St. Lawrence. Concern has been raised that if the trends toward shortened <span class="hlt">sea</span> <span class="hlt">ice</span> seasons and lesser <span class="hlt">sea</span> <span class="hlt">ice</span> coverage continue, this could entail major</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27811286','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27811286"><span>Observed Arctic <span class="hlt">sea-ice</span> loss directly follows anthropogenic CO2 emission.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Notz, Dirk; Stroeve, Julienne</p> <p>2016-11-11</p> <p>Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> is retreating rapidly, raising prospects of a future <span class="hlt">ice</span>-free Arctic Ocean during summer. Because climate-model simulations of the <span class="hlt">sea-ice</span> loss differ substantially, we used a robust linear relationship between monthly-mean September <span class="hlt">sea-ice</span> area and cumulative carbon dioxide (CO 2 ) emissions to infer the future evolution of Arctic summer <span class="hlt">sea</span> <span class="hlt">ice</span> directly from the observational record. The observed linear relationship implies a sustained loss of 3 ± 0.3 square meters of September <span class="hlt">sea-ice</span> area per metric ton of CO 2 emission. On the basis of this sensitivity, Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> will be lost throughout September for an additional 1000 gigatons of CO 2 emissions. Most models show a lower sensitivity, which is possibly linked to an underestimation of the modeled increase in incoming longwave radiation and of the modeled transient climate response. Copyright © 2016, American Association for the Advancement of Science.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFMPP14B..08C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFMPP14B..08C"><span>Identification of contrasting seasonal <span class="hlt">sea</span> <span class="hlt">ice</span> conditions during the Younger Dryas</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Cabedo-Sanz, P.; Belt, S. T.; Knies, J.</p> <p>2012-12-01</p> <p>The presence of the <span class="hlt">sea</span> <span class="hlt">ice</span> diatom biomarker IP25 in Arctic marine sediments has been used in previous studies as a proxy for past spring <span class="hlt">sea</span> <span class="hlt">ice</span> occurrence and as an indicator of wider palaeoenvironmental conditions for different regions of the Arctic over various timescales [e.g. 1, 2]. The current study focuses on high-resolution palaeo <span class="hlt">sea</span> <span class="hlt">ice</span> reconstructions for northern Norway during the last ca. 15 cal. kyr BP. Within this study, particular emphasis has been placed on the identification of the <span class="hlt">sea</span> <span class="hlt">ice</span> conditions during the Younger Dryas and the application of different biomarker-based proxies to both identify and quantify seasonal <span class="hlt">sea</span> <span class="hlt">ice</span> conditions. Firstly, the appearance of the specific <span class="hlt">sea</span> <span class="hlt">ice</span> diatom proxy IP25 at ca. 12.9 cal. kyr BP in a marine sediment core (JM99-1200) obtained from Andfjorden has provided an unambiguous but qualitative measure of seasonal <span class="hlt">sea</span> <span class="hlt">ice</span> and thus the onset of the Younger Dryas stadial. The near continuous occurrence of IP25 for the next ca. 1400 yr demonstrates seasonal <span class="hlt">sea</span> <span class="hlt">ice</span> during this interval, although variable abundances suggest that the recurrent conditions in the early-mid Younger Dryas (ca. 12.9 - 11.9 cal. kyr BP) changed significantly from stable to highly variable <span class="hlt">sea</span> <span class="hlt">ice</span> conditions at ca. 11.9 cal. kyr BP and this instability in <span class="hlt">sea</span> <span class="hlt">ice</span> prevailed for the subsequent ca. 400 yr. At ca. 11.5 cal. kyr BP, IP25 disappeared from the record indicating <span class="hlt">ice</span>-free conditions that signified the beginning of the Holocene. Similarly, a high resolution record from the Kveithola Through, western Barents <span class="hlt">Sea</span>, showed clearly higher IP25 concentrations during the Younger Dryas stadial compared to the Holocene. For both marine records, the IP25 concentrations were also combined with those of the open water phytoplankton biomarker brassicasterol to generate PBIP25 data from which more quantitative measurements of <span class="hlt">sea</span> <span class="hlt">ice</span> were determined. The contrasting seasonal <span class="hlt">sea</span> <span class="hlt">ice</span> conditions during the Younger Dryas were further verified</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li class="active"><span>19</span></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_19 --> <div id="page_20" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li class="active"><span>20</span></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="381"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C33C1218T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C33C1218T"><span>Measurement of spectral <span class="hlt">sea</span> <span class="hlt">ice</span> albedo at Qaanaaq fjord in northwest Greenland</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tanikawa, T.</p> <p>2017-12-01</p> <p>The spectral albedos of <span class="hlt">sea</span> <span class="hlt">ice</span> were measured at Qaanaaq fjord in northwest Greenland. Spectral measurements were conducted for <span class="hlt">sea</span> <span class="hlt">ice</span> covered with snow and <span class="hlt">sea</span> <span class="hlt">ice</span> without snow where snow was artificially removed around measurement point. Thickness of the <span class="hlt">sea</span> <span class="hlt">ice</span> was approximately 1.3 m with 5 cm of snow over the <span class="hlt">sea</span> <span class="hlt">ice</span>. The measurements show that the spectral albedos of the <span class="hlt">sea</span> <span class="hlt">ice</span> with snow were lower than those of natural pure snow especially in the visible regions though the spectral shapes were similar to each other. This is because the spectral albedos in the visible region have information of not only the snow but also the <span class="hlt">sea</span> <span class="hlt">ice</span> under the snow. The spectral albedos of the <span class="hlt">sea</span> <span class="hlt">ice</span> without the snow were approximately 0.4 - 0.5 in the visible region, 0.05-0.25 in the near-infrared region and almost constant of approximately 0.05 in the region of 1500 - 2500 nm. In the visible region, it would be due to multiple scattering by an air bubble within the <span class="hlt">sea</span> <span class="hlt">ice</span>. In contrast, in the near-infrared and shortwave infrared wavelengths, surface reflection at the <span class="hlt">sea</span> <span class="hlt">ice</span> surface would be dominant. Since a light absorption by the <span class="hlt">ice</span> in these regions is relatively strong comparing to the visible region, the light could not be penetrated deeply within the <span class="hlt">sea</span> <span class="hlt">ice</span>, resulting that surface reflection based on Fresnel reflection would be dominant. In this presentation we also show the results of comparison between the radiative transfer calculation and spectral measurement data.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C23B0793M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C23B0793M"><span>Multiyear <span class="hlt">ice</span> transport and small scale <span class="hlt">sea</span> <span class="hlt">ice</span> deformation near the Alaska coast measured by air-deployable <span class="hlt">Ice</span> Trackers</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mahoney, A. R.; Kasper, J.; Winsor, P.</p> <p>2015-12-01</p> <p>Highly complex patterns of <span class="hlt">ice</span> motion and deformation were captured by fifteen satellite-telemetered GPS buoys (known as <span class="hlt">Ice</span> Trackers) deployed near Barrow, Alaska, in spring 2015. Two pentagonal clusters of buoys were deployed on pack <span class="hlt">ice</span> by helicopter in the Beaufort <span class="hlt">Sea</span> between 20 and 80 km offshore. During deployment, <span class="hlt">ice</span> motion in the study region was effectively zero, but two days later the buoys captured a rapid transport event in which multiyear <span class="hlt">ice</span> from the Beaufort <span class="hlt">Sea</span> was flushed into the Chukchi <span class="hlt">Sea</span>. During this event, westward <span class="hlt">ice</span> motion began in the Chukchi <span class="hlt">Sea</span> and propagated eastward. This created new openings in the <span class="hlt">ice</span> and led to rapid elongation of the clusters as the westernmost buoys accelerated away from their neighbors to the east. The buoys tracked <span class="hlt">ice</span> velocities of over 1.5 ms-1, with fastest motion occurring closest to the coast indicating strong current shear. Three days later, <span class="hlt">ice</span> motion reversed and the two clusters became intermingled, rendering divergence calculations based on the area enclosed by clusters invalid. The data show no detectable difference in velocity between first year and multiyear <span class="hlt">ice</span> floes, but Lagrangian timeseries of SAR imagery centered on each buoy show that first year <span class="hlt">ice</span> underwent significant small-scale deformation during the event. The five remaining buoys were deployed by local residents on prominent ridges embedded in the landfast <span class="hlt">ice</span> within 16 km of Barrow in order to track the fate of such features after they detached from the coast. Break-up of the landfast <span class="hlt">ice</span> took place over a period of several days and, although the buoys each initially followed a similar eastward trajectory around Point Barrow into the Beaufort <span class="hlt">Sea</span>, they rapidly dispersed over an area more than 50 km across. With rapid environmental and socio-economic change in the Arctic, understanding the complexity of nearshore <span class="hlt">ice</span> motion is increasingly important for predict future changes in the <span class="hlt">ice</span> and the tracking <span class="hlt">ice</span>-related hazards</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19910047694&hterms=lead+history&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dlead%2Bhistory','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19910047694&hterms=lead+history&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dlead%2Bhistory"><span>Texture analysis of radiometric signatures of new <span class="hlt">sea</span> <span class="hlt">ice</span> forming in Arctic leads</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Eppler, Duane T.; Farmer, L. Dennis</p> <p>1991-01-01</p> <p>Analysis of 33.6-GHz, high-resolution, passive microwave images suggests that new <span class="hlt">sea</span> <span class="hlt">ice</span> accumulating in open leads is characterized by a unique textural signature which can be used to discriminate new <span class="hlt">ice</span> forming in this environment from <span class="hlt">adjacent</span> surfaces of similar radiometric temperature. Ten training areas were selected from the data set, three of which consisted entirely of first-year <span class="hlt">ice</span>, four entirely of multilayer <span class="hlt">ice</span>, and three of new <span class="hlt">ice</span> in open leads in the process of freezing. A simple gradient operator was used to characterize the radiometric texture in each training region in terms of the degree to which radiometric gradients are oriented. New <span class="hlt">ice</span> in leads has a sufficiently high proportion of well-oriented features to distinguish it uniquely from first-year <span class="hlt">ice</span> and multiyear <span class="hlt">ice</span>. The predominance of well-oriented features probably reflects physical processes by which new <span class="hlt">ice</span> accumulates in open leads. Banded structures, which are evident in aerial photographs of new <span class="hlt">ice</span>, apparently give rise to the radiometric signature observed, in which the trend of brightness temperature gradients is aligned parallel to lead trends. First-year <span class="hlt">ice</span> and multiyear <span class="hlt">ice</span>, which have been subjected to a more random growth and process history, lack this banded structure and therefore are characterized by signatures in which well-aligned elements are less dominant.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/19754681','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/19754681"><span>Survival and breeding of polar bears in the southern Beaufort <span class="hlt">Sea</span> in relation to <span class="hlt">sea</span> <span class="hlt">ice</span>.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Regehr, Eric V; Hunter, Christine M; Caswell, Hal; Amstrup, Steven C; Stirling, Ian</p> <p>2010-01-01</p> <p>1. Observed and predicted declines in Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> have raised concerns about marine mammals. In May 2008, the US Fish and Wildlife Service listed polar bears (Ursus maritimus) - one of the most <span class="hlt">ice</span>-dependent marine mammals - as threatened under the US Endangered Species Act. 2. We evaluated the effects of <span class="hlt">sea</span> <span class="hlt">ice</span> conditions on vital rates (survival and breeding probabilities) for polar bears in the southern Beaufort <span class="hlt">Sea</span>. Although <span class="hlt">sea</span> <span class="hlt">ice</span> declines in this and other regions of the polar basin have been among the greatest in the Arctic, to date population-level effects of <span class="hlt">sea</span> <span class="hlt">ice</span> loss on polar bears have only been identified in western Hudson Bay, near the southern limit of the species' range. 3. We estimated vital rates using multistate capture-recapture models that classified individuals by sex, age and reproductive category. We used multimodel inference to evaluate a range of statistical models, all of which were structurally based on the polar bear life cycle. We estimated parameters by model averaging, and developed a parametric bootstrap procedure to quantify parameter uncertainty. 4. In the most supported models, polar bear survival declined with an increasing number of days per year that waters over the continental shelf were <span class="hlt">ice</span> free. In 2001-2003, the <span class="hlt">ice</span>-free period was relatively short (mean 101 days) and adult female survival was high (0.96-0.99, depending on reproductive state). In 2004 and 2005, the <span class="hlt">ice</span>-free period was longer (mean 135 days) and adult female survival was low (0.73-0.79, depending on reproductive state). Breeding rates and cub litter survival also declined with increasing duration of the <span class="hlt">ice</span>-free period. Confidence intervals on vital rate estimates were wide. 5. The effects of <span class="hlt">sea</span> <span class="hlt">ice</span> loss on polar bears in the southern Beaufort <span class="hlt">Sea</span> may apply to polar bear populations in other portions of the polar basin that have similar <span class="hlt">sea</span> <span class="hlt">ice</span> dynamics and have experienced similar, or more severe, <span class="hlt">sea</span> <span class="hlt">ice</span> declines. Our findings therefore are</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1919531L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1919531L"><span>Ensemble <span class="hlt">sea</span> <span class="hlt">ice</span> forecast for predicting compressive situations in the Baltic <span class="hlt">Sea</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lehtiranta, Jonni; Lensu, Mikko; Kokkonen, Iiro; Haapala, Jari</p> <p>2017-04-01</p> <p>Forecasting of <span class="hlt">sea</span> <span class="hlt">ice</span> hazards is important for winter shipping in the Baltic <span class="hlt">Sea</span>. In current numerical models the <span class="hlt">ice</span> thickness distribution and drift are captured well, but compressive situations are often missing from forecast products. Its inclusion is requested by the shipping community, as compression poses a threat to ship operations. As compressing <span class="hlt">ice</span> is capable of stopping ships for days and even damaging them, its inclusion in <span class="hlt">ice</span> forecasts is vital. However, we have found that compression can not be predicted well in a deterministic forecast, since it can be a local and a quickly changing phenomenon. It is also very sensitive to small changes in the wind speed and direction, the prevailing <span class="hlt">ice</span> conditions, and the model parameters. Thus, a probabilistic ensemble simulation is needed to produce a meaningful compression forecast. An ensemble model setup was developed in the SafeWIN project for this purpose. It uses the HELMI multicategory <span class="hlt">ice</span> model, which was amended for making simulations in parallel. The ensemble was built by perturbing the atmospheric forcing and the physical parameters of the <span class="hlt">ice</span> pack. The model setup will provide probabilistic forecasts for the compression in the Baltic <span class="hlt">sea</span> <span class="hlt">ice</span>. Additionally the model setup provides insight into the uncertainties related to different model parameters and their impact on the model results. We have completed several hindcast simulations for the Baltic <span class="hlt">Sea</span> for verification purposes. These results are shown to match compression reports gathered from ships. In addition, an ensemble forecast is in preoperational testing phase and its first evaluation will be presented in this work.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018OcSci..14..127P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018OcSci..14..127P"><span>Observations of brine plumes below melting Arctic <span class="hlt">sea</span> <span class="hlt">ice</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Peterson, Algot K.</p> <p>2018-02-01</p> <p>In <span class="hlt">sea</span> <span class="hlt">ice</span>, interconnected pockets and channels of brine are surrounded by fresh <span class="hlt">ice</span>. Over time, brine is lost by gravity drainage and flushing. The timing of salt release and its interaction with the underlying water can impact subsequent <span class="hlt">sea</span> <span class="hlt">ice</span> melt. Turbulence measurements 1 m below melting <span class="hlt">sea</span> <span class="hlt">ice</span> north of Svalbard reveal anticorrelated heat and salt fluxes. From the observations, 131 salty plumes descending from the warm <span class="hlt">sea</span> <span class="hlt">ice</span> are identified, confirming previous observations from a Svalbard fjord. The plumes are likely triggered by oceanic heat through bottom melt. Calculated over a composite plume, oceanic heat and salt fluxes during the plumes account for 6 and 9 % of the total fluxes, respectively, while only lasting in total 0.5 % of the time. The observed salt flux accumulates to 7.6 kg m-2, indicating nearly full desalination of the <span class="hlt">ice</span>. Bulk salinity reduction between two nearby <span class="hlt">ice</span> cores agrees with accumulated salt fluxes to within a factor of 2. The increasing fraction of younger, more saline <span class="hlt">ice</span> in the Arctic suggests an increase in desalination processes with the transition to the <q>new Arctic</q>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20000101018&hterms=Antarctic+icebergs&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3DAntarctic%2Bicebergs','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20000101018&hterms=Antarctic+icebergs&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3DAntarctic%2Bicebergs"><span>Active Microwave Remote Sensing Observations of Weddell <span class="hlt">Sea</span> <span class="hlt">Ice</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Drinkwater, Mark R.</p> <p>1997-01-01</p> <p>Since July 1991, the European Space Agency's ERS-1 and ERS-2 satellites have acquired radar data of the Weddell <span class="hlt">Sea</span>, Antarctica. The Active Microwave Instrument on board ERS has two modes; SAR and Scatterometer. Two receiving stations enable direct downlink and recording of high bit-rate, high resolution SAR image data of this region. When not in an imaging mode, when direct SAR downlink is not possible, or when a receiving station is inoperable, the latter mode allows normalized radar cross-section data to be acquired. These low bit-rate ERS scatterometer data are tape recorded, downlinked and processed off-line. Recent advances in image generation from Scatterometer backscatter measurements enable complementary medium-scale resolution images to be made during periods when SAR images cannot be acquired. Together, these combined C-band microwave image data have for the first time enabled uninterrupted night and day coverage of the Weddell <span class="hlt">Sea</span> region at both high (25 m) and medium-scale (-20 km) resolutions. C-band ERS-1 radar data are analyzed in conjunction with field data from two simultaneous field experiments in 1992. Satellite radar signature data are compared with shipborne radar data to extract a regional and seasonal signature database for recognition of <span class="hlt">ice</span> types in the images. Performance of automated <span class="hlt">sea-ice</span> tracking algorithms is tested on Antarctic data to evaluate their success. Examples demonstrate that both winter and summer <span class="hlt">ice</span> can be effectively tracked. The kinematics of the main <span class="hlt">ice</span> zones within the Weddell <span class="hlt">Sea</span> are illustrated, together with the complementary time-dependencies in their radar signatures. Time-series of satellite images are used to illustrate the development of the Weddell <span class="hlt">Sea</span> <span class="hlt">ice</span> cover from its austral summer minimum (February) to its winter maximum (September). The combination of time-dependent microwave signatures and <span class="hlt">ice</span> dynamics tracking enable various drift regimes to be defined which relate closely to the circulation of the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1996JGR...10120809K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1996JGR...10120809K"><span>Atmospheric and oceanic forcing of Weddell <span class="hlt">Sea</span> <span class="hlt">ice</span> motion</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kottmeier, C.; Sellmann, Lutz</p> <p>1996-09-01</p> <p>The data from <span class="hlt">sea</span> <span class="hlt">ice</span> buoys, which were deployed during the Winter Weddell <span class="hlt">Sea</span> Project 1986, the Winter Weddell Gyre Studies 1989 and 1992, the <span class="hlt">Ice</span> Station Weddell in 1992, the Antarctic Zone Flux Experiment in 1994, and several ship cruises in Austral summers, are uniformly reanalyzed by the same objective methods. Geostrophic winds are derived after matching of the buoy pressure data with the surface pressure fields of the European Centre for Medium Range Weather Forecasts. The ratio between <span class="hlt">ice</span> drift and geostrophic wind speeds is reduced when winds and currents oppose each other, when the atmospheric surface layer is stably stratified, and when the <span class="hlt">ice</span> is under pressure near coasts. Over the continental shelves, the spatial inhomogeneity of tidal and inertial motion effectively controls the variability of divergence for periods below 36 hours. Far from coasts, speed ratios, which presumably reflect internal stress variations in the <span class="hlt">ice</span> cover, are independent of drift divergence on the spatial scale of 100 km. To study basin-scale <span class="hlt">ice</span> dynamics, all <span class="hlt">ice</span> drift data are related to the geostrophic winds based on the complex linear model [Thorndike and Colony, 1982] for daily averaged data. The composite patterns of mean <span class="hlt">ice</span> motion, geostrophic winds, and geostrophic surface currents document cyclonic basin-wide circulations. Geostrophic ocean currents are generally small in the Weddell <span class="hlt">Sea</span>. Significant features are the coastal current near the southeastern coasts and the bands of larger velocities of ≈6 cm s-1 following the northward and eastward orientation of the continental shelf breaks in the western and northwestern Weddell <span class="hlt">Sea</span>. In the southwestern Weddell <span class="hlt">Sea</span> the mean <span class="hlt">ice</span> drift speed is reduced to less than 0.5% of the geostrophic wind speed and increases rather continuously to 1.5% in the northern, central, and eastern Weddell <span class="hlt">Sea</span>. The linear model accounts for less than 50% of the total variance of drift speeds in the southwestern Weddell <span class="hlt">Sea</span> and up to 80</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017QSRv..169...13D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017QSRv..169...13D"><span>Current state and future perspectives on coupled <span class="hlt">ice</span>-sheet - <span class="hlt">sea</span>-level modelling</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>de Boer, Bas; Stocchi, Paolo; Whitehouse, Pippa L.; van de Wal, Roderik S. W.</p> <p>2017-08-01</p> <p>The interaction between <span class="hlt">ice</span>-sheet growth and retreat and <span class="hlt">sea</span>-level change has been an established field of research for many years. However, recent advances in numerical modelling have shed new light on the precise interaction of marine <span class="hlt">ice</span> sheets with the change in near-field <span class="hlt">sea</span> level, and the related stability of the grounding line position. Studies using fully coupled <span class="hlt">ice</span>-sheet - <span class="hlt">sea</span>-level models have shown that accounting for gravitationally self-consistent <span class="hlt">sea</span>-level change will act to slow down the retreat and advance of marine <span class="hlt">ice</span>-sheet grounding lines. Moreover, by simultaneously solving the '<span class="hlt">sea</span>-level equation' and modelling <span class="hlt">ice</span>-sheet flow, coupled models provide a global field of relative <span class="hlt">sea</span>-level change that is consistent with dynamic changes in <span class="hlt">ice</span>-sheet extent. In this paper we present an overview of recent advances, possible caveats, methodologies and challenges involved in coupled <span class="hlt">ice</span>-sheet - <span class="hlt">sea</span>-level modelling. We conclude by presenting a first-order comparison between a suite of relative <span class="hlt">sea</span>-level data and output from a coupled <span class="hlt">ice</span>-sheet - <span class="hlt">sea</span>-level model.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-PIA18035.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-PIA18035.html"><span>Warm Rivers Play Role in Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> Melt Animation</span></a></p> <p><a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a></p> <p></p> <p>2014-03-05</p> <p>This frame from a NASA MODIS animation depicts warming <span class="hlt">sea</span> surface temperatures in the Arctic Beaufort <span class="hlt">Sea</span> after warm waters from Canada Mackenzie River broke through a shoreline <span class="hlt">sea</span> <span class="hlt">ice</span> barrier in summer 2012, enhancing the melting of <span class="hlt">sea</span> <span class="hlt">ice</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C43B0750J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C43B0750J"><span>Landfast <span class="hlt">Sea</span> <span class="hlt">Ice</span> Breakouts: Stabilizing <span class="hlt">Ice</span> Features, Oceanic and Atmospheric Forcing at Barrow, Alaska</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Jones, J.; Eicken, H.; Mahoney, A. R.; MV, R.; Kambhamettu, C.; Fukamachi, Y.; Ohshima, K. I.; George, C.</p> <p>2016-12-01</p> <p>Landfast <span class="hlt">sea</span> <span class="hlt">ice</span> is an important seasonal feature along most Arctic coastlines, such as that of the Chukchi <span class="hlt">Sea</span> near Barrow, Alaska. Its stability throughout the <span class="hlt">ice</span> season is determined by many factors but grounded pressure ridges are the primary stabilizing component. Landfast <span class="hlt">ice</span> breakouts occur when these grounded ridges fail or unground, and previously stationary <span class="hlt">ice</span> detaches from the coast and drifts away. Using ground-based radar imagery from a coastal <span class="hlt">ice</span> and ocean observatory at Barrow, we have developed a method to estimate the extent of grounded ridges by tracking <span class="hlt">ice</span> motion and deformation over the course of winter and have derived <span class="hlt">ice</span> keel depth and potential for grounding from cumulative convergent <span class="hlt">ice</span> motion. Estimates of landfast <span class="hlt">ice</span> grounding strength have been compared to the atmospheric and oceanic stresses acting on the landfast <span class="hlt">ice</span> before and during breakout events to determine prevailing causes for the failure of stabilizing features. Applying this approach to two case studies in 2008 and 2010, we conclude that a combination of atmospheric and oceanic stresses may have caused the breakouts analyzed in this study, with the latter as the dominant force. Preconditioning (as weakening) of grounded ridges by <span class="hlt">sea</span> level variations may facilitate failure of the <span class="hlt">ice</span> sheet leading to breakout events.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016CSR...126...50J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016CSR...126...50J"><span>Landfast <span class="hlt">sea</span> <span class="hlt">ice</span> breakouts: Stabilizing <span class="hlt">ice</span> features, oceanic and atmospheric forcing at Barrow, Alaska</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Jones, Joshua; Eicken, Hajo; Mahoney, Andrew; MV, Rohith; Kambhamettu, Chandra; Fukamachi, Yasushi; Ohshima, Kay I.; George, J. Craig</p> <p>2016-09-01</p> <p>Landfast <span class="hlt">sea</span> <span class="hlt">ice</span> is an important seasonal feature along most Arctic coastlines, such as that of the Chukchi <span class="hlt">Sea</span> near Barrow, Alaska. Its stability throughout the <span class="hlt">ice</span> season is determined by many factors but grounded pressure ridges are the primary stabilizing component. Landfast <span class="hlt">ice</span> breakouts occur when these grounded ridges fail or unground, and previously stationary <span class="hlt">ice</span> detaches from the coast and drifts away. Using ground-based radar imagery from a coastal <span class="hlt">ice</span> and ocean observatory at Barrow, we have developed a method to estimate the extent of grounded ridges by tracking <span class="hlt">ice</span> motion and deformation over the course of winter and have derived <span class="hlt">ice</span> keel depth and potential for grounding from cumulative convergent <span class="hlt">ice</span> motion. Estimates of landfast <span class="hlt">ice</span> grounding strength have been compared to the atmospheric and oceanic stresses acting on the landfast <span class="hlt">ice</span> before and during breakout events to determine prevailing causes for the failure of stabilizing features. Applying this approach to two case studies in 2008 and 2010, we conclude that a combination of atmospheric and oceanic stresses may have caused the breakouts analyzed in this study, with the latter as the dominant force. Preconditioning (as weakening) of grounded ridges by <span class="hlt">sea</span> level variations may facilitate failure of the <span class="hlt">ice</span> sheet leading to breakout events.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26553610','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26553610"><span>Methane excess in Arctic surface water-triggered by <span class="hlt">sea</span> <span class="hlt">ice</span> formation and melting.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Damm, E; Rudels, B; Schauer, U; Mau, S; Dieckmann, G</p> <p>2015-11-10</p> <p>Arctic amplification of global warming has led to increased summer <span class="hlt">sea</span> <span class="hlt">ice</span> retreat, which influences gas exchange between the Arctic Ocean and the atmosphere where <span class="hlt">sea</span> <span class="hlt">ice</span> previously acted as a physical barrier. Indeed, recently observed enhanced atmospheric methane concentrations in Arctic regions with fractional <span class="hlt">sea-ice</span> cover point to unexpected feedbacks in cycling of methane. We report on methane excess in <span class="hlt">sea</span> <span class="hlt">ice</span>-influenced water masses in the interior Arctic Ocean and provide evidence that <span class="hlt">sea</span> <span class="hlt">ice</span> is a potential source. We show that methane release from <span class="hlt">sea</span> <span class="hlt">ice</span> into the ocean occurs via brine drainage during freezing and melting i.e. in winter and spring. In summer under a fractional <span class="hlt">sea</span> <span class="hlt">ice</span> cover, reduced turbulence restricts gas transfer, then seawater acts as buffer in which methane remains entrained. However, in autumn and winter surface convection initiates pronounced efflux of methane from the <span class="hlt">ice</span> covered ocean to the atmosphere. Our results demonstrate that <span class="hlt">sea</span> <span class="hlt">ice</span>-sourced methane cycles seasonally between <span class="hlt">sea</span> <span class="hlt">ice</span>, <span class="hlt">sea-ice</span>-influenced seawater and the atmosphere, while the deeper ocean remains decoupled. Freshening due to summer <span class="hlt">sea</span> <span class="hlt">ice</span> retreat will enhance this decoupling, which restricts the capacity of the deeper Arctic Ocean to act as a sink for this greenhouse gas.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..16.5573L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..16.5573L"><span>Temporal variatiions of <span class="hlt">Sea</span> <span class="hlt">ice</span> cover in the Baltic <span class="hlt">Sea</span> derived from operational <span class="hlt">sea</span> <span class="hlt">ice</span> products used in NWP.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lange, Martin; Paul, Gerhard; Potthast, Roland</p> <p>2014-05-01</p> <p><span class="hlt">Sea</span> <span class="hlt">ice</span> cover is a crucial parameter for surface fluxes of heat and moisture over water areas. The isolating effect and the much higher albedo strongly reduces the turbulent exchange of heat and moisture from the surface to the atmosphere and allows for cold and dry air mass flow with strong impact on the stability of the whole boundary layer and consequently cloud formation as well as precipitation in the downstream regions. Numerical weather centers as, ECMWF, MetoFrance or DWD use external products to initialize SST and <span class="hlt">sea</span> <span class="hlt">ice</span> cover in their NWP models. To the knowledge of the author there are mainly two global <span class="hlt">sea</span> <span class="hlt">ice</span> products well established with operational availability, one from NOAA NCEP that combines measurements with satellite data, and the other from OSI-SAF derived from SSMI/S sensors. The latter one is used in the Ostia product. DWD additionally uses a regional product for the Baltic <span class="hlt">Sea</span> provided by the national center for shipping and hydrografie which combines observations from ships (and icebreakers) for the German part of the Baltic <span class="hlt">Sea</span> and model analysis from the hydrodynamic HIROMB model of the Swedish meteorological service for the rest of the domain. The temporal evolution of the three different products are compared for a cold period in Februar 2012. Goods and bads will be presented and suggestions for a harmonization of strong day to day jumps over large areas are suggested.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C21C0703A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C21C0703A"><span>Trends in Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> Leads Detection</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ackerman, S. A.; Hoffman, J.; Liu, Y.; Key, J. R.</p> <p>2016-12-01</p> <p><span class="hlt">Sea</span> <span class="hlt">ice</span> leads (fractures) play a critical role in the exchange of mass and energy between the ocean and atmosphere in the polar regions, particularly in the Arctic. Leads result in warming water and accelerated melting because leads absorb more solar energy than the surrounding <span class="hlt">ice</span>. In the autumn, winter, and spring leads impact the local atmospheric structure and cloud properties because of the large flux of heat and moisture into the atmosphere. Given the rapid thinning and loss of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> over the last few decades, changes in the distribution of leads can be expected in response. Leads are largely wind driven, so their distributions will also be affected by the changes in atmospheric circulation that have occurred. From a climate perspective, identifying trends in lead characteristics (width, orientation, and spatial distribution) will advance our understanding of both thermodynamic and mechanical processes. This study presents the spatial and temporal distributions of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> leads since 2002 using a new method to detect and characterize <span class="hlt">sea</span> <span class="hlt">ice</span> leads with optical (visible, infrared) satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS). Using reflective and emissive channels, <span class="hlt">ice</span> concentration is derived in cloud-free regions and used to create a mask of potential leads. An algorithm then uses a combination of image processing techniques to identify and characterizes leads. The results show interannual variability of leads positioning as well as parameters such as area, length, orientation and width.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.G52A..06D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.G52A..06D"><span>Polar <span class="hlt">ice</span>-sheet contributions to <span class="hlt">sea</span> level during past warm periods</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dutton, A.</p> <p>2015-12-01</p> <p>Recent <span class="hlt">sea</span>-level rise has been dominated by thermal expansion and glacier loss, but the contribution from mass loss from the Greenland and Antarctic <span class="hlt">ice</span> sheets is expected to exceed other contributions under future sustained warming. Due to limitations of existing <span class="hlt">ice</span> sheet models and the lack of relevant analogues in the historical record, projecting the timing and magnitude of polar <span class="hlt">ice</span> sheet mass loss in the future remains challenging. One approach to improving our understanding of how polar <span class="hlt">ice</span>-sheet retreat will unfold is to integrate observations and models of <span class="hlt">sea</span> level, <span class="hlt">ice</span> sheets, and climate during past intervals of warmth when the polar <span class="hlt">ice</span> sheets contributed to higher <span class="hlt">sea</span> levels. A recent review evaluated the evidence of polar <span class="hlt">ice</span> sheet mass loss during several warm periods, including interglacials during the mid-Pliocene warm period, Marine Isotope Stage (MIS) 11, 5e (Last Interglacial), and 1 (Holocene). <span class="hlt">Sea</span>-level benchmarks of <span class="hlt">ice</span>-sheet retreat during the first of these three periods, when global mean climate was ~1 to 3 deg. C warmer than preindustrial, are useful for understanding the long-term potential for future <span class="hlt">sea</span>-level rise. Despite existing uncertainties in these reconstructions, it is clear that our present climate is warming to a level associated with significant polar <span class="hlt">ice</span>-sheet loss in the past, resulting in a conservative estimate for a global mean <span class="hlt">sea</span>-level rise of 6 meters above present (or more). This presentation will focus on identifying the approaches that have yielded significant advances in terms of past <span class="hlt">sea</span> level and <span class="hlt">ice</span> sheet reconstruction as well as outstanding challenges. A key element of recent advances in <span class="hlt">sea</span>-level reconstructions is the ability to recognize and quantify the imprint of geophysical processes, such as glacial isostatic adjustment (GIA) and dynamic topography, that lead to significant spatial variability in <span class="hlt">sea</span> level reconstructions. Identifying specific <span class="hlt">ice</span>-sheet sources that contributed to higher <span class="hlt">sea</span> levels</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.C43A0585U','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.C43A0585U"><span>Changes and variations in the turning angle of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ukita, J.; Honda, M.; Ishizuka, S.</p> <p>2012-12-01</p> <p>The motion of <span class="hlt">sea</span> <span class="hlt">ice</span> is under influences of forcing from winds and currents and of <span class="hlt">sea</span> <span class="hlt">ice</span> properties. In facing rapidly changing Arctic climate we are interested in whether we observe and quantify changes in <span class="hlt">sea</span> <span class="hlt">ice</span> conditions reflected in its velocity field. Theoretical consideration on the freedrift model predicts a change in the <span class="hlt">sea</span> <span class="hlt">ice</span> turning angle with respect to the direction of forcing wind in association with thinning <span class="hlt">sea</span> <span class="hlt">ice</span> thickness. Possible changes in atmospheric and ocean boundary layer conditions may be reflected in the <span class="hlt">sea</span> <span class="hlt">ice</span> turning angle through modification of both atmospheric and oceanic Ekman spirals. With these in mind this study examines statistical properties of the turning angle of the Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> and compares them with atmospheric/<span class="hlt">ice</span>/ocean conditions for the period of 1979-2010 on the basis of IABP buoy data. Preliminary results indicate that over this period the turning angle has varying trends depending on different seasons. We found weakly significant (>90% level) changes in the turning angle from August to October with the maximum trend in October. The direction of trends is counter-clockwise with respect to the geostrophic wind direction, which is consistent with the thinning of <span class="hlt">sea</span> <span class="hlt">ice</span>. The interannual variability of the turning angle for this peak season of the reduced <span class="hlt">sea</span> <span class="hlt">ice</span> cover is not the same as that of the Arctic SIE. However, in recent years the turning angle appears to covary with the surface air temperature, providing supporting evidence for the relationship between the angle and <span class="hlt">sea</span> <span class="hlt">ice</span> thickness. In the presentation we will provide results on the relationships between the turning angle and atmospheric and oceanic variables and further discuss their implications.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-GSFC_20171208_Archive_e000190.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-GSFC_20171208_Archive_e000190.html"><span>Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> Is Losing Its Bulwark Against Warming Summers</span></a></p> <p><a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a></p> <p></p> <p>2017-12-08</p> <p>Arctic <span class="hlt">sea</span> <span class="hlt">ice</span>, the vast sheath of frozen seawater floating on the Arctic Ocean and its neighboring <span class="hlt">seas</span>, has been hit with a double whammy over the past decades: as its extent shrunk, the oldest and thickest <span class="hlt">ice</span> has either thinned or melted away, leaving the <span class="hlt">sea</span> <span class="hlt">ice</span> cap more vulnerable to the warming ocean and atmosphere. “What we’ve seen over the years is that the older <span class="hlt">ice</span> is disappearing,” said Walt Meier, a <span class="hlt">sea</span> <span class="hlt">ice</span> researcher at NASA’s Goddard Space Flight Center in Greenbelt, Maryland. “This older, thicker <span class="hlt">ice</span> is like the bulwark of <span class="hlt">sea</span> <span class="hlt">ice</span>: a warm summer will melt all the young, thin <span class="hlt">ice</span> away but it can’t completely get rid of the older <span class="hlt">ice</span>. But this older <span class="hlt">ice</span> is becoming weaker because there’s less of it and the remaining old <span class="hlt">ice</span> is more broken up and thinner, so that bulwark is not as good as it used to be.” Read more: go.nasa.gov/2dPJ9zT NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUOSHE34A1464B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUOSHE34A1464B"><span>An Investigation of Mineral Dynamics in <span class="hlt">Sea</span> <span class="hlt">Ice</span> by Solubility Measurements</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Butler, B.; Kennedy, H.; Papadimitriou, S.</p> <p>2016-02-01</p> <p><span class="hlt">Sea</span> <span class="hlt">ice</span> is a composite material with a sponge-like structure. The framework of the structure is composed of pure <span class="hlt">ice</span>, and within the pores exists a concentrated seawater brine. When the temperature is reduced, the volume of this residual brine decreases, while its salinity increases. As a result of the paired changes to temperature and salinity, the brine becomes supersaturated with respect to a mineral at several points when cooling <span class="hlt">sea</span> <span class="hlt">ice</span> towards -30°C, creating a sequence of minerals that precipitate. The presence of countless microscopic salt crystals encapsulated within the <span class="hlt">ice</span>, coupled with changes in brine volume associated with their precipitation/dissolution, results in changes to the optical and structural properties of the medium that contribute to the surface energy balance in <span class="hlt">sea</span> <span class="hlt">ice</span> environments. Furthermore, attainment of mineral equilibrium can result in abrupt changes in brine composition and osmotic conditions in the isolated brine pockets, imposing challenging conditions upon the biota that habitat the <span class="hlt">sea</span> <span class="hlt">ice</span> environment. Mirabilite (Na2SO4.10H2O), gypsum (CaSO4.2H2O) and hydrohalite (NaCl.2H2O) each represent minerals that are understood to exist within <span class="hlt">sea</span> <span class="hlt">ice</span>. Previous research has focused upon mineral extraction/detection, and the specific temperature for the onset of each minerals precipitation in <span class="hlt">sea</span> <span class="hlt">ice</span>; rather than the overarching dynamics. For this reason, solubility measurements of mirabilite, gypsum and hydrohalite in conditions representative of equilibrium <span class="hlt">sea</span> <span class="hlt">ice</span> brines were carried between 0 and -28°C, covering a range of undersaturated and supersaturated conditions for each mineral. Results provide accurate data for the onset of each minerals formation in <span class="hlt">sea</span> <span class="hlt">ice</span>, as well as important information on the way in which precipitation and dissolution reactions are affected when <span class="hlt">sea</span> <span class="hlt">ice</span> warms or cools. By incorporating the solubility data into a model that simluates the temperature-salinity profiles of first-year <span class="hlt">sea</span> <span class="hlt">ice</span>, the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3048104','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3048104"><span>Exopolymer alteration of physical properties of <span class="hlt">sea</span> <span class="hlt">ice</span> and implications for <span class="hlt">ice</span> habitability and biogeochemistry in a warmer Arctic</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Krembs, Christopher; Eicken, Hajo; Deming, Jody W.</p> <p>2011-01-01</p> <p>The physical properties of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> determine its habitability. Whether <span class="hlt">ice</span>-dwelling organisms can change those properties has rarely been addressed. Following discovery that <span class="hlt">sea</span> <span class="hlt">ice</span> contains an abundance of gelatinous extracellular polymeric substances (EPS), we examined the effects of algal EPS on the microstructure and salt retention of <span class="hlt">ice</span> grown from saline solutions containing EPS from a culture of the <span class="hlt">sea-ice</span> diatom, Melosira arctica. We also experimented with xanthan gum and with EPS from a culture of the cold-adapted bacterium Colwellia psychrerythraea strain 34H. Quantitative microscopic analyses of the artificial <span class="hlt">ice</span> containing Melosira EPS revealed convoluted <span class="hlt">ice</span>-pore morphologies of high fractal dimension, mimicking features found in EPS-rich coastal <span class="hlt">sea</span> <span class="hlt">ice</span>, whereas EPS-free (control) <span class="hlt">ice</span> featured much simpler pore geometries. A heat-sensitive glycoprotein fraction of Melosira EPS accounted for complex pore morphologies. Although all tested forms of EPS increased bulk <span class="hlt">ice</span> salinity (by 11–59%) above the controls, <span class="hlt">ice</span> containing native Melosira EPS retained the most salt. EPS effects on <span class="hlt">ice</span> and pore microstructure improve <span class="hlt">sea</span> <span class="hlt">ice</span> habitability, survivability, and potential for increased primary productivity, even as they may alter the persistence and biogeochemical imprint of <span class="hlt">sea</span> <span class="hlt">ice</span> on the surface ocean in a warming climate. PMID:21368216</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li class="active"><span>20</span></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_20 --> <div id="page_21" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li class="active"><span>21</span></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="401"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/21368216','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/21368216"><span>Exopolymer alteration of physical properties of <span class="hlt">sea</span> <span class="hlt">ice</span> and implications for <span class="hlt">ice</span> habitability and biogeochemistry in a warmer Arctic.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Krembs, Christopher; Eicken, Hajo; Deming, Jody W</p> <p>2011-03-01</p> <p>The physical properties of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> determine its habitability. Whether <span class="hlt">ice</span>-dwelling organisms can change those properties has rarely been addressed. Following discovery that <span class="hlt">sea</span> <span class="hlt">ice</span> contains an abundance of gelatinous extracellular polymeric substances (EPS), we examined the effects of algal EPS on the microstructure and salt retention of <span class="hlt">ice</span> grown from saline solutions containing EPS from a culture of the <span class="hlt">sea-ice</span> diatom, Melosira arctica. We also experimented with xanthan gum and with EPS from a culture of the cold-adapted bacterium Colwellia psychrerythraea strain 34H. Quantitative microscopic analyses of the artificial <span class="hlt">ice</span> containing Melosira EPS revealed convoluted <span class="hlt">ice</span>-pore morphologies of high fractal dimension, mimicking features found in EPS-rich coastal <span class="hlt">sea</span> <span class="hlt">ice</span>, whereas EPS-free (control) <span class="hlt">ice</span> featured much simpler pore geometries. A heat-sensitive glycoprotein fraction of Melosira EPS accounted for complex pore morphologies. Although all tested forms of EPS increased bulk <span class="hlt">ice</span> salinity (by 11-59%) above the controls, <span class="hlt">ice</span> containing native Melosira EPS retained the most salt. EPS effects on <span class="hlt">ice</span> and pore microstructure improve <span class="hlt">sea</span> <span class="hlt">ice</span> habitability, survivability, and potential for increased primary productivity, even as they may alter the persistence and biogeochemical imprint of <span class="hlt">sea</span> <span class="hlt">ice</span> on the surface ocean in a warming climate.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007AGUFM.C21C..01W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007AGUFM.C21C..01W"><span>Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> Thickness - Past, Present And Future</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wadhams, P.</p> <p>2007-12-01</p> <p>In November 2005 the International Workshop on Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> Thickness: Past, Present and Future was held at Rungstedgaard Conference Center, near Copenhagen, Denmark. The proceedings of the Workshop were subsequently published as a book by the European Commission. In this review we summarise the conclusions of the Workshop on the techniques which show the greatest promise for thickness monitoring on different spatial and temporal scales, and for different purposes. Sonic methods, EM techniques, buoys and satellite methods will be considered. Some copies of the book will be available at the lecture, and others can be ordered from the European Commission. The paper goes on to consider early results from some of the latest measurements on Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> thickness done in 2007. These comprise a trans-Arctic voyage by a UK submarine, HMS "Tireless", equipped with a Kongsberg 3002 multibeam sonar which generates a 3-D digital terrain map of the <span class="hlt">ice</span> underside; and experiments at the APLIS <span class="hlt">ice</span> station in the Beaufort <span class="hlt">Sea</span> carried out by the Gavia AUV equipped with a GeoSwath interferometric sonar. In both cases 3-D mapping of <span class="hlt">sea</span> <span class="hlt">ice</span> constitutes a new step forward in <span class="hlt">sea</span> <span class="hlt">ice</span> data collection, but in the case of the submarine the purpose is to map change in <span class="hlt">ice</span> thickness (comparing results with a 2004 "Tireless" cruise and with US and UK data prior to 2000), while for the small AUV the purpose is intensive local mapping of a few ridges to improve our knowledge of their structure, as part of a multisensor programme</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C33E..07F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C33E..07F"><span>Routine Mapping of the Snow Depth Distribution on <span class="hlt">Sea</span> <span class="hlt">Ice</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Farrell, S. L.; Newman, T.; Richter-Menge, J.; Dattler, M.; Paden, J. D.; Yan, S.; Li, J.; Leuschen, C.</p> <p>2016-12-01</p> <p>The annual growth and retreat of the polar <span class="hlt">sea</span> <span class="hlt">ice</span> cover is influenced by the seasonal accumulation, redistribution and melt of snow on <span class="hlt">sea</span> <span class="hlt">ice</span>. Due to its high albedo and low thermal conductivity, snow is also a controlling parameter in the mass and energy budgets of the polar climate system. Under a changing climate scenario it is critical to obtain reliable and routine measurements of snow depth, across basin scales, and long time periods, so as to understand regional, seasonal and inter-annual variability, and the subsequent impacts on the <span class="hlt">sea</span> <span class="hlt">ice</span> cover itself. Moreover the snow depth distribution remains a significant source of uncertainty in the derivation of <span class="hlt">sea</span> <span class="hlt">ice</span> thickness from remote sensing measurements, as well as in numerical model predictions of future climate state. Radar altimeter systems flown onboard NASA's Operation <span class="hlt">Ice</span>Bridge (OIB) mission now provide annual measurements of snow across both the Arctic and Southern Ocean <span class="hlt">ice</span> packs. We describe recent advances in the processing techniques used to interpret airborne radar waveforms and produce accurate and robust snow depth results. As a consequence of instrument effects and data quality issues associated with the initial release of the OIB airborne radar data, the entire data set was reprocessed to remove coherent noise and sidelobes in the radar echograms. These reprocessed data were released to the community in early 2016, and are available for improved derivation of snow depth. Here, using the reprocessed data, we present the results of seven years of radar measurements collected over Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> at the end of winter, just prior to melt. Our analysis provides the snow depth distribution on both seasonal and multi-year <span class="hlt">sea</span> <span class="hlt">ice</span>. We present the inter-annual variability in snow depth for both the Central Arctic and the Beaufort/Chukchi <span class="hlt">Seas</span>. We validate our results via comparison with temporally and spatially coincident in situ measurements gathered during many of the OIB surveys. The results</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4963477','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4963477"><span><span class="hlt">Sea</span> <span class="hlt">ice</span> and millennial-scale climate variability in the Nordic <span class="hlt">seas</span> 90 kyr ago to present</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Hoff, Ulrike; Rasmussen, Tine L.; Stein, Ruediger; Ezat, Mohamed M.; Fahl, Kirsten</p> <p>2016-01-01</p> <p>In the light of rapidly diminishing <span class="hlt">sea</span> <span class="hlt">ice</span> cover in the Arctic during the present atmospheric warming, it is imperative to study the distribution of <span class="hlt">sea</span> <span class="hlt">ice</span> in the past in relation to rapid climate change. Here we focus on glacial millennial-scale climatic events (Dansgaard/Oeschger events) using the <span class="hlt">sea</span> <span class="hlt">ice</span> proxy IP25 in combination with phytoplankton proxy data and quantification of diatom species in a record from the southeast Norwegian <span class="hlt">Sea</span>. We demonstrate that expansion and retreat of <span class="hlt">sea</span> <span class="hlt">ice</span> varies consistently in pace with the rapid climate changes 90 kyr ago to present. <span class="hlt">Sea</span> <span class="hlt">ice</span> retreats abruptly at the start of warm interstadials, but spreads rapidly during cooling phases of the interstadials and becomes near perennial and perennial during cold stadials and Heinrich events, respectively. Low-salinity surface water and the <span class="hlt">sea</span> <span class="hlt">ice</span> edge spreads to the Greenland–Scotland Ridge, and during the largest Heinrich events, probably far into the Atlantic Ocean. PMID:27456826</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27456826','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27456826"><span><span class="hlt">Sea</span> <span class="hlt">ice</span> and millennial-scale climate variability in the Nordic <span class="hlt">seas</span> 90 kyr ago to present.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Hoff, Ulrike; Rasmussen, Tine L; Stein, Ruediger; Ezat, Mohamed M; Fahl, Kirsten</p> <p>2016-07-26</p> <p>In the light of rapidly diminishing <span class="hlt">sea</span> <span class="hlt">ice</span> cover in the Arctic during the present atmospheric warming, it is imperative to study the distribution of <span class="hlt">sea</span> <span class="hlt">ice</span> in the past in relation to rapid climate change. Here we focus on glacial millennial-scale climatic events (Dansgaard/Oeschger events) using the <span class="hlt">sea</span> <span class="hlt">ice</span> proxy IP25 in combination with phytoplankton proxy data and quantification of diatom species in a record from the southeast Norwegian <span class="hlt">Sea</span>. We demonstrate that expansion and retreat of <span class="hlt">sea</span> <span class="hlt">ice</span> varies consistently in pace with the rapid climate changes 90 kyr ago to present. <span class="hlt">Sea</span> <span class="hlt">ice</span> retreats abruptly at the start of warm interstadials, but spreads rapidly during cooling phases of the interstadials and becomes near perennial and perennial during cold stadials and Heinrich events, respectively. Low-salinity surface water and the <span class="hlt">sea</span> <span class="hlt">ice</span> edge spreads to the Greenland-Scotland Ridge, and during the largest Heinrich events, probably far into the Atlantic Ocean.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19840008345&hterms=feeling&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dfeeling','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19840008345&hterms=feeling&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dfeeling"><span>Radar image interpretation techniques applied to <span class="hlt">sea</span> <span class="hlt">ice</span> geophysical problems</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Carsey, F. D.</p> <p>1983-01-01</p> <p>The geophysical science problems in the <span class="hlt">sea</span> <span class="hlt">ice</span> area which at present concern understanding the <span class="hlt">ice</span> budget, where <span class="hlt">ice</span> is formed, how thick it grows and where it melts, and the processes which control the interaction of air-<span class="hlt">sea</span> and <span class="hlt">ice</span> at the <span class="hlt">ice</span> margins is discussed. The science problems relate to basic questions of <span class="hlt">sea</span> <span class="hlt">ice</span>: how much is there, thickness, drift rate, production rate, determination of the morphology of the <span class="hlt">ice</span> margin, storms feeling for the <span class="hlt">ice</span>, storms and influence at the margin to alter the pack, and ocean response to a storm at the margin. Some of these questions are descriptive and some require complex modeling of interactions between the <span class="hlt">ice</span>, the ocean, the atmosphere and the radiation fields. All involve measurements of the character of the <span class="hlt">ice</span> pack, and SAR plays a significant role in the measurements.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2629232','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2629232"><span>Nonlinear threshold behavior during the loss of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span></span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Eisenman, I.; Wettlaufer, J. S.</p> <p>2009-01-01</p> <p>In light of the rapid recent retreat of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span>, a number of studies have discussed the possibility of a critical threshold (or “tipping point”) beyond which the ice–albedo feedback causes the <span class="hlt">ice</span> cover to melt away in an irreversible process. The focus has typically been centered on the annual minimum (September) <span class="hlt">ice</span> cover, which is often seen as particularly susceptible to destabilization by the ice–albedo feedback. Here, we examine the central physical processes associated with the transition from <span class="hlt">ice</span>-covered to <span class="hlt">ice</span>-free Arctic Ocean conditions. We show that although the ice–albedo feedback promotes the existence of multiple <span class="hlt">ice</span>-cover states, the stabilizing thermodynamic effects of <span class="hlt">sea</span> <span class="hlt">ice</span> mitigate this when the Arctic Ocean is <span class="hlt">ice</span> covered during a sufficiently large fraction of the year. These results suggest that critical threshold behavior is unlikely during the approach from current perennial <span class="hlt">sea-ice</span> conditions to seasonally <span class="hlt">ice</span>-free conditions. In a further warmed climate, however, we find that a critical threshold associated with the sudden loss of the remaining wintertime-only <span class="hlt">sea</span> <span class="hlt">ice</span> cover may be likely. PMID:19109440</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19830043095&hterms=cinematography&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dcinematography','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19830043095&hterms=cinematography&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dcinematography"><span><span class="hlt">Sea</span> <span class="hlt">ice</span> motion measurements from Seasat SAR images</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Leberl, F.; Raggam, J.; Elachi, C.; Campbell, W. J.</p> <p>1983-01-01</p> <p>Data from the Seasat synthetic aperture radar (SAR) experiment are analyzed in order to determine the accuracy of this information for mapping the distribution of <span class="hlt">sea</span> <span class="hlt">ice</span> and its motion. Data from observations of <span class="hlt">sea</span> <span class="hlt">ice</span> in the Beaufort <span class="hlt">Sea</span> from seven sequential orbits of the satellite were selected to study the capabilities and limitations of spaceborne radar application to <span class="hlt">sea-ice</span> mapping. Results show that there is no difficulty in identifying homologue <span class="hlt">ice</span> features on sequential radar images and the accuracy is entirely controlled by the accuracy of the orbit data and the geometric calibration of the sensor. Conventional radargrammetric methods are found to serve well for satellite radar <span class="hlt">ice</span> mapping, while ground control points can be used to calibrate the <span class="hlt">ice</span> location and motion measurements in the cases where orbit data and sensor calibration are lacking. The <span class="hlt">ice</span> motion was determined to be approximately 6.4 + or - 0.5 km/day. In addition, the accuracy of pixel location was found over land areas. The use of one control point in 10,000 sq km produced an accuracy of about + or 150 m, while with a higher density of control points (7 in 1000 sq km) the location accuracy improves to the image resolution of + or - 25 m. This is found to be applicable for both optical and digital data.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMPA31D..08N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMPA31D..08N"><span>Transnational <span class="hlt">Sea-Ice</span> Transport in a Warmer, More Mobile Arctic</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Newton, R.; Tremblay, B.; Pfirman, S. L.; DeRepentigny, P.</p> <p>2015-12-01</p> <p>As the Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> thins, summer <span class="hlt">ice</span> continues to shrink in its area, and multi-year <span class="hlt">ice</span> becomes rarer, winter <span class="hlt">ice</span> is not disappearing from the Arctic Basin. Rather, it is ever more dominated by first year <span class="hlt">ice</span>. And each summer, as the total coverage withdraws, the first year <span class="hlt">ice</span> is able travel faster and farther, carrying any <span class="hlt">ice</span>-rafted material with it. Micro-organisms, sediments, pollutants and river runoff all move across the Arctic each summer and are deposited hundreds of kilometers from their origins. Analyzing Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> drift patterns in the context of the exclusive economic zones (EEZs) of the Arctic nations raises concerns about the changing fate of "alien" <span class="hlt">ice</span> which forms within one country's EEZ, then drifts and melts in another country's EEZ. We have developed a new data set from satellite-based <span class="hlt">ice</span>-drift data that allows us to track groups of <span class="hlt">ice</span> "pixels" forward from their origin to their destination, or backwards from their melting location to their point of formation. The software has been integrated with model output to extend the tracking of <span class="hlt">sea</span> <span class="hlt">ice</span> to include climate projections. Results indicate, for example, that Russian <span class="hlt">sea</span> <span class="hlt">ice</span> dominates "imports" to the EEZ of Norway, as expected, but with increasing <span class="hlt">ice</span> mobility it is also is exported into the EEZs of other countries, including Canada and the United States. Regions of potential conflict are identified, including several national borders with extensive and/or changing transboundary <span class="hlt">sea</span> <span class="hlt">ice</span> transport. These data are a starting point for discussion of transborder questions raised by "alien" <span class="hlt">ice</span> and the material it may import from one nation's EEZ to another's.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25885562','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25885562"><span>In situ expression of eukaryotic <span class="hlt">ice</span>-binding proteins in microbial communities of Arctic and Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span>.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Uhlig, Christiane; Kilpert, Fabian; Frickenhaus, Stephan; Kegel, Jessica U; Krell, Andreas; Mock, Thomas; Valentin, Klaus; Beszteri, Bánk</p> <p>2015-11-01</p> <p><span class="hlt">Ice</span>-binding proteins (IBPs) have been isolated from various <span class="hlt">sea-ice</span> organisms. Their characterisation points to a crucial role in protecting the organisms in sub-zero environments. However, their in situ abundance and diversity in natural <span class="hlt">sea-ice</span> microbial communities is largely unknown. In this study, we analysed the expression and phylogenetic diversity of eukaryotic IBP transcripts from microbial communities of Arctic and Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span>. IBP transcripts were found in abundances similar to those of proteins involved in core cellular processes such as photosynthesis. Eighty-nine percent of the IBP transcripts grouped with known IBP sequences from diatoms, haptophytes and crustaceans, but the majority represented novel sequences not previously characterized in cultured organisms. The observed high eukaryotic IBP expression in natural eukaryotic <span class="hlt">sea</span> <span class="hlt">ice</span> communities underlines the essential role of IBPs for survival of many microorganisms in communities living under the extreme conditions of polar <span class="hlt">sea</span> <span class="hlt">ice</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015PhDT.......484S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015PhDT.......484S"><span><span class="hlt">Sea-ice</span> habitat preference of the Pacific walrus (Odobenus rosmarus divergens) in the Bering <span class="hlt">Sea</span>: A multiscaled approach</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sacco, Alexander Edward</p> <p></p> <p>The goal of this thesis is to define specific parameters of mesoscale <span class="hlt">sea-ice</span> seascapes for which walruses show preference during important periods of their natural history. This research thesis incorporates <span class="hlt">sea-ice</span> geophysics, marine-mammal ecology, remote sensing, computer vision techniques, and traditional ecological knowledge of indigenous subsistence hunters in order to quantitatively study walrus preference of <span class="hlt">sea</span> <span class="hlt">ice</span> during the spring migration in the Bering <span class="hlt">Sea</span>. Using an approach that applies seascape ecology, or landscape ecology to the marine environment, our goal is to define specific parameters of <span class="hlt">ice</span> patch descriptors, or mesoscale seascapes in order to evaluate and describe potential walrus preference for such <span class="hlt">ice</span> and the ecological services it provides during an important period of their life-cycle. The importance of specific <span class="hlt">sea-ice</span> properties to walrus occupation motivates an investigation into how walruses use <span class="hlt">sea</span> <span class="hlt">ice</span> at multiple spatial scales when previous research suggests that walruses do not show preference for particular floes. Analysis of aerial imagery, using image processing techniques and digital geomorphometric measurements (floe size, shape, and arrangement), demonstrated that while a particular floe may not be preferred, at larger scales a collection of floes, specifically an <span class="hlt">ice</span> patch (< 4 km2), was preferred. This shows that walruses occupy <span class="hlt">ice</span> patches with distinct <span class="hlt">ice</span> features such as floe convexity, spatial density, and young <span class="hlt">ice</span> and open water concentration. <span class="hlt">Ice</span> patches that are occupied by adult and juvenile walruses show a small number of characteristics that vary from those <span class="hlt">ice</span> patches that were visually unoccupied. Using synthetic aperture radar imagery, we analyzed co-located walrus observations and statistical texture analysis of radar imagery to quantify seascape preferences of walruses during the spring migration. At a coarse resolution of 100 -- 9,000 km2, seascape analysis shows that, for the years 2006 -- 2008</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C24B..04Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C24B..04Z"><span><span class="hlt">Sea</span> <span class="hlt">Ice</span> Concentration Estimation Using Active and Passive Remote Sensing Data Fusion</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhang, Y.; Li, F.; Zhang, S.; Zhu, T.</p> <p>2017-12-01</p> <p>In this abstract, a decision-level fusion method by utilizing SAR and passive microwave remote sensing data for <span class="hlt">sea</span> <span class="hlt">ice</span> concentration estimation is investigated. <span class="hlt">Sea</span> <span class="hlt">ice</span> concentration product from passive microwave concentration retrieval methods has large uncertainty within thin <span class="hlt">ice</span> zone. Passive microwave data including SSM/I, AMSR-E, and AMSR-2 provide daily and long time series observations covering whole polar <span class="hlt">sea</span> <span class="hlt">ice</span> scene, and SAR images provide rich <span class="hlt">sea</span> <span class="hlt">ice</span> details with high spatial resolution including deformation and polarimetric features. In the proposed method, the merits from passive microwave data and SAR data are considered. <span class="hlt">Sea</span> <span class="hlt">ice</span> concentration products from ASI and <span class="hlt">sea</span> <span class="hlt">ice</span> category label derived from CRF framework in SAR imagery are calibrated under least distance protocol. For SAR imagery, incident angle and azimuth angle were used to correct backscattering values from slant range to ground range in order to improve geocoding accuracy. The posterior probability distribution between category label from SAR imagery and passive microwave <span class="hlt">sea</span> <span class="hlt">ice</span> concentration product is modeled and integrated under Bayesian network, where Gaussian statistical distribution from ASI <span class="hlt">sea</span> <span class="hlt">ice</span> concentration products serves as the prior term, which represented as an uncertainty of <span class="hlt">sea</span> <span class="hlt">ice</span> concentration. Empirical model based likelihood term is constructed under Bernoulli theory, which meets the non-negative and monotonically increasing conditions. In the posterior probability estimation procedure, final <span class="hlt">sea</span> <span class="hlt">ice</span> concentration is obtained using MAP criterion, which equals to minimize the cost function and it can be calculated with nonlinear iteration method. The proposed algorithm is tested on multiple satellite SAR data sets including GF-3, Sentinel-1A, RADARSAT-2 and Envisat ASAR. Results show that the proposed algorithm can improve the accuracy of ASI <span class="hlt">sea</span> <span class="hlt">ice</span> concentration products and reduce the uncertainty along the <span class="hlt">ice</span> edge.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20060032490&hterms=sonar&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dsonar','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20060032490&hterms=sonar&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dsonar"><span>Combined Satellite - and ULS-Derived <span class="hlt">Sea-Ice</span> Flux in the Weddell <span class="hlt">Sea</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Drinkwater, M.; Liu, X.; Harms, S.</p> <p>2000-01-01</p> <p>Several years of daily microwave satellite <span class="hlt">ice</span>-drift are combined with moored Upward Looking Sonar (ULS) <span class="hlt">ice</span>-drafts into an <span class="hlt">ice</span> volume flux record at points along a flux gate across the Weddell <span class="hlt">Sea</span>, Antarctica.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JGRC..122.9110V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JGRC..122.9110V"><span>A Model of Icebergs and <span class="hlt">Sea</span> <span class="hlt">Ice</span> in a Joint Continuum Framework</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>VaÅková, Irena; Holland, David M.</p> <p>2017-11-01</p> <p>The <span class="hlt">ice</span> mélange, a mixture of <span class="hlt">sea</span> <span class="hlt">ice</span> and icebergs, often present in front of outlet glaciers in Greenland or <span class="hlt">ice</span> shelves in Antarctica, can have a profound effect on the dynamics of the <span class="hlt">ice</span>-ocean system. The current inability to numerically model the <span class="hlt">ice</span> mélange motivates a new modeling approach proposed here. A continuum <span class="hlt">sea-ice</span> model is taken as a starting point and icebergs are represented as thick and compact pieces of <span class="hlt">sea</span> <span class="hlt">ice</span> held together by large tensile and shear strength, selectively introduced into the <span class="hlt">sea-ice</span> rheology. In order to modify the rheology correctly, an iceberg tracking procedure is implemented within a semi-Lagrangian time-stepping scheme, designed to exactly preserve iceberg shape through time. With the proposed treatment, <span class="hlt">sea</span> <span class="hlt">ice</span> and icebergs are considered a single fluid with spatially varying rheological properties. Mutual interactions are thus automatically included without the need for further parametrization. An important advantage of the presented framework for an <span class="hlt">ice</span> mélange model is its potential to be easily included within <span class="hlt">sea-ice</span> components of existing climate models.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015JGRC..120.8327H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015JGRC..120.8327H"><span>Short-term <span class="hlt">sea</span> <span class="hlt">ice</span> forecasting: An assessment of <span class="hlt">ice</span> concentration and <span class="hlt">ice</span> drift forecasts using the U.S. Navy's Arctic Cap Nowcast/Forecast System</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hebert, David A.; Allard, Richard A.; Metzger, E. Joseph; Posey, Pamela G.; Preller, Ruth H.; Wallcraft, Alan J.; Phelps, Michael W.; Smedstad, Ole Martin</p> <p>2015-12-01</p> <p>In this study the forecast skill of the U.S. Navy operational Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> forecast system, the Arctic Cap Nowcast/Forecast System (ACNFS), is presented for the period February 2014 to June 2015. ACNFS is designed to provide short term, 1-7 day forecasts of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> and ocean conditions. Many quantities are forecast by ACNFS; the most commonly used include <span class="hlt">ice</span> concentration, <span class="hlt">ice</span> thickness, <span class="hlt">ice</span> velocity, <span class="hlt">sea</span> surface temperature, <span class="hlt">sea</span> surface salinity, and <span class="hlt">sea</span> surface velocities. <span class="hlt">Ice</span> concentration forecast skill is compared to a persistent <span class="hlt">ice</span> state and historical <span class="hlt">sea</span> <span class="hlt">ice</span> climatology. Skill scores are focused on areas where <span class="hlt">ice</span> concentration changes by ±5% or more, and are therefore limited to primarily the marginal <span class="hlt">ice</span> zone. We demonstrate that ACNFS forecasts are skilful compared to assuming a persistent <span class="hlt">ice</span> state, especially beyond 24 h. ACNFS is also shown to be particularly skilful compared to a climatologic state for forecasts up to 102 h. Modeled <span class="hlt">ice</span> drift velocity is compared to observed buoy data from the International Arctic Buoy Programme. A seasonal bias is shown where ACNFS is slower than IABP velocity in the summer months and faster in the winter months. In February 2015, ACNFS began to assimilate a blended <span class="hlt">ice</span> concentration derived from Advanced Microwave Scanning Radiometer 2 (AMSR2) and the Interactive Multisensor Snow and <span class="hlt">Ice</span> Mapping System (IMS). Preliminary results show that assimilating AMSR2 blended with IMS improves the short-term forecast skill and <span class="hlt">ice</span> edge location compared to the independently derived National <span class="hlt">Ice</span> Center <span class="hlt">Ice</span> Edge product.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009EOSTr..90R.169P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009EOSTr..90R.169P"><span>Developing and Implementing Protocols for Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> Observations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Perovich, Donald K.; Gerland, Sebastian</p> <p>2009-05-01</p> <p>Arctic Surface-Based <span class="hlt">Sea</span> <span class="hlt">Ice</span> Observations: Integrated Protocols and Coordinated Data Acquisition; Tromsø, Norway, 26-27 January 2009; The Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> cover is diminishing. Over the past several years, not only has <span class="hlt">ice</span> thinned but the extent of <span class="hlt">ice</span> at the end of summer, and hence perennial <span class="hlt">ice</span>, has declined markedly. These changes affect a wide range of issues and are important for a varied group of stakeholders, including Arctic coastal communities, policy makers, industry, the scientific community, and the public. Concerns range from the role of <span class="hlt">sea</span> <span class="hlt">ice</span> cover as an indicator and amplifier of climate change to marine transportation, resource extraction, and coastal erosion. To understand and respond to these ongoing changes, it is imperative to develop and implement consistent and robust observational protocols that can be used to describe the current state of the <span class="hlt">ice</span> cover as well as future changes.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016DSRII.131....7H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016DSRII.131....7H"><span>SIPEX 2012: Extreme <span class="hlt">sea-ice</span> and atmospheric conditions off East Antarctica</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Heil, P.; Stammerjohn, S.; Reid, P.; Massom, R. A.; Hutchings, J. K.</p> <p>2016-09-01</p> <p>In 2012, Antarctic <span class="hlt">sea-ice</span> coverage was marked by weak annual-mean climate anomalies that consisted of opposing anomalies early and late in the year (some setting new records) which were interspersed by near-average conditions for most of the austral autumn and winter. Here, we investigate the ocean-<span class="hlt">ice</span>-atmosphere system off East Antarctica, prior to and during the <span class="hlt">Sea</span> <span class="hlt">Ice</span> Physics and Ecosystems eXperiment [SIPEX] 2012, by exploring relationships between atmospheric and oceanic forcing together with the <span class="hlt">sea-ice</span> and snow characteristics. During August and September 2012, just prior to SIPEX 2012, atmospheric circulation over the Southern Ocean was near-average, setting up the ocean-<span class="hlt">ice</span>-atmosphere system for near-average conditions. However, below-average surface pressure and temperature as well as strengthened circumpolar winds prevailed during June and July 2012. This led to a new record (19.48×106 km2) in maximum Antarctic <span class="hlt">sea-ice</span> extent recorded in late September. In contrast to the weak circum-Antarctic conditions, the East Antarctic sector (including the SIPEX 2012 region) experienced positive <span class="hlt">sea-ice</span> extent and concentration anomalies during most of 2012, coincident with negative atmospheric pressure and <span class="hlt">sea</span>-surface temperature anomalies. Heavily deformed <span class="hlt">sea</span> <span class="hlt">ice</span> appeared to be associated with intensified wind stress due to increased cyclonicity as well as an increased influx of <span class="hlt">sea</span> <span class="hlt">ice</span> from the east. This increased westward <span class="hlt">ice</span> flux is likely linked to the break-up of nearly 80% of the Mertz Glacier Tongue in 2010, which strongly modified the coastal configuration and hence the width of the westward coastal current. Combined with favourable atmospheric conditions the associated changed coastal configuration allowed more <span class="hlt">sea</span> <span class="hlt">ice</span> to remain within the coastal current at the expense of a reduced northward flow in the region around 141°-145°E. In addition a westward propagating positive anomaly of <span class="hlt">sea-ice</span> extent from the western Ross <span class="hlt">Sea</span> during austral winter</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19980237537','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19980237537"><span>Spatial Distribution of Trends and Seasonality in the Hemispheric <span class="hlt">Sea</span> <span class="hlt">Ice</span> Covers</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Gloersen, P.; Parkinson, C. L.; Cavalieri, D. J.; Cosmiso, J. C.; Zwally, H. J.</p> <p>1998-01-01</p> <p>We extend earlier analyses of a 9-year <span class="hlt">sea</span> <span class="hlt">ice</span> data set that described the local seasonal and trend variations in each of the hemispheric <span class="hlt">sea</span> <span class="hlt">ice</span> covers to the recently merged 18.2-year <span class="hlt">sea</span> <span class="hlt">ice</span> record from four satellite instruments. The seasonal cycle characteristics remain essentially the same as for the shorter time series, but the local trends are markedly different, in some cases reversing sign. The sign reversal reflects the lack of a consistent long-term trend and could be the result of localized long-term oscillations in the hemispheric <span class="hlt">sea</span> <span class="hlt">ice</span> covers. By combining the separate hemispheric <span class="hlt">sea</span> <span class="hlt">ice</span> records into a global one, we have shown that there are statistically significant net decreases in the <span class="hlt">sea</span> <span class="hlt">ice</span> coverage on a global scale. The change in the global <span class="hlt">sea</span> <span class="hlt">ice</span> extent, is -0.01 +/- 0.003 x 10(exp 6) sq km per decade. The decrease in the areal coverage of the <span class="hlt">sea</span> <span class="hlt">ice</span> is only slightly smaller, so that the difference in the two, the open water within the packs, has no statistically significant change.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JGRD..122.7235C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JGRD..122.7235C"><span>Meteorological conditions in a thinner Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> regime from winter to summer during the Norwegian Young <span class="hlt">Sea</span> <span class="hlt">Ice</span> expedition (N-<span class="hlt">ICE</span>2015)</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Cohen, Lana; Hudson, Stephen R.; Walden, Von P.; Graham, Robert M.; Granskog, Mats A.</p> <p>2017-07-01</p> <p>Atmospheric measurements were made over Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> north of Svalbard from winter to early summer (January-June) 2015 during the Norwegian Young <span class="hlt">Sea</span> <span class="hlt">Ice</span> (N-<span class="hlt">ICE</span>2015) expedition. These measurements, which are available publicly, represent a comprehensive meteorological data set covering the seasonal transition in the Arctic Basin over the new, thinner <span class="hlt">sea</span> <span class="hlt">ice</span> regime. Winter was characterized by a succession of storms that produced short-lived (less than 48 h) temperature increases of 20 to 30 K at the surface. These storms were driven by the hemispheric scale circulation pattern with a large meridional component of the polar jet stream steering North Atlantic storms into the high Arctic. Nonstorm periods during winter were characterized by strong surface temperature inversions due to strong radiative cooling ("radiatively clear state"). The strength and depth of these inversions were similar to those during the Surface Heat Budget of the Arctic Ocean (SHEBA) campaign. In contrast, atmospheric profiles during the "opaquely cloudy state" were different to those from SHEBA due to differences in the synoptic conditions and location within the <span class="hlt">ice</span> pack. Storm events observed during spring/summer were the result of synoptic systems located in the Barents <span class="hlt">Sea</span> and the Arctic Basin rather than passing directly over N-<span class="hlt">ICE</span>2015. These synoptic systems were driven by a large-scale circulation pattern typical of recent years, with an Arctic Dipole pattern developing during June. Surface temperatures became near-constant 0°C on 1 June marking the beginning of summer. Atmospheric profiles during the spring and early summer show persistent lifted temperature and moisture inversions that are indicative of clouds and cloud processes.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018JGRC..123..939N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018JGRC..123..939N"><span>Influence of <span class="hlt">Sea</span> <span class="hlt">Ice</span> Crack Formation on the Spatial Distribution of Nutrients and Microalgae in Flooded Antarctic Multiyear <span class="hlt">Ice</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Nomura, Daiki; Aoki, Shigeru; Simizu, Daisuke; Iida, Takahiro</p> <p>2018-02-01</p> <p>Cracks are common and natural features of <span class="hlt">sea</span> <span class="hlt">ice</span> formed in the polar oceans. In this study, a <span class="hlt">sea</span> <span class="hlt">ice</span> crack in flooded, multiyear, land-fast Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> was examined to assess its influence on biological productivity and the transport of nutrients and microalgae into the upper layers of neighboring <span class="hlt">sea</span> <span class="hlt">ice</span>. The water inside the crack and the surrounding host <span class="hlt">ice</span> were characterized by a strong discoloration (brown color), an indicator of a massive algal bloom. Salinity and oxygen isotopic ratio measurements indicated that 64-84% of the crack water consisted of snow meltwater supplied during the melt season. Measurements of nutrient and chlorophyll a concentrations within the slush layer pool (the flooded layer at the snow-<span class="hlt">ice</span> interface) revealed the intrusion of water from the crack, likely forced by mixing with underlying seawater during the tidal cycle. Our results suggest that <span class="hlt">sea</span> <span class="hlt">ice</span> crack formation provides conditions favorable for algal blooms by directly exposing the crack water to sunlight and supplying nutrients from the under-<span class="hlt">ice</span> water. Subsequently, constituents of the crack water modified by biological activity were transported into the upper layer of the flooded <span class="hlt">sea</span> <span class="hlt">ice</span>. They were then preserved in the multiyear <span class="hlt">ice</span> column formed by upward growth of <span class="hlt">sea</span> <span class="hlt">ice</span> caused by snow <span class="hlt">ice</span> formation in areas of significant snow accumulation.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li class="active"><span>21</span></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_21 --> <div id="page_22" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li class="active"><span>22</span></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="421"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120010345','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120010345"><span>Laser Altimetry Sampling Strategies over <span class="hlt">Sea</span> <span class="hlt">Ice</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Farrell, Sinead L.; Markus, Thorsten; Kwok, Ron; Connor, Laurence</p> <p>2011-01-01</p> <p>With the conclusion of the science phase of the <span class="hlt">Ice</span>, Cloud and land Elevation Satellite (ICESat) mission in late 2009, and the planned launch of ICESat-2 in late 2015, NASA has recently established the <span class="hlt">Ice</span>Bridge program to provide continuity between missions. A major goal of <span class="hlt">Ice</span>Bridge is to obtain a <span class="hlt">sea-ice</span> thickness time series via airborne surveys over the Arctic and Southern Oceans. Typically two laser altimeters, the Airborne Topographic Mapper (ATM) and the Land, Vegetation and <span class="hlt">Ice</span> Sensor (LVIS), are utilized during <span class="hlt">Ice</span>Bridge flights. Using laser altimetry simulations of conventional analogue systems such as ICESat, LVIS and ATM, with the multi-beam system proposed for ICESat-2, we investigate differences in measurements gathered at varying spatial resolutions and the impact on <span class="hlt">sea-ice</span> freeboard. We assess the ability of each system to reproduce the elevation distributions of two seaice models and discuss potential biases in lead detection and <span class="hlt">sea</span>-surface elevation, arising from variable footprint size and spacing. The conventional systems accurately reproduce mean freeboard over 25km length scales, while ICESat-2 offers considerable improvements over its predecessor ICESat. In particular, its dense along-track sampling of the surface will allow flexibility in the algorithmic approaches taken to optimize the signal-to-noise ratio for accurate and precise freeboard retrieval.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C33C1202F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C33C1202F"><span>Determination of a Critical <span class="hlt">Sea</span> <span class="hlt">Ice</span> Thickness Threshold for the Central Arctic Ocean</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ford, V.; Frauenfeld, O. W.; Nowotarski, C. J.</p> <p>2017-12-01</p> <p>While <span class="hlt">sea</span> <span class="hlt">ice</span> extent is readily measurable from satellite observations and can be used to assess the overall survivability of the Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> pack, determining the spatial variability of <span class="hlt">sea</span> <span class="hlt">ice</span> thickness remains a challenge. Turbulent and conductive heat fluxes are extremely sensitive to <span class="hlt">ice</span> thickness but are dominated by the sensible heat flux, with energy exchange expected to increase with thinner <span class="hlt">ice</span> cover. Fluxes over open water are strongest and have the greatest influence on the atmosphere, while fluxes over thick <span class="hlt">sea</span> <span class="hlt">ice</span> are minimal as heat conduction from the ocean through thick <span class="hlt">ice</span> cannot reach the atmosphere. We know that turbulent energy fluxes are strongest over open ocean, but is there a "critical thickness of <span class="hlt">ice</span>" where fluxes are considered non-negligible? Through polar-optimized Weather Research and Forecasting model simulations, this study assesses how the wintertime Arctic surface boundary layer, via sensible heat flux exchange and surface air temperature, responds to <span class="hlt">sea</span> <span class="hlt">ice</span> thinning. The region immediately north of Franz Josef Land is characterized by a thickness gradient where <span class="hlt">sea</span> <span class="hlt">ice</span> transitions from the thickest multi-year <span class="hlt">ice</span> to the very thin marginal <span class="hlt">ice</span> <span class="hlt">seas</span>. This provides an ideal location to simulate how the diminishing Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> interacts with a warming atmosphere. Scenarios include both fixed <span class="hlt">sea</span> surface temperature domains for idealized thickness variability, and fixed <span class="hlt">ice</span> fields to detect changes in the ocean-<span class="hlt">ice</span>-atmosphere energy exchange. Results indicate that a critical thickness threshold exists below 1 meter. The threshold is between 0.4-1 meters thinner than the critical thickness for melt season survival - the difference between first year and multi-year <span class="hlt">ice</span>. Turbulent heat fluxes and surface air temperature increase as <span class="hlt">sea</span> <span class="hlt">ice</span> thickness transitions from perennial <span class="hlt">ice</span> to seasonal <span class="hlt">ice</span>. While models predict a <span class="hlt">sea</span> <span class="hlt">ice</span> free Arctic at the end of the warm season in future decades, <span class="hlt">sea</span> <span class="hlt">ice</span> will continue to transform</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140017422','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140017422"><span><span class="hlt">Sea</span> <span class="hlt">Ice</span> Prediction Has Easy and Difficult Years</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hamilton, Lawrence C.; Bitz, Cecilia M.; Blanchard-Wrigglesworth, Edward; Cutler, Matthew; Kay, Jennifer; Meier, Walter N.; Stroeve, Julienne; Wiggins, Helen</p> <p>2014-01-01</p> <p>Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> follows an annual cycle, reaching its low point in September each year. The extent of <span class="hlt">sea</span> <span class="hlt">ice</span> remaining at this low point has been trending downwards for decades as the Arctic warms. Around the long-term downward trend, however, there is significant variation in the minimum extent from one year to the next. Accurate forecasts of yearly conditions would have great value to Arctic residents, shipping companies, and other stakeholders and are the subject of much current research. Since 2008 the <span class="hlt">Sea</span> <span class="hlt">Ice</span> Outlook (SIO) (http://www.arcus.org/search-program/seaiceoutlook) organized by the Study of Environmental Arctic Change (SEARCH) (http://www.arcus.org/search-program) has invited predictions of the September Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> minimum extent, which are contributed from the Arctic research community. Individual predictions, based on a variety of approaches, are solicited in three cycles each year in early June, July, and August. (SEARCH 2013).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20100032968','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20100032968"><span>CBSIT 2009: Airborne Validation of Envisat Radar Altimetry and In Situ <span class="hlt">Ice</span> Camp Measurements Over Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Connor, Laurence; Farrell, Sinead; McAdoo, David; Krabill, William; Laxon, Seymour; Richter-Menge, Jacqueline; Markus, Thorsten</p> <p>2010-01-01</p> <p>The past few years have seen the emergence of satellite altimetry as valuable tool for taking quantitative <span class="hlt">sea</span> <span class="hlt">ice</span> monitoring beyond the traditional surface extent measurements and into estimates of <span class="hlt">sea</span> <span class="hlt">ice</span> thickness and volume, parameters that arc fundamental to improved understanding of polar dynamics and climate modeling. Several studies have now demonstrated the use of both microwave (ERS, Envisat/RA-2) and laser (ICESat/GLAS) satellite altimeters for determining <span class="hlt">sea</span> <span class="hlt">ice</span> thickness. The complexity of polar environments, however, continues to make <span class="hlt">sea</span> <span class="hlt">ice</span> thickness determination a complicated remote sensing task and validation studies remain essential for successful monitoring of <span class="hlt">sea</span> <span class="hlt">ice</span> hy satellites. One such validation effort, the Arctic Aircraft Altimeter (AAA) campaign of2006. included underflights of Envisat and ICESat north of the Canadian Archipelago using NASA's P-3 aircraft. This campaign compared Envisat and ICESat <span class="hlt">sea</span> <span class="hlt">ice</span> elevation measurements with high-resolution airborne elevation measurements, revealing the impact of refrozen leads on radar altimetry and <span class="hlt">ice</span> drift on laser altimetry. Continuing this research and validation effort, the Canada Basin <span class="hlt">Sea</span> <span class="hlt">Ice</span> Thickness (CBSIT) experiment was completed in April 2009. CBSIT was conducted by NOAA. and NASA as part of NASA's Operation <span class="hlt">Ice</span> Bridge, a gap-filling mission intended to supplement <span class="hlt">sea</span> and land <span class="hlt">ice</span> monitoring until the launch of NASA's ICESat-2 mission. CBIST was flown on the NASA P-3, which was equipped with a scanning laser altimeter, a Ku-band snow radar, and un updated nadir looking photo-imaging system. The CB5IT campaign consisted of two flights: an under flight of Envisat along a 1000 km track similar to that flown in 2006, and a flight through the Nares Strait up to the Lincoln <span class="hlt">Sea</span> that included an overflight of the Danish GreenArc <span class="hlt">Ice</span> Camp off the coast of northern Greenland. We present an examination of data collected during this campaign, comparing airborne laser altimeter measurements</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA221723','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA221723"><span><span class="hlt">Sea</span> <span class="hlt">Ice</span> Properties and Processes. Proceedings of the W. F. Weeks <span class="hlt">Sea</span> <span class="hlt">Ice</span> Symposium Held In San Francisco, California on December 1988</span></a></p> <p><a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>1990-02-01</p> <p>in the sample by inserting a probe thermometer into a transverse hole that was prepared with a hand drill . Then a portion of the <span class="hlt">ice</span> was cut into...Weddell<span class="hlt">Sea</span> duringJuly-September 1986. holes drilled had the <span class="hlt">ice</span> surface at or below <span class="hlt">sea</span> level The symbols show positions where <span class="hlt">ice</span> cores were at the...flux argument cannot be Table 3. Frequency of drilled statistically confirmed from the observations. holes with negative <span class="hlt">ice</span> free- board. Measurement</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C31A..03A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C31A..03A"><span>Interactions Between <span class="hlt">Ice</span> Thickness, Bottom <span class="hlt">Ice</span> Algae, and Transmitted Spectral Irradiance in the Chukchi <span class="hlt">Sea</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Arntsen, A. E.; Perovich, D. K.; Polashenski, C.; Stwertka, C.</p> <p>2015-12-01</p> <p>The amount of light that penetrates the Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> cover impacts <span class="hlt">sea-ice</span> mass balance as well as ecological processes in the upper ocean. The seasonally evolving macro and micro spatial variability of transmitted spectral irradiance observed in the Chukchi <span class="hlt">Sea</span> from May 18 to June 17, 2014 can be primarily attributed to variations in snow depth, <span class="hlt">ice</span> thickness, and bottom <span class="hlt">ice</span> algae concentrations. This study characterizes the interactions among these dominant variables using observed optical properties at each sampling site. We employ a normalized difference index to compute estimates of Chlorophyll a concentrations and analyze the increased attenuation of incident irradiance due to absorption by biomass. On a kilometer spatial scale, the presence of bottom <span class="hlt">ice</span> algae reduced the maximum transmitted irradiance by about 1.5 orders of magnitude when comparing floes of similar snow and <span class="hlt">ice</span> thicknesses. On a meter spatial scale, the combined effects of disparities in the depth and distribution of the overlying snow cover along with algae concentrations caused maximum transmittances to vary between 0.0577 and 0.282 at a single site. Temporal variability was also observed as the average integrated transmitted photosynthetically active radiation increased by one order of magnitude to 3.4% for the last eight measurement days compared to the first nine. Results provide insight on how interrelated physical and ecological parameters of <span class="hlt">sea</span> <span class="hlt">ice</span> in varying time and space may impact new trends in Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> extent and the progression of melt.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1814695S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1814695S"><span>N-<span class="hlt">ICE</span>2015: Multi-disciplinary study of the young <span class="hlt">sea</span> <span class="hlt">ice</span> system north of Svalbard from winter to summer.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Steen, Harald; Granskog, Mats; Assmy, Philipp; Duarte, Pedro; Hudson, Stephen; Gerland, Sebastian; Spreen, Gunnar; Smedsrud, Lars H.</p> <p>2016-04-01</p> <p>The Arctic Ocean is shifting to a new regime with a thinner and smaller <span class="hlt">sea-ice</span> area cover. Until now, winter <span class="hlt">sea</span> <span class="hlt">ice</span> extent has changed less than during summer, as the heat loss to the atmosphere during autumn and winter is large enough form an <span class="hlt">ice</span> cover in most regions. The insulating snow cover also heavily influences the winter <span class="hlt">ice</span> growth. Consequently, the older, thicker multi-year <span class="hlt">sea</span> <span class="hlt">ice</span> has been replace by a younger and thinner <span class="hlt">sea</span>. These large changes in the <span class="hlt">sea</span> <span class="hlt">ice</span> cover may have dramatic consequences for ecosystems, energy fluxes and ultimately atmospheric circulation and the Northern Hemisphere climate. To study the effects of the changing Arctic the Norwegian Polar Institute, together with national and international partners, launched from January 11 to June 24, 2015 the Norwegian Young <span class="hlt">Sea</span> <span class="hlt">ICE</span> cruise 2015 (N-<span class="hlt">ICE</span>2015). N-<span class="hlt">ICE</span>2015 was a multi-disciplinary cruise aimed at simultaneously studying the effect of the Arctic Ocean changes in the <span class="hlt">sea</span> <span class="hlt">ice</span>, the atmosphere, in radiation, in ecosystems. as well as water chemistry. R/V Lance was frozen into the drift <span class="hlt">ice</span> north of Svalbard at about N83 E25 and drifted passively southwards with the <span class="hlt">ice</span> until she was broken loose. When she was loose, R/V Lance was brought back north to a similar starting position. While fast in the <span class="hlt">ice</span>, she served as a living and working platform for 100 scientist and engineers from 11 countries. One aim of N-<span class="hlt">ICE</span>2015 is to present a comprehensive data-set on the first year <span class="hlt">ice</span> dominated system available for the scientific community describing the state and changes of the Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> system from freezing to melt. Analyzing the data is progressing and some first results will be presented.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016TCry...10.1513R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016TCry...10.1513R"><span>Arctic <span class="hlt">sea-ice</span> diffusion from observed and simulated Lagrangian trajectories</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Rampal, Pierre; Bouillon, Sylvain; Bergh, Jon; Ólason, Einar</p> <p>2016-07-01</p> <p>We characterize <span class="hlt">sea-ice</span> drift by applying a Lagrangian diffusion analysis to buoy trajectories from the International Arctic Buoy Programme (IABP) dataset and from two different models: the standalone Lagrangian <span class="hlt">sea-ice</span> model neXtSIM and the Eulerian coupled <span class="hlt">ice</span>-ocean model used for the TOPAZ reanalysis. By applying the diffusion analysis to the IABP buoy trajectories over the period 1979-2011, we confirm that <span class="hlt">sea-ice</span> diffusion follows two distinct regimes (ballistic and Brownian) and we provide accurate values for the diffusivity and integral timescale that could be used in Eulerian or Lagrangian passive tracers models to simulate the transport and diffusion of particles moving with the <span class="hlt">ice</span>. We discuss how these values are linked to the evolution of the fluctuating displacements variance and how this information could be used to define the size of the search area around the position predicted by the mean drift. By comparing observed and simulated <span class="hlt">sea-ice</span> trajectories for three consecutive winter seasons (2007-2011), we show how the characteristics of the simulated motion may differ from or agree well with observations. This comparison illustrates the usefulness of first applying a diffusion analysis to evaluate the output of modeling systems that include a <span class="hlt">sea-ice</span> model before using these in, e.g., oil spill trajectory models or, more generally, to simulate the transport of passive tracers in <span class="hlt">sea</span> <span class="hlt">ice</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JMS...166....4S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JMS...166....4S"><span>Modelling <span class="hlt">sea</span> <span class="hlt">ice</span> formation in the Terra Nova Bay polynya</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sansiviero, M.; Morales Maqueda, M. Á.; Fusco, G.; Aulicino, G.; Flocco, D.; Budillon, G.</p> <p>2017-02-01</p> <p>Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> is constantly exported from the shore by strong near surface winds that open leads and large polynyas in the pack <span class="hlt">ice</span>. The latter, known as wind-driven polynyas, are responsible for significant water mass modification due to the high salt flux into the ocean associated with enhanced <span class="hlt">ice</span> growth. In this article, we focus on the wind-driven Terra Nova Bay (TNB) polynya, in the western Ross <span class="hlt">Sea</span>. Brine rejected during <span class="hlt">sea</span> <span class="hlt">ice</span> formation processes that occur in the TNB polynya densifies the water column leading to the formation of the most characteristic water mass of the Ross <span class="hlt">Sea</span>, the High Salinity Shelf Water (HSSW). This water mass, in turn, takes part in the formation of Antarctic Bottom Water (AABW), the densest water mass of the world ocean, which plays a major role in the global meridional overturning circulation, thus affecting the global climate system. A simple coupled <span class="hlt">sea</span> <span class="hlt">ice</span>-ocean model has been developed to simulate the seasonal cycle of <span class="hlt">sea</span> <span class="hlt">ice</span> formation and export within a polynya. The <span class="hlt">sea</span> <span class="hlt">ice</span> model accounts for both thermal and mechanical <span class="hlt">ice</span> processes. The oceanic circulation is described by a one-and-a-half layer, reduced gravity model. The domain resolution is 1 km × 1 km, which is sufficient to represent the salient features of the coastline geometry, notably the Drygalski <span class="hlt">Ice</span> Tongue. The model is forced by a combination of Era Interim reanalysis and in-situ data from automatic weather stations, and also by a climatological oceanic dataset developed from in situ hydrographic observations. The sensitivity of the polynya to the atmospheric forcing is well reproduced by the model when atmospheric in situ measurements are combined with reanalysis data. Merging the two datasets allows us to capture in detail the strength and the spatial distribution of the katabatic winds that often drive the opening of the polynya. The model resolves fairly accurately the <span class="hlt">sea</span> <span class="hlt">ice</span> drift and <span class="hlt">sea</span> <span class="hlt">ice</span> production rates in the TNB polynya, leading to</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-PIA01786.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-PIA01786.html"><span>Space Radar Image of Weddell <span class="hlt">Sea</span> <span class="hlt">Ice</span></span></a></p> <p><a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a></p> <p></p> <p>1999-04-15</p> <p>This is the first calibrated, multi-frequency, multi-polarization spaceborne radar image of the seasonal <span class="hlt">sea-ice</span> cover in the Weddell <span class="hlt">Sea</span>, Antarctica. The multi-channel data provide scientists with details about the <span class="hlt">ice</span> pack they cannot see any other way and indicates that the large expanse of <span class="hlt">sea-ice</span> is, in fact, comprised of many smaller rounded <span class="hlt">ice</span> floes, shown in blue-gray. These data are particularly useful in helping scientists estimate the thickness of the <span class="hlt">ice</span> cover which is often extremely difficult to measure with other remote sensing systems. The extent, and especially thickness, of the polar ocean's <span class="hlt">sea-ice</span> cover together have important implications for global climate by regulating the loss of heat from the ocean to the cold polar atmosphere. The image was acquired on October 3, 1994, by the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) onboard the space shuttle Endeavour. This image is produced by overlaying three channels of radar data in the following colors: red (C-band, HH-polarization), green (L-band HV-polarization), and blue (L-band, HH-polarization). The image is oriented almost east-west with a center location of 58.2 degrees South and 21.6 degrees East. Image dimensions are 45 kilometers by 18 kilometers (28 miles by 11 miles). Most of the <span class="hlt">ice</span> cover is composed of rounded, undeformed blue-gray floes, about 0.7 meters (2 feet) thick, which are surrounded by a jumble of red-tinged deformed <span class="hlt">ice</span> pieces which are up to 2 meters (7 feet) thick. The winter cycle of <span class="hlt">ice</span> growth and deformation often causes this <span class="hlt">ice</span> cover to split apart, exposing open water or "leads." <span class="hlt">Ice</span> growth within these openings is rapid due to the cold, brisk Antarctic atmosphere. Different stages of new-<span class="hlt">ice</span> growth can be seen within the linear leads, resulting from continuous opening and closing. The blue lines within the leads are open water areas in new fractures which are roughened by wind. The bright red lines are an intermediate stage of new-<span class="hlt">ice</span></p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA480564','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA480564"><span>Navy <span class="hlt">Sea</span> <span class="hlt">Ice</span> Prediction Systems</span></a></p> <p><a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>2002-01-01</p> <p>for the IABP drifting buoys (red), the model (green), and the model with assimilation (black). 55 Oceanography • Vol. 15 • No. 1/2002 trate the need...SPECIAL ISSUE – NAVY OPERATIONAL MODELS : TEN YEARS LATER Oceanography • Vol. 15 • No. 1/2002 44 <span class="hlt">ice</span> extent and/or <span class="hlt">ice</span> thickness. A general trend...most often based on a combination of models and data. Modeling <span class="hlt">sea</span> <span class="hlt">ice</span> can be a difficult problem, as it exists in many different forms (Figure 1). It</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110011892','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110011892"><span>Observations of Recent Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> Volume Loss and Its Impact on Ocean-Atmosphere Energy Exchange and <span class="hlt">Ice</span> Production</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Kurtz, N. T.; Markus, T.; Farrell, S. L.; Worthen, D. L.; Boisvert, L. N.</p> <p>2011-01-01</p> <p>Using recently developed techniques we estimate snow and <span class="hlt">sea</span> <span class="hlt">ice</span> thickness distributions for the Arctic basin through the combination of freeboard data from the <span class="hlt">Ice</span>, Cloud, and land Elevation Satellite (ICESat) and a snow depth model. These data are used with meteorological data and a thermodynamic <span class="hlt">sea</span> <span class="hlt">ice</span> model to calculate ocean-atmosphere heat exchange and <span class="hlt">ice</span> volume production during the 2003-2008 fall and winter seasons. The calculated heat fluxes and <span class="hlt">ice</span> growth rates are in agreement with previous observations over multiyear <span class="hlt">ice</span>. In this study, we calculate heat fluxes and <span class="hlt">ice</span> growth rates for the full distribution of <span class="hlt">ice</span> thicknesses covering the Arctic basin and determine the impact of <span class="hlt">ice</span> thickness change on the calculated values. Thinning of the <span class="hlt">sea</span> <span class="hlt">ice</span> is observed which greatly increases the 2005-2007 fall period ocean-atmosphere heat fluxes compared to those observed in 2003. Although there was also a decline in <span class="hlt">sea</span> <span class="hlt">ice</span> thickness for the winter periods, the winter time heat flux was found to be less impacted by the observed changes in <span class="hlt">ice</span> thickness. A large increase in the net Arctic ocean-atmosphere heat output is also observed in the fall periods due to changes in the areal coverage of <span class="hlt">sea</span> <span class="hlt">ice</span>. The anomalously low <span class="hlt">sea</span> <span class="hlt">ice</span> coverage in 2007 led to a net ocean-atmosphere heat output approximately 3 times greater than was observed in previous years and suggests that <span class="hlt">sea</span> <span class="hlt">ice</span> losses are now playing a role in increasing surface air temperatures in the Arctic.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC43J..06R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC43J..06R"><span>The direct mechanical influence of <span class="hlt">sea</span> <span class="hlt">ice</span> state on <span class="hlt">ice</span> sheet mass loss via iceberg mélange</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Robel, A.</p> <p>2017-12-01</p> <p>The interaction between <span class="hlt">sea</span> <span class="hlt">ice</span> and land <span class="hlt">ice</span> has typically been considered as a large-scale exchange of moisture, heat and salinity through the ocean and atmosphere. However, recent observations from marine-terminating glaciers in Greenland indicate that the long-term decline of local <span class="hlt">sea</span> <span class="hlt">ice</span> cover has been accompanied by an increase in nearby iceberg calving and associated <span class="hlt">ice</span> sheet mass loss. Near glacier calving fronts, <span class="hlt">sea</span> <span class="hlt">ice</span> binds icebergs together into an aggregate granular material known as iceberg mélange. Studies have hypothesized that mélange may suppress calving by exerting a mechanical buttressing force directly on the glacier terminus. Here, we show explicitly how <span class="hlt">sea</span> <span class="hlt">ice</span> thickness and concentration play a critical role in setting the material strength of mélange. To do so, we adapt a discrete element model to simulate mélange as a cohesive granular material. In these simulations, mélange laden with thick, dense, landfast <span class="hlt">sea</span> <span class="hlt">ice</span> can produce enough resistance to shut down calving at the terminus. When <span class="hlt">sea</span> <span class="hlt">ice</span> thins, mélange weakens, reducing the mechanical force of mélange on the glacier terminus, and increasing the likelihood of calving. We discuss whether longer periods of <span class="hlt">sea-ice</span>-free conditions in winter may lead to a transition from currently slow calving, predominantly occurring in the summer, to rapid calving, occurring throughout the year. We also discuss the potential role of freshwater discharge in promoting <span class="hlt">sea</span> <span class="hlt">ice</span> formation in fjords, potentially strengthening mélange.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20060012295','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20060012295"><span>A Model Assessment of Satellite Observed Trends in Polar <span class="hlt">Sea</span> <span class="hlt">Ice</span> Extents</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Vinnikov, Konstantin Y.; Cavalieri, Donald J.; Parkinson, Claire L.</p> <p>2005-01-01</p> <p>For more than three decades now, satellite passive microwave observations have been used to monitor polar <span class="hlt">sea</span> <span class="hlt">ice</span>. Here we utilize <span class="hlt">sea</span> <span class="hlt">ice</span> extent trends determined from primarily satellite data for both the Northern and Southern Hemispheres for the period 1972(73)-2004 and compare them with results from simulations by eleven climate models. In the Northern Hemisphere, observations show a statistically significant decrease of <span class="hlt">sea</span> <span class="hlt">ice</span> extent and an acceleration of <span class="hlt">sea</span> <span class="hlt">ice</span> retreat during the past three decades. However, from the modeled natural variability of <span class="hlt">sea</span> <span class="hlt">ice</span> extents in control simulations, we conclude that the acceleration is not statistically significant and should not be extrapolated into the future. Observations and model simulations show that the time scale of climate variability in <span class="hlt">sea</span> <span class="hlt">ice</span> extent in the Southern Hemisphere is much larger than in the Northern Hemisphere and that the Southern Hemisphere <span class="hlt">sea</span> <span class="hlt">ice</span> extent trends are not statistically significant.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/biblio/20020695-arctic-sea-ice-variability-context-recent-atmospheric-circulation-trends','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/20020695-arctic-sea-ice-variability-context-recent-atmospheric-circulation-trends"><span>Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> variability in the context of recent atmospheric circulation trends</span></a></p> <p><a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Deser, C.; Walsh, J.E.; Timlin, M.S.</p> <p></p> <p><span class="hlt">Sea</span> <span class="hlt">ice</span> is a sensitive component of the climate system, influenced by conditions in both the atmosphere and ocean. Variations in <span class="hlt">sea</span> <span class="hlt">ice</span> may in turn modulate climate by altering the surface albedo; the exchange of heat, moisture, and momentum between the atmosphere and ocean; and the upper ocean stratification in areas of deep water formation. The surface albedo effect is considered to be one of the dominant factors in the poleward amplification of global warming due to increased greenhouse gas concentrations simulated in many climate models. Forty years (1958--97) of reanalysis products and corresponding <span class="hlt">sea</span> <span class="hlt">ice</span> concentration data aremore » used to document Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> variability and its association with surface air temperature (SAT) and <span class="hlt">sea</span> level pressure (SLP) throughout the Northern Hemisphere extratropics. The dominant mode of winter (January-March) <span class="hlt">sea</span> <span class="hlt">ice</span> variability exhibits out-of-phase fluctuations between the western and eastern North Atlantic, together with a weaker dipole in the North Pacific. The time series of this mode has a high winter-to-winter autocorrelation (0.69) and is dominated by decadal-scale variations and a longer-term trend of diminishing <span class="hlt">ice</span> cover east of Greenland and increasing <span class="hlt">ice</span> cover west of Greenland. Associated with the dominant pattern of winter <span class="hlt">sea</span> <span class="hlt">ice</span> variability are large-scale changes in SAT and SLP that closely resemble the North Atlantic oscillation. The associated SAT and surface sensible and latent heat flux anomalies are largest over the portions of the marginal <span class="hlt">sea</span> <span class="hlt">ice</span> zone in which the trends of <span class="hlt">ice</span> coverage have been greatest, although the well-documented warming of the northern continental regions is also apparent. the temporal and spatial relationships between the SLP and <span class="hlt">ice</span> anomaly fields are consistent with the notion that atmospheric circulation anomalies force the <span class="hlt">sea</span> <span class="hlt">ice</span> variations. However, there appears to be a local response of the atmospheric circulation to the changing <span class="hlt">sea</span> <span class="hlt">ice</span> variations. However</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.4084H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.4084H"><span>A glimpse beneath Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span>: observation of platelet-layer thickness and <span class="hlt">ice</span>-volume fraction with multifrequency EM</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hoppmann, Mario; Hunkeler, Priska A.; Hendricks, Stefan; Kalscheuer, Thomas; Gerdes, Rüdiger</p> <p>2016-04-01</p> <p>In Antarctica, <span class="hlt">ice</span> crystals (platelets) form and grow in supercooled waters below <span class="hlt">ice</span> shelves. These platelets rise, accumulate beneath nearby <span class="hlt">sea</span> <span class="hlt">ice</span>, and subsequently form a several meter thick, porous sub-<span class="hlt">ice</span> platelet layer. This special <span class="hlt">ice</span> type is a unique habitat, influences <span class="hlt">sea-ice</span> mass and energy balance, and its volume can be interpreted as an indicator of the health of an <span class="hlt">ice</span> shelf. Although progress has been made in determining and understanding its spatio-temporal variability based on point measurements, an investigation of this phenomenon on a larger scale remains a challenge due to logistical constraints and a lack of suitable methodology. In the present study, we applied a lateral constrained Marquardt-Levenberg inversion to a unique multi-frequency electromagnetic (EM) induction sounding dataset obtained on the <span class="hlt">ice</span>-shelf influenced fast-<span class="hlt">ice</span> regime of Atka Bay, eastern Weddell <span class="hlt">Sea</span>. We adapted the inversion algorithm to incorporate a sensor specific signal bias, and confirmed the reliability of the algorithm by performing a sensitivity study using synthetic data. We inverted the field data for <span class="hlt">sea-ice</span> and platelet-layer thickness and electrical conductivity, and calculated <span class="hlt">ice</span>-volume fractions within the platelet layer using Archie's Law. The thickness results agreed well with drillhole validation datasets within the uncertainty range, and the <span class="hlt">ice</span>-volume fraction yielded results comparable to other studies. Both parameters together enable an estimation of the total <span class="hlt">ice</span> volume within the platelet layer, which was found to be comparable to the volume of landfast <span class="hlt">sea</span> <span class="hlt">ice</span> in this region, and corresponded to more than a quarter of the annual basal melt volume of the nearby Ekström <span class="hlt">Ice</span> Shelf. Our findings show that multi-frequency EM induction sounding is a suitable approach to efficiently map <span class="hlt">sea-ice</span> and platelet-layer properties, with important implications for research into ocean/<span class="hlt">ice-shelf/sea-ice</span> interactions. However, a successful application of this</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018TCry...12..365R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018TCry...12..365R"><span>Consistent biases in Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> concentration simulated by climate models</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Roach, Lettie A.; Dean, Samuel M.; Renwick, James A.</p> <p>2018-01-01</p> <p>The simulation of Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> in global climate models often does not agree with observations. In this study, we examine the compactness of <span class="hlt">sea</span> <span class="hlt">ice</span>, as well as the regional distribution of <span class="hlt">sea</span> <span class="hlt">ice</span> concentration, in climate models from the latest Coupled Model Intercomparison Project (CMIP5) and in satellite observations. We find substantial differences in concentration values between different sets of satellite observations, particularly at high concentrations, requiring careful treatment when comparing to models. As a fraction of total <span class="hlt">sea</span> <span class="hlt">ice</span> extent, models simulate too much loose, low-concentration <span class="hlt">sea</span> <span class="hlt">ice</span> cover throughout the year, and too little compact, high-concentration cover in the summer. In spite of the differences in physics between models, these tendencies are broadly consistent across the population of 40 CMIP5 simulations, a result not previously highlighted. Separating models with and without an explicit lateral melt term, we find that inclusion of lateral melt may account for overestimation of low-concentration cover. Targeted model experiments with a coupled ocean-<span class="hlt">sea</span> <span class="hlt">ice</span> model show that choice of constant floe diameter in the lateral melt scheme can also impact representation of loose <span class="hlt">ice</span>. This suggests that current <span class="hlt">sea</span> <span class="hlt">ice</span> thermodynamics contribute to the inadequate simulation of the low-concentration regime in many models.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24276772','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24276772"><span>Fatty acid and stable isotope characteristics of <span class="hlt">sea</span> <span class="hlt">ice</span> and pelagic particulate organic matter in the Bering <span class="hlt">Sea</span>: tools for estimating <span class="hlt">sea</span> <span class="hlt">ice</span> algal contribution to Arctic food web production.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Wang, Shiway W; Budge, Suzanne M; Gradinger, Rolf R; Iken, Katrin; Wooller, Matthew J</p> <p>2014-03-01</p> <p>We determined fatty acid (FA) profiles and carbon stable isotopic composition of individual FAs (δ(13)CFA values) from <span class="hlt">sea</span> <span class="hlt">ice</span> particulate organic matter (i-POM) and pelagic POM (p-POM) in the Bering <span class="hlt">Sea</span> during maximum <span class="hlt">ice</span> extent, <span class="hlt">ice</span> melt, and <span class="hlt">ice</span>-free conditions in 2010. Based on FA biomarkers, differences in relative composition of diatoms, dinoflagellates, and bacteria were inferred for i-POM versus p-POM and for seasonal succession stages in p-POM. Proportions of diatom markers were higher in i-POM (16:4n-1, 6.6-8.7%; 20:5n-3, 19.6-25.9%) than in p-POM (16:4n-1, 1.2-4.0%; 20:5n-3, 5.5-14.0%). The dinoflagellate marker 22:6n-3/20:5n-3 was highest in p-POM. Bacterial FA concentration was higher in the bottom 1 cm of <span class="hlt">sea</span> <span class="hlt">ice</span> (14-245 μg L(-1)) than in the water column (0.6-1.7 μg L(-1)). Many i-POM δ(13)C(FA) values were higher (up to ~10‰) than those of p-POM, and i-POM δ(13)C(FA) values increased with day length. The higher i-POM δ(13)C(FA) values are most likely related to the reduced dissolved inorganic carbon (DIC) availability within the semi-closed <span class="hlt">sea</span> <span class="hlt">ice</span> brine channel system. Based on a modified Rayleigh equation, the fraction of <span class="hlt">sea</span> <span class="hlt">ice</span> DIC fixed in i-POM ranged from 12 to 73%, implying that carbon was not limiting for primary productivity in the sympagic habitat. These differences in FA composition and δ(13)C(FA) values between i-POM and p-POM will aid efforts to track the proportional contribution of <span class="hlt">sea</span> <span class="hlt">ice</span> algal carbon to higher trophic levels in the Bering <span class="hlt">Sea</span> and likely other Arctic <span class="hlt">seas</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70035584','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70035584"><span>Survival and breeding of polar bears in the southern Beaufort <span class="hlt">Sea</span> in relation to <span class="hlt">sea</span> <span class="hlt">ice</span></span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Regehr, E.V.; Hunter, C.M.; Caswell, H.; Amstrup, Steven C.; Stirling, I.</p> <p>2010-01-01</p> <p>1. Observed and predicted declines in Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> have raised concerns about marine mammals. In May 2008, the US Fish and Wildlife Service listed polar bears (Ursus maritimus) - one of the most <span class="hlt">ice</span>-dependent marine mammals - as threatened under the US Endangered Species Act. 2. We evaluated the effects of <span class="hlt">sea</span> <span class="hlt">ice</span> conditions on vital rates (survival and breeding probabilities) for polar bears in the southern Beaufort <span class="hlt">Sea</span>. Although <span class="hlt">sea</span> <span class="hlt">ice</span> declines in this and other regions of the polar basin have been among the greatest in the Arctic, to date population-level effects of <span class="hlt">sea</span> <span class="hlt">ice</span> loss on polar bears have only been identified in western Hudson Bay, near the southern limit of the species' range. 3. We estimated vital rates using multistate capture-recapture models that classified individuals by sex, age and reproductive category. We used multimodel inference to evaluate a range of statistical models, all of which were structurally based on the polar bear life cycle. We estimated parameters by model averaging, and developed a parametric bootstrap procedure to quantify parameter uncertainty. 4. In the most supported models, polar bear survival declined with an increasing number of days per year that waters over the continental shelf were <span class="hlt">ice</span> free. In 2001-2003, the <span class="hlt">ice</span>-free period was relatively short (mean 101 days) and adult female survival was high (0 ∙ 96-0 ∙ 99, depending on reproductive state). In 2004 and 2005, the <span class="hlt">ice</span>-free period was longer (mean 135 days) and adult female survival was low (0 ∙ 73-0 ∙ 79, depending on reproductive state). Breeding rates and cub litter survival also declined with increasing duration of the <span class="hlt">ice</span>-free period. Confidence intervals on vital rate estimates were wide. 5. The effects of <span class="hlt">sea</span> <span class="hlt">ice</span> loss on polar bears in the southern Beaufort <span class="hlt">Sea</span> may apply to polar bear populations in other portions of the polar basin that have similar <span class="hlt">sea</span> <span class="hlt">ice</span> dynamics and have experienced similar, or more severe, <span class="hlt">sea</span> <span class="hlt">ice</span> declines. Our findings</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017TCry...11.2033D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017TCry...11.2033D"><span><span class="hlt">Ice</span> bridges and ridges in the Maxwell-EB <span class="hlt">sea</span> <span class="hlt">ice</span> rheology</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dansereau, Véronique; Weiss, Jérôme; Saramito, Pierre; Lattes, Philippe; Coche, Edmond</p> <p>2017-09-01</p> <p>This paper presents a first implementation of a new rheological model for <span class="hlt">sea</span> <span class="hlt">ice</span> on geophysical scales. This continuum model, called Maxwell elasto-brittle (Maxwell-EB), is based on a Maxwell constitutive law, a progressive damage mechanism that is coupled to both the elastic modulus and apparent viscosity of the <span class="hlt">ice</span> cover and a Mohr-Coulomb damage criterion that allows for pure (uniaxial and biaxial) tensile strength. The model is tested on the basis of its capability to reproduce the complex mechanical and dynamical behaviour of <span class="hlt">sea</span> <span class="hlt">ice</span> drifting through a narrow passage. Idealized as well as realistic simulations of the flow of <span class="hlt">ice</span> through Nares Strait are presented. These demonstrate that the model reproduces the formation of stable <span class="hlt">ice</span> bridges as well as the stoppage of the flow, a phenomenon occurring within numerous channels of the Arctic. In agreement with observations, the model captures the propagation of damage along narrow arch-like kinematic features, the discontinuities in the velocity field across these features dividing the <span class="hlt">ice</span> cover into floes, the strong spatial localization of the thickest, ridged <span class="hlt">ice</span>, the presence of landfast <span class="hlt">ice</span> in bays and fjords and the opening of polynyas downstream of the strait. The model represents various dynamical behaviours linked to an overall weakening of the <span class="hlt">ice</span> cover and to the shorter lifespan of <span class="hlt">ice</span> bridges, with implications in terms of increased <span class="hlt">ice</span> export through narrow outflow pathways of the Arctic.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li class="active"><span>22</span></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_22 --> <div id="page_23" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li class="active"><span>23</span></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="441"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70010308','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70010308"><span>Aircraft measurements of microwave emission from Arctic <span class="hlt">Sea</span> <span class="hlt">ice</span></span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Wilheit, T.; Nordberg, W.; Blinn, J.; Campbell, W.; Edgerton, A.</p> <p>1971-01-01</p> <p>Measurements of the microwave emission from Arctic <span class="hlt">Sea</span> <span class="hlt">ice</span> were made with aircraft at 8 wavelengths ranging from 0.510 to 2.81 cm. The expected contrast in emissivities between <span class="hlt">ice</span> and water was observed at all wavelengths. Distributions of <span class="hlt">sea</span> <span class="hlt">ice</span> and open water were mapped from altitudes up to 11 km in the presence of dense cloud cover. Different forms of <span class="hlt">ice</span> also exhibited strong contrasts in emissivity. Emissivity differences of up to 0.2 were observed between two types of <span class="hlt">ice</span> at the 0.811-cm wavelength. The higher emissivity <span class="hlt">ice</span> type is tentatively identified as having been formed more recently than the lower emissivity <span class="hlt">ice</span>. ?? 1971.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19720002627','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19720002627"><span>Aircraft measurements of microwave emission from Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wilheit, T. T.; Blinn, J.; Campbell, W. J.; Edgerton, A. T.; Nordberg, W.</p> <p>1971-01-01</p> <p>Measurements of the microwave emission from Arctic <span class="hlt">Sea</span> <span class="hlt">ice</span> were made with aircraft at 8 wavelengths ranging from 0.510 cm to 2.81 cm. The expected contrast in emissivities between <span class="hlt">ice</span> and water was observed at all wavelengths. Distributions of <span class="hlt">sea</span> <span class="hlt">ice</span> and open water were mapped from altitudes up to 11 km in the presence of dense cloud cover. Different forms of <span class="hlt">ice</span> also exhibited strong contrasts in emissivity. Emissivity differences of up to 0.2 were observed between two types of <span class="hlt">ice</span> at 0.811 cm wavelength. The higher emissivity <span class="hlt">ice</span> type is tentatively identified as having been formed more recently than the lower emissivity <span class="hlt">ice</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012JGRC..11710018S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012JGRC..11710018S"><span>Using MODIS data to estimate <span class="hlt">sea</span> <span class="hlt">ice</span> thickness in the Bohai <span class="hlt">Sea</span> (China) in the 2009-2010 winter</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Su, Hua; Wang, Yunpeng</p> <p>2012-10-01</p> <p>To estimate <span class="hlt">sea</span> <span class="hlt">ice</span> thickness over a large spatial scale is a challenge. In this paper, we propose a direct approach to effectively estimate <span class="hlt">sea</span> <span class="hlt">ice</span> thickness over a large spatial area of the Bohai <span class="hlt">Sea</span> using EOS MODIS data. It is based on the model of an exponential relation between albedo and thickness of <span class="hlt">sea</span> <span class="hlt">ice</span>. Eighteen images of EOS MODIS L1B data in the 2009-2010 winter were used to estimate the <span class="hlt">sea</span> <span class="hlt">ice</span> thickness and to monitor its spatiotemporal evolution in the Bohai <span class="hlt">Sea</span>. The estimated thickness results are in accordance with results based on the Lebedev and Zubov empirical models as well as the forecasting data from the National Marine Environmental Forecasting Centre of China. Model correlation coefficients (R2= 0.864 and 0.858) and close similarity in thickness prediction attest to the reliability and applicability of the proposed method. The average <span class="hlt">ice</span> thickness of the whole Bohai <span class="hlt">Sea</span> ranged from 3 to 21 cm, with an estimated maximum about 40 cm in Liaodong Bay. Multiple-temporal maps of <span class="hlt">sea-ice</span> thickness show that the <span class="hlt">sea</span> <span class="hlt">ice</span> formed initially along the coastline, and gradually expanded away from the shore. <span class="hlt">Sea</span> <span class="hlt">ice</span> first appeared in the Liaodong Bay, and hugged the coast southwards to Bohai and Laizhou Bay. During melting the inverse sequence occurred. Our results also show that <span class="hlt">sea</span> <span class="hlt">ice</span> coverage and thickness are significantly correlated with the value ofθ, the difference between cumulative FDD (Freezing Degree Days) and TDD (Thawing Degree Days).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C11C0934D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C11C0934D"><span>Arctic <span class="hlt">sea-ice</span> syntheses: Charting across scope, scale, and knowledge systems</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Druckenmiller, M. L.; Perovich, D. K.; Francis, J. A.</p> <p>2017-12-01</p> <p>Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> supports and intersects a multitude of societal benefit areas, including regulating regional and global climates, structuring marine food webs, providing for traditional food provisioning by indigenous peoples, and constraining marine shipping and access. At the same time, <span class="hlt">sea</span> <span class="hlt">ice</span> is one of the most rapidly changing elements of the Arctic environment and serves as a source of key physical indicators for monitoring Arctic change. Before the present scientific interest in Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> for climate research, it has long been, and remains, a focus of applied research for industry and national security. For generations, the icy coastal <span class="hlt">seas</span> of the North have also provided a basis for the sharing of local and indigenous knowledge between Arctic residents and researchers, including anthropologists, biologists, and geoscientists. This presentation will summarize an ongoing review of existing synthesis studies of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span>. We will chart efforts to achieve system-level understanding across geography, temporal scales, and the ecosystem services that Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> supports. In doing so, we aim to illuminate the role of interdisciplinary science, together with local and indigenous experts, in advancing knowledge of the roles of <span class="hlt">sea</span> <span class="hlt">ice</span> in the Arctic system and beyond, reveal the historical and scientific evolution of <span class="hlt">sea-ice</span> research, and assess current gaps in system-scale understanding.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70020035','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70020035"><span><span class="hlt">Sea-ice</span> processes in the Laptev <span class="hlt">Sea</span> and their importance for sediment export</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Eicken, H.; Reimnitz, E.; Alexandrov, V.; Martin, T.; Kassens, H.; Viehoff, T.</p> <p>1997-01-01</p> <p>Based on remote-sensing data and an expedition during August-September 1993, the importance of the Laptev <span class="hlt">Sea</span> as a source area for sediment-laden <span class="hlt">sea</span> <span class="hlt">ice</span> was studied. <span class="hlt">Ice</span>-core analysis demonstrated the importance of dynamic <span class="hlt">ice</span>-growth mechanisms as compared to the multi-year cover of the Arctic Basin. <span class="hlt">Ice</span>-rafted sediment (IRS) was mostly associated with congealed frazil <span class="hlt">ice</span>, although evidence for other entrainment mechanisms (anchor <span class="hlt">ice</span>, entrainment into freshwater <span class="hlt">ice</span>) was also found. Concentrations of suspended particulate matter (SPM) in patches of dirty <span class="hlt">ice</span> averaged at 156 g m-3 (standard deviation ?? = 140 g m-3), with a background concentration of 5 g m-3. The potential for sediment entrainment over the broad, shallow Laptev <span class="hlt">Sea</span> shelf during fall freeze-up was studied through analysis of remote-sensing data and weather-station records for the period 1979-1994. Freeze-up commences on 26 September (?? = 7 d) and is completed after 19 days (?? = 6 d). Meteorological conditions as well as <span class="hlt">ice</span> extent prior to and during freeze-up vary considerably, the open-water area ranging between 107 x 103 and 447 x 103 km2. <span class="hlt">Ice</span> motion and transport of IRS were derived from satellite imagery and drifting buoys for the period during and after the expedition (mean <span class="hlt">ice</span> velocities of 0.04 and 0.05 m s-1, respectively). With a best-estimate sediment load of 16 t km-2 (ranging between 9 and 46 t km-2), sediment export from the eastern Laptev <span class="hlt">Sea</span> amounts to 4 x 10-6 t yr-1, with extremes of 2 x 10-6 and 11 x 106 t yr-1. Implications for the sediment budget of the Laptev shelf, in particular with respect to riverine input of SPM, which may be of the same order of magnitude, are discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19870053374&hterms=sonar&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dsonar','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19870053374&hterms=sonar&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dsonar"><span>Remote sensing as a research tool. [<span class="hlt">sea</span> <span class="hlt">ice</span> surveillance from aircraft and spacecraft</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Carsey, F. D.; Zwally, H. J.</p> <p>1986-01-01</p> <p>The application of aircraft and spacecraft remote sensing techniques to <span class="hlt">sea</span> <span class="hlt">ice</span> surveillance is evaluated. The effects of <span class="hlt">ice</span> in the air-<span class="hlt">sea-ice</span> system are examined. The measurement principles and characteristics of remote sensing methods for aircraft and spacecraft surveillance of <span class="hlt">sea</span> <span class="hlt">ice</span> are described. Consideration is given to ambient visible light, IR, passive microwave, active microwave, and laser altimeter and sonar systems. The applications of these systems to <span class="hlt">sea</span> <span class="hlt">ice</span> surveillance are discussed and examples are provided. Particular attention is placed on the use of microwave data and the relation between <span class="hlt">ice</span> thickness and <span class="hlt">sea</span> <span class="hlt">ice</span> interactions. It is noted that spacecraft and aircraft sensing techniques can successfully measure snow cover; <span class="hlt">ice</span> thickness; <span class="hlt">ice</span> type; <span class="hlt">ice</span> concentration; <span class="hlt">ice</span> velocity field; ocean temperature; surface wind vector field; and air, snow, and <span class="hlt">ice</span> surface temperatures.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1346837','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1346837"><span>A New Discrete Element <span class="hlt">Sea-Ice</span> Model for Earth System Modeling</span></a></p> <p><a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Turner, Adrian Keith</p> <p></p> <p><span class="hlt">Sea</span> <span class="hlt">ice</span> forms a frozen crust of <span class="hlt">sea</span> water oating in high-latitude oceans. It is a critical component of the Earth system because its formation helps to drive the global thermohaline circulation, and its seasonal waxing and waning in the high north and Southern Ocean signi cantly affects planetary albedo. Usually 4{6% of Earth's marine surface is covered by <span class="hlt">sea</span> <span class="hlt">ice</span> at any one time, which limits the exchange of heat, momentum, and mass between the atmosphere and ocean in the polar realms. Snow accumulates on <span class="hlt">sea</span> <span class="hlt">ice</span> and inhibits its vertical growth, increases its albedo, and contributes to pooledmore » water in melt ponds that darken the Arctic <span class="hlt">ice</span> surface in the spring. <span class="hlt">Ice</span> extent and volume are subject to strong seasonal, inter-annual and hemispheric variations, and climatic trends, which Earth System Models (ESMs) are challenged to simulate accurately (Stroeve et al., 2012; Stocker et al., 2013). This is because there are strong coupled feedbacks across the atmosphere-<span class="hlt">ice</span>-ocean boundary layers, including the <span class="hlt">ice</span>-albedo feedback, whereby a reduced <span class="hlt">ice</span> cover leads to increased upper ocean heating, further enhancing <span class="hlt">sea-ice</span> melt and reducing incident solar radiation re ected back into the atmosphere (Perovich et al., 2008). A reduction in perennial Arctic <span class="hlt">sea-ice</span> during the satellite era has been implicated in mid-latitude weather changes, including over North America (Overland et al., 2015). Meanwhile, most ESMs have been unable to simulate observed inter-annual variability and trends in Antarctic <span class="hlt">sea-ice</span> extent during the same period (Gagne et al., 2014).« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://pubs.usgs.gov/of/2007/1047/srp/srp029/of2007-1047srp029.pdf','USGSPUBS'); return false;" href="https://pubs.usgs.gov/of/2007/1047/srp/srp029/of2007-1047srp029.pdf"><span><span class="hlt">Sea</span> <span class="hlt">ice</span> concentration temporal variability over the Weddell <span class="hlt">Sea</span> and its relationship with tropical <span class="hlt">sea</span> surface temperature</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Barreira, S.; Compagnucci, R.</p> <p>2007-01-01</p> <p>Principal Components Analysis (PCA) in S-Mode (correlation between temporal series) was performed on <span class="hlt">sea</span> <span class="hlt">ice</span> monthly anomalies, in order to investigate which are the main temporal patterns, where are the homogenous areas located and how are they related to the <span class="hlt">sea</span> surface temperature (SST). This analysis provides 9 patterns (4 in the Amundsen and Bellingshausen <span class="hlt">Seas</span> and 5 in the Weddell <span class="hlt">Sea</span>) that represent the most important temporal features that dominated <span class="hlt">sea</span> <span class="hlt">ice</span> concentration anomalies (SICA) variability in the Weddell, Amundsen and Bellingshausen <span class="hlt">Seas</span> over the 1979-2000 period. Monthly Polar Gridded <span class="hlt">Sea</span> <span class="hlt">Ice</span> Concentrations data set derived from satellite information generated by NASA Team algorithm and acquired from the National Snow and <span class="hlt">Ice</span> Data Center (NSIDC) were used. Monthly means SST are provided by the National Center for Environmental Prediction reanalysis. The first temporal pattern series obtained by PCA has its homogeneous area located at the external region of the Weddell and Bellingshausen <span class="hlt">Seas</span> and Drake Passage, mostly north of 60°S. The second region is centered in 30°W and located at the southeast of the Weddell. The third area is localized east of 30°W and north of 60°S. South of the first area, the fourth PC series has its homogenous region, between 30° and 60°W. The last area is centered at 0° W and south of 60°S. Correlation charts between the five Principal Components series and SST were performed. Positive correlations over the Tropical Pacific Ocean were found for the five PCs when SST series preceded SICA PC series. The sign of the correlation could relate the occurrence of an El Niño/Southern Oscillation (ENSO) warm (cold) event with posterior positive (negative) anomalies of <span class="hlt">sea</span> <span class="hlt">ice</span> concentration over the Weddell <span class="hlt">Sea</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C11E..03B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C11E..03B"><span>Neoglacial Antarctic <span class="hlt">sea-ice</span> expansion driven by mid-Holocene retreat of the Ross <span class="hlt">Ice</span> Shelf.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bendle, J. A.; Newton, K.; Mckay, R. M.; Crosta, X.; Etourneau, J.; Anya, A. B.; Seki, O.; Golledge, N. R.; Bertler, N. A. N.; Willmott, V.; Schouten, S.; Riesselman, C. R.; Masse, G.; Dunbar, R. B.</p> <p>2017-12-01</p> <p>Recent decades have seen expanding Antarctic <span class="hlt">sea-ice</span> coverage, coeval with thinning West Antarctic <span class="hlt">Ice</span> Sheet (WAIS) <span class="hlt">ice</span> shelves and the rapid freshening of surface and bottom waters along the Antarctic margin. The mid-Holocene Neoglacial transition represents the last comparable baseline shift in <span class="hlt">sea-ice</span> behaviour. The drivers and feedbacks involved in both the recent and Holocene events are poorly understood and characterised by large proxy-model mismatches. We present new records of compound specific fatty acid isotope analyses (δ2H-FA), highly-branched isoprenoid alkenes (HBIs) TEX86L temperatures, grain-size, mass accumulations rates (MARs) and image analyses from a 171m Holocene sediment sequence from Site U1357 (IODP leg 318). In combination with published records we reconstruct Holocene changes in glacial meltwater, sedimentary inputs and <span class="hlt">sea-ice</span>. The early Holocene (11 to 10 ka) is characterised by large fluctuations in inputs of deglacial meltwater and sediments and seismic evidence of downlapping material from the south, suggesting a dominating influence from glacial retreat of the local outlet glaciers. From 10 to 8 ka there is decreasing meltwater inputs, an onlapping drift and advection of material from the east. After ca. 8 ka positively correlated δ2H-FA and MARs infer that pulses of glacial melt correlate to stronger easterly currents, driving erosion of material from upstream banks and that the Ross <span class="hlt">Ice</span> Shelf (RIS) becomes a major influence. A large mid-Holocene meltwater pulse (preceded by warming TEX86L temperatures) is evident between ca. 6 to 4.5 ka, culminating in a rapid and permanent increase in <span class="hlt">sea-ice</span> from 4.5 ka. This is coeval with cosmogenic nuclide evidence for a rapid thinning of the Antarctic <span class="hlt">ice</span> sheet during the mid-Holocene (Hein et al., 2016). We suggest this represents a final major pulse of deglaciation from the Ross <span class="hlt">Ice</span> Shelf, which initiates the Neoglacial, driving cool surface waters along the coast and greater <span class="hlt">sea-ice</span></p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1291188','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1291188"><span>Quantifying uncertainty and sensitivity in <span class="hlt">sea</span> <span class="hlt">ice</span> models</span></a></p> <p><a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Urrego Blanco, Jorge Rolando; Hunke, Elizabeth Clare; Urban, Nathan Mark</p> <p></p> <p>The Los Alamos <span class="hlt">Sea</span> <span class="hlt">Ice</span> model has a number of input parameters for which accurate values are not always well established. We conduct a variance-based sensitivity analysis of hemispheric <span class="hlt">sea</span> <span class="hlt">ice</span> properties to 39 input parameters. The method accounts for non-linear and non-additive effects in the model.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2001JQS....16..419S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2001JQS....16..419S"><span>A critical review of the glaciomarine model for Irish <span class="hlt">sea</span> deglaciation: evidence from southern Britain, the Celtic shelf and <span class="hlt">adjacent</span> continental slope</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Scourse, J. D.; Furze, M. F. A.</p> <p>2001-07-01</p> <p>In support of their glaciomarine model for the deglaciation of the Irish <span class="hlt">Sea</span> basin, Eyles and McCabe cited the occurrence of distal glaciomarine mud drapes onshore in the Isles of Scilly and North Devon, and of arctic beach-face gravels and sands around the shores of the Celtic <span class="hlt">Sea</span>. Glacial and <span class="hlt">sea</span>-level data from the southern part of the Irish <span class="hlt">Sea</span> in the terminal zone of the <span class="hlt">ice</span> stream and the <span class="hlt">adjacent</span> continental slope are reviewed here to test this aspect of the model. The suggestion that the glacial sequences of both the Isles of Scilly and Fremington in North Devon are glaciomarine mud drapes is rejected. An actively calving tidewater margin only occurred early in the deglacial sequence close to the terminal zone in the south-central Celtic <span class="hlt">Sea</span>. Relative <span class="hlt">sea</span>-levels were lower, and therefore glacio-isostatic depression less, than envisaged in the glaciomarine model. Geochronological, sedimentological and biostratigraphical data indicate that the raised beach sequences around the shores of the Celtic <span class="hlt">Sea</span> and English Channel were deposited at, or during regression soon after, interglacial eustatic highstands. Evidence for <span class="hlt">ice</span>-rafting at a time of high relative <span class="hlt">sea</span>-levels is restricted to a phase(s) earlier than the Late Devensian. These data indicate that the raised beach sequences have no bearing on the style of Irish <span class="hlt">Sea</span> deglaciation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014QSRv...87...60H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014QSRv...87...60H"><span>The <span class="hlt">sea</span>-level fingerprints of <span class="hlt">ice</span>-sheet collapse during interglacial periods</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hay, Carling; Mitrovica, Jerry X.; Gomez, Natalya; Creveling, Jessica R.; Austermann, Jacqueline; E. Kopp, Robert</p> <p>2014-03-01</p> <p>Studies of <span class="hlt">sea</span> level during previous interglacials provide insight into the stability of polar <span class="hlt">ice</span> sheets in the face of global climate change. Commonly, these studies correct ancient <span class="hlt">sea</span>-level highstands for the contaminating effect of isostatic adjustment associated with past <span class="hlt">ice</span> age cycles, and interpret the residuals as being equivalent to the peak eustatic <span class="hlt">sea</span> level associated with excess melting, relative to present day, of ancient polar <span class="hlt">ice</span> sheets. However, the collapse of polar <span class="hlt">ice</span> sheets produces a distinct geometry, or fingerprint, of <span class="hlt">sea</span>-level change, which must be accounted for to accurately infer peak eustatic <span class="hlt">sea</span> level from site-specific residual highstands. To explore this issue, we compute fingerprints associated with the collapse of the Greenland <span class="hlt">Ice</span> Sheet, West Antarctic <span class="hlt">Ice</span> Sheet, and marine sectors of the East Antarctic <span class="hlt">Ice</span> Sheet in order to isolate regions that would have been subject to greater-than-eustatic <span class="hlt">sea</span>-level change for all three cases. These fingerprints are more robust than those associated with modern melting events, when applied to infer eustatic <span class="hlt">sea</span> level, because: (1) a significant collapse of polar <span class="hlt">ice</span> sheets reduces the sensitivity of the computed fingerprints to uncertainties in the geometry of the melt regions; and (2) the <span class="hlt">sea</span>-level signal associated with the collapse will dominate the signal from steric effects. We evaluate these fingerprints at a suite of sites where <span class="hlt">sea</span>-level records from interglacial marine isotopes stages (MIS) 5e and 11 have been obtained. Using these results, we demonstrate that previously discrepant estimates of peak eustatic <span class="hlt">sea</span> level during MIS5e based on <span class="hlt">sea</span>-level markers in Australia and the Seychelles are brought into closer accord.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..15.7955K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..15.7955K"><span>Springtime atmospheric transport controls Arctic summer <span class="hlt">sea-ice</span> extent</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kapsch, Marie; Graversen, Rune; Tjernström, Michael</p> <p>2013-04-01</p> <p>The <span class="hlt">sea-ice</span> extent in the Arctic has been steadily decreasing during the satellite remote sensing era, 1979 to present, with the highest rate of retreat found in September. Contributing factors causing the <span class="hlt">ice</span> retreat are among others: changes in surface air temperature (SAT; Lindsay and Zhang, 2005), <span class="hlt">ice</span> circulation in response to winds/pressure patterns (Overland et al., 2008) and ocean currents (Comiso et al., 2008), as well as changes in radiative fluxes (e.g. due to changes in cloud cover; Francis and Hunter, 2006; Maksimovich and Vihma, 2012) and ocean conditions. However, large interannual variability is superimposed onto the declining trend - the <span class="hlt">ice</span> extent by the end of the summer varies by several million square kilometer between successive years (Serreze et al., 2007). But what are the processes causing the year-to-year <span class="hlt">ice</span> variability? A comparison of years with an anomalously large September <span class="hlt">sea-ice</span> extent (HIYs - high <span class="hlt">ice</span> years) with years showing an anomalously small <span class="hlt">ice</span> extent (LIYs - low <span class="hlt">ice</span> years) reveals that the <span class="hlt">ice</span> variability is most pronounced in the Arctic Ocean north of Siberia (which became almost entirely <span class="hlt">ice</span> free in September of 2007 and 2012). Significant <span class="hlt">ice</span>-concentration anomalies of up to 30% are observed for LIYs and HIYs in this area. Focusing on this area we find that the greenhouse effect associated with clouds and water-vapor in spring is crucial for the development of the <span class="hlt">sea</span> <span class="hlt">ice</span> during the subsequent months. In years where the end-of-summer <span class="hlt">sea-ice</span> extent is well below normal, a significantly enhanced transport of humid air is evident during spring into the region where the <span class="hlt">ice</span> retreat is encountered. The anomalous convergence of humidity increases the cloudiness, resulting in an enhancement of the greenhouse effect. As a result, downward longwave radiation at the surface is larger than usual. In mid May, when the <span class="hlt">ice</span> anomaly begins to appear and the surface albedo therefore becomes anomalously low, the net shortwave radiation</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC43J..05S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC43J..05S"><span>Integrating Observations and Models to Better Understand a Changing Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> Cover</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Stroeve, J. C.</p> <p>2017-12-01</p> <p>TThe loss of the Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> cover has captured the world's attention. While much attention has been paid to the summer <span class="hlt">ice</span> loss, changes are not limited to summer. The last few winters have seen record low <span class="hlt">sea</span> <span class="hlt">ice</span> extents, with 2017 marking the 3rdyear in a row with a new record low for the winter maximum extent. More surprising is the number of consecutive months between January 2016 through April 2017 with <span class="hlt">ice</span> extent anomalies more than 2 standard deviations below the 1981-2010 mean. Additionally, October 2016 through April 2017 saw 7 consecutive months with record low extents, something that had not happened before in the last 4 decades of satellite observations. As larger parts of the Arctic Ocean become <span class="hlt">ice</span>-free in summer, regional <span class="hlt">seas</span> gradually transition from a perennial to a seasonal <span class="hlt">ice</span> cover. The Barents <span class="hlt">Sea</span> is already only seasonally <span class="hlt">ice</span> covered, whereas the Kara <span class="hlt">Sea</span> has recently lost most of its summer <span class="hlt">ice</span> and is thereby starting to become a seasonally <span class="hlt">ice</span> covered region. These changes serve as harbinger for what's to come for other Arctic <span class="hlt">seas</span>. Given the rapid pace of change, there is an urgent need to improve our understanding of the drivers behind Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> loss, the implications of this <span class="hlt">ice</span> loss and to predict future changes to better inform policy makers. Climate models play a fundamental role in helping us synthesize the complex elements of the Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> system yet generally fail to simulate key features of the <span class="hlt">sea</span> <span class="hlt">ice</span> system and the pace of <span class="hlt">sea</span> <span class="hlt">ice</span> loss. Nevertheless, modeling advances continue to provide better means of diagnosing <span class="hlt">sea</span> <span class="hlt">ice</span> change, and new insights are likely to be gained with model output from the 6th phase of the Coupled Model Intercomparison Project (CMIP6). The CMIP6 <span class="hlt">Sea-Ice</span> Model Intercomparison Project (SIMIP) aim is to better understand biases and errors in <span class="hlt">sea</span> <span class="hlt">ice</span> simulations so that we can improve our understanding of the likely future evolution of the <span class="hlt">sea</span> <span class="hlt">ice</span> cover and its impacts on global climate. To</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFMGC13C1092S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFMGC13C1092S"><span>Impacts of projected <span class="hlt">sea</span> <span class="hlt">ice</span> changes on trans-Arctic navigation</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Stephenson, S. R.; Smith, L. C.</p> <p>2012-12-01</p> <p>Reduced Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> continues to be a palpable signal of global change. Record lows in September <span class="hlt">sea</span> <span class="hlt">ice</span> extent from 2007 - 2011 have fueled speculation that trans-Arctic navigation routes may become physically viable in the 21st century. General Circulation Models project a nearly <span class="hlt">ice</span>-free Arctic Ocean in summer by mid-century; however, how reduced <span class="hlt">sea</span> <span class="hlt">ice</span> will realistically impact navigation is not well understood. Using the ATAM (Arctic Transportation Accessibility Model) we present simulations of 21st-century trans-Arctic voyages as a function of climatic (<span class="hlt">ice</span>) conditions and vessel class. Simulations are based on <span class="hlt">sea</span> <span class="hlt">ice</span> projections for three climatic forcing scenarios (RCP 4.5, 6.0, and 8.5 W/m^2) representing present-day and mid-century conditions, assuming Polar Class 6 (PC6) and open-water vessels (OW) with medium and no <span class="hlt">ice</span>-breaking capability, respectively. Optimal least-cost routes (minimizing travel time while avoiding <span class="hlt">ice</span> impassible to a given vessel class) between the North Atlantic and the Bering Strait were calculated for summer months of each time window. While Arctic navigation depends on other factors besides <span class="hlt">sea</span> <span class="hlt">ice</span> including economics, infrastructure, bathymetry, current, and weather, these projections should be useful for strategic planning by governments, regulatory and environmental agencies, and the global maritime industry to assess potential changes in the spatial and temporal ranges of Arctic marine operations.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EaFut...5..633N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EaFut...5..633N"><span>Increasing transnational <span class="hlt">sea-ice</span> exchange in a changing Arctic Ocean</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Newton, Robert; Pfirman, Stephanie; Tremblay, Bruno; DeRepentigny, Patricia</p> <p>2017-06-01</p> <p>The changing Arctic <span class="hlt">sea-ice</span> cover is likely to impact the trans-border exchange of <span class="hlt">sea</span> <span class="hlt">ice</span> between the exclusive economic zones (EEZs) of the Arctic nations, affecting the risk of <span class="hlt">ice</span>-rafted contamination. We apply the Lagrangian <span class="hlt">Ice</span> Tracking System (LITS) to identify <span class="hlt">sea-ice</span> formation events and track <span class="hlt">sea</span> <span class="hlt">ice</span> to its melt locations. Most <span class="hlt">ice</span> (52%) melts within 100 km of where it is formed; ca. 21% escapes from its EEZ. Thus, most contaminants will be released within an <span class="hlt">ice</span> parcel's originating EEZ, while material carried by over 1 00,000 km2 of ice—an area larger than France and Germany combined—will be released to other nations' waters. Between the periods 1988-1999 and 2000-2014, <span class="hlt">sea-ice</span> formation increased by ˜17% (roughly 6 million km2 vs. 5 million km2 annually). Melting peaks earlier; freeze-up begins later; and the central Arctic Ocean is more prominent in both formation and melt in the later period. The total area of <span class="hlt">ice</span> transported between EEZs increased, while transit times decreased: for example, Russian <span class="hlt">ice</span> reached melt locations in other nations' EEZs an average of 46% faster while North American <span class="hlt">ice</span> reached destinations in Eurasian waters an average of 37% faster. Increased trans-border exchange is mainly a result of increased speed (˜14% per decade), allowing first-year <span class="hlt">ice</span> to escape the summer melt front, even as the front extends further north. Increased trans-border exchange over shorter times is bringing the EEZs of the Arctic nations closer together, which should be taken into account in policy development—including establishment of marine-protected areas.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1342069','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1342069"><span>Moving beyond the total <span class="hlt">sea</span> <span class="hlt">ice</span> extent in gauging model biases</span></a></p> <p><a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Ivanova, Detelina P.; Gleckler, Peter J.; Taylor, Karl E.</p> <p></p> <p>Here, reproducing characteristics of observed <span class="hlt">sea</span> <span class="hlt">ice</span> extent remains an important climate modeling challenge. This study describes several approaches to improve how model biases in total <span class="hlt">sea</span> <span class="hlt">ice</span> distribution are quantified, and applies them to historically forced simulations contributed to phase 5 of the Coupled Model Intercomparison Project (CMIP5). The quantity of hemispheric total <span class="hlt">sea</span> <span class="hlt">ice</span> area, or some measure of its equatorward extent, is often used to evaluate model performance. A new approach is introduced that investigates additional details about the structure of model errors, with an aim to reduce the potential impact of compensating errors when gauging differencesmore » between simulated and observed <span class="hlt">sea</span> <span class="hlt">ice</span>. Using multiple observational datasets, several new methods are applied to evaluate the climatological spatial distribution and the annual cycle of <span class="hlt">sea</span> <span class="hlt">ice</span> cover in 41 CMIP5 models. It is shown that in some models, error compensation can be substantial, for example resulting from too much <span class="hlt">sea</span> <span class="hlt">ice</span> in one region and too little in another. Error compensation tends to be larger in models that agree more closely with the observed total <span class="hlt">sea</span> <span class="hlt">ice</span> area, which may result from model tuning. The results herein suggest that consideration of only the total hemispheric <span class="hlt">sea</span> <span class="hlt">ice</span> area or extent can be misleading when quantitatively comparing how well models agree with observations. Further work is needed to fully develop robust methods to holistically evaluate the ability of models to capture the finescale structure of <span class="hlt">sea</span> <span class="hlt">ice</span> characteristics; however, the “sector scale” metric used here aids in reducing the impact of compensating errors in hemispheric integrals.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1342069-moving-beyond-total-sea-ice-extent-gauging-model-biases','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1342069-moving-beyond-total-sea-ice-extent-gauging-model-biases"><span>Moving beyond the total <span class="hlt">sea</span> <span class="hlt">ice</span> extent in gauging model biases</span></a></p> <p><a target="_blank" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Ivanova, Detelina P.; Gleckler, Peter J.; Taylor, Karl E.; ...</p> <p>2016-11-29</p> <p>Here, reproducing characteristics of observed <span class="hlt">sea</span> <span class="hlt">ice</span> extent remains an important climate modeling challenge. This study describes several approaches to improve how model biases in total <span class="hlt">sea</span> <span class="hlt">ice</span> distribution are quantified, and applies them to historically forced simulations contributed to phase 5 of the Coupled Model Intercomparison Project (CMIP5). The quantity of hemispheric total <span class="hlt">sea</span> <span class="hlt">ice</span> area, or some measure of its equatorward extent, is often used to evaluate model performance. A new approach is introduced that investigates additional details about the structure of model errors, with an aim to reduce the potential impact of compensating errors when gauging differencesmore » between simulated and observed <span class="hlt">sea</span> <span class="hlt">ice</span>. Using multiple observational datasets, several new methods are applied to evaluate the climatological spatial distribution and the annual cycle of <span class="hlt">sea</span> <span class="hlt">ice</span> cover in 41 CMIP5 models. It is shown that in some models, error compensation can be substantial, for example resulting from too much <span class="hlt">sea</span> <span class="hlt">ice</span> in one region and too little in another. Error compensation tends to be larger in models that agree more closely with the observed total <span class="hlt">sea</span> <span class="hlt">ice</span> area, which may result from model tuning. The results herein suggest that consideration of only the total hemispheric <span class="hlt">sea</span> <span class="hlt">ice</span> area or extent can be misleading when quantitatively comparing how well models agree with observations. Further work is needed to fully develop robust methods to holistically evaluate the ability of models to capture the finescale structure of <span class="hlt">sea</span> <span class="hlt">ice</span> characteristics; however, the “sector scale” metric used here aids in reducing the impact of compensating errors in hemispheric integrals.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018AdAtS..35...27K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018AdAtS..35...27K"><span>Atmospheric precursors of and response to anomalous Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> in CMIP5 models</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kelleher, Michael; Screen, James</p> <p>2018-01-01</p> <p>This study examines pre-industrial control simulations from CMIP5 climate models in an effort to better understand the complex relationships between Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> and the stratosphere, and between Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> and cold winter temperatures over Eurasia. We present normalized regressions of Arctic <span class="hlt">sea-ice</span> area against several atmospheric variables at extended lead and lag times. Statistically significant regressions are found at leads and lags, suggesting both atmospheric precursors of, and responses to, low <span class="hlt">sea</span> <span class="hlt">ice</span>; but generally, the regressions are stronger when the atmosphere leads <span class="hlt">sea</span> <span class="hlt">ice</span>, including a weaker polar stratospheric vortex indicated by positive polar cap height anomalies. Significant positive midlatitude eddy heat flux anomalies are also found to precede low <span class="hlt">sea</span> <span class="hlt">ice</span>. We argue that low <span class="hlt">sea</span> <span class="hlt">ice</span> and raised polar cap height are both a response to this enhanced midlatitude eddy heat flux. The so-called "warm Arctic, cold continents" anomaly pattern is present one to two months before low <span class="hlt">sea</span> <span class="hlt">ice</span>, but is absent in the months following low <span class="hlt">sea</span> <span class="hlt">ice</span>, suggesting that the Eurasian cooling and low <span class="hlt">sea</span> <span class="hlt">ice</span> are driven by similar processes. Lastly, our results suggest a dependence on the geographic region of low <span class="hlt">sea</span> <span class="hlt">ice</span>, with low Barents-Kara <span class="hlt">Sea</span> <span class="hlt">ice</span> correlated with a weakened polar stratospheric vortex, whilst low <span class="hlt">Sea</span> of Okhotsk <span class="hlt">ice</span> is correlated with a strengthened polar vortex. Overall, the results support a notion that the <span class="hlt">sea</span> <span class="hlt">ice</span>, polar stratospheric vortex and Eurasian surface temperatures collectively respond to large-scale changes in tropospheric circulation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4951643','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4951643"><span>Biopolymers form a gelatinous microlayer at the air-<span class="hlt">sea</span> interface when Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> melts</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Galgani, Luisa; Piontek, Judith; Engel, Anja</p> <p>2016-01-01</p> <p>The interface layer between ocean and atmosphere is only a couple of micrometers thick but plays a critical role in climate relevant processes, including the air-<span class="hlt">sea</span> exchange of gas and heat and the emission of primary organic aerosols (POA). Recent findings suggest that low-level cloud formation above the Arctic Ocean may be linked to organic polymers produced by marine microorganisms. <span class="hlt">Sea</span> <span class="hlt">ice</span> harbors high amounts of polymeric substances that are produced by cells growing within the <span class="hlt">sea-ice</span> brine. Here, we report from a research cruise to the central Arctic Ocean in 2012. Our study shows that microbial polymers accumulate at the air-<span class="hlt">sea</span> interface when the <span class="hlt">sea</span> <span class="hlt">ice</span> melts. Proteinaceous compounds represented the major fraction of polymers supporting the formation of a gelatinous interface microlayer and providing a hitherto unrecognized potential source of marine POA. Our study indicates a novel link between <span class="hlt">sea</span> <span class="hlt">ice</span>-ocean and atmosphere that may be sensitive to climate change. PMID:27435531</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li class="active"><span>23</span></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_23 --> <div id="page_24" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li class="active"><span>24</span></li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="461"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.A42C..05D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.A42C..05D"><span>Arctic spring ozone reduction associated with projected <span class="hlt">sea</span> <span class="hlt">ice</span> loss</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Deser, C.; Sun, L.; Tomas, R. A.; Polvani, L. M.</p> <p>2013-12-01</p> <p>The impact of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> loss on the stratosphere is investigated using the Whole-Atmosphere Community Climate Model (WACCM), by prescribing the <span class="hlt">sea</span> <span class="hlt">ice</span> in the late 20th century and late 21st century, respectively. The localized <span class="hlt">Sea</span> Surface Temperature (SST) change associated with <span class="hlt">sea</span> <span class="hlt">ice</span> melt is also included in the future run. Overall, the model simulates a negative annular-mode response in the winter and spring. In the stratosphere, polar vortex strengthens from February to April, peaking in March. Consistent with it, there is an anomalous cooling in the high-latitude stratosphere, and polar cap ozone reduction is up to 20 DU. Since the difference between these two runs lies only in the <span class="hlt">sea</span> <span class="hlt">ice</span> and localized SST in the Arctic, the stratospheric circulation and ozone changes can be attributed to the surface forcing. Eliassen-Palm analysis reveals that the upward propagation of planetary waves is suppressed in the spring as a consequence of <span class="hlt">sea</span> <span class="hlt">ice</span> loss. The reduction in propagation causes less wave dissipation and thus less zonal wind deceleration in the extratropical stratosphere.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010EGUGA..12.8769F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010EGUGA..12.8769F"><span>Peopling of the high Arctic - induced by <span class="hlt">sea</span> <span class="hlt">ice</span>?</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Funder, Svend</p> <p>2010-05-01</p> <p>'We travelled in the winter after the return of daylight and did not go into fixed camp until spring, when the <span class="hlt">ice</span> broke up. There was good hunting on the way, seals, beluga, walrus, bear.' (From Old Merkrusârk's account of his childhood's trek from Baffin Island to Northwest Greenland, told to Knud Rasmussen on Saunders Island in 1904) Five thousand years ago people moving eastwards from Beringia spread over the barrens of the Canadian high Arctic. This was the first of three waves of prehistoric Arctic 'cultures', which eventually reached Greenland. The passage into Greenland has to go through the northernmost and most hostile part of the country with a 5 month Polar night, and to understand this extraordinary example of human behaviour and endurance, it has been customary to invoke a more favourable (warmer) climate. This presentation suggests that land-fast <span class="hlt">sea</span> <span class="hlt">ice</span>, i.e. stationary <span class="hlt">sea</span> <span class="hlt">ice</span> anchored to the coast, is among the most important environmental factors behind the spread of prehistoric polar cultures. The <span class="hlt">ice</span> provides the road for travelling and social communion - and access to the most important source of food, the ocean. In the LongTerm Project (2006 and 2007) we attempted to establish a Holocene record for <span class="hlt">sea</span> <span class="hlt">ice</span> variations along oceanic coasts in northernmost Greenland. Presently the coasts north of 80° N are beleaguered by year-round <span class="hlt">sea</span> <span class="hlt">ice</span> - for ten months this is land-fast <span class="hlt">ice</span>, and only for a period in the stormy autumn months are the coasts exposed to pack-<span class="hlt">ice</span>. This presentation Land-fast <span class="hlt">ice</span> - as opposed to pack-<span class="hlt">ice</span> - is a product of local temperatures, but its duration over the year, and especially into the daylight season, is also conditioned by other factors, notably wind strength. In the geological record we recognize long lasting land-fast <span class="hlt">ice</span> by two absences: absence of traces of wave action (no beach formation), which, however, can also be a result of pack-<span class="hlt">ice</span> along the coast; - and absence of driftwood on the shore (land-fast <span class="hlt">ice</span></p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70021023','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70021023"><span>Physical characteristics of summer <span class="hlt">sea</span> <span class="hlt">ice</span> across the Arctic Ocean</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Tucker, W. B.; Gow, A.J.; Meese, D.A.; Bosworth, H.W.; Reimnitz, E.</p> <p>1999-01-01</p> <p><span class="hlt">Sea</span> <span class="hlt">ice</span> characteristics were investigated during July and August on the 1994 transect across the Arctic Ocean. Properties examined from <span class="hlt">ice</span> cores included salinity, temperature, and <span class="hlt">ice</span> structure. Salinities measured near zero at the surface, increasing to 3-4??? at the <span class="hlt">ice</span>-water interface. <span class="hlt">Ice</span> crystal texture was dominated by columnar <span class="hlt">ice</span>, comprising 90% of the <span class="hlt">ice</span> sampled. Surface albedos of various <span class="hlt">ice</span> types, measured with radiometers, showed integrated shortwave albedos of 0.1 to 0.3 for melt ponds, 0.5 for bare, discolored <span class="hlt">ice</span>, and 0.6 to 0.8 for a deteriorated surface or snow-covered <span class="hlt">ice</span>. Aerial photography was utilized to document the distribution of open melt ponds, which decreased from 12% coverage of the <span class="hlt">ice</span> surface in late July at 76??N to almost none in mid-August at 88??N. Most melt ponds were shallow, and depth bore no relationship to size. Sediment was pervasive from the southern Chukchi <span class="hlt">Sea</span> to the north pole, occurring in bands or patches. It was absent in the Eurasian Arctic, where it had been observed on earlier expeditions. Calculations of reverse trajectories of the sediment-bearing floes suggest that the southernmost sediment was entrained during <span class="hlt">ice</span> formation in the Beaufort <span class="hlt">Sea</span> while more northerly samples probably originated in the East Siberian <span class="hlt">Sea</span>, some as far west as the New Siberian Islands.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFM.C24A..03K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFM.C24A..03K"><span>Seasonal climate information preserved within West Antarctic <span class="hlt">ice</span> cores and its relation to large-scale atmospheric circulation and regional <span class="hlt">sea</span> <span class="hlt">ice</span> variations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Küttel, M.; Steig, E. J.; Ding, Q.; Battisti, D. S.</p> <p>2010-12-01</p> <p>Recent evidence suggests that West Antarctica has been warming since at least the 1950s. With the instrumental record being limited to the mid-20th century, indirect information from stable isotopes (δ18O and δD, hereafter collectively δ) preserved within <span class="hlt">ice</span> cores have commonly been used to place this warming into a long term context. Here, using a large number of δ records obtained during the International Trans-Antarctic Scientific Expedition (ITASE), past variations in West Antarctic δ are not only investigated over time but also in space. This study therefore provides an important complement to longer records from single locations as e.g. the currently being processed West Antarctic <span class="hlt">ice</span> sheet (WAIS) Divide <span class="hlt">ice</span> core. Although snow accumulation rates at the ITASE sites in West Antarctica are variable, they are generally high enough to allow studies on sub-annual scale over the last 50-100 years. Here, we show that variations in δ in this region are strongly related to the state of the large-scale atmospheric circulation as well as <span class="hlt">sea</span> <span class="hlt">ice</span> variations in the <span class="hlt">adjacent</span> Southern Ocean, with important seasonal changes. While a strong relationship to <span class="hlt">sea</span> <span class="hlt">ice</span> changes in the Ross and Amundsen <span class="hlt">Sea</span> as well as to the atmospheric circulation offshore is found during austral fall (MAM) and winter (JJA), only modest correlations are found during spring (SON) and summer (DJF). Interestingly, the correlations with the atmospheric circulation in the latter two seasons have the strongest signal over the Antarctic continent, but not offshore - an important difference to MAM and JJA. These seasonal changes are in good agreement with the seasonally varying predominant circulation: meridional with more frequent storms in the Amundsen <span class="hlt">Sea</span> during MAM and JJA and more zonal and stable during SON and DJF. The relationship to regional temperature is similarly seasonally variable with highest correlations found during MAM and JJA. Notably, the circulation pattern found to be strongest</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1422909','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1422909"><span>Climate Modeling and Causal Identification for <span class="hlt">Sea</span> <span class="hlt">Ice</span> Predictability</span></a></p> <p><a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Hunke, Elizabeth Clare; Urrego Blanco, Jorge Rolando; Urban, Nathan Mark</p> <p></p> <p>This project aims to better understand causes of ongoing changes in the Arctic climate system, particularly as decreasing <span class="hlt">sea</span> <span class="hlt">ice</span> trends have been observed in recent decades and are expected to continue in the future. As part of the <span class="hlt">Sea</span> <span class="hlt">Ice</span> Prediction Network, a multi-agency effort to improve <span class="hlt">sea</span> <span class="hlt">ice</span> prediction products on seasonal-to-interannual time scales, our team is studying sensitivity of <span class="hlt">sea</span> <span class="hlt">ice</span> to a collection of physical process and feedback mechanism in the coupled climate system. During 2017 we completed a set of climate model simulations using the fully coupled ACME-HiLAT model. The simulations consisted of experiments inmore » which cloud, <span class="hlt">sea</span> <span class="hlt">ice</span>, and air-ocean turbulent exchange parameters previously identified as important for driving output uncertainty in climate models were perturbed to account for parameter uncertainty in simulated climate variables. We conducted a sensitivity study to these parameters, which built upon a previous study we made for standalone simulations (Urrego-Blanco et al., 2016, 2017). Using the results from the ensemble of coupled simulations, we are examining robust relationships between climate variables that emerge across the experiments. We are also using causal discovery techniques to identify interaction pathways among climate variables which can help identify physical mechanisms and provide guidance in predictability studies. This work further builds on and leverages the large ensemble of standalone <span class="hlt">sea</span> <span class="hlt">ice</span> simulations produced in our previous w14_seaice project.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18..693S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18..693S"><span>Development of source specific diatom lipids biomarkers as Antarctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> proxies</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Smik, Lukas; Belt, Simon T.; Brown, Thomas A.; Lieser, Jan L.; Armand, Leanne K.; Leventer, Amy; Allen, Claire S.</p> <p>2016-04-01</p> <p>C25 highly branched isoprenoid (HBI) are lipid biomarkers biosynthesised by a relatively small number of diatom genera, but are, nonetheless, common constituents of global marine sediments. The occurrence and variable abundance of certain C25 highly branched isoprenoid (HBI) biomarkers in Antarctic marine sediments has previously been proposed as a proxy measure of paleo <span class="hlt">sea-ice</span> extent in the Southern Ocean and a small number of paleo <span class="hlt">sea-ice</span> reconstructions based on the variable abundances of these HBIs have appeared in recent years. However, the development of HBIs as proxies for Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> is much less advanced than that for IP25 (another HBI) in the Arctic and has been based on relatively small number of analyses in <span class="hlt">sea</span> <span class="hlt">ice</span>, water column and sediment samples. To provide further insights into the use of these HBIs as proxies for Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span>, we here describe an assessment of their distributions in surface water, surface sediment and <span class="hlt">sea</span> <span class="hlt">ice</span> samples collected from a number of Antarctic locations experiencing contrasting <span class="hlt">sea</span> <span class="hlt">ice</span> conditions in recent years. Our study shows that distributions of a di-unsaturated HBI (diene II) and tri-unsaturated HBI (triene III) in surface water samples were found to be extremely sensitive to the local <span class="hlt">sea-ice</span> conditions, with diene II detected for sampling sites that experienced seasonal <span class="hlt">sea</span> <span class="hlt">ice</span> and highest concentrations found in coastal locations with longer-lasting <span class="hlt">ice</span> cover and a recurrent polynya. In contrast, triene III was observed in all of the samples analysed, but with highest concentrations within the region of the retreating <span class="hlt">sea</span> <span class="hlt">ice</span> edge, an observation consistent with significant environmental control over the biosynthesis of diene II and triene III by <span class="hlt">sea</span> <span class="hlt">ice</span> diatoms and open water phytoplankton, respectively. However, additional local factors, such as those associated with polynya formation, may also exert some control over the distribution of triene III and the relative concentrations of diene II and</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120009093','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120009093"><span>The Antarctic <span class="hlt">Ice</span> Sheet, <span class="hlt">Sea</span> <span class="hlt">Ice</span>, and the Ozone Hole: Satellite Observations of how they are Changing</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Parkinson, Claire L.</p> <p>2012-01-01</p> <p>Antarctica is the Earth's coldest and highest continent and has major impacts on the climate and life of the south polar vicinity. It is covered almost entirely by the Earth's largest <span class="hlt">ice</span> sheet by far, with a volume of <span class="hlt">ice</span> so great that if all the Antarctic <span class="hlt">ice</span> were to go into the ocean (as <span class="hlt">ice</span> or liquid water), this would produce a global <span class="hlt">sea</span> level rise of about 60 meters (197 feet). The continent is surrounded by <span class="hlt">sea</span> <span class="hlt">ice</span> that in the wintertime is even more expansive than the continent itself and in the summertime reduces to only about a sixth of its wintertime extent. Like the continent, the expansive <span class="hlt">sea</span> <span class="hlt">ice</span> cover has major impacts, reflecting the sun's radiation back to space, blocking exchanges between the ocean and the atmosphere, and providing a platform for some animal species while impeding other species. Far above the continent, the Antarctic ozone hole is a major atmospheric phenomenon recognized as human-caused and potentially quite serious to many different life forms. Satellites are providing us with remarkable information about the <span class="hlt">ice</span> sheet, the <span class="hlt">sea</span> <span class="hlt">ice</span>, and the ozone hole. Satellite visible and radar imagery are providing views of the large scale structure of the <span class="hlt">ice</span> sheet never seen before; satellite laser altimetry has produced detailed maps of the topography of the <span class="hlt">ice</span> sheet; and an innovative gravity-measuring two-part satellite has allowed mapping of regions of mass loss and mass gain on the <span class="hlt">ice</span> sheet. The surrounding <span class="hlt">sea</span> <span class="hlt">ice</span> cover has a satellite record that goes back to the 1970s, allowing trend studies that show a decreasing <span class="hlt">sea</span> <span class="hlt">ice</span> presence in the region of the Bellingshausen and Amundsen <span class="hlt">seas</span>, to the west of the prominent Antarctic Peninsula, but increasing <span class="hlt">sea</span> <span class="hlt">ice</span> presence around much of the rest of the continent. Overall, <span class="hlt">sea</span> <span class="hlt">ice</span> extent around Antarctica has increased at an average rate of about 17,000 square kilometers per year since the late 1970s, as determined from satellite microwave data that can be collected under both light and</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012GeoRL..39.8502N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012GeoRL..39.8502N"><span>Observations reveal external driver for Arctic <span class="hlt">sea-ice</span> retreat</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Notz, Dirk; Marotzke, Jochem</p> <p>2012-04-01</p> <p>The very low summer extent of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> that has been observed in recent years is often casually interpreted as an early-warning sign of anthropogenic global warming. For examining the validity of this claim, previously IPCC model simulations have been used. Here, we focus on the available observational record to examine if this record allows us to identify either internal variability, self-acceleration, or a specific external forcing as the main driver for the observed <span class="hlt">sea-ice</span> retreat. We find that the available observations are sufficient to virtually exclude internal variability and self-acceleration as an explanation for the observed long-term trend, clustering, and magnitude of recent <span class="hlt">sea-ice</span> minima. Instead, the recent retreat is well described by the superposition of an externally forced linear trend and internal variability. For the externally forced trend, we find a physically plausible strong correlation only with increasing atmospheric CO2 concentration. Our results hence show that the observed evolution of Arctic <span class="hlt">sea-ice</span> extent is consistent with the claim that virtually certainly the impact of an anthropogenic climate change is observable in Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> already today.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..16.7084M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..16.7084M"><span>Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> loss and recent extreme cold winter in Eurasia</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mori, Masato; Watanabe, Masahiro; Ishii, Masayoshi; Kimoto, Masahide</p> <p>2014-05-01</p> <p>Extreme cold winter over the Eurasia has occurred more frequently in recent years. Observational evidence in recent studies shows that the wintertime cold anomalies over the Eurasia are associated with decline of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> in preceding autumn to winter season. However, the tropical and/or mid-latitude <span class="hlt">sea</span> surface temperature (SST) anomalies have great influence on the mid- and high-latitude atmospheric variability, it is difficult to isolate completely the impacts of <span class="hlt">sea</span> <span class="hlt">ice</span> change from observational data. In this study, we examine possible linkage between the Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> loss and the extreme cold winter over the Eurasia using a state-of-the-art MIROC4 (T106L56) atmospheric general circulation model (AGCM) to assess the pure atmospheric responses to <span class="hlt">sea</span> <span class="hlt">ice</span> reduction. We perform two sets of experiments with different realistic <span class="hlt">sea</span> <span class="hlt">ice</span> boundary conditions calculated by composite of observed <span class="hlt">sea</span> <span class="hlt">ice</span> concentration; one is reduced <span class="hlt">sea</span> <span class="hlt">ice</span> extent case (referred to as LICE run) and another is enhanced case (HICE run). In both experiments, the model is integrated 6-month from September to February with 100-member ensemble under the climatological SST boundary condition. The difference in ensemble mean of each experiment (LICE minus HICE) shows cold anomalies over the Eurasia in winter and its spatial pattern is very similar to corresponding observation, though the magnitude is smaller than observation. This result indicates that a part of observed cold anomaly can be attributed to the Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> loss. We would like to introduce more important results and mechanisms in detail in my presentation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017GeoRL..44.4953B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017GeoRL..44.4953B"><span>Skillful regional prediction of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> on seasonal timescales</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bushuk, Mitchell; Msadek, Rym; Winton, Michael; Vecchi, Gabriel A.; Gudgel, Rich; Rosati, Anthony; Yang, Xiaosong</p> <p>2017-05-01</p> <p>Recent Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> seasonal prediction efforts and forecast skill assessments have primarily focused on pan-Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> extent (SIE). In this work, we move toward stakeholder-relevant spatial scales, investigating the regional forecast skill of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> in a Geophysical Fluid Dynamics Laboratory (GFDL) seasonal prediction system. Using a suite of retrospective initialized forecasts spanning 1981-2015 made with a coupled atmosphere-ocean-<span class="hlt">sea</span> <span class="hlt">ice</span>-land model, we show that predictions of detrended regional SIE are skillful at lead times up to 11 months. Regional prediction skill is highly region and target month dependent and generically exceeds the skill of an anomaly persistence forecast. We show for the first time that initializing the ocean subsurface in a seasonal prediction system can yield significant regional skill for winter SIE. Similarly, as suggested by previous work, we find that <span class="hlt">sea</span> <span class="hlt">ice</span> thickness initial conditions provide a crucial source of skill for regional summer SIE.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFM.C53B..02O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFM.C53B..02O"><span>Collaborative, International Efforts at Estimating Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> Processes During IPY (Invited)</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Overland, J. E.; Eicken, H.; Wiggins, H. V.</p> <p>2009-12-01</p> <p>Planning for the fourth IPY was conducted during a time of moderate decadal change in the Arctic. However, after this initial planning was completed, further rapid changes were seen, including a 39 % reduction in summer <span class="hlt">sea</span> <span class="hlt">ice</span> extent in 2007 and 2008 relative to the 1980s-1990s, loss of multi-year <span class="hlt">sea</span> <span class="hlt">ice</span>, and increased <span class="hlt">sea</span> <span class="hlt">ice</span> mobility. The SEARCH and DAMOCLES Programs endeavored to increase communication within the research community to promote observations and understanding of rapidly changing Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> conditions during IPY. In May 2008 a web-based <span class="hlt">Sea</span> <span class="hlt">Ice</span> Outlook was initiated, an international collaborative effort that synthesizes, on a monthly basis throughout the summer, the community’s projections for September arctic <span class="hlt">sea</span> <span class="hlt">ice</span> extent. Each month, participating investigators provided a projection for the mean September <span class="hlt">sea</span> <span class="hlt">ice</span> extent based on spring and early summer data, along with a rationale for their estimates. The Outlook continued in summer of 2009. The Outlook is a method of rapidly synthesizing a broad range of remote sensing and field observations collected at the peak of the IPY, with analysis methods ranging from heuristic to statistical to <span class="hlt">ice</span>-ocean model ensemble runs. The 2008 Outlook was a success with 20 groups participating and providing a median <span class="hlt">sea</span> <span class="hlt">ice</span> extent projection from June 2008 data of 4.4 million square kilometers (MSQK)—near the observed extent in September 2008 of 4.7 MSQK, and well below the 1979-2007 climatological extent of 6.7 MSQK. More importantly, the contrast of <span class="hlt">sea</span> <span class="hlt">ice</span> conditions and atmospheric forcing in 2008 compared to 2007 provided clues to the future fate of arctic <span class="hlt">sea</span> <span class="hlt">ice</span>. The question was whether the previous loss of multi-year <span class="hlt">ice</span> and delay in autumn freeze-up in 2007 would allow sufficient winter thickening of <span class="hlt">sea</span> <span class="hlt">ice</span> to last through the summer 2008, promoting recovery from the 2007 minimum, or whether most first-year <span class="hlt">sea</span> <span class="hlt">ice</span> would melt out as in 2005 and 2007, resulting in a new record minimum extent</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19840008344&hterms=sea+world&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dsea%2Bworld','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19840008344&hterms=sea+world&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dsea%2Bworld"><span>Spaceborne SAR and <span class="hlt">sea</span> <span class="hlt">ice</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Weeks, W. F.</p> <p>1983-01-01</p> <p>A number of remote sensing systems deployed in satellites to view the Earth which are successful in gathering data on the behavior of the world's snow and <span class="hlt">ice</span> covers are described. Considering <span class="hlt">sea</span> <span class="hlt">ice</span> which covers over 10% of the world ocean, systems that have proven capable to collect useful data include those operating in the visible, near-infrared, infrared, and microwave frequency ranges. The microwave systems have the essential advantage in observing the <span class="hlt">ice</span> under all weather and lighting conditions. Without this capability data are lost during the long polar night and during times of storm passage, periods when <span class="hlt">ice</span> activity can be intense. The margins of the <span class="hlt">ice</span> pack, a region of particular interest, is shrouded in cloud between 80 and 90% of the time.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C31B0742N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C31B0742N"><span>A Quantitative Proxy for <span class="hlt">Sea-Ice</span> Based on Diatoms: A Cautionary Tale.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Nesterovich, A.; Caissie, B.</p> <p>2016-12-01</p> <p><span class="hlt">Sea</span> <span class="hlt">ice</span> in the Polar Regions supports unique and productive ecosystems, but the current decline in the Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> extent prompts questions about previous <span class="hlt">sea</span> <span class="hlt">ice</span> declines and the response of <span class="hlt">ice</span> related ecosystems. Since satellite data only extend back to 1978, the study of <span class="hlt">sea</span> <span class="hlt">ice</span> before this time requires a proxy. Being one of the most productive, diatom-dominated regions in the world and having a wide range of <span class="hlt">sea</span> <span class="hlt">ice</span> concentrations, the Bering and Chukchi <span class="hlt">seas</span> are a perfect place to find a relationship between the presence of <span class="hlt">sea</span> <span class="hlt">ice</span> and diatom community composition. The aim of this work is to develop a diatom-based proxy for the <span class="hlt">sea</span> <span class="hlt">ice</span> extent. A total of 473 species have been identified in 104 sediment samples, most of which were collected on board the US Coast Guard Cutter Healy <span class="hlt">ice</span> breaker (2006, 2007) and the Norseman II (2008). The study also included some of the archived diatom smear slides made from sediments collected in 1969. The assemblages were compared to satellite-derived <span class="hlt">sea</span> <span class="hlt">ice</span> extent data averaged over the 10 years preceding the sampling. Previous studies in the Arctic and Antarctic regions demonstrated that the Generalized Additive Model (GAM) is one of the best choices for proxy construction. It has the advantage of using only several species instead of the whole assemblage, thus including only <span class="hlt">sea</span> <span class="hlt">ice</span>-associated species and minimizing the noise created by species responding to other environmental factors. Our GAM on three species (Connia compita, Fragilariopsis reginae-jahniae, and Neodenticula seminae) has low standard deviation, high level of explained variation, and holds under the ten-fold cross-validation; the standard residual analysis is acceptable. However, a spatial residual analysis revealed that the model consistently over predicts in the Chukchi <span class="hlt">Sea</span> and under predicts in the Bering <span class="hlt">Sea</span>. Including a spatial model into the GAM didn't improve the situation. This has led us to test other methods, including a non-parametric model</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011ClDy...36.1523J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011ClDy...36.1523J"><span>Influence of coupling on atmosphere, <span class="hlt">sea</span> <span class="hlt">ice</span> and ocean regional models in the Ross <span class="hlt">Sea</span> sector, Antarctica</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Jourdain, Nicolas C.; Mathiot, Pierre; Gallée, Hubert; Barnier, Bernard</p> <p>2011-04-01</p> <p>Air-<span class="hlt">sea</span> <span class="hlt">ice</span>-ocean interactions in the Ross <span class="hlt">Sea</span> sector form dense waters that feed the global thermohaline circulation. In this paper, we develop the new limited-area ocean-<span class="hlt">sea</span> <span class="hlt">ice</span>-atmosphere coupled model TANGO to simulate the Ross <span class="hlt">Sea</span> sector. TANGO is built up by coupling the atmospheric limited-area model MAR to a regional configuration of the ocean-<span class="hlt">sea</span> <span class="hlt">ice</span> model NEMO. A method is then developed to identify the mechanisms by which local coupling affects the simulations. TANGO is shown to simulate realistic <span class="hlt">sea</span> <span class="hlt">ice</span> properties and atmospheric surface temperatures. These skills are mostly related to the skills of the stand alone atmospheric and oceanic models used to build TANGO. Nonetheless, air temperatures over ocean and winter <span class="hlt">sea</span> <span class="hlt">ice</span> thickness are found to be slightly improved in coupled simulations as compared to standard stand alone ones. Local atmosphere ocean feedbacks over the open ocean are found to significantly influence ocean temperature and salinity. In a stand alone ocean configuration, the dry and cold air produces an ocean cooling through sensible and latent heat loss. In a coupled configuration, the atmosphere is in turn moistened and warmed by the ocean; sensible and latent heat loss is therefore reduced as compared to the stand alone simulations. The atmosphere is found to be less sensitive to local feedbacks than the ocean. Effects of local feedbacks are increased in the coastal area because of the presence of <span class="hlt">sea</span> <span class="hlt">ice</span>. It is suggested that slow heat conduction within <span class="hlt">sea</span> <span class="hlt">ice</span> could amplify the feedbacks. These local feedbacks result in less <span class="hlt">sea</span> <span class="hlt">ice</span> production in polynyas in coupled mode, with a subsequent reduction in deep water formation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA601203','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA601203"><span>Forecasting Future <span class="hlt">Sea</span> <span class="hlt">Ice</span> Conditions in the MIZ: A Lagrangian Approach</span></a></p> <p><a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>2013-09-30</p> <p>www.mcgill.ca/meteo/people/tremblay LONG-TERM GOALS 1- Determine the source regions for <span class="hlt">sea</span> <span class="hlt">ice</span> in the seasonally <span class="hlt">ice</span>-covered zones (SIZs...distribution of <span class="hlt">sea</span> <span class="hlt">ice</span> cover and transport pathways. 2- Improve our understanding of the strengths and/or limitations of GCM predictions of future...ocean currents, RGPS <span class="hlt">sea</span> <span class="hlt">ice</span> deformation, Reanalysis surface wind , surface radiative fluxes, etc. Processing the large datasets involved is a tedious</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A43D2472C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A43D2472C"><span>Sensitivity of the <span class="hlt">sea</span> <span class="hlt">ice</span> concentration over the Kara-Barents <span class="hlt">Sea</span> in autumn to the winter temperature variability over East Asia</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Cho, K. H.; Chang, E. C.</p> <p>2017-12-01</p> <p>In this study, we performed sensitivity experiments by utilizing the Global/Regional Integrated Model system with different conditions of the <span class="hlt">sea</span> <span class="hlt">ice</span> concentration over the Kara-Barents (KB) <span class="hlt">Sea</span> in autumn, which can affect winter temperature variability over East Asia. Prescribed <span class="hlt">sea</span> <span class="hlt">ice</span> conditions are 1) climatological autumn <span class="hlt">sea</span> <span class="hlt">ice</span> concentration obtained from 1982 to 2016, 2) reduced autumn <span class="hlt">sea</span> <span class="hlt">ice</span> concentration by 50% of the climatology, and 3) increased autumn <span class="hlt">sea</span> <span class="hlt">ice</span> concentration by 50% of climatology. Differently prescribed <span class="hlt">sea</span> <span class="hlt">ice</span> concentration changes surface albedo, which affects surface heat fluxes and near-surface air temperature. The reduced (increased) <span class="hlt">sea</span> <span class="hlt">ice</span> concentration over the KB <span class="hlt">sea</span> increases (decreases) near-surface air temperature that leads the lower (higher) <span class="hlt">sea</span> level pressure in autumn. These patterns are maintained from autumn to winter season. Furthermore, it is shown that the different <span class="hlt">sea</span> <span class="hlt">ice</span> concentration over the KB <span class="hlt">sea</span> has remote effects on the <span class="hlt">sea</span> level pressure patterns over the East Asian region. The lower (higher) <span class="hlt">sea</span> level pressure over the KB <span class="hlt">sea</span> by the locally decreased (increased) <span class="hlt">ice</span> concentration is related to the higher (lower) pressure pattern over the Siberian region, which induces strengthened (weakened) cold advection over the East Asian region. From these sensitivity experiments it is clarified that the decreased (increased) <span class="hlt">sea</span> <span class="hlt">ice</span> concentration over the KB <span class="hlt">sea</span> in autumn can lead the colder (warmer) surface air temperature over East Asia in winter.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C41A0639L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C41A0639L"><span>Upper Ocean Evolution Across the Beaufort <span class="hlt">Sea</span> Marginal <span class="hlt">Ice</span> Zone</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lee, C.; Rainville, L.; Gobat, J. I.; Perry, M. J.; Freitag, L. E.; Webster, S.</p> <p>2016-12-01</p> <p>The observed reduction of Arctic summertime <span class="hlt">sea</span> <span class="hlt">ice</span> extent and expansion of the marginal <span class="hlt">ice</span> zone (MIZ) have profound impacts on the balance of processes controlling <span class="hlt">sea</span> <span class="hlt">ice</span> evolution, including the introduction of several positive feedback mechanisms that may act to accelerate melting. Examples of such feedbacks include increased upper ocean warming though absorption of solar radiation, elevated internal wave energy and mixing that may entrain heat stored in subsurface watermasses (e.g., the relatively warm Pacific Summer and Atlantic waters), and elevated surface wave energy that acts to deform and fracture <span class="hlt">sea</span> <span class="hlt">ice</span>. Spatial and temporal variability in <span class="hlt">ice</span> properties and open water fraction impact these processes. To investigate how upper ocean structure varies with changing <span class="hlt">ice</span> cover, how the balance of processes shift as a function of <span class="hlt">ice</span> fraction and distance from open water, and how these processes impact <span class="hlt">sea</span> <span class="hlt">ice</span> evolution, a network of autonomous platforms sampled the atmosphere-<span class="hlt">ice</span>-ocean system in the Beaufort, beginning in spring, well before the start of melt, and ending with the autumn freeze-up. Four long-endurance autonomous Seagliders occupied sections that extended from open water, through the marginal <span class="hlt">ice</span> zone, deep into the pack during summer 2014 in the Beaufort <span class="hlt">Sea</span>. Gliders penetrated up to 200 km into the <span class="hlt">ice</span> pack, under complete <span class="hlt">ice</span> cover for up to 10 consecutive days. Sections reveal strong fronts where cold, <span class="hlt">ice</span>-covered waters meet waters that have been exposed to solar warming, and O(10 km) scale eddies near the <span class="hlt">ice</span> edge. In the pack, Pacific Summer Water and a deep chlorophyll maximum form distinct layers at roughly 60 m and 80 m, respectively, which become increasingly diffuse late in the season as they progress through the MIZ and into open water. Stratification just above the Pacific Summer Water rapidly weakens near the <span class="hlt">ice</span> edge and temperature variance increases, likely due to mixing or energetic vertical exchange associated with strong</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..1612477L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..1612477L"><span>Ship speeds and <span class="hlt">sea</span> <span class="hlt">ice</span> forecasts - how are they related?</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Loeptien, Ulrike; Axell, Lars</p> <p>2014-05-01</p> <p>The Baltic <span class="hlt">Sea</span> is a shallow marginal <span class="hlt">sea</span>, located in northern Europe. A seasonally occurring <span class="hlt">sea</span> <span class="hlt">ice</span> cover has the potential to hinder the intense ship traffic substantially. There are thus considerable efforts to fore- and nowcast <span class="hlt">ice</span> conditions. Here we take a somewhat opposite approach and relate ship speeds, as observed via the Automatic Identification System (AIS) network, back to the prevailing <span class="hlt">sea</span> <span class="hlt">ice</span> conditions. We show that these information are useful to constrain fore- and nowcasts. More specifically we find, by fitting a statistical model (mixed effect model) for a test region in the Bothnian Bay, that the forecasted <span class="hlt">ice</span> properties can explain 60-65% of the ship speed variations (based on 25 minute averages).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5244362','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5244362"><span>Leads in Arctic pack <span class="hlt">ice</span> enable early phytoplankton blooms below snow-covered <span class="hlt">sea</span> <span class="hlt">ice</span></span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Assmy, Philipp; Fernández-Méndez, Mar; Duarte, Pedro; Meyer, Amelie; Randelhoff, Achim; Mundy, Christopher J.; Olsen, Lasse M.; Kauko, Hanna M.; Bailey, Allison; Chierici, Melissa; Cohen, Lana; Doulgeris, Anthony P.; Ehn, Jens K.; Fransson, Agneta; Gerland, Sebastian; Hop, Haakon; Hudson, Stephen R.; Hughes, Nick; Itkin, Polona; Johnsen, Geir; King, Jennifer A.; Koch, Boris P.; Koenig, Zoe; Kwasniewski, Slawomir; Laney, Samuel R.; Nicolaus, Marcel; Pavlov, Alexey K.; Polashenski, Christopher M.; Provost, Christine; Rösel, Anja; Sandbu, Marthe; Spreen, Gunnar; Smedsrud, Lars H.; Sundfjord, Arild; Taskjelle, Torbjørn; Tatarek, Agnieszka; Wiktor, Jozef; Wagner, Penelope M.; Wold, Anette; Steen, Harald; Granskog, Mats A.</p> <p>2017-01-01</p> <p>The Arctic icescape is rapidly transforming from a thicker multiyear <span class="hlt">ice</span> cover to a thinner and largely seasonal first-year <span class="hlt">ice</span> cover with significant consequences for Arctic primary production. One critical challenge is to understand how productivity will change within the next decades. Recent studies have reported extensive phytoplankton blooms beneath ponded <span class="hlt">sea</span> <span class="hlt">ice</span> during summer, indicating that satellite-based Arctic annual primary production estimates may be significantly underestimated. Here we present a unique time-series of a phytoplankton spring bloom observed beneath snow-covered Arctic pack <span class="hlt">ice</span>. The bloom, dominated by the haptophyte algae Phaeocystis pouchetii, caused near depletion of the surface nitrate inventory and a decline in dissolved inorganic carbon by 16 ± 6 g C m−2. Ocean circulation characteristics in the area indicated that the bloom developed in situ despite the snow-covered <span class="hlt">sea</span> <span class="hlt">ice</span>. Leads in the dynamic <span class="hlt">ice</span> cover provided added sunlight necessary to initiate and sustain the bloom. Phytoplankton blooms beneath snow-covered <span class="hlt">ice</span> might become more common and widespread in the future Arctic Ocean with frequent lead formation due to thinner and more dynamic <span class="hlt">sea</span> <span class="hlt">ice</span> despite projected increases in high-Arctic snowfall. This could alter productivity, marine food webs and carbon sequestration in the Arctic Ocean. PMID:28102329</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20010028707','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20010028707"><span>Southern Ocean Climate and <span class="hlt">Sea</span> <span class="hlt">Ice</span> Anomalies Associated with the Southern Oscillation</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Kwok, R.; Comiso, J. C.</p> <p>2001-01-01</p> <p>The anomalies in the climate and <span class="hlt">sea</span> <span class="hlt">ice</span> cover of the Southern Ocean and their relationships with the Southern Oscillation (SO) are investigated using a 17-year of data set from 1982 through 1998. We correlate the polar climate anomalies with the Southern Oscillation index (SOI) and examine the composites of these anomalies under the positive (SOI > 0), neutral (0 > SOI > -1), and negative (SOI < -1) phases of SOL The climate data set consists of <span class="hlt">sea</span>-level pressure, wind, surface air temperature, and <span class="hlt">sea</span> surface temperature fields, while the <span class="hlt">sea</span> <span class="hlt">ice</span> data set describes its extent, concentration, motion, and surface temperature. The analysis depicts, for the first time, the spatial variability in the relationship of the above variables and the SOL The strongest correlation between the SOI and the polar climate anomalies are found in the Bellingshausen, Amundsen and Ross <span class="hlt">sea</span> sectors. The composite fields reveal anomalies that are organized in distinct large-scale spatial patterns with opposing polarities at the two extremes of SOI, and suggest oscillating climate anomalies that are closely linked to the SO. Within these sectors, positive (negative) phases of the SOI are generally associated with lower (higher) <span class="hlt">sea</span>-level pressure, cooler (warmer) surface air temperature, and cooler (warmer) <span class="hlt">sea</span> surface temperature in these sectors. Associations between these climate anomalies and the behavior of the Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> cover are clearly evident. Recent anomalies in the <span class="hlt">sea</span> <span class="hlt">ice</span> cover that are apparently associated with the SOI include: the record decrease in the <span class="hlt">sea</span> <span class="hlt">ice</span> extent in the Bellingshausen <span class="hlt">Sea</span> from mid- 1988 through early 199 1; the relationship between Ross <span class="hlt">Sea</span> SST and ENSO signal, and reduced <span class="hlt">sea</span> <span class="hlt">ice</span> concentration in the Ross <span class="hlt">Sea</span>; and, the shortening of the <span class="hlt">ice</span> season in the eastern Ross <span class="hlt">Sea</span>, Amundsen <span class="hlt">Sea</span>, far western Weddell <span class="hlt">Sea</span>, and the lengthening of the <span class="hlt">ice</span> season in the western Ross <span class="hlt">Sea</span>, Bellingshausen <span class="hlt">Sea</span> and central Weddell <span class="hlt">Sea</span> gyre over the period 1988</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li class="active"><span>24</span></li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_24 --> <div id="page_25" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li class="active"><span>25</span></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="481"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012JGRC..117.6024T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012JGRC..117.6024T"><span>Morphology of <span class="hlt">sea</span> <span class="hlt">ice</span> pressure ridges in the northwestern Weddell <span class="hlt">Sea</span> in winter</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tan, Bing; Li, Zhi-Jun; Lu, Peng; Haas, Christian; Nicolaus, Marcel</p> <p>2012-06-01</p> <p>To investigate the morphology and distribution of pressure ridges in the northwestern Weddell <span class="hlt">Sea</span>, <span class="hlt">ice</span> surface elevation profiles were measured by a helicopter-borne laser altimeter during Winter Weddell Outflow Study with the German R/V Polarstern in 2006. An optimal cutoff height of 0.62 m, derived from the best fits between the measured and theoretical ridge height and spacing distributions, was first used to separate pressure ridges from other <span class="hlt">sea</span> <span class="hlt">ice</span> surface undulations. It was found that the measured ridge height distribution was well modeled by a negative exponential function, and the ridge spacing distribution by a lognormal function. Next, based on the ridging intensity Ri (the ratio of mean ridge sail height to mean spacing), all profiles were clustered into three regimes by an improved k-means clustering algorithm: Ri ≤ 0.01, 0.01 < Ri ≤ 0.026, and Ri > 0.026 (denoted as C1, C2, and C3 respectively). Mean (and standard deviation) of sail height was 0.99 (±0.07) m in Regime C1, 1.12 (±0.06) m in C2, and 1.17 (±0.04) m in C3, respectively, while the mean spacings (and standard deviations) were 232 (±240) m, 54 (±20) m, and 31 (±5.6) m. These three <span class="hlt">ice</span> regimes coincided closely with distinct <span class="hlt">sea</span> <span class="hlt">ice</span> regions identified in a satellite radar image, where C1 corresponded to the broken <span class="hlt">ice</span> in the marginal <span class="hlt">ice</span> zone and level <span class="hlt">ice</span> formed in the Larsen Polynya, C2 corresponded to the deformed first- and second-year <span class="hlt">ice</span> formed by dynamic action in the center of the study region, and C3 corresponded to heavily deformed <span class="hlt">ice</span> in the outflowing branch of the Weddell Gyre. The results of our analysis showed that the relationship between the mean ridge height and frequency was well modeled by a logarithmic function with a correlation coefficient of 0.8, although such correlation was weaker when considering each regime individually. The measured ridge height and frequency were both greater than those reported by others for the Ross <span class="hlt">Sea</span>. Compared with reported</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFMPP21G..03M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFMPP21G..03M"><span>Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> variability during the last deglaciation: a biomarker approach</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Müller, J.; Stein, R. H.</p> <p>2014-12-01</p> <p>The last transition from full glacial to current interglacial conditions was accompanied by distinct short-term climate fluctuations caused by changes in the global ocean circulation system. Most palaeoceanographic studies focus on the documentation of the behaviour of the Atlantic Meridional Overturning Circulation (AMOC) during the last deglaciation in response to freshwater forcing events. In this respect, the role of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> remained relatively unconsidered - primarily because of the difficulty of its reconstruction. Here we present new proxy data on late glacial (including the Last Glacial Maximum; LGM) and deglacial <span class="hlt">sea</span> <span class="hlt">ice</span> variability in the Arctic Ocean and its main gateway - the Fram Strait - and how these changes in <span class="hlt">sea</span> <span class="hlt">ice</span> coverage contributed to AMOC perturbations observed during Heinrich Event 1 and the Younger Dryas. Recurrent short-term advances and retreats of <span class="hlt">sea</span> <span class="hlt">ice</span> in Fram Strait, prior and during the LGM, are in line with a variable (or intermittent) North Atlantic heat flow along the eastern corridor of the Nordic <span class="hlt">Seas</span>. Possibly in direct response to the initial freshwater discharge from melting continental <span class="hlt">ice</span>-sheets, a permanent <span class="hlt">sea</span> <span class="hlt">ice</span> cover established only at about 19 ka BP (i.e. post-LGM) and lasted until 17.6 ka BP, when an abrupt break-up of this thick <span class="hlt">ice</span> cover and a sudden discharge of huge amounts of <span class="hlt">sea</span> <span class="hlt">ice</span> and icebergs through Fram Strait coincided with the weakening of the AMOC during Heinrich Event 1. Similarly, another <span class="hlt">sea</span> <span class="hlt">ice</span> maximum at about 12.8 ka BP is associated with the slowdown of the AMOC during the Younger Dryas. The new data sets clearly highlight the important role of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> for the re-organisation of the oceanographic setting in the North Atlantic during the last deglaciation. Further studies and sensitivity experiments to identify crucial driving (and feedback) mechanisms within the High Latitude <span class="hlt">ice</span>-ocean-atmosphere system will contribute the understanding of rapid climate changes.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28561343','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28561343"><span>Pan-Arctic <span class="hlt">sea</span> <span class="hlt">ice</span>-algal chl a biomass and suitable habitat are largely underestimated for multiyear <span class="hlt">ice</span>.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Lange, Benjamin A; Flores, Hauke; Michel, Christine; Beckers, Justin F; Bublitz, Anne; Casey, John Alec; Castellani, Giulia; Hatam, Ido; Reppchen, Anke; Rudolph, Svenja A; Haas, Christian</p> <p>2017-11-01</p> <p>There is mounting evidence that multiyear <span class="hlt">ice</span> (MYI) is a unique component of the Arctic Ocean and may play a more important ecological role than previously assumed. This study improves our understanding of the potential of MYI as a suitable habitat for <span class="hlt">sea</span> <span class="hlt">ice</span> algae on a pan-Arctic scale. We sampled <span class="hlt">sea</span> <span class="hlt">ice</span> cores from MYI and first-year <span class="hlt">sea</span> <span class="hlt">ice</span> (FYI) within the Lincoln <span class="hlt">Sea</span> during four consecutive spring seasons. This included four MYI hummocks with a mean chl a biomass of 2.0 mg/m 2 , a value significantly higher than FYI and MYI refrozen ponds. Our results support the hypothesis that MYI hummocks can host substantial <span class="hlt">ice</span>-algal biomass and represent a reliable <span class="hlt">ice</span>-algal habitat due to the (quasi-) permanent low-snow surface of these features. We identified an <span class="hlt">ice</span>-algal habitat threshold value for calculated light transmittance of 0.014%. <span class="hlt">Ice</span> classes and coverage of suitable <span class="hlt">ice</span>-algal habitat were determined from snow and <span class="hlt">ice</span> surveys. These <span class="hlt">ice</span> classes and associated coverage of suitable habitat were applied to pan-Arctic CryoSat-2 snow and <span class="hlt">ice</span> thickness data products. This habitat classification accounted for the variability of the snow and <span class="hlt">ice</span> properties and showed an areal coverage of suitable <span class="hlt">ice</span>-algal habitat within the MYI-covered region of 0.54 million km 2 (8.5% of total <span class="hlt">ice</span> area). This is 27 times greater than the areal coverage of 0.02 million km 2 (0.3% of total <span class="hlt">ice</span> area) determined using the conventional block-model classification, which assigns single-parameter values to each grid cell and does not account for subgrid cell variability. This emphasizes the importance of accounting for variable snow and <span class="hlt">ice</span> conditions in all <span class="hlt">sea</span> <span class="hlt">ice</span> studies. Furthermore, our results indicate the loss of MYI will also mean the loss of reliable <span class="hlt">ice</span>-algal habitat during spring when food is sparse and many organisms depend on <span class="hlt">ice</span>-algae. © 2017 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/14586466','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/14586466"><span>High interannual variability of <span class="hlt">sea</span> <span class="hlt">ice</span> thickness in the Arctic region.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Laxon, Seymour; Peacock, Neil; Smith, Doug</p> <p>2003-10-30</p> <p>Possible future changes in Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> cover and thickness, and consequent changes in the <span class="hlt">ice</span>-albedo feedback, represent one of the largest uncertainties in the prediction of future temperature rise. Knowledge of the natural variability of <span class="hlt">sea</span> <span class="hlt">ice</span> thickness is therefore critical for its representation in global climate models. Numerical simulations suggest that Arctic <span class="hlt">ice</span> thickness varies primarily on decadal timescales owing to changes in wind and ocean stresses on the <span class="hlt">ice</span>, but observations have been unable to provide a synoptic view of <span class="hlt">sea</span> <span class="hlt">ice</span> thickness, which is required to validate the model results. Here we use an eight-year time-series of Arctic <span class="hlt">ice</span> thickness, derived from satellite altimeter measurements of <span class="hlt">ice</span> freeboard, to determine the mean thickness field and its variability from 65 degrees N to 81.5 degrees N. Our data reveal a high-frequency interannual variability in mean Arctic <span class="hlt">ice</span> thickness that is dominated by changes in the amount of summer melt, rather than by changes in circulation. Our results suggest that a continued increase in melt season length would lead to further thinning of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C21E..05P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C21E..05P"><span>Variability in Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> topography and atmospheric form drag: Combining <span class="hlt">Ice</span>Bridge laser altimetry with ASCAT radar backscatter.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Petty, A.; Tsamados, M.; Kurtz, N. T.</p> <p>2016-12-01</p> <p>Here we present atmospheric form drag estimates over Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> using high resolution, three-dimensional surface elevation data from NASA's Operation <span class="hlt">Ice</span>Bridge Airborne Topographic Mapper (ATM), and surface roughness estimates from the Advanced Scatterometer (ASCAT). Surface features of the <span class="hlt">ice</span> pack (e.g. pressure ridges) are detected using <span class="hlt">Ice</span>Bridge ATM elevation data and a novel surface feature-picking algorithm. We use simple form drag parameterizations to convert the observed height and spacing of surface features into an effective atmospheric form drag coefficient. The results demonstrate strong regional variability in the atmospheric form drag coefficient, linked to variability in both the height and spacing of surface features. This includes form drag estimates around 2-3 times higher over the multiyear <span class="hlt">ice</span> north of Greenland, compared to the first-year <span class="hlt">ice</span> of the Beaufort/Chukchi <span class="hlt">seas</span>. We compare results from both scanning and linear profiling to ensure our results are consistent with previous studies investigating form drag over Arctic <span class="hlt">sea</span> <span class="hlt">ice</span>. A strong correlation between ASCAT surface roughness estimates (using radar backscatter) and the <span class="hlt">Ice</span>Bridge form drag results enable us to extrapolate the <span class="hlt">Ice</span>Bridge data collected over the western-Arctic across the entire Arctic Ocean. While our focus is on spring, due to the timing of the primary <span class="hlt">Ice</span>Bridge campaigns since 2009, we also take advantage of the autumn data collected by <span class="hlt">Ice</span>Bridge in 2015 to investigate seasonality in Arctic <span class="hlt">ice</span> topography and the resulting form drag coefficient. Our results offer the first large-scale assessment of atmospheric form drag over Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> due to variable <span class="hlt">ice</span> topography (i.e. within the Arctic pack <span class="hlt">ice</span>). The analysis is being extended to the Antarctic <span class="hlt">Ice</span>Bridge <span class="hlt">sea</span> <span class="hlt">ice</span> data, and the results are being used to calibrate a sophisticated form drag parameterization scheme included in the <span class="hlt">sea</span> <span class="hlt">ice</span> model CICE, to improve the representation of form drag over Arctic and</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19850053020&hterms=helicopter+sea&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dhelicopter%2Bsea','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19850053020&hterms=helicopter+sea&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dhelicopter%2Bsea"><span>Active microwave measurements of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> under summer conditions</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Onstott, R. G.; Gogineni, S. P.</p> <p>1985-01-01</p> <p>Radar provides a valuable tool in the study of <span class="hlt">sea-ice</span> conditions and the solution of <span class="hlt">sea-ice</span> operational problems. For this reason, the U.S. and Canada have conducted studies to define a bilateral synthetic aperture radar (SAR) satellite program. The present paper is concerned with work which has been performed to explore the needs associated with the study of <span class="hlt">sea-ice</span>-covered waters. The design of a suitable research or operational spaceborne SAR or real aperture radar must be based on an adequate knowledge of the backscatter coefficients of the <span class="hlt">ice</span> features which are of interest. In order to obtain the needed information, studies involving the use of a helicopter were conducted. In these studies L-C-X-Ku-band calibrated radar data were acquired over areas of Arctic first-year and multiyear <span class="hlt">ice</span> during the first half of the summer of 1982. The results show that the microwave response in the case of <span class="hlt">sea</span> <span class="hlt">ice</span> is greatly influenced by summer melt, which produces significant changes in the properties of the snowpack and <span class="hlt">ice</span> sheet.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19950028626&hterms=data+types&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Ddata%2Btypes','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19950028626&hterms=data+types&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Ddata%2Btypes"><span>The classification of the Arctic <span class="hlt">Sea</span> <span class="hlt">ice</span> types and the determination of surface temperature using advanced very high resolution radiometer data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Massom, Robert; Comiso, Josefino C.</p> <p>1994-01-01</p> <p>The accurate quantification of new <span class="hlt">ice</span> and open water areas and surface temperatures within the <span class="hlt">sea</span> <span class="hlt">ice</span> packs is a key to the realistic parameterization of heat, moisture, and turbulence fluxes between ocean and atmosphere in the polar regions. Multispectral NOAA advanced very high resolution radiometer/2 (AVHRR/2) satellite images are analyzed to evaluate how effectively the data can be used to characterize <span class="hlt">sea</span> <span class="hlt">ice</span> in the Bering and Greenland <span class="hlt">seas</span>, both in terms of surface type and physical temperature. The basis of the classification algorithm, which is developed using a late wintertime Bering <span class="hlt">Sea</span> <span class="hlt">ice</span> cover data, is that frequency distributions of 10.8- micrometers radiances provide four distinct peaks, represeting open water, new <span class="hlt">ice</span>, young <span class="hlt">ice</span>, and thick <span class="hlt">ice</span> with a snow cover. The results are found to be spatially and temporally consistent. Possible sources of ambiguity, especially associated with wider temporal and spatial application of the technique, are discussed. An <span class="hlt">ice</span> surface temperature algorithm is developed for the same study area by regressing thermal infrared data from 10.8- and 12.0- micrometers channels against station air temperatures, which are assumed to approximate the skin temperatures of <span class="hlt">adjacent</span> snow and <span class="hlt">ice</span>. The standard deviations of the results when compared with in situ data are about 0.5 K over leads and polynyas to about 0.5-1.5 K over thick <span class="hlt">ice</span>. This study is based upon a set of in situ data limited in scope and coverage. Cloud masks are applied using a thresholding technique that utilizes 3.74- and 10.8- micrometers channel data. The temperature maps produced show coherence with surface features like new <span class="hlt">ice</span> and leads, and consistency with corresponding surface type maps. Further studies are needed to better understand the effects of both the spatial and temporal variability in emissivity, aerosol and precipitable atmospheric <span class="hlt">ice</span> particle distribution, and atmospheric temperature inversions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C11A0748Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C11A0748Y"><span>Comparing <span class="hlt">Ice</span>Bridge and CryoSat-2 <span class="hlt">sea</span> <span class="hlt">ice</span> observations over the Arctic and the Southern Ocean</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Yi, D.; Kurtz, N. T.; Harbeck, J.; Hofton, M. A.; Manizade, S.; Cornejo, H.</p> <p>2016-12-01</p> <p>From 2009 to 2015, CryoSat-2 and <span class="hlt">Ice</span>Bridge had 34 coincident lines over <span class="hlt">sea</span> <span class="hlt">ice</span>, 23 over the Arctic (20 with ATM, 2 with LVIS, and 1 with both ATM and LVIS) and 11 over the Southern Ocean (9 with ATM and 2 with both ATM and LVIS). In this study, we will compare both surface elevation and <span class="hlt">sea</span> <span class="hlt">ice</span> freeboard from CryoSat-2, ATM, and LVIS. We will apply identical ellipsoid, geoid, tide models, and atmospheric corrections to CryoSat-2, ATM, and LVIS data. For CryoSat-2, we will use surface elevation and <span class="hlt">sea</span> <span class="hlt">ice</span> freeboard both in the standard CryoSat-2 data product and calculated through a waveform fitting method. For ATM and LVIS, we will use surface elevation and <span class="hlt">sea</span> <span class="hlt">ice</span> freeboard in the OIB data product and the elevation and <span class="hlt">sea</span> <span class="hlt">ice</span> freeboard calculated through Gaussian waveform fitting method. The results of this study are important for using ATM and LVIS to calibrate/validate CryoSat-2 results and bridging the data gap between ICESat and ICESat-2.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/biblio/211927-transport-contaminants-arctic-sea-ice-surface-ocean-currents','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/211927-transport-contaminants-arctic-sea-ice-surface-ocean-currents"><span>Transport of contaminants by Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> and surface ocean currents</span></a></p> <p><a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Pfirman, S.</p> <p>1995-12-31</p> <p><span class="hlt">Sea</span> <span class="hlt">ice</span> and ocean currents transport contaminants in the Arctic from source areas on the shelves, to biologically active regions often more than a thousand kilometers away. Coastal regions along the Siberian margin are polluted by discharges of agricultural, industrial and military wastes in river runoff, from atmospheric deposition and ocean dumping. The Kara <span class="hlt">Sea</span> is of particular concern because of deliberate dumping of radioactive waste, as well as the large input of polluted river water. Contaminants are incorporated in <span class="hlt">ice</span> during suspension freezing on the shelves, and by atmospheric deposition during drift. <span class="hlt">Ice</span> releases its contaminant load through brinemore » drainage, surface runoff of snow and meltwater, and when the floe disintegrates. The marginal <span class="hlt">ice</span> zone, a region of intense biological activity, may also be the site of major contaminant release. Potentially contaminated <span class="hlt">ice</span> from the Kara <span class="hlt">Sea</span> is likely to influence the marginal <span class="hlt">ice</span> zones of the Barents and Greenland <span class="hlt">seas</span>. From studies conducted to date it appears that <span class="hlt">sea</span> <span class="hlt">ice</span> from the Kara <span class="hlt">Sea</span> does not typically enter the Beaufort Gyre, and thus is unlikely to affect the northern Canadian and Alaskan margins.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24555308','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24555308"><span>Does Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> reduction foster shelf-basin exchange?</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Ivanov, Vladimir; Watanabe, Eiji</p> <p>2013-12-01</p> <p>The recent shift in Arctic <span class="hlt">ice</span> conditions from prevailing multi-year <span class="hlt">ice</span> to first-year <span class="hlt">ice</span> will presumably intensify fall-winter <span class="hlt">sea</span> <span class="hlt">ice</span> freezing and the associated salt flux to the underlying water column. Here, we conduct a dual modeling study whose results suggest that the predicted catastrophic consequences for the global thermohaline circulation (THC), as a result of the disappearance of Arctic <span class="hlt">sea</span> <span class="hlt">ice</span>, may not necessarily occur. In a warmer climate, the substantial fraction of dense water feeding the Greenland-Scotland overflow may form on Arctic shelves and cascade to the deep basin, thus replenishing dense water, which currently forms through open ocean convection in the sub-Arctic <span class="hlt">seas</span>. We have used a simplified model for estimating how increased <span class="hlt">ice</span> production influences shelf-basin exchange associated with dense water cascading. We have carried out case studies in two regions of the Arctic Ocean where cascading was observed in the past. The baseline range of buoyancy-forcing derived from the columnar <span class="hlt">ice</span> formation was calculated as part of a 30-year experiment of the pan-Arctic coupled <span class="hlt">ice</span>-ocean general circulation model (GCM). The GCM results indicate that mechanical <span class="hlt">sea</span> <span class="hlt">ice</span> divergence associated with lateral advection accounts for a significant part of the interannual variations in <span class="hlt">sea</span> <span class="hlt">ice</span> thermal production in the coastal polynya regions. This forcing was then rectified by taking into account sub-grid processes and used in a regional model with analytically prescribed bottom topography and vertical stratification in order to examine specific cascading conditions in the Pacific and Atlantic sectors of the Arctic Ocean. Our results demonstrate that the consequences of enhanced <span class="hlt">ice</span> formation depend on geographical location and shelf-basin bathymetry. In the Pacific sector, strong density stratification in slope waters impedes noticeable deepening of shelf-origin water, even for the strongest forcing applied. In the Atlantic sector, a 1.5x increase of</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014OcSci..10..485H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014OcSci..10..485H"><span>The land-<span class="hlt">ice</span> contribution to 21st-century dynamic <span class="hlt">sea</span> level rise</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Howard, T.; Ridley, J.; Pardaens, A. K.; Hurkmans, R. T. W. L.; Payne, A. J.; Giesen, R. H.; Lowe, J. A.; Bamber, J. L.; Edwards, T. L.; Oerlemans, J.</p> <p>2014-06-01</p> <p>Climate change has the potential to influence global mean <span class="hlt">sea</span> level through a number of processes including (but not limited to) thermal expansion of the oceans and enhanced land <span class="hlt">ice</span> melt. In addition to their contribution to global mean <span class="hlt">sea</span> level change, these two processes (among others) lead to local departures from the global mean <span class="hlt">sea</span> level change, through a number of mechanisms including the effect on spatial variations in the change of water density and transport, usually termed dynamic <span class="hlt">sea</span> level changes. In this study, we focus on the component of dynamic <span class="hlt">sea</span> level change that might be given by additional freshwater inflow to the ocean under scenarios of 21st-century land-based <span class="hlt">ice</span> melt. We present regional patterns of dynamic <span class="hlt">sea</span> level change given by a global-coupled atmosphere-ocean climate model forced by spatially and temporally varying projected <span class="hlt">ice</span>-melt fluxes from three sources: the Antarctic <span class="hlt">ice</span> sheet, the Greenland <span class="hlt">Ice</span> Sheet and small glaciers and <span class="hlt">ice</span> caps. The largest <span class="hlt">ice</span> melt flux we consider is equivalent to almost 0.7 m of global mean <span class="hlt">sea</span> level rise over the 21st century. The temporal evolution of the dynamic <span class="hlt">sea</span> level changes, in the presence of considerable variations in the <span class="hlt">ice</span> melt flux, is also analysed. We find that the dynamic <span class="hlt">sea</span> level change associated with the <span class="hlt">ice</span> melt is small, with the largest changes occurring in the North Atlantic amounting to 3 cm above the global mean rise. Furthermore, the dynamic <span class="hlt">sea</span> level change associated with the <span class="hlt">ice</span> melt is similar regardless of whether the simulated <span class="hlt">ice</span> fluxes are applied to a simulation with fixed CO2 or under a business-as-usual greenhouse gas warming scenario of increasing CO2.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2002JCli...15..487K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2002JCli...15..487K"><span>Southern Ocean Climate and <span class="hlt">Sea</span> <span class="hlt">Ice</span> Anomalies Associated with the Southern Oscillation.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kwok, R.; Comiso, J. C.</p> <p>2002-03-01</p> <p>The anomalies in the climate and <span class="hlt">sea</span> <span class="hlt">ice</span> cover of the Southern Ocean and their relationships with the Southern Oscillation (SO) are investigated using a 17-yr dataset from 1982 to 1998. The polar climate anomalies are correlated with the Southern Oscillation index (SOI) and the composites of these anomalies are examined under the positive (SOI > 0), neutral (0 > SOI > 1), and negative (SOI < 1) phases of SOI. The climate dataset consists of <span class="hlt">sea</span> level pressure, wind, surface air temperature, and <span class="hlt">sea</span> surface temperature fields, while the <span class="hlt">sea</span> <span class="hlt">ice</span> dataset describes its extent, concentration, motion, and surface temperature. The analysis depicts, for the first time, the spatial variability in the relationship of the above variables with the SOI. The strongest correlation between the SOI and the polar climate anomalies are found in the Bellingshausen, Amundsen, and Ross <span class="hlt">Seas</span>. The composite fields reveal anomalies that are organized in distinct large-scale spatial patterns with opposing polarities at the two extremes of SOI, and suggest oscillations that are closely linked to the SO. Within these sectors, positive (negative) phases of the SOI are generally associated with lower (higher) <span class="hlt">sea</span> level pressure, cooler (warmer) surface air temperature, and cooler (warmer) <span class="hlt">sea</span> surface temperature in these sectors. Associations between these climate anomalies and the behavior of the Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span> cover are evident. Recent anomalies in the <span class="hlt">sea</span> <span class="hlt">ice</span> cover that are clearly associated with the SOI include the following: the record decrease in the <span class="hlt">sea</span> <span class="hlt">ice</span> extent in the Bellingshausen <span class="hlt">Sea</span> from mid-1988 to early 1991; the relationship between Ross <span class="hlt">Sea</span> SST and the ENSO signal, and reduced <span class="hlt">sea</span> <span class="hlt">ice</span> concentration in the Ross <span class="hlt">Sea</span>; and the shortening of the <span class="hlt">ice</span> season in the eastern Ross <span class="hlt">Sea</span>, Amundsen <span class="hlt">Sea</span>, far western Weddell <span class="hlt">Sea</span> and lengthening of the <span class="hlt">ice</span> season in the western Ross <span class="hlt">Sea</span>, Bellinghausen <span class="hlt">Sea</span>, and central Weddell <span class="hlt">Sea</span> gyre during the period 1988-94. Four ENSO episodes over the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016ESASP.740E..46J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016ESASP.740E..46J"><span>Newly Formed <span class="hlt">Sea</span> <span class="hlt">Ice</span> in Arctic Leads Monitored by C- and L-Band SAR</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Johansson, A. Malin; Brekke, Camilla; Spreen, Gunnar; King, Jennifer A.; Gerland, Sebastian</p> <p>2016-08-01</p> <p>We investigate the scattering entropy and co-polarization ratio for Arctic lead <span class="hlt">ice</span> using C- and L-band synthetic aperture radar (SAR) satellite scenes. During the Norwegian Young <span class="hlt">sea</span> <span class="hlt">ICE</span> (N-<span class="hlt">ICE</span>2015) cruise campaign overlapping SAR scenes, helicopter borne <span class="hlt">sea</span> <span class="hlt">ice</span> thickness measurements and photographs were collected. We can therefore relate the SAR signal to <span class="hlt">sea</span> <span class="hlt">ice</span> thickness measurements as well as photographs taken of the <span class="hlt">sea</span> <span class="hlt">ice</span>. We show that a combination of scattering and co-polarization ratio values can be used to distinguish young <span class="hlt">ice</span> from open water and surrounding <span class="hlt">sea</span> <span class="hlt">ice</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006AnGla..44..253U','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006AnGla..44..253U"><span>Ship-borne electromagnetic induction sounding of <span class="hlt">sea-ice</span> thickness in the southern <span class="hlt">Sea</span> of Okhotsk</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Uto, Shotaro; Toyota, Takenobu; Shimoda, Haruhito; Tateyama, Kazutaka; Shirasawa, Kunio</p> <p></p> <p>Recent observations have revealed that dynamical thickening is dominant in the growth process of <span class="hlt">sea</span> <span class="hlt">ice</span> in the southern <span class="hlt">Sea</span> of Okhotsk. That indicates the importance of understanding the nature of thick deformed <span class="hlt">ice</span> in this area. The objective of the present paper is to establish a ship-based method for observing the thickness of deformed <span class="hlt">ice</span> with reasonable accuracy. Since February 2003, one of the authors has engaged in the core sampling using a small basket from the icebreaker Soya. Based on these results, we developed a new model which expressed the internal structure of pack <span class="hlt">ice</span> in the southern <span class="hlt">Sea</span> of Okhotsk, as a one-dimensional multilayered structure. Since 2004, the electromagnetic (EM) inductive sounding of <span class="hlt">sea-ice</span> thickness has been conducted on board Soya. By combining the model and theoretical calculations, a new algorithm was developed for transforming the output of the EM inductive instrument to <span class="hlt">ice</span> + snow thickness (total thickness). Comparison with total thickness by drillhole observations showed fair agreement. The probability density functions of total thickness in 2004 and 2005 showed some difference, which reflected the difference of fractions of thick deformed <span class="hlt">ice</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5046916','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5046916"><span>The role of <span class="hlt">sea</span> <span class="hlt">ice</span> for vascular plant dispersal in the Arctic</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Ehrich, Dorothee; Bennike, Ole; Geirsdottir, Aslaug</p> <p>2016-01-01</p> <p><span class="hlt">Sea</span> <span class="hlt">ice</span> has been suggested to be an important factor for dispersal of vascular plants in the Arctic. To assess its role for postglacial colonization in the North Atlantic region, we compiled data on the first Late Glacial to Holocene occurrence of vascular plant species in East Greenland, Iceland, the Faroe Islands and Svalbard. For each record, we reconstructed likely past dispersal events using data on species distributions and genetics. We compared these data to <span class="hlt">sea-ice</span> reconstructions to evaluate the potential role of <span class="hlt">sea</span> <span class="hlt">ice</span> in these past colonization events and finally evaluated these results using a compilation of driftwood records as an independent source of evidence that <span class="hlt">sea</span> <span class="hlt">ice</span> can disperse biological material. Our results show that <span class="hlt">sea</span> <span class="hlt">ice</span> was, in general, more prevalent along the most likely dispersal routes at times of assumed first colonization than along other possible routes. Also, driftwood is frequently dispersed in regions that have <span class="hlt">sea</span> <span class="hlt">ice</span> today. Thus, <span class="hlt">sea</span> <span class="hlt">ice</span> may act as an important dispersal agent. Melting <span class="hlt">sea</span> <span class="hlt">ice</span> may hamper future dispersal of Arctic plants and thereby cause more genetic differentiation. It may also limit the northwards expansion of competing boreal species, and hence favour the persistence of Arctic species. PMID:27651529</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1912428I','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1912428I"><span>September Arctic <span class="hlt">Sea</span> <span class="hlt">Ice</span> minimum prediction - a new skillful statistical approach</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ionita-Scholz, Monica; Grosfeld, Klaus; Scholz, Patrick; Treffeisen, Renate; Lohmann, Gerrit</p> <p>2017-04-01</p> <p><span class="hlt">Sea</span> <span class="hlt">ice</span> in both Polar Regions is an important indicator for the expression of global climate change and its polar amplification. Consequently, a broad interest exists on <span class="hlt">sea</span> <span class="hlt">ice</span>, its coverage, variability and long term change. Knowledge on <span class="hlt">sea</span> <span class="hlt">ice</span> requires high quality data on <span class="hlt">ice</span> extent, thickness and its dynamics. However, its predictability is complex and it depends on various climate and oceanic parameters and conditions. In order to provide insights into the potential development of a monthly/seasonal signal of <span class="hlt">sea</span> <span class="hlt">ice</span> evolution, we developed a robust statistical model based on ocean heat content, <span class="hlt">sea</span> surface temperature and different atmospheric variables to calculate an estimate of the September <span class="hlt">Sea</span> <span class="hlt">ice</span> extent (SSIE) on monthly time scale. Although previous statistical attempts at monthly/seasonal forecasts of SSIE show a relatively reduced skill, we show here that more than 92% (r = 0.96) of the September <span class="hlt">sea</span> <span class="hlt">ice</span> extent can be predicted at the end of May by using previous months' climate and oceanic conditions. The skill of the model increases with a decrease in the time lag used for the forecast. At the end of August, our predictions are even able to explain 99% of the SSIE. Our statistical model captures both the general trend as well as the interannual variability of the SSIE. Moreover, it is able to properly forecast the years with extreme high/low SSIE (e.g. 1996/ 2007, 2012, 2013). Besides its forecast skill for SSIE, the model could provide a valuable tool for identifying relevant regions and climate parameters that are important for the <span class="hlt">sea</span> <span class="hlt">ice</span> development in the Arctic and for detecting sensitive and critical regions in global coupled climate models with focus on <span class="hlt">sea</span> <span class="hlt">ice</span> formation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMGC23D1175M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMGC23D1175M"><span><span class="hlt">Sea</span> <span class="hlt">ice</span>-induced cold air advection as a mechanism controlling tundra primary productivity</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Macias-Fauria, M.; Karlsen, S. R.</p> <p>2015-12-01</p> <p>The recent sharp decline in Arctic <span class="hlt">sea</span> <span class="hlt">ice</span> extent, concentration, and volume leaves urgent questions regarding its effects on ecological processes. Changes in tundra productivity have been associated with <span class="hlt">sea</span> <span class="hlt">ice</span> dynamics on the basis that most tundra ecosystems lay close to the <span class="hlt">sea</span>. Although some studies have addressed the potential effect of <span class="hlt">sea</span> <span class="hlt">ice</span> decline on the primary productivity of terrestrial arctic ecosystems (Bhatt et al., 2010), a clear picture of the mechanisms and patterns linking both processes remains elusive. We hypothesised that <span class="hlt">sea</span> <span class="hlt">ice</span> might influence tundra productivity through 1) cold air advection during the growing season (direct/weather effect) or 2) changes in regional climate induced by changes in <span class="hlt">sea</span> <span class="hlt">ice</span> (indirect/climate effect). We present a test on the direct/weather effect hypothesis: that is, tundra productivity is coupled with <span class="hlt">sea</span> <span class="hlt">ice</span> when <span class="hlt">sea</span> <span class="hlt">ice</span> remains close enough from land vegetation during the growing season for cold air advection to limit temperatures locally. We employed weekly MODIS-derived Normalised Difference Vegetation Index (as a proxy for primary productivity) and <span class="hlt">sea</span> <span class="hlt">ice</span> data at a spatial resolution of 232m for the period 2000-2014 (included), covering the Svalbard Archipelago. Our results suggest that <span class="hlt">sea</span> <span class="hlt">ice</span>-induced cold air advection is a likely mechanism to explain patterns of NDVI trends and heterogeneous spatial dynamics in the Svalbard archipelago. The mechanism offers the potential to explain <span class="hlt">sea</span> <span class="hlt">ice</span>/tundra productivity dynamics in other Arctic areas.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014JGRG..119.2276G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014JGRG..119.2276G"><span>Organic iodine in Antarctic <span class="hlt">sea</span> <span class="hlt">ice</span>: A comparison between winter in the Weddell <span class="hlt">Sea</span> and summer in the Amundsen <span class="hlt">Sea</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Granfors, Anna; Ahnoff, Martin; Mills, Matthew M.; Abrahamsson, Katarina</p> <p>2014-12-01</p> <p>Recent studies have recognized <span class="hlt">sea</span> <span class="hlt">ice</span> as a source of reactive iodine to the Antarctic boundary layer. Volatile iodinated compounds (iodocarbons) are released from <span class="hlt">sea</span> <span class="hlt">ice</span>, and they have been suggested to contribute to the formation of iodine oxide (IO), which takes part in tropospheric ozone destruction in the polar spring. We measured iodocarbons (CH3I, CH2ClI, CH2BrI, and CH2I2) in <span class="hlt">sea</span> <span class="hlt">ice</span>, snow, brine, and air during two expeditions to Antarctica, OSO 10/11 to the Amundsen <span class="hlt">Sea</span> during austral summer and ANT XXIX/6 to the Weddell <span class="hlt">Sea</span> in austral winter. These are the first reported measurements of iodocarbons from the Antarctic winter. Iodocarbons were enriched in <span class="hlt">sea</span> <span class="hlt">ice</span> in relation to seawater in both summer and winter. During summer, the positive relationship to chlorophyll a biomass indicated a biological origin. We suggest that CH3I is formed biotically in <span class="hlt">sea</span> <span class="hlt">ice</span> during both summer and winter. For CH2ClI, CH2BrI, and CH2I2, an additional abiotic source at the snow/<span class="hlt">ice</span> interface in winter is suggested. Elevated air concentrations of CH3I and CH2ClI during winter indicate that they are enriched in lower troposphere and may take part in the formation of IO at polar sunrise.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMMR31A..05O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMMR31A..05O"><span>A Krill's Eye View: <span class="hlt">Sea</span> <span class="hlt">Ice</span> Microstructure and Microchemistry</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Obbard, R. W.; Lieb-Lappen, R.</p> <p>2015-12-01</p> <p><span class="hlt">Sea</span> <span class="hlt">ice</span> plays important roles in the marine ecosystem and our environment, and a detailed understanding of all aspects of its microstructure is especially important in this time of changing climate. For many months of the year, the <span class="hlt">ice</span> forms a permeable barrier between Polar oceans and the atmosphere, and as it freezes and melts, its microstructure evolves and changes in ways that affect other parts of that system. <span class="hlt">Sea</span> <span class="hlt">ice</span> also provides a microhabitat that is an important part of the marine ecosystem, but much remains to be learned about it on this scale. In material terms, <span class="hlt">sea</span> <span class="hlt">ice</span> is multiphase and very close to its melting point, and these properties make its microstructure particularly complex and dynamic, as well as challenging and interesting to study. We use a combination of analytical methods to achieve a very detailed understanding of <span class="hlt">sea</span> <span class="hlt">ice</span> microstructure - specifically the morphology and distribution of <span class="hlt">ice</span> crystals and brine channels. Overall porosity affects freeboard, emissivity, and optical and mechanical properties, but pore connectivity is critical to gas and fluid transport, salt flux to polar oceans, the transfer of halogens to the boundary layer troposphere, and the transport of nutrients and pollutants to microorganisms. When <span class="hlt">sea</span> <span class="hlt">ice</span> forms, salts are expelled from newly formed <span class="hlt">ice</span> crystals and concentrated on grain boundaries and in brine pockets and channels. We use synchrotron-based X-ray fluorescence spectroscopy (SXRF) and scanning electron microscope-based energy dispersive spectroscopy (EDS) to map the location in two dimensions of several important salt components in <span class="hlt">sea</span> <span class="hlt">ice</span>: SXRF for bromine, chlorine, potassium, calcium and iron, EDS for these as well as some lighter elements such as sodium, magnesium, and silicon. We use X-ray microcomputed tomography (microCT) to produce three-dimensional models of brine channels and to study changes in brine network topology due to warming and cooling. Both microCT and optical thin sections provide</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.4013V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.4013V"><span>A model of icebergs and <span class="hlt">sea</span> <span class="hlt">ice</span> in a joint continuum framework</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Vaňková, Irena; Holland, David M.</p> <p>2017-04-01</p> <p>The <span class="hlt">ice</span> mélange, a mixture of <span class="hlt">sea</span> <span class="hlt">ice</span> and icebergs, often present in front of tidewater glaciers in Greenland or <span class="hlt">ice</span> shelves in Antarctica, can have a profound effect on the dynamics of the <span class="hlt">ice</span>-ocean system. The current inability to numerically model the <span class="hlt">ice</span> mélange motivates a new modeling approach proposed here. A continuum <span class="hlt">sea-ice</span> model is taken as a starting point and icebergs are represented as thick and compact pieces of <span class="hlt">sea</span> <span class="hlt">ice</span> held together by large tensile and shear strength selectively introduced into the <span class="hlt">sea</span> <span class="hlt">ice</span> rheology. In order to modify the rheology correctly, a semi-Lagrangian time stepping scheme is introduced and at each time step a Lagrangian grid is constructed such that iceberg shape is preserved exactly. With the proposed treatment, <span class="hlt">sea</span> <span class="hlt">ice</span> and icebergs are considered a single fluid with spatially varying rheological properties, mutual interactions are thus automatically included without the need of further parametrization. An important advantage of the presented framework for an <span class="hlt">ice</span> mélange model is its potential to be easily included in existing climate models.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li class="active"><span>25</span></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_25 --> <div class="footer-extlink text-muted" style="margin-bottom:1rem; text-align:center;">Some links on this page may take you to non-federal websites. 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