sea ice snow: Topics by Science.gov

Sample records for sea ice snow

MODIS Snow and Sea Ice Products

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Riggs, George A.; Salomonson, Vincent V.

2004-01-01

In this chapter, we describe the suite of Earth Observing System (EOS) Moderate-Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua snow and sea ice products. Global, daily products, developed at Goddard Space Flight Center, are archived and distributed through the National Snow and Ice 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. Sea ice products include ice extent determined with two different algorithms, and sea ice surface temperature. The algorithms used to develop these products are described. Both the snow and sea ice products, available since February 24,2000, are useful for modelers. Validation of the products is also discussed.
Snow depth evolution on sea ice from Snow Buoy measurement

NASA Astrophysics Data System (ADS)

Nicolaus, M.; Arndt, S.; Hendricks, S.; Hoppmann, M.; Katlein, C.; König-Langlo, G.; Nicolaus, A.; Rossmann, H. L.; Schiller, M.; Schwegmann, S.; Langevin, D.

2016-12-01

Snow cover is an Essential Climate Variable. On sea ice, snow dominates the energy and momentum exchanges across the atmosphere-ice-ocean interfaces, and actively contributes to sea ice mass balance. Yet, snow depth on sea ice 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 sea ice 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 ice, on landfast sea ice or on an ice shelf. Here we highlight results from two pairs of Snow Buoys installed on drifting pack ice in the Weddell Sea. 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 Sea, allowing a net snow accumulation of 0.2 to 0.9 m per year. In contrast, summer snow melt close to the ice 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 sea ice 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 sea ice 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.
Snow depth on Arctic and Antarctic sea ice derived from autonomous (Snow Buoy) measurements

NASA Astrophysics Data System (ADS)

Nicolaus, Marcel; Arndt, Stefanie; Hendricks, Stefan; Heygster, Georg; Huntemann, Marcus; Katlein, Christian; Langevin, Danielle; Rossmann, Leonard; Schwegmann, Sandra

2016-04-01

The snow cover on sea ice received more and more attention in recent sea ice studies and model simulations, because its physical properties dominate many sea ice and upper ocean processes. In particular; the temporal and spatial distribution of snow depth is of crucial importance for the energy and mass budgets of sea ice, as well as for the interaction with the atmosphere and the oceanic freshwater budget. Snow depth is also a crucial parameter for sea ice thickness retrieval algorithms from satellite altimetry data. Recent time series of Arctic sea ice volume only use monthly snow depth climatology, which cannot take into account annual changes of the snow depth and its properties. For Antarctic sea ice, no such climatology is available. With a few exceptions, snow depth on sea ice is determined from manual in-situ measurements with very limited coverage of space and time. Hence the need for more consistent observational data sets of snow depth on sea ice is frequently highlighted. Here, we present time series measurements of snow depths on Antarctic and Arctic sea ice, recorded by an innovative and affordable platform. This Snow Buoy is optimized to autonomously monitor the evolution of snow depth on sea ice and will allow new insights into its seasonality. In addition, the instruments report air temperature and atmospheric pressure directly into different international networks, e.g. the Global Telecommunication System (GTS) and the International Arctic Buoy Programme (IABP). We introduce the Snow Buoy concept together with technical specifications and results on data quality, reliability, and performance of the units. We highlight the findings from four buoys, which simultaneously drifted through the Weddell Sea for more than 1.5 years, revealing unique information on characteristic regional and seasonal differences. Finally, results from seven snow buoys co-deployed on Arctic sea ice throughout the winter season 2015/16 suggest the great importance of local
Airborne radar surveys of snow depth over Antarctic sea ice during Operation IceBridge

NASA Astrophysics Data System (ADS)

Panzer, B.; Gomez-Garcia, D.; Leuschen, C.; Paden, J. D.; Gogineni, P. S.

2012-12-01

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 sea ice thickness and distribution [5, 6]. Estimation of sea-ice thickness from these altimeters relies on freeboard measurements and the presence of snow cover on sea ice 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 sea-ice thickness estimate. To improve the accuracy of the sea-ice thickness estimates and provide validation for measurements from satellite-based sensors, the Center for Remote Sensing of Ice Sheets deploys the Snow Radar as a part of NASA Operation IceBridge. The Snow Radar is an ultra-wideband, frequency-modulated, continuous-wave radar capable of resolving snow depth on sea ice 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-ice 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-ice 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 IceBridge 2010-2011 Antarctic campaigns. In 2010, three sea ice flights were flown, two in the Weddell Sea and one in the Amundsen and Bellingshausen Seas. 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 Sea was flown, allowing for a
Canadian snow and sea ice: historical trends and projections

NASA Astrophysics Data System (ADS)

Mudryk, Lawrence R.; Derksen, Chris; Howell, Stephen; Laliberté, Fred; Thackeray, Chad; Sospedra-Alfonso, Reinel; Vionnet, Vincent; Kushner, Paul J.; Brown, Ross

2018-04-01

The Canadian Sea Ice 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 sea ice 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 sea ice (area, concentration, type, and thickness) across Canada. We also assess projected changes in snow cover and sea ice 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 ice is decreasing over time, with seasonal and regional variability in the trends consistent with regional differences in surface temperature trends. In particular, summer sea ice cover has decreased significantly across nearly all Canadian marine regions, and the rate of multi-year ice loss in the Beaufort Sea 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 sea ice concentration of 5-10 % per decade (or 15-30 % in total), with similar reductions in winter sea ice 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.
The Effects of Snow Depth Forcing on Southern Ocean Sea Ice Simulations

NASA Technical Reports Server (NTRS)

Powel, Dylan C.; Markus, Thorsten; Stoessel, Achim

2003-01-01

The spatial and temporal distribution of snow on sea ice is an important factor for sea ice 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 ice thickness is relatively thin, snow can impact the ice thickness in two ways: a) As mentioned above snow on sea ice reduces the ocean-atmosphere heat flux and thus reduces freezing at the base of the ice flows; b) a heavy snow load can suppress the ice below sea level which causes flooding and, with subsequent freezing, a thickening of the sea ice (snow-to-ice conversion). In this paper, we compare different snow fall paramterizations (incl. the incorporation of satellite-derived snow depth) and study the effect on the sea ice using a sea ice model.
Routine Mapping of the Snow Depth Distribution on Sea Ice

NASA Astrophysics Data System (ADS)

Farrell, S. L.; Newman, T.; Richter-Menge, J.; Dattler, M.; Paden, J. D.; Yan, S.; Li, J.; Leuschen, C.

2016-12-01

The annual growth and retreat of the polar sea ice cover is influenced by the seasonal accumulation, redistribution and melt of snow on sea ice. 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 sea ice cover itself. Moreover the snow depth distribution remains a significant source of uncertainty in the derivation of sea ice thickness from remote sensing measurements, as well as in numerical model predictions of future climate state. Radar altimeter systems flown onboard NASA's Operation IceBridge (OIB) mission now provide annual measurements of snow across both the Arctic and Southern Ocean ice 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 sea ice at the end of winter, just prior to melt. Our analysis provides the snow depth distribution on both seasonal and multi-year sea ice. We present the inter-annual variability in snow depth for both the Central Arctic and the Beaufort/Chukchi Seas. We validate our results via comparison with temporally and spatially coincident in situ measurements gathered during many of the OIB surveys. The results
Spring snow conditions on Arctic sea ice north of Svalbard, during the Norwegian Young Sea ICE (N-ICE2015) expedition

NASA Astrophysics Data System (ADS)

Gallet, Jean-Charles; Merkouriadi, Ioanna; Liston, Glen E.; Polashenski, Chris; Hudson, Stephen; Rösel, Anja; Gerland, Sebastian

2017-10-01

Snow is crucial over sea ice 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 Sea ICE (N-ICE2015) 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 ice, with an average of 55 ± 27 cm and 32 ± 20 cm on first-year ice. 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 sea ice compared to previous observations, due to more variable sea ice 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.
Snow depth on Arctic sea ice from historical in situ data

NASA Astrophysics Data System (ADS)

Shalina, Elena V.; Sandven, Stein

2018-06-01

The snow data from the Soviet airborne expeditions Sever in the Arctic collected over several decades in March, April and May have been analyzed in this study. The Sever data included more measurements and covered a much wider area, particularly in the Eurasian marginal seas (Kara Sea, Laptev Sea, East Siberian Sea and Chukchi Sea), compared to the Soviet North Pole drifting stations. The latter collected data mainly in the central part of the Arctic Basin. The following snow parameters have been analyzed: average snow depth on the level ice (undisturbed snow) height and area of sastrugi, depth of snow dunes attached to ice ridges and depth of snow on hummocks. In the 1970s-1980s, in the central Arctic, the average depth of undisturbed snow was 21.2 cm, the depth of sastrugi (that occupied about 30 % of the ice surface) was 36.2 cm and the average depth of snow near hummocks and ridges was about 65 cm. For the marginal seas, the average depth of undisturbed snow on the level ice varied from 9.8 cm in the Laptev Sea to 15.3 cm in the East Siberian Sea, which had a larger fraction of multiyear ice. In the marginal seas the spatial variability of snow depth was characterized by standard deviation varying between 66 and 100 %. The average height of sastrugi varied from 23 cm to about 32 cm with standard deviation between 50 and 56 %. The average area covered by sastrugi in the marginal seas was estimated to be 36.5 % of the total ice area where sastrugi were observed. The main result of the study is a new snow depth climatology for the late winter using data from both the Sever expeditions and the North Pole drifting stations. The snow load on the ice observed by Sever expeditions has been described as a combination of the depth of undisturbed snow on the level ice and snow depth of sastrugi weighted in proportion to the sastrugi area. The height of snow accumulated near the ice ridges was not included in the calculations because there are no estimates of the area
Winter snow conditions on Arctic sea ice north of Svalbard during the Norwegian young sea ICE (N-ICE2015) expedition

NASA Astrophysics Data System (ADS)

Merkouriadi, Ioanna; Gallet, Jean-Charles; Graham, Robert M.; Liston, Glen E.; Polashenski, Chris; Rösel, Anja; Gerland, Sebastian

2017-10-01

Snow is a crucial component of the Arctic sea ice system. Its thickness and thermal properties control heat conduction and radiative fluxes across the ocean, ice, 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 ice 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 ice (SYI) in the Atlantic sector of the Arctic Ocean, during the Norwegian young sea ICE (N-ICE2015) expedition (January to March 2015). During N-ICE2015, 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 ice 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 ice and 19 ± 5.4 cm over second-year ice.
Antarctic Sea Ice Thickness and Snow-to-Ice Conversion from Atmospheric Reanalysis and Passive Microwave Snow Depth

NASA Technical Reports Server (NTRS)

Markus, Thorsten; Maksym, Ted

2007-01-01

Passive microwave snow depth, ice concentration, and ice motion estimates are combined with snowfall from the European Centre for Medium Range Weather Forecasting (ECMWF) reanalysis (ERA-40) from 1979-200 1 to estimate the prevalence of snow-to-ice conversion (snow-ice formation) on level sea ice in the Antarctic for April-October. Snow ice is ubiquitous in all regions throughout the growth season. Calculated snow- ice thicknesses fall within the range of estimates from ice core analysis for most regions. However, uncertainties in both this analysis and in situ data limit the usefulness of snow depth and snow-ice production to evaluate the accuracy of ERA-40 snowfall. The East Antarctic is an exception, where calculated snow-ice production exceeds observed ice thickness over wide areas, suggesting that ERA-40 precipitation is too high there. Snow-ice thickness variability is strongly controlled not just by snow accumulation rates, but also by ice divergence. Surprisingly, snow-ice production is largely independent of snow depth, indicating that the latter may be a poor indicator of total snow accumulation. Using the presence of snow-ice formation as a proxy indicator for near-zero freeboard, we examine the possibility of estimating level ice thickness from satellite snow depths. A best estimate for the mean level ice thickness in September is 53 cm, comparing well with 51 cm from ship-based observations. The error is estimated to be 10-20 cm, which is similar to the observed interannual and regional variability. Nevertheless, this is comparable to expected errors for ice thickness determined by satellite altimeters. Improvement in satellite snow depth retrievals would benefit both of these methods.
Sea Ice Thickness, Freeboard, and Snow Depth products from Operation IceBridge Airborne Data

NASA Technical Reports Server (NTRS)

Kurtz, N. T.; Farrell, S. L.; Studinger, M.; Galin, N.; Harbeck, J. P.; Lindsay, R.; Onana, V. D.; Panzer, B.; Sonntag, J. G.

2013-01-01

The study of sea ice using airborne remote sensing platforms provides unique capabilities to measure a wide variety of sea ice 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 sea ice properties. In this paper we describe methods for the retrieval of sea ice thickness, freeboard, and snow depth using data from a multisensor suite of instruments on NASA's Operation IceBridge airborne campaign. We assess the consistency of the results through comparison with independent data sets that demonstrate that the IceBridge products are capable of providing a reliable record of snow depth and sea ice 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 IceBridge mission. The uncertainties associated with the retrieval methods are determined and placed in the context of their impact on the retrieved sea ice thickness. Lastly, we present results for the 2009 and 2010 IceBridge campaigns, which are currently available in product form via the National Snow and Ice Data Center
Improving Surface Mass Balance Over Ice Sheets and Snow Depth on Sea Ice

NASA Technical Reports Server (NTRS)

Koenig, Lora Suzanne; Box, Jason; Kurtz, Nathan

2013-01-01

Surface mass balance (SMB) over ice sheets and snow on sea ice (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 ice 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 sea ice cover. The summer of 2012 saw the largest satellite-recorded melt area over the Greenland ice sheet and the smallest satellite-recorded Arctic sea ice extent, making this meeting both timely and relevant.
Snow accumulation on Arctic sea ice: is it a matter of how much or when?

NASA Astrophysics Data System (ADS)

Webster, M.; Petty, A.; Boisvert, L.; Markus, T.

2017-12-01

Snow on sea ice plays an important, yet sometimes opposing role in sea ice mass balance depending on the season. In autumn and winter, snow reduces the heat exchange from the ocean to the atmosphere, reducing sea ice growth. In spring and summer, snow shields sea ice from solar radiation, delaying sea ice surface melt. Changes in snow depth and distribution in any season therefore directly affect the mass balance of Arctic sea ice. In the western Arctic, a decreasing trend in spring snow depth distribution has been observed and attributed to the combined effect of peak snowfall rates in autumn and the coincident delay in sea ice freeze-up. Here, we build on this work and present an in-depth analysis on the relationship between snow accumulation and the timing of sea ice freeze-up across all Arctic regions. A newly developed two-layer snow model is forced with eight reanalysis precipitation products to: (1) identify the seasonal distribution of snowfall accumulation for different regions, (2) highlight which regions are most sensitive to the timing of sea ice freeze-up with regard to snow accumulation, and (3) show, if precipitation were to increase, which regions would be most susceptible to thicker snow covers. We also utilize a comprehensive sensitivity study to better understand the factors most important in controlling winter/spring snow depths, and to explore what could happen to snow depth on sea ice in a warming Arctic climate.
Canadian snow and sea ice: assessment of snow, sea ice, and related climate processes in Canada's Earth system model and climate-prediction system

NASA Astrophysics Data System (ADS)

Kushner, Paul J.; Mudryk, Lawrence R.; Merryfield, William; Ambadan, Jaison T.; Berg, Aaron; Bichet, Adéline; Brown, Ross; Derksen, Chris; Déry, Stephen J.; Dirkson, Arlan; Flato, Greg; Fletcher, Christopher G.; Fyfe, John C.; Gillett, Nathan; Haas, Christian; Howell, Stephen; Laliberté, Frédéric; McCusker, Kelly; Sigmond, Michael; Sospedra-Alfonso, Reinel; Tandon, Neil F.; Thackeray, Chad; Tremblay, Bruno; Zwiers, Francis W.

2018-04-01

The Canadian Sea Ice 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 sea ice in Canada and the circumpolar Arctic. This study presents an assessment from the CanSISE Network of the ability of the second-generation Canadian Earth System Model (CanESM2) and the Canadian Seasonal to Interannual Prediction System (CanSIPS) to simulate and predict snow and sea ice from seasonal to multi-decadal timescales, with a focus on the Canadian sector. To account for observational uncertainty, model structural uncertainty, and internal climate variability, the analysis uses multi-source observations, multiple Earth system models (ESMs) in Phase 5 of the Coupled Model Intercomparison Project (CMIP5), and large initial-condition ensembles of CanESM2 and other models. It is found that the ability of the CanESM2 simulation to capture snow-related climate parameters, such as cold-region surface temperature and precipitation, lies within the range of currently available international models. Accounting for the considerable disagreement among satellite-era observational datasets on the distribution of snow water equivalent, CanESM2 has too much springtime snow mass over Canada, reflecting a broader northern hemispheric positive bias. Biases in seasonal snow cover extent are generally less pronounced. CanESM2 also exhibits retreat of springtime snow generally greater than observational estimates, after accounting for observational uncertainty and internal variability. Sea ice is biased low in the Canadian Arctic, which makes it difficult to assess the realism of long-term sea ice trends there. The strengths and weaknesses of the modelling system need to be understood as a practical tradeoff: the Canadian models are relatively inexpensive computationally because of their moderate resolution, thus enabling their
On the extraordinary snow on the sea ice off East Antarctica in late winter, 2012

NASA Astrophysics Data System (ADS)

Toyota, Takenobu; Massom, Robert; Lecomte, Olivier; Nomura, Daiki; Heil, Petra; Tamura, Takeshi; Fraser, Alexander D.

2016-09-01

In late winter-early spring 2012, the second Sea Ice Physics and Ecosystems Experiment (SIPEX II) was conducted off Wilkes Land, East Antarctica, onboard R/V Aurora Australis. The sea-ice conditions were characterized by significantly thick first-year ice and snow, trapping the ship for about 10 days in the near coastal region. The deep snow cover was particularly remarkable, in that its average value of 0.45 m was almost three times that observed between 1992 and 2007 in the region. To reveal factors responsible, we used in situ observations and ERA-Interim reanalysis (1990-2012) to examine the relative contribution of the different components of the local-regional snow mass balance equation i.e., snow accumulation on sea ice, precipitation minus evaporation (P-E), and loss by (i) snow-ice formation and (ii) entering into leads due to drifting snow. Results show no evidence for significantly high P-E in the winter of 2012. Ice core analysis has shown that although the snow-ice layer was relatively thin, indicating less transformation from snow to snow-ice in 2012 as compared to measurements from 2007, the difference was not enough to explain the extraordinarily deep snow. Based on these results, we deduce that lower loss of snow into leads was probably responsible for the extraordinary snow in 2012. Statistical analysis and satellite images suggest that the reduction in loss of snow into leads is attributed to rough ice surface associated with active deformation processes and larger floe size due to sea-ice expansion. This highlights the importance of snow-sea ice interaction in determining the mean snow depth on Antarctic sea ice.
Small scale variability of snow properties on Antarctic sea ice

NASA Astrophysics Data System (ADS)

Wever, Nander; Leonard, Katherine; Paul, Stephan; Jacobi, Hans-Werner; Proksch, Martin; Lehning, Michael

2016-04-01

Snow on sea ice plays an important role in air-ice-sea interactions, as snow accumulation may for example increase the albedo. Snow is also able to smooth the ice surface, thereby reducing the surface roughness, while at the same time it may generate new roughness elements by interactions with the wind. Snow density is a key property in many processes, for example by influencing the thermal conductivity of the snow layer, radiative transfer inside the snow as well as the effects of aerodynamic forcing on the snowpack. By comparing snow density and grain size from snow pits and snow micro penetrometer (SMP) measurements, highly resolved density and grain size profiles were acquired during two subsequent cruises of the RV Polarstern in the Weddell Sea, Antarctica, between June and October 2013. During the first cruise, SMP measurements were done along two approximately 40 m transects with a horizontal resolution of approximately 30 cm. During the second cruise, one transect was made with approximately 7.5 m resolution over a distance of 500 m. Average snow densities are about 300 kg/m3, but the analysis also reveals a high spatial variability in snow density on sea ice in both horizontal and vertical direction, ranging from roughly 180 to 360 kg/m3. This variability is expressed by coherent snow structures over several meters. On the first cruise, the measurements were accompanied by terrestrial laser scanning (TLS) on an area of 50x50 m2. The comparison with the TLS data indicates that the spatial variability is exhibiting similar spatial patterns as deviations in surface topology. This suggests a strong influence from surface processes, for example wind, on the temporal development of density or grain size profiles. The fundamental relationship between variations in snow properties, surface roughness and changes therein as investigated in this study is interpreted with respect to large-scale ice movement and the mass balance.
Towards development of an operational snow on sea ice product

NASA Astrophysics Data System (ADS)

Stroeve, J.; Liston, G. E.; Barrett, A. P.; Tschudi, M. A.; Stewart, S.

2017-12-01

Sea ice has been visibly changing over the past couple of decades; most notably the annual minimum extent which has shown a distinct downward, and recently accelerating, trend. September mean sea ice extent was over 7×106 km2 in the 1980's, but has averaged less than 5×106 km2 in the last decade. Should this loss continue, there will be wide-ranging impacts on marine ecosystems, coastal communities, prospects for resource extraction and marine activity, and weather conditions in the Arctic and beyond. While changes in the spatial extent of sea ice have been routinely monitored since the 1970s, less is known about how the thickness of the ice cover has changed. While estimates of ice thickness across the Arctic Ocean have become available over the past 20 years based on data from ERS-1/2, Envisat, ICESat, CryoSat-2 satellites and Operation IceBridge aircraft campaigns, the variety of these different measurement approaches, sensor technologies and spatial coverage present formidable challenges. Key among these is that measurement techniques do not measure ice thickness directly - retrievals also require snow depth and density. Towards that end, a sophisticated snow accumulation model is tested in a Lagrangian framework to map daily snow depths across the Arctic sea ice cover using atmospheric reanalysis data as input. Accuracy of the snow accumulation is assessed through comparison with Operation IceBridge data and ice mass balance buoys (IMBs). Impacts on ice thickness retrievals are further discussed.
Ultra-Wideband Radar Measurements of Thickness of Snow Over Sea Ice

NASA Technical Reports Server (NTRS)

Kanagaratnam, P.; Markus, T.; Lytle, V.; Heavey, B.; Jansen, P.; Prescott, G.; Gogineni, S.

2007-01-01

An accurate knowledge of snow thickness and its variability over sea ice is crucial for determining the overall polar heat and freshwater budget, which influences the global climate. Recently, algorithms have been developed to extract snow thicknesses from passive microwave satellite data. However, validation of these data over the large footprint of the passive microwave sensor has been a challenge. The only method used thus far has been with meter sticks during ship cruises. To address this problem, we developed an ultra wideband frequency-modulated continuous-wave (FM-CW) radar to measure snow thickness over sea ice. We made snow-thickness measurements over Antarctic sea ice by operating the radar from a sled during September and October, 2003. We performed radar measurements over 11 stations with varying snow thickness between 4 and 85 cm. We observed excellent agreement between radar estimates of snow thickness with physical measurements, achieving a correlation coefficient of 0.95 and a vertical resolution of about 3 cm.
Thin Sea Ice, Thick Snow, and Widespread Negative Freeboard Observed During N-ICE2015 North of Svalbard

NASA Astrophysics Data System (ADS)

Rösel, Anja; Itkin, Polona; King, Jennifer; Divine, Dmitry; Wang, Caixin; Granskog, Mats A.; Krumpen, Thomas; Gerland, Sebastian

2018-02-01

In recent years, sea-ice conditions in the Arctic Ocean changed substantially toward a younger and thinner sea-ice cover. To capture the scope of these changes and identify the differences between individual regions, in situ observations from expeditions are a valuable data source. We present a continuous time series of in situ measurements from the N-ICE2015 expedition from January to June 2015 in the Arctic Basin north of Svalbard, comprising snow buoy and ice mass balance buoy data and local and regional data gained from electromagnetic induction (EM) surveys and snow probe measurements from four distinct drifts. The observed mean snow depth of 0.53 m for April to early June is 73% above the average value of 0.30 m from historical and recent observations in this region, covering the years 1955-2017. The modal total ice and snow thicknesses, of 1.6 and 1.7 m measured with ground-based EM and airborne EM measurements in April, May, and June 2015, respectively, lie below the values ranging from 1.8 to 2.7 m, reported in historical observations from the same region and time of year. The thick snow cover slows thermodynamic growth of the underlying sea ice. In combination with a thin sea-ice cover this leads to an imbalance between snow and ice thickness, which causes widespread negative freeboard with subsequent flooding and a potential for snow-ice formation. With certainty, 29% of randomly located drill holes on level ice had negative freeboard.

Snow contribution to first-year and second-year Arctic sea ice mass balance north of Svalbard

NASA Astrophysics Data System (ADS)

Granskog, Mats A.; Rösel, Anja; Dodd, Paul A.; Divine, Dmitry; Gerland, Sebastian; Martma, Tõnu; Leng, Melanie J.

2017-03-01

The salinity and water oxygen isotope composition (δ18O) of 29 first-year (FYI) and second-year (SYI) Arctic sea ice cores (total length 32.0 m) from the drifting ice pack north of Svalbard were examined to quantify the contribution of snow to sea ice mass. Five cores (total length 6.4 m) were analyzed for their structural composition, showing variable contribution of 10-30% by granular ice. In these cores, snow had been entrained in 6-28% of the total ice thickness. We found evidence of snow contribution in about three quarters of the sea ice cores, when surface granular layers had very low δ18O values. Snow contributed 7.5-9.7% to sea ice mass balance on average (including also cores with no snow) based on δ18O mass balance calculations. In SYI cores, snow fraction by mass (12.7-16.3%) was much higher than in FYI cores (3.3-4.4%), while the bulk salinity of FYI (4.9) was distinctively higher than for SYI (2.7). We conclude that oxygen isotopes and salinity profiles can give information on the age of the ice and enables distinction between FYI and SYI (or older) ice in the area north of Svalbard.Plain Language SummaryThe role of snow in sea ice mass balance is largely two fold. Firstly, it can slow down growth and melt due to its high insulation and high reflectance, but secondly it can actually contribute to sea ice growth if the snow cover is turned into ice. The latter is largely a consequence of high mass of snow on top of sea ice that can push the surface of the sea ice below sea level and seawater can flood the ice. This mixture of seawater and snow can then freeze and add to the growth of sea ice. This is very typical in the Antarctic but not believed to be so important in the Arctic. In this work we show, for the first time, that snow actually contributes significantly to the growth of Arctic sea ice. This is likely a consequence of the thinning of the Arctic sea ice. The conditions in the Arctic, with </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C31D..03C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C31D..03C">Modulation of Sea Ice Melt Onset and Retreat in the Laptev Sea by the Timing of Snow Retreat in the West Siberian Plain</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Crawford, A. D.; Stroeve, J.; Serreze, M. C.; Rajagopalan, B.; Horvath, S. 2017-12-01 As much of the Arctic Ocean transitions to ice-free conditions in summer, efforts have increased to improve seasonal forecasts of not only sea ice extent, but also the timing of melt onset and retreat. This research investigates the potential of regional terrestrial snow retreat in spring as a predictor for subsequent sea ice melt onset and retreat in Arctic seas. One pathway involves earlier snow retreat enhancing atmospheric moisture content, which increases downwelling longwave radiation over sea ice cover downstream. Another pathway involves manipulation of jet stream behavior, which may affect the sea ice pack via both dynamic and thermodynamic processes. Although several possible connections between snow and sea ice regions are identified using a mutual information criterion, the physical mechanisms linking snow retreat and sea ice phenology are most clearly exemplified by variability of snow retreat in the West Siberian Plain impacting melt onset and sea ice retreat in the Laptev Sea. The detrended time series of snow retreat in the West Siberian Plain explains 26% of the detrended variance in Laptev Sea melt onset (29% for sea ice retreat). With modest predictive skill and an average time lag of 53 (88) days between snow retreat and sea ice melt onset (retreat), West Siberian Plains snow retreat is useful for refining seasonal sea ice predictions in the Laptev Sea. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C33C1211G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C33C1211G">Is snow-ice now a major contributor to sea ice mass balance in the western Transpolar Drift region?</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Graham, R. M.; Merkouriadi, I.; Cheng, B.; Rösel, A.; Granskog, M. A. 2017-12-01 During the Norwegian young sea ICE (N-ICE2015) campaign, which took place in the first half of 2015 north of Svalbard, a deep winter snow pack (50 cm) on sea ice was observed, that was 50% thicker than earlier climatological studies suggested for this region. Moreover, a significant fraction of snow contributed to the total ice mass in second-year ice (SYI) (9% on average). Interestingly, very little snow (3% snow by mass) was present in first-year ice (FYI). The combination of sea ice thinning and increased precipitation north of Svalbard is expected to promote the formation of snow-ice. Here we use the 1-D snow/ice thermodynamic model HIGHTSI forced with reanalysis data, to show that for the case study of N-ICE2015, snow-ice would even form over SYI with an initial thickness of 2 m. In current conditions north of Svalbard, snow-ice is ubiquitous and contributes to the thickness growth up to 30%. This contribution is important, especially in the absence of any bottom thermodynamic growth due to the thick insulating snow cover. Growth of FYI north of Svalbard is mainly controlled by the timing of growth onset relative to snow precipitation events and cold spells. These usually short-lived conditions are largely determined by the frequency of storms entering the Arctic from the Atlantic Ocean. In our case, a later freeze onset was favorable for FYI growth due to less snow accumulation in early autumn. This limited snow-ice formation but promoted bottom thermodynamic growth. We surmise these findings are related to a regional phenomenon in the Atlantic sector of the Arctic, with frequent storm events which bring increasing amounts of precipitation in autumn and winter, and also affect the duration of cold temperatures required for ice growth in winter. We discuss the implications for the importance of snow-ice in the future Arctic, formerly believed to be non-existent in the central Arctic due to thick perennial ice. </li> <li> <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">Leads in Arctic pack ice enable early phytoplankton blooms below snow-covered sea ice</a> <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> 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. 2017-01-01 The Arctic icescape is rapidly transforming from a thicker multiyear ice cover to a thinner and largely seasonal first-year ice 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 sea ice 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 ice. 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 sea ice. Leads in the dynamic ice cover provided added sunlight necessary to initiate and sustain the bloom. Phytoplankton blooms beneath snow-covered ice might become more common and widespread in the future Arctic Ocean with frequent lead formation due to thinner and more dynamic sea ice despite projected increases in high-Arctic snowfall. This could alter productivity, marine food webs and carbon sequestration in the Arctic Ocean. PMID:28102329 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C33C1207M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C33C1207M">Snow depth retrieval from L-band satellite measurements on Arctic and Antarctic sea ice</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Maaß, N.; Kaleschke, L.; Wever, N.; Lehning, M.; Nicolaus, M.; Rossmann, H. L. 2017-12-01 The passive microwave mission SMOS provides daily coverage of the polar regions and measures at a low frequency of 1.4 GHz (L-band). SMOS observations have been used to operationally retrieve sea ice thickness up to 1 m and to estimate snow depth in the Arctic for thicker ice. Here, we present how SMOS-retrieved snow depths compare with airborne measurements from NASA's Operation IceBridge mission (OIB) and with AMSR-2 satellite retrievals at higher frequencies, and we show first applications to Antarctic sea ice. In previous studies, SMOS and OIB snow depths showed good agreement on spatial scales from 50 to 1000 km for some days and disagreement for other days. Here, we present a more comprehensive comparison of OIB and SMOS snow depths in the Arctic for 2011 to 2015. We find that the SMOS retrieval works best for cold conditions and depends on auxiliary information on ice surface temperature, here provided by MODIS thermal imagery satellite data. However, comparing SMOS and OIB snow depths is difficult because of the different spatial resolutions (SMOS: 40 km, OIB: 40 m). Spatial variability within the SMOS footprint can lead to different snow conditions as seen from SMOS and OIB. Ideally the comparison is made for uniform conditions: Low lead and open water fraction, low spatial and temporal variability of ice surface temperature, no mixture of multi- and first-year ice. Under these conditions and cold temperatures (surface temperatures below -25°C), correlation coefficients between SMOS and OIB snow depths increase from 0.3 to 0.6. A finding from the comparison with AMSR-2 snow depths is that the SMOS-based maps depend less on the age of the sea ice than the maps derived from higher frequencies. Additionally, we show first results of SMOS snow depths for Antarctic sea ice. SMOS observations are compared to measurements of autonomous snow buoys drifting in the Weddell Sea since 2014. For a better comparability of these point measurements with SMOS data, we use </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.C21B0575P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.C21B0575P">Snow Radar Derived Surface Elevations and Snow Depths Multi-Year Time Series over Greenland Sea-Ice During IceBridge Campaigns</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Perkovic-Martin, D.; Johnson, M. P.; Holt, B.; Panzer, B.; Leuschen, C. 2012-12-01 This paper presents estimates of snow depth over sea ice from the 2009 through 2011 NASA Operation IceBridge [1] spring campaigns over Greenland and the Arctic Ocean, derived from Kansas University's wideband Snow Radar [2] over annually repeated sea-ice transects. We compare the estimates of the top surface interface heights between NASA's Atmospheric Topographic Mapper (ATM) [3] and the Snow Radar. We follow this by comparison of multi-year snow depth records over repeated sea-ice transects to derive snow depth changes over the area. For the purpose of this paper our analysis will concentrate on flights over North/South basin transects off Greenland, which are the closest overlapping tracks over this time period. The Snow Radar backscatter returns allow for surface and interface layer types to be differentiated between snow, ice, land and water using a tracking and classification algorithm developed and discussed in the paper. The classification is possible due to different scattering properties of surfaces and volumes at the radar's operating frequencies (2-6.5 GHz), as well as the geometries in which they are viewed by the radar. These properties allow the returns to be classified by a set of features that can be used to identify the type of the surface or interfaces preset in each vertical profile. We applied a Support Vector Machine (SVM) learning algorithm [4] to the Snow Radar data to classify each detected interface into one of four types. The SVM algorithm was trained on radar echograms whose interfaces were visually classified and verified against coincident aircraft data obtained by CAMBOT [5] and DMS [6] imaging sensors as well as the scanning ATM lidar. Once the interface locations were detected for each vertical profile we derived a range to each interface that was used to estimate the heights above the WGS84 ellipsoid for direct comparisons with ATM. Snow Radar measurements were calibrated against ATM data over areas free of snow cover and over GPS </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A23I..05F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A23I..05F">Arctic Sea Salt Aerosol from Blowing Snow and Sea Ice Surfaces - a Missing Natural Source in Winter</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Frey, M. M.; Norris, S. J.; Brooks, I. M.; Nishimura, K.; Jones, A. E. 2015-12-01 Atmospheric particles in the polar regions consist mostly of sea salt aerosol (SSA). SSA plays an important role in regional climate change through influencing the surface energy balance either directly or indirectly via cloud formation. SSA irradiated by sunlight also releases very reactive halogen radicals, which control concentrations of ozone, a pollutant and greenhouse gas. However, models under-predict SSA concentrations in the Arctic during winter pointing to a missing source. It has been recently suggested that salty blowing snow above sea ice, which is evaporating, to be that source as it may produce more SSA than equivalent areas of open ocean. Participation in the 'Norwegian Young Sea Ice Cruise (N-ICE 2015)' on board the research vessel `Lance' allowed to test this hypothesis in the Arctic sea ice zone during winter. Measurements were carried out from the ship frozen into the pack ice North of 80º N during February to March 2015. Observations at ground level (0.1-2 m) and from the ship's crows nest (30 m) included number concentrations and size spectra of SSA (diameter range 0.3-10 μm) as well as snow particles (diameter range 50-500 μm). During and after blowing snow events significant SSA production was observed. In the aerosol and snow phase sulfate is fractionated with respect to sea water, which confirms sea ice surfaces and salty snow, and not the open ocean, to be the dominant source of airborne SSA. Aerosol shows depletion in bromide with respect to sea water, especially after sunrise, indicating photochemically driven release of bromine. We discuss the SSA source strength from blowing snow in light of environmental conditions (wind speed, atmospheric turbulence, temperature and snow salinity) and recommend improved model parameterisations to estimate regional aerosol production. N-ICE 2015 results are then compared to a similar study carried out previously in the Weddell Sea during the Antarctic winter. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.C11D..06N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.C11D..06N">Advances in Airborne Altimetric Techniques for the Measurement of Snow on Arctic Sea Ice</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Newman, T.; Farrell, S. L.; Richter-Menge, J.; Elder, B. C.; Ruth, J.; Connor, L. N. 2014-12-01 Current sea ice observations and models indicate a transition towards a more seasonal Arctic ice pack with a smaller, and geographically more variable, multiyear ice component. To gain a comprehensive understanding of the processes governing this transition it is important to include the impact of the snow cover, determining the mechanisms by which snow is both responding to and forcing changes to the sea ice pack. Data from NASA's Operation IceBridge (OIB) snow radar system, which has been making yearly surveys of the western Arctic since 2009, offers a key resource for investigating the snow cover. In this work, we characterize the OIB snow radar instrument response to ascertain the location of 'side-lobes', aiding the interpretation of snow radar data. We apply novel wavelet-based techniques to identify the primary reflecting interfaces within the snow pack from which snow depth estimates are derived. We apply these techniques to the range of available snow radar data collected over the last 6 years during the NASA OIB mission. Our results are validated through comparison with a range of in-situ data. We discuss the impact of sea ice surface morphology on snow radar returns (with respect to ice type) and the topographic conditions over which accurate snow-radar-derived snow depths may be obtained. Finally we present improvements to in situ survey design that will allow for both an improved sampling of the snow radar footprint and more accurate assessment of the uncertainties in radar-derived snow depths in the future. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140008935','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140008935">Validation of Airborne FMCW Radar Measurements of Snow Thickness Over Sea Ice in Antarctica</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Galin, Natalia; Worby, Anthony; Markus, Thorsten; Leuschen, Carl; Gogineni, Prasad 2012-01-01 Antarctic sea ice and its snow cover are integral components of the global climate system, yet many aspects of their vertical dimensions are poorly understood, making their representation in global climate models poor. Remote sensing is the key to monitoring the dynamic nature of sea ice and its snow cover. Reliable and accurate snow thickness data are currently a highly sought after data product. Remotely sensed snow thickness measurements can provide an indication of precipitation levels, predicted to increase with effects of climate change in the polar regions. Airborne techniques provide a means for regional-scale estimation of snow depth and distribution. Accurate regional-scale snow thickness data will also facilitate an increase in the accuracy of sea ice thickness retrieval from satellite altimeter freeboard estimates. The airborne data sets are easier to validate with in situ measurements and are better suited to validating satellite algorithms when compared with in situ techniques. This is primarily due to two factors: better chance of getting coincident in situ and airborne data sets and the tractability of comparison between an in situ data set and the airborne data set averaged over the footprint of the antennas. A 28-GHz frequency modulated continuous wave (FMCW) radar loaned by the Center for Remote Sensing of Ice Sheets to the Australian Antarctic Division is used to measure snow thickness over sea ice in East Antarctica. Provided with the radar design parameters, the expected performance parameters of the radar are summarized. The necessary conditions for unambiguous identification of the airsnow and snowice layers for the radar are presented. Roughnesses of the snow and ice surfaces are found to be dominant determinants in the effectiveness of layer identification for this radar. Finally, this paper presents the first in situ validated snow thickness estimates over sea ice in Antarctica derived from an FMCW radar on a helicopterborne platform. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20020090884&hterms=modis+snow+cover&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dmodis%2Bsnow%2Bcover','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20020090884&hterms=modis+snow+cover&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dmodis%2Bsnow%2Bcover">MODIS Snow and Ice Production</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Hall, Dorthoy K.; Hoser, Paul (Technical Monitor) 2002-01-01 Daily, global snow cover maps, and sea ice cover and sea ice surface temperature (IST) maps are derived from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS), are available at no cost through the National Snow and Ice Data Center (NSIDC). Included on this CD-ROM are samples of the MODIS snow and ice products. In addition, an animation, done by the Scientific Visualization studio at Goddard Space Flight Center, is also included. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C23B0779C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C23B0779C">Snow Climatology of Arctic Sea Ice: Comparison of Reanalysis and Climate Model Data with In Situ Measurements</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Chevooruvalappil Chandran, B.; Pittana, M.; Haas, C. 2015-12-01 Snow on sea ice is a critical and complex factor influencing sea ice processes. Deep snow with a high albedo and low thermal conductivity inhibits ice growth in winter and minimizes ice loss in summer. Very shallow or absent snow promotes ice growth in winter and ice loss in summer. The timing of snow ablation critically impacts summer sea ice mass balance. Here we assess the accuracy of various snow on sea ice data products from reanalysis and modeling comparing them with in situ measurements. The latter are based on the Warren et al. (1999) monthly climatology derived from snow ruler measurements between 1954-1991, and on daily snow depth retrievals from few drifting ice mass balance buoys (IMB) with sufficiently long observations spanning the summer season. These were compared with snow depth data from the National Center for Environmental Prediction Department of Energy Reanalysis 2 (NCEP), the Community Climate System Model 4 (CCSM4), and the Canadian Earth System Model 2 (CanESM2). Results are quite variable in different years and regions. However, there is often good agreement between CanESM2 and IMB snow depth during the winter accumulation and spring melt periods. Regional analyses show that over the western Arctic covered primarily with multiyear ice NCEP snow depths are in good agreement with the Warren climatology while CCSM4 overestimates snow depth. However, in the Eastern Arctic which is dominated by first-year ice the opposite behavior is observed. Compared to the Warren climatology CanESM2 underestimates snow depth in all regions. Differences between different snow depth products are as large as 10 to 20 cm, with large consequences for the sea ice mass balance. However, it is also very difficult to evaluate the accuracy of reanalysis and model snow depths due to a lack of extensive, continuous in situ measurements. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.nsf.gov/pubs/2005/nsf0539/nsf0539_5.pdf','USGSPUBS'); return false;" href="http://www.nsf.gov/pubs/2005/nsf0539/nsf0539_5.pdf">Correlated declines in Pacific arctic snow and sea ice cover</a> <a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Stone, Robert P.; Douglas, David C.; Belchansky, Gennady I.; Drobot, Sheldon 2005-01-01 Simulations of future climate suggest that global warming will reduce Arctic snow and ice cover, resulting in decreased surface albedo (reflectivity). Lowering of the surface albedo leads to further warming by increasing solar absorption at the surface. This phenomenon is referred to as “temperature–albedo feedback.” Anticipation of such a feedback is one reason why scientists look to the Arctic for early indications of global warming. Much of the Arctic has warmed significantly. Northern Hemisphere snow cover has decreased, and sea ice has diminished in area and thickness. As reported in the Arctic Climate Impact Assessment in 2004, the trends are considered to be outside the range of natural variability, implicating global warming as an underlying cause. Changing climatic conditions in the high northern latitudes have influenced biogeochemical cycles on a broad scale. Warming has already affected the sea ice, the tundra, the plants, the animals, and the indigenous populations that depend on them. Changing annual cycles of snow and sea ice also affect sources and sinks of important greenhouse gases (such as carbon dioxide and methane), further complicating feedbacks involving the global budgets of these important constituents. For instance, thawing permafrost increases the extent of tundra wetlands and lakes, releasing greater amounts of methane into the atmosphere. Variable sea ice cover may affect the hemispheric carbon budget by altering the ocean–atmosphere exchange of carbon dioxide. There is growing concern that amplification of global warming in the Arctic will have far-reaching effects on lower latitude climate through these feedback mechanisms. Despite the diverse and convincing observational evidence that the Arctic environment is changing, it remains unclear whether these changes are anthropogenically forced or result from natural variations of the climate system. A better understanding of what controls the seasonal distributions of snow and ice </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014JGRC..119.4141K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014JGRC..119.4141K">Snow depth of the Weddell and Bellingshausen sea ice covers from IceBridge surveys in 2010 and 2011: An examination</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Kwok, R.; Maksym, T. 2014-07-01 We examine the snow radar data from the Weddell and Bellingshausen Seas acquired by eight IceBridge (OIB) flightlines in October of 2010 and 2011. In snow depth retrieval, the sidelobes from the stronger scattering snow-ice (s-i) interfaces could be misidentified as returns from the weaker air-snow (a-s) interfaces. In this paper, we first introduce a retrieval procedure that accounts for the structure of the radar system impulse response followed by a survey of the snow depths in the Weddell and Bellingshausen Seas. Limitations and potential biases in our approach are discussed. Differences between snow depth estimates from a repeat survey of one Weddell Sea track separated by 12 days, without accounting for variability due to ice motion, is -0.7 ± 13.6 cm. Average snow depth is thicker in coastal northwestern Weddell and thins toward Cape Norvegia, a decrease of >30 cm. In the Bellingshausen, the thickest snow is found nearshore in both Octobers and is thickest next to the Abbot Ice Shelf. Snow depth is linearly related to freeboard when freeboards are low but diverge as the freeboard increases especially in the thicker/rougher ice of the western Weddell. We find correlations of 0.71-0.84 between snow depth and surface roughness suggesting preferential accumulation over deformed ice. Retrievals also seem to be related to radar backscatter through surface roughness. Snow depths reported here, generally higher than those from in situ records, suggest dissimilarities in sample populations. Implications of these differences on Antarctic sea ice thickness are discussed. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/AD1013722','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/AD1013722">Optimizing Observations of Sea Ice Thickness and Snow Depth in the Arctic</a> <a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a> 2015-09-30 Region Research and Engineering Laboratory (CRREL), Naval Research Laboratory (NRL) and National Aeronautics and Space Administration ( NASA ) in...and results from this focused effort with data collected during related national and international activities (e.g. other NASA IceBridge sea ice...surface elevation of the snow or ice/air interface, and radar altimetry measurements of the snow/ice interface, taken by NASA IceBridge and NRL </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/AD1013735','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/AD1013735">Snow on Sea Ice Workshop - An Icy Meeting of the Minds: Modelers and Measurers</a> <a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a> 2015-09-30 1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Snow on Sea Ice Workshop - An Icy Meeting of the Minds...workshop was to promote more seamless and better integration between measurements and modeling of snow on sea ice , thereby improving our predictive...capabilities for sea ice . OBJECTIVES The key objective was to improve the ability of modelers and measurers work together closely. To that end, we </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C31A..06R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C31A..06R">The impact of the snow cover on sea-ice thickness products retrieved by Ku-band radar altimeters</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Ricker, R.; Hendricks, S.; Helm, V.; Perovich, D. K. 2015-12-01 Snow on sea ice is a relevant polar climate parameter related to ocean-atmospheric interactions and surface albedo. It also remains an important factor for sea-ice thickness products retrieved from Ku-band satellite radar altimeters like Envisat or CryoSat-2, which is currently on its mission and the subject of many recent studies. Such satellites sense the height of the sea-ice surface above the sea level, which is called sea-ice freeboard. By assuming hydrostatic equilibrium and that the main scattering horizon is given by the snow-ice interface, the freeboard can be transformed into sea-ice thickness. Therefore, information about the snow load on hemispherical scale is crucial. Due to the lack of sufficient satellite products, only climatological values are used in current studies. Since such values do not represent the high variability of snow distribution in the Arctic, they can be a substantial contributor to the total sea-ice thickness uncertainty budget. Secondly, recent studies suggest that the snow layer cannot be considered as homogenous, but possibly rather featuring a complex stratigraphy due to wind compaction and/or ice lenses. Therefore, the Ku-band radar signal can be scattered at internal layers, causing a shift of the main scattering horizon towards the snow surface. This alters the freeboard and thickness retrieval as the assumption that the main scattering horizon is given by the snow-ice interface is no longer valid and introduces a bias. Here, we present estimates for the impact of snow depth uncertainties and snow properties on CryoSat-2 sea-ice thickness retrievals. We therefore compare CryoSat-2 freeboard measurements with field data from ice mass-balance buoys and aircraft campaigns from the CryoSat Validation Experiment. This unique validation dataset includes airborne laser scanner and radar altimeter measurements in spring coincident to CryoSat-2 overflights, and allows us to evaluate how the main scattering horizon is altered by the </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC53A0867D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC53A0867D">Impacts of 1, 1.5, and 2 Degree Warming on Arctic Terrestrial Snow and Sea Ice</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. 2017-12-01 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 sea ice 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 sea ice 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 sea ice extent, and the loss of a large proportion of multi-year sea ice. The spatial patterns of observed snow and sea ice loss are coherent across adjacent terrestrial/marine regions. There are strong pattern correlations between snow and temperature trends, with weaker association between sea ice and temperature due to the additional influence of dynamical effects such wind-driven redistribution of sea ice. 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 ice 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C33C1213N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C33C1213N">On the Impact of Snow Salinity on CryoSat-2 First-Year Sea Ice Thickness Retrievals</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Nandan, V.; Yackel, J.; Geldsetzer, T.; Mahmud, M. 2017-12-01 European Space Agency's Ku-band altimeter CryoSat-2 (CS-2) has demonstrated its potential to provide extensive basin-scale spatial and temporal measurements of Arctic sea ice freeboard. It is assumed that CS-2 altimetric returns originate from the snow/sea ice interface (assumed to be the main scattering horizon). However, in newly formed thin ice ( 0.6 m) through to thick first-year sea ice (FYI) ( 2 m), upward wicking of brine into the snow cover from the underlying sea ice surface produces saline snow layers, especially in the bottom 6-8 cm of a snow cover. This in turn modifies the brine volume at/or near the snow/sea ice interface, altering the dielectric and scattering properties of the snow cover, leading to strong Ku-band microwave attenuation within the upper snow volume. Such significant reductions in Ku-band penetration may substantially affect CS-2 FYI freeboard retrievals. Therefore, the goal of this study is to evaluate a theoretical approach to estimate snow salinity induced uncertainty on CS-2 Arctic FYI freeboard measurements. Using the freeboard-to-thickness hydrostatic equilibrium equation, we quantify the error differences between the CS-2 FYI thickness, (assuming complete penetration of CS-2 radar signals to the snow/FYI interface), and the FYI thickness based on the modeled Ku-band main scattering horizon for different snow cover cases. We utilized naturally occurring saline and non-saline snow cover cases ranging between 6 cm to 32 cm from the Canadian Arctic, observed during late-winter from 1993 to 2017, on newly-formed ice ( 0.6 m), medium ( 1.5 m) and thick FYI ( 2 m). Our results suggest that irrespective of the thickness of the snow cover overlaying FYI, the thickness of brine-wetted snow layers and actual FYI freeboard strongly influence the amount with which CS-2 FYI freeboard estimates and thus thickness calculations are overestimated. This effect is accentuated for increasingly thicker saline snow covers overlaying newly-formed ice </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.C23B0489B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.C23B0489B">Response of Arctic Snow and Sea Ice Extents to Melt Season Atmospheric Forcing Across the Land-Ocean Boundary</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Bliss, A. C.; Anderson, M. R. 2011-12-01 Little research has gone into studying the concurrent variations in the annual loss of continental snow cover and sea ice extent across the land-ocean boundary, however, the analysis of these data averaged spatially over three study regions located in North America and Eastern and Western Russia, reveals a distinct difference in the response of anomalous snow and sea ice conditions to the atmospheric forcing. This study compares the monthly continental snow cover and sea ice extent loss in the Arctic, during the melt season months (May-August) for the period 1979-2007, with regional atmospheric conditions known to influence summer melt including: mean sea level pressures, 925 hPa air temperatures, and mean 2 m U and V wind vectors from NCEP/DOE Reanalysis 2. The monthly hemispheric snow cover extent data used are from the Rutgers University Global Snow Lab and sea ice extents for this study are derived from the monthly passive microwave satellite Bootstrap algorithm sea ice concentrations available from the National Snow and Ice Data Center. Three case study years (1985, 1996, and 2007) are used to compare the direct response of monthly anomalous sea ice and snow cover areal extents to monthly mean atmospheric forcing averaged spatially over the extent of each study region. This comparison is then expanded for all summer months over the 29 year study period where the monthly persistence of sea ice and snow cover extent anomalies and changes in the sea ice and snow conditions under differing atmospheric conditions are explored further. The monthly anomalous atmospheric conditions are classified into four categories including: warmer temperatures with higher pressures, warmer temperatures with lower pressures, cooler temperatures with higher pressures, and cooler temperatures with lower pressures. Analysis of the atmospheric conditions surrounding anomalous loss of snow and ice cover over the independent study regions indicates that conditions of warmer temperatures </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ERL....12h4010L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ERL....12h4010L">Improved simulation of Antarctic sea ice due to the radiative effects of falling snow</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Li, J.-L. F.; Richardson, Mark; Hong, Yulan; Lee, Wei-Liang; Wang, Yi-Hui; Yu, Jia-Yuh; Fetzer, Eric; Stephens, Graeme; Liu, Yinghui 2017-08-01 Southern Ocean sea-ice cover exerts critical control on local albedo and Antarctic precipitation, but simulated Antarctic sea-ice concentration commonly disagrees with observations. Here we show that the radiative effects of precipitating ice (falling snow) contribute substantially to this discrepancy. Many models exclude these radiative effects, so they underestimate both shortwave albedo and downward longwave radiation. Using two simulations with the climate model CESM1, we show that including falling-snow radiative effects improves the simulations relative to cloud properties from CloudSat-CALIPSO, radiation from CERES-EBAF and sea-ice concentration from passive microwave sensors. From 50-70°S, the simulated sea-ice-area bias is reduced by 2.12 × 106 km2 (55%) in winter and by 1.17 × 106 km2 (39%) in summer, mainly because increased wintertime longwave heating restricts sea-ice growth and so reduces summer albedo. Improved Antarctic sea-ice simulations will increase confidence in projected Antarctic sea level contributions and changes in global warming driven by long-term changes in Southern Ocean feedbacks. </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_1");'>1</a></li> <li class="active">2</li> <li><a href="#" onclick='return showDiv("page_3");'>3</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><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_3" 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_1");'>1</a></li> <li><a href="#" onclick='return showDiv("page_2");'>2</a></li> <li class="active">3</li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</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="41"> <li> <a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA103734','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA103734">Review of Thermal Properties of Snow, Ice and Sea Ice,</a> <a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a> 1981-06-01 AD-AL03 734 COLD RE61ONS RESEARCH AND ENGINEERING LAS HANOVER NH F/G 8/12AI3 3REVIEW OF THERMAL PROPERTIES OF SNOW. ICE AND SEA ICE,(U)UNCLASSIFIlED...Distribution/ Availability Codes Avail and/or D~ Dis~t Special D 1 7 C- T > L) UNITED STATES ARMY CORPS OF ENGINEERS COLD REGIONS RESEARCH AND ENGINEERING...PROGRAM ELEMENT, PROJECT. TASK AREA A WORK UNIT NUMBERS U.S. Army Cold Regions Research and Engineering Laboratory Hanover, New Hampshire 03755 DA Pr </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20090038693','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20090038693">Estimation of Sea Ice Thickness Distributions through the Combination of Snow Depth and Satellite Laser Altimetry Data</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Kurtz, Nathan T.; Markus, Thorsten; Cavalieri, Donald J.; Sparling, Lynn C.; Krabill, William B.; Gasiewski, Albin J.; Sonntag, John G. 2009-01-01 Combinations of sea ice freeboard and snow depth measurements from satellite data have the potential to provide a means to derive global sea ice thickness values. However, large differences in spatial coverage and resolution between the measurements lead to uncertainties when combining the data. High resolution airborne laser altimeter retrievals of snow-ice freeboard and passive microwave retrievals of snow depth taken in March 2006 provide insight into the spatial variability of these quantities as well as optimal methods for combining high resolution satellite altimeter measurements with low resolution snow depth data. The aircraft measurements show a relationship between freeboard and snow depth for thin ice allowing the development of a method for estimating sea ice thickness from satellite laser altimetry data at their full spatial resolution. This method is used to estimate snow and ice thicknesses for the Arctic basin through the combination of freeboard data from ICESat, snow depth data over first-year ice from AMSR-E, and snow depth over multiyear ice from climatological data. Due to the non-linear dependence of heat flux on ice thickness, the impact on heat flux calculations when maintaining the full resolution of the ICESat data for ice thickness estimates is explored for typical winter conditions. Calculations of the basin-wide mean heat flux and ice growth rate using snow and ice thickness values at the 70 m spatial resolution of ICESat are found to be approximately one-third higher than those calculated from 25 km mean ice thickness values. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C33C1209N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C33C1209N">A full year of snow on sea ice observations and simulations - Plans for MOSAiC 2019/20</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Nicolaus, M.; Geland, S.; Perovich, D. K. 2017-12-01 The snow cover on sea on sea ice dominates many exchange processes and properties of the ice covered polar oceans. It is a major interface between the atmosphere and the sea ice with the ocean underneath. Snow on sea ice is known for its extraordinarily large spatial and temporal variability from micro scales and minutes to basin wide scales and decades. At the same time, snow cover properties and even snow depth distributions are among the least known and most difficult to observe climate variables. Starting in October 2019 and ending in October 2020, the international MOSAiC drift experiment will allow to observe the evolution of a snow pack on Arctic sea ice over a full annual cycle. During the drift with one ice floe along the transpolar drift, we will study snow processes and interactions as one of the main topics of the MOSAiC research program. Thus we will, for the first time, be able to perform such studies on seasonal sea ice and relate it to previous expeditions and parallel observations at different locations. Here we will present the current status of our planning of the MOSAiC snow program. We will summarize the latest implementation ideas to combine the field observations with numerical simulations. The field program will include regular manual observations and sampling on the main floe of the central observatory, autonomous recordings in the distributed network, airborne observations in the surrounding of the central observatory, and retrievals of satellite remote sensing products. Along with the field program, numerical simulations of the MOSAiC snow cover will be performed on different scales, including large-scale interaction with the atmosphere and the sea ice. The snow studies will also bridge between the different disciplines, including physical, chemical, biological, and geochemical measurements, samples, and fluxes. The main challenge of all measurements will be to accomplish the description of the full annual cycle. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20060038062&hterms=flower&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dflower','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20060038062&hterms=flower&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dflower">(abstract) A Polarimetric Model for Effects of Brine Infiltrated Snow Cover and Frost Flowers on Sea Ice Backscatter</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Nghiem, S. V.; Kwok, R.; Yueh, S. H. 1995-01-01 A polarimetric scattering model is developed to study effects of snow cover and frost flowers with brine infiltration on thin sea ice. Leads containing thin sea ice in the Artic icepack are important to heat exchange with the atmosphere and salt flux into the upper ocean. Surface characteristics of thin sea ice in leads are dominated by the formation of frost flowers with high salinity. In many cases, the thin sea ice layer is covered by snow, which wicks up brine from sea ice due to capillary force. Snow and frost flowers have a significant impact on polarimetric signatures of thin ice, which needs to be studied for accessing the retrieval of geophysical parameters such as ice thickness. Frost flowers or snow layer is modeled with a heterogeneous mixture consisting of randomly oriented ellipsoids and brine infiltration in an air background. Ice crystals are characterized with three different axial lengths to depict the nonspherical shape. Under the covering multispecies medium, the columinar sea-ice layer is an inhomogeneous anisotropic medium composed of ellipsoidal brine inclusions preferentially oriented in the vertical direction in an ice background. The underlying medium is homogeneous sea water. This configuration is described with layered inhomogeneous media containing multiple species of scatterers. The species are allowed to have different size, shape, and permittivity. The strong permittivity fluctuation theory is extended to account for the multispecies in the derivation of effective permittivities with distributions of scatterer orientations characterized by Eulerian rotation angles. Polarimetric backscattering coefficients are obtained consistently with the same physical description used in the effective permittivity calculation. The mulitspecies model allows the inclusion of high-permittivity species to study effects of brine infiltrated snow cover and frost flowers on thin ice. The results suggest that the frost cover with a rough interface </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20000038117&hterms=SSM&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3DSSM','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20000038117&hterms=SSM&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3DSSM">A Comparison of Sea Ice Type, Sea Ice Temperature, and Snow Thickness Distributions in the Arctic Seasonal Ice Zones with the DMSP SSM/I</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> St.Germain, Karen; Cavalieri, Donald J.; Markus, Thorsten 1997-01-01 Global climate studies have shown that sea ice is a critical component in the global climate system through its effect on the ocean and atmosphere, and on the earth's radiation balance. Polar energy studies have further shown that the distribution of thin ice and open water largely controls the distribution of surface heat exchange between the ocean and atmosphere within the winter Arctic ice pack. The thickness of the ice, the depth of snow on the ice, and the temperature profile of the snow/ice composite are all important parameters in calculating surface heat fluxes. In recent years, researchers have used various combinations of DMSP SSMI channels to independently estimate the thin ice type (which is related to ice thickness), the thin ice temperature, and the depth of snow on the ice. In each case validation efforts provided encouraging results, but taken individually each algorithm gives only one piece of the information necessary to compute the energy fluxes through the ice and snow. In this paper we present a comparison of the results from each of these algorithms to provide a more comprehensive picture of the seasonal ice zone using passive microwave observations. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017PhDT.......190B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017PhDT.......190B">Machine Learning Algorithms for Automated Satellite Snow and Sea Ice Detection</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Bonev, George The continuous mapping of snow and ice cover, particularly in the arctic and poles, are critical to understanding the earth and atmospheric science. Much of the world's sea ice and snow covers the most inhospitable places, making measurements from satellite-based remote sensors essential. Despite the wealth of data from these instruments many challenges remain. For instance, remote sensing instruments reside on-board different satellites and observe the earth at different portions of the electromagnetic spectrum with different spatial footprints. Integrating and fusing this information to make estimates of the surface is a subject of active research. In response to these challenges, this dissertation will present two algorithms that utilize methods from statistics and machine learning, with the goal of improving on the quality and accuracy of current snow and sea ice detection products. The first algorithm aims at implementing snow detection using optical/infrared instrument data. The novelty in this approach is that the classifier is trained using ground station measurements of snow depth that are collocated with the reflectance observed at the satellite. Several classification methods are compared using this training data to identify the one yielding the highest accuracy and optimal space/time complexity. The algorithm is then evaluated against the current operational NASA snow product and it is found that it produces comparable and in some cases superior accuracy results. The second algorithm presents a fully automated approach to sea ice detection that integrates data obtained from passive microwave and optical/infrared satellite instruments. For a particular region of interest the algorithm generates sea ice maps of each individual satellite overpass and then aggregates them to a daily composite level, maximizing the amount of high resolution information available. The algorithm is evaluated at both, the individual satellite overpass level, and at the daily </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.A23C0165M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.A23C0165M">Influence of projected snow and sea-ice changes on future climate in heavy snowfall region</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Matsumura, S.; Sato, T. 2011-12-01 Snow/ice albedo and cloud feedbacks are critical for climate change projection in cryosphere regions. However, future snow and sea-ice distributions are significantly different in each GCM. Thus, surface albedo in cryosphere regions is one of the causes of the uncertainty for climate change projection. Northern Japan is one of the heaviest snowfall regions in the world. In particular, Hokkaido is bounded on the north by the Okhotsk Sea, where is the southernmost ocean in the Northern Hemisphere that is covered with sea ice during winter. Wintertime climate around Hokkaido is highly sensitive to fluctuations in snow and sea-ice. The purpose of this study is to evaluate the influence of global warming on future climate around Hokkaido, using the Pseudo-Global-Warming method (PGW) by a regional climate model. The boundary conditions of the PGW run were obtained by adding the difference between the future (2090s) and past (1990s) climates simulated by coupled general circulation model (MIROC3.2 medres), which is from the CMIP3 multi-model dataset, into the 6-hourly NCEP reanalysis (R-2) and daily OISST data in the past climate (CTL) run. The PGW experiments show that snow depth significantly decreases over mountainous areas and snow cover mainly decreases over plain areas, contributing to higher surface warming due to the decreased snow albedo. Despite the snow reductions, precipitation mainly increases over the mountainous areas because of enhanced water vapor content. However, precipitation decreases over the Japan Sea and the coastal areas, indicating the weakening of a convergent cloud band, which is formed by convergence between cold northwesteries from the Eurasian continent and anticyclonic circulation over the Okhotsk Sea. These results suggest that Okhotsk sea-ice decline may change the atmospheric circulation and the resulting effect on cloud formation, resulting in changes in winter snow or precipitation. We will also examine another CMIP3 model (MRI-CGCM2 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20150001450','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20150001450">An Ultra-Wideband, Microwave Radar for Measuring Snow Thickness on Sea Ice and Mapping Near-Surface Internal Layers in Polar Firn</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Panzer, Ben; Gomez-Garcia, Daniel; Leuschen, Carl; Paden, John; Rodriguez-Morales, Fernando; Patel, Azsa; Markus, Thorsten; Holt, Benjamin; Gogineni, Prasad 2013-01-01 Sea ice is generally covered with snow, which can vary in thickness from a few centimeters to >1 m. Snow cover acts as a thermal insulator modulating the heat exchange between the ocean and the atmosphere, and it impacts sea-ice growth rates and overall thickness, a key indicator of climate change in polar regions. Snow depth is required to estimate sea-ice thickness using freeboard measurements made with satellite altimeters. The snow cover also acts as a mechanical load that depresses ice freeboard (snow and ice above sea level). Freeboard depression can result in flooding of the snow/ice interface and the formation of a thick slush layer, particularly in the Antarctic sea-ice cover. The Center for Remote Sensing of Ice Sheets (CReSIS) has developed an ultra-wideband, microwave radar capable of operation on long-endurance aircraft to characterize the thickness of snow over sea ice. The low-power, 100mW signal is swept from 2 to 8GHz allowing the air/snow and snow/ ice interfaces to be mapped with 5 c range resolution in snow; this is an improvement over the original system that worked from 2 to 6.5 GHz. From 2009 to 2012, CReSIS successfully operated the radar on the NASA P-3B and DC-8 aircraft to collect data on snow-covered sea ice in the Arctic and Antarctic for NASA Operation IceBridge. The radar was found capable of snow depth retrievals ranging from 10cm to >1 m. We also demonstrated that this radar can be used to map near-surface internal layers in polar firn with fine range resolution. Here we describe the instrument design, characteristics and performance of the radar. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018CliPa..14..193B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018CliPa..14..193B">The Ross Sea Dipole - temperature, snow accumulation and sea ice variability in the Ross Sea region, Antarctica, over the past 2700 years</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Bertler, Nancy A. N.; Conway, Howard; Dahl-Jensen, Dorthe; Emanuelsson, Daniel B.; Winstrup, Mai; Vallelonga, Paul T.; Lee, James E.; Brook, Ed J.; Severinghaus, Jeffrey P.; Fudge, Taylor J.; Keller, Elizabeth D.; Baisden, W. Troy; Hindmarsh, Richard C. A.; Neff, Peter D.; Blunier, Thomas; Edwards, Ross; Mayewski, Paul A.; Kipfstuhl, Sepp; Buizert, Christo; Canessa, Silvia; Dadic, Ruzica; Kjær, Helle A.; Kurbatov, Andrei; Zhang, Dongqi; Waddington, Edwin D.; Baccolo, Giovanni; Beers, Thomas; Brightley, Hannah J.; Carter, Lionel; Clemens-Sewall, David; Ciobanu, Viorela G.; Delmonte, Barbara; Eling, Lukas; Ellis, Aja; Ganesh, Shruthi; Golledge, Nicholas R.; Haines, Skylar; Handley, Michael; Hawley, Robert L.; Hogan, Chad M.; Johnson, Katelyn M.; Korotkikh, Elena; Lowry, Daniel P.; Mandeno, Darcy; McKay, Robert M.; Menking, James A.; Naish, Timothy R.; Noerling, Caroline; Ollive, Agathe; Orsi, Anaïs; Proemse, Bernadette C.; Pyne, Alexander R.; Pyne, Rebecca L.; Renwick, James; Scherer, Reed P.; Semper, Stefanie; Simonsen, Marius; Sneed, Sharon B.; Steig, Eric J.; Tuohy, Andrea; Ulayottil Venugopal, Abhijith; Valero-Delgado, Fernando; Venkatesh, Janani; Wang, Feitang; Wang, Shimeng; Winski, Dominic A.; Winton, V. Holly L.; Whiteford, Arran; Xiao, Cunde; Yang, Jiao; Zhang, Xin 2018-02-01 High-resolution, well-dated climate archives provide an opportunity to investigate the dynamic interactions of climate patterns relevant for future projections. Here, we present data from a new, annually dated ice core record from the eastern Ross Sea, named the Roosevelt Island Climate Evolution (RICE) ice core. Comparison of this record with climate reanalysis data for the 1979-2012 interval shows that RICE reliably captures temperature and snow precipitation variability in the region. Trends over the past 2700 years in RICE are shown to be distinct from those in West Antarctica and the western Ross Sea captured by other ice cores. For most of this interval, the eastern Ross Sea was warming (or showing isotopic enrichment for other reasons), with increased snow accumulation and perhaps decreased sea ice concentration. However, West Antarctica cooled and the western Ross Sea showed no significant isotope temperature trend. This pattern here is referred to as the Ross Sea Dipole. Notably, during the Little Ice Age, West Antarctica and the western Ross Sea experienced colder than average temperatures, while the eastern Ross Sea underwent a period of warming or increased isotopic enrichment. From the 17th century onwards, this dipole relationship changed. All three regions show current warming, with snow accumulation declining in West Antarctica and the eastern Ross Sea but increasing in the western Ross Sea. We interpret this pattern as reflecting an increase in sea ice in the eastern Ross Sea with perhaps the establishment of a modern Roosevelt Island polynya as a local moisture source for RICE. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017TCry...11.2571K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017TCry...11.2571K">Intercomparison of snow depth retrievals over Arctic sea ice from radar data acquired by Operation IceBridge</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Kwok, Ron; Kurtz, Nathan T.; Brucker, Ludovic; Ivanoff, Alvaro; Newman, Thomas; Farrell, Sinead L.; King, Joshua; Howell, Stephen; Webster, Melinda A.; Paden, John; Leuschen, Carl; MacGregor, Joseph A.; Richter-Menge, Jacqueline; Harbeck, Jeremy; Tschudi, Mark 2017-11-01 Since 2009, the ultra-wideband snow radar on Operation IceBridge (OIB; a NASA airborne mission to survey the polar ice covers) has acquired data in annual campaigns conducted during the Arctic and Antarctic springs. Progressive improvements in radar hardware and data processing methodologies have led to improved data quality for subsequent retrieval of snow depth. Existing retrieval algorithms differ in the way the air-snow (a-s) and snow-ice (s-i) interfaces are detected and localized in the radar returns and in how the system limitations are addressed (e.g., noise, resolution). In 2014, the Snow Thickness On Sea Ice Working Group (STOSIWG) was formed and tasked with investigating how radar data quality affects snow depth retrievals and how retrievals from the various algorithms differ. The goal is to understand the limitations of the estimates and to produce a well-documented, long-term record that can be used for understanding broader changes in the Arctic climate system. Here, we assess five retrieval algorithms by comparisons with field measurements from two ground-based campaigns, including the BRomine, Ozone, and Mercury EXperiment (BROMEX) at Barrow, Alaska; a field program by Environment and Climate Change Canada at Eureka, Nunavut; and available climatology and snowfall from ERA-Interim reanalysis. The aim is to examine available algorithms and to use the assessment results to inform the development of future approaches. We present results from these assessments and highlight key considerations for the production of a long-term, calibrated geophysical record of springtime snow thickness over Arctic sea ice. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JGRC..122.9548T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JGRC..122.9548T">Biogeochemical Impact of Snow Cover and Cyclonic Intrusions on the Winter Weddell Sea Ice Pack</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Tison, J.-L.; Schwegmann, S.; Dieckmann, G.; Rintala, J.-M.; Meyer, H.; Moreau, S.; Vancoppenolle, M.; Nomura, D.; Engberg, S.; Blomster, L. J.; Hendrickx, S.; Uhlig, C.; Luhtanen, A.-M.; de Jong, J.; Janssens, J.; Carnat, G.; Zhou, J.; Delille, B. 2017-12-01 Sea ice is a dynamic biogeochemical reactor and a double interface actively interacting with both the atmosphere and the ocean. However, proper understanding of its annual impact on exchanges, and therefore potentially on the climate, notably suffer from the paucity of autumnal and winter data sets. Here we present the results of physical and biogeochemical investigations on winter Antarctic pack ice in the Weddell Sea (R. V. Polarstern AWECS cruise, June-August 2013) which are compared with those from two similar studies conducted in the area in 1986 and 1992. The winter 2013 was characterized by a warm sea ice cover due to the combined effects of deep snow and frequent warm cyclones events penetrating southward from the open Southern Ocean. These conditions were favorable to high ice permeability and cyclic events of brine movements within the sea ice cover (brine tubes), favoring relatively high chlorophyll-a (Chl-a) concentrations. We discuss the timing of this algal activity showing that arguments can be presented in favor of continued activity during the winter due to the specific physical conditions. Large-scale sea ice model simulations also suggest a context of increasingly deep snow, warm ice, and large brine fractions across the three observational years, despite the fact that the model is forced with a snowfall climatology. This lends support to the claim that more severe Antarctic sea ice conditions, characterized by a longer ice season, thicker, and more concentrated ice are sufficient to increase the snow depth and, somehow counterintuitively, to warm the ice. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..1711590F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..1711590F">Chemical Atmosphere-Snow-Sea Ice Interactions: defining future research in the field, lab and modeling</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Frey, Markus 2015-04-01 The air-snow-sea ice system plays an important role in the global cycling of nitrogen, halogens, trace metals or carbon, including greenhouse gases (e.g. CO2 air-sea flux), and therefore influences also climate. Its impact on atmospheric composition is illustrated for example by dramatic ozone and mercury depletion events which occur within or close to the sea ice zone (SIZ) mostly during polar spring and are catalysed by halogens released from SIZ ice, snow or aerosol. Recent field campaigns in the high Arctic (e.g. BROMEX, OASIS) and Antarctic (Weddell sea cruises) highlight the importance of snow on sea ice as a chemical reservoir and reactor, even during polar night. However, many processes, participating chemical species and their interactions are still poorly understood and/or lack any representation in current models. Furthermore, recent lab studies provide a lot of detail on the chemical environment and processes but need to be integrated much better to improve our understanding of a rapidly changing natural environment. During a 3-day workshop held in Cambridge/UK in October 2013 more than 60 scientists from 15 countries who work on the physics, chemistry or biology of the atmosphere-snow-sea ice system discussed research status and challenges, which need to be addressed in the near future. In this presentation I will give a summary of the main research questions identified during this workshop as well as ways forward to answer them through a community-based interdisciplinary approach. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110008454','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110008454">Freeboard, Snow Depth and Sea-Ice Roughness in East Antarctica from In Situ and Multiple Satellite Data</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Markus, Thorsten; Masson, Robert; Worby, Anthony; Lytle, Victoria; Kurtz, Nathan; Maksym, Ted 2011-01-01 In October 2003 a campaign on board the Australian icebreaker Aurora Australis had the objective to validate standard Aqua Advanced Microwave Scanning Radiometer (AMSR-E) sea-ice products. Additionally, the satellite laser altimeter on the Ice, Cloud and land Elevation Satellite (ICESat) was in operation. To capture the large-scale information on the sea-ice conditions necessary for satellite validation, the measurement strategy was to obtain large-scale sea-ice statistics using extensive sea-ice measurements in a Lagrangian approach. A drifting buoy array, spanning initially 50 km 100 km, was surveyed during the campaign. In situ measurements consisted of 12 transects, 50 500 m, with detailed snow and ice measurements as well as random snow depth sampling of floes within the buoy array using helicopters. In order to increase the amount of coincident in situ and satellite data an approach has been developed to extrapolate measurements in time and in space. Assuming no change in snow depth and freeboard occurred during the period of the campaign on the floes surveyed, we use buoy ice-drift information as well as daily estimates of thin-ice fraction and rough-ice vs smooth-ice fractions from AMSR-E and QuikSCAT, respectively, to estimate kilometer-scale snow depth and freeboard for other days. The results show that ICESat freeboard estimates have a mean difference of 1.8 cm when compared with the in situ data and a correlation coefficient of 0.6. Furthermore, incorporating ICESat roughness information into the AMSR-E snow depth algorithm significantly improves snow depth retrievals. Snow depth retrievals using a combination of AMSR-E and ICESat data agree with in situ data with a mean difference of 2.3 cm and a correlation coefficient of 0.84 with a negligible bias. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMIN43B0087W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMIN43B0087W">Alaska Testbed for the Fusion of Citizen Science and Remote Sensing of Sea Ice and Snow</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Walsh, J. E.; Sparrow, E.; Lee, O. A.; Brook, M.; Brubaker, M.; Casas, J. 2017-12-01 Citizen science, remote sensing and related environmental information sources for the Alaskan Arctic are synthesized with the objectives of (a) placing local observations into a broader geospatial framework and (b) enabling the use of local observations to evaluate sea ice, snow and land surface products obtained from remote sensing. In its initial phase, the project instituted a coordinated set of community-based observations of sea ice and snow in three coastal communities in western and northern Alaska: Nome, Point Hope and Barrow. Satellite maps of sea ice concentration have been consolidated with the in situ reports, leading to a three-part depiction of surface conditions at each site: narrative reports, surface-based photos, and satellite products. The project has developed a prototype visualization package, enabling users to select a location and date for which the three information sources can be viewed. Visual comparisons of the satellite products and the local reports show generally consistent depictions of the sea ice concentrations in the vicinity of the coastlines, although the satellite products are generally biased low, especially in coastal regions where shorefast ice persists after the appearance of open water farther offshore. A preliminary comparison of the local snow reports and the MODIS daily North American snow cover images indicates that areas of snow persisted in the satellite images beyond the date of snow disappearance reported by the observers. The "in-town" location of most of the snow reports is a factor that must be addressed in further reporting and remote sensing comparisons. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140011040','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140011040">Snow Dunes: A Controlling Factor of Melt Pond Distribution on Arctic Sea Ice</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Petrich, Chris; Eicken, Hajo; Polashenski, Christopher M.; Sturm, Matthew; Harbeck, Jeremy P.; Perovich, Donald K.; Finnegan, David C. 2012-01-01 The location of snow dunes over the course of the ice-growth season 2007/08 was mapped on level landfast first-year sea ice near Barrow, Alaska. Landfast ice formed in mid-December and exhibited essentially homogeneous snow depths of 4-6 cm in mid-January; by early February distinct snow dunes were observed. Despite additional snowfall and wind redistribution throughout the season, the location of the dunes was fixed by March, and these locations were highly correlated with the distribution of meltwater ponds at the beginning of June. Our observations, including ground-based light detection and ranging system (lidar) measurements, show that melt ponds initially form in the interstices between snow dunes, and that the outline of the melt ponds is controlled by snow depth contours. The resulting preferential surface ablation of ponded ice creates the surface topography that later determines the melt pond evolution. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018TCry...12..993Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018TCry...12..993Z">On the retrieval of sea ice thickness and snow depth using concurrent laser altimetry and L-band remote sensing data</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Zhou, Lu; Xu, Shiming; Liu, Jiping; Wang, Bin 2018-03-01 The accurate knowledge of sea ice parameters, including sea ice thickness and snow depth over the sea ice cover, is key to both climate studies and data assimilation in operational forecasts. Large-scale active and passive remote sensing is the basis for the estimation of these parameters. In traditional altimetry or the retrieval of snow depth with passive microwave remote sensing, although the sea ice thickness and the snow depth are closely related, the retrieval of one parameter is usually carried out under assumptions over the other. For example, climatological snow depth data or as derived from reanalyses contain large or unconstrained uncertainty, which result in large uncertainty in the derived sea ice thickness and volume. In this study, we explore the potential of combined retrieval of both sea ice thickness and snow depth using the concurrent active altimetry and passive microwave remote sensing of the sea ice cover. Specifically, laser altimetry and L-band passive remote sensing data are combined using two forward models: the L-band radiation model and the isostatic relationship based on buoyancy model. Since the laser altimetry usually features much higher spatial resolution than L-band data from the Soil Moisture Ocean Salinity (SMOS) satellite, there is potentially covariability between the observed snow freeboard by altimetry and the retrieval target of snow depth on the spatial scale of altimetry samples. Statistically significant correlation is discovered based on high-resolution observations from Operation IceBridge (OIB), and with a nonlinear fitting the covariability is incorporated in the retrieval algorithm. By using fitting parameters derived from large-scale surveys, the retrievability is greatly improved compared with the retrieval that assumes flat snow cover (i.e., no covariability). Verifications with OIB data show good match between the observed and the retrieved parameters, including both sea ice thickness and snow depth. With </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUOSHE34A1450N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUOSHE34A1450N">Export of Algal Communities from Land Fast Arctic Sea Ice Influenced by Overlying Snow Depth and Episodic Rain Events</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Neuer, S.; Juhl, A. R.; Aumack, C.; McHugh, C.; Wolverton, M. A.; Kinzler, K. 2016-02-01 Sea ice algal communities dominate primary production of the coastal Arctic Ocean in spring. As the sea ice bloom terminates, algae are released from the ice into the underlying, nutrient-rich waters, potentially seeding blooms and feeding higher trophic levels in the water column and benthos. We studied the sea ice community including export events over four consecutive field seasons (2011-2014) during the spring ice algae bloom in land-fast ice near Barrow, Alaska, allowing us to investigate both seasonal and interannual differences. Within each year, we observed a delay in algal export from ice in areas covered by thicker snow compared to areas with thinner snow coverage. Variability in snow cover therefore resulted in a prolonged supply of organic matter to the underlying water column. Earlier export in 2012 was followed by a shift in the diatom community within the ice from pennates to centrics. During an unusual warm period in early May 2014, precipitation falling as rain substantially decreased the snow cover thickness (from snow depth > 20 cm down to 0-2 cm). After the early snowmelt, algae were rapidly lost from the sea ice, and a subsequent bloom of taxonomically-distinct, under-ice phytoplankton developed a few days later. The typical immured sea ice diatoms never recovered in terms of biomass, though pennate diatoms (predominantly Nitzschia frigida) did regrow to some extent near the ice bottom. Sinking rates of the under-ice phytoplankton were much more variable than those of ice algae particles, which would potentially impact residence time in the water column, and fluxes to the benthos. Thus, the early melt episode, triggered by rain, transitioned directly into the seasonal melt and the release of biomass from the ice, shifting production from sea ice to the water column, with as-of-yet unknown consequences for the springtime Arctic food web. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C13C0831F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C13C0831F">First Results from the ASIBIA (Arctic Sea-Ice, snow, Biogeochemistry and Impacts on the Atmosphere) Sea-Ice Chamber</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Frey, M. M.; France, J.; von Glasow, R.; Thomas, M. 2015-12-01 The ocean-ice-atmosphere system is very complex, and there are numerous challenges with conducting fieldwork on sea-ice including costs, safety, experimental controls and access. By creating a new coupled Ocean-Sea-Ice-(Snow)-Atmosphere facility at the University of East Anglia, UK, we are able to perform controlled investigations in areas such as sea-ice physics, physicochemical and biogeochemical processes in sea-ice, and to quantify the bi-directional flux of gases in established, freezing and melting sea-ice. The environmental chamber is capable of controlled programmable temperatures from -55°C to +30°C, allowing a full range of first year sea-ice growing conditions in both the Arctic and Antarctic to be simulated. The sea-ice 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 ice biogeochemistry and photochemistry. Ice growth in the tank will be ideally suited for studying first-year sea-ice physical properties, with in-situ ice-profile measurements of temperature, salinity, conductivity, pressure and spectral light transmission. Under water and above ice cameras are installed to observe the physical development of the sea-ice. The ASIBIA facility is also well equipped for gas exchange and diffusion studies through sea-ice 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 sea-ice chamber, focussing on the physical development of first-year sea-ice and show the future plans for the facility over </li> <li> <a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70024388','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70024388">Contaminants in arctic snow collected over northwest Alaskan sea ice</a> <a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Garbarino, J.R.; Snyder-Conn, E.; Leiker, T.J.; Hoffman, G.L. 2002-01-01 Snow cores were collected over sea ice from four northwest Alaskan Arctic estuaries that represented the annual snowfall from the 1995-1996 season. Dissolved trace metals, major cations and anions, total mercury, and organochlorine compounds were determined and compared to concentrations in previous arctic studies. Traces (<4 nanograms per liter, ng L-1) of cis- and trans-chlordane, dimethyl 2,3,5,6-tetrachloroterephthalate, dieldrin, endosulfan II, and PCBs were detected in some samples, with endosulfan I consistently present. High chlorpyrifos concentrations (70-80 ng L-1) also were estimated at three sites. The snow was highly enriched in sulfates (69- 394 mg L-1), with high proportions of nonsea salt sulfates at three of five sites (9 of 15 samples), thus indicating possible contamination through long-distance transport and deposition of sulfate-rich atmospheric aerosols. Mercury, cadmium, chromium, molybdenum, and uranium were typically higher in the marine snow (n = 15) in relation to snow from arctic terrestrial studies, whereas cations associated with terrigenous sources, such as aluminum, frequently were lower over the sea ice. One Kasegaluk Lagoon site (Chukchi Sea) had especially high concentrations of total mercury (mean = 214 ng L-1, standard deviation = 5 ng L-1), but no methyl mercury was detected above the method detection limit (0.036 ng L-1) at any of the sites. Elevated concentrations of sulfate, mercury, and certain heavy metals might indicate mechanisms of contaminant loss from the arctic atmosphere over marine water not previously reported over land areas. Scavenging by snow, fog, or riming processes and the high content of deposited halides might facilitate the loss of such contaminants from the atmosphere. Both the mercury and chlorpyrifos concentrations merit further investigation in view of their toxicity to aquatic organisms at low concentrations. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20030022773','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20030022773">Snow and Ice Products from the Moderate Resolution Imaging Spectroradiometer</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Hall, Dorothy K.; Salomonson, Vincent V.; Riggs, George A.; Klein, Andrew G. 2003-01-01 Snow and sea ice products, derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument, flown on the Terra and Aqua satellites, are or will be available through the National Snow and Ice Data Center Distributed Active Archive Center (DAAC). The algorithms that produce the products are automated, thus providing a consistent global data set that is suitable for climate studies. The suite of MODIS snow products begins with a 500-m resolution, 2330-km swath snow-cover map that is then projected onto a sinusoidal grid to produce daily and 8-day composite tile products. The sequence proceeds to daily and 8-day composite climate-modeling grid (CMG) products at 0.05 resolution. A daily snow albedo product will be available in early 2003 as a beta test product. The sequence of sea ice products begins with a swath product at 1-km resolution that provides sea ice extent and ice-surface temperature (IST). The sea ice swath products are then mapped onto the Lambert azimuthal equal area or EASE-Grid projection to create a daily and 8-day composite sea ice tile product, also at 1 -km resolution. Climate-Modeling Grid (CMG) sea ice products in the EASE-Grid projection at 4-km resolution are planned for early 2003. </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_1");'>1</a></li> <li><a href="#" onclick='return showDiv("page_2");'>2</a></li> <li class="active">3</li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_4" 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_2");'>2</a></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li class="active">4</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> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="61"> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C53C..04Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C53C..04Z">Simultaneous retrieval of sea ice thickness and snow depth using concurrent active altimetry and passive L-band remote sensing data</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Zhou, L.; Xu, S.; Liu, J. 2017-12-01 The retrieval of sea ice thickness mainly relies on satellite altimetry, and the freeboard measurements are converted to sea ice thickness (hi) under certain assumptions over snow loading. The uncertain in snow depth (hs) is a major source of uncertainty in the retrieved sea ice thickness and total volume for both radar and laser altimetry. In this study, novel algorithms for the simultaneous retrieval of hi and hs are proposed for the data synergy of L-band (1.4 GHz) passive remote sensing and both types of active altimetry: (1) L-band (1.4GHz) brightness temperature (TB) from Soil Moisture Ocean Salinity (SMOS) satellite and sea ice freeboard (FBice) from radar altimetry, (2) L-band TB data and snow freeboard (FBsnow) from laser altimetry. Two physical models serve as the forward models for the retrieval: L-band radiation model, and the hydrostatic equilibrium model. Verification with SMOS and Operational IceBridge (OIB) data is carried out, showing overall good retrieval accuracy for both sea ice parameters. Specifically, we show that the covariability between hs and FBsnow is crucial for the synergy between TB and FBsnow. Comparison with existing algorithms shows lower uncertainty in both sea ice parameters, and that the uncertainty in the retrieved sea ice thickness as caused by that of snow depth is spatially uncorrelated, with the potential reduction of the volume uncertainty through spatial sampling. The proposed algorithms can be applied to the retrieval of sea ice parameters at basin-scale, using concurrent active and passive remote sensing data based on satellites. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006AGUFM.C12A..01A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006AGUFM.C12A..01A">Turbulent Surface Flux Measurements over Snow-Covered Sea Ice</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Andreas, E. L.; Fairall, C. W.; Grachev, A. A.; Guest, P. S.; Jordan, R. E.; Persson, P. G. 2006-12-01 Our group has used eddy correlation to make over 10,000 hours of measurements of the turbulent momentum and heat fluxes over snow-covered sea ice in both the Arctic and the Antarctic. Polar sea ice is an ideal site for studying fundamental processes for turbulent exchange over snow. Both our Arctic and Antarctic sites---in the Beaufort Gyre and deep into the Weddell Sea, respectively---were expansive, flat areas with continuous snow cover; and both were at least 300 km from any topography that might have complicated the atmospheric flow. In this presentation, we will review our measurements of the turbulent fluxes of momentum and sensible and latent heat. In particular, we will describe our experiences making turbulence instruments work in the fairly harsh polar, marine boundary layer. For instance, several of our Arctic sites were remote from our main camp and ran unattended for a week at a time. Besides simply making flux measurements, we have been using the data to develop a bulk flux algorithm and to study fundamental turbulence processes in the atmospheric surface layer. The bulk flux algorithm predicts the turbulent surface fluxes from mean meteorological quantities and, thus, will find use in data analyses and models. For example, components of the algorithm are already embedded in our one- dimensional mass and energy budget model SNTHERM. Our fundamental turbulence studies have included deducing new scaling regimes in the stable boundary layer; examining the Monin-Obukhov similarity functions, especially in stable stratification; and evaluating the von Kármán constant with the largest atmospheric data set ever applied to such a study. During this presentation, we will highlight some of this work. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20000038122&hterms=modis+snow+cover&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dmodis%2Bsnow%2Bcover','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20000038122&hterms=modis+snow+cover&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dmodis%2Bsnow%2Bcover">MODIS Snow and Ice Products from the NSIDC DAAC</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Scharfen, Greg R.; Hall, Dorothy K.; Riggs, George A. 1997-01-01 The National Snow and Ice Data Center (NSIDC) Distributed Active Archive Center (DAAC) provides data and information on snow and ice processes, especially pertaining to interactions among snow, ice, atmosphere and ocean, in support of research on global change detection and model validation, and provides general data and information services to cryospheric and polar processes research community. The NSIDC DAAC is an integral part of the multi-agency-funded support for snow and ice data management services at NSIDC. The Moderate Resolution Imaging Spectroradiometer (MODIS) will be flown on the first Earth Observation System (EOS) platform (AM-1) in 1998. The MODIS Instrument Science Team is developing geophysical products from data collected by the MODIS instrument, including snow and ice products which will be archived and distributed by NSIDC DAAC. The MODIS snow and ice mapping algorithms will generate global snow, lake ice, and sea ice cover products on a daily basis. These products will augment the existing record of satellite-derived snow cover and sea ice products that began about 30 years ago. The characteristics of these products, their utility, and comparisons to other data set are discussed. Current developments and issues are summarized. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19790069568&hterms=limnology&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dlimnology','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19790069568&hterms=limnology&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dlimnology">Remote sensing of snow and ice</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Rango, A. 1979-01-01 This paper reviews remote sensing of snow and ice, techniques for improved monitoring, and incorporation of the new data into forecasting and management systems. The snowcover interpretation of visible and infrared data from satellites, automated digital methods, radiative transfer modeling to calculate the solar reflectance of snow, and models using snowcover input data and elevation zones for calculating snowmelt are discussed. The use of visible and near infrared techniques for inferring snow properties, microwave monitoring of snowpack characteristics, use of Landsat images for collecting glacier data, monitoring of river ice with visible imagery from NOAA satellites, use of sequential imagery for tracking ice flow movement, and microwave studies of sea ice are described. Applications of snow and ice research to commercial use are examined, and it is concluded that a major problem to be solved is characterization of snow and ice in nature, since assigning of the correct properties to a real system to be modeled has been difficult. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/11589227','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/11589227">[Psycrophilic organisms in snow and ice].</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Kohshima, S 2000-12-01 Psychrophilic and psycrotrophic organisms are important in global ecology as a large proportion of our planet is cold. Two-third of sea-water covering more than 70% of Earth is cold deep sea water with temperature around 2 degrees C, and more than 90% of freshwater is in polar ice-sheets and mountain glaciers. Though biological activity in snow and ice had been believed to be extremely limited, various specialized biotic communities were recently discovered at glaciers of various part of the world. The glacier is relatively simple and closed ecosystem with special biotic community containing various psychrophilic and psycrotrophic organisms. Since psychrophilic organisms was discovered in the deep ice-core recovered from the antarctic ice-sheet and a lake beneath it, snow and ice environments in Mars and Europa are attracting a great deal of scientific attention as possible extraterrestrial habitats of life. This paper briefly reviews the results of the studies on ecology of psychrophilic organisms living in snow and ice environments and their physiological and biochemical adaptation to low temperature. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5134033','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5134033">Sea ice, rain-on-snow and tundra reindeer nomadism in Arctic Russia</a> <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Kumpula, Timo; Meschtyb, Nina; Laptander, Roza; Macias-Fauria, Marc; Zetterberg, Pentti; Verdonen, Mariana; Kim, Kwang-Yul; Boisvert, Linette N.; Stroeve, Julienne C.; Bartsch, Annett 2016-01-01 Sea ice loss is accelerating in the Barents and Kara Seas (BKS). Assessing potential linkages between sea ice retreat/thinning and the region's ancient and unique social–ecological systems is a pressing task. Tundra nomadism remains a vitally important livelihood for indigenous Nenets and their large reindeer herds. Warming summer air temperatures have been linked to more frequent and sustained summer high-pressure systems over West Siberia, Russia, but not to sea ice retreat. At the same time, autumn/winter rain-on-snow (ROS) events have become more frequent and intense. Here, we review evidence for autumn atmospheric warming and precipitation increases over Arctic coastal lands in proximity to BKS ice loss. Two major ROS events during November 2006 and 2013 led to massive winter reindeer mortality episodes on the Yamal Peninsula. Fieldwork with migratory herders has revealed that the ecological and socio-economic impacts from the catastrophic 2013 event will unfold for years to come. The suggested link between sea ice loss, more frequent and intense ROS events and high reindeer mortality has serious implications for the future of tundra Nenets nomadism. PMID:27852939 </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27852939','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27852939">Sea ice, rain-on-snow and tundra reindeer nomadism in Arctic Russia.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Forbes, Bruce C; Kumpula, Timo; Meschtyb, Nina; Laptander, Roza; Macias-Fauria, Marc; Zetterberg, Pentti; Verdonen, Mariana; Skarin, Anna; Kim, Kwang-Yul; Boisvert, Linette N; Stroeve, Julienne C; Bartsch, Annett 2016-11-01 Sea ice loss is accelerating in the Barents and Kara Seas (BKS). Assessing potential linkages between sea ice retreat/thinning and the region's ancient and unique social-ecological systems is a pressing task. Tundra nomadism remains a vitally important livelihood for indigenous Nenets and their large reindeer herds. Warming summer air temperatures have been linked to more frequent and sustained summer high-pressure systems over West Siberia, Russia, but not to sea ice retreat. At the same time, autumn/winter rain-on-snow (ROS) events have become more frequent and intense. Here, we review evidence for autumn atmospheric warming and precipitation increases over Arctic coastal lands in proximity to BKS ice loss. Two major ROS events during November 2006 and 2013 led to massive winter reindeer mortality episodes on the Yamal Peninsula. Fieldwork with migratory herders has revealed that the ecological and socio-economic impacts from the catastrophic 2013 event will unfold for years to come. The suggested link between sea ice loss, more frequent and intense ROS events and high reindeer mortality has serious implications for the future of tundra Nenets nomadism. © 2016 The Authors. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70011332','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70011332">Snow and ice in a changing hydrological world.</a> <a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Meier, M.F. 1983-01-01 Snow cover on land (especially in the Northern Hemisphere) and sea ice (especially in the Southern Hemisphere) vary seasonally, and this seasonal change has an important affect on the world climate because snow and sea ice reflect solar radiation efficiently and affect other heat flow processes between atmosphere and land or ocean. Glaciers, including ice sheets, store most of the fresh water on Earth, but change dimensions relatively slowly. There is no clear evidence that the glacier ice volume currently is declining, but more needs to be known about mountain glacier and ice sheet mass balances. -from Author </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012PhDT.......190H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012PhDT.......190H">The influence of sea ice on Antarctic ice core sulfur chemistry and on the future evolution of Arctic snow depth: Investigations using global models</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Hezel, Paul J. SO2-4 deposition to differences between the modern and LGM climates, including sea ice extent, sea surface temperatures, oxidant concentrations, and meteorological conditions. We are unable to find a mechanism whereby MSA deposition fluxes are higher than nss SO2-4 deposition fluxes on the East Antarctic Plateau in the LGM compared the modern period. We conclude that the observed differences between MSA and nss SO2-4 on glacial-interglacial time scales are due to post-depositional processes that affect the ice core MSA concentrations. We can not rule out the possibility of increased DMS emissions in the LGM compared to the modern day. If oceanic DMS production and ocean-to-air fluxes in the sea ice zone are significantly enhanced by the presence of sea ice as indicated by observations, we suggest that the potentially larger amplitude of the seasonal cycle in sea ice extent in the LGM implies a more important role for sea ice in modulating the sulfur cycle during the LGM compared to the modern period. We then shift our focus to study the evolution of snow depth on sea ice in global climate model simulations of the 20th and 21st centuries from the Coupled Model Intercomparison Project 5 (CMIP5). Two competing processes, decreasing sea ice extent and increasing precipitation, will affect snow accumulation on sea ice in the future, and it is not known a priori which will dominate. The decline in Arctic sea ice extent is a well-studied problem in future scenarios of climate change. Moisture convergence into the Arctic is also expected to increase in a warmer world, which may result in increasing snowfall rates. We show that the accumulated snow depth on sea ice in the spring declines as a result of decreased ice extent in the early autumn, in spite of increased winter snowfall rates. The ringed seal (Phoca hispida ) depends on accumulated snow in the spring to build subnivean birth lairs, and provides one of the motivations for this study. Using an empirical threshold of </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19870020585','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19870020585">NASA sea ice and snow validation plan for the Defense Meteorological Satellite Program special sensor microwave/imager</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Cavalieri, Donald J. (Editor); Swift, Calvin T. (Editor) 1987-01-01 This document addresses the task of developing and executing a plan for validating the algorithm used for initial processing of sea ice data from the Special Sensor Microwave/Imager (SSMI). The document outlines a plan for monitoring the performance of the SSMI, for validating the derived sea ice parameters, and for providing quality data products before distribution to the research community. Because of recent advances in the application of passive microwave remote sensing to snow cover on land, the validation of snow algorithms is also addressed. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19880047735&hterms=Climate+Change+impacts&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3DClimate%2BChange%2Bimpacts','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19880047735&hterms=Climate+Change+impacts&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3DClimate%2BChange%2Bimpacts">A vertically integrated snow/ice model over land/sea for climate models. I - Development. II - Impact on orbital change experiments</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Neeman, Binyamin U.; Ohring, George; Joseph, Joachim H. 1988-01-01 A vertically integrated formulation (VIF) model for sea ice/snow and land snow is discussed which can simulate the nonlinear effects of heat storage and transfer through the layers of snow and ice. The VIF demonstates the accuracy of the multilayer formulation, while benefitting from the computational flexibility of linear formulations. In the second part, the model is implemented in a seasonal dynamic zonally averaged climate model. It is found that, in response to a change between extreme high and low summer insolation orbits, the winter orbital change dominates over the opposite summer change for sea ice. For snow over land the shorter but more pronounced summer orbital change is shown to dominate. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.C31A0625D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.C31A0625D">The Role of Snow Thickness over Arctic Winter Sea Ice in the Survival and Dispersal of Brine-Derived Microbes</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Deming, J. W.; Ewert, M.; Bowman, J. S. 2013-12-01 The brines of polar winter sea ice are inhabited by significant densities of microbes (Bacteria and Archaea) that experience a range of extreme conditions depending on location in, and age of, the ice. Newly formed sea ice in winter expels microbes (and organic exudates) onto the surface of the ice, where they can be wicked into frost flowers or into freshly deposited snow, resulting in populations at the ice-air and air-snow interfaces characterized by even more extreme conditions. The influence of snow thickness over the ice on the fate of these microbes, and their potential for dispersal or mediation of exchanges with other components of the ice-snow system, is not well known. Examination of in situ temperature data from the Mass Balance Observatory (MBO) offshore of Barrow, Alaska, during the winter of 2011 allowed recognition of an hierarchy of fluctuation regimes in temperature and (by calculation) brine salinity, where the most stable conditions were encountered within the sea ice and the least stable highest in the snow cover, where temperature fluctuations were significantly more energetic as determined by an analysis of power spectral density. A prior analysis of snow thickness near the MBO had already revealed significant ablation events, potentially associated with bacterial mortality, that would have exposed the saline (microbe-rich) snow layer to wind-based dispersal. To better understand the survival of marine bacteria under these dynamic and extreme conditions, we conducted laboratory experiments with Arctic bacterial isolates, subjecting them to simulations of the freezing regimes documented at the MBS. The impact of the fluctuation regime was shown to be species-specific, with the organism of narrower temperature and salinity growth ranges suffering 30-50% mortality (which could be partially relieved by providing protection against salt-shock). This isolate, the psychrophilic marine bacterium Colwellia psychrerythraea strain 34H (temperature range </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018BGeo...15.3331N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018BGeo...15.3331N">CO2 flux over young and snow-covered Arctic pack ice in winter and spring</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Nomura, Daiki; Granskog, Mats A.; Fransson, Agneta; Chierici, Melissa; Silyakova, Anna; Ohshima, Kay I.; Cohen, Lana; Delille, Bruno; Hudson, Stephen R.; Dieckmann, Gerhard S. 2018-06-01 Rare CO2 flux measurements from Arctic pack ice show that two types of ice contribute to the release of CO2 from the ice to the atmosphere during winter and spring: young, thin ice with a thin layer of snow and older (several weeks), thicker ice with thick snow cover. Young, thin sea ice is characterized by high salinity and high porosity, and snow-covered thick ice remains relatively warm ( > -7.5 °C) due to the insulating snow cover despite air temperatures as low as -40 °C. Therefore, brine volume fractions of these two ice types are high enough to provide favorable conditions for gas exchange between sea ice and the atmosphere even in mid-winter. Although the potential CO2 flux from sea ice decreased due to the presence of the snow, the snow surface is still a CO2 source to the atmosphere for low snow density and thin snow conditions. We found that young sea ice that is formed in leads without snow cover produces CO2 fluxes an order of magnitude higher than those in snow-covered older ice (+1.0 ± 0.6 mmol C m-2 day-1 for young ice and +0.2 ± 0.2 mmol C m-2 day-1 for older ice). </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C41B1213T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C41B1213T">Ultra-Wideband Radiometry Remote Sensing of Polar Ice Sheet Temperature Profile, Sea Ice and Terrestrial Snow Thickness: Forward Modeling and Data Analysis</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Tsang, L.; Tan, S.; Sanamzadeh, M.; Johnson, J. T.; Jezek, K. C.; Durand, M. T. 2017-12-01 The recent development of an ultra-wideband software defined radiometer (UWBRAD) operating over the unprotected spectrum of 0.5 2.0 GHz using radio-frequency interference suppression techniques offers new methodologies for remote sensing of the polar ice sheets, sea ice, and terrestrial snow. The instrument was initially designed for remote sensing of the intragalcial temperature profile of the ice sheet, where a frequency dependent penetration depth yields a frequency dependent brightness temperature (Tb) spectrum that can be linked back to the temperature profile of the ice sheet. The instrument was tested during a short flight over Northwest Greenland in September, 2016. Measurements were successfully made over the different snow facies characteristic of Greenland including the ablation, wet snow and percolation facies, and ended just west of Camp Century during the approach to the dry snow zone. Wide-band emission spectra collected during the flight have been processed and analyzed. Results show that the spectra are highly sensitive to the facies type with scattering from ice lenses being the dominant reason for low Tbs in the percolation zone. Inversion of Tb to physical temperature at depth was conducted on the measurements near Camp Century, achieving a -1.7K ten-meter error compared to borehole measurements. However, there is a relatively large uncertainty in the lower part possibly due to the large scattering near the surface. Wideband radiometry may also be applicable to sea ice and terrestrial snow thickness retrieval. Modeling studies suggest that the UWBRAD spectra reduce ambiguities inherent in other sea ice thickness retrievals by utilizing coherent wave interferences that appear in the Tb spectrum. When applied to a lossless medium such as terrestrial snow, this coherent oscillation turns out to be the single key signature that can be used to link back to snow thickness. In this paper, we report our forward modeling findings in support of instrument </li> <li> <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">About uncertainties in sea ice thickness retrieval from satellite radar altimetry: results from the ESA-CCI Sea Ice ECV Project Round Robin Exercise</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Kern, S.; Khvorostovsky, K.; Skourup, H.; Rinne, E.; Parsakhoo, Z. S.; Djepa, V.; Wadhams, P.; Sandven, S. 2014-03-01 One goal of the European Space Agency Climate Change Initiative sea ice Essential Climate Variable project is to provide a quality controlled 20 year long data set of Arctic Ocean winter-time sea ice thickness distribution. An important step to achieve this goal is to assess the accuracy of sea ice thickness retrieval based on satellite radar altimetry. For this purpose a data base is created comprising sea ice freeboard derived from satellite radar altimetry between 1993 and 2012 and collocated observations of snow and sea ice freeboard from Operation Ice Bridge (OIB) and CryoSat Validation Experiment (CryoVEx) air-borne campaigns, of sea ice 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 ice 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 sea ice draft agrees with the mean sea ice 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 sea ice draft observed by moored ULS satisfactorily. A sensitivity analysis of the freeboard-to-thickness conversion suggests: in order to obtain sea ice thickness as accurate as 0.5 m from radar altimetry, besides a freeboard estimate with centimetre accuracy, an ice-type dependent sea ice density is as mandatory </li> <li> <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">Microwave properties of sea ice in the marginal ice zone</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Onstott, R. G.; Larson, R. W. 1986-01-01 Active microwave properties of summer sea ice 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, ice surface roughness, and deformation characteristics are the fundamental scene parameters which govern the summer sea ice backscatter response. A thick, wet snow cover dominates the backscatter response and masks any ice 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 ice type are not necessarily well understood and produce unique microwave signature characteristics. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.C33A0669O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.C33A0669O">Recent Increases in Snow Accumulation and Decreases in Sea-Ice Concentration Recorded in a Coastal NW Greenland Ice Core</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Osterberg, E. C.; Thompson, J. T.; Wong, G. J.; Hawley, R. L.; Kelly, M. A.; Lutz, E.; Howley, J.; Ferris, D. G. 2013-12-01 A significant rise in summer temperatures over the past several decades has led to widespread retreat of the Greenland Ice Sheet (GIS) margin and surrounding sea ice. Recent observations from geodetic stations and GRACE show that ice mass loss progressed from South Greenland up to Northwest Greenland by 2005 (Khan et al., 2010). Observations from meteorological stations at the U.S. Thule Air Force Base, remote sensing platforms, and climate reanalyses indicate a 3.5C mean annual warming in the Thule region and a 44% decrease in summer (JJAS) sea-ice concentrations in Baffin Bay from 1980-2010. Mean annual precipitation near Thule increased by 12% over this interval, with the majority of the increase occurring in fall (SON). To improve projections of future ice loss and sea-level rise in a warming climate, we are currently developing multi-proxy records (lake sediment cores, ice cores, glacial geologic data, glaciological models) of Holocene climate variability and cryospheric response in NW Greenland, with a focus on past warm periods. As part of our efforts to develop a millennial-length ice core paleoclimate record from the Thule region, we collected and analyzed snow pit samples and short firn cores (up to 20 m) from the coastal region of the GIS (2Barrel site; 76.9317 N, 63.1467 W) and the summit of North Ice Cap (76.938 N, 67.671 W) in 2011 and 2012, respectively. The 2Barrel ice core was sampled using a continuous ice core melting system at Dartmouth, and subsequently analyzed for major anion and trace element concentrations and stable water isotope ratios. Here we show that the 2Barrel ice core spanning 1990-2010 records a 25% increase in mean annual snow accumulation, and is positively correlated (r = 0.52, p<0.01) with ERA-Interim precipitation. The 2Barrel annual sea-salt Na concentration is strongly correlated (r = 0.5-0.8, p<0.05) with summer and fall sea-ice concentrations in northern Baffin Bay near Thule (Figure 1). We hypothesize that the positive </li> <li> <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">[Spectral features analysis of sea ice in the Arctic Ocean].</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Ke, Chang-qing; Xie, Hong-jie; Lei, Rui-bo; Li, Qun; Sun, Bo 2012-04-01 Sea ice 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 sea ice were measured with portable ASD FieldSpec 3 spectrometer during the long-term ice station of the 4th Chinese national Arctic Expedition in 2010, and the spectral features were analyzed systematically. The results indicated that the reflectance of sea ice covered by snow is the highest one, naked sea ice the second, and melted sea ice the lowest. Peak and valley characteristics of spectrum curves of sea ice 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 sea ice, white ice and blue ice are basically same, the reflectance of them is medium, and that of grey ice is far lower than natural sea ice, white ice and blue ice. It is very significant for scientific research to analyze the spectral features of sea ice in the Arctic Ocean and to implement the quantitative remote sensing of sea ice, and to further analyze its response to the global warming. </li> <li> <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">An Investigation of the Radiative Effects and Climate Feedbacks of Sea Ice Sources of Sea Salt Aerosol</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Horowitz, H. M.; Alexander, B.; Bitz, C. M.; Jaegle, L.; Burrows, S. M. 2017-12-01 In polar regions, sea ice is a major source of sea salt aerosol through lofting of saline frost flowers or blowing saline snow from the sea ice surface. Under continued climate warming, an ice-free Arctic in summer with only first-year, more saline sea ice in winter is likely. Previous work has focused on climate impacts in summer from increasing open ocean sea salt aerosol emissions following complete sea ice 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 sea ice sources of sea salt aerosol in a future, warmer climate has not previously been explored. Understanding how sea ice loss affects the Arctic climate system requires investigating both open-ocean and sea ice sources of sea-salt aerosol and their potential interactions. Here, we implement a blowing snow source of sea salt aerosol into the Community Earth System Model (CESM) dynamically coupled to the latest version of the Los Alamos sea ice model (CICE5). Snow salinity is a key parameter affecting blowing snow sea salt emissions and previous work has assumed constant regional snow salinity over sea ice. We develop a parameterization for dynamic snow salinity in the sea ice model and examine how its spatial and temporal variability impacts the production of sea salt from blowing snow. We evaluate and constrain the snow salinity parameterization using available observations. Present-day coupled CESM-CICE5 simulations of sea salt aerosol concentrations including sea ice 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 sea salt aerosol with respect to aerosol-radiation and aerosol-cloud interactions. The relative contributions of sea ice vs. open ocean sources of sea salt aerosol to radiative forcing in polar regions is </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018E%26SS....5...30G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018E%26SS....5...30G">High Angular Resolution Measurements of the Anisotropy of Reflectance of Sea Ice and Snow</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Goyens, C.; Marty, S.; Leymarie, E.; Antoine, D.; Babin, M.; Bélanger, S. 2018-01-01 We introduce a new method to determine the anisotropy of reflectance of sea ice and snow at spatial scales from 1 m2 to 80 m2 using a multispectral circular fish-eye radiance camera (CE600). The CE600 allows measuring radiance simultaneously in all directions of a hemisphere at a 1° angular resolution. The spectral characteristics of the reflectance and its dependency on illumination conditions obtained from the camera are compared to those obtained with a hyperspectral field spectroradiometer manufactured by Analytical Spectral Device, Inc. (ASD). Results confirm the potential of the CE600, with the suggested measurement setup and data processing, to measure commensurable sea ice and snow hemispherical-directional reflectance factor, HDRF, values. Compared to the ASD, the reflectance anisotropy measured with the CE600 provides much higher resolution in terms of directional reflectance (N = 16,020). The hyperangular resolution allows detecting features that were overlooked using the ASD due to its limited number of measurement angles (N = 25). This data set of HDRF further documents variations in the anisotropy of the reflectance of snow and ice with the geometry of observation and illumination conditions and its spectral and spatial scale dependency. Finally, in order to reproduce the hyperangular CE600 reflectance measurements over the entire 400-900 nm spectral range, a regression-based method is proposed to combine the ASD and CE600 measurements. Results confirm that both instruments may be used in synergy to construct a hyperangular and hyperspectral snow and ice reflectance anisotropy data set. </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">4</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> </div> </div> <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">5</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> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19800047931&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=19800047931&hterms=sea+ice+albedo&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dsea%2Bice%2Balbedo">The seasonal cycle of snow cover, sea ice and surface albedo</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Robock, A. 1980-01-01 The paper examines satellite data used to construct mean snow cover caps for the Northern Hemisphere. The zonally averaged snow cover from these maps is used to calculate the seasonal cycle of zonally averaged surface albedo. The effects of meltwater on the surface, solar zenith angle, and cloudiness are parameterized and included in the calculations of snow and ice albedo. The data allows a calculation of surface albedo for any land or ocean 10 deg latitude band as a function of surface temperature ice and snow cover; the correct determination of the ice boundary is more important than the snow boundary for accurately simulating the ice and snow albedo feedback. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C33C1218T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C33C1218T">Measurement of spectral sea ice albedo at Qaanaaq fjord in northwest Greenland</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Tanikawa, T. 2017-12-01 The spectral albedos of sea ice were measured at Qaanaaq fjord in northwest Greenland. Spectral measurements were conducted for sea ice covered with snow and sea ice without snow where snow was artificially removed around measurement point. Thickness of the sea ice was approximately 1.3 m with 5 cm of snow over the sea ice. The measurements show that the spectral albedos of the sea ice 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 sea ice under the snow. The spectral albedos of the sea ice 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 sea ice. In contrast, in the near-infrared and shortwave infrared wavelengths, surface reflection at the sea ice surface would be dominant. Since a light absorption by the ice in these regions is relatively strong comparing to the visible region, the light could not be penetrated deeply within the sea ice, 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C21G1192Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C21G1192Z">Under Sea Ice phytoplankton bloom detection and contamination in Antarctica</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Zeng, C.; Zeng, T.; Xu, H. 2017-12-01 Previous researches reported compelling sea ice phytoplankton bloom in Arctic, while seldom reports studied about Antarctic. Here, lab experiment showed sea ice increased the visible light albedo of the water leaving radiance. Even a new formed sea ice 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 sea ice 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 sea ice. Going further, varying thickness of sea ice modulated the changing rate of estimating [Chl-a] non-linearly, thus current routine OC4 model cannot estimate under sea ice [Chl-a] appropriately. Besides, marginal sea ice zone has a large amount of mixture regions containing sea ice, water and snow, where is favorable for phytoplankton. We applied 6S model to estimate the sea ice/snow contamination on sub-pixel water leaving radiance of 4.25km spatial resolution ocean color products. Results showed that sea ice/snow scale effectiveness overestimated [Chl-a] concentration based on routine band ratio OC4 model, which contamination increased with the rising fraction of sea ice/snow within one pixel. Finally, we analyzed the under sea ice bloom in Antarctica based on the [Chl-a] concentration trends during 21 days after sea ice retreating. Regardless of those overestimation caused by sea ice/snow sub scale contamination, we still did not see significant under sea ice blooms in Antarctica in 2012-2017 compared with Arctic. This research found that Southern Ocean is not favorable for under sea ice blooms and the phytoplankton bloom preferred to occur in at least 3 weeks after sea ice retreating. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018JGRC..123.1907W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018JGRC..123.1907W">Estimation of Antarctic Land-Fast Sea Ice Algal Biomass and Snow Thickness From Under-Ice Radiance Spectra in Two Contrasting Areas</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Wongpan, P.; Meiners, K. M.; Langhorne, P. J.; Heil, P.; Smith, I. J.; Leonard, G. H.; Massom, R. A.; Clementson, L. A.; Haskell, T. G. 2018-03-01 Fast ice is an important component of Antarctic coastal marine ecosystems, providing a prolific habitat for ice algal communities. This work examines the relationships between normalized difference indices (NDI) calculated from under-ice radiance measurements and sea ice algal biomass and snow thickness for Antarctic fast ice. While this technique has been calibrated to assess biomass in Arctic fast ice and pack ice, as well as Antarctic pack ice, relationships are currently lacking for Antarctic fast ice characterized by bottom ice algae communities with high algal biomass. We analyze measurements along transects at two contrasting Antarctic fast ice sites in terms of platelet ice presence: near and distant from an ice shelf, i.e., in McMurdo Sound and off Davis Station, respectively. Snow and ice thickness, and ice salinity and temperature measurements support our paired in situ optical and biological measurements. Analyses show that NDI wavelength pairs near the first chlorophyll a (chl a) absorption peak (≈440 nm) explain up to 70% of the total variability in algal biomass. Eighty-eight percent of snow thickness variability is explained using an NDI with a wavelength pair of 648 and 567 nm. Accounting for pigment packaging effects by including the ratio of chl a-specific absorption coefficients improved the NDI-based algal biomass estimation only slightly. Our new observation-based algorithms can be used to estimate Antarctic fast ice algal biomass and snow thickness noninvasively, for example, by using moored sensors (time series) or mapping their spatial distributions using underwater vehicles. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.osti.gov/sciencecinema/biblio/987230','SCIGOVIMAGE-SCICINEMA'); return false;" href="http://www.osti.gov/sciencecinema/biblio/987230">The Role of Snow and Ice in the Climate System</a> <a target="_blank" href="http://www.osti.gov/sciencecinema/">ScienceCinema</a> Barry, Roger G. 2017-12-09 Global snow and ice cover (the 'cryosphere') plays a major role in global climate and hydrology through a range of complex interactions and feedbacks, the best known of which is the ice - albedo feedback. Snow and ice cover undergo marked seasonal and long term changes in extent and thickness. The perennial elements - the major ice sheets and permafrost - play a role in present-day regional and local climate and hydrology, but the large seasonal variations in snow cover and sea ice are of importance on continental to hemispheric scales. The characteristics of these variations, especially in the Northern Hemisphere, and evidence for recent trends in snow and ice extent are discussed. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20000021334','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20000021334">Airborne Spectral Measurements of Surface-Atmosphere Anisotropy for Arctic Sea Ice and Tundra</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Arnold, G. Thomas; Tsay, Si-Chee; King, Michael D.; Li, Jason Y.; Soulen, Peter F. 1999-01-01 Angular distributions of spectral reflectance for four common arctic surfaces: snow-covered sea ice, melt-season sea ice, snow-covered tundra, and tundra shortly after snowmelt were measured using an aircraft based, high angular resolution (1-degree) multispectral radiometer. Results indicate bidirectional reflectance is higher for snow-covered sea ice than melt-season sea ice at all wavelengths between 0.47 and 2.3 pm, with the difference increasing with wavelength. Bidirectional reflectance of snow-covered tundra is higher than for snow-free tundra for measurements less than 1.64 pm, with the difference decreasing with wavelength. Bidirectional reflectance patterns of all measured surfaces show maximum reflectance in the forward scattering direction of the principal plane, with identifiable specular reflection for the melt-season sea ice and snow-free tundra cases. The snow-free tundra had the most significant backscatter, and the melt-season sea ice the least. For sea ice, bidirectional reflectance changes due to snowmelt were more significant than differences among the different types of melt-season sea ice. Also the spectral-hemispherical (plane) albedo of each measured arctic surface was computed. Comparing measured nadir reflectance to albedo for sea ice and snow-covered tundra shows albedo underestimated 5-40%, with the largest bias at wavelengths beyond 1 pm. For snow-free tundra, nadir reflectance underestimates plane albedo by about 30-50%. </li> <li> <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">C-Band Backscatter Measurements of Winter Sea-Ice in the Weddell Sea, Antarctica</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Drinkwater, M. R.; Hosseinmostafa, R.; Gogineni, P. 1995-01-01 During the 1992 Winter Weddell Gyre Study, a C-band scatterometer was used from the German ice-breaker R/V Polarstern to obtain detailed shipborne measurement scans of Antarctic sea-ice. 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 ice types as the icebreaker crossed the Weddell Sea and detailed measurements were made of corresponding snow and sea-ice 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/ice interfaces. Observations indicate so e similarities with Arctic sea-ice scattering signatures, although the main difference is generally lower mean backscattering coefficients in the Weddell Sea. This is due to the younger mean ice age and thickness, and correspondingly higher mean salinities. In particular, smooth white ice found in 1992 in divergent areas within the Weddell Gyre ice 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 ice forms do not produce as distinctively different scattering signatures as observed in the Arctic. Thick deformed first-year and second-year ice on the other hand are clearly discriminated from younger undeformed ice. thereby allowing successful separation of thick and thin ice. Time-series data also indicate that C-band is sensitive to changes in snow and ice 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018JGRC..123.1586G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018JGRC..123.1586G">Atmosphere-Ice-Ocean-Ecosystem Processes in a Thinner Arctic Sea Ice Regime: The Norwegian Young Sea ICE (N-ICE2015) Expedition</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19930066535&hterms=sea+ice+albedo&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dsea%2Bice%2Balbedo','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19930066535&hterms=sea+ice+albedo&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dsea%2Bice%2Balbedo">Operational satellites and the global monitoring of snow and ice</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Walsh, John E. 1991-01-01 The altitudinal dependence of the global warming projected by global climate models is at least partially attributable to the albedo-temperature feedback involving snow and ice, which must be regarded as key variables in the monitoring for global change. Statistical analyses of data from IR and microwave sensors monitoring the areal coverage and extent of sea ice have led to mixed conclusions about recent trends of hemisphere sea ice coverage. Seasonal snow cover has been mapped for over 20 years by NOAA/NESDIS on the basis of imagery from a variety of satellite sensors. Multichannel passive microwave data show some promise for the routine monitoring of snow depth over unforested land areas. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.C22A..04T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.C22A..04T">Spatially-resolved mean flow and turbulence help explain observed erosion and deposition patterns of snow over Antarctic sea ice</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Trujillo, E.; Giometto, M. G.; Leonard, K. C.; Maksym, T. L.; Meneveau, C. V.; Parlange, M. B.; Lehning, M. 2014-12-01 Sea ice-atmosphere interactions are major drivers of patterns of sea ice drift and deformations in the Polar regions, and affect snow erosion and deposition at the surface. Here, we combine analyses of sea ice surface topography at very high-resolutions (1-10 cm), and Large Eddy Simulations (LES) to study surface drag and snow erosion and deposition patterns from process scales to floe scales (1 cm - 100 m). The snow/ice elevations were obtained using a Terrestrial Laser Scanner during the SIPEX II (Sea Ice Physics and Ecosystem eXperiment II) research voyage to East Antarctica (September-November 2012). LES are performed on a regular domain adopting a mixed pseudo-spectral/finite difference spatial discretization. A scale-dependent dynamic subgrid-scale model based on Lagrangian time averaging is adopted to determine the eddy-viscosity in the bulk of the flow. Effects of larger-scale features of the surface on wind flows (those features that can be resolved in the LES) are accounted for through an immersed boundary method. Conversely, drag forces caused by subgrid-scale features of the surface should be accounted for through a parameterization. However, the effective aerodynamic roughness parameter z0 for snow/ice is not known. Hence, a novel dynamic approach is utilized, in which z0 is determined using the constraint that the total momentum flux (drag) must be independent on grid-filter scale. We focus on three ice floe surfaces. The first of these surfaces (October 6, 2012) is used to test the performance of the model, validate the algorithm, and study the spatial distributed fields of resolved and modeled stress components. The following two surfaces, scanned at the same location before and after a snow storm event (October 20/23, 2012), are used to propose an application to study how spatially resolved mean flow and turbulence relates to observed patterns of snow erosion and deposition. We show how erosion and deposition patterns are correlated with the </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19970015273','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19970015273">Estimating the Thickness of Sea Ice Snow Cover in the Weddell Sea from Passive Microwave Brightness Temperatures</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Arrigo, K. R.; vanDijken, G. L.; Comiso, J. C. 1996-01-01 Passive microwave satellite observations have frequently been used to observe changes in sea ice cover and concentration. Comiso et al. showed that there may also be a direct relationship between the thickness of snow cover (h(sub s)) on ice and microwave emissivity at 90 GHz. Because the in situ experiment of experiment of Comiso et al. was limited to a single station, the relationship is re-examined in this paper in a more general context and using more extensive in situ microwave observations and measurements of h from the Weddell Sea 1986 and 1989 winter cruises. Good relationships were found to exist between h(sub s) sand the emissivity at 90 GHz - 10 GHz and the emissivity at 90 GHz - 18.7 GHz when the standard deviation of h(sub s) was less than 50% of the mean and when h(sub s) was less than 0.25 m. The reliance of these relationships on h(sub s) is most likely caused by the limited penetration through the snow of radiation at 90 GHz. When the algorithm was applied to the Special Sensor Microwave/Imager (SSM/I) satellite data from the Weddell Sea, the resulting mean h(sub s) agreed within 5% of the mean calculated from greater than 1400 in situ observations. </li> <li> <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">Seasonal Changes of Arctic Sea Ice Physical Properties Observed During N-ICE2015: An Overview</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. 2015-12-01 Arctic sea ice is changing, and for improving the understanding of the cryosphere, data is needed to describe the status and processes controlling current seasonal sea ice growth, change and decay. We present preliminary results from in-situ observations on sea ice 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 ice floes, drifting with the sea ice and allowing an international group of scientists to conduct detailed research. Each drift lasted until the ship reached the marginal ice zone and ice 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 sea ice system, and in the ocean, as well as biological studies, in this presentation we focus on physics of snow and sea ice. Different ice types could be investigated: young ice in refrozen leads, first year ice, and old ice. Snow surveys included regular snow pits with standardized measurements of physical properties and sampling. Snow and ice thickness were measured at stake fields, along transects with electromagnetics, and in drillholes. For quantifying ice physical properties and texture, ice cores were obtained regularly and analyzed. Optical properties of snow and ice 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 (ice 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C41D0750F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C41D0750F">MODIS Collection 6 Data at the National Snow and Ice Data Center (NSIDC)</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Fowler, D. K.; Steiker, A. E.; Johnston, T.; Haran, T. M.; Fowler, C.; Wyatt, P. 2015-12-01 For over 15 years, the NASA National Snow and Ice Data Center Distributed Active Archive Center (NSIDC DAAC) has archived and distributed snow and sea ice products derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on the NASA Earth Observing System (EOS) Aqua and Terra satellites. Collection 6 represents the next revision to NSIDC's MODIS archive, mainly affecting the snow-cover products. Collection 6 specifically addresses the needs of the MODIS science community by targeting the scenarios that have historically confounded snow detection and introduced errors into the snow-cover and fractional snow-cover maps even though MODIS snow-cover maps are typically 90 percent accurate or better under good observing conditions, Collection 6 uses revised algorithms to discriminate between snow and clouds, resolve uncertainties along the edges of snow-covered regions, and detect summer snow cover in mountains. Furthermore, Collection 6 applies modified and additional snow detection screens and new Quality Assessment protocols that enhance the overall accuracy of the snow maps compared with Collection 5. Collection 6 also introduces several new MODIS snow products, including a daily Climate Modelling Grid (CMG) cloud gap-filled (CGF) snow-cover map which generates cloud-free maps by using the most recent clear observations.. The MODIS Collection 6 sea ice extent and ice surface temperature algorithms and products are much the same as Collection 5; however, Collection 6 updates to algorithm inputs—in particular, the L1B calibrated radiances, land and water mask, and cloud mask products—have improved the sea ice outputs. The MODIS sea ice products are currently available at NSIDC, and the snow cover products are soon to follow in 2016 NSIDC offers a variety of methods for obtaining these data. Users can download data directly from an online archive or use the NASA Reverb Search & Order Tool to perform spatial, temporal, and parameter </li> <li> <a target="_blank" onclick="trackOutboundLink('http://nsidc.org','SCIGOVWS'); return false;" href="http://nsidc.org">National Snow and Ice Data Center |</a> <a target="_blank" href="http://www.science.gov/aboutsearch.html">Science.gov Websites</a> Temperature Glaciers Ice Sheets Permafrost Sea Ice Soil Moisture Snow ...search for more Scientific Data Web pages Data Sets Drought on the range Drought on the range Using satellite soil moisture data as a tool for drought monitoring. Read more ... SMAP Soil Moisture Active Passive Data (SMAP) NASA SMAP data </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C53B0779H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C53B0779H">The Operation IceBridge Sea Ice Freeboard, Snow Septh and Thickness Product: An In-Depth Look at Past, Current and Future Versions</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Harbeck, J.; Kurtz, N. T.; Studinger, M.; Onana, V.; Yi, D. 2015-12-01 The NASA Operation IceBridge Project Science Office has recently released an updated version of the sea ice freeboard, snow depth and thickness product (IDCSI4). This product is generated through the combination of multiple IceBridge instrument data, primarily the ATM laser altimeter, DMS georeferenced imagery and the CReSIS snow radar, and is available on a campaign-specific basis as all upstream data sets become available. Version 1 data (IDCSI2) was the initial data production; we have subsequently received community feedback that has now been incorporated, allowing us to provide an improved data product. All data now available to the public at the National Snow and Ice Data Center (NSIDC) have been homogeneously reprocessed using the new IDCSI4 algorithm. This algorithm contains significant upgrades that improve the quality and consistency of the dataset, including updated atmospheric and oceanic tidal models and replacement of the geoid with a more representative mean sea surface height product. Known errors with the IDCSI2 algorithm, identified by the Project Science Office as well as feedback from the scientific community, have been incorporated into the new algorithm as well. We will describe in detail the various steps of the IDCSI4 algorithm, show the improvements made over the IDCSI2 dataset and their beneficial impact and discuss future upgrades planned for the next version. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA617899','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA617899">An Innovative Network to Improve Sea Ice Prediction in a Changing Arctic</a> <a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a> 2014-09-30 sea ice volume. The EXP ensemble is initialized with 1/5 of CNTL snow depths, thus resulting in a reduced snow cover and lower summer albedo ... Sea Ice - Albedo Feedback in Sea Ice Predictions is also about understanding sea ice predictability. REFERENCES Blanchard-Wrigglesworth, E., K...1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. An Innovative Network to Improve Sea Ice Prediction </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C33B0777R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C33B0777R">Relationship between RADARSAT-2 Derived Snow Thickness on Winter First Year Sea-Ice and Aerial Melt-Pond Distribution using Geostatistics and GLCM Texture</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Ramjan, S.; Geldsetzer, T.; Yackel, J. 2016-12-01 A contemporary shift from primarily thicker, older multi-year sea ice (MYI) to thinner, smoother first-year sea ice (FYI) has been attributed to increased atmospheric and oceanic warming in the Arctic, with a steady diminishing of Arctic sea ice thickness due to a reduction of thick MYI compared to FYI. With an increase in FYI fraction, increased melting takes place during the summer months, exposing the sea ice to additional incoming solar radiation. With this change, an increase in melt pond fraction has been observed during the summer melt season. Prior research advocated that thin/thick snow leads to dominant surface flooding/snow patches during summer because of an enhanced ice-albedo feedback. For instance, thin snow cover areas form melt ponds first. Therefore, aerial measurements of melt pond fraction provide a proxy for relative snow thickness. RADARSAT-2 polarimetric SAR data can provide enhanced information about both surface scattering and volume scattering mechanisms, as well as recording the phase difference between polarizations. These polarimetric parameters can be computed that have a useful physical interpretation. The principle research focus is to establish a methodology to determine the relationship between selected geostatistics and image texture measures of pre-melt RADARSAT-2 parameters and aerially-measured melt pond fraction. Overall, the notion of this study is to develop an algorithm to estimate relative snow thickness variability in winter through an integrated approach utilizing SAR polarimetric parameters, geostatistical analysis and texture measures. Results are validated with test sets of melt pond fractions, and in situ snow thickness measurements. Preliminary findings show significant correlations with pond fraction for the standard deviation of HH and HV parameters at small incidence angles, and for the mean of the co-pol phase difference parameter at large incidence angles. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19940026115','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19940026115">The role of sea ice dynamics in global climate change</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Hibler, William D., III 1992-01-01 The topics covered include the following: general characteristics of sea ice drift; sea ice rheology; ice thickness distribution; sea ice thermodynamic models; equilibrium thermodynamic models; effect of internal brine pockets and snow cover; model simulations of Arctic Sea ice; and sensitivity of sea ice models to climate change. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20040085502','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20040085502">Interannual Variability of Snow and Ice and Impact on the Carbon Cycle</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Yung, Yuk L. 2004-01-01 The goal of this research is to assess the impact of the interannual variability in snow/ice using global satellite data sets acquired in the last two decades. This variability will be used as input to simulate the CO2 interannual variability at high latitudes using a biospheric model. The progress in the past few years is summarized as follows: 1) Albedo decrease related to spring snow retreat; 2) Observed effects of interannual summertime sea ice variations on the polar reflectance; 3) The Northern Annular Mode response to Arctic sea ice loss and the sensitivity of troposphere-stratosphere interaction; 4) The effect of Arctic warming and sea ice loss on the growing season in northern terrestrial ecosystem. </li> <li> <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">Influence of Sea Ice Crack Formation on the Spatial Distribution of Nutrients and Microalgae in Flooded Antarctic Multiyear Ice</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Nomura, Daiki; Aoki, Shigeru; Simizu, Daisuke; Iida, Takahiro 2018-02-01 Cracks are common and natural features of sea ice formed in the polar oceans. In this study, a sea ice crack in flooded, multiyear, land-fast Antarctic sea ice was examined to assess its influence on biological productivity and the transport of nutrients and microalgae into the upper layers of neighboring sea ice. The water inside the crack and the surrounding host ice 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-ice interface) revealed the intrusion of water from the crack, likely forced by mixing with underlying seawater during the tidal cycle. Our results suggest that sea ice crack formation provides conditions favorable for algal blooms by directly exposing the crack water to sunlight and supplying nutrients from the under-ice water. Subsequently, constituents of the crack water modified by biological activity were transported into the upper layer of the flooded sea ice. They were then preserved in the multiyear ice column formed by upward growth of sea ice caused by snow ice formation in areas of significant snow accumulation. </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">5</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> <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">6</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> <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">Measurements of sea ice mass redistribution during ice deformation event in Arctic winter</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Itkin, P.; Spreen, G.; King, J.; Rösel, A.; Skourup, H.; Munk Hvidegaard, S.; Wilkinson, J.; Oikkonen, A.; Granskog, M. A.; Gerland, S. 2016-12-01 Sea-ice growth during high winter is governed by ice dynamics. The highest growth rates are found in leads that open under divergent conditions, where exposure to the cold atmosphere promotes thermodynamic growth. Additionally ice thickens dynamically, where convergence causes rafting and ridging. We present a local study of sea-ice growth and mass redistribution between two consecutive airborne measurements, on 19 and 24 April 2015, during the N-ICE2015 expedition in the area north of Svalbard. Between the two overflights an ice deformation event was observed. Airborne laser scanner (ALS) measurements revisited the same sea-ice area of approximately 3x3 km. By identifying the sea surface within the ALS measurements as a reference the sea ice 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 ice thickness. The snow depth is estimated from in-situ measurements. Sea ice 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 sea-ice 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 ice classes and an increase of the thick ice classes. While there was no observable snowfall and a very low sea-ice growth of older level ice 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 sea ice deformation with the associated sea-ice 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70186594','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70186594">Diminishing sea ice in the western Arctic Ocean</a> <a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Stone, R.S.; Belchansky, G.I.; Drobot, Sheldon; Douglas, David C.; Levinson, D.H.; Waple, A.M. 2004-01-01 Since the advent of satellite passive microwave radiometry (1978), variations in sea ice extent and concentration have been carefully monitored from space. An estimated 7.4% decrease in sea ice 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 sea ice melt dynamics and snowmelt dates at the NOAA–CMDL Barrow Observatory (BRW) reveal intriguing correlations.Melt-onset dates over sea ice (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 sea ice and the BRW record of melt dates was approximately aligned with the climatological center of the Beaufort Sea Anticyclone (BSA). The BSA induces anticyclonic ice motion in the region, effectively forcing the Beaufort gyre. A weak gyre caused by a breakdown of the BSA diminishes transport of multiyear ice 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 ice 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 ice in the western Arctic Ocean. </li> <li> <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">Online sea ice data platform: www.seaiceportal.de</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 2016-04-01 There is an increasing public interest in sea ice 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 sea ice 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 sea ice and its snow cover. The data sets result from measurements acquired by various platforms as well as numerical simulations. Satellite observations of sea ice concentration, freeboard, thickness and drift are available as gridded data sets. Sea ice and snow temperatures and thickness as well as atmospheric parameters are available from autonomous platforms (buoys). Additional ship observations, ice 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 sea ice 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMED41A0831H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMED41A0831H">Use of Unmanned Aircraft Systems in Observations of Glaciers, Ice Sheets, Sea Ice and Snow Fields</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Herzfeld Mayer, M. U. 2015-12-01 Unmanned Aircraft Systems (UAS) are being used increasingly in observations of the Earth, especially as such UAS become smaller, lighter and hence less expensive. In this paper, we present examples of observations of snow fields, glaciers and ice sheets and of sea ice in the Arctic that have been collected from UAS. We further examine possibilities for instrument miniaturization, using smaller UAS and smaller sensors for collecting data. The quality and type of data is compared to that of satellite observations, observations from manned aircraft and to measurements made during field experiments on the ground. For example, a small UAS can be sent out to observe a sudden event, such as a natural catastrophe, and provide high-resolution imagery, but a satellite has the advantage of providing the same type of data over much of the Earth's surface and for several years, but the data is generally of lower resolution. Data collected on the ground typically have the best control and quality, but the survey area is usually small. Here we compare micro-topographic measurements made on snow fields the Colorado Rocky Mountains with airborne and satellite data. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19930063976&hterms=1535&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3D1535','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19930063976&hterms=1535&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3D1535">Comparison of radar backscatter from Antarctic and Arctic sea ice</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Hosseinmostafa, R.; Lytle, V. 1992-01-01 Two ship-based step-frequency radars, one at C-band (5.3 GHz) and one at Ku-band (13.9 GHz), measured backscatter from ice in the Weddell Sea. Most of the backscatter data were from first-year (FY) and second-year (SY) ice at the ice stations where the ship was stationary and detailed snow and ice characterizations were performed. The presence of a slush layer at the snow-ice interface masks the distinction between FY and SY ice in the Weddell Sea, whereas in the Arctic the separation is quite distinct. The effect of snow-covered ice on backscattering coefficients (sigma0) from the Weddell Sea region indicates that surface scattering is the dominant factor. Measured sigma0 values were compared with Kirchhoff and regression-analysis models. The Weibull power-density function was used to fit the measured backscattering coefficients at 45 deg. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C23B0776Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C23B0776Z">Relating C-band Microwave and Optical Satellite Observations as A Function of Snow Thickness on First-Year Sea Ice during the Winter to Summer Transition</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Zheng, J.; Yackel, J. 2015-12-01 The Arctic sea ice and its snow cover have a direct impact on both the Arctic and global climate system through their ability to moderate heat exchange across the ocean-sea ice-atmosphere (OSA) interface. Snow cover plays a key role in the OSA interface radiation and energy exchange, as it controls the growth and decay of first-year sea ice (FYI). However, meteoric accumulation and redistribution of snow on FYI is highly stochastic over space and time, which makes it poorly understood. Previous studies have estimated local-scale snow thickness distributions using in-situ technique and modelling but it is spatially limited and challenging due to logistic difficulties. Moreover, snow albedo is also critical for determining the surface energy balance of the OSA during the critical summer ablation season. Even then, due to persistent and widespread cloud cover in the Arctic at various spatio-temporal scales, it is difficult and unreliable to remotely measure albedo of snow cover on FYI in the optical spectrum. Previous studies demonstrate that only large-scale sea ice albedo was successfully estimated using optical-satellite sensors. However, space-borne microwave sensors, with their capability of all-weather and 24-hour imaging, can provide enhanced information about snow cover on FYI. Daily spaceborne C-band scatterometer data (ASCAT) and MODIS data are used to investigate the the seasonal co-evolution of the microwave backscatter coefficient and optical albedo as a function of snow thickness on smooth FYI. The research focuses on snow-covered FYI near Cambridge Bay, Nunavut (Fig.1) during the winter to advanced-melt period (April-June, 2014). The ACSAT time series (Fig.2) show distinct increase in scattering at melt onset indicating the first occurrence of melt water in the snow cover. The corresponding albedo exhibits no decrease at this stage. We show how the standard deviation of ASCAT backscatter on FYI during winter can be used as a proxy for surface roughness </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C51E..03M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C51E..03M">Ice shelf snow accumulation rates from the Amundsen-Bellingshausen Sea sector of West Antarctica derived from airborne radar</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Medley, B.; Kurtz, N. T.; Brunt, K. M. 2015-12-01 The large ice shelves surrounding the Antarctic continent buttress inland ice, limiting the grounded ice-sheet flow. Many, but not all, of the thick ice shelves located along the Amundsen-Bellingshausen Seas are experiencing rapid thinning due to enhanced basal melting driven by the intrusion of warm circumpolar deep water. Determination of their mass balance provides an indicator as to the future of the shelves buttressing capability; however, measurements of surface accumulation are few, limiting the precision of the mass balance estimates. Here, we present new radar-derived measurements of snow accumulation primarily over the Getz and Abbott Ice Shelves, as well as the Dotson and Crosson, which have been the focus of several of NASA's Operation IceBridge airborne surveys between 2009 and 2014. Specifically, we use the Center for Remote Sensing of Ice Sheets (CReSIS) snow radar to map the near-surface (< 30 m) internal stratigraphy to measure snow accumulation. Due to the complexities of the local topography (e.g., ice rises and rumples) and their relative proximity to the ocean, the spatial pattern of accumulation can be equally varied. Therefore, atmospheric models might not be able to reproduce these small-scale features because of their limited spatial resolution. To evaluate whether this is the case over these narrow shelves, we will compare the radar-derived accumulation rates with those from atmospheric models. </li> <li> <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">Pan-Arctic sea ice-algal chl a biomass and suitable habitat are largely underestimated for multiyear ice.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> 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 2017-11-01 There is mounting evidence that multiyear ice (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 sea ice algae on a pan-Arctic scale. We sampled sea ice cores from MYI and first-year sea ice (FYI) within the Lincoln Sea 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 ice-algal biomass and represent a reliable ice-algal habitat due to the (quasi-) permanent low-snow surface of these features. We identified an ice-algal habitat threshold value for calculated light transmittance of 0.014%. Ice classes and coverage of suitable ice-algal habitat were determined from snow and ice surveys. These ice classes and associated coverage of suitable habitat were applied to pan-Arctic CryoSat-2 snow and ice thickness data products. This habitat classification accounted for the variability of the snow and ice properties and showed an areal coverage of suitable ice-algal habitat within the MYI-covered region of 0.54 million km 2 (8.5% of total ice area). This is 27 times greater than the areal coverage of 0.02 million km 2 (0.3% of total ice 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 ice conditions in all sea ice studies. Furthermore, our results indicate the loss of MYI will also mean the loss of reliable ice-algal habitat during spring when food is sparse and many organisms depend on ice-algae. © 2017 The Authors. Global Change Biology Published by John Wiley & Sons Ltd. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140017663','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140017663">An AeroCom Assessment of Black Carbon in Arctic Snow and Sea Ice</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Jiao, C.; Flanner, M. G.; Balkanski, Y.; Bauer, S. E.; Bellouin, N.; Bernsten, T. K.; Bian, H.; Carslaw, K. S.; Chin, M.; DeLuca, N.; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_20140017663'); toggleEditAbsImage('author_20140017663_show'); toggleEditAbsImage('author_20140017663_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_20140017663_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_20140017663_hide"> 2014-01-01 Though many global aerosols models prognose surface deposition, only a few models have been used to directly simulate the radiative effect from black carbon (BC) deposition to snow and sea ice. Here, we apply aerosol deposition fields from 25 models contributing to two phases of the Aerosol Comparisons between Observations and Models (AeroCom) project to simulate and evaluate within-snow BC concentrations and radiative effect in the Arctic. We accomplish this by driving the offline land and sea ice components of the Community Earth System Model with different deposition fields and meteorological conditions from 2004 to 2009, during which an extensive field campaign of BC measurements in Arctic snow occurred. We find that models generally underestimate BC concentrations in snow in northern Russia and Norway, while overestimating BC amounts elsewhere in the Arctic. Although simulated BC distributions in snow are poorly correlated with measurements, mean values are reasonable. The multi-model mean (range) bias in BC concentrations, sampled over the same grid cells, snow depths, and months of measurements, are -4.4 (-13.2 to +10.7) ng/g for an earlier phase of AeroCom models (phase I), and +4.1 (-13.0 to +21.4) ng/g for a more recent phase of AeroCom models (phase II), compared to the observational mean of 19.2 ng/g. Factors determining model BC concentrations in Arctic snow include Arctic BC emissions, transport of extra-Arctic aerosols, precipitation, deposition efficiency of aerosols within the Arctic, and meltwater removal of particles in snow. Sensitivity studies show that the model-measurement evaluation is only weakly affected by meltwater scavenging efficiency because most measurements were conducted in non-melting snow. The Arctic (60-90degN) atmospheric residence time for BC in phase II models ranges from 3.7 to 23.2 days, implying large inter-model variation in local BC deposition efficiency. Combined with the fact that most Arctic BC deposition originates </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/biblio/1124032-aerocom-assessment-black-carbon-arctic-snow-sea-ice','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1124032-aerocom-assessment-black-carbon-arctic-snow-sea-ice">An AeroCom assessment of black carbon in Arctic snow and sea ice</a> <a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Jiao, C.; Flanner, M. G.; Balkanski, Y. 2014-01-01 Though many global aerosols models prognose surface deposition, only a few models have been used to directly simulate the radiative effect from black carbon (BC) deposition to snow and sea ice. In this paper, we apply aerosol deposition fields from 25 models contributing to two phases of the Aerosol Comparisons between Observations and Models (AeroCom) project to simulate and evaluate within-snow BC concentrations and radiative effect in the Arctic. We accomplish this by driving the offline land and sea ice components of the Community Earth System Model with different deposition fields and meteorological conditions from 2004 to 2009, during whichmore » an extensive field campaign of BC measurements in Arctic snow occurred. We find that models generally underestimate BC concentrations in snow in northern Russia and Norway, while overestimating BC amounts elsewhere in the Arctic. Although simulated BC distributions in snow are poorly correlated with measurements, mean values are reasonable. The multi-model mean (range) bias in BC concentrations, sampled over the same grid cells, snow depths, and months of measurements, are -4.4 (-13.2 to +10.7) ng g -1 for an earlier phase of AeroCom models (phase I), and +4.1 (-13.0 to +21.4) ng g -1 for a more recent phase of AeroCom models (phase II), compared to the observational mean of 19.2 ng g -1. Factors determining model BC concentrations in Arctic snow include Arctic BC emissions, transport of extra-Arctic aerosols, precipitation, deposition efficiency of aerosols within the Arctic, and meltwater removal of particles in snow. Sensitivity studies show that the model–measurement evaluation is only weakly affected by meltwater scavenging efficiency because most measurements were conducted in non-melting snow. The Arctic (60–90° N) atmospheric residence time for BC in phase II models ranges from 3.7 to 23.2 days, implying large inter-model variation in local BC deposition efficiency. Combined with the fact that most </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20170003145','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20170003145">Antarctic Sea-Ice Freeboard and Estimated Thickness from NASA's ICESat and IceBridge Observations</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Yi, Donghui; Kurtz, Nathan; Harbeck, Jeremy; Manizade, Serdar; Hofton, Michelle; Cornejo, Helen G.; Zwally, H. Jay; Robbins, John 2016-01-01 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. IceBridge 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 Ice Sensor (LVIS) campaigns over the Antarctic sea ice. Freeboard heights are derived from ICESat, ATM and LVIS elevation and waveform data. With nominal densities of snow, water, and sea ice, combined with snow depth data from AMSR-E/AMSR2 passive microwave observation over the southern ocean, sea-ice thickness is derived from the freeboard. Combined with AMSR-E/AMSR2 ice concentration, sea-ice area and volume are also calculated. During the 2003-2009 period, sea-ice freeboard and thickness distributions show clear seasonal variations that reflect the yearly cycle of the growth and decay of the Antarctic pack ice. We found no significant trend of thickness or area for the Antarctic sea ice during the ICESat period. IceBridge sea ice freeboard and thickness data from 2009 to 2011 over the Weddell Sea and Amundsen and Bellingshausen Seas are compared with the ICESat results. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA617621','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA617621">Wave-Ice and Air-Ice-Ocean Interaction During the Chukchi Sea Ice Edge Advance</a> <a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a> 2014-09-30 During cruise CU-B UAF UW Airborne expendable Ice Buoy (AXIB) Ahead, at and inside ice edge Surface meteorology T, SLP ~1 year CU-B UW...Balance (IMB) buoys Inside ice edge w/ >50cm thickness Ice mass balance T in snow-ice-ocean, T, SLP at surface ~1 year WHOI CRREL (SeaState DRI </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.C41E0448B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.C41E0448B">The NRL 2011 Airborne Sea-Ice Thickness Campaign</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Brozena, J. M.; Gardner, J. M.; Liang, R.; Ball, D.; Richter-Menge, J. 2011-12-01 In March of 2011, the US Naval Research Laboratory (NRL) performed a study focused on the estimation of sea-ice thickness from airborne radar, laser and photogrammetric sensors. The study was funded by ONR to take advantage of the Navy's ICEX2011 ice-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 sea-ice 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 ice-camp (see Richter-Menge et al., this session) along which ice and snow thickness were directly measured. Additionally, US Navy submarines collected ice 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 sea ice thickness are calculated assuming local hydrostatic balance, and require the densities of water, ice and snow, snow depth, and freeboard (defined as the elevation of sea ice, plus accumulated snow, above local sea 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 ice thickness are similar to those employed in NASA ICEBRIDGE sea-ice 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1364126','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1364126">CICE, The Los Alamos Sea Ice Model</a> <a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Hunke, Elizabeth; Lipscomb, William; Jones, Philip The Los Alamos sea ice model (CICE) is the result of an effort to develop a computationally efficient sea ice component for a fully coupled atmosphere–land–ocean–ice 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 ice due to vertical conductive, radiative and turbulent fluxes, along with snowfall; an elastic-viscous-plastic model of ice dynamics, which predicts the velocity field of themore » ice pack based on a model of the material strength of the ice; an incremental remapping transport model that describes horizontal advection of the areal concentration, ice and snow volume and other state variables; and a ridging parameterization that transfers ice among thickness categories based on energetic balances and rates of strain. It also includes a biogeochemical model that describes evolution of the ice ecosystem. The CICE sea ice 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 sea ice forecasting in the polar regions and in numerical weather prediction models.« less </li> <li> <a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-GSFC_20171208_Archive_e000769.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-GSFC_20171208_Archive_e000769.html">Sea ice off western Alaska</a> <a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a> 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 </li> <li> <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">Polar Climate: Arctic sea ice</a> <a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Stone, R.S.; Douglas, David C.; Belchansky, G.I.; Drobot, S.D. 2005-01-01 Recent decreases in snow and sea ice cover in the high northern latitudes are among the most notable indicators of climate change. Northern Hemisphere sea ice 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 sea ice extent, which is at the end of the summer melt season and is typically the month with the lowest sea ice 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 sea ice retreat in the Arctic (Stroeve et al. 2005). Some model simulations indicate that ice-free summers will occur in the Arctic by the year 2070 (ACIA 2004). </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/14699053','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/14699053">Soot climate forcing via snow and ice albedos.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Hansen, James; Nazarenko, Larissa 2004-01-13 Plausible estimates for the effect of soot on snow and ice albedos (1.5% in the Arctic and 3% in Northern Hemisphere land areas) yield a climate forcing of +0.3 W/m(2) in the Northern Hemisphere. The "efficacy" of this forcing is approximately 2, i.e., for a given forcing it is twice as effective as CO(2) in altering global surface air temperature. This indirect soot forcing may have contributed to global warming of the past century, including the trend toward early springs in the Northern Hemisphere, thinning Arctic sea ice, and melting land ice and permafrost. If, as we suggest, melting ice and sea level rise define the level of dangerous anthropogenic interference with the climate system, then reducing soot emissions, thus restoring snow albedos to pristine high values, would have the double benefit of reducing global warming and raising the global temperature level at which dangerous anthropogenic interference occurs. However, soot contributions to climate change do not alter the conclusion that anthropogenic greenhouse gases have been the main cause of recent global warming and will be the predominant climate forcing in the future. </li> <li> <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">Remote sensing as a research tool. [sea ice surveillance from aircraft and spacecraft</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Carsey, F. D.; Zwally, H. J. 1986-01-01 The application of aircraft and spacecraft remote sensing techniques to sea ice surveillance is evaluated. The effects of ice in the air-sea-ice system are examined. The measurement principles and characteristics of remote sensing methods for aircraft and spacecraft surveillance of sea ice 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 sea ice surveillance are discussed and examples are provided. Particular attention is placed on the use of microwave data and the relation between ice thickness and sea ice interactions. It is noted that spacecraft and aircraft sensing techniques can successfully measure snow cover; ice thickness; ice type; ice concentration; ice velocity field; ocean temperature; surface wind vector field; and air, snow, and ice surface temperatures. </li> <li> <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">Interactions Between Ice Thickness, Bottom Ice Algae, and Transmitted Spectral Irradiance in the Chukchi Sea</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Arntsen, A. E.; Perovich, D. K.; Polashenski, C.; Stwertka, C. 2015-12-01 The amount of light that penetrates the Arctic sea ice cover impacts sea-ice 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 Sea from May 18 to June 17, 2014 can be primarily attributed to variations in snow depth, ice thickness, and bottom ice 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 ice algae reduced the maximum transmitted irradiance by about 1.5 orders of magnitude when comparing floes of similar snow and ice 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 sea ice in varying time and space may impact new trends in Arctic sea ice extent and the progression of melt. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120012935','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120012935">A Comparison of Snow Depth on Sea Ice Retrievals Using Airborne Altimeters and an AMSR-E Simulator</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Cavalieri, D. J.; Marksu, T.; Ivanoff, A.; Miller, J. A.; Brucker, L.; Sturm, M.; Maslanik, J. A.; Heinrichs, J. F.; Gasiewski, A.; Leuschen, C.; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_20120012935'); toggleEditAbsImage('author_20120012935_show'); toggleEditAbsImage('author_20120012935_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_20120012935_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_20120012935_hide"> 2011-01-01 A comparison of snow depths on sea ice was made using airborne altimeters and an Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) simulator. The data were collected during the March 2006 National Aeronautics and Space Administration (NASA) Arctic field campaign utilizing the NASA P-3B aircraft. The campaign consisted of an initial series of coordinated surface and aircraft measurements over Elson Lagoon, Alaska and adjacent seas followed by a series of large-scale (100 km ? 50 km) coordinated aircraft and AMSR-E snow depth measurements over portions of the Chukchi and Beaufort seas. This paper focuses on the latter part of the campaign. The P-3B aircraft carried the University of Colorado Polarimetric Scanning Radiometer (PSR-A), the NASA Wallops Airborne Topographic Mapper (ATM) lidar altimeter, and the University of Kansas Delay-Doppler (D2P) radar altimeter. The PSR-A was used as an AMSR-E simulator, whereas the ATM and D2P altimeters were used in combination to provide an independent estimate of snow depth. Results of a comparison between the altimeter-derived snow depths and the equivalent AMSR-E snow depths using PSR-A brightness temperatures calibrated relative to AMSR-E are presented. Data collected over a frozen coastal polynya were used to intercalibrate the ATM and D2P altimeters before estimating an altimeter snow depth. Results show that the mean difference between the PSR and altimeter snow depths is -2.4 cm (PSR minus altimeter) with a standard deviation of 7.7 cm. The RMS difference is 8.0 cm. The overall correlation between the two snow depth data sets is 0.59. </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">6</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> <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">7</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> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMPA13A1975T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMPA13A1975T">Guide to Sea Ice Information and Sea Ice Data Online - the Sea Ice Knowledge and Data Platform www.meereisportal.de and www.seaiceportal.de</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. 2016-12-01 The combination of multi-disciplinary sea ice 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: `sea ice' 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 sea ice; 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 sea ice related research. The principle concept of the new knowledge platform is based on three pillars: (1) sea ice 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 sea ice 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 sea ice concentration, freeboard, thickness and drift are available as gridded data sets. Sea ice and snow temperatures and thickness as well as atmospheric parameters are available from autonomous ice-tethered platforms (buoys). Additional ship observations, ice station measurements, and </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19870060019&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=19870060019&hterms=marginal&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dmarginal">Evolution of microwave sea ice signatures during early summer and midsummer in the marginal ice zone</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Onstott, R. G.; Grenfell, T. C.; Matzler, C.; Luther, C. A.; Svendsen, E. A. 1987-01-01 Emissivities at frequencies from 5 to 94 GHz and backscatter at frequencies from 1 to 17 GHz were measured from sea ice in Fram Strait during the marginal Ice Zone Experiment in June and July of 1983 and 1984. The ice observed was primarily multiyear; the remainder, first-year ice, was often deformed. Results from this active and passive microwave study include the description of the evolution of the sea ice during early summer and midsummer; the absorption properties of summer snow; the interrelationship between ice thickness and the state and thickness of snow; and the modulation of the microwave signature, especially at the highest frequencies, by the freezing of the upper few centimeters of the ice. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.4621R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.4621R">State of Arctic Sea Ice North of Svalbard during N-ICE2015</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Rösel, Anja; King, Jennifer; Gerland, Sebastian 2016-04-01 The N-ICE2015 cruise, led by the Norwegian Polar Institute, was a drift experiment with the research vessel R/V Lance from January to June 2015, where the ship started the drift North of Svalbard at 83°14.45' N, 21°31.41' E. The drift was repeated as soon as the vessel drifted free. Altogether, 4 ice stations where installed and the complex ocean-sea ice-atmosphere system was studied with an interdisciplinary Approach. During the N-ICE2015 cruise, extensive ice thickness and snow depth measurements were performed during both, winter and summer conditions. Total ice and snow thickness was measured with ground-based and airborne electromagnetic instruments; snow depth was measured with a GPS snow depth probe. Additionally, ice mass balance and snow buoys were deployed. Snow and ice thickness measurements were performed on repeated transects to quantify the ice growth or loss as well as the snow accumulation and melt rate. Additionally, we collected independent values on surveys to determine the general ice thickness distribution. Average snow depths of 32 cm on first year ice, and 52 cm on multi-year ice were measured in January, the mean snow depth on all ice types even increased until end of March to 49 cm. The average total ice and snow thickness in winter conditions was 1.92 m. During winter we found a small growth rate on multi-year ice of about 15 cm in 2 months, due to above-average snow depths and some extraordinary storm events that came along with mild temperatures. In contrast thereto, we also were able to study new ice formation and thin ice on newly formed leads. In summer conditions an enormous melt rate, mainly driven by a warm Atlantic water inflow in the marginal ice zone, was observed during two ice stations with melt rates of up to 20 cm per 24 hours. To reinforce the local measurements around the ship and to confirm their significance on a larger scale, we compare them to airborne thickness measurements and classified SAR-satellite scenes. The </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015JGRD..12011391D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015JGRD..12011391D">Interannual variations of light-absorbing particles in snow on Arctic sea ice</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Doherty, Sarah J.; Steele, Michael; Rigor, Ignatius; Warren, Stephen G. 2015-11-01 Samples of snow on sea ice were collected in springtime of the 6 years 2008-2013 in the region between Greenland, Ellesmere Island, and the North Pole (82°N -89°N, 0°W-100°W). The meltwater was passed through filters, whose spectral absorption was then measured to determine the separate contributions by black carbon (BC) and other light-absorbing impurities. The median mixing ratio of BC across all years' samples was 4 ± 3 ng g-1, and the median fraction of absorption due to non-BC absorbers was 36 ± 11%. Variances represent both spatial and interannual variability; there was no interannual trend in either variable. The absorption Ångström exponent, however, decreased with latitude, suggesting a transition from dominance by biomass-burning sources in the south to an increased influence by fossil-fuel-burning sources in the north, consistent with earlier measurements of snow in Svalbard and at the North Pole. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C41B0699A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C41B0699A">Impact of weather events on Arctic sea ice albedo evolution</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Arntsen, A. E.; Perovich, D. K.; Polashenski, C.; Stwertka, C. 2015-12-01 Arctic sea ice undergoes a seasonal evolution from cold snow-covered ice to melting snow to bare ice with melt ponds. Associated with this physical evolution is a decrease in the albedo of the ice cover. While the change in albedo is often considered as a steady seasonal decrease, weather events during melt, such as rain or snow, can impact the albedo evolution. Measurements on first year ice in the Chukchi Sea showed a decrease in visible albedo to 0.77 during the onset of melt. New snow from 4 - 6 June halted melting and increased the visible albedo to 0.87. It took 12 days for the albedo to decrease to levels prior to the snowfall. Incident solar radiation is large in June and thus a change in albedo has a large impact on the surface heat budget. The snowfall increased the albedo by 0.1 and reduced the absorbed sunlight from 5 June to 17 June by approximately 32 MJ m-2. The total impact of the snowfall will be even greater, since the delay in albedo reduction will be propagated throughout the entire summer. A rain event would have the opposite impact, increasing solar heat input and accelerating melting. Snow or rain in May or June can impact the summer melt cycle of Arctic sea ice. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.fs.fed.us/pnw/pubs/pnw_gtr950.pdf','USGSPUBS'); return false;" href="https://www.fs.fed.us/pnw/pubs/pnw_gtr950.pdf">Snow and ice: Chapter 3</a> <a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Littell, Jeremy; McAfee, Stephanie A.; O'Neel, Shad; Sass, Louis; Burgess, Evan; Colt, Steve; Clark, Paul; Hayward, Gregory D.; Colt, Steve; McTeague, Monica L.; Hollingsworth, Teresa N. 2017-01-01 Temperature and precipitation are key determinants of snowpack levels. Therefore, climate change is likely to affect the role of snow and ice in the landscapes and hydrology of the Chugach National Forest region.Downscaled climate projections developed by Scenarios Network for Alaska and Arctic Planning (SNAP) are useful for examining projected changes in snow at relatively fine resolution using a variable called “snowday fraction (SDF),” the percentage of days with precipitation falling as snow.We summarized SNAP monthly SDF from five different global climate models for the Chugach region by 500 m elevation bands, and compared historical (1971–2000) and future (2030–2059) SDF. We found that:Snow-day fraction and snow-water equivalent (SWE) are projected to decline most in late autumn (October to November) and at lower elevations.Snow-day fraction is projected to decrease 23 percent (averaged across five climate models) from October to March, between sea level and 500 m. Between sea level and 1000 m, SDF is projected to decrease by 17 percent between October and March.Snow-water equivalent is projected to decrease most in autumn (October and November) and at lower elevations (below 1500 m), an average of -26 percent for the 2030–2059 period compared to 1971– 2000. Averaged across the cool season and the entire domain, SWE is projected to decrease at elevations below 1000 m because of increased temperature, but increase at higher elevations because of increased precipitation.Compared to 1971–2000, the percentage of the landscape that is snowdominant in 2030–2059 is projected to decrease, and the percentage in which rain and snow are co-dominant (transient hydrology) is projected to increase from 27 to 37 percent. Most of this change is at lower elevations.Glaciers on the Chugach National Forest are currently losing about 6 km3 of ice per year; half of this loss comes from Columbia Glacier (Berthier et al. 2010).Over the past decade, almost all </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C21A0651T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C21A0651T">Online Sea Ice Knowledge and Data Platform: www.seaiceportal.de</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Treffeisen, R. E.; Nicolaus, M.; Bartsch, A.; Fritzsch, B.; Grosfeld, K.; Haas, C.; Hendricks, S.; Heygster, G.; Hiller, W.; Krumpen, T.; Melsheimer, C.; Nicolaus, A.; Ricker, R.; Weigelt, M. 2016-12-01 There is an increasing public interest in sea ice 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 sea ice 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 archived data of many key parameters of sea ice 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 sea ice concentration, freeboard, thickness and drift are available as gridded data sets. Sea ice and snow temperatures and thickness as well as atmospheric parameters are available from autonomous ice-tethered platforms (buoys). Additional ship observations, ice 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 sea ice 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 and are open for potential new partners. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A51E2111V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A51E2111V">Toward Surface Mass Balance Modeling over Antarctic Peninsula with Improved Snow/Ice Physics within WRF</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Villamil-Otero, G.; Zhang, J.; Yao, Y. 2017-12-01 The Antarctic Peninsula (AP) has long been the focus of climate change studies due to its rapid environmental changes such as significantly increased glacier melt and retreat, and ice-shelf break-up. Progress has been continuously made in the use of regional modeling to simulate surface mass changes over ice sheets. Most efforts, however, focus on the ice sheets of Greenland with considerable fewer studies in Antarctica. In this study the Weather Research and Forecasting (WRF) model, which has been applied to the Antarctic region for weather modeling, is adopted to capture the past and future surface mass balance changes over AP. In order to enhance the capabilities of WRF model simulating surface mass balance over the ice surface, we implement various ice and snow processes within the WRF and develop a new WRF suite (WRF-Ice). The WRF-Ice includes a thermodynamic ice sheet model that improves the representation of internal melting and refreezing processes and the thermodynamic effects over ice sheet. WRF-Ice also couples a thermodynamic sea ice model to improve the simulation of surface temperature and fluxes over sea ice. Lastly, complex snow processes are also taken into consideration including the implementation of a snowdrift model that takes into account the redistribution of blowing snow as well as the thermodynamic impact of drifting snow sublimation on the lower atmospheric boundary layer. Intensive testing of these ice and snow processes are performed to assess the capability of WRF-Ice in simulating the surface mass balance changes over AP. </li> <li> <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">Temporal dynamics of ikaite in experimental sea ice</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. 2014-08-01 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 sea ice, and it has been suggested that their precipitation may play an important role in air-sea CO2 exchange in ice-covered seas. Little is known, however, of the spatial and temporal dynamics of ikaite in sea ice. Here we present evidence for highly dynamic ikaite precipitation and dissolution in sea ice grown at an outdoor pool of the Sea-ice Environmental Research Facility (SERF) in Manitoba, Canada. During the experiment, ikaite precipitated in sea ice 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 sea ice to warm and ikaite crystals to dissolve. Manual removal of the snow cover allowed the sea ice 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 sea ice increases with decreasing temperature. Thus, varying snow conditions may play a key role in ikaite precipitation and dissolution in sea ice. This could have a major implication for CO2 exchange with the atmosphere and ocean that has not been accounted for previously. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1918364H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1918364H">Sea Ice Mass Balance Buoys (IMBs): First Results from a Data Processing Intercomparison Study</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Hoppmann, Mario; Tiemann, Louisa; Itkin, Polona 2017-04-01 IMBs are autonomous instruments able to continuously monitor the growth and melt of sea ice and its snow cover at a single point on an ice floe. Complementing field expeditions, remote sensing observations and modelling studies, these in-situ data are crucial to assess the mass balance and seasonal evolution of sea ice and snow in the polar oceans. Established subtypes of IMBs combine coarse-resolution temperature profiles through air, snow, ice and ocean with ultrasonic pingers to detect snow accumulation and ice thermodynamic growth. Recent technological advancements enable the use of high-resolution temperature chains, which are also able to identify the surrounding medium through a „heating cycle". The temperature change during this heating cycle provides additional information on the internal properties and processes of the ice. However, a unified data processing technique to reliably and accurately determine sea ice thickness and snow depth from this kind of data is still missing, and an unambiguous interpretation remains a challenge. Following the need to improve techniques for remotely measuring sea ice mass balance, an international IMB working group has recently been established. The main goals are 1) to coordinate IMB deployments, 2) to enhance current IMB data processing and -interpretation techniques, and 3) to provide standardized IMB data products to a broader community. Here we present first results from two different data processing algorithms, applied to selected IMB datasets from the Arctic and Antarctic. Their performance with regard to sea ice thickness and snow depth retrieval is evaluated, and an uncertainty is determined. Although several challenges and caveats in IMB data processing and -interpretation are found, such datasets bear great potential and yield plenty of useful information about sea ice properties and processes. It is planned to include many more algorithms from contributors within the working group, and we explicitly invite </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25901605','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25901605">Comparing springtime ice-algal chlorophyll a and physical properties of multi-year and first-year sea ice from the Lincoln Sea.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Lange, Benjamin A; Michel, Christine; Beckers, Justin F; Casey, J Alec; Flores, Hauke; Hatam, Ido; Meisterhans, Guillaume; Niemi, Andrea; Haas, Christian 2015-01-01 With near-complete replacement of Arctic multi-year ice (MYI) by first-year ice (FYI) predicted to occur within this century, it remains uncertain how the loss of MYI will impact the abundance and distribution of sea ice associated algae. In this study we compare the chlorophyll a (chl a) concentrations and physical properties of MYI and FYI from the Lincoln Sea during 3 spring seasons (2010-2012). Cores were analysed for texture, salinity, and chl a. We identified annual growth layers for 7 of 11 MYI cores and found no significant differences in chl a concentration between the bottom first-year-ice portions of MYI, upper old-ice portions of MYI, and FYI cores. Overall, the maximum chl a concentrations were observed at the bottom of young FYI. However, there were no significant differences in chl a concentrations between MYI and FYI. This suggests little or no change in algal biomass with a shift from MYI to FYI and that the spatial extent and regional variability of refrozen leads and younger FYI will likely be key factors governing future changes in Arctic sea ice algal biomass. Bottom-integrated chl a concentrations showed negative logistic relationships with snow depth and bulk (snow plus ice) integrated extinction coefficients; indicating a strong influence of snow cover in controlling bottom ice algal biomass. The maximum bottom MYI chl a concentration was observed in a hummock, representing the thickest ice with lowest snow depth of this study. Hence, in this and other studies MYI chl a biomass may be under-estimated due to an under-representation of thick MYI (e.g., hummocks), which typically have a relatively thin snowpack allowing for increased light transmission. Therefore, we suggest the on-going loss of MYI in the Arctic Ocean may have a larger impact on ice-associated production than generally assumed. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20040120981','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20040120981">EOS Aqua AMSR-E Arctic Sea Ice Validation Program: Arctic2003 Aircraft Campaign Flight Report</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Cavalieri, D. J.; Markus,T. 2003-01-01 In March 2003 a coordinated Arctic sea ice validation field campaign using the NASA Wallops P-3B aircraft was successfully completed. This campaign was part of the program for validating the Earth Observing System (EOS) Aqua Advanced Microwave Scanning Radiometer (AMSR-E) sea ice products. The AMSR-E, designed and built by the Japanese National Space Development Agency for NASA, was launched May 4, 2002 on the EOS Aqua spacecraft. The AMSR-E sea ice products to be validated include sea ice concentration, sea ice temperature, and snow depth on sea ice. This flight report describes the suite of instruments flown on the P-3, the objectives of each of the seven flights, the Arctic regions overflown, and the coordination among satellite, aircraft, and surface-based measurements. Two of the seven aircraft flights were coordinated with scientists making surface measurements of snow and ice properties including sea ice temperature and snow depth on sea ice at a study area near Barrow, AK and at a Navy ice camp located in the Beaufort Sea. Two additional flights were dedicated to making heat and moisture flux measurements over the St. Lawrence Island polynya to support ongoing air-sea-ice processes studies of Arctic coastal polynyas. The remaining flights covered portions of the Bering Sea ice edge, the Chukchi Sea, and Norton Sound. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMGC23D1176F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMGC23D1176F">Sea Ice, Hydrocarbon Extraction, Rain-on-Snow and Tundra Reindeer Nomadism in Arctic Russia</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Forbes, B. C.; Kumpula, T.; Meschtyb, N.; Laptander, R.; Macias-Fauria, M.; Zetterberg, P.; Verdonen, M. 2015-12-01 It is assumed that retreating sea ice in the Eurasian Arctic will accelerate hydrocarbon development and associated tanker traffic along Russia's Northern Sea Route. However, oil and gas extraction along the Kara and Barents Sea coasts will likely keep developing rapidly regardless of whether the Northwest Eurasian climate continues to warm. Less certain are the real and potential linkages to regional biota and social-ecological systems. Reindeer nomadism continues to be a vitally important livelihood for indigenous tundra Nenets and their large herds of semi-domestic reindeer. Warming summer air temperatures over the NW Russian Arctic have been linked to increases in tundra productivity, longer growing seasons, and accelerated growth of tall deciduous shrubs. These temperature increases have, in turn, been linked to more frequent and sustained summer high-pressure systems over West Siberia, but not to sea ice retreat. At the same time, winters have been warming and rain-on-snow (ROS) events have become more frequent and intense, leading to record-breaking winter and spring mortality of reindeer. What is driving this increase in ROS frequency and intensity is not clear. Recent modelling and simulation have found statistically significant near-surface atmospheric warming and precipitation increases during autumn and winter over Arctic coastal lands in proximity to regions of sea-ice loss. During the winter of 2013-14 an extensive and lasting ROS event led to the starvation of 61,000 reindeer out of a population of ca. 300,000 animals on Yamal Peninsula, West Siberia. Historically, this is the region's largest recorded mortality episode. More than a year later, participatory fieldwork with nomadic herders during spring-summer 2015 revealed that the ecological and socio-economic impacts from this extreme event will unfold for years to come. There is an urgent need to understand whether and how ongoing Barents and Kara Sea ice retreat may affect the region's ancient </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C34A..08G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C34A..08G">Seasonal thickness changes of Arctic sea ice north of Svalbard and implications for satellite remote sensing, ecosystem, and environmental management</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Gerland, S.; Rösel, A.; King, J.; Spreen, G.; Divine, D.; Eltoft, T.; Gallet, J. C.; Hudson, S. R.; Itkin, P.; Krumpen, T.; Liston, G. E.; Merkouriadi, I.; Negrel, J.; Nicolaus, M.; Polashenski, C.; Assmy, P.; Barber, D. G.; Duarte, P.; Doulgeris, A. P.; Haas, C.; Hughes, N.; Johansson, M.; Meier, W.; Perovich, D. K.; Provost, C.; Richter-Menge, J.; Skourup, H.; Wagner, P.; Wilkinson, J.; Granskog, M. A.; Steen, H. 2016-12-01 Sea-ice thickness is a crucial parameter to consider when assessing the status of Arctic sea ice, whether for environmental management, monitoring projects, or regional or pan-arctic assessments. Modern satellite remote sensing techniques allow us to monitor ice extent and to estimate sea-ice thickness changes; but accurate quantifications of sea-ice thickness distribution rely on in situ and airborne surveys. From January to June 2015, an international expedition (N-ICE2015) took place in the Arctic Ocean north of Svalbard, with the Norwegian research vessel RV Lance frozen into drifting sea ice. In total, four drifts, with four different floes were made during that time. Sea-ice and snow thickness measurements were conducted on all main ice types present in the region, first year ice, multiyear ice, and young ice. Measurement methods included ground and helicopter based electromagnetic surveys, drillings, hot-wire installations, snow-sonde transects, snow stakes, and ice mass balance and snow buoys. Ice thickness distributions revealed modal thicknesses in spring between 1.6 and 1.7 m, which is lower than reported for the region from comparable studies in 2009 (2.4 m) and 2011 (1.8 m). Knowledge about the ice thickness distribution in a region is crucial to the understanding of climate processes, and also relevant to other disciplines. Sea-ice thickness data collected during N-ICE2015 can also give us insights into how ice and snow thicknesses affect ecosystem processes. In this presentation, we will explore the influence of snow cover and ocean properties on ice thickness, and the role of sea-ice thickness in air-ice-ocean interactions. We will also demonstrate how information about ice thickness aids classification of different sea ice types from SAR satellite remote sensing, which has real-world applications for shipping and ice forecasting, and how sea ice thickness data contributes to climate assessments. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMPA13A0223V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMPA13A0223V">New Tools for Sea Ice Data Analysis and Visualization: NSIDC's Arctic Sea Ice News and Analysis</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4406449','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4406449">Comparing Springtime Ice-Algal Chlorophyll a and Physical Properties of Multi-Year and First-Year Sea Ice from the Lincoln Sea</a> <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Lange, Benjamin A.; Michel, Christine; Beckers, Justin F.; Casey, J. Alec; Flores, Hauke; Hatam, Ido; Meisterhans, Guillaume; Niemi, Andrea; Haas, Christian 2015-01-01 With near-complete replacement of Arctic multi-year ice (MYI) by first-year ice (FYI) predicted to occur within this century, it remains uncertain how the loss of MYI will impact the abundance and distribution of sea ice associated algae. In this study we compare the chlorophyll a (chl a) concentrations and physical properties of MYI and FYI from the Lincoln Sea during 3 spring seasons (2010-2012). Cores were analysed for texture, salinity, and chl a. We identified annual growth layers for 7 of 11 MYI cores and found no significant differences in chl a concentration between the bottom first-year-ice portions of MYI, upper old-ice portions of MYI, and FYI cores. Overall, the maximum chl a concentrations were observed at the bottom of young FYI. However, there were no significant differences in chl a concentrations between MYI and FYI. This suggests little or no change in algal biomass with a shift from MYI to FYI and that the spatial extent and regional variability of refrozen leads and younger FYI will likely be key factors governing future changes in Arctic sea ice algal biomass. Bottom-integrated chl a concentrations showed negative logistic relationships with snow depth and bulk (snow plus ice) integrated extinction coefficients; indicating a strong influence of snow cover in controlling bottom ice algal biomass. The maximum bottom MYI chl a concentration was observed in a hummock, representing the thickest ice with lowest snow depth of this study. Hence, in this and other studies MYI chl a biomass may be under-estimated due to an under-representation of thick MYI (e.g., hummocks), which typically have a relatively thin snowpack allowing for increased light transmission. Therefore, we suggest the on-going loss of MYI in the Arctic Ocean may have a larger impact on ice–associated production than generally assumed. PMID:25901605 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007AGUFM.C23B..08K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007AGUFM.C23B..08K">Monitoring Snow on ice as Critical Habitat for Ringed Seals</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Kelly, B. P.; Moran, J.; Douglas, D. C.; Nghiem, S. V. 2007-12-01 Ringed seals are the primary prey of polar bears, and they are found in all seasonally ice covered seas of the northern hemisphere as well as in several freshwater lakes. The presence of snow covered sea ice is essential for successful ringed seal reproduction. Ringed seals abrade holes in the ice allowing them to surface and breathe under the snow cover. Where snow accumulates to sufficient depths, ringed seals excavate subnivean lairs above breathing holes. They rest, give birth, and nurse their young in those lairs. Temperatures within the lairs remain within a few degrees of freezing, well within the zone of thermal neutrality for newborn ringed seals, even at ambient temperatures of -30° C. High rates of seal mortality have been recorded when early snow melt caused lairs to collapse exposing newborn seals to predators and to subsequent extreme cold events. As melt onset dates come earlier in the Arctic Ocean, ringed seal populations (and the polar bears that depend upon them) will be increasingly challenged. We determined dates of lair abandonment by ringed seals fitted with radio transmitters in the Beaufort Sea (n = 60). We compared abandonment dates to melt onset dates measured in the field, as well as estimated dates derived from active (Ku-band backscatter) and passive (SSM/I) microwave satellite imagery. Date of snow melt significantly improved models of environmental influences on the timing of lair abandonment. We used an algorithm based on multi-channel means and variances of passive microwave data to detect melt onset dates. Those melt onset dates predicted the date of lair abandonment ± 3 days (r 2 = 0.982, p = 0.001). The predictive power of passive microwave proxies combined with their historical record suggest they could serve to monitor critical changes to ringed seal habitat. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC44B..03T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC44B..03T">Multi-decadal Arctic sea ice roughness.</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Tsamados, M.; Stroeve, J.; Kharbouche, S.; Muller, J. P., , Prof; Nolin, A. W.; Petty, A.; Haas, C.; Girard-Ardhuin, F.; Landy, J. 2017-12-01 The transformation of Arctic sea ice from mainly perennial, multi-year ice to a seasonal, first-year ice is believed to have been accompanied by a reduction of the roughness of the ice 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 ice thickness distribution which in turn controls the snow and melt pond repartition over the ice cover, and (iii) to bias airborne and satellite remote sensing measurements that depend on the scattering and reflective characteristics over the sea ice surface topography. We will review existing and novel remote sensing methodologies proposed to estimate sea ice roughness, ranging from airborne LIDAR measurement (ie Operation IceBridge), 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 sea ice roughness. Implications for sea ice physics, climate and remote sensing will also be discussed. </li> <li> <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">NASA IceBridge: Scientific Insights from Airborne Surveys of the Polar Sea Ice Covers</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Richter-Menge, J.; Farrell, S. L. 2015-12-01 The NASA Operation IceBridge (OIB) airborne sea ice surveys are designed to continue a valuable series of sea ice thickness measurements by bridging the gap between NASA's Ice, 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 sea ice 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 sea ice processes across all length scales. Key scientific insights gained on the state of the sea ice cover will be highlighted, including snow depth, ice thickness, surface roughness and morphology, and melt pond evolution. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19890005108','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19890005108">Investigation of radar backscattering from second-year sea ice</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Lei, Guang-Tsai; Moore, Richard K.; Gogineni, S. P. 1988-01-01 The scattering properties of second-year ice were studied in an experiment at Mould Bay in April 1983. Radar backscattering measurements were made at frequencies of 5.2, 9.6, 13.6, and 16.6 GHz for vertical polarization, horizontal polarization and cross polarizations, with incidence angles ranging from 15 to 70 deg. The results indicate that the second-year ice scattering characteristics were different from first-year ice and also different from multiyear ice. The fading properties of radar signals were studied and compared with experimental data. The influence of snow cover on sea ice can be evaluated by accounting for the increase in the number of independent samples from snow volume with respect to that for bare ice surface. A technique for calculating the snow depth was established by this principle and a reasonable agreement has been observed. It appears that this is a usable way to measure depth in snow or other snow-like media using radar. </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">7</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> <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">8</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> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C33B1192G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C33B1192G">Direct observations of atmosphere - sea ice - ocean interactions during Arctic winter and spring storms</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Graham, R. M.; Itkin, P.; Granskog, M. A.; Assmy, P.; Cohen, L.; Duarte, P.; Doble, M. J.; Fransson, A.; Fer, I.; Fernandez Mendez, M.; Frey, M. M.; Gerland, S.; Haapala, J. J.; Hudson, S. R.; Liston, G. E.; Merkouriadi, I.; Meyer, A.; Muilwijk, M.; Peterson, A.; Provost, C.; Randelhoff, A.; Rösel, A.; Spreen, G.; Steen, H.; Smedsrud, L. H.; Sundfjord, A. 2017-12-01 To study the thinner and younger sea ice that now dominates the Arctic the Norwegian Young Sea ICE expedition (N-ICE2015) was launched in the ice-covered region north of Svalbard, from January to June 2015. During this time, eight local and remote storms affected the region and rare direct observations of the atmosphere, snow, ice and ocean were conducted. Six of these winter storms passed directly over the expedition and resulted in air temperatures rising from below -30oC to near 0oC, followed by abrupt cooling. Substantial snowfall prior to the campaign had already formed a snow pack of approximately 50 cm, to which the February storms contributed an additional 6 cm. The deep snow layer effectively isolated the ice cover and prevented bottom ice growth resulting in low brine fluxes. Peak wind speeds during winter storms exceeded 20 m/s, causing strong snow re-distribution, release of sea salt aerosol and sea ice deformation. The heavy snow load caused widespread negative freeboard; during sea ice deformation events, level ice floes were flooded by sea water, and at least 6-10 cm snow-ice layer was formed. Elevated deformation rates during the most powerful winter storms damaged the ice cover permanently such that the response to wind forcing increased by 60 %. As a result of a remote storm in April deformation processes opened about 4 % of the total area into leads with open water, while a similar amount of ice was deformed into pressure ridges. The strong winds also enhanced ocean mixing and increased ocean heat fluxes three-fold in the pycnocline from 4 to 12 W/m2. Ocean heat fluxes were extremely large (over 300 W/m2) during storms in regions where the warm Atlantic inflow is located close to surface over shallow topography. This resulted in very large (5-25 cm/day) bottom ice melt and in cases flooding due to heavy snow load. Storm events increased the carbon dioxide exchange between the atmosphere and ocean but also affected the pCO2 in surface waters </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19820009687','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19820009687">An optical model for the microwave properties of sea ice</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Gloersen, P.; Larabee, J. K. 1981-01-01 The complex refractive index of sea ice is modeled and used to predict the microwave signatures of various sea ice 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 sea ice. The success of this modeling procedure vis a vis modeling of the dielectric properties of sea ice constituents used earlier by several others is explained. Multiple layer radiative transfer calculations are used to predict the microwave properties of first-year sea ice with and without snow, and multiyear sea ice. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006AGUFMIN24A..06H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006AGUFMIN24A..06H">Hyperparameter Classification of Arctic Sea Ice and Snow Based on Aerial Laser Data, Passive Microwave Data and Field Data</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Herzfeld, U. C.; Maslanik, J.; Williams, S.; Sturm, M.; Cavalieri, D. 2006-12-01 In the past year, the Arctic sea-ice cover has been shrinking at an alarming rate. Remote-sensing technologies provide opportunities for observations of the sea ice at unprecedented repetition rates and spatial resolutions. The advance of new observational technologies is not only fascinating, it also brings with it the challenge and necessity to derive adequate new geoinformatical and geomathematical methods as a basis for analysis and geophysical interpretation of new data types. Our research includes validation and analysis of NASA EOS data, development of observational instrumentation and advanced geoinformatics. In this talk we emphasize the close linkage between technological development and geoinformatics along case studies of sea-ice near Point Barrow, Alaska, based on the following data types: AMSR-E and PSR passive microwave data, RADARSAT and ERS SAR data, manually-collected snow-depth data and laser-elevation data from unmanned aerial vehicles. The hyperparameter concept is introduced to facilitate characterization and classification of the same sea-ice properties and spatial structures from these data sets, which differ with respect to spatial resolution, measured parameters and observed geophysical variables. Mathematically, this requires parameter identification in undersampled, oversampled or overprinted situations. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19790015307','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19790015307">Remote sensing of snow and ice: A review of the research in the United States 1975 - 1978</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Rango, A. 1979-01-01 Research work in the United States from 1975-1978 in the field of remote sensing of snow and ice is reviewed. Topics covered include snowcover mapping, snowmelt runoff forecasting, demonstration projects, snow water equivalent and free water content determination, glaciers, river and lake ice, and sea ice. A bibliography of 200 references is included. </li> <li> <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">Microalgal photophysiology and macronutrient distribution in summer sea ice in the Amundsen and Ross Seas, Antarctica</a> <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Fransson, Agneta; Currie, Kim; Wulff, Angela; Chierici, Melissa 2018-01-01 Our study addresses how environmental variables, such as macronutrients concentrations, snow cover, carbonate chemistry and salinity affect the photophysiology and biomass of Antarctic sea-ice algae. We have measured vertical profiles of inorganic macronutrients (phosphate, nitrite + nitrate and silicic acid) in summer sea ice and photophysiology of ice algal assemblages in the poorly studied Amundsen and Ross Seas sectors of the Southern Ocean. Brine-scaled bacterial abundance, chl a and macronutrient concentrations were often high in the ice 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, ice thickness and brine salinity, which highlights a wide range of photoacclimation in Antarctic pack-ice algae. It is likely that the pack ice was in a post-bloom situation during the late sea-ice season, with low photosynthetic efficiency and a high degree of nutrient accumulation occurring in the ice. In order to predict how key biogeochemical processes are affected by future changes in sea ice cover, such as in situ photosynthesis and nutrient cycling, we need to understand how physicochemical properties of sea ice affect the microbial community. Our results support existing hypothesis about sea-ice algal photophysiology, and provide additional observations on high nutrient concentrations in sea ice that could influence the planktonic communities as the ice is retreating. PMID:29634756 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C33C1214B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C33C1214B">An Evaluation of Arctic Ocean Precipitation from Reanalyses for use in Snow Accumulation and Melt Models over Sea Ice</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Barrett, A. P.; Stroeve, J.; Liston, G. E.; Tschudi, M. A.; Stewart, S. 2017-12-01 Retrievals of sea ice thickness from satellite- and air-borne sensors require knowledge of snow depth and density. Early retrievals used climatologies of snow depth and density - "The Warren Climatology" - based on observations from 31 Soviet drifting stations between 1957 and 1991. This climatology was the best available Arctic-wide data set at the time. However, it does not account for year-to-year variations in spatial and temporal patterns of snow depth, nor does it account for changes in snow depth over longer time periods. Recent efforts to retrieve ice thickness have used output from global and regional atmospheric reanalyses directly or as input to snow accumulation, density evolution, and melt models to estimate snow depth. While such efforts represent the state-of-the-art in terms of Arctic-wide snow depth fields, there can be large differences between precipitation (and other variables) from reanalyses. Knowledge about these differences and about biases in precipitation magnitude are important for getting the best-possible retrievals of ice thickness. Here, we evaluate fields of total precipitation and snow fall from the NASA MERRA and MERRA2, NOAA CFSR and CFSR version 2, ECMWF ERA-Interim, and Arctic System (ASR) reanalyses with a view to understanding differences in the magnitude, and temporal and spatial patterns of precipitation. Where possible we use observations to understand biases in the reanalysis output. Time series of annual total precipitation for the central Arctic correlate well with all reanalyses showing similar year-to-year variability. Time series for MERRA, MERRA2 and CFSR show no evidence of long-term trends. By contrast ERA-Interim appears to be wetter in the most recent decade. The ASR records only spans 2000 to 2012 but is similar to ERA-Interim. CFSR and MERRA2 are wetter than the other five reanalyses, especially over the eastern Arctic and North Atlantic. </li> <li> <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">Microbial mercury methylation in Antarctic sea ice.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> 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 2016-08-01 Atmospheric deposition of mercury onto sea ice and circumpolar sea 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, sea ice and sea 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 sea ice. Anaerobic bacteria known to methylate mercury were notably absent from sea-ice metagenomes. We propose that Antarctic sea ice can harbour a microbial source of methylmercury in the Southern Ocean. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017GeoRL..4411482W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017GeoRL..4411482W">Snow Accumulation Variability Over the West Antarctic Ice Sheet Since 1900: A Comparison of Ice Core Records With ERA-20C Reanalysis</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Wang, Yetang; Thomas, Elizabeth R.; Hou, Shugui; Huai, Baojuan; Wu, Shuangye; Sun, Weijun; Qi, Shanzhong; Ding, Minghu; Zhang, Yulun 2017-11-01 This study uses a set of 37 firn core records over the West Antarctic Ice Sheet (WAIS) to test the performance of the twentieth century from the European Centre for Medium-Range Weather Forecasts (ERA-20C) reanalysis for snow accumulation and quantify temporal variability in snow accumulation since 1900. The firn cores are allocated to four geographical areas demarcated by drainage divides (i.e., Antarctic Peninsula (AP), western WAIS, central WAIS, and eastern WAIS) to calculate stacked records of regional snow accumulation. Our results show that the interannual variability in ERA-20C precipitation minus evaporation (P - E) agrees well with the corresponding ice core snow accumulation composites in each of the four geographical regions, suggesting its skill for simulating snow accumulation changes before the modern satellite era (pre-1979). Snow accumulation experiences significantly positive trends for the AP and eastern WAIS, a negative trend for the western WAIS, and no significant trend for the central WAIS from 1900 to 2010. The contrasting trends are associated with changes in the large-scale moisture transport driven by a deepening of the low-pressure systems and anomalies of sea ice in the Amundsen Sea Low region. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017GeoRL..44.2802P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017GeoRL..44.2802P">Anatomy of a late spring snowfall on sea ice</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Perovich, Donald; Polashenski, Christopher; Arntsen, Alexandra; Stwertka, Carolyn 2017-03-01 Spring melt initiation is a critical process for Arctic sea ice. Melting conditions decrease surface albedo at a time of high insolation, triggering powerful albedo feedback. Weather events during melt initiation, such as new snowfalls, can stop or reverse the albedo decline, however. Here we present field observations of such a snow event and demonstrate its enduring impact through summer. Snow fell 3-6 June 2014 in the Chukchi Sea, halting melt onset. The snow not only raised albedo but also provided a significant negative latent heat flux, averaging -51 W m-2 from 3 to 6 June. The snowfall delayed sustained melt by 11 days, creating cascading impacts on surface energy balance that totaled some 135 MJ/m2 by mid-August. The findings highlight the sensitivity of sea ice conditions on seasonal time scales to melt initiation processes. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19970009603','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19970009603">Polarimetric Signatures of Sea Ice. Part 1; Theoretical Model</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Nghiem, S. V.; Kwok, R.; Yueh, S. H.; Drinkwater, M. R. 1995-01-01 Physical, structural, and electromagnetic properties and interrelating processes in sea ice are used to develop a composite model for polarimetric backscattering signatures of sea ice. Physical properties of sea ice constituents such as ice, brine, air, and salt are presented in terms of their effects on electromagnetic wave interactions. Sea ice 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 sea ice, are consistently used to derive both effective permittivities and polarimetric scattering coefficients. Polarimetric signatures of sea ice depend on crystal sizes and brine volumes, which are affected by ice growth rates. Desalination by brine expulsion, drainage, or other mechanisms modifies wave penetration and scattering. Sea ice 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 sea ice, a composite model is developed to calculate effective permittivities and backscattering covariance matrices at microwave frequencies for interpretation of sea ice polarimetric signatures. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007AGUFM.C11B0422W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007AGUFM.C11B0422W">Antarctic sea ice thickness data archival and recovery at the Australian Antarctic Data Centre</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Worby, A. P.; Treverrow, A.; Raymond, B.; Jordan, M. 2007-12-01 A new effort is underway to establish a portal for Antarctic sea ice thickness data at the Australian Antarctic Data Centre (http://aadc-maps.aad.gov.au/aadc/sitd/). The intention is to provide a central online access point for a wide range of sea ice data sets, including sea ice and snow thickness data collected using a range of techniques, and sea ice core data. The recommendation to establish this facility came from the SCAR/CliC- sponsored International Workshop on Antarctic Sea Ice Thickness, held in Hobart in July 2006. It was recognised, in particular, that satellite altimetry retrievals of sea ice and snow cover thickness rely on large-scale assumptions of the sea ice and snow cover properties such as density, freeboard height, and snow stratigraphy. The synthesis of historical data is therefore particularly important for algorithm development. This will be closely coordinated with similar efforts in the Arctic. A small working group was formed to identify suitable data sets for inclusion in the archive. A series of standard proformas have been designed for converting old data, and to help standardize the collection of new data sets. These proformas are being trialled on two Antarctic sea ice research cruises in September - October 2007. The web-based portal allows data custodians to remotely upload and manage their data, and for all users to search the holdings and extract data relevant to their needs. This presentation will report on the establishment of the data portal, recent progress in identifying appropriate data sets and making them available online. maps.aad.gov.au/aadc/sitd/ </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20040079837&hterms=ice+antarctica&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dice%2Bantarctica','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20040079837&hterms=ice+antarctica&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dice%2Bantarctica">Validation of EOS Aqua AMSR Sea Ice Products for East Antarctica</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Massom, Rob; Lytle, Vicky; Allison, Ian; Worby, Tony; Markus, Thorsten; Scambos, Ted; Haran, Terry; Enomoto, Hiro; Tateyama, Kazu; Pfaffling, Andi 2004-01-01 This paper presents results from AMSR-E validation activities during a collaborative international cruise onboard the RV Aurora Australis to the East Antarctic sea ice zone (64-65 deg.S, 110-120 deg.E) in the early Austral spring of 2003. The validation strategy entailed an IS-day survey of the statistical characteristics of sea ice and snowcover over a Lagrangian grid 100 x 50 km in size (demarcated by 9 drifting ice beacons) i.e. at a scale representative of Ah4SR pixels. Ice conditions ranged h m consolidated first-year ice to a large polynya offshore from Casey Base. Data sets collected include: snow depth and snow-ice interface temperatures on 24 (?) randomly-selected floes in grid cells within a 10 x 50 km area (using helicopters); detailed snow and ice measurements at 13 dedicated ice stations, one of which lasted for 4 days; time-series measurements of snow temperature and thickness at selected sites; 8 aerial photography and thermal-IR radiometer flights; other satellite products (SAR, AVHRR, MODIS, MISR, ASTER and Envisat MERIS); ice drift data; and ancillary meteorological (ship-based, meteorological buoys, twice-daily radiosondes). These data are applied to a validation of standard AMSR-E ice concentration, snowcover thickness and ice-temperature products. In addition, a validation is carried out of ice-surface skin temperature products h m the NOAA AVHRR and EOS MODIS datasets. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20070021414&hterms=impact+factor&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dimpact%2Bfactor','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20070021414&hterms=impact+factor&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dimpact%2Bfactor">Impact of Surface Roughness on AMSR-E Sea Ice Products</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Stroeve, Julienne C.; Markus, Thorsten; Maslanik, James A.; Cavalieri, Donald J.; Gasiewski, Albin J.; Heinrichs, John F.; Holmgren, Jon; Perovich, Donald K.; Sturm, Matthew 2006-01-01 This paper examines the sensitivity of Advanced Microwave Scanning Radiometer (AMSR-E) brightness temperatures (Tbs) to surface roughness by a using radiative transfer model to simulate AMSR-E Tbs as a function of incidence angle at which the surface is viewed. The simulated Tbs are then used to examine the influence that surface roughness has on two operational sea ice algorithms, namely: 1) the National Aeronautics and Space Administration Team (NT) algorithm and 2) the enhanced NT algorithm, as well as the impact of roughness on the AMSR-E snow depth algorithm. Surface snow and ice data collected during the AMSR-Ice03 field campaign held in March 2003 near Barrow, AK, were used to force the radiative transfer model, and resultant modeled Tbs are compared with airborne passive microwave observations from the Polarimetric Scanning Radiometer. Results indicate that passive microwave Tbs are very sensitive even to small variations in incidence angle, which can cause either an over or underestimation of the true amount of sea ice in the pixel area viewed. For example, this paper showed that if the sea ice areas modeled in this paper mere assumed to be completely smooth, sea ice concentrations were underestimated by nearly 14% using the NT sea ice algorithm and by 7% using the enhanced NT algorithm. A comparison of polarization ratios (PRs) at 10.7,18.7, and 37 GHz indicates that each channel responds to different degrees of surface roughness and suggests that the PR at 10.7 GHz can be useful for identifying locations of heavily ridged or rubbled ice. Using the PR at 10.7 GHz to derive an "effective" viewing angle, which is used as a proxy for surface roughness, resulted in more accurate retrievals of sea ice concentration for both algorithms. The AMSR-E snow depth algorithm was found to be extremely sensitive to instrument calibration and sensor viewing angle, and it is concluded that more work is needed to investigate the sensitivity of the gradient ratio at 37 and </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.gpo.gov/fdsys/pkg/CFR-2014-title14-vol3/pdf/CFR-2014-title14-vol3-sec139-313.pdf','CFR2014'); return false;" href="https://www.gpo.gov/fdsys/pkg/CFR-2014-title14-vol3/pdf/CFR-2014-title14-vol3-sec139-313.pdf">14 CFR 139.313 - Snow and ice control.</a> <a target="_blank" href="http://www.gpo.gov/fdsys/browse/collectionCfr.action?selectedYearFrom=2014&page.go=Go">Code of Federal Regulations, 2014 CFR</a> 2014-01-01 ... 14 Aeronautics and Space 3 2014-01-01 2014-01-01 false Snow and ice control. 139.313 Section 139... AIRPORTS Operations § 139.313 Snow and ice control. (a) As determined by the Administrator, each... carry out a snow and ice control plan in a manner authorized by the Administrator. (b) The snow and ice... </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.gpo.gov/fdsys/pkg/CFR-2010-title14-vol3/pdf/CFR-2010-title14-vol3-sec139-313.pdf','CFR'); return false;" href="https://www.gpo.gov/fdsys/pkg/CFR-2010-title14-vol3/pdf/CFR-2010-title14-vol3-sec139-313.pdf">14 CFR 139.313 - Snow and ice control.</a> <a target="_blank" href="http://www.gpo.gov/fdsys/browse/collectionCfr.action?selectedYearFrom=2010&page.go=Go">Code of Federal Regulations, 2010 CFR</a> 2010-01-01 ... 14 Aeronautics and Space 3 2010-01-01 2010-01-01 false Snow and ice control. 139.313 Section 139... AIRPORTS Operations § 139.313 Snow and ice control. (a) As determined by the Administrator, each... carry out a snow and ice control plan in a manner authorized by the Administrator. (b) The snow and ice... </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.gpo.gov/fdsys/pkg/CFR-2011-title14-vol3/pdf/CFR-2011-title14-vol3-sec139-313.pdf','CFR2011'); return false;" href="https://www.gpo.gov/fdsys/pkg/CFR-2011-title14-vol3/pdf/CFR-2011-title14-vol3-sec139-313.pdf">14 CFR 139.313 - Snow and ice control.</a> <a target="_blank" href="http://www.gpo.gov/fdsys/browse/collectionCfr.action?selectedYearFrom=2011&page.go=Go">Code of Federal Regulations, 2011 CFR</a> 2011-01-01 ... 14 Aeronautics and Space 3 2011-01-01 2011-01-01 false Snow and ice control. 139.313 Section 139... AIRPORTS Operations § 139.313 Snow and ice control. (a) As determined by the Administrator, each... carry out a snow and ice control plan in a manner authorized by the Administrator. (b) The snow and ice... </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.gpo.gov/fdsys/pkg/CFR-2013-title14-vol3/pdf/CFR-2013-title14-vol3-sec139-313.pdf','CFR2013'); return false;" href="https://www.gpo.gov/fdsys/pkg/CFR-2013-title14-vol3/pdf/CFR-2013-title14-vol3-sec139-313.pdf">14 CFR 139.313 - Snow and ice control.</a> <a target="_blank" href="http://www.gpo.gov/fdsys/browse/collectionCfr.action?selectedYearFrom=2013&page.go=Go">Code of Federal Regulations, 2013 CFR</a> 2013-01-01 ... 14 Aeronautics and Space 3 2013-01-01 2013-01-01 false Snow and ice control. 139.313 Section 139... AIRPORTS Operations § 139.313 Snow and ice control. (a) As determined by the Administrator, each... carry out a snow and ice control plan in a manner authorized by the Administrator. (b) The snow and ice... </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.gpo.gov/fdsys/pkg/CFR-2012-title14-vol3/pdf/CFR-2012-title14-vol3-sec139-313.pdf','CFR2012'); return false;" href="https://www.gpo.gov/fdsys/pkg/CFR-2012-title14-vol3/pdf/CFR-2012-title14-vol3-sec139-313.pdf">14 CFR 139.313 - Snow and ice control.</a> <a target="_blank" href="http://www.gpo.gov/fdsys/browse/collectionCfr.action?selectedYearFrom=2012&page.go=Go">Code of Federal Regulations, 2012 CFR</a> 2012-01-01 ... 14 Aeronautics and Space 3 2012-01-01 2012-01-01 false Snow and ice control. 139.313 Section 139... AIRPORTS Operations § 139.313 Snow and ice control. (a) As determined by the Administrator, each... carry out a snow and ice control plan in a manner authorized by the Administrator. (b) The snow and ice... </li> <li> <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">Quantification of ikaite in Antarctic sea ice</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Fischer, M.; Thomas, D. N.; Krell, A.; Nehrke, G.; Göttlicher, J.; Norman, L.; Riaux-Gobin, C.; Dieckmann, G. S. 2012-02-01 Calcium carbonate precipitation in sea ice can increase pCO2 during precipitation in winter and decrease pCO2 during dissolution in spring. CaCO3 precipitation in sea ice 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 sea ice. This is the first quantitative study of hydrous calcium carbonate, as ikaite, in sea ice and discusses its potential significance for the carbon cycle in polar oceans. Ice cores and brine samples were collected from pack and land fast sea ice 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 sea ice with values up to 126 mg ikaite per liter melted sea ice. 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 sea ice was heterogenous. We also found the precipitate in the snow on top of the sea ice. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20100032968','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20100032968">CBSIT 2009: Airborne Validation of Envisat Radar Altimetry and In Situ Ice Camp Measurements Over Arctic Sea Ice</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Connor, Laurence; Farrell, Sinead; McAdoo, David; Krabill, William; Laxon, Seymour; Richter-Menge, Jacqueline; Markus, Thorsten 2010-01-01 The past few years have seen the emergence of satellite altimetry as valuable tool for taking quantitative sea ice monitoring beyond the traditional surface extent measurements and into estimates of sea ice 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 sea ice thickness. The complexity of polar environments, however, continues to make sea ice thickness determination a complicated remote sensing task and validation studies remain essential for successful monitoring of sea ice 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 sea ice elevation measurements with high-resolution airborne elevation measurements, revealing the impact of refrozen leads on radar altimetry and ice drift on laser altimetry. Continuing this research and validation effort, the Canada Basin Sea Ice Thickness (CBSIT) experiment was completed in April 2009. CBSIT was conducted by NOAA. and NASA as part of NASA's Operation Ice Bridge, a gap-filling mission intended to supplement sea and land ice 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 Sea that included an overflight of the Danish GreenArc Ice Camp off the coast of northern Greenland. We present an examination of data collected during this campaign, comparing airborne laser altimeter measurements </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">8</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> <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">9</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> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27780352','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27780352">Seasonal Study of Mercury Species in the Antarctic Sea Ice Environment.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Nerentorp Mastromonaco, Michelle G; Gårdfeldt, Katarina; Langer, Sarka; Dommergue, Aurélien 2016-12-06 Limited studies have been conducted on mercury concentrations in the polar cryosphere and the factors affecting the distribution of mercury within sea ice and snow are poorly understood. Here we present the first comprehensive seasonal study of elemental and total mercury concentrations in the Antarctic sea ice environment covering data from measurements in air, sea ice, seawater, snow, frost flowers, and brine. The average concentration of total mercury in sea ice decreased from winter (9.7 ng L -1 ) to spring (4.7 ng L -1 ) while the average elemental mercury concentration increased from winter (0.07 ng L -1 ) to summer (0.105 ng L -1 ). The opposite trends suggest potential photo- or dark oxidation/reduction processes within the ice and an eventual loss of mercury via brine drainage or gas evasion of elemental mercury. Our results indicate a seasonal variation of mercury species in the polar sea ice environment probably due to varying factors such as solar radiation, temperature, brine volume, and atmospheric deposition. This study shows that the sea ice environment is a significant interphase between the polar ocean and the atmosphere and should be accounted for when studying how climate change may affect the mercury cycle in polar regions. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-GSFC_20171208_Archive_e000582.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-GSFC_20171208_Archive_e000582.html">Sea Ice in the Bellingshausen Sea</a> <a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a> 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 </li> <li> <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">Organic iodine in Antarctic sea ice: A comparison between winter in the Weddell Sea and summer in the Amundsen Sea</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Granfors, Anna; Ahnoff, Martin; Mills, Matthew M.; Abrahamsson, Katarina 2014-12-01 Recent studies have recognized sea ice as a source of reactive iodine to the Antarctic boundary layer. Volatile iodinated compounds (iodocarbons) are released from sea ice, 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 sea ice, snow, brine, and air during two expeditions to Antarctica, OSO 10/11 to the Amundsen Sea during austral summer and ANT XXIX/6 to the Weddell Sea in austral winter. These are the first reported measurements of iodocarbons from the Antarctic winter. Iodocarbons were enriched in sea ice 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 sea ice during both summer and winter. For CH2ClI, CH2BrI, and CH2I2, an additional abiotic source at the snow/ice 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. </li> <li> <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">Sea ice and pollution-modulated changes in Greenland ice core methanesulfonate and bromine</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Maselli, Olivia J.; Chellman, Nathan J.; Grieman, Mackenzie; Layman, Lawrence; McConnell, Joseph R.; Pasteris, Daniel; Rhodes, Rachael H.; Saltzman, Eric; Sigl, Michael 2017-01-01 Reconstruction of past changes in Arctic sea ice extent may be critical for understanding its future evolution. Methanesulfonate (MSA) and bromine concentrations preserved in ice cores have both been proposed as indicators of past sea ice conditions. In this study, two ice 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 ice core MSA and the HadISST1 ICE sea ice 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 sea ice in the same source regions. The positive correlation between ice core MSA and bromine persists until the mid-20th century, when the acidity of Greenland ice begins to increase markedly due to increased fossil fuel emissions. After that time, MSA levels decrease as a result of declining sea ice extent but bromine levels increase. We consider several possible explanations and ultimately suggest that increased acidity, specifically nitric acid, of snow on sea ice stimulates the release of reactive Br from sea ice, resulting in increased transport and deposition on the Greenland ice sheet. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19980027706','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19980027706">Snow and Ice Applications of AVHRR in Polar Regions: Report of a Workshop</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Steffen, K.; Bindschadler, R.; Casassa, G.; Comiso, J.; Eppler, D.; Fetterer, F.; Hawkins, J.; Key, J.; Rothrock, D.; Thomas, R.; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_19980027706'); toggleEditAbsImage('author_19980027706_show'); toggleEditAbsImage('author_19980027706_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_19980027706_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_19980027706_hide"> 1993-01-01 The third symposium on Remote Sensing of Snow and Ice, organized by the International Glaciological Society, took place in Boulder, Colorado, 17-22 May 1992. As part of this meeting a total of 21 papers was presented on snow and ice applications of Advanced Very High Resolution Radiometer (AVHRR) satellite data in polar regions. Also during this meeting a NASA sponsored Workshop was held to review the status of polar surface measurements from AVHRR. In the following we have summarized the ideas and recommendations from the workshop, and the conclusions of relevant papers given during the regular symposium sessions. The seven topics discussed include cloud masking, ice surface temperature, narrow-band albedo, ice concentration, lead statistics, sea-ice motion and ice-sheet studies with specifics on applications, algorithms and accuracy, following recommendations for future improvements. In general, we can affirm the strong potential of AVHRR for studying sea ice and snow covered surfaces, and we highly recommend this satellite data set for long-term monitoring of polar process studies. However, progress is needed to reduce the uncertainty of the retrieved parameters for all of the above mentioned topics to make this data set useful for direct climate applications such as heat balance studies and others. Further, the acquisition and processing of polar AVHRR data must become better coordinated between receiving stations, data centers and funding agencies to guarantee a long-term commitment to the collection and distribution of high quality data. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110011892','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110011892">Observations of Recent Arctic Sea Ice Volume Loss and Its Impact on Ocean-Atmosphere Energy Exchange and Ice Production</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Kurtz, N. T.; Markus, T.; Farrell, S. L.; Worthen, D. L.; Boisvert, L. N. 2011-01-01 Using recently developed techniques we estimate snow and sea ice thickness distributions for the Arctic basin through the combination of freeboard data from the Ice, Cloud, and land Elevation Satellite (ICESat) and a snow depth model. These data are used with meteorological data and a thermodynamic sea ice model to calculate ocean-atmosphere heat exchange and ice volume production during the 2003-2008 fall and winter seasons. The calculated heat fluxes and ice growth rates are in agreement with previous observations over multiyear ice. In this study, we calculate heat fluxes and ice growth rates for the full distribution of ice thicknesses covering the Arctic basin and determine the impact of ice thickness change on the calculated values. Thinning of the sea ice 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 sea ice thickness for the winter periods, the winter time heat flux was found to be less impacted by the observed changes in ice 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 sea ice. The anomalously low sea ice coverage in 2007 led to a net ocean-atmosphere heat output approximately 3 times greater than was observed in previous years and suggests that sea ice losses are now playing a role in increasing surface air temperatures in the Arctic. </li> <li> <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">Antarctic Sea ice--a habitat for extremophiles.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Thomas, D N; Dieckmann, G S 2002-01-25 The pack ice 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 ice 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 sea-ice organisms thrive in the ice, 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 sea ice have become the focus for novel biotechnology, as well as being considered proxies for possible life forms on ice-covered extraterrestrial bodies. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUFM.C41C0534R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUFM.C41C0534R">Recent increase in snow-melt area in the Greenland Ice sheet as an indicator of the effect of reduced surface albedo by snow impurities</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Rikiishi, K. 2008-12-01 Recent rapid decline of cryosphere including mountain glaciers, sea ice, and seasonal snow cover tends to be associated with global warming. However, positive feedback is likely to operate between the cryosphere and air temperature, and then it may not be so simple to decide the cause-and-effect relation between them. The theory of heat budget for snow surface tells us that sensible heat transfer from the air to the snow by atmospheric warming by 1°C is about 10 W/m2, which is comparable with heat supply introduced by reduction of the snow surface albedo by only 0.02. Since snow impurities such as black carbon and soil- origin dusts have been accumulated every year on the snow surface in snow-melting season, it is very important to examine whether the snow-melting on the ice sheets, mountain glaciers, and sea ice is caused by global warming or by accumulated snow impurities originated from atmospheric pollutants. In this paper we analyze the dataset of snow-melt area in the Greenland ice sheet for the years 1979 - 2007 (available from the National Snow and Ice Data Center), which is reduced empirically from the satellite micro-wave observations by SMMR and SMM/I. It has been found that, seasonally, the snow-melt area extends most significantly from the second half of June to the first half of July when the sun is highest and sunshine duration is longest, while it doesn't extend any more from the second half of July to the first half of August when the air temperature is highest. This fact may imply that sensible heat required for snow-melting comes from the solar radiation rather than from the atmosphere. As for the interannual variation of snow-melt area, on the other hand, we have found that the growth rate of snow-melt area gradually increases from July, to August, and to the first half of September as the impurities come out to and accumulated at the snow surface. However, the growth rate is almost zero in June and the second half of September when fresh snow </li> <li> <a target="_blank" onclick="trackOutboundLink('https://rosap.ntl.bts.gov/view/dot/29587','DOTNTL'); return false;" href="https://rosap.ntl.bts.gov/view/dot/29587">Performance evaluation of snow and ice plows.</a> <a target="_blank" href="http://ntlsearch.bts.gov/tris/index.do">DOT National Transportation Integrated Search</a> 2015-11-01 Removal of ice and snow from road surfaces is a critical task in the northern tier of the United States, : including Illinois. Highways with high levels of traffic are expected to be cleared of snow and ice quickly : after each snow storm. This is ne... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110005552','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110005552">ICESat Observations of Seasonal and Interannual Variations of Sea-Ice Freeboard and Estimated Thickness in the Weddell Sea, Antarctica (2003-2009)</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Yi, Donghui; Robbins, John W. 2010-01-01 Sea-ice freeboard heights for 17 ICESat campaign periods from 2003 to 2009 are derived from ICESat data. Freeboard is combined with snow depth from Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) data and nominal densities of snow, water and sea ice, to estimate sea-ice thickness. Sea-ice freeboard and thickness distributions show clear seasonal variations that reflect the yearly cycle of growth and decay of the Weddell Sea (Antarctica) pack ice. During October-November, sea ice grows to its seasonal maximum both in area and thickness; the mean freeboards are 0.33-0.41 m and the mean thicknesses are 2.10-2.59 m. During February-March, thinner sea ice melts away and the sea-ice pack is mainly distributed in the west Weddell Sea; the mean freeboards are 0.35-0.46 m and the mean thicknesses are 1.48-1.94 m. During May-June, the mean freeboards and thicknesses are 0.26-0.29 m and 1.32-1.37 m, respectively. The 6 year trends in sea-ice extent and volume are (0.023+/-0.051) x 10(exp 6)sq km/a (0.45%/a) and (0.007+/-1.0.092) x 10(exp 3)cu km/a (0.08%/a); however, the large standard deviations indicate that these positive trends are not statistically significant. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA617971','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA617971">Optimizing Observations of Sea Ice Thickness and Snow Depth in the Arctic</a> <a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a> 2014-09-30 changes in the thickness of sea ice, glaciers , and ice sheets. These observations are critical for predicting the response of Earth’s polar ice to...Arctic Sea Ice Conditions in Spring 2009 - 2013 Prior to Melt , Geophys. Res. Lett., 40, 5888-5893, doi: 10.1002/2013GL058011. [published, refereed </li> <li> <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">Sea ice and polar climate in the NCAR CSM</a> <a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Weatherly, J.W.; Briegleb, B.P.; Large, W.G. The Climate System Model (CSM) consists of atmosphere, ocean, land, and sea-ice components linked by a flux coupler, which computes fluxes of energy and momentum between components. The sea-ice component consists of a thermodynamic formulation for ice, snow, and leads within the ice pack, and ice dynamics using the cavitating-fluid ice rheology, which allows for the compressive strength of ice but ignores shear viscosity. The results of a 300-yr climate simulation are presented, with the focus on sea ice and the atmospheric forcing over sea ice 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 sea-ice concentrations and velocities are compared to satellite observational data. The atmospheric sea level pressure (SLP) in CSM exhibits a high in the central Arctic displaced poleward from the observed Beaufort high. The Southern Hemisphere SLP over sea ice is generally 5 mb lower than observed. Air temperatures over sea ice 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C21B1120W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C21B1120W">Autonomous Ice Mass Balance Buoys for Seasonal Sea Ice</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Whitlock, J. D.; Planck, C.; Perovich, D. K.; Parno, J. T.; Elder, B. C.; Richter-Menge, J.; Polashenski, C. M. 2017-12-01 The ice mass-balance represents the integration of all surface and ocean heat fluxes and attributing the impact of these forcing fluxes on the ice cover can be accomplished by increasing temporal and spatial measurements. Mass balance information can be used to understand the ongoing changes in the Arctic sea ice cover and to improve predictions of future ice conditions. Thinner seasonal ice in the Arctic necessitates the deployment of Autonomous Ice Mass Balance buoys (IMB's) capable of long-term, in situ data collection in both ice and open ocean. Seasonal IMB's (SIMB's) are free floating IMB's that allow data collection in thick ice, thin ice, during times of transition, and even open water. The newest generation of SIMB aims to increase the number of reliable IMB's in the Arctic by leveraging inexpensive commercial-grade instrumentation when combined with specially developed monitoring hardware. Monitoring tasks are handled by a custom, expandable data logger that provides low-cost flexibility for integrating a large range of instrumentation. The SIMB features ultrasonic sensors for direct measurement of both snow depth and ice thickness and a digital temperature chain (DTC) for temperature measurements every 2cm through both snow and ice. Air temperature and pressure, along with GPS data complete the Arctic picture. Additionally, the new SIMB is more compact to maximize deployment opportunities from multiple types of platforms. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/AD1013699','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/AD1013699">Applying High Resolution Imagery to Understand the Role of Dynamics in the Diminishing Arctic Sea Ice Cover</a> <a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a> 2015-09-30 observations collected by the NASA Operation IceBridge (OIB) project, including high-resolution visible-band imagery (Onana et al., 2013), snow depth ( Newman et...2014; Farrell et al., 2015; Hutchings et al., 2015; Richter-Menge and Farrell, 2014), snow depth ( Newman et al., 2014; Webster et al., 2014), sea ice...with A. Mahoney , H. Eicken and C. Haas on an ONR-funded project "Mass balance of multi-year sea ice in the southern Beaufort Sea". This effort </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1913097K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1913097K">Improved method for sea ice age computation based on combination of sea ice drift and concentration</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3153057','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3153057">Diversity and Vertical Distribution of Microbial Eukaryotes in the Snow, Sea Ice and Seawater Near the North Pole at the End of the Polar Night</a> <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Bachy, Charles; López-García, Purificación; Vereshchaka, Alexander; Moreira, David 2011-01-01 Our knowledge about the microorganisms living in the high Arctic Ocean is still rudimentary compared to other oceans mostly because of logistical challenges imposed by its inhospitable climate and the presence of a multi-year ice cap. We have used 18S rRNA gene libraries to study the diversity of microbial eukaryotes in the upper part of the water column (0–170 m depth), the sea ice (0–1.5 m depth) and the overlying snow from samples collected in the vicinity of the North Pole (N88°35′, E015°59) at the very end of the long polar night. We detected very diverse eukaryotes belonging to Alveolata, Fungi, Amoebozoa, Viridiplantae, Metazoa, Rhizaria, Heterokonta, and Telonemia. Different alveolates (dinoflagellates and Marine Alveolate Groups I and II species) were the most abundant and diverse in gene libraries from water and sea ice, representing 80% of the total number of clones and operational taxonomic units. Only contaminants and/or species from continental ecosystems were detected in snow, suggesting wind- and animal- or human-mediated cosmopolitan dispersal of some taxa. By contrast, sea ice and seawater samples harbored a larger and more similar inter-sample protist diversity as compared with snow. The North Pole was found to harbor distinctive eukaryotic communities along the vertical gradient with an unparalleled diversity of core dinoflagellates, largely dominant in libraries from the water column, as compared to other oceanic locations. In contrast, phototrophic organisms typical of Arctic sea ice and plankton, such as diatoms and prasinophytes, were very rare in our samples. This was most likely due to a decrease of their populations after several months of polar night darkness and to the presence of rich populations of diverse grazers. Whereas strict phototrophs were scarce, we identified a variety of likely mixotrophic taxa, which supports the idea that mixotrophy may be important for the survival of diverse protists through the long polar </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26408452','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26408452">Snow and ice ecosystems: not so extreme.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Maccario, Lorrie; Sanguino, Laura; Vogel, Timothy M; Larose, Catherine 2015-12-01 Snow and ice environments cover up to 21% of the Earth's surface. They have been regarded as extreme environments because of their low temperatures, high UV irradiation, low nutrients and low water availability, and thus, their microbial activity has not been considered relevant from a global microbial ecology viewpoint. In this review, we focus on why snow and ice habitats might not be extreme from a microbiological perspective. Microorganisms interact closely with the abiotic conditions imposed by snow and ice habitats by having diverse adaptations, that include genetic resistance mechanisms, to different types of stresses in addition to inhabiting various niches where these potential stresses might be reduced. The microbial communities inhabiting snow and ice are not only abundant and taxonomically diverse, but complex in terms of their interactions. Altogether, snow and ice seem to be true ecosystems with a role in global biogeochemical cycles that has likely been underestimated. Future work should expand past resistance studies to understanding the function of these ecosystems. Copyright © 2015 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved. </li> <li> <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">Trend analysis of Arctic sea ice extent</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Silva, M. E.; Barbosa, S. M.; Antunes, Luís; Rocha, Conceição 2009-04-01 The extent of Arctic sea ice is a fundamental parameter of Arctic climate variability. In the context of climate change, the area covered by ice in the Arctic is a particularly useful indicator of recent changes in the Arctic environment. Climate models are in near universal agreement that Arctic sea ice extent will decline through the 21st century as a consequence of global warming and many studies predict a ice free Arctic as soon as 2012. Time series of satellite passive microwave observations allow to assess the temporal changes in the extent of Arctic sea ice. Much of the analysis of the ice 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 sea ice extent time series available at National Snow and Ice 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 sea ice extent. Therefore, alternative parametrizations such as long-range dependence should be considered for characterising long-term Arctic sea ice variability. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20040171250','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20040171250">ICESat Observations of Arctic Sea Ice: A First Look</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Kwok, Ron; Zwally, H. Jay; Yi, Dong-Hui 2004-01-01 Analysis of near-coincident ICESat and RADARSAT imagery shows that the retrieved elevations from the laser altimeter are sensitive to new openings (containing thin ice or open water) in the sea ice cover as well as to surface relief of old and first-year ice. The precision of the elevation estimates, measured over relatively flat sea ice, is approx. 2 cm Using the thickness of thin-ice in recent openings to estimate sea level references, we obtain the sea-ice free-board along the altimeter tracks. This step is necessitated by the large uncertainties in the time-varying sea 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 ice 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 ice cover at length scales at and above the spatial dimension of the altimeter footprint. </li> <li> <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">Variability of sea salts in ice and firn cores from Fimbul Ice Shelf, Dronning Maud Land, Antarctica</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Paulina Vega, Carmen; Isaksson, Elisabeth; Schlosser, Elisabeth; Divine, Dmitry; Martma, Tõnu; Mulvaney, Robert; Eichler, Anja; Schwikowski-Gigar, Margit 2018-05-01 Major ions were analysed in firn and ice cores located at Fimbul Ice Shelf (FIS), Dronning Maud Land - DML, Antarctica. FIS is the largest ice shelf in the Haakon VII Sea, with an extent of approximately 36 500 km2. Three shallow firn cores (about 20 m deep) were retrieved in different ice 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 sea. Sea-salt species (mainly Na+ and Cl-) generally dominate the precipitation chemistry in the study region. We associate a significant sixfold increase in median sea-salt concentrations, observed in the S100 core after the 1950s, to an enhanced exposure of the S100 site to primary sea-salt aerosol due to a shorter distance from the S100 site to the ice front, and to enhanced sea-salt aerosol production from blowing salty snow over sea ice, most likely related to the calving of Trolltunga occurred during the 1960s. This increase in sea-salt concentrations is synchronous with a shift in non-sea-salt sulfate (nssSO42-) toward negative values, suggesting a possible contribution of fractionated aerosol to the sea-salt load in the S100 core most likely originating from salty snow found on sea ice. In contrast, there is no evidence of a significant contribution of fractionated sea salt to the ice-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 sea-salt record dominated by the proximity of the site to the ocean, and processes of sea ice formation in the neighbouring waters. In contrast, the ice-rises firn cores register a larger-scale signal of atmospheric flow conditions and a less efficient transport of sea-salt aerosols to these sites. These findings are a </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">9</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> <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">10</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> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19990024954','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19990024954">Improved Upper Ocean/Sea Ice Modeling in the GISS GCM for Investigating Climate Change</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 1997-01-01 This project built on our previous results in which we highlighted the importance of sea ice in overall climate sensitivity by determining that for both warming and cooling climates, when sea ice was not allowed to change, climate sensitivity was reduced by 35-40%. We also modified the Goddard Institute for Space Studies (GISS) 8 deg x lO deg atmospheric General Circulation Model (GCM) to include an upper-ocean/sea-ice model involving the Semtner three-layer ice/snow thermodynamic model, the Price et al. (1986) ocean mixed layer model and a general upper ocean vertical advection/diffusion scheme for maintaining and fluxing properties across the pycnocline. This effort, in addition to improving the sea ice representation in the AGCM, revealed a number of sensitive components of the sea ice/ocean system. For example, the ability to flux heat through the ice/snow properly is critical in order to resolve the surface temperature properly, since small errors in this lead to unrestrained climate drift. The present project, summarized in this report, had as its objectives: (1) introducing a series of sea ice and ocean improvements aimed at overcoming remaining weaknesses in the GCM sea ice/ocean representation, and (2) performing a series of sensitivity experiments designed to evaluate the climate sensitivity of the revised model to both Antarctic and Arctic sea ice, determine the sensitivity of the climate response to initial ice distribution, and investigate the transient response to doubling CO2. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19990040408','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19990040408">Improved Upper Ocean/Sea Ice Modeling in the GISS GCM for Investigating Climate Change</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 1998-01-01 This project built on our previous results in which we highlighted the importance of sea ice in overall climate sensitivity by determining that for both warming and cooling climates, when sea ice was not allowed to change, climate sensitivity was reduced by 35-40%. We also modified the GISS 8 deg x lO deg atmospheric GCM to include an upper-ocean/sea-ice model involving the Semtner three-layer ice/snow thermodynamic model, the Price et al. (1986) ocean mixed layer model and a general upper ocean vertical advection/diffusion scheme for maintaining and fluxing properties across the pycnocline. This effort, in addition to improving the sea ice representation in the AGCM, revealed a number of sensitive components of the sea ice/ocean system. For example, the ability to flux heat through the ice/snow properly is critical in order to resolve the surface temperature properly, since small errors in this lead to unrestrained climate drift. The present project, summarized in this report, had as its objectives: (1) introducing a series of sea ice and ocean improvements aimed at overcoming remaining weaknesses in the GCM sea ice/ocean representation, and (2) performing a series of sensitivity experiments designed to evaluate the climate sensitivity of the revised model to both Antarctic and Arctic sea ice, determine the sensitivity of the climate response to initial ice distribution, and investigate the transient response to doubling CO2. </li> <li> <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">Spaceborne SAR and sea ice</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Weeks, W. F. 1983-01-01 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 ice covers are described. Considering sea ice 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 ice 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 ice activity can be intense. The margins of the ice pack, a region of particular interest, is shrouded in cloud between 80 and 90% of the time. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C53C..03D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C53C..03D">A Decade of High-Resolution Arctic Sea Ice Measurements from Airborne Altimetry</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Duncan, K.; Farrell, S. L.; Connor, L. N.; Jackson, C.; Richter-Menge, J. 2017-12-01 Satellite altimeters carried on board ERS-1,-2, EnviSat, ICESat, CryoSat-2, AltiKa and Sentinel-3 have transformed our ability to map the thickness and volume of the polar sea ice cover, on seasonal and decadal time-scales. The era of polar satellite altimetry has coincided with a rapid decline of the Arctic ice cover, which has thinned, and transitioned from a predominantly multi-year to first-year ice cover. In conjunction with basin-scale satellite altimeter observations, airborne surveys of the Arctic Ocean at the end of winter are now routine. These surveys have been targeted to monitor regions of rapid change, and are designed to obtain the full snow and ice thickness distribution, across a range of ice types. Sensors routinely deployed as part of NASA's Operation IceBridge (OIB) campaigns include the Airborne Topographic Mapper (ATM) laser altimeter, the frequency-modulated continuous-wave snow radar, and the Digital Mapping System (DMS). Airborne measurements yield high-resolution data products and thus present a unique opportunity to assess the quality and characteristics of the satellite observations. We present a suite of sea ice data products that describe the snow depth and thickness of the Arctic ice cover during the last decade. Fields were derived from OIB measurements collected between 2009-2017, and from reprocessed data collected during ad-hoc sea ice campaigns prior to OIB. Our bespoke algorithms are designed to accommodate the heterogeneous sea ice surface topography, that varies at short spatial scales. We assess regional and inter-annual variability in the sea ice thickness distribution. Results are compared to satellite-derived ice thickness fields to highlight the sensitivities of satellite footprints to the tails of the thickness distribution. We also show changes in the dynamic forcing shaping the ice pack over the last eight years through an analysis of pressure-ridge sail-height distributions and surface roughness conditions </li> <li> <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">Variability of Arctic Sea Ice as Viewed from Space</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Parkinson, Claire L. 1998-01-01 year and region to region are large, overall the Arctic ice extents did show a statistically significant, 2.8%/ decade negative trend over the 18.2-year period. Ice season lengths, which vary from only a few weeks near the ice margins to the full year in the large region of perennial ice coverage, also experienced interannual variability, and mapping their trends allows detailed geographic information on exactly where the ice season lengthened and where it shortened. Over the 18 years, ice season lengthening occurred predominantly in the western hemisphere and was strongest in the western Labrador Sea, while ice season shortening occurred predominantly in the eastern hemisphere and was strongest in the eastern Barents Sea. Much information about other important Arctic sea ice variables has also been obtained from satellite data, including information about melt ponding, temperature, snow cover, and ice velocities. For instance, maps of ice velocities have now been made from satellite scatterometry data, including information about melt ponding, temperature, snow cover, and ice velocities. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C33B0782T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C33B0782T">Radiative transfer model of snow for bare ice regions</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Tanikawa, T.; Aoki, T.; Niwano, M.; Hosaka, M.; Shimada, R.; Hori, M.; Yamaguchi, S. 2016-12-01 Modeling a radiative transfer (RT) for coupled atmosphere-snow-bare ice systems is of fundamental importance for remote sensing applications to monitor snow and bare ice regions in the Greenland ice sheet and for accurate climate change predictions by regional and global climate models. Recently, the RT model for atmosphere-snow system was implemented for our regional and global climate models. However, the bare ice region where recently it has been expanded on the Greenland ice sheet due to the global warming, has not been implemented for these models, implying that this region leads miscalculations in these climate models. Thus, the RT model of snow for bare ice regions is needed for accurate climate change predictions. We developed the RT model for coupled atmosphere-snow-bare ice systems, and conducted a sensitivity analysis of the RT model to know the effect of snow, bare ice and geometry parameters on the spectral radiant quantities. The RT model considers snow and bare-ice inherent optical properties (IOPs), including snow grain size, air bubble size and its concentration and bare ice thickness. The conventional light scattering theory, Mie theory, was used for IOP calculations. Monte Carlo method was used for the multiple scattering. The sensitivity analyses showed that spectral albedo for the bare ice increased with increasing the concentration of the air bubble in the bare ice for visible wavelengths because the air bubble is scatterer with no absorption. For near infrared wavelengths, spectral albedo has no dependence on the air bubble due to the strong light absorption by ice. When increasing solar zenith angle, the spectral albedo were increased for all wavelengths. This is the similar trend with spectral snow albedo. Cloud cover influenced the bare ice spectral albedo by covering direct radiation into diffuse radiation. The purely diffuse radiation has an effective solar zenith angle near 50°. Converting direct into diffuse radiation reduces the </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.C24A..08P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.C24A..08P">Global mountain snow and ice loss driven by dust and black carbon radiative forcing</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Painter, T. H. 2014-12-01 Changes in mountain snow and glaciers have been our strongest indicators of the effects of changing climate. Earlier melt of snow and losses of glacier mass have perturbed regional water cycling, regional climate, and ecosystem dynamics, and contributed strongly to sea level rise. Recent studies however have revealed that in some regions, the reduction of albedo by light absorbing impurities in snow and ice such as dust and black carbon can be distinctly more powerful than regional warming at melting snow and ice. In the Rocky Mountains, dust deposition has increased 5 to 7 fold in the last 150 years, leading to ~3 weeks earlier loss of snow cover from forced melt. In absolute terms, in some years dust radiative forcing there can shorten snow cover duration by nearly two months. Remote sensing retrievals are beginning to reveal powerful dust and black carbon radiative forcing in the Hindu Kush through Himalaya. In light of recent ice cores that show pronounced increases in loading of dust and BC during the Anthropocene, these forcings may have contributed far more to glacier retreat than previously thought. For example, we have shown that the paradoxical end of the Little Ice Age in the European Alps beginning around 1850 (when glaciers began to retreat but temperatures continued to decline and precipitation was unchanged) very likely was driven by the massive increases in deposition to snow and ice of black carbon from industrialization in surrounding nations. A more robust understanding of changes in mountain snow and ice during the Anthropocene requires that we move past simplistic treatments (e.g. temperature-index modeling) to energy balance approaches that assess changes in the individual forcings such as the most powerful component for melt - net solar radiation. Remote sensing retrievals from imaging spectrometers and multispectral sensors are giving us more powerful insights into the time-space variation of snow and ice albedo. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20030062791','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20030062791">First Moderate Resolution Imaging Spectroradiometer (MODIS) Snow and Ice Workshop</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Hall, Dorothy K. (Editor) 1995-01-01 This document is a compilation of summaries of talks presented at a 2-day workshop on Moderate Resolution maging Spectroradiometer (MODIS) snow and ice products. The objectives of the workshop were to: inform the snow and ce community of potential MODIS products, seek advice from the participants regarding the utility of the products, and letermine the needs for future post-launch MODIS snow and ice products. Four working groups were formed to discuss at-launch snow products, at-launch ice products, post-launch snow and ice products and utility of MODIS snow and ice products, respectively. Each working group presented recommendations at the conclusion of the workshop. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19870007751&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=19870007751&hterms=helicopter+sea&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dhelicopter%2Bsea">An inter-sensor comparison of the microwave signatures of Arctic sea ice</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Onstott, R. G. 1986-01-01 Active and passive microwave and physical properties of Arctic sea ice in the marginal ice zone were measured during the summer. Results of an intercomparison of data acquired by an aircraft synthetic aperture radar, a passive microwave imager and a helicopter-mounted scatterometer indicate that early-to-mid summer sea ice microwave signatures are dominated by snowpack characteristics. Measurements show that the greatest contrast between thin first-year and multiyear sea ice occurs when operating actively between 5 and 10 GHz. Significant information about the state of melt of snow and ice is contained in the active and passive microwave signatures. </li> <li> <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">Modeling of Antarctic Sea Ice in a General Circulation Model.</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Wu, Xingren; Simmonds, Ian; Budd, W. F. 1997-04-01 A dynamic-thermodynamic sea ice model is developed and coupled with the Melbourne University general circulation model to simulate the seasonal cycle of the Antarctic sea ice distribution. The model is efficient, rapid to compute, and useful for a range of climate studies. The thermodynamic part of the sea ice model is similar to that developed by Parkinson and Washington, the dynamics contain a simplified ice rheology that resists compression. The thermodynamics is based on energy conservation at the top surface of the ice/snow, the ice/water interface, and the open water area to determine the ice formation, accretion, and ablation. A lead parameterization is introduced with an effective partitioning scheme for freezing between and under the ice floes. The dynamic calculation determines the motion of ice, which is forced with the atmospheric wind, taking account of ice resistance and rafting. The simulated sea ice distribution compares reasonably well with observations. The seasonal cycle of ice extent is well simulated in phase as well as in magnitude. Simulated sea ice 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 sea ice distribution. </li> <li> <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">Modeling of Antarctic sea ice in a general circulation model</a> <a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Wu, Xingren; Budd, W.F.; Simmonds, I. 1997-04-01 A dynamic-thermodynamic sea ice model is developed and coupled with the Melbourne University general circulation model to simulate the seasonal cycle of the Antarctic sea ice distributions The model is efficient, rapid to compute, and useful for a range of climate studies. The thermodynamic part of the sea ice model is similar to that developed by Parkinson and Washington, the dynamics contain a simplified ice rheology that resists compression. The thermodynamics is based on energy conservation at the top surface of the ice/snow, the ice/water interface, and the open water area to determine the ice formation, accretion, and ablation. Amore » lead parameterization is introduced with an effective partitioning scheme for freezing between and under the ice floes. The dynamic calculation determines the motion of ice, which is forced with the atmospheric wind, taking account of ice resistance and rafting. The simulated sea ice distribution compares reasonably well with observations. The seasonal cycle of ice extent is well simulated in phase as well as in magnitude. Simulated sea ice 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 sea ice distribution. 64 refs., 15 figs., 2 tabs.« less </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFM.C31A0435M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFM.C31A0435M">Help, I don’t know which sea ice algorithm to use?!: Developing an authoritative sea ice climate data record</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Meier, W.; Stroeve, J.; Duerr, R. E.; Fetterer, F. M. 2009-12-01 The declining Arctic sea ice 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 sea ice data is expanding well beyond the sea ice community. The most comprehensive sea ice data are from a series of satellite-borne passive microwave sensors. They provide a near-complete daily timeseries of sea ice 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 ice edge determination and lack of small-scale detail (e.g., lead detection) within the ice pack; surface melt depresses concentration values during summer; thin ice 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 sea ice concentration products and outline the future steps needed to complete a sea ice climate data record. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19980021232','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19980021232">Sea Ice on the Southern Ocean</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Jacobs, Stanley S. 1998-01-01 Year-round satellite records of sea ice 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 sea ice. In the Amundsen & Bellingshausen Seas, sea ice 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 sea ice 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 ice thickness, with attendant impacts upon vertical heat flux and the formation of snow ice and brine. The cause of the regional warming and loss of sea ice 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 Sea, ice extent fluctuates over periods of several years, with summer minima and winter maxima roughly in phase. This leads to large interannual cycles of sea ice 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C41A0644M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C41A0644M">Modelling of Sea Ice Thermodynamics and Biogeochemistry during the N-ICE2015 Expedition in the Arctic Ocean</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. 2016-12-01 Changes in the sea ice regime of the Arctic Ocean over the last decades from a thick perennial multiyear ice to a first year ice have been well documented. These changes in the sea ice regime will affect feedback mechanisms between the sea ice, atmosphere and ocean. Here we evaluate the performance of the Los Alamos Sea Ice Model (CICE), a state of the art sea ice model, to predict sea ice 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 sea Ice (N-ICE-2015) expedition north of Svalbard opens the possibility to properly test CICE. Oceanographic, atmospheric, sea ice, snow, and biological data were collected above, on, and below the ice using R/V Lance as the base for the ice camps that were drifting south towards the Fram Strait. Over six months, four different drifts took place, from the Nansen Basin, through the marginal ice zone, to the open ocean. Obtained results from the model show a good performance regarding ice thickness, salinity and temperature. Nutrients and sea ice 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2003PhDT........41T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2003PhDT........41T">Measurement and evolution of the thickness distribution and morphology of deformed features of Antarctic sea ice</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Tin, Tina Antarctic sea ice thickness data obtained from drilling on sea ice floes were examined with the goal of enhancing our capability to estimate ice thickness remotely, especially from air- or space-borne altimetry and shipboard visual observations. The state of hydrostatic equilibrium of deformed ice features and the statistical relationships between ice thickness and top surface roughness were examined. Results indicate that ice thickness may be estimated fairly reliably from surface measurements of snow elevation on length scales of ≥100 m. Examination of the morphology of deformed ice features show that Antarctic pressure ridges are flatter and less massive than Arctic pressure ridges and that not all surface features (ridge sails) are associated with features underwater (ridge keels). I propose that the differences in morphology are due to differences in sampling strategies, parent ice characteristics and the magnitude and duration of driving forces. As a result of these findings, the existing methodology used to estimate ice thickness from shipboard visual observations was modified to incorporate the probability that a sail is associated with a keel underwater, and the probability that keels may be found under level surfaces. Using the improved methodology, ice thickness was estimated from ship observations data obtained during two cruises in the Ross Sea, Antarctica. The dynamic and thermodynamic processes involved in the development of the ice prior to their observation were examined employing a regional sea ice-mixed layer-pycnocline model. Both our model results and previously published ice core data indicate that thermodynamic thickening is the dominant process that determines the thickness of first year ice in the central Ross Sea, although dynamic thickening also plays a significant role. Ice core data also indicate that snow ice forms a significant proportion of the total ice mass. For ice in the northeast Ross Sea in the summer, model results and </li> <li> <a target="_blank" onclick="trackOutboundLink('https://pubs.usgs.gov/of/2010/1176/','USGSPUBS'); return false;" href="https://pubs.usgs.gov/of/2010/1176/">Arctic sea ice decline: Projected changes in timing and extent of sea ice in the Bering and Chukchi Seas</a> <a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1996JGR...101.1163Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1996JGR...101.1163Z">Modeling the heating and melting of sea ice through light absorption by microalgae</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Zeebe, Richard E.; Eicken, Hajo; Robinson, Dale H.; Wolf-Gladrow, Dieter; Dieckmann, Gerhard S. 1996-01-01 In sea ice of polar regions, high concentrations of microalgae are observed during the spring. Algal standing stocks may attain peak values of over 300 mg chl a m-2 in the congelation ice habitat. As of yet, the effect of additional heating of sea ice through conversion of solar radiation into heat by algae has not been investigated in detail. Local effects, such as a decrease in albedo, increasing melt rates, and a decrease of the physical strength of ice sheets may occur. To investigate the effects of microalgae on the thermal regime of sea ice, a time-dependent, one-dimensional thermodynamic model of sea ice was coupled to a bio-optical model. A spectral one-stream model was employed to determine spectral attenuation by snow, sea ice, and microalgae. Beer's law was assumed to hold for every wavelength. Energy absorption was obtained by calculating the divergence of irradiance in every layer of the model (Δz = 1 cm). Changes in sea ice temperature profiles were calculated by solving the heat conduction equation with a finite difference scheme. Model results indicate that when algal biomass is concentrated at the bottom of congelation ice, melting of ice resulting from the additional conversion of solar radiation into heat may effectively destroy the algal habitat, thereby releasing algal biomass into the water column. An algal layer located in the top of the ice sheet induced a significant increase in sea ice temperature (ΔT > 0.3 K) for snow depths less than 5 cm and algal standing stocks higher than 150 mg chl a m-2. Furthermore, under these conditions, brine volume increased by 21% from 181 to 219 parts per thousand, which decreased the physical strength of the ice. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JGRG..122.1486K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JGRG..122.1486K">Windows in Arctic sea ice: Light transmission and ice algae in a refrozen lead</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19900017843','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19900017843">Applications of ISES for snow, ice, and sea state</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Chang, Alfred T. C.; Delnore, Victor E. 1990-01-01 There will be six facility instruments on the NASA NPOP-1 and NPOP-2 and additional instruments on the Japanese and European satellites. Also, there are the 24 selected NASA instruments that may be flown on one of the platforms. Many of these instruments can provide data that could be very useful for real-time data studies in the snow and ice area. Any one instrument is not addressed in particular, but emphasis is placed on what is potentially possible using the capabilities of some of these instruments. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25837523','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25837523">The contribution of mycosporine-like amino acids, chromophoric dissolved organic matter and particles to the UV protection of sea-ice organisms in the Baltic Sea.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Piiparinen, Jonna; Enberg, Sara; Rintala, Janne-Markus; Sommaruga, Ruben; Majaneva, Markus; Autio, Riitta; Vähätalo, Anssi V 2015-05-01 The effects of ultraviolet radiation (UVR) on the synthesis of mycosporine-like amino acids (MAAs) in sea-ice communities and on the other UV-absorption properties of sea ice were studied in a three-week long in situ experiment in the Gulf of Finland, Baltic Sea in March 2011. The untreated snow-covered ice and two snow-free ice treatments, one exposed to wavelengths > 400 nm (PAR) and the other to full solar spectrum (PAR + UVR), were analysed for MAAs and absorption coefficients of dissolved (aCDOM) and particulate (ap) fractions, the latter being further divided into non-algal (anap) and algal (aph) components. Our results showed that the diatom and dinoflagellate dominated sea-ice algal community responded to UVR down to 25-30 cm depth by increasing their MAA : chlorophyll-a ratio and by extending the composition of MAA pool from shinorine and palythine to porphyra-334 and an unknown compound with absorption peaks at ca. 335 and 360 nm. MAAs were the dominant absorbing components in algae in the top 10 cm of ice, and their contribution to total absorption became even more pronounced under UVR exposure. In addition to MAAs, the high absorption by chromophoric dissolved organic matter (CDOM) and by deposited atmospheric particles provided UV-protection for sea-ice organisms in the exposed ice. Efficient UV-protection will especially be of importance under the predicted future climate conditions with more frequent snow-free conditions. </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">10</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> <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">11</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> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.C13F0701S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.C13F0701S">2009/2010 Eurasian Cold Winter and Loss of Arctic Sea-ice over Barents/Kara Sea</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Shim, T.; Kim, B.; Kim, S. 2012-12-01 In 2009/2010 winter, a few extreme cold events and heavy snowfall occurred over central North America, north western Europe, and East Asia exerting a severe social and economic impacts. In this study, we performed modeling experiments to examine the role of substantially reduced Arctic sea-ice over Barents/Kara Sea on the 2009/2010 cold winters. Although several previous studies investigated cause of the extreme events and emphasized the large snow-covered area over Siberia in autumn 2009, we note that the area extent of Arctic sea-ice over Barents/Kara sea in autumn 2009 was anomalously low and the possible impact from Arctic for the extreme cold events has not been presented. To investigate the influence from the Arctic, we designed three model runs using Community Atmosphere Model Version 3 (CAM3). Each simulation differs by the prescribed surface boundary conditions: (a) CTRL - climatological seasonal cycle of sea surface temperature (SST) and sea-ice concentration (SIC) are prescribed everywhere, (b) EXP_65N - SST and SIC inside the Arctic circle (north of 65°N) are replaced by 2009/2010 values. Elsewhere, the climatology is used, (c) EXP_BK - Same with (b) except that SIC and SST are fixed only over Barents/Kara Sea where the sea-ice area dropped significantly in 2009/2010 winter. Model results from EXP_65N and EXP_BK commonly showed a large increase of air temperature in the lower troposphere where Arctic sea-ice showed a large reduction. Also, compared with the observation, model successfully captured thickened geopotential height in the Arctic and showed downstream wave propagation toward midlatitude. From the analysis, we reveal that this large dipolar Arctic-midlatitude teleconnection pattern in the upper troposphere easily propagate upward and played a role in the weakening of polar vortex. This is also confirmed in the observation. However, the timing of excitation of upward propagating wave in EXP_65N and EXP_BK were different and thus the timing of </li> <li> <a target="_blank" onclick="trackOutboundLink('https://pubs.usgs.gov/fs/2012/3131/pdf/fs20123131.pdf','USGSPUBS'); return false;" href="https://pubs.usgs.gov/fs/2012/3131/pdf/fs20123131.pdf">Polar bear and walrus response to the rapid decline in Arctic sea ice</a> <a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Oakley, K.; Whalen, M.; Douglas, David C.; Udevitz, Mark S.; Atwood, Todd C.; Jay, C. 2012-01-01 The Arctic is warming faster than other regions of the world due to positive climate feedbacks associated with loss of snow and ice. One highly visible consequence has been a rapid decline in Arctic sea ice over the past 3 decades - a decline projected to continue and result in ice-free summers likely as soon as 2030. The polar bear (Ursus maritimus) and the Pacific walrus (Odobenus rosmarus divergens) are dependent on sea ice over the continental shelves of the Arctic Ocean's marginal seas. The continental shelves are shallow regions with high biological productivity, supporting abundant marine life within the water column and on the sea floor. Polar bears use sea ice as a platform for hunting ice seals; walruses use sea ice as a resting platform between dives to forage for clams and other bottom-dwelling invertebrates. How have sea ice changes affected polar bears and walruses? How will anticipated changes affect them in the future? </li> <li> <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">Tropospheric characteristics over sea ice during N-ICE2015</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Kayser, Markus; Maturilli, Marion; Graham, Robert; Hudson, Stephen; Cohen, Lana; Rinke, Annette; Kim, Joo-Hong; Park, Sang-Jong; Moon, Woosok; Granskog, Mats 2017-04-01 Over recent years, the Arctic Ocean region has shifted towards a younger and thinner sea-ice regime. The Norwegian young sea ICE (N-ICE2015) expedition was designed to investigate the atmosphere-snow-ice-ocean interactions in this new ice regime north of Svalbard. Here we analyze upper-air measurements made by radiosondes launched twice daily together with surface meteorology observations during N-ICE2015 from January to June 2015. We study the multiple cyclonic events observed during N-ICE2015 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-ICE2015 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C32B..03N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C32B..03N">Seasonality of light transmittance through Arctic sea ice during spring and summe</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Nicolaus, M.; Hudson, S. R.; Granskog, M. A.; Pavlov, A.; Taskjelle, T.; Kauko, H.; Katlein, C.; Geland, S.; Perovich, D. K. 2017-12-01 The energy budget of sea ice and the upper ocean during spring, summer, and autumn is strongly affected by the transfer of solar shortwave radiation through sea ice and into the upper ocean. Previous studies highlighted the great importance of the spring-summer transition, when incoming fluxes are highest and even small changes in surface albedo and transmittance have strong impacts on the annual budgets. The timing of melt onset and changes in snow and ice conditions are also crucial for primary productivity and biogeochemical processes. Here we present results from time series measurements of radiation fluxes through seasonal Arctic sea ice, as it may be expected to play a key role in the future Arctic. Our observations were performed during the Norwegian N-ICE drift experiment in 2015 and the Polarstern expedition PS106 in 2017, both studying sea ice north of Svalbard. Autonomous stations were installed to monitor spectral radiation fluxes above and under sea ice. The observation periods cover the spring-summer transition, including snow melt and early melt pond formation. The results show the direct relation of optical properties to under ice algae blooms and their influence on the energy budget. Beyond these results, we will discuss the latest plans and implementation of radiation measurements during the MOSAiC drift in 2019/2020. Then, a full annual cycle of radiation fluxes may be studied from manned and autonomous (buoys) measurements as well as using a remotely operated vehicle (ROV) as measurement platform. These measurements will be performed in direct relation with numerical simulations on different scales. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C51A0953Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C51A0953Y">Comparing elevation and freeboard from IceBridge and four different CryoSat-2 retrackers for coincident sea ice observations</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Yi, D.; Kurtz, N. T.; Harbeck, J. 2017-12-01 The airborne IceBridge and spaceborne Cryosat-2 missions observe polar sea ice at different altitudes with different footprint sizes and often at different time and locations. Many studies use different retrackers to derive Cryosat-2 surface elevation, which we find causes large differences in the elevation and freeboard comparisons of IceBridge and Cryosat-2. In this study, we compare sea ice surface elevation and freeboard using 8 coincident CryoSat-2, ATM, and LVIS observations with IceBridge airplanes under flying the Cryosat-2 ground tracks. We apply identical ellipsoid, geoid model, tide model, and atmospheric correction to CryoSat-2 and IceBridge data to reduce elevation bias due to their differences. IceBridge's ATM and LVIS elevation and freeboard and Snow Radar snow depth are averaged at each CryoSat-2 footprint for comparison. The four different Cryosat-2 retrackers (ESA, GSFC, AWI, and JPL) show distinct differences in mean elevation up to 0.35 meters over leads and over floes, which suggests that systematic elevation bias exists between the retrackers. The mean IceBridge elevation over leads is within the mean elevation distribution of the four Cryosat-2 retrackers. The mean IceBridge elevation over floes is above the mean elevation distribution of the four Cryosat-2 retrackers. After removing the snow depth from IceBridge elevation, over floe, the mean elevation of IceBridge is within the mean elevation distribution of the four Cryosat-2 retrackers. By identifying the strengths and weaknesses of the retrackers, this study provides a mechanism to improve freeboard retrievals from existing methods. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28715890','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28715890">Spring Melt and the Redistribution of Organochlorine Pesticides in the Sea-Ice Environment: A Comparative Study between Arctic and Antarctic Regions.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Bigot, Marie; Hawker, Darryl W; Cropp, Roger; Muir, Derek Cg; Jensen, Bjarne; Bossi, Rossana; Bengtson Nash, Susan M 2017-08-15 Complementary sampling of air, snow, sea-ice, and seawater for a range of organochlorine pesticides (OCPs) was undertaken through the early stages of respective spring sea-ice melting at coastal sites in northeast Greenland and eastern Antarctica to investigate OCP concentrations and redistribution during this time. Mean concentrations in seawater, sea-ice and snow were generally greater at the Arctic site. For example, α-HCH was found to have the largest concentrations of all analytes in Arctic seawater and sea-ice meltwater samples (224-253 and 34.7-48.2 pg·L -1 respectively compared to 1.0-1.3 and <0.63 pg·L -1 respectively for Antarctic samples). Differences in atmospheric samples were generally not as pronounced however. Findings suggest that sea-ice OCP burdens originate from both snow and seawater. The distribution profile between seawater and sea-ice showed a compound-dependency for Arctic samples not evident with those from the Antarctic, possibly due to full submersion of sea-ice at the former. Seasonal sea-ice melt processes may alter the exchange rates of selected OCPs between air and seawater, but are not expected to reverse their direction, which fugacity modeling indicates is volatilisation in the Arctic and net deposition in the Antarctic. These predictions are consistent with the limited current observations. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JGRD..12210855K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JGRD..12210855K">Vertical thermodynamic structure of the troposphere during the Norwegian young sea ICE expedition (N-ICE2015)</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Kayser, Markus; Maturilli, Marion; Graham, Robert M.; Hudson, Stephen R.; Rinke, Annette; Cohen, Lana; Kim, Joo-Hong; Park, Sang-Jong; Moon, Woosok; Granskog, Mats A. 2017-10-01 The Norwegian young sea ICE (N-ICE2015) expedition was designed to investigate the atmosphere-snow-ice-ocean interactions in the young and thin sea ice regime north of Svalbard. Radiosondes were launched twice daily during the expedition from January to June 2015. Here we use these upper air measurements to study the multiple cyclonic events observed during N-ICE2015 with respect to changes in the vertical thermodynamic structure, moisture content, and boundary layer characteristics. We provide statistics of temperature inversion characteristics, static stability, and boundary layer extent. During winter, when radiative cooling is most effective, we find the strongest impact of synoptic cyclones. Changes to thermodynamic characteristics of the boundary layer are associated with transitions between the radiatively "clear" and "opaque" atmospheric states. In spring, radiative fluxes warm the surface leading to lifted temperature inversions and a statically unstable boundary layer. Further, we compare the N-ICE2015 static stability distributions to corresponding profiles from ERA-Interim reanalysis, from the closest land station in the Arctic North Atlantic sector, Ny-Ålesund, and to soundings from the SHEBA expedition (1997/1998). We find similar stability characteristics for N-ICE2015 and SHEBA throughout the troposphere, despite differences in location, sea ice thickness, and snow cover. For Ny-Ålesund, we observe similar characteristics above 1000 m, while the topography and ice-free fjord surrounding Ny-Ålesund generate great differences below. The long-term radiosonde record (1993-2014) from Ny-Ålesund indicates that during the N-ICE2015 spring period, temperatures were close to the climatological mean, while the lowest 3000 m were 1-3°C warmer than the climatology during winter. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1325643','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1325643">Uncertainty quantification and global sensitivity analysis of the Los Alamos sea ice model</a> <a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Urrego-Blanco, Jorge Rolando; Urban, Nathan Mark; Hunke, Elizabeth Clare Changes in the high-latitude climate system have the potential to affect global climate through feedbacks with the atmosphere and connections with midlatitudes. Sea ice and climate models used to understand these changes have uncertainties that need to be characterized and quantified. We present a quantitative way to assess uncertainty in complex computer models, which is a new approach in the analysis of sea ice models. We characterize parametric uncertainty in the Los Alamos sea ice model (CICE) in a standalone configuration and quantify the sensitivity of sea ice area, extent, and volume with respect to uncertainty in 39 individual modelmore » parameters. Unlike common sensitivity analyses conducted in previous studies where parameters are varied one at a time, this study uses a global variance-based approach in which Sobol' sequences are used to efficiently sample the full 39-dimensional parameter space. We implement a fast emulator of the sea ice model whose predictions of sea ice extent, area, and volume are used to compute the Sobol' sensitivity indices of the 39 parameters. Main effects and interactions among the most influential parameters are also estimated by a nonparametric regression technique based on generalized additive models. A ranking based on the sensitivity indices indicates that model predictions are most sensitive to snow parameters such as snow conductivity and grain size, and the drainage of melt ponds. Lastly, it is recommended that research be prioritized toward more accurately determining these most influential parameter values by observational studies or by improving parameterizations in the sea ice model.« less </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1325643-uncertainty-quantification-global-sensitivity-analysis-los-alamos-sea-ice-model','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1325643-uncertainty-quantification-global-sensitivity-analysis-los-alamos-sea-ice-model">Uncertainty quantification and global sensitivity analysis of the Los Alamos sea ice model</a> <a target="_blank" href="http://www.osti.gov/pages">DOE PAGES</a> Urrego-Blanco, Jorge Rolando; Urban, Nathan Mark; Hunke, Elizabeth Clare; ... 2016-04-01 Changes in the high-latitude climate system have the potential to affect global climate through feedbacks with the atmosphere and connections with midlatitudes. Sea ice and climate models used to understand these changes have uncertainties that need to be characterized and quantified. We present a quantitative way to assess uncertainty in complex computer models, which is a new approach in the analysis of sea ice models. We characterize parametric uncertainty in the Los Alamos sea ice model (CICE) in a standalone configuration and quantify the sensitivity of sea ice area, extent, and volume with respect to uncertainty in 39 individual modelmore » parameters. Unlike common sensitivity analyses conducted in previous studies where parameters are varied one at a time, this study uses a global variance-based approach in which Sobol' sequences are used to efficiently sample the full 39-dimensional parameter space. We implement a fast emulator of the sea ice model whose predictions of sea ice extent, area, and volume are used to compute the Sobol' sensitivity indices of the 39 parameters. Main effects and interactions among the most influential parameters are also estimated by a nonparametric regression technique based on generalized additive models. A ranking based on the sensitivity indices indicates that model predictions are most sensitive to snow parameters such as snow conductivity and grain size, and the drainage of melt ponds. Lastly, it is recommended that research be prioritized toward more accurately determining these most influential parameter values by observational studies or by improving parameterizations in the sea ice model.« less </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JGRC..121.2709U','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JGRC..121.2709U">Uncertainty quantification and global sensitivity analysis of the Los Alamos sea ice model</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Urrego-Blanco, Jorge R.; Urban, Nathan M.; Hunke, Elizabeth C.; Turner, Adrian K.; Jeffery, Nicole 2016-04-01 Changes in the high-latitude climate system have the potential to affect global climate through feedbacks with the atmosphere and connections with midlatitudes. Sea ice and climate models used to understand these changes have uncertainties that need to be characterized and quantified. We present a quantitative way to assess uncertainty in complex computer models, which is a new approach in the analysis of sea ice models. We characterize parametric uncertainty in the Los Alamos sea ice model (CICE) in a standalone configuration and quantify the sensitivity of sea ice area, extent, and volume with respect to uncertainty in 39 individual model parameters. Unlike common sensitivity analyses conducted in previous studies where parameters are varied one at a time, this study uses a global variance-based approach in which Sobol' sequences are used to efficiently sample the full 39-dimensional parameter space. We implement a fast emulator of the sea ice model whose predictions of sea ice extent, area, and volume are used to compute the Sobol' sensitivity indices of the 39 parameters. Main effects and interactions among the most influential parameters are also estimated by a nonparametric regression technique based on generalized additive models. A ranking based on the sensitivity indices indicates that model predictions are most sensitive to snow parameters such as snow conductivity and grain size, and the drainage of melt ponds. It is recommended that research be prioritized toward more accurately determining these most influential parameter values by observational studies or by improving parameterizations in the sea ice model. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C41B0700O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C41B0700O">Light Absorption in Arctic Sea Ice - Black Carbon vs Chlorophyll</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Ogunro, O. O.; Wingenter, O. W.; Elliott, S.; Hunke, E. C.; Flanner, M.; Wang, H.; Dubey, M. K.; Jeffery, N. 2015-12-01 The fingerprint of climate change is more obvious in the Arctic than any other place on Earth. This is not only because the surface temperature there has increased at twice the rate of global mean temperature but also because Arctic sea ice extent has reached a record low of 49% reduction relative to the 1979-2000 climatology. Radiation absorption through black carbon (BC) deposited on Arctic snow and sea ice surface is one of the major hypothesized contributors to the decline. However, we note that chlorophyll-a absorption owing to increasing biology activity in this region could be a major competitor during boreal spring. Modeling of sea-ice physical and biological processes together with experiments and field observations promise rapid progress in the quality of Arctic ice predictions. Here we develop a dynamic ice system module to investigate discrete absorption of both BC and chlorophyll in the Arctic, using BC deposition fields from version 5 of Community Atmosphere Model (CAM5) and vertically distributed layers of chlorophyll concentrations from Sea Ice Model (CICE). To this point, our black carbon mixing ratios compare well with available in situ data. Both results are in the same order of magnitude. Estimates from our calculations show that sea ice and snow around the Canadian Arctic Archipelago and Baffin Bay has the least black carbon absorption while values at the ice-ocean perimeter in the region of the Barents Sea peak significantly. With regard to pigment concentrations, high amounts of chlorophyll are produced in Arctic sea ice by the bottom microbial community, and also within the columnar pack wherever substantial biological activity takes place in the presence of moderate light. We show that the percentage of photons absorbed by chlorophyll in the spring is comparable to the amount attributed to BC, especially in areas where the total deposition rates are decreasing with time on interannual timescale. We expect a continuous increase in </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010JGRD..11522112S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010JGRD..11522112S">Synoptic controls on precipitation pathways and snow delivery to high-accumulation ice core sites in the Ross Sea region, Antarctica</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Sinclair, K. E.; Bertler, N. A. N.; Trompetter, W. J. 2010-11-01 Dominant storm tracks to two ice core sites on the western margin of the Ross Sea, Antarctica (Skinner Saddle (SKS) and Evans Piedmont Glacier), are investigated to establish key synoptic controls on snow accumulation. This is critical in terms of understanding the seasonality, source regions, and transport pathways of precipitation delivered to these sites. In situ snow depth and meteorological observations are used to identify major accumulation events in 2007-2008, which differ considerably between sites in terms of their magnitude and seasonal distribution. While snowfall at Evans Piedmont Glacier occurs almost exclusively during summer and spring, Skinner Saddle receives precipitation year round with a lull during the months of April and May. Cluster analysis of daily back trajectories reveals that the highest-accumulation days at both sites result from fast-moving air masses, associated with synoptic-scale low-pressure systems. There is evidence that short-duration pulses of snowfall at SKS also originate from mesocyclone development over the Ross Ice Shelf and local moisture sources. Changes in the frequency and seasonal distribution of these mechanisms of precipitation delivery will have a marked impact on annual accumulation over time and will therefore need careful consideration during the interpretation of stable isotope and geochemical records from these ice cores. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ACP....17.8577H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ACP....17.8577H">Frost flowers and sea-salt aerosols over seasonal sea-ice areas in northwestern Greenland during winter-spring</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Hara, Keiichiro; Matoba, Sumito; Hirabayashi, Motohiro; Yamasaki, Tetsuhide 2017-07-01 Sea salts and halogens in aerosols, frost flowers, and brine play an important role in atmospheric chemistry in polar regions. Simultaneous sampling and observations of frost flowers, brine, and aerosol particles were conducted around Siorapaluk in northwestern Greenland during December 2013 to March 2014. Results show that water-soluble frost flower and brine components are sea-salt components (e.g., Na+, Cl-, Mg2+, K+, Ca2+, Br-, and iodine). Concentration factors of sea-salt components of frost flowers and brine relative to seawater were 1.14-3.67. Sea-salt enrichment of Mg2+, K+, Ca2+, and halogens (Cl-, Br-, and iodine) in frost flowers is associated with sea-salt fractionation by precipitation of mirabilite and hydrohalite. High aerosol number concentrations correspond to the occurrence of higher abundance of sea-salt particles in both coarse and fine modes, and blowing snow and strong winds. Aerosol number concentrations, particularly in coarse mode, are increased considerably by release from the sea-ice surface under strong wind conditions. Sulfate depletion by sea-salt fractionation was found to be limited in sea-salt aerosols because of the presence of non-sea-salt (NSS) SO42-. However, coarse and fine sea-salt particles were found to be rich in Mg. Strong Mg enrichment might be more likely to proceed in fine sea-salt particles. Magnesium-rich sea-salt particles might be released from the surface of snow and slush layer (brine) on sea ice and frost flowers. Mirabilite-like and ikaite-like particles were identified only in aerosol samples collected near new sea-ice areas. From the field evidence and results from earlier studies, we propose and describe sea-salt cycles in seasonal sea-ice areas. </li> <li> <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">Sea Ice in McClure Strait</a> <a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a> 2017-12-08 NASA image acquired August 17, 2010 In mid-August 2010, the Northwest Passage was almost—but not quite—free of ice. The ice content in the northern route through the passage (through the Western Parry Channel) was very light, but ice 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 ice-free, immediately west of Prince Patrick Island, a band of sea ice stretches southward across the strait (left edge of the image). The National Snow and Ice Data Center Sea Ice News and Analysis blog reported that even more ice remained in the southern route (through Amundsen’s Passage) of the Northwest Passage in mid-August 2010. Nevertheless, the ice 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 sea ice set a record low. As of mid-August 2010, however, overall sea ice 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015ACP....15.8457O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015ACP....15.8457O">X-ray computed microtomography of sea ice - comment on "A review of air-ice chemical and physical interactions (AICI): liquids, quasi-liquids, and solids in snow" by Bartels-Rausch et al. (2014)</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Obbard, R. W. 2015-07-01 This comment addresses a statement made in "A review of air-ice chemical and physical interactions (AICI): liquids, quasi-liquids, and solids in snow" by Bartels-Rausch et al. (Atmos. Chem. Phys., 14, 1587-1633, <a href="http://dx.doi.org/10.5194/acp-14-1587-2014"target="_blank"> doi:10.5194/acp-14-1587-2014</a>, 2014). Here we rebut the assertion that X-ray computed microtomography of sea ice fails to reveal liquid brine inclusions by discussing the phases present at the analysis temperature. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009EGUGA..11.1821W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009EGUGA..11.1821W">Satellite microwave observations of the interannual variability of snowmelt on sea ice in the Southern Ocean</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Willmes, S.; Haas, C.; Nicolaus, M.; Bareiss, J. 2009-04-01 Snowmelt processes on Antarctic sea ice are examined. We present a simple snowmelt indicator based on diurnal brightness temperature variations from microwave satellite data. The method is validated through extensive field data from the western Weddell Sea and lends itself to the investigation of interannual and spatial variations of the typical snowmelt on Antarctic sea ice. We use in situ measurements of physical snow properties to show that despite the absence of strong melting, the summer period is distinct from all other seasons with enhanced diurnal variations of snow wetness. A microwave emission model reveals that repeated thawing and refreezing causes the typical microwave emissivity signatures that are found on perennial Antarctic sea ice during summer. The proposed melt indicator accounts for the characteristic phenomenological stages of snowmelt in the Southern Ocean and detects the onset of diurnal snow wetting. An algorithm is presented to map large-scale snowmelt onset, based on satellite data from the period between 1988 and 2006. The results indicate strong meridional gradients of snowmelt onset with the Weddell, Amundsen and Ross Seas showing earliest (beginning of October) and most frequent snowmelt. Moreover, a distinct interannual variability of melt onset dates and large areas of first-year ice where no diurnal freeze-thawing occurs at the surface are determined. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009JGRC..114.3006W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009JGRC..114.3006W">Satellite microwave observations of the interannual variability of snowmelt on sea ice in the Southern Ocean</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Willmes, Sascha; Haas, Christian; Nicolaus, Marcel; Bareiss, JöRg 2009-03-01 Snowmelt processes on Antarctic sea ice are examined. We present a simple snowmelt indicator based on diurnal brightness temperature variations from microwave satellite data. The method is validated through extensive field data from the western Weddell Sea and lends itself to the investigation of interannual and spatial variations of the typical snowmelt on Antarctic sea ice. We use in-situ measurements of physical snow properties to show that despite the absence of strong melting, the summer period is distinct from all other seasons with enhanced diurnal variations of snow wetness. A microwave emission model reveals that repeated thawing and refreezing cause the typical microwave emissivity signatures that are found on perennial Antarctic sea ice during summer. The proposed melt indicator accounts for the characteristic phenomenological stages of snowmelt in the Southern Ocean and detects the onset of diurnal snow wetting. An algorithm is presented to map large-scale snowmelt onset based on satellite data from the period between 1988 and 2006. The results indicate strong meridional gradients of snowmelt onset with the Weddell, Amundsen, and Ross Seas showing earliest (beginning of October) and most frequent snowmelt. Moreover, a distinct interannual variability of melt onset dates and large areas of first-year ice where no diurnal freeze thawing occurs at the surface are determined. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C41D0732M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C41D0732M">Object-Based Arctic Sea Ice Feature Extraction through High Spatial Resolution Aerial photos</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Miao, X.; Xie, H. 2015-12-01 High resolution aerial photographs used to detect and classify sea ice features can provide accurate physical parameters to refine, validate, and improve climate models. However, manually delineating sea ice features, such as melt ponds, submerged ice, water, ice/snow, and pressure ridges, is time-consuming and labor-intensive. An object-based classification algorithm is developed to automatically extract sea ice features efficiently from aerial photographs taken during the Chinese National Arctic Research Expedition in summer 2010 (CHINARE 2010) in the MIZ near the Alaska coast. The algorithm includes four steps: (1) the image segmentation groups the neighboring pixels into objects based on the similarity of spectral and textural information; (2) the random forest classifier distinguishes four general classes: water, general submerged ice (GSI, including melt ponds and submerged ice), shadow, and ice/snow; (3) the polygon neighbor analysis separates melt ponds and submerged ice based on spatial relationship; and (4) pressure ridge features are extracted from shadow based on local illumination geometry. The producer's accuracy of 90.8% and user's accuracy of 91.8% are achieved for melt pond detection, and shadow shows a user's accuracy of 88.9% and producer's accuracies of 91.4%. Finally, pond density, pond fraction, ice floes, mean ice concentration, average ridge height, ridge profile, and ridge frequency are extracted from batch processing of aerial photos, and their uncertainties are estimated. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20080030194&hterms=climate+change+evidence&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dclimate%2Bchange%2Bevidence','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20080030194&hterms=climate+change+evidence&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dclimate%2Bchange%2Bevidence">Remote Sensing of Terrestrial Snow and Ice for Global Change Studies</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Kelly, Richard; Hall, Dorothy K. 2007-01-01 Snow and ice play a significant role in the Earth's water cycle and are sensitive and informative indicators climate change. Significant changes in terrestrial snow and ice water storage are forecast, and while evidence of large-scale changes is emerging, in situ measurements alone are insufficient to help us understand and explain these changes. Imaging remote sensing systems are capable of successfully observing snow and ice in the cryosphere. This chapter examines how those remote sensing sensors, that now have more than 35 years of observation records, are capable of providing information about snow cover, snow water equivalent, snow melt, ice sheet temperature and ice sheet albedo. While significant progress has been made, especially in the last five years, a better understanding is required of the records of satellite observations of these cryospheric variables. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C41B0701R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C41B0701R">The Relationship Between Arctic Sea Ice Albedo and the Geophysical Parameters of the Ice Cover</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Riihelä, A. 2015-12-01 The Arctic sea ice cover is thinning and retreating. Remote sensing observations have also shown that the mean albedo of the remaining ice 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 ice concentration and enhanced surface melt of the ice, remains an important research question for the forecasting of future conditions of the ice cover. A necessary step towards this goal is understanding the relationships between Arctic sea ice albedo and the geophysical parameters of the ice cover. Particularly the question of the relationship between sea ice albedo and ice age is both interesting and not widely studied. The recent changes in the Arctic sea ice zone have led to a substantial decrease of its multi-year sea ice, as old ice melts and is replaced by first-year ice during the next freezing season. It is generally known that younger sea ice tends to have a lower albedo than older ice because of several reasons, such as wetter snow cover and enhanced melt ponding. However, the quantitative correlation between sea ice age and sea ice 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 sea ice albedo relative to the geophysical parameters of the ice 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 sea ice albedo as a function of sea ice age are presented for the whole Arctic Ocean and for potentially interesting marginal sea cases. This allows us to see if the the albedo of the older sea </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">11</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> <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">12</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> <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">Transport of contaminants by Arctic sea ice and surface ocean currents</a> <a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Pfirman, S. 1995-12-31 Sea ice 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 Sea 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 ice during suspension freezing on the shelves, and by atmospheric deposition during drift. Ice releases its contaminant load through brinemore » drainage, surface runoff of snow and meltwater, and when the floe disintegrates. The marginal ice zone, a region of intense biological activity, may also be the site of major contaminant release. Potentially contaminated ice from the Kara Sea is likely to influence the marginal ice zones of the Barents and Greenland seas. From studies conducted to date it appears that sea ice from the Kara Sea does not typically enter the Beaufort Gyre, and thus is unlikely to affect the northern Canadian and Alaskan margins.« less </li> <li> <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">Ship-borne electromagnetic induction sounding of sea-ice thickness in the southern Sea of Okhotsk</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Uto, Shotaro; Toyota, Takenobu; Shimoda, Haruhito; Tateyama, Kazutaka; Shirasawa, Kunio Recent observations have revealed that dynamical thickening is dominant in the growth process of sea ice in the southern Sea of Okhotsk. That indicates the importance of understanding the nature of thick deformed ice in this area. The objective of the present paper is to establish a ship-based method for observing the thickness of deformed ice 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 ice in the southern Sea of Okhotsk, as a one-dimensional multilayered structure. Since 2004, the electromagnetic (EM) inductive sounding of sea-ice 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 ice + 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 ice. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.gpo.gov/fdsys/pkg/CFR-2010-title30-vol1/pdf/CFR-2010-title30-vol1-sec56-11016.pdf','CFR'); return false;" href="https://www.gpo.gov/fdsys/pkg/CFR-2010-title30-vol1/pdf/CFR-2010-title30-vol1-sec56-11016.pdf">30 CFR 56.11016 - Snow and ice on walkways and travelways.</a> <a target="_blank" href="http://www.gpo.gov/fdsys/browse/collectionCfr.action?selectedYearFrom=2010&page.go=Go">Code of Federal Regulations, 2010 CFR</a> 2010-07-01 ... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Snow and ice on walkways and travelways. 56... Travelways § 56.11016 Snow and ice on walkways and travelways. Regularly used walkways and travelways shall be sanded, salted, or cleared of snow and ice as soon as practicable. ... </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.gpo.gov/fdsys/pkg/CFR-2011-title30-vol1/pdf/CFR-2011-title30-vol1-sec56-11016.pdf','CFR2011'); return false;" href="https://www.gpo.gov/fdsys/pkg/CFR-2011-title30-vol1/pdf/CFR-2011-title30-vol1-sec56-11016.pdf">30 CFR 56.11016 - Snow and ice on walkways and travelways.</a> <a target="_blank" href="http://www.gpo.gov/fdsys/browse/collectionCfr.action?selectedYearFrom=2011&page.go=Go">Code of Federal Regulations, 2011 CFR</a> 2011-07-01 ... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Snow and ice on walkways and travelways. 56... Travelways § 56.11016 Snow and ice on walkways and travelways. Regularly used walkways and travelways shall be sanded, salted, or cleared of snow and ice as soon as practicable. ... </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.gpo.gov/fdsys/pkg/CFR-2012-title30-vol1/pdf/CFR-2012-title30-vol1-sec56-11016.pdf','CFR2012'); return false;" href="https://www.gpo.gov/fdsys/pkg/CFR-2012-title30-vol1/pdf/CFR-2012-title30-vol1-sec56-11016.pdf">30 CFR 56.11016 - Snow and ice on walkways and travelways.</a> <a target="_blank" href="http://www.gpo.gov/fdsys/browse/collectionCfr.action?selectedYearFrom=2012&page.go=Go">Code of Federal Regulations, 2012 CFR</a> 2012-07-01 ... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Snow and ice on walkways and travelways. 56... Travelways § 56.11016 Snow and ice on walkways and travelways. Regularly used walkways and travelways shall be sanded, salted, or cleared of snow and ice as soon as practicable. ... </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.gpo.gov/fdsys/pkg/CFR-2013-title30-vol1/pdf/CFR-2013-title30-vol1-sec56-11016.pdf','CFR2013'); return false;" href="https://www.gpo.gov/fdsys/pkg/CFR-2013-title30-vol1/pdf/CFR-2013-title30-vol1-sec56-11016.pdf">30 CFR 56.11016 - Snow and ice on walkways and travelways.</a> <a target="_blank" href="http://www.gpo.gov/fdsys/browse/collectionCfr.action?selectedYearFrom=2013&page.go=Go">Code of Federal Regulations, 2013 CFR</a> 2013-07-01 ... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Snow and ice on walkways and travelways. 56... Travelways § 56.11016 Snow and ice on walkways and travelways. Regularly used walkways and travelways shall be sanded, salted, or cleared of snow and ice as soon as practicable. ... </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.gpo.gov/fdsys/pkg/CFR-2014-title30-vol1/pdf/CFR-2014-title30-vol1-sec56-11016.pdf','CFR2014'); return false;" href="https://www.gpo.gov/fdsys/pkg/CFR-2014-title30-vol1/pdf/CFR-2014-title30-vol1-sec56-11016.pdf">30 CFR 56.11016 - Snow and ice on walkways and travelways.</a> <a target="_blank" href="http://www.gpo.gov/fdsys/browse/collectionCfr.action?selectedYearFrom=2014&page.go=Go">Code of Federal Regulations, 2014 CFR</a> 2014-07-01 ... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Snow and ice on walkways and travelways. 56... Travelways § 56.11016 Snow and ice on walkways and travelways. Regularly used walkways and travelways shall be sanded, salted, or cleared of snow and ice as soon as practicable. ... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013TCD.....7.6075R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013TCD.....7.6075R">Dynamic ikaite production and dissolution in sea ice - control by temperature, salinity and pCO2 conditions</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Rysgaard, S.; Wang, F.; Galley, R. J.; Grimm, R.; Lemes, M.; Geilfus, N.-X.; Chaulk, A.; Hare, A. A.; Crabeck, O.; Else, B. G. T.; Campbell, K.; Papakyriakou, T.; Sørensen, L. L.; Sievers, J.; Notz, D. 2013-12-01 Ikaite is a hydrous calcium carbonate mineral (CaCO3 · 6H2O). It is only found in a metastable state, and decomposes rapidly once removed from near-freezing water. Recently, ikaite crystals have been found in sea ice and it has been suggested that their precipitation may play an important role in air-sea CO2 exchange in ice-covered seas. Little is known, however, of the spatial and temporal dynamics of ikaite in sea ice. Here we present evidence for highly dynamic ikaite precipitation and dissolution in sea ice grown at an out-door pool of the Sea-ice Environmental Research Facility (SERF). During the experiment, ikaite precipitated in sea ice with temperatures below -3 °C, creating three distinct zones of ikaite concentrations: (1) a mm to cm thin surface layer containing frost flowers and brine skim with bulk concentrations of > 2000 μmol kg-1, (2) an internal layer with concentrations of 200-400 μmol kg-1 and (3) a~bottom layer with concentrations of < 100 μmol kg-1. Snowfall events caused the sea ice to warm, dissolving ikaite crystals under acidic conditions. Manual removal of the snow cover allowed the sea ice to cool and brine salinities to increase, resulting in rapid ikaite precipitation. The modeled (FREZCHEM) ikaite concentrations were in the same order of magnitude as observations and suggest that ikaite concentration in sea ice increase with decreasing temperatures. Thus, varying snow conditions may play a key role in ikaite precipitation and dissolution in sea ice. This will have implications for CO2 exchange with the atmosphere and ocean. </li> <li> <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">Spatial Variability of Barrow-Area Shore-Fast Sea Ice and Its Relationships to Passive Microwave Emissivity</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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"> 2006-01-01 Aircraft-acquired passive microwave data, laser radar height observations, RADARSAT synthetic aperture radar imagery, and in situ measurements obtained during the AMSR-Ice03 experiment are used to investigate relationships between microwave emission and ice characteristics over several space scales. The data fusion allows delineation of the shore-fast ice and pack ice in the Barrow area, AK, into several ice classes. Results show good agreement between observed and Polarimetric Scanning Radiometer (PSR)-derived snow depths over relatively smooth ice, with larger differences over ridged and rubbled ice. The PSR results are consistent with the effects on snow depth of the spatial distribution and nature of ice roughness, ridging, and other factors such as ice age. Apparent relationships exist between ice roughness and the degree of depolarization of emission at 10,19, and 37 GHz. This depolarization .would yield overestimates of total ice 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 sea ice and large contrast between sea ice and adjacent land, are also apparent in the PSR data. Overall, the results further demonstrate the importance of macroscale ice roughness conditions such as ridging and rubbling on snow depth and microwave emissivity. </li> <li> <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">Observed and Modeled Trends in Southern Ocean Sea Ice</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Parkinson, Claire L. 2003-01-01 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 ice 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 sea ice variations in the model calculations. Both sea ice thickness and sea ice extent decrease markedly in the doubled CO, case, thereby allowing the ice feedbacks to occur. Stand-alone sea ice models have shown Southern Ocean hemispherically averaged winter ice-edge retreats of 1.4 deg latitude for each 1 K increase in atmospheric temperatures. Observations, however, show a much more varied Southern Ocean ice cover, both spatially and temporally, than many of the modeled expectations. In fact, the satellite passive-microwave record of Southern Ocean sea ice since late 1978 has revealed overall increases rather than decreases in ice extents, with ice extent trends on the order of 11,000 sq km/year. When broken down spatially, the positive trends are strongest in the Ross Sea, while the trends are negative in the Bellingshausen/Amundsen Seas. Greater spatial detail can be obtained by examining trends in the length of the sea ice season, and those trends show a coherent picture of shortening sea ice seasons throughout almost the entire Bellingshausen and Amundsen Seas to the west of the Antarctic Peninsula and in the far western Weddell Sea immediately to the east of the Peninsula, with lengthening sea ice 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.7692A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.7692A">Timing and regional patterns of snowmelt on Antarctic sea ice from passive microwave satellite observations</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Arndt, Stefanie; Willmes, Sascha; Dierking, Wolfgang; Nicolaus, Marcel 2016-04-01 The better understanding of temporal variability and regional distribution of surface melt on Antarctic sea ice is crucial for the understanding of atmosphere-ocean interactions and the determination of mass and energy budgets of sea ice. Since large regions of Antarctic sea ice are covered with snow during most of the year, observed inter-annual and regional variations of surface melt mainly represents melt processes in the snow. It is therefore important to understand the mechanisms that drive snowmelt, both at different times of the year and in different regions around Antarctica. In this study we combine two approaches for observing both surface and volume snowmelt by means of passive microwave satellite data. The former is achieved by measuring diurnal differences of the brightness temperature TB at 37 GHz, the latter by analyzing the ratio TB(19GHz)/TB(37GHz). Moreover, we use both melt onset proxies to divide the Antarctic sea ice cover into characteristic surface melt patterns from 1988/89 to 2014/15. Our results indicate four characteristic melt types. On average, 43% of the ice-covered ocean shows diurnal freeze-thaw cycles in the surface snow layer, resulting in temporary melt (Type A), less than 1% shows continuous snowmelt throughout the snowpack, resulting in strong melt over a period of several days (Type B), 19% shows Type A and B taking place consecutively (Type C), and for 37% no melt is observed at all (Type D). Continuous melt is primarily observed in the outflow of the Weddell Gyre and in the northern Ross Sea, usually 20 days after the onset of temporary melt. Considering the entire data set, snowmelt processes and onset do not show significant temporal trends. Instead, areas of increasing (decreasing) sea-ice extent have longer (shorter) periods of continuous snowmelt. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://pubs.usgs.gov/wri/1997/4142/report.pdf','USGSPUBS'); return false;" href="https://pubs.usgs.gov/wri/1997/4142/report.pdf">Snow and ice volume on Mount Spurr Volcano, Alaska, 1981</a> <a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> March, Rod S.; Mayo, Lawrence R.; Trabant, Dennis C. 1997-01-01 Mount Spurr (3,374 meters altitude) is an active volcano 130 kilometers west of Anchorage, Alaska, with an extensive covering of seasonal and perennial snow, and glaciers. Knowledge of the volume and distribution of snow and ice on a volcano aids in assessing hydrologic hazards such as floods, mudflows, and debris flows. In July 1981, ice thickness was measured at 68 locations on the five main glaciers of Mount Spurr: 64 of these measurements were made using a portable 1.7 megahertz monopulse ice-radar system, and 4 measurements were made using the helicopter altimeter where the glacier bed was exposed by ice avalanching. The distribution of snow and ice derived from these measurements is depicted on contour maps and in tables compiled by altitude and by drainage basins. Basal shear stresses at 20 percent of the measured locations ranged from 200 to 350 kilopascals, which is significantly higher than the 50 to 150 kilopascals commonly referred to in the literature as the 'normal' range for glaciers. Basal shear stresses higher than 'normal' have also been found on steep glaciers on volcanoes in the Cascade Range in the western United States. The area of perennial snow and ice coverage on Mount Spurr was 360 square kilometers in 1981, with an average thickness of 190?50 meters. Seasonal snow increases the volume about 1 percent and increases the area about 30 percent with a maximum in May or June. Runoff from Mount Spurr feeds the Chakachatna River and the Chichantna River (a tributary of the Beluga River). The Chakachatna River drainage contains 14 cubic kilometers of snow and ice and the Chichantna River drainage contains 53 cubic kilometers. The snow and ice volume on the mountain was 67?17 cubic kilometers, approximately 350 times more snow and ice than was on Mount St. Helens before its May 18, 1980, eruption, and 15 times more snow and ice than on Mount Rainier, the most glacierized of the measured volcanoes in the Cascade Range. On the basis of these relative </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017MsT..........4D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017MsT..........4D">Development of an Algorithm for Satellite Remote Sensing of Sea and Lake Ice</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Dorofy, Peter T. Satellite remote sensing of snow and ice has a long history. The traditional method for many snow and ice detection algorithms has been the use of the Normalized Difference Snow Index (NDSI). This manuscript is composed of two parts. Chapter 1, Development of a Mid-Infrared Sea and Lake Ice Index (MISI) using the GOES Imager, discusses the desirability, development, and implementation of alternative index for an ice detection algorithm, application of the algorithm to the detection of lake ice, and qualitative validation against other ice mapping products; such as, the Ice Mapping System (IMS). Chapter 2, Application of Dynamic Threshold in a Lake Ice Detection Algorithm, continues with a discussion of the development of a method that considers the variable viewing and illumination geometry of observations throughout the day. The method is an alternative to Bidirectional Reflectance Distribution Function (BRDF) models. Evaluation of the performance of the algorithm is introduced by aggregating classified pixels within geometrical boundaries designated by IMS and obtaining sensitivity and specificity statistical measures. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/14972976','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/14972976">Branch breakage under snow and ice loads.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Cannell, M G; Morgan, J 1989-09-01 Measurements were made on branches and trunks of Picea sitchensis (Bong.) Carr. to determine the relationship between (i) the bending moment at the bases of branches that cause breakage, and (ii) midpoint diameter cubed. The theory for cantilever beams was then used to calculate the basal bending moments and midpoint diameters of branches with different numbers of laterals and endpoint deflections, given previously measured values of Young's modulus, taper and weights of foliage and wood. Snow and ice loads (equal to 2 and 4 g cm(-1) of shoot, respectively) were then included in the calculation to determine whether the basal bending moments exceeded the breakage values. The likelihood of breakage increased with an increase in (i) number of laterals, and (ii) endpoint deflection under self weight (without snow or ice)-features that had previously been shown to lessen the amount of branch wood required to support a unit of foliage. However, branches which deflected moderately (> 10% of their length) under their own weight deflected greatly under snow or ice loads and might shed powdery snow before breakage occurs. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23413190','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23413190">Export of algal biomass from the melting Arctic sea ice.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Boetius, Antje; Albrecht, Sebastian; Bakker, Karel; Bienhold, Christina; Felden, Janine; Fernández-Méndez, Mar; Hendricks, Stefan; Katlein, Christian; Lalande, Catherine; Krumpen, Thomas; Nicolaus, Marcel; Peeken, Ilka; Rabe, Benjamin; Rogacheva, Antonina; Rybakova, Elena; Somavilla, Raquel; Wenzhöfer, Frank 2013-03-22 In the Arctic, under-ice primary production is limited to summer months and is restricted not only by ice thickness and snow cover but also by the stratification of the water column, which constrains nutrient supply for algal growth. Research Vessel Polarstern visited the ice-covered eastern-central basins between 82° to 89°N and 30° to 130°E in summer 2012, when Arctic sea ice declined to a record minimum. During this cruise, we observed a widespread deposition of ice algal biomass of on average 9 grams of carbon per square meter to the deep-sea floor of the central Arctic basins. Data from this cruise will contribute to assessing the effect of current climate change on Arctic productivity, biodiversity, and ecological function. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010ems..confE..91M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010ems..confE..91M">Meteorological factors controlling year-to-year variations in the spring onset of snow melt over the Arctic sea ice</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Maksimovich, E. 2010-09-01 The spring onset of snow melt on the Arctic sea ice shows large inter-annual variability. Surface melt triggers positive feedback mechanisms between the albedo, snow properties and thickness, as well as sea ice thickness. Hence, it is important to quantify the factors contributing to inter-annual variability of the melt onset (MO) in various parts of the Arctic Ocean. Meteorological factors controlling surface heat budget and surface melting/freezing are the shortwave and longwave radiative fluxes and the turbulent fluxes of sensible and latent heat. These fluxes depend on the weather conditions, including the radiative impact of clouds, heat advection and wind speed. We make use of SSM/I-based MO time series (Markus, Miller and Stroeve) and the ECMWF ERA Interim reanalysis on the meteorological conditions and surface fluxes, both data sets spanning the period 1989-2008 and covering recent years with a rapid sea ice decline. The advantage is that SSM/I-based MO time series are independent of the ERA-Interim data. Our objective is to investigate if there exists a physically consistent and statistically significant relationship between MO timing and corresponding meteorological conditions. Results based on the regression analysis between the MO timing and seasonal anomalies of surface longwave radiative fluxes reveal strong relationships. Synoptic scale (3-14 days) anomalies in downward longwave radiation are essential in the Western Arctic. Regarding the longer history (20-60 days) the distinct contribution from the downward longwave radiative fluxes is captured within the whole study region. Positive anomalies in the downward longwave radiation dominate over the simultaneous negative anomalies in the downward shortwave radiation. The anomalies in downward radiative fluxes are consistent with the total column water vapor, sea level pressure and 10-m wind direction. Sensible and latent heat fluxes affect surface melt timing in the Beaufort Sea and in the Atlantic </li> <li> <a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70021023','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70021023">Physical characteristics of summer sea ice across the Arctic Ocean</a> <a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Tucker, W. B.; Gow, A.J.; Meese, D.A.; Bosworth, H.W.; Reimnitz, E. 1999-01-01 Sea ice characteristics were investigated during July and August on the 1994 transect across the Arctic Ocean. Properties examined from ice cores included salinity, temperature, and ice structure. Salinities measured near zero at the surface, increasing to 3-4??? at the ice-water interface. Ice crystal texture was dominated by columnar ice, comprising 90% of the ice sampled. Surface albedos of various ice types, measured with radiometers, showed integrated shortwave albedos of 0.1 to 0.3 for melt ponds, 0.5 for bare, discolored ice, and 0.6 to 0.8 for a deteriorated surface or snow-covered ice. Aerial photography was utilized to document the distribution of open melt ponds, which decreased from 12% coverage of the ice 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 Sea 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 ice formation in the Beaufort Sea while more northerly samples probably originated in the East Siberian Sea, some as far west as the New Siberian Islands. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C11A0757G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C11A0757G">Sea Ice Thickness Estimates from Data Collected Using Airborne Sensors and Coincident In Situ Data</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Gardner, J. M.; Brozena, J. M.; Abelev, A.; Hagen, R. A.; Liang, R.; Ball, D. 2016-12-01 The Naval Research Laboratory collected data using Airborne sensors and coincident in-situ measurements over multiple sites of floating, but land-fast ice north of Barrow, AK. The in-situ data provide ground-truth for airborne measurements from a scanning LiDAR (Riegl Q 560i), digital photogrammetry (Applanix DSS-439), a low-frequency SAR (P-band in 2014 and P and L bands in 2015 and 2016) and a snow/Ku radar procured from the Center for Remote Sensing of Ice Sheets of the University of Kansas. The CReSIS radar was updated in 2015 to integrate the snow and Ku radars into a single continuous chirp, thus improving resolution. The objective of the surveys was to aid our understanding of the accuracy of ice thickness estimation via the freeboard method using the airborne sensor suite. Airborne data were collected on multiple overflights of the transect areas. The LiDAR measured total freeboard (ice + snow) referenced to leads in the ice, and produced swaths 200-300 m wide. The SAR imaged the ice beneath the snow and the snow/Ku radar measured snow thickness. The freeboard measurements and snow thickness are used to estimate ice thickness via isostasy and density estimates. Comparisons and processing methodology will be shown using data from three field seasons (2014-2016). The results of this ground-truth experiment will inform our analysis of grids of airborne data collected over areas of sea-ice illuminated by Cryosat-2. </li> <li> <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">Short-term sea ice forecasting: An assessment of ice concentration and ice drift forecasts using the U.S. Navy's Arctic Cap Nowcast/Forecast System</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Hebert, David A.; Allard, Richard A.; Metzger, E. Joseph; Posey, Pamela G.; Preller, Ruth H.; Wallcraft, Alan J.; Phelps, Michael W.; Smedstad, Ole Martin 2015-12-01 In this study the forecast skill of the U.S. Navy operational Arctic sea ice 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 sea ice and ocean conditions. Many quantities are forecast by ACNFS; the most commonly used include ice concentration, ice thickness, ice velocity, sea surface temperature, sea surface salinity, and sea surface velocities. Ice concentration forecast skill is compared to a persistent ice state and historical sea ice climatology. Skill scores are focused on areas where ice concentration changes by ±5% or more, and are therefore limited to primarily the marginal ice zone. We demonstrate that ACNFS forecasts are skilful compared to assuming a persistent ice 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 ice 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 ice concentration derived from Advanced Microwave Scanning Radiometer 2 (AMSR2) and the Interactive Multisensor Snow and Ice Mapping System (IMS). Preliminary results show that assimilating AMSR2 blended with IMS improves the short-term forecast skill and ice edge location compared to the independently derived National Ice Center Ice Edge product. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C43B0744A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C43B0744A">Spatial scales of light transmission through Antarctic pack ice: Surface flooding vs. floe-size distribution</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Arndt, S.; Meiners, K.; Krumpen, T.; Ricker, R.; Nicolaus, M. 2016-12-01 Snow on sea ice plays a crucial role for interactions between the ocean and atmosphere within the climate system of polar regions. Antarctic sea ice is covered with snow during most of the year. The snow contributes substantially to the sea-ice mass budget as the heavy snow loads can depress the ice below water level causing flooding. Refreezing of the snow and seawater mixture results in snow-ice formation on the ice surface. The snow cover determines also the amount of light being reflected, absorbed, and transmitted into the upper ocean, determining the surface energy budget of ice-covered oceans. The amount of light penetrating through sea ice into the upper ocean is of critical importance for the timing and amount of bottom sea-ice melt, biogeochemical processes and under-ice ecosystems. Here, we present results of several recent observations in the Weddell Sea measuring solar radiation under Antarctic sea ice with instrumented Remotely Operated Vehicles (ROV). The combination of under-ice optical measurements with simultaneous characterization of surface properties, such as sea-ice thickness and snow depth, allows the identification of key processes controlling the spatial distribution of the under-ice light. Thus, our results show how the distinction between flooded and non-flooded sea-ice regimes dominates the spatial scales of under-ice light variability for areas smaller than 100-by-100m. In contrast, the variability on larger scales seems to be controlled by the floe-size distribution and the associated lateral incidence of light. These results are related to recent studies on the spatial variability of Arctic under-ice light fields focusing on the distinctly differing dominant surface properties between the northern (e.g. summer melt ponds) and southern (e.g. year-round snow cover, surface flooding) hemisphere sea-ice cover. </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">12</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> <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">13</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> <a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1346837','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1346837">A New Discrete Element Sea-Ice Model for Earth System Modeling</a> <a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Turner, Adrian Keith Sea ice forms a frozen crust of sea 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 sea ice 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 sea ice and inhibits its vertical growth, increases its albedo, and contributes to pooledmore » water in melt ponds that darken the Arctic ice surface in the spring. Ice 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-ice-ocean boundary layers, including the ice-albedo feedback, whereby a reduced ice cover leads to increased upper ocean heating, further enhancing sea-ice melt and reducing incident solar radiation re ected back into the atmosphere (Perovich et al., 2008). A reduction in perennial Arctic sea-ice 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 sea-ice extent during the same period (Gagne et al., 2014).« less </li> <li> <a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-200910220008HQ.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-200910220008HQ.html">Ice Bridge Antarctic Sea Ice</a> <a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a> 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) </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFM.C41A0448F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFM.C41A0448F">Operational Products Archived at the National Snow and Ice Data Center</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Fetterer, F. M.; Ballagh, L.; Gergely, K.; Kovarik, J.; Wallace, A.; Windnagel, A. 2009-12-01 Sea ice charts for shipping interests from the Navy/NOAA/Coast Guard National Ice Center are often laboriously produced by manually interpreting and synthesizing data from many sources, both satellite and in situ. They are generally more accurate than similar products from single sources. Upward looking sonar data from U.S. Navy submarines operating in the Arctic provides information on ice thickness. Similarly extensive data were available from no other source prior to the recently established reliability of ice thickness estimates from polar orbiting instruments like the Geoscience Laser Altimeter System (GLAS). Snow Data Assimilation System (SNODAS) products from the NOAA NWS National Operational Hydrologic Remote Sensing Center give researchers the best possible estimates of snow cover and associated variables to support hydrologic modeling and analysis for the continental U.S. These and other snow and ice data products are produced by the U.S. Navy, the NOAA National Weather Service, and other agency entities to serve users who have an operational need: to get a ship safely to its destination, for example, or to predict stream flow. NOAA supports work at NSIDC with data from operational sources that can be used for climate research and change detection. We make these products available to a new user base, by archiving operational data, making data available online, providing documentation, and fielding questions from researchers about the data. These data demand special consideration: often they are advantageous because they are available on a schedule in near real time, but their use in climate studies is problematic since many are produced with regard for ‘best now’ and without regard for time series consistency. As arctic climate changes rapidly, operational and semi-operational products have an expanding science support role to play. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.gpo.gov/fdsys/pkg/CFR-2014-title30-vol1/pdf/CFR-2014-title30-vol1-sec57-11016.pdf','CFR2014'); return false;" href="https://www.gpo.gov/fdsys/pkg/CFR-2014-title30-vol1/pdf/CFR-2014-title30-vol1-sec57-11016.pdf">30 CFR 57.11016 - Snow and ice on walkways and travelways.</a> <a target="_blank" href="http://www.gpo.gov/fdsys/browse/collectionCfr.action?selectedYearFrom=2014&page.go=Go">Code of Federal Regulations, 2014 CFR</a> 2014-07-01 ... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Snow and ice on walkways and travelways. 57... MINES Travelways and Escapeways Travelways-Surface and Underground § 57.11016 Snow and ice on walkways... ice as soon as practicable. ... </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.gpo.gov/fdsys/pkg/CFR-2010-title30-vol1/pdf/CFR-2010-title30-vol1-sec57-11016.pdf','CFR'); return false;" href="https://www.gpo.gov/fdsys/pkg/CFR-2010-title30-vol1/pdf/CFR-2010-title30-vol1-sec57-11016.pdf">30 CFR 57.11016 - Snow and ice on walkways and travelways.</a> <a target="_blank" href="http://www.gpo.gov/fdsys/browse/collectionCfr.action?selectedYearFrom=2010&page.go=Go">Code of Federal Regulations, 2010 CFR</a> 2010-07-01 ... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Snow and ice on walkways and travelways. 57... MINES Travelways and Escapeways Travelways-Surface and Underground § 57.11016 Snow and ice on walkways... ice as soon as practicable. ... </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.gpo.gov/fdsys/pkg/CFR-2012-title30-vol1/pdf/CFR-2012-title30-vol1-sec57-11016.pdf','CFR2012'); return false;" href="https://www.gpo.gov/fdsys/pkg/CFR-2012-title30-vol1/pdf/CFR-2012-title30-vol1-sec57-11016.pdf">30 CFR 57.11016 - Snow and ice on walkways and travelways.</a> <a target="_blank" href="http://www.gpo.gov/fdsys/browse/collectionCfr.action?selectedYearFrom=2012&page.go=Go">Code of Federal Regulations, 2012 CFR</a> 2012-07-01 ... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Snow and ice on walkways and travelways. 57... MINES Travelways and Escapeways Travelways-Surface and Underground § 57.11016 Snow and ice on walkways... ice as soon as practicable. ... </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.gpo.gov/fdsys/pkg/CFR-2013-title30-vol1/pdf/CFR-2013-title30-vol1-sec57-11016.pdf','CFR2013'); return false;" href="https://www.gpo.gov/fdsys/pkg/CFR-2013-title30-vol1/pdf/CFR-2013-title30-vol1-sec57-11016.pdf">30 CFR 57.11016 - Snow and ice on walkways and travelways.</a> <a target="_blank" href="http://www.gpo.gov/fdsys/browse/collectionCfr.action?selectedYearFrom=2013&page.go=Go">Code of Federal Regulations, 2013 CFR</a> 2013-07-01 ... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Snow and ice on walkways and travelways. 57... MINES Travelways and Escapeways Travelways-Surface and Underground § 57.11016 Snow and ice on walkways... ice as soon as practicable. ... </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.gpo.gov/fdsys/pkg/CFR-2011-title30-vol1/pdf/CFR-2011-title30-vol1-sec57-11016.pdf','CFR2011'); return false;" href="https://www.gpo.gov/fdsys/pkg/CFR-2011-title30-vol1/pdf/CFR-2011-title30-vol1-sec57-11016.pdf">30 CFR 57.11016 - Snow and ice on walkways and travelways.</a> <a target="_blank" href="http://www.gpo.gov/fdsys/browse/collectionCfr.action?selectedYearFrom=2011&page.go=Go">Code of Federal Regulations, 2011 CFR</a> 2011-07-01 ... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Snow and ice on walkways and travelways. 57... MINES Travelways and Escapeways Travelways-Surface and Underground § 57.11016 Snow and ice on walkways... ice as soon as practicable. ... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C21G1187P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C21G1187P">Spatial and Temporal Means and Variability of Arctic Sea Ice Climate Indicators from Satellite Data</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Peng, G.; Meier, W.; Bliss, A. C.; Steele, M.; Dickinson, S. 2017-12-01 Arctic sea ice has been undergoing rapid and accelerated loss since satellite-based measurements became available in late 1970s, especially the summer ice coverage. For the Arctic as a whole, the long-term trend for the annual sea ice extent (SIE) minimum is about -13.5±2.93 % per decade change relative to the 1979-2015 climate average, while the trends of the annual SIE minimum for the local regions can range from 0 to up to -42 % per decade. This presentation aims to examine and baseline spatial and temporal means and variability of Arctic sea ice climate indicators, such as the annual SIE minimum and maximum, snow/ice melt onset, etc., from a consistent, inter-calibrated, long-term time series of remote sensing sea ice data for understanding regional vulnerability and monitoring ice state for climate adaptation and risk mitigation. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/biblio/419613-classification-baltic-sea-ice-types-airborne-multifrequency-microwave-radiometer','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/419613-classification-baltic-sea-ice-types-airborne-multifrequency-microwave-radiometer">Classification of Baltic Sea ice types by airborne multifrequency microwave radiometer</a> <a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Kurvonen, L.; Hallikainen, M. An airborne multifrequency radiometer (24, 34, 48, and 94 GHz, vertical polarization) was used to investigate the behavior of the brightness temperature of different sea ice types in the Gulf of Bothnia (Baltic Sea). The measurements and the main results of the analysis are presented. The measurements were made in dry and wet conditions (air temperature above and below 0 C). The angle of incidence was 45{degree} in all measurements. The following topics are evaluated: (a) frequency dependency of the brightness temperature of different ice types, (b) the capability of the multifrequency radiometer to classify ice types for winter navigationmore » purposes, and (c) the optimum measurement frequencies for mapping sea ice. The weather conditions had a significant impact on the radiometric signatures of some ice types (snow-covered compact pack ice and frost-covered new ice); the impact was the highest at 94 GHz. In all cases the overall classification accuracy was around 90% (the kappa coefficient was from 0.86 to 0.96) when the optimum channel combination (24/34 GHz and 94 GHz) was used.« less </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.C43A0590F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.C43A0590F">Statistical Analyses of High-Resolution Aircraft and Satellite Observations of Sea Ice: Applications for Improving Model Simulations</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Farrell, S. L.; Kurtz, N. T.; Richter-Menge, J.; Harbeck, J. P.; Onana, V. 2012-12-01 Satellite-derived estimates of ice thickness and observations of ice extent over the last decade point to a downward trend in the basin-scale ice volume of the Arctic Ocean. This loss has broad-ranging impacts on the regional climate and ecosystems, as well as implications for regional infrastructure, marine navigation, national security, and resource exploration. New observational datasets at small spatial and temporal scales are now required to improve our understanding of physical processes occurring within the ice pack and advance parameterizations in the next generation of numerical sea-ice models. High-resolution airborne and satellite observations of the sea ice are now available at meter-scale resolution or better that provide new details on the properties and morphology of the ice pack across basin scales. For example the NASA IceBridge airborne campaign routinely surveys the sea ice of the Arctic and Southern Oceans with an advanced sensor suite including laser and radar altimeters and digital cameras that together provide high-resolution measurements of sea ice freeboard, thickness, snow depth and lead distribution. Here we present statistical analyses of the ice pack primarily derived from the following IceBridge instruments: the Digital Mapping System (DMS), a nadir-looking, high-resolution digital camera; the Airborne Topographic Mapper, a scanning lidar; and the University of Kansas snow radar, a novel instrument designed to estimate snow depth on sea ice. Together these instruments provide data from which a wide range of sea ice properties may be derived. We provide statistics on lead distribution and spacing, lead width and area, floe size and distance between floes, as well as ridge height, frequency and distribution. The goals of this study are to (i) identify unique statistics that can be used to describe the characteristics of specific ice regions, for example first-year/multi-year ice, diffuse ice edge/consolidated ice pack, and convergent </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.C31D0341K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.C31D0341K">Sea Ice Characteristics and the Open-Linked Data World</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Khalsa, S. J. S.; McGuinness, D. L.; Duerr, R.; Pulsifer, P. L.; Fox, P. A.; Thompson, C.; Yan, R. 2014-12-01 The audience for sea ice data sets has broadened dramatically over the past several decades. Initially the National Snow and Ice Data Center (NSIDC) sea ice products were used primarily by sea ice 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 Sea Ice Interoperability Initiative (SSIII) is an NSF-funded research project aimed at making sea ice 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, sea ice research and modeling communities, as well as members of local communities in Alaska, a suite of ontologies describing the physical characteristics of sea ice have been developed and used to provide one of NSIDC's data sets, the operational Arctic sea ice charts obtained from the Canadian Ice 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., sea ice concentration, form and stage of development) of the sea ice in the region </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1912539S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1912539S">Analysis on variability and trend in Antarctic sea ice albedo between 1983 and 2009</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Seo, Minji; Kim, Hyun-cheol; Choi, Sungwon; Lee, Kyeong-sang; Han, Kyung-soo 2017-04-01 Sea ice is key parameter in order to understand the cryosphere climate change. Several studies indicate the different trend of sea ice between Antarctica and Arctic. Albedo is important factor for understanding the energy budget and factors for observing of environment changes of Cryosphere such as South Pole, due to it mainly covered by ice and snow with high albedo value. In this study, we analyzed variability and trend of long-term sea ice albedo data to understand the changes of sea ice over Antarctica. In addiction, sea ice albedo researched the relationship with Antarctic oscillation in order to determine the atmospheric influence. We used the sea ice albedo data at The Satellite Application Facility on Climate Monitoring and Antarctic Oscillation data at NOAA Climate Prediction Center (CPC). We analyzed the annual trend in albedo using linear regression to understand the spatial and temporal tendency. Antarctic sea ice albedo has two spatial trend. Weddle sea / Ross sea sections represent a positive trend (0.26% ˜ 0.04% yr-1) and Bellingshausen Amundsen sea represents a negative trend (- 0.14 ˜ -0.25%yr-1). Moreover, we performed the correlation analysis between albedo and Antarctic oscillation. As a results, negative area indicate correlation coefficient of - 0.3639 and positive area indicates correlation coefficient of - 0.0741. Theses results sea ice albedo has regional trend according to ocean. Decreasing sea ice trend has negative relationship with Antarctic oscillation, its represent a possibility that sea ice influence atmospheric factor. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1999JGR...10425735G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1999JGR...10425735G">Observations of sea ice ridging in the Weddell Sea</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Granberg, Hardy B.; Leppaäranta, Matti 1999-11-01 Sea ice surface topography data were obtained by helicopter-borne laser profiling during the First Finnish Antarctic Expedition (FINNARP-89). The measurements were made near the ice margin at about 73°S, 27°W in the eastern Weddell Sea on December 31, 1989, and January 1, 1990. Five transects, ranging in length from 127 to 163 km and covering a total length of 724 km, are analyzed. With a lower cutoff of 0.91 m the overall ridge frequency was 8.4 ridges/km and the average ridge height was 1.32 m. The spatial variations in ridging were large; for 36 individual 20-km segments the frequencies were 2-16 ridges/km and the mean heights were 1.16-1.56 m. The frequencies and mean heights were weakly correlated. The distributions of the ridge heights followed the exponential distribution; the spacings did not pass tests for either the exponential or the lognormal distribution, but the latter was much closer. In the 20-km segments the areally averaged thickness of ridged ice was 0.51±0.28 m, ranging from 0.10 to 1.15 m. The observed ridge size and frequency are greater than those known for the Ross Sea. Compared with the central Arctic, the Weddell Sea ridging frequencies are similar but the ridge heights are smaller, possibly as a result of differences in snow accumulation. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19950048358&hterms=Frost&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3DFrost','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19950048358&hterms=Frost&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3DFrost">Measurements of thermal infrared spectral reflectance of frost, snow, and ice</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Salisbury, John W.; D'Aria, Dana M.; Wald, Andrew 1994-01-01 Because much of Earth's surface is covered by frost, snow, and ice, the spectral emissivities of these materials are a significant input to radiation balance calculations in global atmospheric circulation and climate change models. Until now, however, spectral emissivities of frost and snow have been calculated from the optical constants of ice. We have measured directional hemispherical reflectance spectra of frost, snow, and ice from which emissivities can be predicted using Kirchhoff's law (e = 1-R). These measured spectra show that contrary to conclusions about the emissivity of snow drawn from previously calculated spectra, snow emissivity departs significantly from blackbody behavior in the 8-14 micrometer region of the spectrum; snow emissivity decreases with both increasing particle size and increasing density due to packing or grain welding; while snow emissivity increases due to the presence of meltwater. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018TCry...12.1307W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018TCry...12.1307W">Open-source algorithm for detecting sea ice surface features in high-resolution optical imagery</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Wright, Nicholas C.; Polashenski, Chris M. 2018-04-01 Snow, ice, and melt ponds cover the surface of the Arctic Ocean in fractions that change throughout the seasons. These surfaces control albedo and exert tremendous influence over the energy balance in the Arctic. Increasingly available meter- to decimeter-scale resolution optical imagery captures the evolution of the ice and ocean surface state visually, but methods for quantifying coverage of key surface types from raw imagery are not yet well established. Here we present an open-source system designed to provide a standardized, automated, and reproducible technique for processing optical imagery of sea ice. The method classifies surface coverage into three main categories: snow and bare ice, melt ponds and submerged ice, and open water. The method is demonstrated on imagery from four sensor platforms and on imagery spanning from spring thaw to fall freeze-up. Tests show the classification accuracy of this method typically exceeds 96 %. To facilitate scientific use, we evaluate the minimum observation area required for reporting a representative sample of surface coverage. We provide an open-source distribution of this algorithm and associated training datasets and suggest the community consider this a step towards standardizing optical sea ice imagery processing. We hope to encourage future collaborative efforts to improve the code base and to analyze large datasets of optical sea ice imagery. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70013684','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70013684">ASPECTS OF ARCTIC SEA ICE OBSERVABLE BY SEQUENTIAL PASSIVE MICROWAVE OBSERVATIONS FROM THE NIMBUS-5 SATELLITE.</a> <a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Campbell, William J.; Gloersen, Per; Zwally, H. Jay; , 1984-01-01 Observations made from 1972 to 1976 with the Electrically Scanning Microwave Radiometer on board the Nimbus-5 satellite provide sequential synoptic information of the Arctic sea ice cover. This four-year data set was used to construct a fairly continuous series of three-day average 19-GHz passive microwave images which has become a valuable source of polar information, yielding many anticipated and unanticipated discoveries of the sea ice canopy observed in its entirety through the clouds and during the polar night. Short-term, seasonal, and annual variations of key sea ice parameters, such as ice edge position, ice types, mixtures of ice types, ice concentrations, and snow melt on the ice, are presented for various parts of the Arctic. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA601068','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA601068">Sunlight, Sea Ice, and the Ice Albedo Feedback in a Changing Arctic Sea Ice Cover</a> <a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.C54A..08M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.C54A..08M">Object-based Image Classification of Arctic Sea Ice and Melt Ponds through Aerial Photos</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Miao, X.; Xie, H.; Li, Z.; Lei, R. 2013-12-01 The last six years have marked the lowest Arctic summer sea ice extents in the modern era, with a new record summer minimum (3.4 million km2) set on 13 September 2012. It has been predicted that the Arctic could be free of summer ice within the next 25-30. The loss of Arctic summer ice could have serious consequences, such as higher water temperature due to the positive feedback of albedo, more powerful and frequent storms, rising sea levels, diminished habitats for polar animals, and more pollution due to fossil fuel exploitation and/ or increased traffic through the Northwest/ Northeast Passage. In these processes, melt ponds play an important role in Earth's radiation balance since they strongly absorb solar radiation rather than reflecting it as snow and ice do. Therefore, it is necessary to develop the ability of predicting the sea ice/ melt pond extents and space-time evolution, which is pivotal to prepare for the variation and uncertainty of the future environment, political, economic, and military needs. A lot of efforts have been put into Arctic sea ice modeling to simulate sea ice processes. However, these sea ice models were initiated and developed based on limited field surveys, aircraft or satellite image data. Therefore, it is necessary to collect high resolution sea ice aerial photo in a systematic way to tune up, validate, and improve models. Currently there are many sea ice aerial photos available, such as Chinese Arctic Exploration (CHINARE 2008, 2010, 2012), SHEBA 1998 and HOTRAX 2005. However, manually delineating of sea ice and melt pond from these images is time-consuming and labor-intensive. In this study, we use the object-based remote sensing classification scheme to extract sea ice and melt ponds efficiently from 1,727 aerial photos taken during the CHINARE 2010. The algorithm includes three major steps as follows. (1) Image segmentation groups the neighboring pixels into objects according to the similarity of spectral and texture </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1814695S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1814695S">N-ICE2015: Multi-disciplinary study of the young sea ice system north of Svalbard from winter to summer.</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Steen, Harald; Granskog, Mats; Assmy, Philipp; Duarte, Pedro; Hudson, Stephen; Gerland, Sebastian; Spreen, Gunnar; Smedsrud, Lars H. 2016-04-01 The Arctic Ocean is shifting to a new regime with a thinner and smaller sea-ice area cover. Until now, winter sea ice extent has changed less than during summer, as the heat loss to the atmosphere during autumn and winter is large enough form an ice cover in most regions. The insulating snow cover also heavily influences the winter ice growth. Consequently, the older, thicker multi-year sea ice has been replace by a younger and thinner sea. These large changes in the sea ice 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 Sea ICE cruise 2015 (N-ICE2015). N-ICE2015 was a multi-disciplinary cruise aimed at simultaneously studying the effect of the Arctic Ocean changes in the sea ice, the atmosphere, in radiation, in ecosystems. as well as water chemistry. R/V Lance was frozen into the drift ice north of Svalbard at about N83 E25 and drifted passively southwards with the ice 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 ice, she served as a living and working platform for 100 scientist and engineers from 11 countries. One aim of N-ICE2015 is to present a comprehensive data-set on the first year ice dominated system available for the scientific community describing the state and changes of the Arctic sea ice system from freezing to melt. Analyzing the data is progressing and some first results will be presented. </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">13</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> <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">14</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> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140006601','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140006601">Arctic Sea Ice Freeboard from Icebridge Acquisitions in 2009: Estimates and Comparisons with ICEsat</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Kwok, R.; Cunningham, Glenn F.; Manizade, S. S.; Krabill, W. B. 2012-01-01 During the spring of 2009, the Airborne Topographic Mapper (ATM) system on the IceBridge mission acquired cross-basin surveys of surface elevations of Arctic sea ice. In this paper, the total freeboard derived from four 2000 km transects are examined and compared with those from the 2009 ICESat campaign. Total freeboard, the sum of the snow and ice freeboards, is the elevation of the air-snow interface above the local sea surface. Prior to freeboard retrieval, signal dependent range biases are corrected. With data from a near co-incident outbound and return track on 21 April, we show that our estimates of the freeboard are repeatable to within 4 cm but dependent locally on the density and quality of sea surface references. Overall difference between the ATM and ICESat freeboards for the four transects is 0.7 (8.5) cm (quantity in bracket is standard deviation), with a correlation of 0.78 between the data sets of one hundred seventy-eight 50 km averages. This establishes a level of confidence in the use of ATM freeboards to provide regional samplings that are consistent with ICESat. In early April, mean freeboards are 41 cm and 55 cm over first year and multiyear sea ice (MYI), respectively. Regionally, the lowest mean ice freeboard (28 cm) is seen on 5 April where the flight track sampled the large expanse of seasonal ice in the western Arctic. The highest mean freeboard (71 cm) is seen in the multiyear ice just west of Ellesmere Island from 21 April. The relatively large unmodeled variability of the residual sea surface resolved by ATM elevations is discussed. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19740002268','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19740002268">Microwave signatures of snow and fresh water ice</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Schmugge, T.; Wilheit, T. T.; Gloersen, P.; Meier, M. F.; Frank, D.; Dirmhirn, I. 1973-01-01 During March of 1971, the NASA Convair 990 Airborne Observatory carrying microwave radiometers in the wavelength range 0.8 to 21 cm was flown over dry snow with different substrata: Lake ice at Bear Lake in Utah; wet soil in the Yampa River Valley near Steamboat Springs, Colorado; and glacier ice, firm and wet snow on the South Cascade Glacier in Washington. The data presented indicate that the transparency of the snow cover is a function of wavelength. False-color images of microwave brightness temperatures obtained from a scanning radiometer operating at a wavelength of 1.55 cm demonstrate the capability of scanning radiometers for mapping snowfields. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C11C0920H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C11C0920H">Everywhere and nowhere: snow and its linkages</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Hiemstra, C. A. 2017-12-01 Interest has grown in quantifying higher latitude precipitation change and snow-related ecosystem and economic impacts. There is a high demand for creating and using snow-related datasets, yet available datasets contain limitations, aren't scale appropriate, or lack thorough validation. Much of the uncertainty in snow estimates relates to ongoing snow measurement problems that are chronic and pervasive in windy, Arctic environments. This, coupled with diminishing support for long-term snow field observations, creates formidable hydrologic gaps in snow dominated landscapes. Snow touches most aspects of high latitude landscapes and spans albedo, ecosystems, soils, permafrost, and sea ice. In turn, snow can be impacted by disturbances, landscape change, ecosystem, structure, and later arrival of sea or lake ice. Snow, and its changes touch infrastructure, housing, and transportation. Advances in snow measurements, modeling, and data assimilation are under way, but more attention and a concerted effort is needed in a time of dwindling resources to make required advances during a time of rapid change. </li> <li> <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">Sea ice concentration temporal variability over the Weddell Sea and its relationship with tropical sea surface temperature</a> <a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Barreira, S.; Compagnucci, R. 2007-01-01 Principal Components Analysis (PCA) in S-Mode (correlation between temporal series) was performed on sea ice 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 sea surface temperature (SST). This analysis provides 9 patterns (4 in the Amundsen and Bellingshausen Seas and 5 in the Weddell Sea) that represent the most important temporal features that dominated sea ice concentration anomalies (SICA) variability in the Weddell, Amundsen and Bellingshausen Seas over the 1979-2000 period. Monthly Polar Gridded Sea Ice Concentrations data set derived from satellite information generated by NASA Team algorithm and acquired from the National Snow and Ice 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 Seas 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 sea ice concentration over the Weddell Sea. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006AnGla..44...47P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006AnGla..44...47P">The interaction of ultraviolet light with Arctic sea ice during SHEBA</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Perovich, Donald K. The reflection, absorption and transmission of ultraviolet light by a sea-ice cover strongly impacts primary productivity, higher trophic components of the food web, and humans. Measurements of the incident irradiance at 305, 320, 340 and 380 nm and of the photosynthetically active radiation were made from April through September 1998 as part of the SHEBA (Surface Heat Budget of the Arctic Ocean program) field experiment in the Arctic Ocean. In addition, observations of snow depth and ice thickness were made at more than 100 sites encompassing a comprehensive range of conditions. The thickness observations were combined with a radiative transfer model to compute a time series of the ultraviolet light transmitted by the ice cover from April through September. Peak values of incident ultraviolet irradiance occurred in mid-June. Peak transmittance was later in the summer at the end of the melt season when the snow cover had completely melted, the ice had thinned and pond coverage was extensive. The fraction of the incident ultraviolet irradiance transmitted through the ice increased by several orders of magnitude as the melt season progressed. Ultraviolet transmittance was approximately a factor of ten greater for melt ponds than bare ice. Climate change has the potential to alter the amplitude and timing of the annual albedo cycle of sea ice. If the onset of melt occurs at increasingly earlier dates, ultraviolet transmittance will be significantly enhanced, with potentially deleterious biological impacts. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.C43B0393W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.C43B0393W">Arctic Sea Ice Predictability and the Sea Ice Prediction Network</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.U11A..06W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.U11A..06W">Albedo of bare ice near the Trans-Antarctic Mountains to represent sea-glaciers on the tropical ocean of Snowball Earth</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Warren, S. G.; Dadic, R.; Mullen, P.; Schneebeli, M.; Brandt, R. E. 2012-12-01 The albedos of snow and ice surfaces are, because of their positive feedback, crucial to the initiation, maintenance, and termination of a snowball event, as well as for determining the ice thickness on the ocean. Despite the name, Snowball Earth would not have been entirely snow-covered. As on modern Earth, evaporation would exceed precipitation over much of the tropical ocean. After a transient period with sea ice, the dominant ice type would probably be sea-glaciers flowing in from higher latitude. As they flowed equatorward into the tropical region of net sublimation, their surface snow and subsurface firn would sublimate away, exposing bare glacier ice to the atmosphere and to solar radiation. This ice would be freshwater (meteoric) ice, which originated from snow and firn, so it would contain numerous air bubbles, which determine the albedo. The modern surrogate for this type of ice (glacier ice exposed by sublimation, which has never experienced melting), are the bare-ice surfaces of the Antarctic Ice Sheet near the Trans-Antarctic Mountains. These areas have been well mapped because of their importance in the search for meteorites. A transect across an icefield can sample ice of different ages that has traveled to different depths en route to the sublimation front. On a 6-km transect from snow to ice near the Allan Hills, spectral albedo was measured and 1-m core samples were collected. This short transect is meant to represent a north-south transect across many degrees of latitude on the snowball ocean. Surfaces on the transect transitioned through the sequence: new snow - old snow - firn - young white ice - old blue ice. The transect from snow to ice showed a systematic progression of decreasing albedo at all wavelengths, as well as decreasing specific surface area (SSA; ratio of air-ice interface area to ice mass) and increasing density. The measured spectral albedos are integrated over wavelength and weighted by the spectral solar flux to obtain </li> <li> <a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70022603','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70022603">Snow crystal imaging using scanning electron microscopy: III. Glacier ice, snow and biota</a> <a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Rango, A.; Wergin, W.P.; Erbe, E.F.; Josberger, E.G. 2000-01-01 Low-temperature scanning electron microscopy (SEM) was used to observe metamorphosed snow, glacial firn, and glacial ice obtained from South Cascade Glacier in Washington State, USA. Biotic samples consisting of algae (Chlamydomonas nivalis) and ice worms (a species of oligochaetes) were also collected and imaged. In the field, the snow and biological samples were mounted on copper plates, cooled in liquid nitrogen, and stored in dry shipping containers which maintain a temperature of -196??C. The firn and glacier ice samples were obtained by extracting horizontal ice cores, 8 mm in diameter, at different levels from larger standard glaciological (vertical) ice cores 7.5 cm in diameter. These samples were cooled in liquid nitrogen and placed in cryotubes, were stored in the same dry shipping container, and sent to the SEM facility. In the laboratory, the samples were sputter coated with platinum and imaged by a low-temperature SEM. To image the firn and glacier ice samples, the cores were fractured in liquid nitrogen, attached to a specimen holder, and then imaged. While light microscope images of snow and ice are difficult to interpret because of internal reflection and refraction, the SEM images provide a clear and unique view of the surface of the samples because they are generated from electrons emitted or reflected only from the surface of the sample. In addition, the SEM has a great depth of field with a wide range of magnifying capabilities. The resulting images clearly show the individual grains of the seasonal snowpack and the bonding between the snow grains. Images of firn show individual ice crystals, the bonding between the crystals, and connected air spaces. Images of glacier ice show a crystal structure on a scale of 1-2 mm which is considerably smaller than the expected crystal size. Microscopic air bubbles, less than 15 ??m in diameter, clearly marked the boundaries between these crystal-like features. The life forms associated with the glacier were </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.C13E0662E','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.C13E0662E">High-precision GPS autonomous platforms for sea ice dynamics and physical oceanography</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Elosegui, P.; Wilkinson, J.; Olsson, M.; Rodwell, S.; James, A.; Hagan, B.; Hwang, B.; Forsberg, R.; Gerdes, R.; Johannessen, J.; Wadhams, P.; Nettles, M.; Padman, L. 2012-12-01 Project "Arctic Ocean sea ice and ocean circulation using satellite methods" (SATICE), is the first high-rate, high-precision, continuous GPS positioning experiment on sea ice in the Arctic Ocean. The SATICE systems collect continuous, dual-frequency carrier-phase GPS data while drifting on sea ice. Additional geophysical measurements also collected include ocean water pressure, ocean surface salinity, atmospheric pressure, snow-depth, air-ice-ocean temperature profiles, photographic imagery, and others, enabling sea ice drift, freeboard, weather, ice mass balance, and sea-level height determination. Relatively large volumes of data from each buoy are streamed over a satellite link to a central computer on the Internet in near real time, where they are processed to estimate the time-varying buoy positions. SATICE system obtains continuous GPS data at sub-minute intervals with a positioning precision of a few centimetres in all three dimensions. Although monitoring of sea ice motions goes back to the early days of satellite observations, these autonomous platforms bring out a level of spatio-temporal detail that has never been seen before, especially in the vertical axis. These high-resolution data allows us to address new polar science questions and challenge our present understanding of both sea ice dynamics and Arctic oceanography. We will describe the technology behind this new autonomous platform, which could also be adapted to other applications that require high resolution positioning information with sustained operations and observations in the polar marine environment, and present results pertaining to sea ice dynamics and physical oceanography. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFMGC31A0676B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFMGC31A0676B">Snow and Ice Crust Changes over Northern Eurasia since 1966</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Bulygina, O.; Groisman, P. Y.; Razuvaev, V.; Radionov, V. 2009-12-01 When temperature of snow cover reaches zero Celsius first time since its establishment, snowmelt starts. In many parts of the world this process can be lengthy. The initial amount of heat that “arrives” to the snowpack might be insufficient for complete snowmelt, during the colder nights re-freeze of the melted snow may occur (thus creating the ice crust layers), and a new cold front (or the departure of the warm front that initiated melt) can decrease temperatures below the freezing point again and stop the snowmelt completely. It well can be that first such snowmelt occurs in winter (thaw day) and for several months thereafter snowpack stays on the ground. However, even the first such melt initiates a process of snow metamorphosis on its surface changing snow albedo and generating snow crust as well as on its bottom generating ice crust. Once emerged, the crusts will not disappear until the complete snowmelt. Furthermore, these crusts have numerous pathways of impact on the wild birds and animals in the Arctic environment as well as on domesticated reindeers. In extreme cases, the crusts may kill some wild species and prevent reindeers’ migration and feeding. Ongoing warming in high latitudes created situations when in the western half of Eurasian continent days with thaw became more frequent. Keeping in mind potential detrimental impacts of winter thaws and associated with them snow/ice crust development, it is worthwhile to study directly what are the major features of snow and ice crust over Eurasia and what is their dynamics. For the purpose of this study, we employed the national snow survey data set archived at the Russian Institute for Hydrometeorological Information. The dataset has routine snow surveys run throughout the cold season each decade (during the intense snowmelt, each 5 days) at all meteorological stations of the former USSR, thereafter, in Russia since 1966. Prior to 1966 snow surveys are also available but the methodology of </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20150000365','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20150000365">Aquarius Radiometer and Scatterometer Weekly Polar-Gridded Products to Monitor Ice Sheets, Sea Ice, and Frozen Soil</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Brucker, Ludovic; Dinnat, Emmanuel; Koenig, Lora 2014-01-01 Space-based microwave sensors have been available for several decades, and with time more frequencies have been offered. Observations made at frequencies between 7 and 183 GHz were often used for monitoring cryospheric properties (e.g. sea ice concentration, snow accumulation, snow melt extent and duration). Since 2009, satellite observations are available at the low frequency of 1.4 GHz. Such observations are collected by the Soil Moisture and Ocean Salinity (SMOS) mission, and the Aquarius/SAC-D mission. Even though these missions have been designed for the monitoring of soil moisture and sea surface salinity, new applications are being developed to study the cryosphere. For instance, L-band observations can be used to monitor soil freeze/thaw (e.g. Rautiainen et al., 2012), and thin sea ice thickness (e.g. Kaleschke et al., 2010, Huntemann et al., 2013). Moreover, with the development of satellite missions comes the need for calibration and validation sites. These sites must have stable characteristics, such as the Antarctic Plateau (Drinkwater et al., 2004, Macelloni et al., 2013). Therefore, studying the cryosphere with 1.4 GHz observations is relevant for both science applications, and remote sensing applications. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140017806','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140017806">Aquarius Radiometer and Scatterometer Weekly-Polar-Gridded Products to Monitor Ice Sheets, Sea Ice, and Frozen Soil</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Brucker, Ludovic; Dinnat, Emmanuel; Koenig, Lora 2014-01-01 Space-based microwave sensors have been available for several decades, and with time more frequencies have been offered. Observations made at frequencies between 7 and 183 GHz were often used for monitoring cryospheric properties (e.g. sea ice concentration, snow accumulation, snow melt extent and duration). Since 2009, satellite observations are available at the low frequency of 1.4 GHz. Such observations are collected by the Soil Moisture and Ocean Salinity (SMOS) mission, and the AquariusSAC-D mission. Even though these missions have been designed for the monitoring of soil moisture and sea surface salinity, new applications are being developed to study the cryosphere. For instance, L-band observations can be used to monitor soil freezethaw (e.g. Rautiainen et al., 2012), and thin sea ice thickness (e.g. Kaleschke et al., 2010, Huntemann et al., 2013). Moreover, with the development of satellite missions comes the need for calibration and validation sites. These sites must have stable characteristics, such as the Antarctic Plateau (Drinkwater et al., 2004, Macelloni et al., 2013). Therefore, studying the cryosphere with 1.4 GHz observations is relevant for both science applications, and remote sensing applications. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUFM.C11B0499S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUFM.C11B0499S">Expanding research capabilities with sea ice climate records for analysis of long-term climate change and short-term variability</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Scott, D. J.; Meier, W. N. 2008-12-01 Recent sea ice analysis is leading to predictions of a sea ice-free summertime in the Arctic within 20 years, or even sooner. Sea ice topics, such as concentration, extent, motion, and age, are predominately studied using satellite data. At the National Snow and Ice Data Center (NSIDC), passive microwave sea ice data sets provide timely assessments of seasonal-scale variability as well as consistent long-term climate data records. Such data sets are crucial to understanding changes and assessing their impacts. Noticeable impacts of changing sea ice conditions on native cultures and wildlife in the Arctic region are now being documented. With continued deterioration in Arctic sea ice, global economic impacts will be seen as new shipping routes open. NSIDC is at the forefront of making climate data records available to address the changes in sea ice and its global impacts. By focusing on integrated data sets, NSIDC leads the way by broadening the studies of sea ice beyond the traditional cryospheric community. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015TCD.....9.5521K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015TCD.....9.5521K">Seasonal sea ice predictions for the Arctic based on assimilation of remotely sensed observations</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Kauker, F.; Kaminski, T.; Ricker, R.; Toudal-Pedersen, L.; Dybkjaer, G.; Melsheimer, C.; Eastwood, S.; Sumata, H.; Karcher, M.; Gerdes, R. 2015-10-01 The recent thinning and shrinking of the Arctic sea ice cover has increased the interest in seasonal sea ice forecasts. Typical tools for such forecasts are numerical models of the coupled ocean sea ice system such as the North Atlantic/Arctic Ocean Sea Ice Model (NAOSIM). The model uses as input the initial state of the system and the atmospheric boundary condition over the forecasting period. This study investigates the potential of remotely sensed ice thickness observations in constraining the initial model state. For this purpose it employs a variational assimilation system around NAOSIM and the Alfred Wegener Institute's CryoSat-2 ice thickness product in conjunction with the University of Bremen's snow depth product and the OSI SAF ice concentration and sea surface temperature products. We investigate the skill of predictions of the summer ice conditions starting in March for three different years. Straightforward assimilation of the above combination of data streams results in slight improvements over some regions (especially in the Beaufort Sea) but degrades the over-all fit to independent observations. A considerable enhancement of forecast skill is demonstrated for a bias correction scheme for the CryoSat-2 ice thickness product that uses a spatially varying scaling factor. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70175509','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70175509">Water, ice and mud: Lahars and lahar hazards at ice- and snow-clad volcanoes</a> <a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Waythomas, Christopher F. 2014-01-01 Large-volume lahars are significant hazards at ice and snow covered volcanoes. Hot eruptive products produced during explosive eruptions can generate a substantial volume of melt water that quickly evolves into highly mobile flows of ice, sediment and water. At present it is difficult to predict the size of lahars that can form at ice and snow covered volcanoes due to their complex flow character and behaviour. However, advances in experiments and numerical approaches are producing new conceptual models and new methods for hazard assessment. Eruption triggered lahars that are ice-dominated leave behind thin, almost unrecognizable sedimentary deposits, making them likely to be under-represented in the geological record. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C32B..05A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C32B..05A">Spatial variability and trends of seasonal snowmelt processes over Antarctic sea ice observed by satellite scatterometers</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Arndt, S.; Haas, C. 2017-12-01 Snow is one of the key drivers determining the seasonal energy and mass budgets of sea ice in the Southern Ocean. Here, we analyze radar backscatter time series from the European Remote Sensing Satellites (ERS)-1 and-2 scatterometers, from the Quick Scatterometer (QSCAT), and from the Advanced Scatterometer (ASCAT) in order to observe the regional and inter-annual variability of Antarctic snowmelt processes from 1992 to 2014. On perennial ice, seasonal backscatter changes show two different snowmelt stages: A weak backscatter rise indicating the initial warming and metamorphosis of the snowpack (pre-melt), followed by a rapid rise indicating the onset of internal snowmelt and thaw-freeze cycles (snowmelt). In contrast, similar seasonal backscatter cycles are absent on seasonal ice, preventing the periodic retrieval of spring/summer transitions. This may be due to the dominance of ice bottom melt over snowmelt, leading to flooding and ice disintegration before strong snowmelt sets in. Resulting snowmelt onset dates on perennial sea ice show the expected latitudinal gradient from early melt onsets (mid-November) in the northern Weddell Sea towards late (end-December) or even absent snowmelt conditions further south. This result is likely related to seasonal variations in solar shortwave radiation (absorption). In addition, observations with different microwave frequencies allow to detect changing snow properties at different depths. We show that short wavelengths of passive microwave observations indicate earlier pre-melt and snowmelt onset dates than longer wavelength scatterometer observations, in response to earlier warming of upper snow layers compared to lower snow layers. Similarly, pre-melt and snowmelt onset dates retrieved from Ku-Band radars were earlier by an average of 11 and 23 days, respectively, than those retrieved from C-Band. This time difference was used to correct melt onset dates retrieved from Ku-Band to compile a consistent time series from </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19850043757&hterms=war&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dwar','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19850043757&hterms=war&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dwar">Dirty snow after nuclear war</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Warren, S. G.; Wiscombe, W. J. 1985-01-01 It is shown that smoke from fires started by nuclear explosions could continue to cause significant disruption even after it has fallen from the atmosphere, by lowering the reflectivity of snow and sea ice surfaces, with possible effects on climate in northern latitudes caused by enhanced absorption of sunlight. The reduced reflectivity could persist for several years on Arctic sea ice and on the ablation area of the Greenland ice sheet. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C32B..04G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C32B..04G">Ultra-Wideband Radars for Measurements over Land and Sea Ice</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Gogineni, S.; Hale, R.; Miller, H. G.; Yan, S.; Rodriguez-Morales, F.; Leuschen, C.; Wang, Z.; Gomez-Garcia, D.; Binder, T.; Steinhage, D.; Gehrmann, M.; Braaten, D. A. 2015-12-01 We developed two ultra-wideband (UWB) radars for measurements over the ice sheets in Greenland and Antarctica and sea ice. One of the UWB radars operates over a 150-600 MHz frequency range with a large, cross-track 24-element array. It is designed to sound ice, image the ice-bed interface, and map internal layers with fine resolution. The 24-element array consists of three 8-element sub-arrays. One of these sub-arrays is mounted under the fuselage of a BT-67 aircraft; the other two are mounted under the wings. The polarization of each antenna element can be individually reconfigured depending on the target of interest. The measured inflight VSWR is less than 2 over the operating range. The fuselage sub-array is used both for transmission and reception, and the wing-mounted sub-arrays are used for reception. The transmitter consists of an 8-channel digital waveform generator to synthesize chirped pulses of selectable pulse width, duration, and bandwidth. It also consists of drivers and power amplifiers to increase the power level of each individual channel to about 1 kW and a fast high-power transmit/receive switch. Each receiver consists of a limiter, switches, low-noise and driver amplifiers, and filters to shape and amplify received signals to the level required for digitization. The digital sub-section consists of timing and control sub-systems and 24 14-bit A/D converters to digitize received signals at a rate of 1.6 GSPS. The radar performance is evaluated using an optical delay line to simulate returns from about 2 km thick ice, and the measured radar loop sensitivity is about 215 dB. The other UWB microwave radar operates over a 2-18 GHz frequency range in Frequency-Modulated Continuous Wave (FM-CW) mode. It is designed to sound more than 1 m of snow over sea ice and map internal layers to a depth about 25-40 m in polar firn and ice. We operated the microwave radar over snow-covered sea ice and mapped snow as thin as 5 cm and as thick as 60 cm. We mapped </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JGRC..122..669J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JGRC..122..669J">Combined observations of Arctic sea ice with near-coincident colocated X-band, C-band, and L-band SAR satellite remote sensing and helicopter-borne measurements</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Johansson, A. M.; King, J. A.; Doulgeris, A. P.; Gerland, S.; Singha, S.; Spreen, G.; Busche, T. 2017-01-01 In this study, we compare colocated near-coincident X-, C-, and L-band fully polarimetry SAR satellite images with helicopter-borne ice thickness measurements acquired during the Norwegian Young sea ICE 2015 (N-ICE2015) expedition in the region of the Arctic Ocean north of Svalbard in April 2015. The air-borne surveys provide near-coincident snow plus ice thickness, surface roughness data, and photographs. This unique data set allows us to investigate how the different frequencies can complement one another for sea ice studies, but also to raise awareness of limitations. X-band and L-band satellite scenes were shown to be a useful complement to the standard SAR frequency for sea ice monitoring (C-band) for lead ice and newly formed sea ice identification. This may be in part be due to the frequency but also the high spatial resolution of these sensors. We found a relatively low correlation between snow plus ice thickness and surface roughness. Therefore, in our dataset ice thickness cannot directly be observed by SAR which has important implications for operational ice charting based on automatic segmentation. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1424016','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1424016">Synchrotron X-ray fluorescence spectroscopy of salts in natural sea ice</a> <a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Obbard, Rachel W.; Lieb-Lappen, Ross M.; Nordick, Katherine V. We describe the use of synchrotron-based X-ray fluorescence spectroscopy to examine the microstructural location of specific elements, primarily salts, in sea ice. This work was part of an investigation of the location of bromine in the sea ice-snowpack-blowing snow system, where it plays a part in the heterogeneous chemistry that contributes to tropospheric ozone depletion episodes. We analyzed samples at beamline 13-ID-E of the Advanced Photon Source at Argonne National Laboratory. Using an 18 keV incident energy beam, we produced elemental maps of salts for sea ice samples from the Ross Sea, Antarctica. The distribution of salts in sea icemore » depends on ice type. In our columnar ice samples, Br was located in parallel lines spaced roughly 0.5 mm apart, corresponding to the spacing of lamellae in the skeletal region during initial ice growth. The maps revealed concentrations of Br in linear features in samples from all but the topmost and bottommost depths. For those samples, the maps revealed rounded features. Calibration of the Br elemental maps showed bulk concentrations to be 5–10 g/m 3, with concentrations ten times larger in the linear features. Through comparison with horizontal thin sections, we could verify that these linear features were brine sheets or layers.« less </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">14</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> <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">15</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> <a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1424016-synchrotron-ray-fluorescence-spectroscopy-salts-natural-sea-ice','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1424016-synchrotron-ray-fluorescence-spectroscopy-salts-natural-sea-ice">Synchrotron X-ray fluorescence spectroscopy of salts in natural sea ice</a> <a target="_blank" href="http://www.osti.gov/pages">DOE PAGES</a> Obbard, Rachel W.; Lieb-Lappen, Ross M.; Nordick, Katherine V.; ... 2016-10-23 We describe the use of synchrotron-based X-ray fluorescence spectroscopy to examine the microstructural location of specific elements, primarily salts, in sea ice. This work was part of an investigation of the location of bromine in the sea ice-snowpack-blowing snow system, where it plays a part in the heterogeneous chemistry that contributes to tropospheric ozone depletion episodes. We analyzed samples at beamline 13-ID-E of the Advanced Photon Source at Argonne National Laboratory. Using an 18 keV incident energy beam, we produced elemental maps of salts for sea ice samples from the Ross Sea, Antarctica. The distribution of salts in sea icemore » depends on ice type. In our columnar ice samples, Br was located in parallel lines spaced roughly 0.5 mm apart, corresponding to the spacing of lamellae in the skeletal region during initial ice growth. The maps revealed concentrations of Br in linear features in samples from all but the topmost and bottommost depths. For those samples, the maps revealed rounded features. Calibration of the Br elemental maps showed bulk concentrations to be 5–10 g/m 3, with concentrations ten times larger in the linear features. Through comparison with horizontal thin sections, we could verify that these linear features were brine sheets or layers.« less </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016TCry...10.1823S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016TCry...10.1823S">Mapping and assessing variability in the Antarctic marginal ice zone, pack ice and coastal polynyas in two sea ice algorithms with implications on breeding success of snow petrels</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Stroeve, Julienne C.; Jenouvrier, Stephanie; Campbell, G. Garrett; Barbraud, Christophe; Delord, Karine 2016-08-01 Sea ice variability within the marginal ice zone (MIZ) and polynyas plays an important role for phytoplankton productivity and krill abundance. Therefore, mapping their spatial extent as well as seasonal and interannual variability is essential for understanding how current and future changes in these biologically active regions may impact the Antarctic marine ecosystem. Knowledge of the distribution of MIZ, consolidated pack ice and coastal polynyas in the total Antarctic sea ice cover may also help to shed light on the factors contributing towards recent expansion of the Antarctic ice cover in some regions and contraction in others. The long-term passive microwave satellite data record provides the longest and most consistent record for assessing the proportion of the sea ice cover that is covered by each of these ice categories. However, estimates of the amount of MIZ, consolidated pack ice and polynyas depend strongly on which sea ice algorithm is used. This study uses two popular passive microwave sea ice algorithms, the NASA Team and Bootstrap, and applies the same thresholds to the sea ice concentrations to evaluate the distribution and variability in the MIZ, the consolidated pack ice and coastal polynyas. Results reveal that the seasonal cycle in the MIZ and pack ice is generally similar between both algorithms, yet the NASA Team algorithm has on average twice the MIZ and half the consolidated pack ice area as the Bootstrap algorithm. Trends also differ, with the Bootstrap algorithm suggesting statistically significant trends towards increased pack ice area and no statistically significant trends in the MIZ. The NASA Team algorithm on the other hand indicates statistically significant positive trends in the MIZ during spring. Potential coastal polynya area and amount of broken ice within the consolidated ice pack are also larger in the NASA Team algorithm. The timing of maximum polynya area may differ by as much as 5 months between algorithms. These </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C13E..04H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C13E..04H">Towards decadal time series of Arctic and Antarctic sea ice thickness from radar altimetry</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Hendricks, S.; Rinne, E. J.; Paul, S.; Ricker, R.; Skourup, H.; Kern, S.; Sandven, S. 2016-12-01 The CryoSat-2 mission has demonstrated the value of radar altimetry to assess the interannual variability and short-term trends of Arctic sea ice over the existing observational record of 6 winter seasons. CryoSat-2 is a particular successful mission for sea ice mass balance assessment due to its novel radar altimeter concept and orbit configuration, but radar altimetry data is available since 1993 from the ERS-1/2 and Envisat missions. Combining these datasets promises a decadal climate data record of sea ice thickness, but inter-mission biases must be taken into account due to the evolution of radar altimeters and the impact of changing sea ice conditions on retrieval algorithm parametrizations. The ESA Climate Change Initiative on Sea Ice aims to extent the list of data records for Essential Climate Variables (ECV's) with a consistent time series of sea ice thickness from available radar altimeter data. We report on the progress of the algorithm development and choices for auxiliary data sets for sea ice thickness retrieval in the Arctic and Antarctic Oceans. Particular challenges are the classification of surface types and freeboard retrieval based on radar waveforms with significantly varying footprint sizes. In addition, auxiliary data sets, e.g. for snow depth, are far less developed in the Antarctic and we will discuss the expected skill of the sea ice thickness ECV's in both hemispheres. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.B13F0697C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.B13F0697C">Arctic sea ice: an investigation into the origin of nitrate using δ15N, δ18O and Δ17O</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Clark, S. C.; Mastorakis, A.; Granger, J.; Aguilar-Islas, A. M.; Hastings, M. G. 2016-12-01 Nitrogen (N) is essential to primary production and is made bioavailable through N2-fixation, and potentially, atmospheric deposition. While the Pacific delivers a significant supply of reactive N to the Arctic, it is unclear if atmospheric deposition helps fuel primary production in the N-deplete western Arctic Ocean. Sea ice and snow provide a unique opportunity to partition the end-member contributions of nitrate (NO3-) from the atmosphere to the ocean. Sea ice cores and snow samples were collected at six stations between 82 and 89°N as part of the U.S. Arctic GEOTRACES expedition in 2015. Sea ice samples had NO3- concentrations ranging from 0.2-1.0 µmol L-1 while snow samples were slightly higher ranging from 1.1-3.7 µmol L-1. The complete isotopic composition of NO3- (δ15N, δ18O, Δ17O) was measured using the denitrifier method on all snow samples and 32 core sub-samples. The Δ17O (Δ17O=δ17O-0.52*δ18O≠0) is a proven diagnostic tool for atmospheric NO3- compared to other NO3- sources because a nonzero Δ17O originates from the influence of ozone on the formation of NO3- in the atmosphere. Snow samples were characteristic of atmospheric NO3- with generally negative δ15N (-5.9-2‰) and highly enriched 17O and 18O (Δ17O=27.1-33.5‰; δ18O =70.8-87.8‰). In contrast, sea ice samples were more enriched in 15N (-0.3-15‰) and depleted in 17O and 18O (Δ17O=0-12.4‰; δ18O=23.3-67.5‰). The presence of a Δ17O>0‰ occurs at various depths, indicating that atmospheric NO3- is an important component of the NO3- found in sea ice. However, the lower Δ17O and δ18O values compared to snow suggest that a significant portion of the NO3- is either derived from seawater and/or issued from biological cycling of atmospheric/seawater reactive N in sea ice. Moreover, it appears that atmospheric NO3- is lost or consumed such that this biological processing of NO3- is most prominent. Recent trends in sea ice decline may result in future changes to the </li> <li> <a target="_blank" onclick="trackOutboundLink('https://pubs.usgs.gov/wri/1999/4176/report.pdf','USGSPUBS'); return false;" href="https://pubs.usgs.gov/wri/1999/4176/report.pdf">Perennial snow and ice volumes on Iliamna Volcano, Alaska, estimated with ice radar and volume modeling</a> <a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Trabant, Dennis C. 1999-01-01 The volume of four of the largest glaciers on Iliamna Volcano was estimated using the volume model developed for evaluating glacier volumes on Redoubt Volcano. The volume model is controlled by simulated valley cross sections that are constructed by fitting third-order polynomials to the shape of the valley walls exposed above the glacier surface. Critical cross sections were field checked by sounding with ice-penetrating radar during July 1998. The estimated volumes of perennial snow and glacier ice for Tuxedni, Lateral, Red, and Umbrella Glaciers are 8.6, 0.85, 4.7, and 0.60 cubic kilometers respectively. The estimated volume of snow and ice on the upper 1,000 meters of the volcano is about 1 cubic kilometer. The volume estimates are thought to have errors of no more than ?25 percent. The volumes estimated for the four largest glaciers are more than three times the total volume of snow and ice on Mount Rainier and about 82 times the total volume of snow and ice that was on Mount St. Helens before its May 18, 1980 eruption. Volcanoes mantled by substantial snow and ice covers have produced the largest and most catastrophic lahars and floods. Therefore, it is prudent to expect that, during an eruptive episode, flooding and lahars threaten all of the drainages heading on Iliamna Volcano. On the other hand, debris avalanches can happen any time. Fortunately, their influence is generally limited to the area within a few kilometers of the summit. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://rosap.ntl.bts.gov/view/dot/32648','DOTNTL'); return false;" href="https://rosap.ntl.bts.gov/view/dot/32648">North American study on contracting snow and ice response : final report.</a> <a target="_blank" href="http://ntlsearch.bts.gov/tris/index.do">DOT National Transportation Integrated Search</a> 2017-01-01 Snow and ice control operations are a vital function often conducted by state and local transportation agencies. Many states are choosing to contract snow and ice response services, instead of or in addition to the use of in-house forces, to maintain... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ISPAr42.3.1259M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ISPAr42.3.1259M">Sea Ice Thickness Measurement by Ground Penetrating Radar for Ground Truth of Microwave Remote Sensing Data</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Matsumoto, M.; Yoshimura, M.; Naoki, K.; Cho, K.; Wakabayashi, H. 2018-04-01 Observation of sea ice thickness is one of key issues to understand regional effect of global warming. One of approaches to monitor sea ice in large area is microwave remote sensing data analysis. However, ground truth must be necessary to discuss the effectivity of this kind of approach. The conventional method to acquire ground truth of ice thickness is drilling ice layer and directly measuring the thickness by a ruler. However, this method is destructive, time-consuming and limited spatial resolution. Although there are several methods to acquire ice thickness in non-destructive way, ground penetrating radar (GPR) can be effective solution because it can discriminate snow-ice and ice-sea water interface. In this paper, we carried out GPR measurement in Lake Saroma for relatively large area (200 m by 300 m, approximately) aiming to obtain grand truth for remote sensing data. GPR survey was conducted at 5 locations in the area. The direct measurement was also conducted simultaneously in order to calibrate GPR data for thickness estimation and to validate the result. Although GPR Bscan image obtained from 600MHz contains the reflection which may come from a structure under snow, the origin of the reflection is not obvious. Therefore, further analysis and interpretation of the GPR image, such as numerical simulation, additional signal processing and use of 200 MHz antenna, are required to move on thickness estimation. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28708127','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28708127">An active bacterial community linked to high chl-a concentrations in Antarctic winter-pack ice and evidence for the development of an anaerobic sea-ice bacterial community.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Eronen-Rasimus, Eeva; Luhtanen, Anne-Mari; Rintala, Janne-Markus; Delille, Bruno; Dieckmann, Gerhard; Karkman, Antti; Tison, Jean-Louis 2017-10-01 Antarctic sea-ice bacterial community composition and dynamics in various developmental stages were investigated during the austral winter in 2013. Thick snow cover likely insulated the ice, leading to high (<4 μg l -1 ) chlorophyll-a (chl-a) concentrations and consequent bacterial production. Typical sea-ice bacterial genera, for example, Octadecabacter, Polaribacter and Glaciecola, often abundant in spring and summer during the sea-ice algal bloom, predominated in the communities. The variability in bacterial community composition in the different ice types was mainly explained by the chl-a concentrations, suggesting that as in spring and summer sea ice, the sea-ice bacteria and algae may also be coupled during the Antarctic winter. Coupling between the bacterial community and sea-ice algae was further supported by significant correlations between bacterial abundance and production with chl-a. In addition, sulphate-reducing bacteria (for example, Desulforhopalus) together with odour of H 2 S were observed in thick, apparently anoxic ice, suggesting that the development of the anaerobic bacterial community may occur in sea ice under suitable conditions. In all, the results show that bacterial community in Antarctic sea ice can stay active throughout the winter period and thus possible future warming of sea ice and consequent increase in bacterial production may lead to changes in bacteria-mediated processes in the Antarctic sea-ice zone. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..15.2629R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..15.2629R">Air- ice-snow interaction in the Northern Hemisphere under different stability conditions</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Repina, Irina; Chechin, Dmitry; Artamonov, Arseny 2013-04-01 The traditional parameterizations of the atmospheric boundary layer are based on similarity theory and the coefficients of turbulent transfer, describing the atmospheric-surface interaction and the diffusion of impurities in the operational models of air pollution, weather forecasting and climate change. Major drawbacks of these parameterizations is that they are not applicable for the extreme conditions of stratification and currents over complex surfaces (such as sea ice, marginal ice zone or stormy sea). These problem could not be overcome within the framework of classical theory, i.e, by rectifying similarity functions or through the introduction of amendments to the traditional turbulent closure schemes. Lack of knowledge on the structure of the surface air layer and the exchange of momentum, heat and moisture between the rippling water surface and the atmosphere at different atmospheric stratifications is at present the major obstacle which impede proper functioning of the operational global and regional weather prediction models and expert models of climate and climate change. This is especially important for the polar regions, where in winter time the development of strong stable boundary layer in the presence of polynyas and leads usually occur. Experimental studies of atmosphere-ice-snow interaction under different stability conditions are presented. Strong stable and unstable conditions are discussed. Parametrizations of turbulent heat and gas exchange at the atmosphere ocean interface are developed. The dependence of the exchange coefficients and aerodynamic roughness on the atmospheric stratification over the snow and ice surface is experimentally confirmed. The drag coefficient is reduced with increasing stability. The behavior of the roughness parameter is simple. This result was obtained in the Arctic from the measurements over hummocked surface. The value of the roughness in the Arctic is much less than that observed over the snow in the middle and </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JGRC..121.5916A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JGRC..121.5916A">Timing and regional patterns of snowmelt on Antarctic sea ice from passive microwave satellite observations</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Arndt, Stefanie; Willmes, Sascha; Dierking, Wolfgang; Nicolaus, Marcel 2016-08-01 An improved understanding of the temporal variability and the spatial distribution of snowmelt on Antarctic sea ice is crucial to better quantify atmosphere-ice-ocean interactions, in particular sea-ice mass and energy budgets. It is therefore important to understand the mechanisms that drive snowmelt, both at different times of the year and in different regions around Antarctica. In this study, we combine diurnal brightness temperature differences (dTB(37 GHz)) and ratios (TB(19 GHz)/TB(37 GHz)) to detect and classify snowmelt processes. We distinguish temporary snowmelt from continuous snowmelt to characterize dominant melt patterns for different Antarctic sea-ice regions from 1988/1989 to 2014/2015. Our results indicate four characteristic melt types. On average, 38.9 ± 6.0% of all detected melt events are diurnal freeze-thaw cycles in the surface snow layer, characteristic of temporary melt (Type A). Less than 2% reveal immediate continuous snowmelt throughout the snowpack, i.e., strong melt over a period of several days (Type B). In 11.7 ± 4.0%, Type A and B take place consecutively (Type C), and for 47.8 ± 6.8% no surface melt is observed at all (Type D). Continuous snowmelt is primarily observed in the outflow of the Weddell Gyre and in the northern Ross Sea, usually 17 days after the onset of temporary melt. Comparisons with Snow Buoy data suggest that also the onset of continuous snowmelt does not translate into changes in snow depth for a longer period but might rather affect the internal stratigraphy and density structure of the snowpack. Considering the entire data set, the timing of snowmelt processes does not show significant temporal trends. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=PIA03717&hterms=Russia&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3DRussia','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=PIA03717&hterms=Russia&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3DRussia">Distinguishing Clouds from Ice over the East Siberian Sea, Russia</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 2002-01-01 As a consequence of its capability to retrieve cloud-top elevations, stereoscopic observations from the Multi-angle Imaging SpectroRadiometer (MISR) can discriminate clouds from snow and ice. The central portion of Russia's East Siberian Sea, including one of the New Siberian Islands, Novaya Sibir, are portrayed in these views from data acquired on May 28, 2002.The left-hand image is a natural color view from MISR's nadir camera. On the right is a height field retrieved using automated computer processing of data from multiple MISR cameras. Although both clouds and ice appear white in the natural color view, the stereoscopic retrievals are able to identify elevated clouds based on the geometric parallax which results when they are observed from different angles. Owing to their elevation above sea level, clouds are mapped as green and yellow areas, whereas land, sea ice, and very low clouds appear blue and purple. Purple, in particular, denotes elevations very close to sea level. The island of Novaya Sibir is located in the lower left of the images. It can be identified in the natural color view as the dark area surrounded by an expanse of fast ice. In the stereo map the island appears as a blue region indicating its elevation of less than 100 meters above sea level. Areas where the automated stereo processing failed due to lack of sufficient spatial contrast are shown in dark gray. The northern edge of the Siberian mainland can be found at the very bottom of the panels, and is located a little over 250 kilometers south of Novaya Sibir. Pack ice containing numerous fragmented ice floes surrounds the fast ice, and narrow areas of open ocean are visible.The East Siberian Sea is part of the Arctic Ocean and is ice-covered most of the year. The New Siberian Islands are almost always covered by snow and ice, and tundra vegetation is very scant. Despite continuous sunlight from the end of April until the middle of August, the ice between the island and the </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20080030353','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20080030353">Enhancement of the MODIS Snow and Ice Product Suite Utilizing Image Segmentation</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Tilton, James C.; Hall, Dorothy K.; Riggs, George A. 2006-01-01 A problem has been noticed with the current NODIS Snow and Ice Product in that fringes of certain snow fields are labeled as "cloud" whereas close inspection of the data indicates that the correct labeling is a non-cloud category such as snow or land. This occurs because the current MODIS Snow and Ice Product generation algorithm relies solely on the MODIS Cloud Mask Product for the labeling of image pixels as cloud. It is proposed here that information obtained from image segmentation can be used to determine when it is appropriate to override the cloud indication from the cloud mask product. Initial tests show that this approach can significantly reduce the cloud "fringing" in modified snow cover labeling. More comprehensive testing is required to determine whether or not this approach consistently improves the accuracy of the snow and ice product. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70182747','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70182747">An automated approach for mapping persistent ice and snow cover over high latitude regions</a> <a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Selkowitz, David J.; Forster, Richard R. 2016-01-01 We developed an automated approach for mapping persistent ice and snow cover (glaciers and perennial snowfields) from Landsat TM and ETM+ data across a variety of topography, glacier types, and climatic conditions at high latitudes (above ~65°N). Our approach exploits all available Landsat scenes acquired during the late summer (1 August–15 September) over a multi-year period and employs an automated cloud masking algorithm optimized for snow and ice covered mountainous environments. Pixels from individual Landsat scenes were classified as snow/ice covered or snow/ice free based on the Normalized Difference Snow Index (NDSI), and pixels consistently identified as snow/ice covered over a five-year period were classified as persistent ice and snow cover. The same NDSI and ratio of snow/ice-covered days to total days thresholds applied consistently across eight study regions resulted in persistent ice and snow cover maps that agreed closely in most areas with glacier area mapped for the Randolph Glacier Inventory (RGI), with a mean accuracy (agreement with the RGI) of 0.96, a mean precision (user’s accuracy of the snow/ice cover class) of 0.92, a mean recall (producer’s accuracy of the snow/ice cover class) of 0.86, and a mean F-score (a measure that considers both precision and recall) of 0.88. We also compared results from our approach to glacier area mapped from high spatial resolution imagery at four study regions and found similar results. Accuracy was lowest in regions with substantial areas of debris-covered glacier ice, suggesting that manual editing would still be required in these regions to achieve reasonable results. The similarity of our results to those from the RGI as well as glacier area mapped from high spatial resolution imagery suggests it should be possible to apply this approach across large regions to produce updated 30-m resolution maps of persistent ice and snow cover. In the short term, automated PISC maps can be used to rapidly </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012EGUGA..14.3174F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012EGUGA..14.3174F">Validation and Interpretation of a new sea ice GlobIce dataset using buoys and the CICE sea ice model</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C51A0663S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C51A0663S">Short-term sea ice forecasts with the RASM-ESRL coupled model: A testbed for improving simulations of ocean-ice-atmosphere interactions in the marginal ice zone</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Solomon, A.; Cox, C. J.; Hughes, M.; Intrieri, J. M.; Persson, O. P. G. 2015-12-01 The dramatic decrease of Arctic sea-ice has led to a new Arctic sea-ice paradigm and to increased commercial activity in the Arctic Ocean. NOAA's mission to provide accurate and timely sea-ice forecasts, as explicitly outlined in the National Ocean Policy and the U.S. National Strategy for the Arctic Region, needs significant improvement across a range of time scales to improve safety for human activity. Unfortunately, the sea-ice evolution in the new Arctic involves the interaction of numerous physical processes in the atmosphere, ice, and ocean, some of which are not yet understood. These include atmospheric forcing of sea-ice movement through stress and stress deformation; atmospheric forcing of sea-ice melt and formation through energy fluxes; and ocean forcing of the atmosphere through new regions of seasonal heat release. Many of these interactions involve emerging complex processes that first need to be understood and then incorporated into forecast models in order to realize the goal of useful sea-ice forecasting. The underlying hypothesis for this study is that errors in simulations of "fast" atmospheric processes significantly impact the forecast of seasonal sea-ice retreat in summer and its advance in autumn in the marginal ice zone (MIZ). We therefore focus on short-term (0-20 day) ice-floe movement, the freeze-up and melt-back processes in the MIZ, and the role of storms in modulating stress and heat fluxes. This study uses a coupled ocean-atmosphere-seaice forecast model as a testbed to investigate; whether ocean-sea ice-atmosphere coupling improves forecasts on subseasonal time scales, where systematic biases develop due to inadequate parameterizations (focusing on mixed-phase clouds and surface fluxes), how increased atmospheric resolution of synoptic features improves the forecasts, and how initialization of sea ice area and thickness and snow depth impacts the skill of the forecasts. Simulations are validated with measurements at pan-Arctic land </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.C11C..05F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.C11C..05F">A Decade of Arctic Sea Ice Thickness Change from Airborne and Satellite Altimetry (Invited)</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Farrell, S. L.; Richter-Menge, J.; Kurtz, N. T.; McAdoo, D. C.; Newman, T.; Zwally, H.; Ruth, J. 2013-12-01 Altimeters on both airborne and satellite platforms provide direct measurements of sea ice freeboard from which sea ice thickness may be calculated. Satellite altimetry observations of Arctic sea ice from ICESat and CryoSat-2 indicate a significant decline in ice thickness, and volume, over the last decade. During this time the ice pack has experienced a rapid change in its composition, transitioning from predominantly thick, multi-year ice to thinner, increasingly seasonal ice. We will discuss the regional trends in ice thickness derived from ICESat and IceBridge altimetry between 2003 and 2013, contrasting observations of the multi-year ice pack with seasonal ice zones. ICESat ceased operation in 2009, and the final, reprocessed data set became available recently. We extend our analysis to April 2013 using data from the IceBridge airborne mission, which commenced operations in 2009. We describe our current efforts to more accurately convert from freeboard to ice thickness, with a modified methodology that corrects for range errors, instrument biases, and includes an enhanced treatment of snow depth, with respect to ice type. With the planned launch by NASA of ICESat-2 in 2016 we can expect continuity of the sea ice thickness time series through the end of this decade. Data from the ICESat-2 mission, together with ongoing observations from CryoSat-2, will allow us to understand both the decadal trends and inter-annual variability in the Arctic sea ice thickness record. We briefly present the status of planned ICESat-2 sea ice data products, and demonstrate the utility of micro-pulse, photon-counting laser altimetry over sea ice. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1910064G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1910064G">Multi-decadal evolution of ice/snow covers in the Mont-Blanc massif (France)</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Guillet, Grégoire; Ravanel, Ludovic 2017-04-01 Dynamics and evolution of the major glaciers of the Mont-Blanc massif have been vastly studied since the XXth century. Ice/snow covers on steep rock faces as part of the cryosphere however remain poorly studied with only qualitative descriptions existing. The study of ice/snow covers is primordial to further understand permafrost degradation throughout the Mont-Blanc massif and to improve safety and prevention for mountain sports practitioners. This study focuses on quantifying the evolution of ice/snow covers surface during the past century using a specially developed monoplotting tool using Bayesian statistics and Markov Chain Monte Carlo algorithms. Combining digital elevation models and photographs covering a time-span of 110 years, we calculated the ice/snow cover surface for 3 study sites — North faces of the Tour Ronde (3792 m a.s.l.) and the Grandes Jorasses (4208 m a.s.l.) and Triangle du Tacul (3970 m a.s.l.) — and deduced the evolution of their area throughout the XXth century. First results are showing several increase/decrease periods. The first decrease in ice/snow cover surface occurs between the 1940's and the 1950's. It is followed by an increase up to the 1980's. Since then, ice/snow covers show a general decrease in surface which is faster since the 2010's. Furthermore, the gain/loss during the increase/decrease periods varies with the considered ice/snow cover, making it an interesting cryospheric entity of its own. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24015900','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24015900">Sea ice ecosystems.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> 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. </li> <li> <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">SIPEX 2012: Extreme sea-ice and atmospheric conditions off East Antarctica</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Heil, P.; Stammerjohn, S.; Reid, P.; Massom, R. A.; Hutchings, J. K. 2016-09-01 In 2012, Antarctic sea-ice 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-ice-atmosphere system off East Antarctica, prior to and during the Sea Ice Physics and Ecosystems eXperiment [SIPEX] 2012, by exploring relationships between atmospheric and oceanic forcing together with the sea-ice 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-ice-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 sea-ice extent recorded in late September. In contrast to the weak circum-Antarctic conditions, the East Antarctic sector (including the SIPEX 2012 region) experienced positive sea-ice extent and concentration anomalies during most of 2012, coincident with negative atmospheric pressure and sea-surface temperature anomalies. Heavily deformed sea ice appeared to be associated with intensified wind stress due to increased cyclonicity as well as an increased influx of sea ice from the east. This increased westward ice 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 sea ice 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 sea-ice extent from the western Ross Sea during austral winter </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19840019240','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19840019240">Satellite remote sensing over ice</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Thomas, R. H. 1984-01-01 Satellite remote sensing provides unique opportunities for observing ice-covered terrain. Passive-microwave data give information on snow extent on land, sea-ice extent and type, and zones of summer melting on the polar ice sheets, with the potential for estimating snow-accumulation rates on these ice sheets. All weather, high-resolution imagery of sea ice is obtained using synthetic aperture radars, and ice-movement vectors can be deduced by comparing sequential images of the same region. Radar-altimetry data provide highly detailed information on ice-sheet topography, with the potential for deducing thickening/thinning rates from repeat surveys. The coastline of Antarctica can be mapped accurately using altimetry data, and the size and spatial distribution of icebergs can be monitored. Altimetry data also distinguish open ocean from pack ice and they give an indication of sea-ice characteristics. </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">15</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> <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">16</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> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19860043882&hterms=Antarctic+icebergs&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3DAntarctic%2Bicebergs','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19860043882&hterms=Antarctic+icebergs&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3DAntarctic%2Bicebergs">Satellite remote sensing over ice</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Thomas, R. H. 1986-01-01 Satellite remote sensing provides unique opportunities for observing ice-covered terrain. Passive-microwave data give information on snow extent on land, sea-ice extent and type, and zones of summer melting on the polar ice sheets, with the potential for estimating snow-accumulation rates on these ice sheets. All weather, high-resolution imagery of sea ice is obtained using synthetic aperture radars, and ice-movement vectors can be deduced by comparing sequential images of the same region. Radar-altimetry data provide highly detailed information on ice-sheet topography, with the potential for deducing thickening/thinning rates from repeat surveys. The coastline of Antarctica can be mapped accurately using altimetry data, and the size and spatial distribution of icebergs can be monitored. Altimetry data also distinguish open ocean from pack ice and they give an indication of sea-ice characteristics. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-200910220009HQ.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-200910220009HQ.html">Ice Bridge Antarctic Sea Ice</a> <a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a> 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‚Äôs Operation Ice Bridge airborne Earth science mission to study Antarctic ice sheets, sea ice, and ice shelves. Photo Credit: (NASA/Jane Peterson) </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017TCry...11.2611C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017TCry...11.2611C">Quantifying bioalbedo: a new physically based model and discussion of empirical methods for characterising biological influence on ice and snow albedo</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Cook, Joseph M.; Hodson, Andrew J.; Gardner, Alex S.; Flanner, Mark; Tedstone, Andrew J.; Williamson, Christopher; Irvine-Fynn, Tristram D. L.; Nilsson, Johan; Bryant, Robert; Tranter, Martyn 2017-11-01 The darkening effects of biological impurities on ice and snow have been recognised as a control on the surface energy balance of terrestrial snow, sea ice, glaciers and ice sheets. With a heightened interest in understanding the impacts of a changing climate on snow and ice processes, quantifying the impact of biological impurities on ice and snow albedo (<q>bioalbedo</q>) and its evolution through time is a rapidly growing field of research. However, rigorous quantification of bioalbedo has remained elusive because of difficulties in isolating the biological contribution to ice albedo from that of inorganic impurities and the variable optical properties of the ice itself. For this reason, isolation of the biological signature in reflectance data obtained from aerial/orbital platforms has not been achieved, even when ground-based biological measurements have been available. This paper provides the cell-specific optical properties that are required to model the spectral signatures and broadband darkening of ice. Applying radiative transfer theory, these properties provide the physical basis needed to link biological and glaciological ground measurements with remotely sensed reflectance data. Using these new capabilities we confirm that biological impurities can influence ice albedo, then we identify 10 challenges to the measurement of bioalbedo in the field with the aim of improving future experimental designs to better quantify bioalbedo feedbacks. These challenges are (1) ambiguity in terminology, (2) characterising snow or ice optical properties, (3) characterising solar irradiance, (4) determining optical properties of cells, (5) measuring biomass, (6) characterising vertical distribution of cells, (7) characterising abiotic impurities, (8) surface anisotropy, (9) measuring indirect albedo feedbacks, and (10) measurement and instrument configurations. This paper aims to provide a broad audience of glaciologists and biologists with an overview of radiative </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017TCry...11.2867M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017TCry...11.2867M">Optical properties of sea ice doped with black carbon - an experimental and radiative-transfer modelling comparison</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Marks, Amelia A.; Lamare, Maxim L.; King, Martin D. 2017-12-01 Radiative-transfer calculations of the light reflectivity and extinction coefficient in laboratory-generated sea ice doped with and without black carbon demonstrate that the radiative-transfer model TUV-snow can be used to predict the light reflectance and extinction coefficient as a function of wavelength. The sea ice is representative of first-year sea ice containing typical amounts of black carbon and other light-absorbing impurities. The experiments give confidence in the application of the model to predict albedo of other sea ice fabrics. Sea ices, ˜ 30 cm thick, were generated in the Royal Holloway Sea Ice Simulator ( ˜ 2000 L tanks) with scattering cross sections measured between 0.012 and 0.032 m2 kg-1 for four ices. Sea ices were generated with and without ˜ 5 cm upper layers containing particulate black carbon. Nadir reflectances between 0.60 and 0.78 were measured along with extinction coefficients of 0.1 to 0.03 cm-1 (e-folding depths of 10-30 cm) at a wavelength of 500 nm. Values were measured between light wavelengths of 350 and 650 nm. The sea ices generated in the Royal Holloway Sea Ice Simulator were found to be representative of natural sea ices. Particulate black carbon at mass ratios of ˜ 75, ˜ 150 and ˜ 300 ng g-1 in a 5 cm ice layer lowers the albedo to 97, 90 and 79 % of the reflectivity of an undoped <q>clean</q> sea ice (at a wavelength of 500 nm). </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFMGC11A0540O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFMGC11A0540O">Impacts of Organic Macromolecules, Chlorophyll and Soot on Arctic Sea Ice</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Ogunro, O. O.; Wingenter, O. W.; Elliott, S.; Flanner, M.; Dubey, M. K. 2014-12-01 Recent intensification of Arctic amplification can be strongly connected to positive feedback relating black carbon deposition to sea ice surface albedo. In addition to soot deposition on the ice and snow pack, ice algal chlorophyll is likely to compete as an absorber and redistributor of energy. Hence, solar radiation absorption by chlorophyll and some components of organic macromolecules in/under the ice column is currently being examined to determine the level of influence on predicted rate of ice loss. High amounts of organic macromolecules and chlorophyll are produced in global sea ice by the bottom microbial community and also in vertically distributed layers where substantial biological activities take place. Brine channeling in columnar ice can allow for upward flow of nutrients which leads to greater primary production in the presence of moderate light. Modeling of the sea-ice processes in tandem with experiments and field observations promises rapid progress in enhancing Arctic ice predictions. We are designing and conducting global climate model experiments to determine the impact of organic macromolecules and chlorophyll on Arctic sea ice. Influences on brine network permeability and radiation/albedo will be considered in this exercise. Absorption by anthropogenic materials such as soot and black carbon will be compared with that of natural pigments. We will indicate areas of soot and biological absorption dominance in the sense of single scattering, then couple into a full radiation transfer scheme to attribute the various contributions to polar climate change amplification. The work prepares us to study more traditional issues such as chlorophyll warming of the pack periphery and chemical effects of the flow of organics from ice internal communities. The experiments started in the Arctic will broaden to include Antarctic sea ice and shelves. Results from the Arctic simulations will be presented. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C33E..08N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C33E..08N">Arctic Sea Ice Classification and Mapping for Surface Albedo Parameterization in Sea Ice Modeling</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUFM.C51B..01S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUFM.C51B..01S">Impacts of Declining Arctic Sea Ice: An International Challenge</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Serreze, M. 2008-12-01 As reported by the National Snow and Ice Data Center in late August of 2008, Arctic sea ice extent had already fallen to its second lowest level since regular monitoring began by satellite. As of this writing, we were closing in on the record minimum set in September of 2007. Summers may be free of sea ice by the year 2030. Recognition is growing that ice loss will have environmental impacts that may extend well beyond the Arctic. The Arctic Ocean will in turn become more accessible, not just to tourism and commercial shipping, but to exploitation of oil wealth at the bottom of the ocean. In recognition of growing accessibility and oil operations, the United States Coast Guard set up temporary bases this summer at Barrow and Prudhoe Bay, AK, from which they conducted operations to test their readiness and capabilities, such as for search and rescue. The Canadians have been busy showing a strong Arctic presence. In August, a German crew traversed the Northwest Passage from east to west in one of their icebreakers, the Polarstern. What are the major national and international research efforts focusing on the multifaceted problem of declining sea ice? What are the areas of intersection, and what is the state of collaboration? How could national and international collaboration be improved? This talk will review some of these issues. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JGRC..122.7466C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JGRC..122.7466C">Modeling Arctic sea-ice algae: Physical drivers of spatial distribution and algae phenology</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Castellani, Giulia; Losch, Martin; Lange, Benjamin A.; Flores, Hauke 2017-09-01 Algae growing in sea ice represent a source of carbon for sympagic and pelagic ecosystems and contribute to the biological carbon pump. The biophysical habitat of sea ice on large scales and the physical drivers of algae phenology are key to understanding Arctic ecosystem dynamics and for predicting its response to ongoing Arctic climate change. In addition, quantifying potential feedback mechanisms between algae and physical processes is particularly important during a time of great change. These mechanisms include a shading effect due to the presence of algae and increased basal ice melt. The present study shows pan-Arctic results obtained from a new Sea Ice Model for Bottom Algae (SIMBA) coupled with a 3-D sea-ice-ocean model. The model is evaluated with data collected during a ship-based campaign to the Eastern Central Arctic in summer 2012. The algal bloom is triggered by light and shows a latitudinal dependency. Snow and ice also play a key role in ice algal growth. Simulations show that after the spring bloom, algae are nutrient limited before the end of summer and finally they leave the ice habitat during ice melt. The spatial distribution of ice algae at the end of summer agrees with available observations, and it emphasizes the importance of thicker sea-ice regions for hosting biomass. Particular attention is given to the distinction between level ice and ridged ice. Ridge-associated algae are strongly light limited, but they can thrive toward the end of summer, and represent an additional carbon source during the transition into polar night. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFM.C41A0425S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFM.C41A0425S">Precipitation Impacts of a Shrinking Arctic Sea Ice Cover</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Stroeve, J. C.; Frei, A.; Gong, G.; Ghatak, D.; Robinson, D. A.; Kindig, D. 2009-12-01 Since the beginning of the modern satellite record in October 1978, the extent of Arctic sea ice has declined in all months, with the strongest downward trend at the end of the melt season in September. Recently the September trends have accelerated. Through 2001, the extent of September sea ice was decreasing at a rate of -7 per cent per decade. By 2006, the rate of decrease had risen to -8.9 per cent per decade. In September 2007, Arctic sea ice extent fell to its lowest level recorded, 23 per cent below the previous record set in 2005, boosting the downward trend to -10.7 per cent per decade. Ice extent in September 2008 was the second lowest in the satellite record. Including 2008, the trend in September sea ice extent stands at -11.8 percent per decade. Compared to the 1970s, September ice extent has retreated by 40 per cent. Summer 2009 looks to repeat the anomalously low ice conditions that characterized the last couple of years. Scientists have long expected that a shrinking Arctic sea ice cover will lead to strong warming of the overlying atmosphere, and as a result, affect atmospheric circulation and precipitation patterns. Recent results show clear evidence of Arctic warming linked to declining ice extent, yet observational evidence for responses of atmospheric circulation and precipitation patterns is just beginning to emerge. Rising air temperatures should lead to an increase in the moisture holding capacity of the atmosphere, with the potential to impact autumn precipitation. Although climate models predict a hemispheric wide decrease in snow cover as atmospheric concentrations of GHGs increase, increased precipitation, particular in autumn and winter may result as the Arctic transitions towards a seasonally ice free state. In this study we use atmospheric reanalysis data and a cyclone tracking algorithm to investigate the influence of recent extreme ice loss years on precipitation patterns in the Arctic and the Northern Hemisphere. Results show </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120003985','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120003985">Seafloor Control on Sea Ice</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19900016074','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19900016074">A laboratory investigation into microwave backscattering from sea ice. Ph.D. Thesis</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Bredow, Jonathan W. 1989-01-01 The sources of scattering of artificial sea ice were determined, backscatter measurements semi-quantitatively were compared with theoretical predictions, and inexpensive polarimetric radars were developed for sea ice backscatter studies. A brief review of the dielectric properties of sea ice and of commonly used surface and volume scattering theories is presented. A description is provided of the backscatter measurements performed and experimental techniques used. The development of inexpensive short-range polarimetric radars is discussed. The steps taken to add polarimetric capability to a simple FM-W radar are considered as are sample polarimetric phase measurements of the radar. Ice surface characterization data and techniques are discussed, including computation of surface rms height and correlation length and air bubble distribution statistics. A method is also presented of estimating the standard deviation of rms height and correlation length for cases of few data points. Comparisons were made of backscatter measurements and theory. It was determined that backscatter from an extremely smooth saline ice surface at C band cannot be attributed only to surface scatter. It was found that snow cover had a significant influence on backscatter from extremely smooth saline ice at C band. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20120015900&hterms=export&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dexport','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20120015900&hterms=export&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dexport">Variability and Trends in Sea Ice Extent and Ice Production in the Ross Sea</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A41C0068W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A41C0068W">Arctic Moisture Source for Eurasian Snow Cover Variations in Autumn</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Wegmann, M. 2015-12-01 Global warming is enhanced at high northern latitudes where the Arctic surface airtemperature has risen at twice the rate of the global average in recent decades - afeature called Arctic amplification. This recent Arctic warming signal likely resultsfrom several factors such as the albedo feedback due to a diminishing cryosphere,enhanced poleward atmospheric and oceanic transport, and change in humidity. Moreover, Arcticsummer sea-ice extent has declined by more than 10% per decade since the start ofthe satellite era (e.g. Stroeve et al., 2012), culminating in a new record low inSeptember 2012.Eurasian snow cover changes have been suggested as a driver for changes in theArctic Oscillation and might provide a link between sea ice decline in the Arcticduring summer and atmospheric circulation in the following winter. However, themechanism connecting snow cover in Eurasia to sea ice decline in autumn is stillunder debate. Our analysis focuses on sea ice decline in the Barents-Kara Sea region, which allowsus to specify regions of interest for FLEXPART forward and backwards moisturetrajectories. Based on Eularian and Lagrangian diagnostics from ERA-INTERIM, wecan address the origin and cause of late autumn snow depth variations in a dense(snow observations from 820 land stations), unutilized observational datasets over theCommonwealth of Independent States.Open waters in the Barents and Kara Sea have been shown to increase the diabaticheating of the atmosphere, which amplifies baroclinic cyclones and might induce aremote atmospheric response by triggering stationary Rossby waves (Honda et al.2009).In agreement with these studies, our results show enhanced storm activity originatingat the Barents and Kara with disturbances entering the continent through a smallsector from the Barents and Kara Seas. Maxima in storm activity trigger increasing uplift, oftenaccompanied by positive snowfall and snow depth anomalies.We show that declining sea ice in the Barents and Kara Seas </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016CSR...118..154S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016CSR...118..154S">Surface water mass composition changes captured by cores of Arctic land-fast sea ice</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Smith, I. J.; Eicken, H.; Mahoney, A. R.; Van Hale, R.; Gough, A. J.; Fukamachi, Y.; Jones, J. 2016-04-01 In the Arctic, land-fast sea ice growth can be influenced by fresher water from rivers and residual summer melt. This paper examines a method to reconstruct changes in water masses using oxygen isotope measurements of sea ice cores. To determine changes in sea water isotope composition over the course of the ice growth period, the output of a sea ice thermodynamic model (driven with reanalysis data, observations of snow depth, and freeze-up dates) is used along with sea ice oxygen isotope measurements and an isotopic fractionation model. Direct measurements of sea ice growth rates are used to validate the output of the sea ice growth model. It is shown that for sea ice formed during the 2011/2012 ice growth season at Barrow, Alaska, large changes in isotopic composition of the ocean waters were captured by the sea ice isotopic composition. Salinity anomalies in the ocean were also tracked by moored instruments. These data indicate episodic advection of meteoric water, having both lower salinity and lower oxygen isotopic composition, during the winter sea ice growth season. Such advection of meteoric water during winter is surprising, as no surface meltwater and no local river discharge should be occurring at this time of year in that area. How accurately changes in water masses as indicated by oxygen isotope composition can be reconstructed using oxygen isotope analysis of sea ice cores is addressed, along with methods/strategies that could be used to further optimize the results. The method described will be useful for winter detection of meteoric water presence in Arctic fast ice regions, which is important for climate studies in a rapidly changing Arctic. Land-fast sea ice effective fractionation coefficients were derived, with a range of +1.82‰ to +2.52‰. Those derived effective fractionation coefficients will be useful for future water mass component proportion calculations. In particular, the equations given can be used to inform choices made when </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFM.C53B..07A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFM.C53B..07A">Summer Sea ice in the Pacific Arctic sector from the CHINARE-2010 cruise</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Ackley, S. F.; Xie, H.; Lei, R.; Huang, W.; Chinare 2010 Arctic Sea Ice Group 2010-12-01 The Fourth Chinese National Arctic Research Expedition (CHINARE) from July 1 to Sep. 23, 2010, the last Chinese campaign in Arctic Ocean contributing to the fourth International Polar Year (IPY), conducted comprehensive scientific studies on ocean-ice-atmosphere interaction and the marine ecosystem’s response to climatic change in Arctic. This paper presents an overview on sea ice (ice concentration, floe size, melt pond coverage, sea ice and snow thickness) of the Pacific Arctic sector, in particular between 150°W to 180°W to 86°N, based on: (1) underway visual observations of sea ice at half-hourly and automatic cameras recording (both side looking from the icebreaker R.V. Xuelong) every 10 to 15 seconds; (2) a downward-looking video mounted on the left side of the vessel at a height of 7 m above waterline recording overturning of ice floes; (3) on-site measurements of snow and ice thickness using drilling and electromagnetic instrument EM31 (9.8 kHz) at eight short-term (~3 hours each) and one 12-day ice stations; (4) six flights of aerial photogrammetry from helicopter, and (5) Satellite data (AMSE-E ice concentration and ENVISAT ASAR) and NIC ice charts) that extended the observations/measurements along beyond the ship track and airborne flights. In the northward leg, the largest ice concentration zone was in the area starting from ~75°N (July 29), with ice concentration of 60-90% (mean ~80%), ice thickness of 1.5-2m, melt ponds of 10-50% of ice, ridged ice of 10-30% of ice, and floe size of 100’s meters to kms. The 12-day ice station (from Aug 7-19), started at 86.92°N/178.88°W and moved a total of 175.7km, was on an ice floe over 100 km2 in size and ~2 m in mean thickness. There were two heavy and several slight snowfall events in the period (July 29 to Aug 19). Snow thickness varies from 5cm to 15 cm, and melted about 5cm during the 12-day ice camp. In the southward leg, the largest sea ice concentration zone was in the area between 87°N to 80� </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.C14B..04C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.C14B..04C">Polarimetric C-/X-band Synthetic Aperture Radar Observations of Melting Sea Ice in the Canadian Arctic Archipelago</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Casey, J. A.; Beckers, J. F.; Brossier, E.; Haas, C. 2013-12-01 Operational ice information services rely heavily on space-borne synthetic aperture radar (SAR) data for the production of ice charts to meet their mandate of providing timely and accurate sea ice information to support safe and efficient marine operations. During the summer melt period, the usefulness of SAR data for sea ice monitoring is limited by the presence of wet snow and melt ponds on the ice surface, which can mask the signature of the underlying ice. This is a critical concern for ice services whose clients (e.g. commercial shipping, cruise tourism, resource exploration and extraction) are most active at this time of year when sea ice is at its minimum extent, concentration and thickness. As a result, there is a need to further quantify the loss of ice information in SAR data during the melt season and to identify what information can still be retrieved about ice surface conditions and melt pond evolution at this time of year. To date the majority of studies have been limited to analysis of single-polarization C-band SAR data. This study will investigate the potential complimentary and unique sea ice information that polarimetric C- and X-band SAR data can provide to supplement the information available from traditional single co-polarized C-band SAR data. A time-series of polarimetric C- and X-band SAR data was acquired over Jones Sound in the Canadian Arctic Archipelago, in the vicinity of the Grise Fiord, Nunavut. Five RADARSAT-2 Wide Fine Quad-pol images and 11 TerraSAR-X StripMap dual-pol (HH/VV) images were acquired. The time-series begins at the onset of melt in early June and extends through advanced melt conditions in late July. Over this period several ponding and drainage events and two snowfall events occurred. Field observations of sea ice properties were collected using an Ice Mass Balance (IMB) buoy, hourly photos from a time-lapse camera deployed on a coastal cliff, and manual in situ measurements of snow thickness and melt pond depth </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C21G1188D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C21G1188D">Estimation of Melt Ponds over Arctic Sea Ice using MODIS Surface Reflectance Data</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Ding, Y.; Cheng, X.; Liu, J. 2017-12-01 Melt ponds over Arctic sea ice is one of the main factors affecting variability of surface albedo, increasing absorption of solar radiation and further melting of snow and ice. In recent years, a large number of melt ponds have been observed during the melt season in Arctic. Moreover, some studies have suggested that late spring to mid summer melt ponds information promises to improve the prediction skill of seasonal Arctic sea ice minimum. In the study, we extract the melt pond fraction over Arctic sea ice since 2000 using three bands MODIS weekly surface reflectance data by considering the difference of spectral reflectance in ponds, ice and open water. The preliminary comparison shows our derived Arctic-wide melt ponds are in good agreement with that derived by the University of Hamburg, especially at the pond distribution. We analyze seasonal evolution, interannual variability and trend of the melt ponds, as well as the changes of onset and re-freezing. The melt pond fraction shows an asymmetrical growth and decay pattern. The observed melt ponds fraction is almost within 25% in early May and increases rapidly in June and July with a high fraction of more than 40% in the east of Greenland and Beaufort Sea. A significant increasing trend in the melt pond fraction is observed for the period of 2000-2017. The relationship between melt pond fraction and sea ice extent will be also discussed. Key Words: melt ponds, sea ice, Arctic </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2005AGUFMED11D1122R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2005AGUFMED11D1122R">What About Sea Ice? People, animals, and climate change in the polar regions: An online resource for the International Polar Year and beyond</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Renfrow, S.; Meier, W. N.; Wolfe, J.; Scott, D.; Leon, A.; Weaver, R. 2005-12-01 Decreasing Arctic sea ice has been one of the most noticeable changes on Earth over the past quarter-century. The years 2002 through 2005 have had much lower summer sea ice extents than the long-term (1979-2000). Reduced sea ice extent has a direct impact on Arctic wildlife and people, as well as ramifications for regional and global climate. Students, educators, and the general public want and need to have a better understanding of sea ice. Most of us are unfamiliar with sea ice: what it is, where it occurs, and how it affects global climate. The upcoming International Polar Year will provide an opportunity for the public to learn about sea ice. Here, we provide an overview of sea ice, the changes that the sea ice is undergoing, and information about the relation between sea ice and climate. The information presented here is condensed from the National Snow and Ice Data Center's new 'All About Sea Ice' Web site (http://www.nsidc.org/seaice/), a comprehensive resource of information for sea ice. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-GSFC_20171208_Archive_e000643.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-GSFC_20171208_Archive_e000643.html">Sea ice in the Greenland Sea</a> <a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-GSFC_20171208_Archive_e001910.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-GSFC_20171208_Archive_e001910.html">Windblown Snow</a> <a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a> 2011-04-11 On April 11, 2011, IceBridge finally got the clear weather necessary to fly over glaciers in southeast Greenland, but with clear skies came winds of up to 70 knots. What looks like clouds is actually wind-blown snow. The data could help scientists to evaluate the impact of wind-blown snow on satellite-based laser altimetry measurements. Operation IceBridge, now in its third year, makes annual campaigns in the Arctic and Antarctic where science flights monitor glaciers, ice sheets and sea ice. Credit: NASA/GSFC/Michael Studinger To learn more about Ice Bridge go to: www.nasa.gov/mission_pages/icebridge/news/spr11/index.html 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 Join us on Facebook </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">16</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> <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">17</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> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007AGUFM.C11B0430C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007AGUFM.C11B0430C">Mining Existing Radar Altimetry for Sea Ice Freeboard and Thickness Estimates</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Childers, V. A.; Brozena, J. M. 2007-12-01 Although satellites can easily monitor ice extent and a variety of ice attributes, they cannot directly measure ice thickness. As a result, very few ice thickness measurements exist to constrain models of Arctic climate change. We estimated sea ice freeboard and thickness from X-band radar altimeter measurements collected over seven field seasons between 1992 and 1999 as part of a Naval Research Lab (NRL)-sponsored airborne geophysical survey of gravity and magnetics over the Arctic Ocean. These freeboard and thickness estimates were compared with the SCICEX ice draft record and the observed thinning of the Arctic Ocean ice cover during the 1990's. Our initial calculations (shown here) suggest that retrieved profiles from this radar altimeter (with uncertainty of about 5 cm) are sensitive to openings in the ice cover. Thus, conversion of these profiles to ice thickness adds an invaluable dataset for assessment of recent and future changes of Arctic climate. And, snow loading is a minor issue here as all the airborne surveys were conducted during mid- to late-summer when the ice cover is mostly bare. The strengths of this dataset are its small antenna footprint of ~50 m and density of spatial coverage allows for detailed characterization of the field of ice thickness, and it provides surveys of regions not covered by SCICEX cruises. The entire survey covers more than half the Arctic Ocean. We find that the Canadian Basin sea ice behavior differs from that in the Eurasian Basin and ultimately affects mean sea ice thickness for each basin. </li> <li> <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">Airborne Grid Sea-Ice Surveys for Comparison with CryoSat-2</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Brozena, J. M.; Gardner, J. M.; Liang, R.; Hagen, R. A.; Ball, D. 2014-12-01 The U.S. Naval Research Laboratory is engaged in a study of the changing Arctic with a particular focus on ice thickness and distribution variability. The purpose is to optimize computer models used to predict sea ice changes. An important part of our study is to calibrate/validate CryoSat-2 ice thickness data prior to its incorporation into new ice forecast models. The large footprint of the CryoSat-2 altimeter over sea-ice 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 sea-ice that would extend far enough cross-track to capture the illuminated area. One difficulty in the collection of grids comprised of adjacent overlapping tracks is that the ice 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 ice motion. This was accomplished by a photogrammetric method of ice 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 ice deformation over the period of the survey. An important factor is that we were able to reconstruct the ice 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 ice surface using the lidar grid which includes both snow and ice using radar profiles to determine snow thickness. In 2013 a set of 6 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C21A0650P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C21A0650P">Sea Ice Summer Camp: Bringing Together Arctic Sea Ice Modelers and Observers</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.4624G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.4624G">Bromine release from blowing snow and its impact on tropospheric chemistry</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Griffiths, Paul; Yang, Xin; Abraham, N. Luke; Archibald, Alexander; Pyle, John 2016-04-01 In the last two decades, significant depletion of boundary layer ozone (ozone depletion events, ODEs) has been observed in both Arctic and Antarctic spring. ODEs are attributed to catalytic destruction by bromine radicals (Br plus BrO), especially during bromine explosion events (BEs), when high concentrations of BrO periodically occur. The source of bromine and the mechanism that sustains the high BrO levels are still the subject of study. Recent work by Pratt et al. (2013) posits Br2 production within saline snow and sea ice which leads to sudden ODEs. Previously, Yang et al. (2008) suggested snow could provide a source of (depleted) sea-salt aerosol if wicked from the surface of ice. They suggest that rapid depletion of bromide from the aerosol will constitute a source of photochemical Bry. Given the large sea ice extent in polar regions, this may constitute a significant source of sea salt and bromine in the polar lower atmosphere. While bromine release from blowing snow is perhaps less likely to trigger sudden ODEs, it may make a contribution to regional scale processes affecting ozone levels. Currently, the model parameterisations of Yang et al. assumes that rapid release of bromine occurs from fresh snow on sea ice during periods of strong wind. The parameterisation depends on an assumed sea-salt aerosol distribution generated via sublimation of the snow above the boundary layer, as well as taking into account the salinity of the snow. In this work, we draw on recent measurements by scientists from the British Antarctic Survey during a cruise aboard the Polarstern in the southern oceans. This has provided an extensive set of measurements of the chemical and physical characteristics of blowing snow over sea ice, and of the aerosol associated with it. Based on the observations, we have developed an improved parameterisation of the release of bromine from blowing snow. The paper presents results from the simulation performed using the United Kingdom Chemistry </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..17.3005W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..17.3005W">Arctic moisture source for Eurasian snow cover variations in autumn</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Wegmann, Martin; Orsolini, Yvan; Vázquez Dominguez, Marta; Gimeno Presa, Luis; Nieto, Raquel; Buligyna, Olga; Jaiser, Ralf; Handorf, Dörthe; Rinke, Anette; Dethloff, Klaus; Sterin, Alexander; Brönnimann, Stefan 2015-04-01 Global warming is enhanced at high northern latitudes where the Arctic surface air temperature has risen at twice the rate of the global average in recent decades - a feature called Arctic amplification. This recent Arctic warming signal likely results from several factors such as the albedo feedback due to a diminishing cryosphere, enhanced poleward atmospheric and oceanic transport, and change in humidity. The reduction in Arctic sea ice is without doubt substantial and a key factor. Arctic summer sea-ice extent has declined by more than 10% per decade since the start of the satellite era (e.g. Stroeve et al., 2012), culminating in a new record low in September 2012, with the long-term trend largely attributed to anthropogenic global warming. Eurasian snow cover changes have been suggested as a driver for changes in the Arctic Oscillation and might provide a link between sea ice decline in the Arctic during summer and atmospheric circulation in the following winter. However, the mechanism connecting snow cover in Eurasia to sea ice decline in autumn is still under debate. Our analysis focuses at sea ice decline in the Barents-Kara Sea region, which allows us to specify regions of interest for FLEXPART forward and backwards moisture trajectories. Based on Eularian and Lagrangian diagnostics from ERA-INTERIM, we can address the origin and cause of late autumn snow depth variations in a dense (snow observations from 820 land stations), unutilized observational datasets over the Commonwealth of Independent States. Open waters in the Barents and Kara Sea have been shown to increase the diabatic heating of the atmosphere, which amplifies baroclinic cyclones and might induce a remote atmospheric response by triggering stationary Rossby waves (Honda et al. 2009). In agreement with these studies, our results show enhanced storm activity originating at the Barents and Kara with disturbances entering the continent through a small sector from the Barents and Kara Seas </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19890004490','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19890004490">NASA Sea Ice and Snow Validation Program for the DMSP SSM/I: NASA DC-8 flight report</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Cavalieri, D. J. 1988-01-01 In June 1987 a new microwave sensor called the Special Sensor Microwave Imager (SSM/I) was launched as part of the Defense Meteorological Satellite Program (DMSP). In recognition of the importance of this sensor to the polar research community, NASA developed a program to acquire the data, to convert the data into sea ice parameters, and finally to validate and archive both the SSM/I radiances and the derived sea ice parameters. Central to NASA's sea ice validation program was a series of SSM/I aircraft underflights with the NASA DC-8 airborne Laboratory. The mission (the Arctic '88 Sea Ice Mission) was completed in March 1988. This report summarizes the mission and includes a summary of aircraft instrumentation, coordination with participating Navy aircraft, flight objectives, flight plans, data collected, SSM/I orbits for each day during the mission, and lists several piggyback experiments supported during this mission. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014OcMod..84...51L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014OcMod..84...51L">Processes driving sea ice variability in the Bering Sea in an eddying ocean/sea ice model: Mean seasonal cycle</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C21G1186T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C21G1186T">There goes the sea ice: following Arctic sea ice parcels and their properties.</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFMGC12A..01S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFMGC12A..01S">Towards Improving Sea Ice Predictabiity: Evaluating Climate Models Against Satellite Sea Ice Observations</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C53B0782B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C53B0782B">Airborne Grid Sea-Ice Surveys for Comparison with Cryosat-2</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Brozena, J. M.; Gardner, J. M.; Liang, R.; Hagen, R. A.; Ball, D.; Newman, T. 2015-12-01 The Naval Research Laboratory is studying of the changing Arctic with a focus on ice thickness and distribution variability. The goal is optimization of computer models used to predict sea ice changes. An important part of our study is to calibrate/validate Cryosat-2 ice thickness data prior to its incorporation into new ice forecast models. The footprint of the altimeter over sea-ice 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 sea-ice that would extend far enough cross-track to capture the illuminated area. The difficulty in the collection of such grids, which are comprised of adjacent overlapping tracks is ice 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 ice motion is necessary for a coherent data set. This was accomplished by a an NRL devised photogrammetric method of ice velocity determination. Post-processing refinements resulted in typical track-to-track miss-ties of ~ 1-2 m, much of which could be attributed to ice deformation over the period of the survey. This allows us to reconstruct the ice 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 ice 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2004AGUFM.C31A0292F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2004AGUFM.C31A0292F">Climate Sensitivity to Realistic Solar Heating of Snow and Ice</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Flanner, M.; Zender, C. S. 2004-12-01 Snow and ice-covered surfaces are highly reflective and play an integral role in the planetary radiation budget. However, GCMs typically prescribe snow reflection and absorption based on minimal knowledge of snow physical characteristics. We performed climate sensitivity simulations with the NCAR CCSM including a new physically-based multi-layer snow radiative transfer model. The model predicts the effects of vertically resolved heating, absorbing aerosol, and snowpack transparency on snowpack evolution and climate. These processes significantly reduce the model's near-infrared albedo bias over deep snowpacks. While the current CCSM implementation prescribes all solar radiative absorption to occur in the top 2 cm of snow, we estimate that about 65% occurs beneath this level. Accounting for the vertical distribution of snowpack heating and more realistic reflectance significantly alters snowpack depth, surface albedo, and surface air temperature over Northern Hemisphere regions. Implications for the strength of the ice-albedo feedback will be discussed. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140006009','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140006009">A Supplementary Clear-Sky Snow and Ice Recognition Technique for CERES Level 2 Products</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Radkevich, Alexander; Khlopenkov, Konstantin; Rutan, David; Kato, Seiji 2013-01-01 Identification of clear-sky snow and ice is an important step in the production of cryosphere radiation budget products, which are used in the derivation of long-term data series for climate research. In this paper, a new method of clear-sky snow/ice identification for Moderate Resolution Imaging Spectroradiometer (MODIS) is presented. The algorithm's goal is to enhance the identification of snow and ice within the Clouds and the Earth's Radiant Energy System (CERES) data after application of the standard CERES scene identification scheme. The input of the algorithm uses spectral radiances from five MODIS bands and surface skin temperature available in the CERES Single Scanner Footprint (SSF) product. The algorithm produces a cryosphere rating from an aggregated test: a higher rating corresponds to a more certain identification of the clear-sky snow/ice-covered scene. Empirical analysis of regions of interest representing distinctive targets such as snow, ice, ice and water clouds, open waters, and snow-free land selected from a number of MODIS images shows that the cryosphere rating of snow/ice targets falls into 95% confidence intervals lying above the same confidence intervals of all other targets. This enables recognition of clear-sky cryosphere by using a single threshold applied to the rating, which makes this technique different from traditional branching techniques based on multiple thresholds. Limited tests show that the established threshold clearly separates the cryosphere rating values computed for the cryosphere from those computed for noncryosphere scenes, whereas individual tests applied consequently cannot reliably identify the cryosphere for complex scenes. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C31D..06T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C31D..06T">Submesoscale sea ice-ocean interactions in marginal ice zones</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C33B0786L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C33B0786L">Spaceborne Radar Observations of High Mountain Asia Snow and Ice</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Lund, J. 2016-12-01 The glaciers of High Mountain Asia show a negative trend in mass balance. Within its sub regions, however, a complex pattern of climate regions and glacial forcings arise. This complexity, coupled with the challenges of field study in the region, illicit notable uncertainties both in observation and prediction of glacial mass balance. Beyond being valuable indicators of climate variability, the glaciers of High Mountain Asia are important water resources for densely populated downstream regions, and also contribute to global sea level rise. Scatterometry, regularly used in polar regions to detect melt in snow and ice, has seen little use in lower latitude glaciers. In High Mountain Asia, focus has been placed on spatial and temporal trends in scatterometer signals for melt onset and freeze-up. In polar regions, scatterometry and synthetic aperture radar (SAR) data have been used to estimate snow accumulation, along with interferometric SAR (InSAR) to measure glacier velocity, better constraining glacial mass balance estimates. For this poster, multiple radar sensors will be compared with both in situ as well as reanalysis precipitation data in varying climate regions in High Mountain Asia to explore correlations between snow accumulation and radar signals. Snowmelt timing influences on InSAR coherence may also be explored. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19990080911&hterms=water+meter&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dwater%2Bmeter','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19990080911&hterms=water+meter&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dwater%2Bmeter">Optical Thickness and Effective Radius Retrievals of Liquid Water Clouds over Ice and Snow Surface</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Platnick, S.; King, M. D.; Tsay, S.-C.; Arnold, G. T.; Gerber, H.; Hobbs, P. V.; Rangno, A. 1999-01-01 Cloud optical thickness and effective radius retrievals from solar reflectance measurements traditionally depend on a combination of spectral channels that are absorbing and non-absorbing for liquid water droplets. Reflectances in non-absorbing channels (e.g., 0.67, 0.86 micrometer bands) are largely dependent on cloud optical thickness, while longer wavelength absorbing channels (1.6, 2.1, and 3.7 micrometer window bands) provide cloud particle size information. Retrievals are complicated by the presence of an underlying ice/snow surface. At the shorter wavelengths, sea ice is both bright and highly variable, significantly increasing cloud retrieval uncertainty. However, reflectances at the longer wavelengths are relatively small and may be comparable to that of dark open water. Sea ice spectral albedos derived from Cloud Absorption Radiometer (CAR) measurements during April 1992 and June 1995 Arctic field deployments are used to illustrate these statements. A modification to the traditional retrieval technique is devised. The new algorithm uses a combination of absorbing spectral channels for which the snow/ice albedo is relatively small. Using this approach, preliminary retrievals have been made with the MODIS Airborne Simulator (MAS) imager flown aboard the NASA ER-2 during FIRE-ACE. Data from coordinated ER-2 and University of Washington CV-580 aircraft observations of liquid water stratus clouds on June 3 and June 6, 1998 have been examined. Size retrievals are compared with in situ cloud profile measurements of effective radius made with the CV-580 PMS FSSP probe, and optical thickness retrievals are compared with extinction profiles derived from the Gerber Scientific "g-meter" probe. MAS retrievals are shown to be in good agreement with the in situ measurements. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JGRC..122.9455M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JGRC..122.9455M">Submesoscale Sea Ice-Ocean Interactions in Marginal Ice Zones</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012EGUGA..14.6756D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012EGUGA..14.6756D">Albedo of bare ice near the Trans-Antarctic Mountains as an analogue of sea-glaciers on the tropical ocean of Snowball Earth</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Dadic, R.; Mullen, P.; Schneebeli, M.; Brandt, R. E.; Fitzpatric, M.; Carns, R.; Warren, S. G. 2012-04-01 The albedos of snow and ice surfaces are, because of their positive feedback, crucial to the initiation, continuation, and termination of a snowball event, as well as for determining the ice thickness on the ocean. Despite the name, Snowball Earth would not have been entirely snow-covered. As on modern Earth, evaporation would exceed precipitation over much of the tropical ocean. After a transient period with sea ice, the dominant ice type would probably be sea-glaciers flowing in from higher latitude. As they flowed equatorward into the tropical region of net sublimation, their surface snow and subsurface firn would sublimate away, exposing bare glacier ice to the atmosphere and to solar radiation. This ice would be freshwater (meteoric) ice, which originated from snow and firn, so it would contain numerous air bubbles, which determine the albedo. The modern surrogate for this type of ice (glacier ice exposed by pure sublimation, which has never experienced melting), are the bare-ice surfaces of the East Antarctic Ice Sheet near the Trans-Antarctic Mountains. These areas have been well mapped because of their importance in the search for meteorites. A transect across an icefield can potentially sample ice of different ages that has traveled to different depths en route to the sublimation front. We examined a 6-km transect from snow to ice near the Allan Hills (77 S, 158 E, 2000 m ASL), measuring spectral albedo and collecting 1-m core samples. This short transect is a surrogate of a north-south transect across many degrees of latitude on the Snowball ocean. Surfaces on the transect transitioned through the sequence: new snow - old snow - firn - young white ice - old blue ice. The transect from snow to ice showed a systematic progression of decreasing albedo at all wavelengths, as well as decreasing specific surface area (SSA; ratio of air-ice interface area to ice mass) and increasing density. The measured spectral albedos are integrated over wavelength and </li> <li> <a target="_blank" onclick="trackOutboundLink('https://rosap.ntl.bts.gov/view/dot/27184','DOTNTL'); return false;" href="https://rosap.ntl.bts.gov/view/dot/27184">Evaluation of the effectiveness of salt neutralizers for washing snow and ice equipment.</a> <a target="_blank" href="http://ntlsearch.bts.gov/tris/index.do">DOT National Transportation Integrated Search</a> 2014-01-01 In winter maintenance, the chloride-based deicers used to keep roadways clear of : snow and ice are highly corrosive to vehicles and equipment. Corrosion of snow and ice equipment : is a major issue causing increased maintenance and repair costs, red... </li> <li> <a target="_blank" onclick="trackOutboundLink('https://rosap.ntl.bts.gov/view/dot/3912','DOTNTL'); return false;" href="https://rosap.ntl.bts.gov/view/dot/3912">Southeast Michigan Snow and Ice Management (SEMSIM)</a> <a target="_blank" href="http://ntlsearch.bts.gov/tris/index.do">DOT National Transportation Integrated Search</a> 2001-07-01 The Southeast Michigan Snow and Ice Management (SEMSIM) partnership includes the Detroit Department of Public Works, the Road Commission of Macomb County, the Road Commission for Oakland County, and the Wayne County Department of Public Services. The... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140005670','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140005670">Sea Ice</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </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">17</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> <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">18</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> <a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70191516','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70191516">The effects of snow and salt on ice table stability in University Valley, Antarctica</a> <a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Williams, Kaj; Heldmann, Jennifer L.; McKay, Christopher P.; Mellon, Michael T. 2018-01-01 The Antarctic Dry Valleys represent a unique environment where it is possible to study dry permafrost overlaying an ice-rich permafrost. In this paper, two opposing mechanisms for ice table stability in University Valley are addressed: i) diffusive recharge via thin seasonal snow deposits and ii) desiccation via salt deposits in the upper soil column. A high-resolution time-marching soil and snow model was constructed and applied to University Valley, driven by meteorological station atmospheric measurements. It was found that periodic thin surficial snow deposits (observed in University Valley) are capable of drastically slowing (if not completely eliminating) the underlying ice table ablation. The effects of NaCl, CaCl2 and perchlorate deposits were then modelled. Unlike the snow cover, however, the presence of salt in the soil surface (but no periodic snow) results in a slight increase in the ice table recession rate, due to the hygroscopic effects of salt sequestering vapour from the ice table below. Near-surface pore ice frequently forms when large amounts of salt are present in the soil due to the suppression of the saturation vapour pressure. Implications for Mars high latitudes are discussed. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19810038158&hterms=Parkinsons+circulation&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DParkinsons%2Bcirculation','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19810038158&hterms=Parkinsons+circulation&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DParkinsons%2Bcirculation">Sea ice simulations based on fields generated by the GLAS GCM. [Goddard Laboratory for Atmospheric Sciences General Circulation Model</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Parkinson, C. L.; Herman, G. F. 1980-01-01 The GLAS General Circulation Model (GCM) was applied to the four-month simulation of the thermodynamic part of the Parkinson-Washington sea ice model using atmospheric boundary conditions. The sea ice thickness and distribution were predicted for the Jan. 1-Apr. 30 period using the GCM-fields of solar and infrared radiation, specific humidity and air temperature at the surface, and snow accumulation; the sensible heat and evaporative surface fluxes were consistent with the ground temperatures produced by the ice model and the air temperatures determined by the atmospheric concept. It was concluded that the Parkinson-Washington sea ice model results in acceptable ice concentrations and thicknesses when used with GLAS GCM for the Jan.-Apr. period suggesting the feasibility of fully coupled ice-atmosphere simulations with these two approaches. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014TCD.....8.5227I','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014TCD.....8.5227I">The melt pond fraction and spectral sea ice albedo retrieval from MERIS data: validation and trends of sea ice albedo and melt pond fraction in the Arctic for years 2002-2011</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Istomina, L.; Heygster, G.; Huntemann, M.; Schwarz, P.; Birnbaum, G.; Scharien, R.; Polashenski, C.; Perovich, D.; Zege, E.; Malinka, A.; Prikhach, A.; Katsev, I. 2014-10-01 The presence of melt ponds on the Arctic sea ice strongly affects the energy balance of the Arctic Ocean in summer. It affects albedo as well as transmittance through the sea ice, which has consequences on the heat balance and mass balance of sea ice. An algorithm to retrieve melt pond fraction and sea ice albedo (Zege et al., 2014) from the MEdium Resolution Imaging Spectrometer (MERIS) data is validated against aerial, ship borne and in situ campaign data. The result show the best correlation for landfast and multiyear ice of high ice concentrations (albedo: R = 0.92, RMS = 0.068, melt pond fraction: R = 0.6, RMS = 0.065). The correlation for lower ice concentrations, subpixel ice floes, blue ice and wet ice is lower due to complicated surface conditions and ice drift. Combining all aerial observations gives a mean albedo RMS equal to 0.089 and a mean melt pond fraction RMS equal to 0.22. The in situ melt pond fraction correlation is R = 0.72 with an RMS = 0.14. Ship cruise data might be affected by documentation of varying accuracy within the ASPeCT protocol, which is the reason for discrepancy between the satellite value and observed value: mean R = 0.21, mean RMS = 0.16. An additional dynamic spatial cloud filter for MERIS over snow and ice has been developed to assist with the validation on swath data. The case studies and trend analysis for the whole MERIS period (2002-2011) show pronounced and reasonable spatial features of melt pond fractions and sea ice albedo. The most prominent feature is the melt onset shifting towards spring (starting already in weeks 3 and 4 of June) within the multiyear ice area, north to the Queen Elizabeth Islands and North Greenland. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1914888H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1914888H">Stress and deformation characteristics of sea ice in a high resolution numerical sea ice model.</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA617900','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA617900">Early Student Support to Investigate the Role of Sea Ice-Albedo Feedback in Sea Ice Predictions</a> <a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012CliPa...8.2079V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012CliPa...8.2079V">Sea-ice dynamics strongly promote Snowball Earth initiation and destabilize tropical sea-ice margins</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C44B..08S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C44B..08S">How will we ensure the long-term sea ice data record continues?</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Stroeve, J. C.; Kaleschke, L. 2017-12-01 The multi-channel satellite passive microwave record has been of enormous benefit to the science community and society at large since the late 1970s. Starting with the launch of the Nimbus-7 Scanning Multi-Channel Microwave Radiometer (SMMR) in October 1978, and continuing with the launch of a series of Special Sensor Microwave Imagers (SSM/Is) in June 1987 by the Defense Meteorological Satellite Program (DMSP), places previously difficult to monitor year-round, such as the polar regions, came to light. Together these sensors have provided nearly 4 decades of climate data records on the state of sea ice cover over the ocean and snow on land. This data has also been used to map melt extent on the large ice sheets, timing of snow melt onset over land and sea ice. Application also extend well beyond the polar regions, mapping important climate variables, such as soil moisture content, oceanic wind speed, rainfall, water vapor, cloud liquid water and total precipitable water. Today the current SSMIS operational satellite (F18) is 7 years old and there is no follow-on mission planned by the DMSP. With the end of the SSMI family of Sensors, will the polar regions once again be in the dark? Other sensors that may contribute to the long-term data record include the JAXA AMSR2 (5 years old as of May 2017), the Chinese Fen-Yung-3 and the Russian Meteor-N2. Scatterometry and L-band radiometry from SMOS and NASA's SMOS may also provide some potential means of extending the sea ice extent data record, as well as future sensors by the DoD, JAXA and ESA. However, this will require considerable effort to intercalibrate the different sensors to ensure consistency in the long-term data record. Differences in measurement approach, frequency and spatial resolution make this a non-trivial matter. The passive microwave sea ice extent data record is one of the longest and most consistent climate data records available. It provides daily monitoring of one of the most striking changes in </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AtmEn.140..415H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AtmEn.140..415H">Effects of different temperature treatments on biological ice nuclei in snow samples</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Hara, Kazutaka; Maki, Teruya; Kakikawa, Makiko; Kobayashi, Fumihisa; Matsuki, Atsushi 2016-09-01 The heat tolerance of biological ice nucleation activity (INA) depends on their types. Different temperature treatments may cause varying degrees of inactivation on biological ice nuclei (IN) in precipitation samples. In this study, we measured IN concentration and bacterial INA in snow samples using a drop freezing assay, and compared the results for unheated snow and snow treated at 40 °C and 90 °C. At a measured temperature of -7 °C, the concentration of IN in untreated snow was 100-570 L-1, whereas the concentration in snow treated at 40 °C and 90 °C was 31-270 L-1 and 2.5-14 L-1, respectively. In the present study, heat sensitive IN inactivated by heating at 40 °C were predominant, and ranged 23-78% of IN at -7 °C compared with untreated samples. Ice nucleation active Pseudomonas strains were also isolated from the snow samples, and heating at 40 °C and 90 °C inactivated these microorganisms. Consequently, different temperature treatments induced varying degrees of inactivation on IN in snow samples. Differences in the concentration of IN across a range of treatment temperatures might reflect the abundance of different heat sensitive biological IN components. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ACP....18.8155M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ACP....18.8155M">Long-range-transported bioaerosols captured in snow cover on Mount Tateyama, Japan: impacts of Asian-dust events on airborne bacterial dynamics relating to ice-nucleation activities</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Maki, Teruya; Furumoto, Shogo; Asahi, Yuya; Lee, Kevin C.; Watanabe, Koichi; Aoki, Kazuma; Murakami, Masataka; Tajiri, Takuya; Hasegawa, Hiroshi; Mashio, Asami; Iwasaka, Yasunobu 2018-06-01 The westerly wind travelling at high altitudes over eastern Asia transports aerosols from the Asian deserts and urban areas to downwind areas such as Japan. These long-range-transported aerosols include not only mineral particles but also microbial particles (bioaerosols), that impact the ice-cloud formation processes as ice nuclei. However, the detailed relations of airborne bacterial dynamics to ice nucleation in high-elevation aerosols have not been investigated. Here, we used the aerosol particles captured in the snow cover at altitudes of 2450 m on Mt Tateyama to investigate sequential changes in the ice-nucleation activities and bacterial communities in aerosols and elucidate the relationships between the two processes. After stratification of the snow layers formed on the walls of a snow pit on Mt Tateyama, snow samples, including aerosol particles, were collected from 70 layers at the lower (winter accumulation) and upper (spring accumulation) parts of the snow wall. The aerosols recorded in the lower parts mainly came from Siberia (Russia), northern Asia and the Sea of Japan, whereas those in the upper parts showed an increase in Asian dust particles originating from the desert regions and industrial coasts of Asia. The snow samples exhibited high levels of ice nucleation corresponding to the increase in Asian dust particles. Amplicon sequencing analysis using 16S rRNA genes revealed that the bacterial communities in the snow samples predominately included plant associated and marine bacteria (phyla Proteobacteria) during winter, whereas during spring, when dust events arrived frequently, the majority were terrestrial bacteria of phyla Actinobacteria and Firmicutes. The relative abundances of Firmicutes (Bacilli) showed a significant positive relationship with the ice nucleation in snow samples. Presumably, Asian dust events change the airborne bacterial communities over Mt Tateyama and carry terrestrial bacterial populations, which possibly induce ice </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19930016861','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19930016861">Radar backscatter measurements from Arctic sea ice during the fall freeze-up</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Beaven, S.; Gogineni, S. P.; Shanableh, M.; Gow, A.; Tucker, W.; Jezek, K. 1993-01-01 Radar backscatter measurements from sea ice during the fall freeze-up were performed by the United States Coast Guard Icebreaker Polar Star as a part of the International Arctic Ocean Expedition (IAOE'91) from Aug. to Sep. 1991. The U.S. portion of the experiment took place on board the Polar Star and was referred to as TRAPOLEX '91 (Transpolar expedition) by some investigators. Before prematurely aborting its mission because of mechanical failure of her port shaft, the Polar Star reached 84 deg 57 min N latitude at 35 deg E longitude. The ship was in the ice (greater than 50 percent coverage) from 14 Aug. until 3 Sep. and was operational for all but 6 days due to two instances of mechanical problems with the port shaft. The second was fatal to the ship's participation in the expedition. During the expedition, radar backscatter was measured at C-band under a variety of conditions. These included measurements from young ice types as well as from multiyear and first-/second-year sea ice during the fall freeze-up. The sea ice types were determined by measurement of the ice properties at several of the stations and by visual inspection on others. Radar backscatter measurements were performed over a large portion of the ship's transit into the Arctic ice pack. These were accompanied by in situ sea ice property characterization by the U.S. Army Cold Regions Research and Engineering Laboratory (CRREL) at several stations and, when snow was present, its properties were documented by The Microwave Group, Ottawa River (MWG). </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C33B1190R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C33B1190R">Atmospheric Influences on the Anomalous 2016 Antarctic Sea Ice Decay</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Raphael, M. N.; Schlosser, E.; Haumann, A. 2017-12-01 Over the past three decades, a small but significant increase in sea ice extent (SIE) has been observed in the Antarctic. However, in 2016 there was a surprisingly early onset of the melt season. The maximum Antarctic SIE was reached in August rather than end of September, and was followed by a rapid decrease. The decline of the sea ice area (SIA) started even earlier, in July. The retreat of the ice was particularly large in November where Antarctic SIE exhibited a negative anomaly (compared to the 1981-2010 average) of almost 2 Mio. km2, which, combined with reduced Arctic SIE, led to a distinct minimum in global SIE. And, satellite observations show that from November 2016 to February 2017, the daily Antarctic SIE has been at record low levels. We use sea level pressure and geopotential height data from the ECMWF- Interim reanalysis, in conjunction with sea ice data obtained from the National Snow and Ice Data Centre (NSIDC), to investigate possible atmospheric influences on the observed phenomena. Indications are that both the onset of the melt in July and the rapid decrease in SIA and SIE in November were triggered by atmospheric flow patterns related to a positive Zonal Wave 3 index, i.e. synoptic situations leading to strong meridional flow. Additionally the Southern Annular Mode (SAM) index reached its second lowest November value since the beginning of the satellite observations. It is likely that the SIE decrease was preconditioned by SIA decrease. Positive feedback effects led to accelerated melt and consequently to the extraordinary low November SIE. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://rosap.ntl.bts.gov/view/dot/21787','DOTNTL'); return false;" href="https://rosap.ntl.bts.gov/view/dot/21787">Snow and ice control at extreme temperatures.</a> <a target="_blank" href="http://ntlsearch.bts.gov/tris/index.do">DOT National Transportation Integrated Search</a> 2011-04-25 As expected, most state and provincial DOTs that we spoke with are using traditional methods to prevent and : remove snow and ice at very low temperatures. In addition to a review of current research, we spoke with six winter : maintenance profession... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19740014838','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19740014838">The application of ERTS imagery to monitoring Arctic sea ice. [mapping ice in Bering Sea, Beaufort Sea, Canadian Archipelago, and Greenland Sea</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JGRD..122.8427W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JGRD..122.8427W">Atmospheric components of the surface energy budget over young sea ice: Results from the N-ICE2015 campaign</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Walden, Von P.; Hudson, Stephen R.; Cohen, Lana; Murphy, Sarah Y.; Granskog, Mats A. 2017-08-01 The Norwegian young sea ice campaign obtained the first measurements of the surface energy budget over young, thin Arctic sea ice through the seasonal transition from winter to summer. This campaign was the first of its kind in the North Atlantic sector of the Arctic. This study describes the atmospheric and surface conditions and the radiative and turbulent heat fluxes over young, thin sea ice. The shortwave albedo of the snow surface ranged from about 0.85 in winter to 0.72-0.80 in early summer. The near-surface atmosphere was typically stable in winter, unstable in spring, and near neutral in summer once the surface skin temperature reached 0°C. The daily average radiative and turbulent heat fluxes typically sum to negative values (-40 to 0 W m-2) in winter but then transition toward positive values of up to nearly +60 W m-2 as solar radiation contributes significantly to the surface energy budget. The sensible heat flux typically ranges from +20-30 W m-2 in winter (into the surface) to negative values between 0 and -20 W m-2 in spring and summer. A winter case study highlights the significant effect of synoptic storms and demonstrates the complex interplay of wind, clouds, and heat and moisture advection on the surface energy components over sea ice in winter. A spring case study contrasts a rare period of 24 h of clear-sky conditions with typical overcast conditions and highlights the impact of clouds on the surface radiation and energy budgets over young, thin sea ice. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20010027899','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20010027899">Studies of Antarctic Sea Ice Concentrations from Satellite Data and Their Applications</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Comiso, Josefino C.; Steffen, Konrad; Zukor, Dorothy J. (Technical Monitor) 2001-01-01 Large changes in the sea ice cover have been observed recently. Because of the relevance of such changes to climate change studies it is important that key ice concentration data sets used for evaluating such changes are interpreted properly. High and medium resolution visible and infrared satellite data are used in conjunction with passive microwave data to study the true characteristics of the Antarctic sea ice cover, assess errors in currently available ice concentration products, and evaluate the applications and limitations of the latter in polar process studies. Cloud-free high resolution data provide valuable information about the natural distribution, stage of formation, and composition of the ice cover that enables interpretation of the large spatial and temporal variability of the microwave emissivity of Antarctic sea ice. Comparative analyses of co-registered visible, infrared and microwave data were used to evaluate ice concentrations derived from standard ice algorithms (i.e., Bootstrap and Team) and investigate the 10 to 35% difference in derived values from large areas within the ice pack, especially in the Weddell Sea, Amundsen Sea, and Ross Sea regions. Landsat and OLS data show a predominance of thick consolidated ice in these areas and show good agreement with the Bootstrap Algorithm. While direct measurements were not possible, the lower values from the Team Algorithm results are likely due to layering within the ice and snow and/or surface flooding, which are known to affect the polarization ratio. In predominantly new ice regions, the derived ice concentration from passive microwave data is usually lower than the true percentage because the emissivity of new ice changes with age and thickness and is lower than that of thick ice. However, the product provides a more realistic characterization of the sea ice cover, and are more useful in polar process studies since it allows for the identification of areas of significant divergence and polynya </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFMED41C0686C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFMED41C0686C">Understanding the Sea Ice Zone: Scientists and Communities Partnering to Archive, Analyze and Disseminate Local Ice Observations</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Collins, J. A.; Oldenburg, J.; Liu, M.; Pulsifer, P. L.; Kaufman, M.; Eicken, H.; Parsons, M. A. 2012-12-01 Knowledge of sea ice is critical to the hunting, whaling, and cultural activities of many Indigenous communities in Northern and Western Alaska. Experienced hunters have monitored seasonal changes of the sea ice over many years, giving them a unique expertise in assessing the current state of the sea ice as well as any anomalies in seasonal sea ice conditions. The Seasonal Ice Zone Observing Network (SIZONet), in collaboration with the Exchange for Local Observations and Knowledge of the Arctic (ELOKA), has developed an online application for collecting, storing, and analyzing sea ice observations contributed by local experts from coastal Alaskan communities. Here we present the current iteration of the application, outline future plans and discuss how the development process and resulting system have improved our collective understanding of sea ice processes and changes. The SIZONet application design is based on the needs of the research scientists responsible for entering observation data into the database, the needs of local sea ice experts contributing their observations and knowledge, and the information needs of Alaska coastal communities. Entry forms provide a variety of input methods, including menus, check boxes, and free text input. Input options strive to balance flexibility in capturing concepts and details with the need for analytical consistency. Currently, research staff at the University of Alaska Fairbanks use the application to enter observations received via written or electronic communications from local sea ice experts. Observation data include current weather conditions, snow and ice quantity and quality, and wildlife sighted or taken. Future plans call for direct use of the SIZONet interface by local sea ice experts as well as students, both as contributors to the data collection and as users seeking meaning in the data. This functionality is currently available to a limited number of community members as we extend the application to support </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013QSRv...79..168A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013QSRv...79..168A">A review of sea ice proxy information from polar ice cores</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1810332R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1810332R">Trends in annual minimum exposed snow and ice cover in High Mountain Asia from MODIS</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Rittger, Karl; Brodzik, Mary J.; Painter, Thomas H.; Racoviteanu, Adina; Armstrong, Richard; Dozier, Jeff 2016-04-01 Though a relatively short record on climatological scales, data from the Moderate Resolution Imaging Spectroradiometer (MODIS) from 2000-2014 can be used to evaluate changes in the cryosphere and provide a robust baseline for future observations from space. We use the MODIS Snow Covered Area and Grain size (MODSCAG) algorithm, based on spectral mixture analysis, to estimate daily fractional snow and ice cover and the MODICE Persistent Ice (MODICE) algorithm to estimate the annual minimum snow and ice fraction (fSCA) for each year from 2000 to 2014 in High Mountain Asia. We have found that MODSCAG performs better than other algorithms, such as the Normalized Difference Index (NDSI), at detecting snow. We use MODICE because it minimizes false positives (compared to maximum extents), for example, when bright soils or clouds are incorrectly classified as snow, a common problem with optical satellite snow mapping. We analyze changes in area using the annual MODICE maps of minimum snow and ice cover for over 15,000 individual glaciers as defined by the Randolph Glacier Inventory (RGI) Version 5, focusing on the Amu Darya, Syr Darya, Upper Indus, Ganges, and Brahmaputra River basins. For each glacier with an area of at least 1 km2 as defined by RGI, we sum the total minimum snow and ice covered area for each year from 2000 to 2014 and estimate the trends in area loss or gain. We find the largest loss in annual minimum snow and ice extent for 2000-2014 in the Brahmaputra and Ganges with 57% and 40%, respectively, of analyzed glaciers with significant losses (p-value<0.05). In the Upper Indus River basin, we see both gains and losses in minimum snow and ice extent, but more glaciers with losses than gains. Our analysis shows that a smaller proportion of glaciers in the Amu Darya and Syr Darya are experiencing significant changes in minimum snow and ice extent (3.5% and 12.2%), possibly because more of the glaciers in this region are smaller than 1 km2 than in the Indus </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.C23E0542F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.C23E0542F">Validation and Interpretation of a New Sea Ice Globice Dataset Using Buoys and the Cice Sea Ice Model</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009EGUGA..1113752H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009EGUGA..1113752H">L-band radiometry for sea ice applications</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Heygster, G.; Hedricks, S.; Mills, P.; Kaleschke, L.; Stammer, D.; Tonboe, R. 2009-04-01 Although sea ice 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 ice and water surfaces, estimates of ice concentration with passive and active microwave sensors remain challenging. Newly formed thin ice 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 sea ice data product based on SMOS. In detail, the project objectives are (1) to model the L band emission of sea ice, and to assess the potential (2) to retrieve sea ice 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 ice 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 ice 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 sea ice, three-layer (air, ice and water) dielectric slab models which take as input a single effective permittivity for the ice layer are appropriate. By ignoring scattering effects one can derive a simple analytic expression for a dielectric slab as shown by Apinis and </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">18</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> <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">19</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> <a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70037527','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70037527">Quaternary Sea-ice history in the Arctic Ocean based on a new Ostracode sea-ice proxy</a> <a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> 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. </li> <li> <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">Springtime atmospheric transport controls Arctic summer sea-ice extent</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Kapsch, Marie; Graversen, Rune; Tjernström, Michael 2013-04-01 anomaly becomes positive. The net shortwave radiation contributes during the rest of the melting season to an enhanced energy flux towards the surface. These findings lead to the conclusion that enhanced longwave radiation associated with positive humidity and cloud anomalies during spring plays a significant role in initiating the summer ice melt, whereas shortwave-radiation anomalies act as an amplifying feedback once the melt has started. References: Lindsay, R. and J. Zhang. The thinning of Arctic Sea Ice, 19882003: Have We Passed a Tipping Point?. J. Clim. 18, 48794894 (2005). Overland, J. E., M. Wang and S. Salo. The recent Arctic warm period. Tellus 60A, 589-597 (2008). Comiso, J. C., C. L. Parkinson, R. Gersten and L. Stock. Accelerated Decline in the Arctic sea ice cover. Geophys. Res. Lett. 35, L01703 (2008). Francis, J. A. and E. Hunter. New Insight Into the Disappearing Arctic Sea Ice. EOS T. Am. Geophys. Un. 87, 509511 (2006). Maksimovich, E. and T. Vihma. The effect of heat fluxes on interannual variability in the spring onset of snow melt in the central Arctic Ocean. J. Geophys. Res. 117, C07012 (2012). Serreze, M. C., M. M. Holland and J. Stroeve. Perspectives on the Arctic's Shrinking Sea-Ice Cover. Science 315, 1533-1536 (2007). </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20070035107&hterms=remote+sensing+satellites&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dremote%2Bsensing%2Bsatellites','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20070035107&hterms=remote+sensing+satellites&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dremote%2Bsensing%2Bsatellites">ARISE (Antarctic Remote Ice Sensing Experiment) in the East 2003: Validation of Satellite-derived Sea-ice Data Product</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Massom, Robert A.; Worby, Anthony; Lytle, Victoria; Markus, Thorsten; Allison, Ian; Scambos, Theodore; Enomoto, Hiroyuki; Tateyama, Kazutaka; Haran, Terence; Comiso, Josefino C.; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_20070035107'); toggleEditAbsImage('author_20070035107_show'); toggleEditAbsImage('author_20070035107_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_20070035107_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_20070035107_hide"> 2006-01-01 Preliminary results are presented from the first validation of geophysical data products (ice concentration, snow thickness on sea ice (h(sub s) and ice temperature (T(sub i))fr om the NASA EOS Aqua AMSR-E sensor, in East Antarctica (in September-October 2003). The challenge of collecting sufficient measurements with which to validate the coarse-resolution AMSR-E data products adequately was addressed by means of a hierarchical approach, using detailed in situ measurements, digital aerial photography and other satellite data. Initial results from a circumnavigation of the experimental site indicate that, at least under cold conditions with a dry snow cover, there is a reasonably close agreement between satellite- and aerial-photo-derived ice concentrations, i.e. 97.2+/-.6% for NT2 and 96.5+/-2.5% for BBA algorithms vs 94.3% for the aerial photos. In general, the AMSR-E concentration represents a slight overestimate of the actual concentration, with the largest discrepancies occurring in regions containing a relatively high proportion of thin ice. The AMSR-E concentrations from the NT2 and BBA algorithms are similar on average, although differences of up to 5% occur in places, again related to thin-ice distribution. The AMSR-E ice temperature (T(sub i)) product agrees with coincident surface measurements to approximately 0.5 C in the limited dataset analyzed. Regarding snow thickness, the AMSR h(sub s) retrieval is a significant underestimate compared to in situ measurements weighted by the percentage of thin ice (and open water) present. For the case study analyzed, the underestimate was 46% for the overall average, but 23% compared to smooth-ice measurements. The spatial distribution of the AMSR-E h(sub s) product follows an expected and consistent spatial pattern, suggesting that the observed difference may be an offset (at least under freezing conditions). Areas of discrepancy are identified, and the need for future work using the more extensive dataset is </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFM.C41A0504B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFM.C41A0504B">Managing IceBridge Airborne Mission Data at the National Snow and Ice Data Center</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Brodzik, M.; Kaminski, M. L.; Deems, J. S.; Scambos, T. A. 2010-12-01 a map-based interface. This portal will provide flight line rendering and multi-instrument data previewing capabilities to facilitate use of the wide array of data types, resolutions, and configurations in this dynamic airborne mission. Together with the IceBridge Science Team and Ice Bridge Science Working Groups, NSIDC is generating value-added products from the Ice Bridge data streams and other ancillary data. These products will provide simple, useful combinations of Ice Bridge products and regional maps of important geophysical parameters from other sources. Planned value-added products include: (1) gridded products in which new profiles from Ice Bridge (e.g. elevation or ice thickness) are combined with existing DEMs or bed maps to produce revised grids and (2) flight-profile multi-instrument products in which data from several instruments are combined into ice sheet profiles (surface elevation, ice thickness, internal reflection data, bed reflection intensity, and gravimetry), sea ice profiles (freeboard, snow cover, and thickness), and surface data profiles (elevation, slope, roughness, near-surface layering, and imagery). </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19890016983','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19890016983">Snow as a habitat for microorganisms</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Hoham, Ronald W. 1989-01-01 There are three major habitats involving ice and snow, and the microorganisms studied from these habitats are most eukaryotic. Sea ice is inhabited by algae called diatoms, glacial ice has sparse populations of green algai cal desmids, and the temporary and permanent snows in mountainous regions and high latitudes are inhabited mostly by green algal flagellates. The life cycle of green algal flagellates is summarized by discussing the effects of light, temperature, nutrients, and snow melts. Specific examples of optimal conditions and environmental effects for various snow algae are given. It is not likely that the eukaryotic snow algae presented are candidated for life on the planet Mars. Evolutionally, eukaryotic cells as know on Earth may not have had the opportunity to develop on Mars (if life evolved at all on Mars) since eukaryotes did not appear on Earth until almost two billion years after the first prokaryotic organisms. However, the snow/ice ecosystems on Earth present themselves as extreme habitats were there is evidence of prokaryotic life (eubacteria and cyanbacteria) of which literally nothing is known. Any future surveillances of extant and/or extinct life on Mars should include probes (if not landing sites) to investigate sites of concentrations of ice water. The possibility of signs of life in Martian polar regions should not be overlooked. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C11C0930W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C11C0930W">The Sea Ice Index: A Resource for Cryospheric Knowledge Mobilization</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Windnagel, A. K.; Fetterer, F. M. 2017-12-01 The Sea Ice Index is a popular source of information about Arctic and Antarctic sea ice data and trends created at the National Snow and Ice Data Center (NSIDC) in 2002. It has been used by cryospheric scientists, cross-discipline scientists, the press, policy makers, and the public for the past 15 years. The Index started as a prototype sea ice extent product in 2001 and was envisioned as a website that would meet a need for readily accessible, easy-to-use information on sea ice trends and anomalies, with products that would assist in monitoring and diagnosing the ice extent minima that were gaining increasing attention in the research community in the late 1990s. The goal was to easily share these valuable data with everyone that needed them, which is the essence of knowledge mobilization. As time has progressed, we have found new ways of disseminating the information carried by the data by providing simple pictures on a website, animating those images, creating Google Earth animations that show the data on a globe, providing simple text files of data values that do not require special software to read, writing a monthly blog about the data that has over 1.7 million readers annually, providing the data to NOAA's Science on Sphere to be seen in museums and classrooms across 23 countries, and creating geo-registered images for use in geospatial software. The Index helps to bridge the gap between sea ice science and the public. Through NSIDC's User Services Office, we receive feedback on the Index and have endeavored to meet the changing needs of our stakeholder communities to best mobilize this knowledge in their direction. We have learned through trial-by-fire the best practices for delivering these data and data services. This tells the tale of managing an unassuming data set as it has journeyed from a simple product consisting of images of sea ice to one that is robust enough to be used in the IPCC Climate Change Report but easy enough to be understood by K-12 </li> <li> <a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70186956','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70186956">Snow and ice perturbation during historical volcanic eruptions and the formation of lahars and floods</a> <a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Major, Jon J.; Newhall, Christopher G. 1989-01-01 Historical eruptions have produced lahars and floods by perturbing snow and ice at more than 40 volcanoes worldwide. Most of these volcanoes are located at latitudes higher than 35°; those at lower latitudes reach altitudes generally above 4000 m. Volcanic events can perturb mantles of snow and ice in at least five ways: (1) scouring and melting by flowing pyroclastic debris or blasts of hot gases and pyroclastic debris, (2) surficial melting by lava flows, (3) basal melting of glacial ice or snow by subglacial eruptions or geothermal activity, (4) ejection of water by eruptions through a crater lake, and (5) deposition of tephra fall. Historical records of volcanic eruptions at snow-clad volcanoes show the following: (1) Flowing pyroclastic debris (pyroclastic flows and surges) and blasts of hot gases and pyroclastic debris are the most common volcanic events that generate lahars and floods; (2) Surficial lava flows generally cannot melt snow and ice rapidly enough to form large lahars or floods; (3) Heating the base of a glacier or snowpack by subglacial eruptions or by geothermal activity can induce basal melting that may result in ponding of water and lead to sudden outpourings of water or sediment-rich debris flows; (4) Tephra falls usually alter ablation rates of snow and ice but generally produce little meltwater that results in the formation of lahars and floods; (5) Lahars and floods generated by flowing pyroclastic debris, blasts of hot gases and pyroclastic debris, or basal melting of snow and ice commonly have volumes that exceed 105 m3.The glowing lava (pyroclastic flow) which flowed with force over ravines and ridges...gathered in the basin quickly and then forced downwards. As a result, tremendously wide and deep pathways in the ice and snow were made and produced great streams of water (Wolf 1878). </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1989BVol...52....1M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1989BVol...52....1M">Snow and ice perturbation during historical volcanic eruptions and the formation of lahars and floods</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Major, Jon J.; Newhall, Christopher G. 1989-10-01 Historical eruptions have produced lahars and floods by perturbing snow and ice at more than 40 volcanoes worldwide. Most of these volcanoes are located at latitudes higher than 35°; those at lower latitudes reach altitudes generally above 4000 m. Volcanic events can perturb mantles of snow and ice in at least five ways: (1) scouring and melting by flowing pyroclastic debris or blasts of hot gases and pyroclastic debris, (2) surficial melting by lava flows, (3) basal melting of glacial ice or snow by subglacial eruptions or geothermal activity, (4) ejection of water by eruptions through a crater lake, and (5) deposition of tephra fall. Historical records of volcanic eruptions at snow-clad volcanoes show the following: (1) Flowing pyroclastic debris (pyroclastic flows and surges) and blasts of hot gases and pyroclastic debris are the most common volcanic events that generate lahars and floods; (2) Surficial lava flows generally cannot melt snow and ice rapidly enough to form large lahars or floods; (3) Heating the base of a glacier or snowpack by subglacial eruptions or by geothermal activity can induce basal melting that may result in ponding of water and lead to sudden outpourings of water or sediment-rich debris flows; (4) Tephra falls usually alter ablation rates of snow and ice but generally produce little meltwater that results in the formation of lahars and floods; (5) Lahars and floods generated by flowing pyroclastic debris, blasts of hot gases and pyroclastic debris, or basal melting of snow and ice commonly have volumes that exceed 105 m3. The glowing lava (pyroclastic flow) which flowed with force over ravines and ridges...gathered in the basin quickly and then forced downwards. As a result, tremendously wide and deep pathways in the ice and snow were made and produced great streams of water (Wolf 1878). </li> <li> <a target="_blank" onclick="trackOutboundLink('https://eric.ed.gov/?q=igneous+AND+rock&pg=2&id=EJ275135','ERIC'); return false;" href="https://eric.ed.gov/?q=igneous+AND+rock&pg=2&id=EJ275135">Winter Ice and Snow as Models of Igneous Rock Formation.</a> <a target="_blank" href="http://www.eric.ed.gov/ERICWebPortal/search/extended.jsp?_pageLabel=advanced">ERIC Educational Resources Information Center</a> Romey, William D. 1983-01-01 Examines some features of ice and snow that offer teachers and researchers help in understanding many aspects of igneous processes and configurations. Careful observation of such processes as melting, decay, evolution, and snow accumulation provide important clues to understanding processes by which many kinds of rocks form. (Author/JN) </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.gpo.gov/fdsys/pkg/FR-2011-02-09/pdf/2011-2837.pdf','FEDREG'); return false;" href="https://www.gpo.gov/fdsys/pkg/FR-2011-02-09/pdf/2011-2837.pdf">76 FR 7238 - Pipeline Safety: Dangers of Abnormal Snow and Ice Build-Up on Gas Distribution Systems</a> <a target="_blank" href="http://www.gpo.gov/fdsys/browse/collection.action?collectionCode=FR">Federal Register 2010, 2011, 2012, 2013, 2014</a> 2011-02-09 ... been related to either the stress of snow and ice or the malfunction of pressure control equipment due... to have been related to either the stress of snow and ice or malfunction of pressure control... from the stresses imposed by the additional loading of the snow or ice. Damage to facilities may also... </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19950049157&hterms=solar+energy&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dsolar%2Benergy','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19950049157&hterms=solar+energy&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dsolar%2Benergy">The effect of sea ice on the solar energy budget in the astmosphere-sea ice-ocean system: A model study</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Jin, Z.; Stamnes, Knut; Weeks, W. F.; Tsay, Si-Chee 1994-01-01 A coupled one-dimensional multilayer and multistream radiative transfer model has been developed and applied to the study of radiative interactions in the atmosphere, sea ice, and ocean system. The consistent solution of the radiative transfer equation in this coupled system automatically takes into account the refraction and reflection at the air-ice interface and allows flexibility in choice of stream numbers. The solar radiation spectrum (0.25 micron-4.0 micron) is divided into 24 spectral bands to account adequately for gaseous absorption in the atmosphere. The effects of ice property changes, including salinity and density variations, as well as of melt ponds and snow cover variations over the ice on the solar energy distribution in the entire system have been studied quantitatively. The results show that for bare ice it is the scattering, determined by air bubbles and brine pockets, in just a few centimeters of the top layer of ice that plays the most important role in the solar energy absorption and partitioning in the entire system. Ice thickness is important to the energy distribution only when the ice is thin, while the absorption in the atmosphere is not sensitive to ice thickness exceeds about 70 cm. The presence of clouds moderates all the sensitivities of the absorptive amounts in each layer to the variations in the ice properties and ice thickness. Comparisons with observational spectral albedo values for two simple ice types are also presented. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://polar.ncep.noaa.gov/seaice','SCIGOVWS'); return false;" href="http://polar.ncep.noaa.gov/seaice">NCEP MMAB Sea Ice Home Page</a> <a target="_blank" href="http://www.science.gov/aboutsearch.html">Science.gov Websites</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-GSFC_20171208_Archive_e000757.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-GSFC_20171208_Archive_e000757.html">Arctic Sea Ice Sets New Record Winter Low</a> <a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a> 2015-03-19 The sea ice cap of the Arctic appeared to reach its annual maximum winter extent on February 25, according to data from the NASA-supported National Snow and Ice Data Center (NSIDC) at the University of Colorado, Boulder. At 5.61 million square miles (14.54 million square kilometers), this year’s maximum extent was the smallest on the satellite record and also one of the earliest. Credit: NASA Goddard Space Flight Center 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014JGRC..119.4168M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014JGRC..119.4168M">Calibration of sea ice dynamic parameters in an ocean-sea ice model using an ensemble Kalman filter</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018BGeo...15.1987S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018BGeo...15.1987S">Do pelagic grazers benefit from sea ice? Insights from the Antarctic sea ice proxy IPSO25</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C23E..02W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C23E..02W">When Models and Observations Collide: Journeying towards an Integrated Snow Depth Product</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Webster, M.; Petty, A.; Boisvert, L.; Markus, T.; Kurtz, N. T.; Kwok, R.; Perovich, D. K. 2017-12-01 Knowledge of snow depth is essential for assessing changes in sea ice mass balance due to snow's insulating and reflective properties. In remote sensing applications, the accuracy of sea ice thickness retrievals from altimetry crucially depends on snow depth. Despite the need for snow depth data, we currently lack continuous observations that capture the basin-scale snow depth distribution and its seasonal evolution. Recent in situ and remote sensing observations are sparse in space and time, and contain uncertainties, caveats, and/or biases that often require careful interpretation. Likewise, using model output for remote sensing applications is limited due to uncertainties in atmospheric forcing and different treatments of snow processes. Here, we summarize our efforts in bringing observational and model data together to develop an approach for an integrated snow depth product. We start with a snow budget model and incrementally incorporate snow processes to determine the effects on snow depth and to assess model sensitivity. We discuss lessons learned in model-observation integration and ideas for potential improvements to the treatment of snow in models. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C51A0955L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C51A0955L">Sea ice roughness: the key for predicting Arctic summer ice albedo</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016TCry...10.2173G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016TCry...10.2173G">Estimates of ikaite export from sea ice to the underlying seawater in a sea ice-seawater mesocosm</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..1512466B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..1512466B">Monitoring Snow and Land Ice Using Satellite data in the GMES Project CryoLand</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Bippus, Gabriele; Nagler, Thomas 2013-04-01 The main objectives of the project "CryoLand - GMES Service Snow and Land Ice" are to develop, implement and validate services for snow, glaciers and lake and river ice products as a Downstream Service within the Global Monitoring for Environment and Security (GMES) program of the European Commission. CryoLand exploits Earth Observation data from current optical and microwave sensors and of the upcoming GMES Sentinel satellite family. The project prepares also the basis for the cryospheric component of the GMES Land Monitoring services. The CryoLand project team consists of 10 partner organisations from Austria, Finland, Norway, Sweden, Switzerland and Romania and is funded by the 7th Framework Program of the European Commission. The CryoLand baseline products for snow include fractional snow extent from optical satellite data, the extent of melting snow from SAR data, and coarse resolution snow water equivalent maps from passive microwave data. Experimental products include maps of snow surface wetness and temperature. The products range from large scale coverage at medium resolution to regional products with high resolution, in order to address a wide user community. Medium resolution optical data (e.g. MODIS, in the near future Sentinel-3) and SAR (ENVISAT ASAR, in the near future Sentinel-1) are the main sources of EO data for generating large scale products in near real time. For generation of regional products high resolution satellite data are used. Glacier products are based on high resolution optical (e.g. SPOT-5, in the near future Sentinel-2) and SAR (TerraSAR-X, in the near future Sentinel-1) data and include glacier outlines, mapping of glacier facies, glacier lakes and ice velocity. The glacier products are generated on users demand. Current test areas are located in the Alps, Norway, Greenland and the Himalayan Mountains. The lake and river ice products include ice extent and its temporal changes and snow extent on ice. The algorithms for these </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23135470','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23135470">Greenland ice-sheet contribution to sea-level rise buffered by meltwater storage in firn.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Harper, J; Humphrey, N; Pfeffer, W T; Brown, J; Fettweis, X 2012-11-08 Surface melt on the Greenland ice sheet has shown increasing trends in areal extent and duration since the beginning of the satellite era. Records for melt were broken in 2005, 2007, 2010 and 2012. Much of the increased surface melt is occurring in the percolation zone, a region of the accumulation area that is perennially covered by snow and firn (partly compacted snow). The fate of melt water in the percolation zone is poorly constrained: some may travel away from its point of origin and eventually influence the ice sheet's flow dynamics and mass balance and the global sea level, whereas some may simply infiltrate into cold snow or firn and refreeze with none of these effects. Here we quantify the existing water storage capacity of the percolation zone of the Greenland ice sheet and show the potential for hundreds of gigatonnes of meltwater storage. We collected in situ observations of firn structure and meltwater retention along a roughly 85-kilometre-long transect of the melting accumulation area. Our data show that repeated infiltration events in which melt water penetrates deeply (more than 10 metres) eventually fill all pore space with water. As future surface melt intensifies under Arctic warming, a fraction of melt water that would otherwise contribute to sea-level rise will fill existing pore space of the percolation zone. We estimate the lower and upper bounds of this storage sink to be 322 ± 44 gigatonnes and 1,289(+388)(-252) gigatonnes, respectively. Furthermore, we find that decades are required to fill this pore space under a range of plausible future climate conditions. Hence, routing of surface melt water into filling the pore space of the firn column will delay expansion of the area contributing to sea-level rise, although once the pore space is filled it cannot quickly be regenerated. </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">19</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> <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">20</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> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27665449','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27665449">Water-soluble elements in snow and ice on Mt. Yulong.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Niu, Hewen; Kang, Shichang; Shi, Xiaofei; He, Yuanqing; Lu, Xixi; Shi, Xiaoyi; Paudyal, Rukumesh; Du, Jiankuo; Wang, Shijin; Du, Jun; Chen, Jizu 2017-01-01 Melting of high-elevation glaciers can be accelerated by the deposition of light-absorbing aerosols (e.g., organic carbon, mineral dust), resulting in significant reductions of the surface albedo on glaciers. Organic carbon deposited in glaciers is of great significance to global carbon cycles, snow photochemistry, and air-snow exchange processes. In this work, various snow and ice samples were collected at high elevation sites (4300-4850masl) from Mt. Yulong on the southeastern Tibetan Plateau in 2015. These samples were analyzed for water-soluble organic carbon (DOC), total nitrogen (TN), and water-soluble inorganic ions (WSIs) to elucidate the chemical species and compositions of the glaciers in the Mt. Yulong region. Generally, glacial meltwater had the lowest DOC content (0.39mgL -1 ), while fresh snow had the highest (2.03mgL -1 ) among various types of snow and ice samples. There were obvious spatial and temporal trends of DOC and WSIs in glaciers. The DOC and TN concentrations decreased in the order of fresh snow, snow meltwater, snowpit, and surface snow, resulting from the photolysis of DOC and snow's quick-melt effects. The surface snow had low DOC and TN depletion ratios in the melt season; specifically, the ratios were -0.79 and -0.19mgL -1 d -1 , respectively. In the winter season, the ratios of DOC and TN were remarkably higher, with values of -0.20mgL -1 d -1 and -0.08mgL -1 d -1 , respectively. A reduction of the DOC and TN content in glaciers was due to snow's quick melt and sublimation. Deposition of these light-absorbing impurities (LAPs) in glaciers might accelerate snowmelt and even glacial retreat. Copyright © 2016 Elsevier B.V. All rights reserved. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..1612097L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..1612097L">The Met Office Coupled Atmosphere/Land/Ocean/Sea-Ice Data Assimilation System</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Lea, Daniel; Mirouze, Isabelle; Martin, Matthew; Hines, Adrian; Guiavarch, Catherine; Shelly, Ann 2014-05-01 The Met Office has developed a weakly-coupled data assimilation (DA) system using the global coupled model HADGEM3 (Hadley Centre Global Environment Model, version 3). This model combines the atmospheric model UM (Unified Model) at 60 km horizontal resolution on 85 vertical levels, the ocean model NEMO (Nucleus for European Modeling of the Ocean) at 25 km (at the equator) horizontal resolution on 75 vertical levels, and the sea-ice model CICE at the same resolution as NEMO. The atmosphere and the ocean/sea-ice fields are coupled every 1-hour using the OASIS coupler. The coupled model is corrected using two separate 6-hour window data assimilation systems: a 4D-Var for the atmosphere with associated soil moisture content nudging and snow analysis schemes on the one hand, and a 3D-Var FGAT for the ocean and sea-ice on the other hand. The background information in the DA systems comes from a previous 6-hour forecast of the coupled model. To show the impact of coupled DA, one-month experiments have been carried out, including 1) a full atmosphere/land/ocean/sea-ice coupled DA run, 2) an atmosphere-only run forced by OSTIA SSTs and sea-ice with atmosphere and land DA, and 3) an ocean-only run forced by atmospheric fields from run 2 with ocean and sea-ice DA. In addition, 5-day forecast runs, started twice a day, have been produced from initial conditions generated by either run 1 or a combination of runs 2 and 3. The different results have been compared to each other and, whenever possible, to other references such as the Met Office atmosphere and ocean operational analyses or the OSTIA data. These all show the coupled DA system functioning well. Evidence of imbalances and initialisation shocks has also been looked for. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/985326','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/985326">Measured Black Carbon Deposition on the Sierra Nevada Snow Pack and Implication for Snow Pack Retreat</a> <a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Hadley, O.L.; Corrigan, C.E.; Kirchstetter, T.W. 2010-01-12 Modeling studies show that the darkening of snow and ice by black carbon deposition is a major factor for the rapid disappearance of arctic sea ice, mountain glaciers and snow packs. This study provides one of the first direct measurements for the efficient removal of black carbon from the atmosphere by snow and its subsequent deposition to the snow packs of California. The early melting of the snow packs in the Sierras is one of the contributing factors to the severe water problems in California. BC concentrations in falling snow were measured at two mountain locations and in rain atmore » a coastal site. All three stations reveal large BC concentrations in precipitation, ranging from 1.7 ng/g to 12.9 ng/g. The BC concentrations in the air after the snow fall were negligible suggesting an extremely efficient removal of BC by snow. The data suggest that below cloud scavenging, rather than ice nuclei, was the dominant source of BC in the snow. A five-year comparison of BC, dust, and total fine aerosol mass concentrations at multiple sites reveals that the measurements made at the sampling sites were representative of large scale deposition in the Sierra Nevada. The relative concentration of iron and calcium in the mountain aerosol indicates that one-quarter to one-third of the BC may have been transported from Asia.« less </li> <li> <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">The classification of the Arctic Sea ice types and the determination of surface temperature using advanced very high resolution radiometer data</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Massom, Robert; Comiso, Josefino C. 1994-01-01 The accurate quantification of new ice and open water areas and surface temperatures within the sea ice 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 sea ice in the Bering and Greenland seas, both in terms of surface type and physical temperature. The basis of the classification algorithm, which is developed using a late wintertime Bering Sea ice cover data, is that frequency distributions of 10.8- micrometers radiances provide four distinct peaks, represeting open water, new ice, young ice, and thick ice 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 ice 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 adjacent snow and ice. 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 ice. 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 ice 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 ice particle distribution, and atmospheric temperature inversions. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1916487A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1916487A">SWEAT: Snow Water Equivalent with AlTimetry</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Agten, Dries; Benninga, Harm-Jan; Diaz Schümmer, Carlos; Donnerer, Julia; Fischer, Georg; Henriksen, Marie; Hippert Ferrer, Alexandre; Jamali, Maryam; Marinaci, Stefano; Mould, Toby JD; Phelan, Liam; Rosker, Stephanie; Schrenker, Caroline; Schulze, Kerstin; Emanuel Telo Bordalo Monteiro, Jorge 2017-04-01 To study how the water cycle changes over time, satellite and airborne remote sensing missions are typically employed. Over the last 40 years of satellite missions, the measurement of true water inventories stored in sea and land ice within the cryosphere have been significantly hindered by uncertainties introduced by snow cover. Being able to determine the thickness of this snow cover would act to reduce such error, improving current estimations of hydrological and climate models, Earth's energy balance (albedo) calculations and flood predictions. Therefore, the target of the SWEAT (Snow Water Equivalent with AlTimetry) mission is to directly measure the surface Snow Water Equivalent (SWE) on sea and land ice within the polar regions above 60°and below -60° latitude. There are no other satellite missions currently capable of directly measuring SWE. In order to achieve this, the proposed mission will implement a novel combination of Ka- and Ku-band radioaltimeters (active microwave sensors), capable of penetrating into the snow microstructure. The Ka-band altimeter (λ ≈ 0.8 cm) provides a low maximum snow pack penetration depth of up to 20 cm for dry snow at 37 GHz, since the volume scattering of snow dominates over the scattering caused by the underlying ice surface. In contrast, the Ku-band altimeter (λ ≈ 2 cm) provides a high maximum snowpack penetration depth of up to 15 m in high latitudes regions with dry snow, as volume scattering is decreased by a factor of 55. The combined difference in Ka- and Ku-band signal penetration results will provide more accurate and direct determination of SWE. Therefore, the SWEAT mission aims to improve estimations of global SWE interpreted from passive microwave products, and improve the reliability of numerical snow and climate models. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017GMD....10.3105P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017GMD....10.3105P">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</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C11F..05G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C11F..05G">Microwave Observations of Snow-Covered Freshwater Lake Ice obtained during the Great Lakes Winter EXperiment (GLAWEX), 2017</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Gunn, G. E.; Hall, D. K.; Nghiem, S. V. 2017-12-01 Studies observing lake ice using active microwave acquisitions suggest that the dominant scattering mechanism in ice is caused by double-bounce of the signal off vertical tubular bubble inclusions. Recent polarimetric SAR observations and target decomposition algorithms indicate single-bounce interactions may be the dominant source of returns, and in the absence of field observations, has been hypothesized to be the result of roughness at the ice-water interface on the order of incident wavelengths. This study presents in-situ physical observations of snow-covered lake ice in western Michigan and Wisconsin acquired during the Great Lakes Winter EXperiment in 2017 (GLAWEX'17). In conjunction with NASA's SnowEx airborne snow campaign in Colorado (http://snow.nasa.gov), C- (Sentinel-1, RADARSAT-2) and X-band (TerraSAR-X) synthetic aperture radar (SAR) observations were acquired coincidently to surface physical snow and ice observations. Small/large scale roughness features at the ice-water interface are quantified through auger transects and used as an input variable in lake ice backscatter models to assess the relative contributions from different scattering mechanisms. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA474361','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA474361">Understanding Recent Variability in the Arctic Sea Ice Cover -- Synthesis of Model Results and Observations</a> <a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a> 2007-09-01 ARCTIC SEA ICE RESEARCH The effects of global warming on the Arctic Ocean finally gained the American public’s full attention in early 2007 with the...Arctic (Brass, 2002). The observed global warming trend is most pronounced in the higher latitudes due to an effect known as the snow/ice-albedo...due to increased melting thus exposing greater areas of lower albedo land and open water areas. The effect of global warming will result in a </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFMGC13I0797F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFMGC13I0797F">ICE911 Research: Preserving and Rebuilding Reflective Ice</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Field, L. A.; Chetty, S.; Manzara, A.; Venkatesh, S. 2014-12-01 We have developed a localized surface albedo modification technique that shows promise as a method to increase reflective multi-year ice using floating materials, chosen so as to have low subsidiary environmental impact. It is now well-known that multi-year reflective ice has diminished rapidly in the Arctic over the past 3 decades and this plays a part in the continuing rapid decrease of summer-time ice. As summer-time bright ice disappears, the Arctic is losing its ability to reflect summer insolation, and this has widespread climatic effects, as well as a direct effect on sea level rise, as oceans heat and once-land-based ice melts into the sea. We have tested the albedo modification technique on a small scale over six Winter/Spring seasons at sites including California's Sierra Nevada Mountains, a Canadian lake, and a small man-made lake in Minnesota, using various materials and an evolving array of instrumentation. The materials can float and can be made to minimize effects on marine habitat and species. The instrumentation is designed to be deployed in harsh and remote locations. Localized snow and ice preservation, and reductions in water heating, have been quantified in small-scale testing. We have continued to refine our material and deployment approaches, and we have had laboratory confirmation by NASA. In the field, the materials were successfully deployed to shield underlying snow and ice from melting; applications of granular materials remained stable in the face of local wind and storms. We are evaluating the effects of snow and ice preservation for protection of infrastructure and habitat stabilization, and we are concurrently developing our techniques to aid in water conservation. Localized albedo modification options such as those being studied in this work may act to preserve ice, glaciers, permafrost and seasonal snow areas, and perhaps aid natural ice formation processes. If this method is deployed on a large enough scale, it could conceivably </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19750049790&hterms=LOSS+SOIL&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3DLOSS%2BSOIL','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19750049790&hterms=LOSS+SOIL&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3DLOSS%2BSOIL">Microwave signatures of snow, ice and soil at several wavelengths</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Gloersen, P.; Schmugge, T. J.; Chang, T. C. 1974-01-01 Analyses of data obtained from aircraft-borne radiometers have shown that the microwave signatures of various parts of the terrain depend on both the volume scattering cross-section and the dielectric loss in the medium. In soil, it has been found that experimental data fit a model in which the scattering cross section is negligible compared to the dielectric loss. On the other hand, the volume scattering cross-section in snow and continental ice was found, from analyzing data obtained with aircraft- and spacecraft-borne radiometers, to be more important than the dielectric loss or surface reflectivity in determining the observed microwave emissivity. A model which assumes Mie scattering of ice particles of various sizes was found to be the dominant volume scattering mechanism in these media. Both spectral variation in the microwave signatures of snow and ice fields, as well as the variation in the emissivity of continental ice sheets such as those covering Greenland and Antarctica appear to be consistent with this model. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19720021734','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19720021734">Microwave emission characteristics of sea ice</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20030062802','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20030062802">Satellite Snow-Cover Mapping: A Brief Review</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Hall, Dorothy K. 1995-01-01 Satellite snow mapping has been accomplished since 1966, initially using data from the reflective part of the electromagnetic spectrum, and now also employing data from the microwave part of the spectrum. Visible and near-infrared sensors can provide excellent spatial resolution from space enabling detailed snow mapping. When digital elevation models are also used, snow mapping can provide realistic measurements of snow extent even in mountainous areas. Passive-microwave satellite data permit global snow cover to be mapped on a near-daily basis and estimates of snow depth to be made, but with relatively poor spatial resolution (approximately 25 km). Dense forest cover limits both techniques and optical remote sensing is limited further by cloudcover conditions. Satellite remote sensing of snow cover with imaging radars is still in the early stages of research, but shows promise at least for mapping wet or melting snow using C-band (5.3 GHz) synthetic aperture radar (SAR) data. Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) data beginning with the launch of the first EOS platform in 1998. Digital maps will be produced that will provide daily, and maximum weekly global snow, sea ice and lake ice cover at 1-km spatial resolution. Statistics will be generated on the extent and persistence of snow or ice cover in each pixel for each weekly map, cloudcover permitting. It will also be possible to generate snow- and ice-cover maps using MODIS data at 250- and 500-m resolution, and to study and map snow and ice characteristics such as albedo. been under development. Passive-microwave data offer the potential for determining not only snow cover, but snow water equivalent, depth and wetness under all sky conditions. A number of algorithms have been developed to utilize passive-microwave brightness temperatures to provide information on snow cover and water equivalent. The variability of vegetative Algorithms are being developed to map global snow </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1338808','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1338808">The CMIP6 Sea-Ice Model Intercomparison Project (SIMIP): Understanding sea ice through climate-model simulations</a> <a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1338808-cmip6-sea-ice-model-intercomparison-project-simip-understanding-sea-ice-through-climate-model-simulations','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1338808-cmip6-sea-ice-model-intercomparison-project-simip-understanding-sea-ice-through-climate-model-simulations">The CMIP6 Sea-Ice Model Intercomparison Project (SIMIP): Understanding sea ice through climate-model simulations</a> <a target="_blank" href="http://www.osti.gov/pages">DOE PAGES</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19890018778','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19890018778">Analysis of sea ice dynamics</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A13D2086M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A13D2086M">VIIRS Data and Data Access at the NASA National Snow and Ice Data Center Distributed Active Archive Center</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Moth, P.; Johnston, T.; Fowler, D. K. 2017-12-01 Working collaboratively, NASA and NOAA are producing data from the Visible Infrared Imaging Radiometer Suite (VIIRS). The National Snow and Ice Data Center (NSIDC), a NASA Distributed Active Archive Center (DAAC), is distributing VIIRS snow cover, ice surface temperature, and sea ice cover products. Data is available in .nc and HDF5 formats with a temporal coverage of 1 January 2012 and onward. VIIRS, NOAA's latest radiometer, was launched aboard the Suomi National Polar-orbiting Partnership (SNPP) satellite on October 28, 2011. The instrument comprises 22 bands; five for high-resolution imagery, 16 at moderate resolution, and one panchromatic day/night band. VIIRS is a whiskbroom scanning radiometer that covers the spectrum between 0.412 μm and 12.01 μm and acquires spatial resolutions at nadir of 750 m, 375 m, and 750 m, respectively. One distinct advantage of VIIRS is to ensure continuity that will lead to the development of snow and sea ice climate data records with data from the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on the NASA Earth Observing System (EOS) Aqua and Terra satellites. Combined with the Advanced Very-High-resolution Radiometer (AVHRR), the AVHRR-MODIS-VIIRS timeline will start in the early 1980s and span at least four decades-and perhaps beyond-enabling researchers to produce and gain valuable insight from long, high-quality Earth System Data Records (ESDRs). Several options are available to view and download VIIRS data: Direct download from NSIDC via HTTPS. Using NASA Earthdata Search, users can explore and download VIIRS data with temporal and/or spatial filters, re-format, re-project, and subset by spatial extent and parameter. API access is also available for all these options; Using NASA Worldview, users can view Global Imagery Browse Services (GIBS) from VIIRS data; Users can join a VIIRS subscription list to have new VIIRS data automatically ftp'd or staged on a local server as it is archived at NSIDC. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JGRC..121.4966L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JGRC..121.4966L">The spectral albedo of sea ice and salt crusts on the tropical ocean of Snowball Earth: 1. Laboratory measurements</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Light, Bonnie; Carns, Regina C.; Warren, Stephen G. 2016-07-01 The ice-albedo feedback mechanism likely contributed to global glaciation during the Snowball Earth events of the Neoproterozoic era (1 Ga to 544 Ma). This feedback results from the albedo contrast between sea ice and open ocean. Little is known about the optical properties of some of the possible surface types that may have been present, including sea ice that is both snow-free and cold enough for salts to precipitate within brine inclusions. A proxy surface for such ice was grown in a freezer laboratory using the single salt NaCl and kept below the eutectic temperature (-21.2°C) of the NaCl-H2O binary system. The resulting ice cover was composed of ice and precipitated hydrohalite crystals (NaCl · 2H2O). As the cold ice sublimated, a thin lag-deposit of salt formed on the surface. To hasten its growth in the laboratory, the deposit was augmented by addition of a salt-enriched surface crust. Measurements of the spectral albedo of this surface were carried out over 90 days as the hydrohalite crust thickened due to sublimation of ice, and subsequently over several hours as the crust warmed and dissolved, finally resulting in a surface with puddled liquid brine. The all-wave solar albedo of the subeutectic crust is 0.93 (in contrast to 0.83 for fresh snow and 0.67 for melting bare sea ice). Incorporation of these processes into a climate model of Snowball Earth will result in a positive salt-albedo feedback operating between -21°C and -36°C. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007PhDT........29K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007PhDT........29K">Arctic landfast sea ice</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.1074H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.1074H">Mechanical sea-ice strength parameterized as a function of ice temperature</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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). </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29507286','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29507286">Sea ice dynamics across the Mid-Pleistocene transition in the Bering Sea.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> 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. </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">20</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> <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">21</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> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20050179461','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20050179461">Sea Ice</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C13E0999L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C13E0999L">Supporting Snow Research: SnowEx Data and Services at the NASA National Snow and Ice Data Center DAAC</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Leon, A.; Tanner, S.; Deems, J. S. 2017-12-01 The National Snow and Ice Data Center Distributed Active Archive Center (NSIDC DAAC), part of the Cooperative Institute for Research in Environmental Sciences (CIRES) at the University of Colorado Boulder, will archive and distribute all primary data sets collected during the NASA SnowEx campaigns. NSIDC DAAC's overarching goal for SnowEx data management is to steward the diverse SnowEx data sets to provide a reliable long-term archive, to enable effective data discovery, retrieval, and usage, and to support end user engagement. This goal will be achieved though coordination and collaboration with SnowEx project management and investigators. NSIDC DAAC's core functions for SnowEx data management include: Data Creation: Advise investigators on data formats and structure as well as metadata creation and content to enable preservation, usability, and discoverability. Data Documentation: Develop comprehensive data set documentation describing the instruments, data collection and derivation methods, and data file contents. Data Distribution: Provide discovery and access through NSIDC and NASA data portals to make SnowEx data available to a broad user community Data & User Support: Assist user communities with the selection and usage of SnowEx data products. In an effort to educate and broaden the SnowEx user community, we will present an overview of the SnowEx data products, tools, and services which will be available at the NSIDC DAAC. We hope to gain further insight into how the DAAC can enable the user community to seamlessly and effectively utilize SnowEx data in their research and applications. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/12208033','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/12208033">Influence of ice and snow covers on the UV exposure of terrestrial microbial communities: dosimetric studies.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Cockell, Charles S; Rettberg, Petra; Horneck, Gerda; Wynn-Williams, David D; Scherer, Kerstin; Gugg-Helminger, Anton 2002-08-01 Bacillus subtilis spore biological dosimeters and electronic dosimeters were used to investigate the exposure of terrestrial microbial communities in micro-habitats covered by snow and ice in Antarctica. The melting of snow covers of between 5- and 15-cm thickness, depending on age and heterogeneity, could increase B. subtilis spore inactivation by up to an order of magnitude, a relative increase twice that caused by a 50% ozone depletion. Within the snow-pack at depths of less than approximately 3 cm snow algae could receive two to three times the DNA-weighted irradiance they would receive on bare ground. At the edge of the snow-pack, warming of low albedo soils resulted in the formation of overhangs that provided transient UV protection to thawed and growing microbial communities on the soils underneath. In shallow aquatic habitats, thin layers of heterogeneous ice of a few millimetres thickness were found to reduce DNA-weighted irradiances by up to 55% compared to full-sky values with equivalent DNA-weighted diffuse attenuation coefficients (K(DNA)) of >200 m(-1). A 2-mm snow-encrusted ice cover on a pond was equivalent to 10 cm of ice on a perennially ice covered lake. Ice covers also had the effect of stabilizing the UV exposure, which was often subject to rapid variations of up to 33% of the mean value caused by wind-rippling of the water surface. These data show that changing ice and snow covers cause relative changes in microbial UV exposure at least as great as those caused by changing ozone column abundance. Copyright 2002 Elsevier Science B.V. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017TCry...11.1553S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017TCry...11.1553S">Sea-ice deformation in a coupled ocean-sea-ice model and in satellite remote sensing data</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2004AGUSM.C42A..02D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2004AGUSM.C42A..02D">Operationally Monitoring Sea Ice at the Canadian Ice Service</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015ChJOL..33..458Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015ChJOL..33..458Z">Influences of sea ice on eastern Bering Sea phytoplankton</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016TCry...10.2027S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016TCry...10.2027S">Sea-ice indicators of polar bear habitat</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> 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. </li> <li> <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">Ice and AIS: ship speed data and sea ice forecasts in the Baltic Sea</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Löptien, U.; Axell, L. 2014-12-01 The Baltic Sea is a seasonally ice-covered marginal sea located in a densely populated area in northern Europe. Severe sea ice conditions have the potential to hinder the intense ship traffic considerably. Thus, sea ice fore- and nowcasts are regularly provided by the national weather services. Typically, the forecast comprises several ice 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 ice 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 ice properties when fitting a mixed-effect model. This statistical fit is based on a test region in the Bothnian Sea during the severe winter 2011 and employs 15 to 25 min averages of ship speed. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28116688','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28116688">Spatiotemporal variability in surface energy balance across tundra, snow and ice in Greenland.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Lund, Magnus; Stiegler, Christian; Abermann, Jakob; Citterio, Michele; Hansen, Birger U; van As, Dirk 2017-02-01 The surface energy balance (SEB) is essential for understanding the coupled cryosphere-atmosphere system in the Arctic. In this study, we investigate the spatiotemporal variability in SEB across tundra, snow and ice. During the snow-free period, the main energy sink for ice sites is surface melt. For tundra, energy is used for sensible and latent heat flux and soil heat flux leading to permafrost thaw. Longer snow-free period increases melting of the Greenland Ice Sheet and glaciers and may promote tundra permafrost thaw. During winter, clouds have a warming effect across surface types whereas during summer clouds have a cooling effect over tundra and a warming effect over ice, reflecting the spatial variation in albedo. The complex interactions between factors affecting SEB across surface types remain a challenge for understanding current and future conditions. Extended monitoring activities coupled with modelling efforts are essential for assessing the impact of warming in the Arctic. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5889940','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5889940">Snow Grain Size Retrieval over the Polar Ice Sheets with the Ice, Cloud, and land Elevation Satellite (ICESat) Observations</a> <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Yang, Yuekui; Marshak, Alexander; Han, Mei; Palm, Stephen P.; Harding, David J. 2018-01-01 Snow grain size is an important parameter for cryosphere studies. As a proof of concept, this paper presents an approach to retrieve this parameter over Greenland, East and West Antarctica ice sheets from surface reflectances observed with the Geoscience Laser Altimeter System (GLAS) onboard the Ice, Cloud, and land Elevation Satellite (ICESat) at 1064 nm. Spaceborne lidar observations overcome many of the disadvantages in passive remote sensing, including difficulties in cloud screening and low sun angle limitations; hence tend to provide more accurate and stable retrievals. Results from the GLAS L2A campaign, which began on 25 September and lasted until 19 November, 2003, show that the mode of the grain size distribution over Greenland is the largest (~300 μm) among the three, West Antarctica is the second (~220 μm) and East Antarctica is the smallest (~190 μm). Snow grain sizes are larger over the coastal regions compared to inland the ice sheets. These results are consistent with previous studies. Applying the broadband snow surface albedo parameterization scheme developed by Garder and Sharp (2010) to the retrieved snow grain size, ice sheet surface albedo is also derived. In the future, more accurate retrievals can be achieved with multiple wavelengths lidar observations. PMID:29636591 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20170003362','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20170003362">Snow Grain Size Retrieval over the Polar Ice Sheets with the Ice, Cloud and Land Elevation Satellite (ICESat) Observations</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Yang, Yuekui; Marshak, Alexander; Han, Mei; Palm, Stephen P.; Harding, David J. 2016-01-01 Snow grain size is an important parameter for cryosphere studies. As a proof of concept, this paper presents an approach to retrieve this parameter over Greenland, East and West Antarctica ice sheets from surface reflectances observed with the Geoscience Laser Altimeter System (GLAS) onboard the Ice, Cloud, and land Elevation Satellite (ICESat) at 1064 nanometers. Spaceborne lidar observations overcome many of the disadvantages in passive remote sensing, including difficulties in cloud screening and low sun angle limitations; hence tend to provide more accurate and stable retrievals. Results from the GLAS L2A campaign, which began on 25 September and lasted until 19 November, 2003, show that the mode of the grain size distribution over Greenland is the largest (approximately 300 microns) among the three, West Antarctica is the second (220 microns) and East Antarctica is the smallest (190 microns). Snow grain sizes are larger over the coastal regions compared to inland the ice sheets. These results are consistent with previous studies. Applying the broadband snow surface albedo parameterization scheme developed by Garder and Sharp (2010) to the retrieved snow grain size, ice sheet surface albedo is also derived. In the future, more accurate retrievals can be achieved with multiple wavelengths lidar observations. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140017082','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140017082">An Improved Cryosat-2 Sea Ice Freeboard Retrieval Algorithm Through the Use of Waveform Fitting</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Kurtz, Nathan T.; Galin, N.; Studinger, M. 2014-01-01 We develop an empirical model capable of simulating the mean echo power cross product of CryoSat-2 SAR and SAR In mode waveforms over sea ice covered regions. The model simulations are used to show the importance of variations in the radar backscatter coefficient with incidence angle and surface roughness for the retrieval of surfaceelevation of both sea ice floes and leads. The numerical model is used to fit CryoSat-2 waveforms to enable retrieval of surface elevation through the use of look-up tables and a bounded trust region Newton least squares fitting approach. The use of a model to fit returns from sea ice regions offers advantages over currently used threshold retrackingmethods which are here shown to be sensitive to the combined effect of bandwidth limited range resolution and surface roughness variations. Laxon et al. (2013) have compared ice thickness results from CryoSat-2 and IceBridge, and found good agreement, however consistent assumptions about the snow depth and density of sea ice werenot used in the comparisons. To address this issue, we directly compare ice freeboard and thickness retrievals from the waveform fitting and threshold tracker methods of CryoSat-2 to Operation IceBridge data using a consistent set of parameterizations. For three IceBridge campaign periods from March 20112013, mean differences (CryoSat-2 IceBridge) of 0.144m and 1.351m are respectively found between the freeboard and thickness retrievals using a 50 sea ice floe threshold retracker, while mean differences of 0.019m and 0.182m are found when using the waveform fitting method. This suggests the waveform fitting technique is capable of better reconciling the seaice thickness data record from laser and radar altimetry data sets through the usage of consistent physical assumptions. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMGC43C1219U','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMGC43C1219U">Uncertainty Quantification and Sensitivity Analysis in the CICE v5.1 Sea Ice Model</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Urrego-Blanco, J. R.; Urban, N. M. 2015-12-01 Changes in the high latitude climate system have the potential to affect global climate through feedbacks with the atmosphere and connections with mid latitudes. Sea ice and climate models used to understand these changes have uncertainties that need to be characterized and quantified. In this work we characterize parametric uncertainty in Los Alamos Sea Ice model (CICE) and quantify the sensitivity of sea ice area, extent and volume with respect to uncertainty in about 40 individual model parameters. Unlike common sensitivity analyses conducted in previous studies where parameters are varied one-at-a-time, this study uses a global variance-based approach in which Sobol sequences are used to efficiently sample the full 40-dimensional parameter space. This approach requires a very large number of model evaluations, which are expensive to run. A more computationally efficient approach is implemented by training and cross-validating a surrogate (emulator) of the sea ice model with model output from 400 model runs. The emulator is used to make predictions of sea ice extent, area, and volume at several model configurations, which are then used to compute the Sobol sensitivity indices of the 40 parameters. A ranking based on the sensitivity indices indicates that model output is most sensitive to snow parameters such as conductivity and grain size, and the drainage of melt ponds. The main effects and interactions among the most influential parameters are also estimated by a non-parametric regression technique based on generalized additive models. It is recommended research to be prioritized towards more accurately determining these most influential parameters values by observational studies or by improving existing parameterizations in the sea ice model. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C21A0655Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C21A0655Z">Assimilation of sea ice concentration data in the Arctic via DART/CICE5 in the CESM1</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Zhang, Y.; Bitz, C. M.; Anderson, J. L.; Collins, N.; Hendricks, J.; Hoar, T. J.; Raeder, K. 2016-12-01 Arctic sea ice cover has been experiencing significant reduction in the past few decades. Climate models predict that the Arctic Ocean may be ice-free in late summer within a few decades. Better sea ice prediction is crucial for regional and global climate prediction that are vital to human activities such as maritime shipping and subsistence hunting, as well as wildlife protection as animals face habitat loss. The physical processes involved with the persistence and re-emergence of sea ice cover are found to extend the predictability of sea ice concentration (SIC) and thickness at the regional scale up to several years. This motivates us to investigate sea ice predictability stemming from initial values of the sea ice cover. Data assimilation is a useful technique to combine observations and model forecasts to reconstruct the states of sea ice in the past and provide more accurate initial conditions for sea ice prediction. This work links the most recent version of the Los Alamos sea ice model (CICE5) within the Community Earth System Model version 1.5 (CESM1.5) and the Data Assimilation Research Testbed (DART). The linked DART/CICE5 is ideal to assimilate multi-scale and multivariate sea ice observations using an ensemble Kalman filter (EnKF). The study is focused on the assimilation of SIC data that impact SIC, sea ice thickness, and snow thickness. The ensemble sea ice model states are constructed by introducing uncertainties in atmospheric forcing and key model parameters. The ensemble atmospheric forcing is a reanalysis product generated with DART and the Community Atmosphere Model (CAM). We also perturb two model parameters that are found to contribute significantly to the model uncertainty in previous studies. This study applies perfect model observing system simulation experiments (OSSEs) to investigate data assimilation algorithms and post-processing methods. One of the ensemble members of a CICE5 free run is chosen as the truth. Daily synthetic </li> <li> <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">Some Results on Sea Ice Rheology for the Seasonal Ice Zone, Obtained from the Deformation Field of Sea Ice Drift Pattern</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Toyota, T.; Kimura, N. 2017-12-01 Sea ice rheology which relates sea ice stress to the large-scale deformation of the ice cover has been a big issue to numerical sea ice modelling. At present the treatment of internal stress within sea ice area is based mostly on the rheology formulated by Hibler (1979), where the whole sea ice 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 sea ice area and horizontal resolution of the model. However, this formulation was initially developed to reproduce the seasonal variation of the perennial ice in the Arctic Ocean. As for its applicability to the seasonal ice zones (SIZ), where various types of sea ice are present, it still needs validation from observational data. In this study, the validity of this rheology was examined for the Sea of Okhotsk ice, typical of the SIZ, based on the AMSR-derived ice drift pattern in comparison with the result obtained for the Beaufort Sea. To examine the dependence on a horizontal scale, the coastal radar data operated near the Hokkaido coast, Japan, were also used. Ice 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 Sea of Okhotsk and the Beaufort Sea and 1.3 km from the coastal radar for the near-shore Sea 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 ice areas. Since this result corresponds with the yield criterion by Tresca and </li> <li> <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">Blue Beaufort Sea Ice from Operation IceBridge</a> <a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a> 2017-12-08 Mosaic image of sea ice in the Beaufort Sea created by the Digital Mapping System (DMS) instrument aboard the IceBridge P-3B. The dark area in the middle of the image is open water seen through a lead, or opening, in the ice. Light blue areas are thick sea ice and dark blue areas are thinner ice formed as water in the lead refreezes. Leads are formed when cracks develop in sea ice 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.C52B..05L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.C52B..05L">Tracking sea ice floes from the Lincoln Sea to Nares Strait and deriving large scale melt from coincident spring and summer (2009) aerial EM thickness surveys</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Lange, B. A.; Haas, C.; Beckers, J.; Hendricks, S. 2011-12-01 Satellite observations demonstrate a decreasing summer Arctic sea ice extent over the past ~40 years, as well as a smaller perennial sea ice zone, with a significantly accelerated decline in the last decade. Recent ice extent observations are significantly lower than predicted by any model employed by the Intergovernmental Panel on Climate Change. The disagreement of the modeled and observed results, along with the large variability of model results, can be in part attributed to a lack of consistent and long term sea ice mass balance observations for the High Arctic. This study presents the derivation of large scale (individual floe) seasonal sea ice mass balance in the Lincoln Sea and Nares Strait. Large scale melt estimates are derived by comparing aerial borne electromagnetic induction thickness surveys conducted in spring with surveys conducted in summer 2009. The comparison of coincident floes is ensured by tracking sea ice using ENIVSAT ASAR and MODIS satellite imagery. Only EM thickness survey sections of floes that were surveyed in both spring and summer are analyzed and the resulting modal thicknesses of the distributions, which represent the most abundant ice type, are compared to determine the difference in thickness and therefore total melt (snow+basal ice+surface ice melt). Preliminary analyses demonstrate a bulk (regional ice tracking) seasonal total thickness variability of 1.1m, Lincoln Sea modal thickness 3.7m (April, 2009) and Nares Strait modal thickness 2.6m (August 2009)(Fig1). More detailed floe tracking, in depth analysis of EM surveys and removal of deformed ridged/rafted sea ice (due to inaccuracies over deformed ice) will result in more accurate melt estimates for this region and will be presented. The physical structure of deformed sea ice and the footprint of the EM instrument typically underestimate the total thicknesses observed. Seasonal variations of sea ice properties can add additional uncertainty to the response of the EM </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.C33A0684F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.C33A0684F">Ice911 Research: Preserving and Rebuilding Multi-Year Ice</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Field, L. A.; Chetty, S.; Manzara, A. 2013-12-01 A localized surface albedo modification technique is being developed that shows promise as a method to increase multi-year ice using reflective floating materials, chosen so as to have low subsidiary environmental impact. Multi-year ice has diminished rapidly in the Arctic over the past 3 decades (Riihela et al, Nature Climate Change, August 4, 2013) and this plays a part in the continuing rapid decrease of summer-time ice. As summer-time ice disappears, the Arctic is losing its ability to act as the earth's refrigeration system, and this has widespread climatic effects, as well as a direct effect on sea level rise, as oceans heat, and once-land-based ice melts into the sea. We have tested the albedo modification technique on a small scale over five Winter/Spring seasons at sites including California's Sierra Nevada Mountains, a Canadian lake, and a small man-made lake in Minnesota, using various materials and an evolving array of instrumentation. The materials can float and can be made to minimize effects on marine habitat and species. The instrumentation is designed to be deployed in harsh and remote locations. Localized snow and ice preservation, and reductions in water heating, have been quantified in small-scale testing. Climate modeling is underway to analyze the effects of this method of surface albedo modification in key areas on the rate of oceanic and atmospheric temperature rise. We are also evaluating the effects of snow and ice preservation for protection of infrastructure and habitat stabilization. This paper will also discuss a possible reduction of sea level rise with an eye to quantification of cost/benefit. The most recent season's experimentation on a man-made private lake in Minnesota saw further evolution in the material and deployment approach. The materials were successfully deployed to shield underlying snow and ice from melting; applications of granular materials remained stable in the face of local wind and storms. Localized albedo </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140017491','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140017491">NASA Team 2 Sea Ice Concentration Algorithm Retrieval Uncertainty</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Brucker, Ludovic; Cavalieri, Donald J.; Markus, Thorsten; Ivanoff, Alvaro 2014-01-01 Satellite microwave radiometers are widely used to estimate sea ice cover properties (concentration, extent, and area) through the use of sea ice concentration (IC) algorithms. Rare are the algorithms providing associated IC uncertainty estimates. Algorithm uncertainty estimates are needed to assess accurately global and regional trends in IC (and thus extent and area), and to improve sea ice predictions on seasonal to interannual timescales using data assimilation approaches. This paper presents a method to provide relative IC uncertainty estimates using the enhanced NASA Team (NT2) IC algorithm. The proposed approach takes advantage of the NT2 calculations and solely relies on the brightness temperatures (TBs) used as input. NT2 IC and its associated relative uncertainty are obtained for both the Northern and Southern Hemispheres using the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) TB. NT2 IC relative uncertainties estimated on a footprint-by-footprint swath-by-swath basis were averaged daily over each 12.5-km grid cell of the polar stereographic grid. For both hemispheres and throughout the year, the NT2 relative uncertainty is less than 5%. In the Southern Hemisphere, it is low in the interior ice pack, and it increases in the marginal ice zone up to 5%. In the Northern Hemisphere, areas with high uncertainties are also found in the high IC area of the Central Arctic. Retrieval uncertainties are greater in areas corresponding to NT2 ice types associated with deep snow and new ice. Seasonal variations in uncertainty show larger values in summer as a result of melt conditions and greater atmospheric contributions. Our analysis also includes an evaluation of the NT2 algorithm sensitivity to AMSR-E sensor noise. There is a 60% probability that the IC does not change (to within the computed retrieval precision of 1%) due to sensor noise, and the cumulated probability shows that there is a 90% chance that the IC varies by less than </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19940015961&hterms=glacier+melt&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dglacier%2Bmelt','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19940015961&hterms=glacier+melt&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dglacier%2Bmelt">Radar backscattering from snow facies of the Greenland ice sheet: Results from the AIRSAR 1991 campaign</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Rignot, Eric; Jezek, K.; Vanzyl, J. J.; Drinkwater, Mark R.; Lou, Y. L. 1993-01-01 In June 1991, the NASA/JPL airborne SAR (AIRSAR) acquired C- (lambda = 5.6cm), L- (lambda = 24cm), and P- (lambda = 68m) band polarimetric SAR data over the Greenland ice sheet. These data are processed using version 3.55 of the AIRSAR processor which provides radiometrically and polarimetrically calibrated images. The internal calibration of the AIRSAR data is cross-checked using the radar response from corner reflectors deployed prior to flight in one of the scenes. In addition, a quantitative assessment of the noise power level at various frequencies and polarizations is made in all the scenes. Synoptic SAR data corresponding to a swath width of about 12 by 50 km in length (compared to the standard 12 x 12 km size of high-resolution scenes) are also processed and calibrated to study transitions in radar backscatter as a function of snow facies at selected frequencies and polarizations. The snow facies on the Greenland ice sheet are traditionally categorized based on differences in melting regime during the summer months. The interior of Greenland corresponds to the dry snow zone where terrain elevation is the highest and no snow melt occurs. The lowest elevation boundary of the dry snow zone is known traditionally as the dry snow line. Beneath it is the percolation zone where melting occurs in the summer and water percolates through the snow freezing at depth to form massive ice lenses and ice pipes. At the downslope margin of this zone is the wet snow line. Below it, the wet snow zone corresponds to the lowest elevations where snow remains at the end of the summer. Ablation produces enough meltwater to create areas of snow saturated with water, together with ponds and lakes. The lowest altitude zone of ablation sees enough summer melt to remove all traces of seasonal snow accumulation, such that the surface comprises bare glacier ice. </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">21</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> <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">22</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> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2004AGUSM.U24A..01B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2004AGUSM.U24A..01B">OASIS: Ocean-Atmosphere-Sea-Ice-Snowpack Interactions in Polar Regions</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Bottenheim, J. W.; Abbatt, J.; Beine, H.; Berg, T.; Bigg, K.; Domine, F.; Leck, C.; Lindberg, S.; Matrai, P.; MacDonald, R.; McConnell, J.; Platt, U.; Raspopov, O.; Shepson, P.; Shumilov, O.; Stutz, J.; Wolff, E. 2004-05-01 While Polar regions encompass a large part of the globe, little attention has been paid to the interactions between the atmosphere and its extensive snow-covered surfaces. Recent discoveries in the Arctic and Antarctic show that the top ten centimeters of snow is not simply a white blanket but in fact is a surprisingly reactive medium for chemical reactions in the troposphere. It has been concluded that interlinked physical, chemical, and biological mechanisms, fueled by the sun and occurring in the snow, are responsible for depletion of tropospheric ozone and gaseous mercury. At the same time production of highly reactive compounds (e.g. formaldehyde, nitrogen dioxide) has been observed at the snow surface. Air-snow interactions also have an impact on the chemical composition of the snow and hence the nature and amounts of material released in terrestrial/marine ecosystems during the melting of seasonal snow-packs. Many details of these possibly naturally occurring processes are yet to be discovered. For decades humans have added waste products including acidic particles (sulphates) and toxic contaminants such as gaseous mercury and POPs (persistent organic pollutants) to the otherwise pristine snow surface. Virtually nothing is known about transformations of these contaminants in the snowpack, making it impossible to assess the risk to the polar environment, including humans. This is especially disconcerting when considering that climate change will undoubtedly alter the nature of these transformations involving snow, ice, atmosphere, ocean, and, ultimately, biota. To address these topics an interdisciplinary group of scientists from North America, Europe and Japan is developing a set of coordinated research activities under the banner of the IGBP programs IGAC and SOLAS. The program of Ocean-Atmosphere-Sea Ice-Snowpack (OASIS) interactions has been established with a mission statement aimed at determining the impact of OASIS chemical exchange on tropospheric </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/biblio/1042528-enhanced-solar-energy-absorption-internally-mixed-black-carbon-snow-grains','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1042528-enhanced-solar-energy-absorption-internally-mixed-black-carbon-snow-grains">Enhanced Solar Energy Absorption by Internally-mixed Black Carbon in Snow Grains</a> <a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Flanner, M. G.; Liu, Xiaohong; Zhou, Cheng 2012-05-30 Here we explore light absorption by snowpack containing black carbon (BC) particles residing within ice grains. Basic considerations of particle volumes and BC/snow mass concentrations show that there are generally 0:05-109 BC particles for each ice grain. This suggests that internal BC is likely distributed as multiple inclusions within ice grains, and thus the dynamic effective medium approximation (DEMA) (Chylek and Srivastava, 1983) is a more appropriate optical representation for BC/ice composites than coated-sphere or standard mixing approximations. DEMA calculations show that the 460 nm absorption cross-section of BC/ice composites, normalized to the mass of BC, is typically enhanced bymore » factors of 1.8-2.1 relative to interstitial BC. BC effective radius is the dominant cause of variation in this enhancement, compared with ice grain size and BC volume fraction. We apply two atmospheric aerosol models that simulate interstitial and within-hydrometeor BC lifecycles. Although only {approx}2% of the atmospheric BC burden is cloud-borne, 71-83% of the BC deposited to global snow and sea-ice surfaces occurs within hydrometeors. Key processes responsible for within-snow BC deposition are development of hydrophilic coatings on BC, activation of liquid droplets, and subsequent snow formation through riming or ice nucleation by other species and aggregation/accretion of ice particles. Applying deposition fields from these aerosol models in offline snow and sea-ice simulations, we calculate that 32-73% of BC in global surface snow resides within ice grains. This fraction is smaller than the within-hydrometeor deposition fraction because meltwater flux preferentially removes internal BC, while sublimation and freezing within snowpack expose internal BC. Incorporating the DEMA into a global climate model, we simulate increases in BC/snow radiative forcing of 43-86%, relative to scenarios that apply external optical properties to all BC. We show that snow </li> <li> <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">[Reflectance of sea ice in Liaodong Bay].</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Xu, Zhan-tang; Yang, Yue-zhong; Wang, Gui-fen; Cao, Wen-xi; Kong, Xiang-peng 2010-07-01 In the present study, the relationships between sea ice albedo and the bidirectional reflectance distribution in Liaodong Bay were investigated. The results indicate that: (1) sea ice albedo alpha(lambda) is closely related to the components of sea ice, the higher the particulate concentration in sea ice surface is, the lower the sea ice albedo alpha(lambda) is. On the contrary, the higher the bubble concentration in sea ice is, the higher sea ice albedo alpha(lambda) is. (2) Sea ice 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 sea ice would have the different anisotropic reflectance factors. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..1511292F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..1511292F">Ice2sea - Estimating the future contribution of continental ice to sea-level rise - project summary</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Ford, Elaina; Vaughan, David 2013-04-01 Ice2sea brings together the EU's scientific and operational expertise from 24 leading institutions across Europe and beyond. Improved projections of the contribution of ice to sea-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 ice-sheets as the most significant remaining uncertainty in projections of sea-level rise. Understanding about the crucial ice-sheet effects was "too limited to assess their likelihood or provide a best estimate of an upper bound for sea-level rise". Ice2sea 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 ice2sea project. </li> <li> <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">Ecological consequences of sea-ice decline.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> 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 2013-08-02 After a decade with nine of the lowest arctic sea-ice minima on record, including the historically low minimum in 2012, we synthesize recent developments in the study of ecological responses to sea-ice decline. Sea-ice 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 sea ice 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 sea ice diminishes. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C12A..02G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C12A..02G">Analysis of Light Absorbing Aerosols in Northern Pakistan: Concentration on Snow/Ice, their Source Regions and Impacts on Snow Albedo</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Gul, C.; Praveen, P. S.; Shichang, K.; Adhikary, B.; Zhang, Y.; Ali, S. 2016-12-01 Elemental carbon (EC) and light absorbing organic carbon (OC) are important particulate impurities in snow and ice which significantly reduce the albedo of glaciers and accelerate their melting. Snow and ice samples were collected from Karakorum-Himalayan region of North Pakistan during the summer campaign (May-Jun) 2015 and only snow samples were collected during winter (Dec 2015- Jan 2016). Total 41 surface snow/ice samples were collected during summer campaign along different elevation ranges (2569 to 3895 a.m.s.l) from six glaciers: Sachin, Henarche, Barpu, Mear, Gulkin and Passu. Similarly 18 snow samples were collected from Sust, Hoper, Tawas, Astore, Shangla, and Kalam regions during the winter campaign. Quartz filters were used for filtering of melted snow and ice samples which were then analyzed by thermal optical reflectance (TOR) method to determine the concentration of EC and OC. The average concentration of EC (ng/g), OC (ng/g) and dust (ppm) were found as follows: Passu (249.5, 536.8, 475), Barpu (1190, 397.6, 1288), Gulkin (412, 793, 761), Sachin (911, 2130, 358), Mear (678, 2067, 83) and Henarche (755, 1868, 241) respectively during summer campaign. Similarly, average concentration of EC (ng/g), OC (ng/g) and dust (ppm) was found in the samples of Sust (2506, 1039, 131), Hoper (646, 1153, 76), Tawas (650, 1320, 16), Astore (1305, 2161, 97), Shangla (739, 2079, 31) and Kalam (107, 347, 5) respectively during winter campaign. Two methods were adopted to identify the source regions: one coupled emissions inventory with back trajectories, second with a simple region tagged chemical transport modeling analysis. In addition, CALIPSO subtype aerosol composition indicated that frequency of smoke in the atmosphere over the region was highest followed by dust and then polluted dust. SNICAR model was used to estimate the snow albedo reduction from our in-situ measurements. Snow albedo reduction was observed to be 0.3% to 27.6%. The derived results were used </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFM.C43E0592P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFM.C43E0592P">The Last Arctic Sea Ice Refuge</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Pfirman, S. L.; Tremblay, B.; Newton, R.; Fowler, C. 2010-12-01 Summer sea ice 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 ice-associated species. Observations and models indicate that some ice 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 sea ice transport rates, both the central Arctic and Siberian shelf seas may be sources of ice to the region. An international system of monitoring and management of the sea ice refuge, along with the ice source regions, has the potential to maintain viable habitat for ice-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 sea ice in this region based on observations, models and paleoenvironmental information + the extent and characteristics of the “ice shed” contributing sea ice 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 ice-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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C21A0665P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C21A0665P">An Explanation for the Arctic Sea Ice Melt Pond Fractal Transition</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Popovic, P.; Abbot, D. S. 2016-12-01 As Arctic sea ice melts during the summer, pools of melt water form on its surface. This decreases the ice's albedo, which signifcantly impacts its subsequent evolution. Understanding this process is essential for buiding accurate sea ice models in GCMs and using them to forecast future changes in sea ice. A feature of melt ponds that helps determine their impact on ice albedo is that they often form complex geometric shapes. One characteristic of their shape, the fractal dimension of the pond boundaries, D, has been shown to transition between the two fundamental limits of D = 1 and D = 2 at some critical pond size. Here, we provide an explanation for this behavior. First, using aerial photographs taken during the SHEBA mission, we show how this fractal transition curve changes with time, and show that there is a qualitative difference in the pond shape as ice transitions from impermeable to permeable. While ice is impermeable, the maximum fractal dimension is less than 2, whereas after it becomes permeable, the maximum fractal dimension becomes very close to 2. We then show how the fractal dimension of the boundary of a collection of overlapping circles placed randomly on a plane also transitions from D = 1 to D = 2 at a size equal to the average size of a single circle. We, therefore, conclude that this transition is a simple geometric consequence of regular shapes connecting. The one physical parameter that can be extracted from the fractal transition curve is the length scale at which transition occurs. Previously, this length scale has been associated with the typical size of snow dunes created on the ice surface during winter. We provide an alternative explanation by noting that the flexural wavelength of the ice poses a fundamental limit on the size of melt ponds on permeable ice. If this is true, melt ponds could be used as a proxy for ice thickness. Finally, we provide some remarks on how to observationally distinguish between the two ideas for what </li> <li> <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">Sea-ice thickness from field measurements in the northwestern Barents Sea</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> King, Jennifer; Spreen, Gunnar; Gerland, Sebastian; Haas, Christian; Hendricks, Stefan; Kaleschke, Lars; Wang, Caixin 2017-02-01 The Barents Sea is one of the fastest changing regions of the Arctic, and has experienced the strongest decline in winter-time sea-ice area in the Arctic, at -23±4% decade-1. Sea-ice thickness in the Barents Sea is not well studied. We present two previously unpublished helicopter-borne electromagnetic (HEM) ice thickness measurements from the northwestern Barents Sea acquired in March 2003 and 2014. The HEM data are compared to ice thickness calculated from ice draft measured by ULS deployed between 1994 and 1996. These data show that ice 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 sea-ice from the Arctic Basin, the Barents Sea ice cover is dominated by thick multiyear ice; as was the case in 2003 and 1995. In a year with an ice cover that was mainly grown in situ, the ice 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 ice thickness. In 2003 the dominant ice class was more than 2 years old; and modal sea-ice thickness varied regionally from 0.6 to 1.4 m, with the thinner ice being either first-year ice, or multiyear ice which had come into contact with warm Atlantic water. In 2014 the ice cover was predominantly locally grown ice less than 1 month old (regional modes of 0.5-0.8 m). These two situations represent two extremes of a range of possible ice thickness distributions that can present very different conditions for shipping traffic; or have a different impact on heat transport from ocean to atmosphere. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29055575','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29055575">Review of levoglucosan in glacier snow and ice studies: Recent progress and future perspectives.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> You, Chao; Xu, Chao 2018-03-01 Levoglucosan (LEV) in glacier snow and ice layers provides a fingerprint of fire activity, ranging from modern air pollution to ancient fire emissions. In this study, we review recent progress in our understanding and application of LEV in glaciers, including analytical methods, transport and post-depositional processes, and historical records. We firstly summarize progress in analytical methods for determination of LEV in glacier snow and ice. Then, we discuss the processes influencing the records of LEV in snow and ice layers. Finally, we make some recommendations for future work, such as assessing the stability of LEV and obtaining continuous records, to increase reliability of the reconstructed ancient fire activity. This review provides an update for researchers working with LEV and will facilitate the further use of LEV as a biomarker in paleo-fire studies based on ice core records. Copyright © 2017 Elsevier B.V. All rights reserved. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C11C0923F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C11C0923F">Improving Arctic Sea Ice Observations and Data Access to Support Advances in Sea Ice Forecasting</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Farrell, S. L. 2017-12-01 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 sea ice cover. Since sea ice 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 ice cover will pose both challenges and opportunities. The sea ice 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 sea ice observational data and those conducting numerical modeling studies and forecasting ice 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 sea ice forecasting. Here, we focus on sea ice thickness, a key varaible of the Arctic ice cover. We describe multi-sensor, and blended, sea ice 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19950034737&hterms=radar+77+ghz&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dradar%2B77%2Bghz','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19950034737&hterms=radar+77+ghz&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dradar%2B77%2Bghz">Observation of melt onset on multiyear Arctic sea ice using the ERS 1 synthetic aperture radar</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Winebrenner, D. P.; Nelson, E. D.; Colony, R.; West, R. D. 1994-01-01 We present nearly coincident observations of backscattering from the Earth Remote-Sensing Satellite (ERS) 1 synthetic aperture radar (SAR) and of near-surface temperature from six drifting buoys in the Beaufort Sea, showing that the onset of melting in snow on multiyear sea ice is clearly detectable in the SAR data. Melt onset is marked by a clean, steep decrease in the backscattering cross section of multiyear ice at 5.3 GHz and VV polarization. We investigate the scattering physics responsible for the signature change and find that the cross section decrease is due solely to the appearance of liquid water in the snow cover overlying the ice. A thin layer of moist snow is sufficient to cause the observed decrease. We present a prototype algorithm to estimate the date of melt onset using the ERS 1 SAR and apply the algorithm first to the SAR data for which we have corresponding buoy temperatures. The melt onset dates estimated by the SAR algorithm agree with those obtained independently from the temperature data to within 4 days or less, with the exception of one case in which temperatures oscillated about 0 C for several weeks. Lastly, we apply the algorithm to the entire ERS 1 SAR data record acquired by the Alaska SAR Facility for the Beaufort Sea north of 73 deg N during the spring of 1992, to produce a map of the dates of melt onset over an area roughly 1000 km on a side. The progression of melt onset is primarily poleward but shows a weak meridional dependence at latitudes of approximately 76 deg-77 deg N. Melting begins in the southern part of the study region on June 13 and by June 20 has progressed to the northermost part of the region. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C21D1141B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C21D1141B">Forecast of Antarctic Sea Ice and Meteorological Fields</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Barreira, S.; Orquera, F. 2017-12-01 Since 2001, we have been forecasting the climatic fields of the Antarctic sea ice (SI) and surface air temperature, surface pressure and precipitation anomalies for the Southern Hemisphere at the Meteorological Department of the Argentine Naval Hydrographic Service with different techniques that have evolved with the years. Forecast is based on the results of Principal Components Analysis applied to SI series (S-Mode) that gives patterns of temporal series with validity areas (these series are important to determine which areas in Antarctica will have positive or negative SI anomalies based on what happen in the atmosphere) and, on the other hand, to SI fields (T-Mode) that give us the form of the SI fields anomalies based on a classification of 16 patterns. Each T-Mode pattern has unique atmospheric fields associated to them. Therefore, it is possible to forecast whichever atmosphere variable we decide for the Southern Hemisphere. When the forecast is obtained, each pattern has a probability of occurrence and sometimes it is necessary to compose more than one of them to obtain the final result. S-Mode and T-Mode are monthly updated with new data, for that reason the forecasts improved with the increase of cases since 2001. We used the Monthly Polar Gridded Sea Ice Concentrations database derived from satellite information generated by NASA Team algorithm provided monthly by the National Snow and Ice Data Center of USA that begins in November 1978. Recently, we have been experimenting with multilayer Perceptron (neuronal network) with supervised learning and a back-propagation algorithm to improve the forecast. The Perceptron is the most common Artificial Neural Network topology dedicated to image pattern recognition. It was implemented through the use of temperature and pressure anomalies field images that were associated with a the different sea ice anomaly patterns. The variables analyzed included only composites of surface air temperature and pressure anomalies </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.V21A2763E','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.V21A2763E">Experimental Insights on Natural Lava-Ice/Snow Interactions and Their Implications for Glaciovolcanic and Submarine Eruptions</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Edwards, B. R.; Karson, J.; Wysocki, R.; Lev, E.; Bindeman, I. N.; Kueppers, U. 2012-12-01 Lava-ice-snow interactions have recently gained global attention through the eruptions of ice-covered volcanoes, particularly from Eyjafjallajokull in south-central Iceland, with dramatic effects on local communities and global air travel. However, as with most submarine eruptions, direct observations of lava-ice/snow interactions are rare. Only a few hundred potentially active volcanoes are presently ice-covered, these volcanoes are generally in remote places, and their associated hazards make close observation and measurements dangerous. Here we report the results of the first large-scale experiments designed to provide new constraints on natural interactions between lava and ice/snow. The experiments comprised controlled effusion of tens of kilograms of melted basalt on top of ice/snow, and provide insights about observations from natural lava-ice-snow interactions including new constraints for: 1) rapid lava advance along the ice-lava interface; 2) rapid downwards melting of lava flows through ice; 3) lava flow exploitation of pre-existing discontinuities to travel laterally beneath and within ice; and 4) formation of abundant limu o Pele and non-explosive vapor transport from the base to the top of the lava flow with minor O isotope exchange. The experiments are consistent with observations from eruptions showing that lava is more efficient at melting ice when emplaced on top of the ice as opposed to beneath the ice, as well as the efficacy of tephra cover for slowing melting. The experimental extrusion rates are as within the range of those for submarine eruptions as well, and reproduce some features seen in submarine eruptions including voluminous production of gas rich cavities within initially anhydrous lavas and limu on lava surfaces. Our initial results raise questions about the possibility of secondary ingestion of water by submarine and glaciovolcanic lava flows, and the origins of apparent primary gas cavities in those flows. Basaltic melt moving down </li> <li> <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">Monitoring Arctic Sea ice using ERTS imagery. [Bering Sea, Beaufort Sea, Canadian Archipelago, and Greenland Sea</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Barnes, J. C.; Bowley, C. J. 1974-01-01 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 other 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 imagery is compared with visual ice reports and aerial photography from the NASA CV-990 aircraft. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C33G..08B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C33G..08B">Characterizing the Chemical and Physical Signature of the 2015-16 El Niño in the Quelccaya Ice Cap Snow and Ice to Calibrate Past ENSO Reconstructions.</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Beaudon, E.; Barker, J. D.; Kenny, D. V.; Thompson, L. G. 2017-12-01 Pacific Sea Surface Temperature (SST) anomalies have reached +3°C in the Niño 3.4 region in November 2015 making this one of the strongest El Niños in 100 years. This warm phase of the El Niño - Southern Oscillation (ENSO) has pronounced differential impacts across the tropical Pacific as well as in South America. Peru statistically experienced flooding in the northern and central regions and drought conditions in the south on the Altiplano. However, the 2015-16 El Nino event led to drought throughout the Peruvian Andes. El Niño is a warm and dry episode, phase locked with the accumulation season on the Quelccaya Ice Cap (QIC) so that this strong event create conditions favorable for enhanced surface ablation and dry deposition of soluble and insoluble aerosols. Here we present new glaciochemical (major and organic ions, dust, black carbon, oxygen isotopes) results from two consecutive snow and ice sampling campaign on QIC framing the climax of the 2015/2016 El Niño episode in Peru. We allocate the ionic and black carbon sources and describe the biogenic and evaporitic contributions to Quelccaya snow chemistry under El Niño atmospheric conditions. Elution factors and ionic budgets are compared to those of the snow and ice samples collected prior to the El Niño initiation and thereby assess the magnitude of the impact of El Niño-induced post-depositional processes. Our results provide the database needed to verify that: 1) melt and percolation induced by El Niño is identifiable in the prior year's snow layer and thus might be calibrated to the El Niño's strength; and 2) the concentration and co-association of biogenic (e.g., NH4, black carbon) and evaporitic (salts) species is enhanced and detectable deeper in the ice and thereby might serve as a proxy for documenting past El Niño frequency. By capturing the chemical signature of a modern El Niño event occurring in a warming world, these results shed light on past ENSO variability preserved in ice core </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20050139693','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20050139693">Earth Observing System (EOS) Snow and Ice Products for Observation and Modeling</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Hall, D.; Kaminski, M.; Cavalieri, D.; Dickinson, R.; Marquis, M.; Riggs, G.; Robinson, D.; VanWoert, M.; Wolfe, R. 2005-01-01 Snow and ice are the key components of the Earth's cryosphere, and their influence on the Earth's energy balance is very significant due at least in part to the large areal extent and high albedo characterizing these features. Large changes in the cryosphere have been measured over the last century and especially over the past decade, and remote sensing plays a pivotal role in documenting these changes. Many of NASA's Earth Observing System (EOS) products derived from instruments on the Terra, Aqua, and Ice, Cloud and land Elevation Satellite (ICESat) satellites are useful for measuring changes in features that are associated with climate change. The utility of the products is continually enhanced as the length of the time series increases. To gain a more coherent view of the cryosphere and its historical and recent changes, the EOS products may be employed together, in conjunction with other sources of data, and in models. To further this goal, the first EOS Snow and Ice Products Workshop was convened. The specific goals of the workshop were to provide current and prospective users of EOS snow and ice products up-to-date information on the products, their validation status and future enhancements, to help users utilize the data products through hands-on demonstrations, and to facilitate the integration of EOS products into models. Oral and poster sessions representing a wide variety of snow and ice topics were held; three panels were also convened to discuss workshop themes. Panel discussions focused on data fusion and assimilation of the products into models. Approximately 110 people attended, representing a wide array of interests and organizations in the cryospheric community. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2003EAEJA....12815H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2003EAEJA....12815H">Data sets for snow cover monitoring and modelling from the National Snow and Ice Data Center</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Holm, M.; Daniels, K.; Scott, D.; McLean, B.; Weaver, R. 2003-04-01 A wide range of snow cover monitoring and modelling data sets are pending or are currently available from the National Snow and Ice Data Center (NSIDC). In-situ observations support validation experiments that enhance the accuracy of remote sensing data. In addition, remote sensing data are available in near-real time, providing coarse-resolution snow monitoring capability. Time series data beginning in 1966 are valuable for modelling efforts. NSIDC holdings include SMMR and SSM/I snow cover data, MODIS snow cover extent products, in-situ and satellite data collected for NASA's recent Cold Land Processes Experiment, and soon-to-be-released ASMR-E passive microwave products. The AMSR-E and MODIS sensors are part of NASA's Earth Observing System flying on the Terra and Aqua satellites Characteristics of these NSIDC-held data sets, appropriateness of products for specific applications, and data set access and availability will be presented. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C53B0775Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C53B0775Y">Derive Arctic Sea-ice Freeboard and Thickness from NASA's LVIS Observations</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Yi, D.; Hofton, M. A.; Harbeck, J.; Cornejo, H.; Kurtz, N. T. 2015-12-01 The sea-ice freeboard and thickness are derived from the six sea-ice flights of NASA's IceBridge Land, Vegetation, and Ice Sensor (LVIS) over the Arctic from 2009 to 2013. The LVIS is an airborne scanning laser altimeter. It can operate at an altitude up to 10 km above the ground and produce a data swath up to 2 km wide with 20-m wide footprints. The laser output wavelength is 1064 nm and pulse repetition rate is 1000 Hz. The LVIS L2 geolocated surface elevation product and Level-1b waveform product (http://nsidc.org/data/ilvis2.html and http://nsidc.org/data/ilvis1b.html) at National Snow and Ice Data Center, USA (NSIDC) are used in this study. The elevations are referenced to a geoid with tides and dynamic atmospheric corrections applied. The LVIS waveforms were fitted with Gaussian curves to calculate pulse width, peak location, pulse amplitude, and signal baseline. For each waveform, the centroid, skewness, kurtosis, and pulse area were also calculated. The waveform parameters were calibrated based on laser off pointing angle and laser channels. Calibrated LVIS waveform parameters show a coherent response to variations in surface features along their ground tracks. These parameters, combined with elevation, can be used to identify leads, enabling the derivation of sea-ice freeboard and thickness without relying upon visual images. Preliminary results show that the elevations in some of the LVIS campaigns may vary with laser incident angle; this can introduce an elevation bias if not corrected. Further analysis of the LVIS data shown that the laser incident angle related elevation bias can be removed empirically. The sea-ice freeboard and thickness results from LVIS are compared with NASA's Airborne Topographic Mapper (ATM) for an April 20, 2010 flight, when both LVIS and ATM sensors were on the same aircraft and made coincidental measurements along repeat ground tracks. </li> <li> <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">Ice and AIS: ship speed data and sea ice forecasts in the Baltic Sea</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Löptien, U.; Axell, L. 2014-07-01 The Baltic Sea is a seasonally ice covered marginal sea located in a densely populated area in northern Europe. Severe sea ice conditions have the potential to hinder the intense ship traffic considerably. Thus, sea ice fore- and nowcasts are regularly provided by the national weather services. Typically, several ice 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 ice 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 ice 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. </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">22</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> <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">23</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> <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">SIPEX--Exploring the Antarctic Sea Ice Zone</a> <a target="_blank" href="http://www.eric.ed.gov/ERICWebPortal/search/extended.jsp?_pageLabel=advanced">ERIC Educational Resources Information Center</a> Zicus, Sandra; Dobson, Jane; Worby, Anthony 2008-01-01 Sea ice in the polar regions plays a key role in both regulating global climate and maintaining marine ecosystems. The international Sea Ice Physics and Ecosystem eXperiment (SIPEX) explored the sea ice zone around Antarctica in September and October 2007, investigating relationships between the physical sea ice environment and the structure of… </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C33B1187W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C33B1187W">Sea Ice in the NCEP Seasonal Forecast System</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Wu, X.; Saha, S.; Grumbine, R. W.; Bailey, D. A.; Carton, J.; Penny, S. G. 2017-12-01 Sea ice 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 sea ice is represented. Sea ice prediction is challenging; sea ice can form or melt, it can move with wind and/or ocean current; sea ice 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 sea ice model. In this work, we present the NCEP coupled model, the CFSv2 sea ice component that includes a dynamic thermodynamic sea ice model and a simple "assimilation" scheme, how sea ice has been assimilated in CFSR, the characteristics of the sea ice from CFSR and CFSv2, and the improvements of sea ice needed for future seasonal prediction system, part of the Unified Global Coupled System (UGCS), which is being developed and under testing, including sea ice data assimilation with the Local Ensemble Transform Kalman Filter (LETKF). Preliminary results from the UGCS testing will also be presented. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C33G..07L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C33G..07L">Investigating the Impact of Aerosol Deposition on Snow Melt over the Greenland Ice Sheet Using a New Kernel</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Li, Y.; Flanner, M. 2017-12-01 Accelerating surface melt on the Greenland Ice Sheet (GrIS) has led to a doubling of Greenland's contribution to global sea level rise during recent decades. The darkening effect due to black carbon (BC), dust, and other light absorbing impurities (LAI) enhances snow melt by boosting its absorption of solar energy. It is therefore important for coupled aerosol-climate and ice sheet models to include snow darkening effects from LAI, and yet most do not. In this study, we develop an aerosol deposition—snow melt kernel based on the Community Earth System Model (CESM) to investigate changes in melt flux due to variations in the amount and timing of aerosol deposition on the GrIS. The Community Land Model (CLM) component of CESM is driven with a large range of aerosol deposition fluxes to determine non-linear relationships between melt perturbation and deposition amount occurring in different months and location (thereby capturing variations in base state associated with elevation and latitude). The kernel product will include climatological-mean effects and standard deviations associated with interannual variability. Finally, the kernel will allow aerosol deposition fluxes from any global or regional aerosol model to be translated into surface melt perturbations of the GrIS, thus extending the utility of state-of-the-art aerosol models. </li> <li> <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">Iceberg in sea ice</a> <a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a> 2017-12-08 An iceberg embedded in sea ice as seen from the IceBridge DC-8 over the Bellingshausen Sea on Oct. 19, 2012. Credit: NASA / James Yungel NASA's Operation IceBridge is an airborne science mission to study Earth's polar ice. For more information about IceBridge, 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19930018948','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19930018948">Sea ice-atmospheric interaction: Application of multispectral satellite data in polar surface energy flux estimates</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Steffen, Konrad; Key, J.; Maslanik, J.; Schweiger, A. 1993-01-01 This is the third annual report on: Sea Ice-Atmosphere Interaction - Application of Multispectral Satellite Data in Polar Surface Energy Flux Estimates. The main emphasis during the past year was on: radiative flux estimates from satellite data; intercomparison of satellite and ground-based cloud amounts; radiative cloud forcing; calibration of the Advanced Very High Resolution Radiometer (AVHRR) visible channels and comparison of two satellite derived albedo data sets; and on flux modeling for leads. Major topics covered are arctic clouds and radiation; snow and ice albedo, and leads and modeling. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JGRC..121.7898K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JGRC..121.7898K">Winter ocean-ice interactions under thin sea ice observed by IAOOS platforms during N-ICE2015: Salty surface mixed layer and active basal melt</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Koenig, Zoé; Provost, Christine; Villacieros-Robineau, Nicolas; Sennéchael, Nathalie; Meyer, Amelie 2016-10-01 IAOOS (Ice Atmosphere Arctic Ocean Observing System) platforms, measuring physical parameters at the atmosphere-snow-ice-ocean interface deployed as part of the N-ICE2015 campaign, provide new insights on winter conditions North of Svalbard. The three regions crossed during the drifts, the Nansen Basin, the Sofia Deep, and the Svalbard northern continental slope featured distinct hydrographic properties and ice-ocean exchanges. In the Nansen Basin, the quiescent warm layer was capped by a stepped halocline (60 and 110 m) and a deep thermocline (110 m). Ice was forming and the winter mixed layer salinity was larger by ˜0.1 g/kg than previously observed. Over the Svalbard continental slope, the Atlantic Water (AW) was very shallow (20 m from the surface) and extended offshore from the 500 m isobath by a distance of about 70 km, sank along the slope (40 m from the surface) and probably shed eddies into the Sofia Deep. In the Sofia Deep, relatively warm waters of Atlantic origin extended from 90 m downward. Resulting from different pathways, these waters had a wide range of hydrographic characteristics. Sea-ice melt was widespread over the Svalbard continental slope and ocean-to-ice heat fluxes reached values of 400 W m-2 (mean of ˜150 W m-2 over the continental slope). Sea-ice melt events were associated with near 12 h fluctuations in the mixed-layer temperature and salinity corresponding to the periodicity of tides and near-inertial waves potentially generated by winter storms, large barotropic tides over steep topography, and/or geostrophic adjustments. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C11C0929S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C11C0929S">Collaborations for Arctic Sea Ice Information and Tools</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Sheffield Guy, L.; Wiggins, H. V.; Turner-Bogren, E. J.; Rich, R. H. 2017-12-01 The dramatic and rapid changes in Arctic sea ice 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 sea ice knowledge. Sea Ice 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 sea ice conditions relevant to walrus in the northern Bering and southern Chukchi seas. Collaboration among scientists, Alaskan Native sea-ice experts, and the Eskimo Walrus Commission is fundamental to this project's success. Sea Ice Prediction Network (SIPN: https://www.arcus.org/sipn) - A collaborative, multi-agency-funded project focused on seasonal Arctic sea ice predictions. The goals of SIPN include: coordinate and evaluate Arctic sea ice predictions; integrate, assess, and guide observations; synthesize predictions and observations; and disseminate predictions and engage key stakeholders. The Sea Ice Outlook—a key activity of SIPN—is an open process to share and synthesize predictions of the September minimum Arctic sea ice extent and other variables. Other SIPN activities include workshops, webinars, and communications across the network. Directory of Sea Ice Experts (https://www.arcus.org/researchers) - ARCUS has undertaken a pilot project to develop a web-based directory of sea ice 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 sea ice. 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ERL....13c4008Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ERL....13c4008Z">Wind-sea surface temperature-sea ice relationship in the Chukchi-Beaufort Seas during autumn</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Zhang, Jing; Stegall, Steve T.; Zhang, Xiangdong 2018-03-01 Dramatic climate changes, especially the largest sea ice retreat during September and October, in the Chukchi-Beaufort Seas could be a consequence of, and further enhance, complex air-ice-sea interactions. To detect these interaction signals, statistical relationships between surface wind speed, sea surface temperature (SST), and sea ice 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 sea ice, with a negative correlation over open water but a positive correlation in sea ice dominated areas. The examination of spatial structures indicates that wind speed tends to increase when approaching the ice edge from open water and the area fully covered by sea ice. 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. </li> <li> <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">Canadian Arctic sea ice reconstructed from bromine in the Greenland NEEM ice core.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> 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 2016-09-21 Reconstructing the past variability of Arctic sea ice provides an essential context for recent multi-year sea ice 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, sea ice in so-called "bromine explosions" and we employ a 1-D chemistry transport model to quantify processes of bromine enrichment over first-year sea ice and depositional transport over multi-year sea ice and land ice. We report bromine enrichment in the Northwest Greenland Eemian NEEM ice core since the end of the Eemian interglacial 120,000 years ago, finding the maximum extension of first-year sea ice occurred approximately 9,000 years ago during the Holocene climate optimum, when Greenland temperatures were 2 to 3 °C above present values. First-year sea ice extent was lowest during the glacial stadials suggesting complete coverage of the Arctic Ocean by multi-year sea ice. These findings demonstrate a clear relationship between temperature and first-year sea ice extent in the Arctic and suggest multi-year sea ice 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1811086D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1811086D">Atmospheric forcing of sea ice anomalies in the Ross Sea Polynya region</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Dale, Ethan; McDonald, Adrian; Rack, Wolfgang 2016-04-01 Despite warming trends in global temperatures, sea ice extent in the southern hemisphere has shown an increasing trend over recent decades. Wind-driven sea ice export from coastal polynyas is an important source of sea ice production. Areas of major polynyas in the Ross Sea, the region with largest increase in sea ice extent, have been suggested to produce the vast amount of the sea ice in the region. We investigate the impacts of strong wind events on polynyas and the subsequent sea ice production. We utilize Bootstrap sea ice 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 Sea region. We found that persistent weak winds near the edge of the Ross Ice Shelf are generally associated with positive SIC anomalies in the Ross Sea polynya area (RSP). Conversely we found negative SIC anomalies in this area during persistent strong winds. By analyzing sea ice motion vectors derived from SSM/I brightness temperatures, we find significant sea ice motion anomalies throughout the Ross Sea 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 sea ice 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 Sea ice motion anomalies, highlighting the production </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2005AGUFM.A31C..05F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2005AGUFM.A31C..05F">Dirty Snow, Atmospheric Warming, and Climate Feedbacks from Boreal Black Carbon Emissions</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Flanner, M. G.; Zender, C. S.; Randerson, J. T.; Jin, Y. 2005-12-01 Black carbon (BC) emitted from boreal fires darkens snow and sea-ice surfaces, increases solar absorption in the atmosphere, and decreases the incident flux at the surface. Although global surface forcing of darkened snow/ice is small relative to atmospheric forcing, the former directly triggers ice-albedo feedback, whereas the latter directly alters the atmospheric lapse rate. This highlights the importance of examining climate feedback strength as well as instantaneous forcings. We used a coupled land-atmosphere GCM (NCAR CAM3) to compare the relative forcings and climate feedbacks of BC emitted from a suite of boreal forest fires over the last decade, accounting for both enhanced snow/ice and atmospheric absorption by BC. The net change in absorbed energy at the surface was about three times greater than the instantaneous surface forcing when BC interactively heated the snow. Timing and location of fires determined the magnitude of darkened snow/ice feedback potential. We also assessed climate feedback strength from BC emitted globally during extreme high and low fire years, including the 1998 fire season. </li> <li> <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">Loss of sea ice in the Arctic.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Perovich, Donald K; Richter-Menge, Jacqueline A 2009-01-01 The Arctic sea ice cover is in decline. The areal extent of the ice cover has been decreasing for the past few decades at an accelerating rate. Evidence also points to a decrease in sea ice thickness and a reduction in the amount of thicker perennial sea ice. A general global warming trend has made the ice cover more vulnerable to natural fluctuations in atmospheric and oceanic forcing. The observed reduction in Arctic sea ice is a consequence of both thermodynamic and dynamic processes, including such factors as preconditioning of the ice cover, overall warming trends, changes in cloud coverage, shifts in atmospheric circulation patterns, increased export of older ice out of the Arctic, advection of ocean heat from the Pacific and North Atlantic, enhanced solar heating of the ocean, and the ice-albedo feedback. The diminishing Arctic sea ice is creating social, political, economic, and ecological challenges. </li> <li> <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">Ice2sea - the future glacial contribution to sea-level rise</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Vaughan, D. G.; Ice2sea Consortium 2009-04-01 The melting of continental ice (glaciers, ice caps and ice sheets) is a substantial source of current sea-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 sea-level rise is dominated by uncertainty concerning continental ice, and that understanding of the key processes that will lead to loss of continental ice must be improved before reliable projections of sea-level rise can be produced. Such projections are urgently required for effective sea-defence management and coastal adaptation planning. Ice2sea 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 sea-level rise. This includes improving understanding of the processes that control, past, current and future sea-level rise, and generation of improved estimates of the contribution of glacial components to sea-level rise over the next 200 years. The programme will include targeted studies of key processes in mountain glacier systems and ice caps (e.g. Svalbard), and in ice 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 ice-sheet model. Ice2sea 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 sea-level rise, and to leave a legacy of improved tools and techniques that will form the basis of ongoing refinements in sea-level projection. Ice2sea will provide exciting opportunities for many </li> <li> <a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70193280','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70193280">Drivers and environmental responses to the changing annual snow cycle of northern Alaska</a> <a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Cox, Christopher J.; Stone, Robert S.; Douglas, David C.; Stanitski, Diane; Divoky, George J.; Dutton, Geoff S.; Sweeney, Colm; George, J. Craig; Longenecker, David U. 2017-01-01 On the North Slope of Alaska, earlier spring snowmelt and later onset of autumn snow accumulation are tied to atmospheric dynamics and sea ice conditions, and result in environmental responses.Linkages between atmospheric, ecological and biogeochemical variables in the changing Arctic are analyzed using long-term measurements near Utqiaġvik (formerly Barrow), Alaska. Two key variables are the date when snow disappears in spring, as determined primarily by atmospheric dynamics, precipitation, air temperature, winter snow accumulation and cloud cover, as well as the date of onset of snowpack in autumn that is additionally influenced by ocean temperature and sea ice extent. In 2015 and 2016 the snow melted early at Utqiaġvik due mainly to anomalous warmth during May of both years attributed to atmospheric circulation patterns, with 2016 having the record earliest snowmelt. These years are discussed in the context of a 115-year snowmelt record at Utqiaġvik with a trend toward earlier melting since the mid- 1970s (-2.86 days/decade, 1975-2016). At nearby Cooper Island, where a colony of seabirds, Black Guillemots, have been monitored since 1975, timing of egg laying is correlated with Utqiaġvik snowmelt with 2015 and 2016 being the earliest years in the 42-year record. Ice-out at a nearby freshwater lagoon is also correlated with Utqiaġvik snowmelt. The date when snow begins to accumulate in autumn at Utqiaġvik shows a trend towards later dates (+4.6 days/decade, 1975-2016), with 2016 the latest on record. The relationships between the lengthening snow-free season and regional phenology, soil temperatures, fluxes of gases from the tundra, and to regional sea ice conditions are discussed. Better understanding of these interactions is needed to predict the annual snow cycles in the region at seasonal to decadal scales, and to anticipate coupled environmental responses. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA629258','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA629258">Passive Polarimetric Remote Sensing of Snow and Ice</a> <a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a> 1997-09-30 In recent years, polarimetric radiometry has shown great potential to revolutionize passive remote sensing of the ocean surface. As a result, several...polarimetric radiometer, in 2001. This project explores the possibility of applying this new technology to remote sensing in the Polar Regions by investigating the polarimetric signature of ice and snow. </li> <li> <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">Ice in Caspian Sea and Aral Sea, Kazakhstan</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 2002-01-01 In this MODIS image from December 3, 2001, winter sea ice can be seen forming in the shallow waters of the northern Caspian (left) and Aral (upper right) Seas. Despite the inflow of the Volga River (upper left), the northern portion of the Caspian Sea 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 Sea is deeper and remains ice-free throughout the winter. The dirty appearance of the ice 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 ice to pile up in hummocks that are anchored to the sea bottom. The eastern portion of the Aral Sea is also beginning to freeze. At least two characteristics of the Aral Sea 'compete' in determining whether its waters will freeze. The Sea 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 ice to form. As the waters that feed the Aral Sea continue to be diverted for agriculture, the Sea 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 </li> <li> <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">Clouds Over Sea Ice</a> <a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a> 2012-11-01 Low-lying clouds over sea ice on the Bellingshausen Sea. Credit: NASA / Maria-Jose Vinas NASA's Operation IceBridge is an airborne science mission to study Earth's polar ice. For more information about IceBridge, 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2892304','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2892304">Contribution of mycosporine-like amino acids and colored dissolved and particulate matter to sea ice optical properties and ultraviolet attenuation</a> <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Uusikivi, Jari; Vähätalo, Anssi V.; Granskog, Mats A.; Sommaruga, Ruben 2010-01-01 In the Baltic Sea ice, the spectral absorption coefficients for particulate matter (PM) were about two times higher at ultraviolet wavelengths than at photosynthetically available radiation (PAR) wavelengths. PM absorption spectra included significant absorption by mycosporine-like amino acids (MAAs) between 320 and 345 nm. In the surface ice layer, the concentration of MAAs (1.37 μg L−1) was similar to that of chlorophyll a, resulting in a MAAs-to-chlorophyll a ratio as high as 0.65. Ultraviolet radiation (UVR) intensity and the ratio of UVR to PAR had a strong relationship with MAAs concentration (R2 = 0.97, n = 3) in the ice. In the surface ice layer, PM and especially MAAs dominated the absorption (absorption coefficient at 325 nm: 0.73 m−1). In the columnar ice layers, colored dissolved organic matter was the most significant absorber in the UVR (< 380 nm) (absorption coefficient at 325 nm: 1.5 m−1). Our measurements and modeling of UVR and PAR in Baltic Sea ice show that organic matter, both particulate and dissolved, influences the optical properties of sea ice and strongly modifies the UVR exposure of biological communities in and under snow-free sea ice. PMID:20585592 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19990025392','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19990025392">Satellite Detection of Smoke Aerosols Over a Snow/Ice Surface by TOMS</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Hsu, N. Christina; Herman, Jay R.; Gleason, J. F.; Torres, O.; Seftor, C. J. 1998-01-01 The use of TOMS (Total Ozone Mapping Spectrometer) satellite data demonstrates the recently developed technique of using satellite UV radiance measurements to detect absorbing tropospheric aerosols is effective over snow/ice surfaces. Instead of the traditional single wavelength (visible or infrared) method of measuring tropospheric aerosols, this method takes advantage of the wavelength dependent reduction in the backscattered radiance due to the presence of absorbing aerosols over snow/ice surfaces. An example of the resulting aerosol distribution derived from TOMS data is shown for an August 1998 event in which smoke generated by Canadian forest fires drifts over and across Greenland. As the smoke plume moved over Greenland, the TOMS observed 380 nm reflectivity over the snow/ice surface dropped drastically from 90-100% down to 30-40%. To study the effects of this smoke plume in both the UV and visible regions of the spectrum, we compared a smoke-laden spectrum taken over Greenland by the high spectral resolution (300 to 800 nm) GOME instrument with one that is aerosol-free. We also discuss the results of modeling the darkening effects of various types of absorbing aerosols over snow/ice surfaces using a radiative transfer code. Finally, we investigated the history of such events by looking at the nearly twenty year record of TOMS aerosol index measurements and found that there is a large interannual variability in the amount of smoke aerosols observed over Greenland. This information will be available for studies of radiation and transport properties in the Arctic. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ACP....18.4981G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ACP....18.4981G">Concentrations and source regions of light-absorbing particles in snow/ice in northern Pakistan and their impact on snow albedo</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Gul, Chaman; Praveen Puppala, Siva; Kang, Shichang; Adhikary, Bhupesh; Zhang, Yulan; Ali, Shaukat; Li, Yang; Li, Xiaofei 2018-04-01 Black carbon (BC), water-insoluble organic carbon (OC), and mineral dust are important particles in snow and ice which significantly reduce albedo and accelerate melting. Surface snow and ice samples were collected from the Karakoram-Himalayan region of northern Pakistan during 2015 and 2016 in summer (six glaciers), autumn (two glaciers), and winter (six mountain valleys). The average BC concentration overall was 2130 ± 1560 ng g-1 in summer samples, 2883 ± 3439 ng g-1 in autumn samples, and 992 ± 883 ng g-1 in winter samples. The average water-insoluble OC concentration overall was 1839 ± 1108 ng g-1 in summer samples, 1423 ± 208 ng g-1 in autumn samples, and 1342 ± 672 ng g-1 in winter samples. The overall concentration of BC, OC, and dust in aged snow samples collected during the summer campaign was higher than the concentration in ice samples. The values are relatively high compared to reports by others for the Himalayas and the Tibetan Plateau. This is probably the result of taking more representative samples at lower elevation where deposition is higher and the effects of ageing and enrichment are more marked. A reduction in snow albedo of 0.1-8.3 % for fresh snow and 0.9-32.5 % for aged snow was calculated for selected solar zenith angles during daytime using the Snow, Ice, and Aerosol Radiation (SNICAR) model. The daily mean albedo was reduced by 0.07-12.0 %. The calculated radiative forcing ranged from 0.16 to 43.45 W m-2 depending on snow type, solar zenith angle, and location. The potential source regions of the deposited pollutants were identified using spatial variance in wind vector maps, emission inventories coupled with backward air trajectories, and simple region-tagged chemical transport modeling. Central, south, and west Asia were the major sources of pollutants during the sampling months, with only a small contribution from east Asia. Analysis based on the Weather Research and Forecasting (WRF-STEM) chemical transport model identified a </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">23</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> <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">24</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> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20010037604','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20010037604">Satellite Remote Sensing: Passive-Microwave Measurements of Sea Ice</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Parkinson, Claire L.; Zukor, Dorothy J. (Technical Monitor) 2001-01-01 Satellite passive-microwave measurements of sea ice have provided global or near-global sea ice 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 sea ice concentrations (percent areal coverages), sea ice extents, the length of the sea ice season, sea ice temperatures, and sea ice velocities, and to determine the timing of the seasonal onset of melt as well as aspects of the ice-type composition of the sea ice cover. In each case, the calculations are based on the microwave emission characteristics of sea ice and the important contrasts between the microwave emissions of sea ice and those of the surrounding liquid-water medium. </li> <li> <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">Sensitivity of open-water ice growth and ice concentration evolution in a coupled atmosphere-ocean-sea ice model</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Shi, Xiaoxu; Lohmann, Gerrit 2017-09-01 A coupled atmosphere-ocean-sea ice model is applied to investigate to what degree the area-thickness distribution of new ice formed in open water affects the ice and ocean properties. Two sensitivity experiments are performed which modify the horizontal-to-vertical aspect ratio of open-water ice growth. The resulting changes in the Arctic sea-ice concentration strongly affect the surface albedo, the ocean heat release to the atmosphere, and the sea-ice production. The changes are further amplified through a positive feedback mechanism among the Arctic sea ice, the Atlantic Meridional Overturning Circulation (AMOC), and the surface air temperature in the Arctic, as the Fram Strait sea ice import influences the freshwater budget in the North Atlantic Ocean. Anomalies in sea-ice transport lead to changes in sea 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-sea ice model with an unstructured mesh and multi-resolution. We find that the subpolar sea-ice boundary in the Northern Hemisphere can be improved by tuning the process of open-water ice growth, which strongly influences the sea ice concentration in the marginal ice zone, the North Atlantic circulation, salinity and Arctic sea ice volume. Since the distribution of new ice 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 sea ice growth which could significantly affect the climate system sensitivity. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMOS43B2035W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMOS43B2035W">Biogeochemical Coupling between Ocean and Sea Ice</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Wang, S.; Jeffery, N.; Maltrud, M. E.; Elliott, S.; Wolfe, J. 2016-12-01 Biogeochemical processes in ocean and sea ice are tightly coupled at high latitudes. Ongoing changes in Arctic and Antarctic sea ice 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 sea ice 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 sea ice biogeochemical module has recently been incorporated into the sea ice 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 sea ice. The coupling of ocean and sea ice biology-chemistry will enable representation of key processes such as the release of important climate active constituents or seeding algae from melting sea ice into surface waters. Sensitivity tests suggest sea ice and ocean biogeochemical coupling influences phytoplankton competition, biological production, and the CO2 flux. Sea ice 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 sea ice-ocean BGC system to physical changes in polar climate. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFM.A22A..08H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFM.A22A..08H">The Global Radiative Impact of the Sea-Ice-Albedo Feedback in the Arctic</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Hudson, S. R. 2009-12-01 The sea-ice-albedo feedback is known to be an important element of climatic changes over and near regions of ocean with ice cover. It is one of several feedbacks that lead to the polar enhancement of observed and projected global warming. Many studies in the past have used climate models to look at the regional and global impact of the albedo feedback on specific climate variables, most often temperature. These studies generally report a strong regional effect, but also some global effects due to the feedback. Recent changes in Arctic sea ice have led to increased reference to the importance of the sea-ice-albedo feedback, but few studies have examined the global impact of the feedback specifically associated with changes to sea ice in the Arctic; most have included changes to sea ice in both hemispheres, and in many cases, also to snow. That reduced sea ice cover will have a local warming effect is clear from modeling studies. On the other hand, given the relatively small area of the globe that is covered by Arctic sea ice, and the relatively small amounts of sunlight incident on these areas annually, it should be investigated how important reductions in sea ice are to the global solar radiation budget. In this study I present calculations of the global radiative impact of the reduction in Earth’s albedo resulting from reduced sea-ice cover in the Arctic. The intended result is a number, in W m-2, that represents the total increase in absorbed solar radiation due to the reduction in Arctic sea-ice cover, averaged over the globe and over the year. This number is relevant to assessing the long-term, global importance of the sea-ice-albedo feedback to climate change, and can help put it into context by allowing a comparison of this radiative forcing with other forcings, such as those due to CO2 increases and to aerosols, as given in Figure SPM.2 from the IPCC AR4 WG1. Rather than try to determine this forcing with a model, in which the assumptions and </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1248935','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1248935">Norwegian Young Sea Ice Experiment (N-ICE) Field Campaign Report</a> <a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Walden, V. P.; Hudson, S. R.; Cohen, L. The Norwegian Young Sea Ice (N-ICE) 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 sea ice. This includes understanding of how different components of the Arctic system affect sea ice, but also how changing sea ice 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, ice or mixed) of the lower-level clouds over the sea ice. Data obtained from the MPL during the N-ICE experiment show large cloud fractions over young, thin Arctic sea ice 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 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20010100393','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20010100393">Variability of Antarctic Sea Ice 1979-1998</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Zwally, H. Jay; Comiso, Josefino C.; Parkinson, Claire L.; Cavalieri, Donald J.; Gloersen, Per; Koblinsky, Chester J. (Technical Monitor) 2001-01-01 The principal characteristics of the variability of Antarctic sea ice 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 sea ice extent (concentration > 15 %) increased by 13,440 +/- 4180 sq km/year (+1.18 +/- 0.37%/decade). The area of sea ice 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 Sea (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 Seas sector (-9.5 +/- 1.5%/decade). For the entire ice pack, small ice 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 Seas sector. During winter and spring, the trends are negative or near zero in all sectors except the Ross Sea, 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 ice pack. The interannual variability of the annual mean sea-ice extent is only 1.6% overall, compared to 5% to 9% in each of five regional sectors. Analysis of the relation between regional sea ice extents and spatially-averaged surface temperatures over the ice pack gives an overall sensitivity between winter ice cover and temperature of -0.7% change in sea ice extent per K. For summer, some regional ice extents vary positively with temperature and others negatively. The observed increase in Antarctic sea ice cover is counter to the observed decreases in the Arctic. It is also qualitatively consistent with the </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24429521','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24429521">Convective forcing of mercury and ozone in the Arctic boundary layer induced by leads in sea ice.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Moore, Christopher W; Obrist, Daniel; Steffen, Alexandra; Staebler, Ralf M; Douglas, Thomas A; Richter, Andreas; Nghiem, Son V 2014-02-06 The ongoing regime shift of Arctic sea ice from perennial to seasonal ice is associated with more dynamic patterns of opening and closing sea-ice leads (large transient channels of open water in the ice), which may affect atmospheric and biogeochemical cycles in the Arctic. Mercury and ozone are rapidly removed from the atmospheric boundary layer during depletion events in the Arctic, caused by destruction of ozone along with oxidation of gaseous elemental mercury (Hg(0)) to oxidized mercury (Hg(II)) in the atmosphere and its subsequent deposition to snow and ice. Ozone depletion events can change the oxidative capacity of the air by affecting atmospheric hydroxyl radical chemistry, whereas atmospheric mercury depletion events can increase the deposition of mercury to the Arctic, some of which can enter ecosystems during snowmelt. Here we present near-surface measurements of atmospheric mercury and ozone from two Arctic field campaigns near Barrow, Alaska. We find that coastal depletion events are directly linked to sea-ice dynamics. A consolidated ice cover facilitates the depletion of Hg(0) and ozone, but these immediately recover to near-background concentrations in the upwind presence of open sea-ice leads. We attribute the rapid recoveries of Hg(0) and ozone to lead-initiated shallow convection in the stable Arctic boundary layer, which mixes Hg(0) and ozone from undepleted air masses aloft. This convective forcing provides additional Hg(0) to the surface layer at a time of active depletion chemistry, where it is subject to renewed oxidation. Future work will need to establish the degree to which large-scale changes in sea-ice dynamics across the Arctic alter ozone chemistry and mercury deposition in fragile Arctic ecosystems. </li> <li> <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">The interaction between sea ice and salinity-dominated ocean circulation: implications for halocline stability and rapid changes of sea ice cover</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Jensen, Mari F.; Nilsson, Johan; Nisancioglu, Kerim H. 2016-11-01 Changes in the sea ice cover of the Nordic Seas 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 sea ice and oceanic heat and freshwater transports affect the stability of an upper-ocean halocline in a semi-enclosed basin. The model represents a sea ice covered and salinity stratified Nordic Seas, and consists of a sea ice component and a two-layer ocean. The sea ice thickness depends on the atmospheric energy fluxes as well as the ocean heat flux. We introduce a thickness-dependent sea ice export. Whether sea ice 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 sea ice acts as a positive feedback on a freshwater perturbation. If the diapycnal flow decreases with density differences, the sea ice 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 sea ice. In addition to low freshwater forcing, increasing deep-ocean temperatures promote instability and the disappearance of sea ice. 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 sea ice. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C51E..02K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C51E..02K">The self-organization of snow surfaces and the growth of sastrugi</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Kochanski, K.; Bertholet, C.; Anderson, R. S.; Tucker, G. E. 2017-12-01 Seasonal snow covers approximately 15% of the surface of the Earth. The majority of this snow is found on tundra, ice sheets, and sea ice. These windswept snow surfaces self-organize into depositional bedforms, such as ripples, barchan dunes, and transverse waves, and erosional bedforms, such as anvil-shaped sastrugi. Previous researchers have shown that these bedforms influence the reflectivity, thermal conductivity, and aerodynamic roughness of the surface. For the past two winters, we have observed the growth and movement of snow bedforms on Niwot Ridge, Colorado, at an elevation of 3500m. We have observed that (1) when wind speeds are below 3m/s, snow surfaces can be smooth, (2) when winds are higher than 3m/s during and immediately following a storm, the smooth surface is unstable and self-organizes into a field of dunes, (3) as snow begins to harden, it forms erosional bedforms that are characterized by vertical edges facing upwind (4) between 12 and 48 hours after each snowfall, alternating stripes of erosional and depositional bedforms occur, and (5) within 60 hours of each storm, the surface self-organizes into a field of sastrugi, which remains stable until it melts or becomes buried by the next snowfall. Polar researchers should therefore expect snow-covered surfaces to be characterized by fields of bedforms, which evolve in response to variations in snow delivery, windspeed, and periods of sintering. Smooth drifts may be found in sheltered and forested regions. On most ice sheets and sea ice where snowfall is frequent, the typical surface is likely to consist of an evolving mix of depositional and erosional bedforms. Where snowfall is infrequent, for example in Antarctica, the surface will be dominated by sastrugi fields. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C51A0965H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C51A0965H">Sea Ice Mass Reconciliation Exercise (SIMRE) for altimetry derived sea ice thickness data sets</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Hendricks, S.; Haas, C.; Tsamados, M.; Kwok, R.; Kurtz, N. T.; Rinne, E. J.; Uotila, P.; Stroeve, J. 2017-12-01 Satellite altimetry is the primary remote sensing data source for retrieval of Arctic sea-ice 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 Sea Ice Mass Reconciliation Exercise (SIMRE) is a project by the sea-ice 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 sea ice 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 ice thickness estimates. Three regions representative of first-year ice, multiyear ice and mixed ice 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 sea ice thickness will be added in a later phase of the project to extend the scope of SIMRE beyond EO products. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20010124074','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20010124074">The Potential of Using Landsat 7 Data for the Classification of Sea Ice Surface Conditions During Summer</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Markus, Thorsten; Cavalieri, Donald J.; Ivanoff, Alvaro; Koblinsky, Chester J. (Technical Monitor) 2001-01-01 During spring and summer, the Surface of the Arctic sea ice cover undergoes rapid changes that greatly affect the surface albedo and significantly impact the further decay of the sea ice. These changes are primarily the development of a wet snow cover and the development of melt ponds. As melt pond diameters generally do not exceed a couple of meters, the spatial resolutions of sensors like AVHRR and MODIS are too coarse for their identification. Landsat 7, on the other hand, has a spatial resolution of 30 m (15 m for the pan-chromatic band). The different wavelengths (bands) from blue to near-infrared offer the potential to distinguish among different surface conditions. Landsat 7 data for the Baffin Bay region for June 2000 have been analyzed. The analysis shows that different surface conditions, such as wet snow and meltponded areas, have different signatures in the individual Landsat bands. Consistent with in-situ albedo measurements, melt ponds show up as blueish whereas dry and wet ice have a white to gray appearance in the Landsat true-color image. These spectral differences enable the distinction of melt ponds. The melt pond fraction for the scene studied in this paper was 37%. </li> <li> <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">The EUMETSAT sea ice concentration climate data record</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Tonboe, Rasmus T.; Eastwood, Steinar; Lavergne, Thomas; Sørensen, Atle M.; Rathmann, Nicholas; Dybkjær, Gorm; Toudal Pedersen, Leif; Høyer, Jacob L.; Kern, Stefan 2016-09-01 An Arctic and Antarctic sea ice area and extent dataset has been generated by EUMETSAT's Ocean and Sea Ice 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 sea ice 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, sea ice, and water emission characteristics and inter-sensor differences/biases; and (3) a hybrid sea ice concentration algorithm using the Bristol algorithm over ice and the Bootstrap algorithm in frequency mode over open water. A new sea ice concentration uncertainty algorithm has been developed to estimate the spatial and temporal variability in sea ice concentration retrieval accuracy. A comparison to US National Ice Center sea ice charts from the Arctic and the Antarctic shows that ice concentrations are higher in the ice charts than estimated from the radiometer data at intermediate sea ice concentrations between open water and 100 % ice. The sea ice 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. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C41C0706G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C41C0706G">Potential Elevation Biases for Laser Altimeters from Subsurface Scattered Photons: Laboratory and Model Exploration of Green Light Scattering in Snow</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Greeley, A.; Neumann, T.; Markus, T.; Kurtz, N. T.; Cook, W. B. 2015-12-01 Existing visible light laser altimeters such as MABEL (Multiple Altimeter Beam Experimental Lidar) - a single photon counting simulator for ATLAS (Advanced Topographic Laser Altimeter System) on NASA's upcoming ICESat-2 mission - and ATM (Airborne Topographic Mapper) on NASA's Operation IceBridge mission provide scientists a view of Earth's ice sheets, glaciers, and sea ice with unprecedented detail. Precise calibration of these instruments is needed to understand rapidly changing parameters like sea ice freeboard and to measure optical properties of surfaces like snow covered ice sheets using subsurface scattered photons. Photons travelling into snow, ice, or water before scattering back to the altimeter receiving system (subsurface photons) travel farther and longer than photons scattering off the surface only, causing a bias in the measured elevation. We seek to identify subsurface photons in a laboratory setting using a flight-tested laser altimeter (MABEL) and to quantify their effect on surface elevation estimates for laser altimeter systems. We also compare these estimates with previous laboratory measurements of green laser light transmission through snow, as well as Monte Carlo simulations of backscattered photons from snow. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120009528','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120009528">Antarctic Sea Ice Variability and Trends, 1979-2010</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Parkinson, C. L.; Cavalieri, D. J. 2012-01-01 In sharp contrast to the decreasing sea ice coverage of the Arctic, in the Antarctic the sea ice 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 ice 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 Sea, with lesser contributions from the Weddell Sea and Indian Ocean. One region, that of the Bellingshausen/Amundsen Seas, has, like the Arctic, instead experienced significant sea ice decreases, with an overall ice 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 sea ice cover as a whole experienced positive ice 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 Sea and Indian Ocean also had positive trends in each month, while the Bellingshausen/Amundsen Seas had negative trends in each month, and the Weddell Sea and Western Pacific Ocean had a mixture of positive and negative trends. Comparing ice-area results to ice-extent results, in each case the ice-area trend has the same sign as the ice-extent trend, but differences in the magnitudes of the two trends identify regions with overall increasing ice concentrations and others with overall decreasing ice concentrations. The strong pattern of decreasing ice coverage in the Bellingshausen/Amundsen Seas region and increasing ice coverage in the Ross Sea region is suggestive of changes in atmospheric circulation. This is a key topic for future research. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016SPIE.9839E..0LC','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016SPIE.9839E..0LC">Mapping of ice, snow and water using aircraft-mounted LiDAR</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Church, Philip; Matheson, Justin; Owens, Brett 2016-05-01 Neptec Technologies Corp. has developed a family of obscurant-penetrating 3D laser scanners (OPAL 2.0) that are being adapted for airborne platforms for operations in Degraded Visual Environments (DVE). The OPAL uses a scanning mechanism based on the Risley prism pair. Data acquisition rates can go as high as 200kHz for ranges within 240m and 25kHz for ranges exceeding 240m. The scan patterns are created by rotating two prisms under independent motor control producing a conical Field-Of-View (FOV). An OPAL laser scanner with 90° FOV was installed on a Navajo aircraft, looking down through an aperture in the aircraft floor. The rotation speeds of the Risley prisms were selected to optimize a uniformity of the data samples distribution on the ground. Flight patterns simulating a landing approach over snow and ice in an unprepared Arctic environment were also performed to evaluate the capability of the OPAL LiDAR to map snow and ice elevation distribution in real-time and highlight potential obstacles. Data was also collected to evaluate the detection of wires when flying over water, snow and ice. Main results and conclusions obtained from the flight data analysis are presented. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUOSHE54B1584J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUOSHE54B1584J">The interaction between sea ice and salinity-dominated ocean circulation: implications for halocline stability and rapid changes of sea-ice cover</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Jensen, M. F.; Nilsson, J.; Nisancioglu, K. H. 2016-02-01 In this study, we develop a simple conceptual model to examine how interactions between sea ice and oceanic heat and freshwater transports affect the stability of an upper-ocean halocline in a semi-enclosed basin. The model represents a sea-ice covered and salinity stratified ocean, and consists of a sea-ice component and a two-layer ocean; a cold, fresh surface layer above a warmer, more saline layer. The sea-ice thickness depends on the atmospheric energy fluxes as well as the ocean heat flux. We introduce a thickness-dependent sea-ice export. Whether sea ice 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 sea ice acts as a positive feedback on a freshwater perturbation. If the vertical diffusivity is derived from a constant mixing energy constraint, the sea ice 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 sea ice. In addition to low freshwater forcing, increasing deep-ocean temperatures promote instability and the disappearance of sea ice. 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 sea ice. </li> <li> <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">Sea Ice Biogeochemistry: A Guide for Modellers</a> <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Tedesco, Letizia; Vichi, Marcello 2014-01-01 Sea ice is a fundamental component of the climate system and plays a key role in polar trophic food webs. Nonetheless sea ice 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 sea ice 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 sea ice 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 sea ice in the Arctic, the one currently needing the most urgent understanding. The aim is to (1) introduce sea ice biogeochemistry and address its relevance to ocean modelers of polar regions, supporting them in adding a new sea ice component to their modelling framework for a more adequate representation of the sea ice-covered ocean ecosystem as a whole, and (2) extend our knowledge on the relevant controlling factors of sea ice algal production, showing that beyond the light and nutrient availability, the duration of the sea ice season may play a key-role shaping the algal production during the on going and upcoming projected changes. PMID:24586604 </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C33D1232R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C33D1232R">The Contribution to High Asia Runoff from Ice and Snow (CHARIS): Understanding the source and trends of cryospheric contributions to the water balance</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Rittger, K.; Armstrong, R. L.; Bair, N.; Racoviteanu, A.; Brodzik, M. J.; Hill, A. F.; Wilson, A. M.; Khan, A. L.; Ramage, J. M.; Khalsa, S. J. S.; Barrett, A. P.; Raup, B. H.; Painter, T. H. 2017-12-01 The Contribution to High Asia Runoff from Ice and Snow, or CHARIS, project is systematically assessing the role that glaciers and seasonal snow play in the freshwater resources of Central and South Asia. The study area encompasses roughly 3 million square kilometers of the Himalaya, Karakoram, Hindu Kush, Pamir and Tien Shan mountain ranges that drain to five major rivers: the Ganges, Brahmaputra, Indus, Amu Darya and Syr Darya. We estimate daily snow and glacier ice contributions to the water balance. Our automated partitioning method generates daily maps of 1) snow over ice (SOI), 2) exposed glacier ice (EGI), 3) debris covered glacier ice (DGI) and 4) snow over land (SOL) using fractional snow cover, snow grain size, and annual minimum ice and snow from the 500 m MODIS-derived MODSCAG and MODICE products. Maps of snow and ice cover are validated using high-resolution (30 m) maps of snow, ice, and debris cover from Landsat. The probability of detection is 0.91 and precision is 0.85 for MODICE. We examine trends in annual and monthly snow and ice maps and use daily maps as inputs to a calibrated temperature-index model and an uncalibrated energy balance model, ParBal. Melt model results and measurements of isotopes and specific ions used as an independent validation of melt modeling indicate a sharp geographic contrast in the role of snow and ice melt to downstream water supplies between the arid Tien Shan and Pamir ranges of Central Asia, where melt water dominates dry season flows, and the monsoon influenced central and eastern Himalaya where rain controls runoff. We also compare melt onset and duration from the melt models to the Calibrated, Enhanced Resolution Passive Microwave Brightness Temperature Earth Science Data Record. Trend analysis of annual and monthly area of permanent snow and ice (the union of SOI and EGI) for 2000 to 2016 shows statistically significant negative trends in the Ganges and Brahmaputra basins. There are no statistically significant </li> <li> <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">Variational Ridging in Sea Ice Models</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Roberts, A.; Hunke, E. C.; Lipscomb, W. H.; Maslowski, W.; Kamal, S. 2017-12-01 This work presents the results of a new development to make basin-scale sea ice 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 sea ice 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 sea ice 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 sea ice models. We present results from this theoretical development, as well as plans to apply it to the Regional Arctic System Model and a community sea ice code. Most importantly, the new ridging model is particularly useful for pinpointing gaps in our observational record of sea ice ridges, and points to the need for improved measurements of the evolution of porosity of deformed ice in the Arctic and Antarctic. Such knowledge is not only useful for improving models, but also for improving estimates of sea ice volume derived from altimetric measurements of sea ice freeboard. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1235365','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1235365">Full-physics 3D heterogeneous simulations of electromagnetic induction fields on level and deformed sea ice</a> <a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Samluk, Jesse P.; Geiger, Cathleen A.; Weiss, Chester J. In this article we explore simulated responses of electromagnetic (EM) signals relative to in situ field surveys and quantify the effects that different values of conductivity in sea ice have on the EM fields. We compute EM responses of ice types with a three-dimensional (3-D) finite-volume discretization of Maxwell's equations and present 2-D sliced visualizations of their associated EM fields at discrete frequencies. Several interesting observations result: First, since the simulator computes the fields everywhere, each gridcell acts as a receiver within the model volume, and captures the complete, coupled interactions between air, snow, sea ice and sea water asmore » a function of their conductivity; second, visualizations demonstrate how 1-D approximations near deformed ice features are violated. But the most important new finding is that changes in conductivity affect EM field response by modifying the magnitude and spatial patterns (i.e. footprint size and shape) of current density and magnetic fields. These effects are demonstrated through a visual feature we define as 'null lines'. Null line shape is affected by changes in conductivity near material boundaries as well as transmitter location. Our results encourage the use of null lines as a planning tool for better ground-truth field measurements near deformed ice types.« less </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">24</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> <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">25</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> <a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1235365-full-physics-heterogeneous-simulations-electromagnetic-induction-fields-level-deformed-sea-ice','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1235365-full-physics-heterogeneous-simulations-electromagnetic-induction-fields-level-deformed-sea-ice">Full-physics 3D heterogeneous simulations of electromagnetic induction fields on level and deformed sea ice</a> <a target="_blank" href="http://www.osti.gov/pages">DOE PAGES</a> Samluk, Jesse P.; Geiger, Cathleen A.; Weiss, Chester J.; ... 2015-10-01 In this article we explore simulated responses of electromagnetic (EM) signals relative to in situ field surveys and quantify the effects that different values of conductivity in sea ice have on the EM fields. We compute EM responses of ice types with a three-dimensional (3-D) finite-volume discretization of Maxwell's equations and present 2-D sliced visualizations of their associated EM fields at discrete frequencies. Several interesting observations result: First, since the simulator computes the fields everywhere, each gridcell acts as a receiver within the model volume, and captures the complete, coupled interactions between air, snow, sea ice and sea water asmore » a function of their conductivity; second, visualizations demonstrate how 1-D approximations near deformed ice features are violated. But the most important new finding is that changes in conductivity affect EM field response by modifying the magnitude and spatial patterns (i.e. footprint size and shape) of current density and magnetic fields. These effects are demonstrated through a visual feature we define as 'null lines'. Null line shape is affected by changes in conductivity near material boundaries as well as transmitter location. Our results encourage the use of null lines as a planning tool for better ground-truth field measurements near deformed ice types.« less </li> <li> <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">NASA Science Flights Target Melting Arctic Sea Ice</a> <a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a> 2017-12-08 This summer, with sea ice across the Arctic Ocean shrinking to below-average levels, a NASA airborne survey of polar ice just completed its first flights. Its target: aquamarine pools of melt water on the ice surface that may be accelerating the overall sea ice retreat. NASA’s Operation IceBridge 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 sea ice 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 sea ice, as seen from an Operation IceBridge flight over the Beaufort Sea on July 14, 2016. During this summer campaign, IceBridge will map the extent, frequency and depth of melt ponds like these to help scientists forecast the Arctic sea ice yearly minimum extent in September. Credit: NASA/Operation IceBridge </li> <li> <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">Predicting September sea ice: Ensemble skill of the SEARCH Sea Ice Outlook 2008-2013</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Stroeve, Julienne; Hamilton, Lawrence C.; Bitz, Cecilia M.; Blanchard-Wrigglesworth, Edward 2014-04-01 Since 2008, the Study of Environmental Arctic Change Sea Ice Outlook has solicited predictions of September sea-ice 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 ice 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 ice, atmosphere and ocean conditions, and summer storms and weather in contributing to the challenge of sea-ice prediction. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA601522','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA601522">Multiscale Models of Melting Arctic Sea Ice</a> <a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a> 2013-09-30 September 29, 2013 LONG-TERM GOALS Sea ice reflectance or albedo , a key parameter in climate modeling, is primarily determined by melt pond...and ice floe configurations. Ice - albedo feedback has played a major role in the recent declines of the summer Arctic sea ice pack. However...understanding the evolution of melt ponds and sea ice albedo remains a significant challenge to improving climate models. Our research is focused on </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20170007842&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=20170007842&hterms=sea&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dsea">Comparison of Passive Microwave-Derived Early Melt Onset Records on Arctic Sea Ice</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Bliss, Angela C.; Miller, Jeffrey A.; Meier, Walter N. 2017-01-01 Two long records of melt onset (MO) on Arctic sea ice from passive microwave brightness temperatures (Tbs) obtained by a series of satellite-borne instruments are compared. The Passive Microwave (PMW) method and Advanced Horizontal Range Algorithm (AHRA) detect the increase in emissivity that occurs when liquid water develops around snow grains at the onset of early melting on sea ice. The timing of MO on Arctic sea ice influences the amount of solar radiation absorbed by the ice-ocean system throughout the melt season by reducing surface albedos in the early spring. This work presents a thorough comparison of these two methods for the time series of MO dates from 1979through 2012. The methods are first compared using the published data as a baseline comparison of the publically available data products. A second comparison is performed on adjusted MO dates we produced to remove known differences in inter-sensor calibration of Tbs and masking techniques used to develop the original MO date products. These adjustments result in a more consistent set of input Tbs for the algorithms. Tests of significance indicate that the trends in the time series of annual mean MO dates for the PMW and AHRA are statistically different for the majority of the Arctic Ocean including the Laptev, E. Siberian, Chukchi, Beaufort, and central Arctic regions with mean differences as large as 38.3 days in the Barents Sea. Trend agreement improves for our more consistent MO dates for nearly all regions. Mean differences remain large, primarily due to differing sensitivity of in-algorithm thresholds and larger uncertainties in thin-ice regions. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC44B..01P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC44B..01P">Sea Ice, Clouds, Sunlight, and Albedo: The Umbrella Versus the Blanket</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Perovich, D. K. 2017-12-01 The Arctic sea ice cover has undergone a major decline in recent years, with reductions in ice extent, ice thickness, and ice age. Understanding the feedbacks and forcing driving these changes is critical in improving predictions. The surface radiation budget plays a central role in summer ice melt and is governed by clouds and surface albedo. Clouds act as an umbrella reducing the downwelling shortwave, but also serve as a blanket increasing the downwelling longwave, with the surface albedo also determining the net balance. Using field observations from the SHEBA program, pairs of clear and cloudy days were selected for each month from May through September and the net radiation flux was calculated for different surface conditions and albedos. To explore the impact of albedo we calculated a break even albedo, where the net radiation for cloudy skies is the same as clear skies. For albedos larger than the break-even value the net radiation flux is smaller under clear skies compared to cloudy skies. Break-even albedos ranged from 0.30 in September to 0.58 in July. For snow covered or bare ice, clear skies always resulted in less radiative heat input. In contrast, leads always had, and ponds usually had, more radiative heat input under clear skies than cloudy skies. Snow covered ice had a net radiation flux that was negative or near zero under clear skies resulting in radiative cooling. We combined the albedo of individual ice types with the area of those ice types to calculate albedos averaged over a 50 km x 50 km area. The July case had the smallest areally averaged albedo of 0.50. This was less than the breakeven albedo, so cloudy skies had a smaller net radiation flux than clear skies. For the cases from the other four months, the areally averaged albedo was greater than the break-even albedo. The areally averaged net radiation flux was negative under clear skies for the May and September cases. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1990JGR....9513411C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1990JGR....9513411C">Arctic multiyear ice classification and summer ice cover using passive microwave satellite data</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Comiso, J. C. 1990-08-01 The ability to classify and monitor Arctic multiyear sea ice cover using multispectral passive microwave data is studied. Sea ice concentration maps during several summer minima have been analyzed to obtain estimates of ice surviving the summer. The results are compared with multiyear ice concentrations derived from data the following winter, using an algorithm that assumes a certain emissivity for multiyear ice. The multiyear ice cover inferred from the winter data is approximately 25 to 40% less than the summer ice cover minimum, suggesting that even during winter when the emissivity of sea ice is most stable, passive microwave data may account for only a fraction of the total multiyear ice cover. The difference of about 2×106 km2 is considerably more than estimates of advection through Fram Strait during the intervening period. It appears that as in the Antarctic, some multiyear ice floes in the Arctic, especially those near the summer marginal ice zone, have first-year ice or intermediate signatures in the subsequent winter. A likely mechanism for this is the intrusion of seawater into the snow-ice interface, which often occurs near the marginal ice zone or in areas where snow load is heavy. Spatial variations in melt and melt ponding effects also contribute to the complexity of the microwave emissivity of multiyear ice. Hence the multiyear ice data should be studied in conjunction with the previous summer ice data to obtain a more complete characterization of the state of the Arctic ice cover. The total extent and actual areas of the summertime Arctic pack ice were estimated to be 8.4×106 km2 and 6.2×106 km2, respectively, and exhibit small interannual variability during the years 1979 through 1985, suggesting a relatively stable ice cover. </li> <li> <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">Sea-ice eukaryotes of the Gulf of Finland, Baltic Sea, and evidence for herbivory on weakly shade-adapted ice algae.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Majaneva, Markus; Blomster, Jaanika; Müller, Susann; Autio, Riitta; Majaneva, Sanna; Hyytiäinen, Kirsi; Nagai, Satoshi; Rintala, Janne-Markus 2017-02-01 To determine community composition and physiological status of early spring sea-ice organisms, we collected sea-ice, slush and under-ice water samples from the Baltic Sea. We combined light microscopy, HPLC pigment analysis and pyrosequencing, and related the biomass and physiological status of sea-ice 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 ice, dinoflagellates, euglenoids and the cyanobacterium Aphanizomenon sp. predominated in the sea-ice sections and unidentified flagellates in the slush. Based on pigment analyses, the ice-algal communities showed no adjusted photosynthetic pigment pools throughout the sea ice, and the bottom-ice communities were not shade-adapted. The sea ice included more characteristic phototrophic taxa (49%) than did slush (18%) and under-ice 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 ice and with a high Eurytemora affinis read abundance in the pack ice, indicating that ciliates and Eurytemora affinis were grazing on algae. Copyright Â© 2016 Elsevier GmbH. All rights reserved. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-PIA02456.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-PIA02456.html">SeaWinds Wind-Ice Interaction</a> <a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a> 2000-05-07 The figure demonstrates of the capability of the SeaWinds instrument on NASA QuikScat satellite in monitoring both sea ice and ocean surface wind, thus helping to further our knowledge in wind-ice interaction and its effect on climate change. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=67188&keyword=LAKE+AND+ICE&actType=&TIMSType=+&TIMSSubTypeID=&DEID=&epaNumber=&ntisID=&archiveStatus=Both&ombCat=Any&dateBeginCreated=&dateEndCreated=&dateBeginPublishedPresented=&dateEndPublishedPresented=&dateBeginUpdated=&dateEndUpdated=&dateBeginCompleted=&dateEndCompleted=&personID=&role=Any&journalID=&publisherID=&sortBy=revisionDate&count=50','EPA-EIMS'); return false;" href="https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=67188&keyword=LAKE+AND+ICE&actType=&TIMSType=+&TIMSSubTypeID=&DEID=&epaNumber=&ntisID=&archiveStatus=Both&ombCat=Any&dateBeginCreated=&dateEndCreated=&dateBeginPublishedPresented=&dateEndPublishedPresented=&dateBeginUpdated=&dateEndUpdated=&dateBeginCompleted=&dateEndCompleted=&personID=&role=Any&journalID=&publisherID=&sortBy=revisionDate&count=50">ALBEDO MODELS FOR SNOW AND ICE ON A FRESHWATER LAKE. (R824801)</a> <a target="_blank" href="http://oaspub.epa.gov/eims/query.page">EPA Science Inventory</a> <h2>Abstract</h2>Snow and ice albedo measurements were taken over a freshwater lake in Minnesota for three months during the winter of 1996¯1997 for use in a winter lake water quality model. The mean albedo of new snow was measured as 0.83±0.028, while the... </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010JGRC..115.2005V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010JGRC..115.2005V">Modeling brine and nutrient dynamics in Antarctic sea ice: The case of dissolved silica</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Vancoppenolle, Martin; Goosse, Hugues; de Montety, Anne; Fichefet, Thierry; Tremblay, Bruno; Tison, Jean-Louis 2010-02-01 Sea ice ecosystems are characterized by microalgae living in brine inclusions. The growth rate of ice algae depends on light and nutrient supply. Here, the interactions between nutrients and brine dynamics under the influence of algae are investigated using a one-dimensional model. The model includes snow and ice thermodynamics with brine physics and an idealized sea ice biological component, characterized by one nutrient, namely, dissolved silica (DSi). In the model, DSi follows brine motion and is consumed by ice algae. Depending on physical ice characteristics, the brine flow is either advective, diffusive, or turbulent. The vertical profiles of ice salinity and DSi concentration are solutions of advection-diffusion equations. The model is configured to simulate the typical thermodynamic regimes of first-year Antarctic pack ice. The simulated vertical profiles of salinity and DSi qualitatively reproduce observations. Analysis of results highlights the role of convection in the lowermost 5-10 cm of ice. Convection mixes saline, nutrient-poor brine with comparatively fresh, nutrient-rich seawater. This implies a rejection of salt to the ocean and a flux of DSi to the ice. In the presence of growing algae, the simulated ocean-to-ice DSi flux increases by 0-115% compared to an abiotic situation. In turn, primary production and brine convection act in synergy to form a nutrient pump. The other important processes are the flooding of the surface by seawater and the percolation of meltwater. The former refills nutrients near the ice surface in spring. The latter, if present, tends to expell nutrients from the ice in summer. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20160010642&hterms=airborne&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dairborne','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20160010642&hterms=airborne&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dairborne">Annual Greenland Accumulation Rates (2009-2012) from Airborne Snow Radar</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Koenig, Lora S.; Ivanoff, Alvaro; Alexander, Patrick M.; MacGregor, Joseph A.; Fettweis, Xavier; Panzer, Ben; Paden, John D.; Forster, Richard R.; Das, Indrani; McConnell, Joseph R.; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_20160010642'); toggleEditAbsImage('author_20160010642_show'); toggleEditAbsImage('author_20160010642_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_20160010642_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_20160010642_hide"> 2016-01-01 Contemporary climate warming over the Arctic is accelerating mass loss from the Greenland Ice Sheet through increasing surface melt, emphasizing the need to closely monitor its surface mass balance in order to improve sea-level rise predictions. Snow accumulation is the largest component of the ice sheet's surface mass balance, but in situ observations thereof are inherently sparse and models are difficult to evaluate at large scales. Here, we quantify recent Greenland accumulation rates using ultra-wideband (2-6.5 gigahertz) airborne snow radar data collected as part of NASA's Operation IceBridge between 2009 and 2012. We use a semi-automated method to trace the observed radiostratigraphy and then derive annual net accumulation rates for 2009-2012. The uncertainty in these radar-derived accumulation rates is on average 14 percent. A comparison of the radarderived accumulation rates and contemporaneous ice cores shows that snow radar captures both the annual and longterm mean accumulation rate accurately. A comparison with outputs from a regional climate model (MAR - Modele Atmospherique Regional for Greenland and vicinity) shows that this model matches radar-derived accumulation rates in the ice sheet interior but produces higher values over southeastern Greenland. Our results demonstrate that snow radar can efficiently and accurately map patterns of snow accumulation across an ice sheet and that it is valuable for evaluating the accuracy of surface mass balance models. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AMT....10.3215E','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AMT....10.3215E">Combined retrieval of Arctic liquid water cloud and surface snow properties using airborne spectral solar remote sensing</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Ehrlich, André; Bierwirth, Eike; Istomina, Larysa; Wendisch, Manfred 2017-09-01 The passive solar remote sensing of cloud properties over highly reflecting ground is challenging, mostly due to the low contrast between the cloud reflectivity and that of the underlying surfaces (sea ice and snow). Uncertainties in the retrieved cloud optical thickness τ and cloud droplet effective radius reff, C may arise from uncertainties in the assumed spectral surface albedo, which is mainly determined by the generally unknown effective snow grain size reff, S. Therefore, in a first step the effects of the assumed snow grain size are systematically quantified for the conventional bispectral retrieval technique of τ and reff, C for liquid water clouds. In general, the impact of uncertainties of reff, S is largest for small snow grain sizes. While the uncertainties of retrieved τ are independent of the cloud optical thickness and solar zenith angle, the bias of retrieved reff, C increases for optically thin clouds and high Sun. The largest deviations between the retrieved and true original values are found with 83 % for τ and 62 % for reff, C. In the second part of the paper a retrieval method is presented that simultaneously derives all three parameters (τ, reff, C, reff, S) and therefore accounts for changes in the snow grain size. Ratios of spectral cloud reflectivity measurements at the three wavelengths λ1 = 1040 nm (sensitive to reff, S), λ2 = 1650 nm (sensitive to τ), and λ3 = 2100 nm (sensitive to reff, C) are combined in a trispectral retrieval algorithm. In a feasibility study, spectral cloud reflectivity measurements collected by the Spectral Modular Airborne Radiation measurement sysTem (SMART) during the research campaign Vertical Distribution of Ice in Arctic Mixed-Phase Clouds (VERDI, April/May 2012) were used to test the retrieval procedure. Two cases of observations above the Canadian Beaufort Sea, one with dense snow-covered sea ice and another with a distinct snow-covered sea ice edge are analysed. The retrieved values of τ, reff </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010cosp...38..279H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010cosp...38..279H">Determining and validating the effective snow grain size and pollution amount from satellite measurements in polar regions</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Heygster, Georg; Wiebe, Heidrun; Zege, Eleonora; Aoki, Teruo; Kokhanovsky, Alexander; Katsev, I. L.; Prikhach, Alexander; Malinka, A. V.; Grudo, J. O. Sea ice is part of the cryosphere, besides the ice sheets, ice shelves, and glaciers. Compared to the other components, it is small in volume but large in area. Snow on top of the sea ice is even less in mass, but strongly influences the albedo of the sea ice, and thus the local radiative balance which plays an essential role for the albedo feedback process. The albedo of snow does not have a constant value, but depends on the grain size (smaller grains have higher albedo) and the amount of pollution like soot and in fewer cases dust which both lower the albedo significantly. Our retrievals are based on an algorithm that uses optical satellite observations to calculate the size of the snow grains and its pollution, the Snow Grain Size and Pollution amount (SGSP) algorithm (Zege et al. 2009) Here we present the algorithm and its operational implementation, based on MODIS data, to calculate the snow grain size and pollution amount in near real time, and a destriping procedure. The resulting data are used for a validation study by comparing them to in situ data taken at several places near Hokkaido (Japan), Barrow (Alaska, USA) between 2002 and 2005 and in Antarctica in 2003. While each single set of observations, in the Arctic and in the Antarctic, shows encouraging correlations, the regression lines between in situ and satellite retrievals of the snow grain size are quite different, with slopes of 1.01 (Arctic and Japan) and 0.44 (Antarctica). The discrepancy remains unresolved, emphasizing the need for more in situ observations for validation. Among the potential reasons for the discrepancy are the different kinds of in situ measured snow grain sizes. The crystal size was measured in the Arctic (Barrow) and Japan (Hokkaido) using a lens and optical methods have been used in Antarctica. </li> <li> <a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2002AGUFMOS21B0197M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2002AGUFMOS21B0197M">Biologically-Oriented Processes in the Coastal Sea Ice Zone of the White Sea</a> <a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Melnikov, I. A. 2002-12-01 The annual advance and retreat of sea ice is a major physical determinant of spatial and temporal changes in the structure and function of marine coastal biological communities. Sea ice biological data obtained in the tidal zone of Kandalaksha Gulf (White Sea) during 1996-2001 period will be presented. Previous observations in this area were mainly conducted during the ice-free summer season. However, there is little information on the ice-covered winter season (6-7 months duration), and, especially, on the sea-ice 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 ice. Trends in the annual extent of sea ice showed significant impacts on ice-associated biological communities. Three types of sea ice impact on kelps, balanoides, littorinas and amphipods are distinguished: (i) positive, when sea ice protects these populations from grinding (ii) negative, when ice grinds both fauna and flora, and (iii) a combined effect, when fast ice protects, but anchored ice 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 sea ice melting caused by global warming, an integrated, long-term study of the physical, chemical, and biological processes is needed. </li> <li> <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">Proteorhodopsin-bearing bacteria in Antarctic sea ice.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Koh, Eileen Y; Atamna-Ismaeel, Nof; Martin, Andrew; Cowie, Rebecca O M; Beja, Oded; Davy, Simon K; Maas, Elizabeth W; Ryan, Ken G 2010-09-01 Proteorhodopsins (PRs) are widespread bacterial integral membrane proteins that function as light-driven proton pumps. Antarctic sea ice supports a complex community of autotrophic algae, heterotrophic bacteria, viruses, and protists that are an important food source for higher trophic levels in ice-covered regions of the Southern Ocean. Here, we present the first report of PR-bearing bacteria, both dormant and active, in Antarctic sea ice from a series of sites in the Ross Sea using gene-specific primers. Positive PR sequences were generated from genomic DNA at all depths in sea ice, 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 sea ice samples. This finding indicates that these sequences were generated from metabolically active cells and suggests that the PR gene is functional within sea ice. 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 sea ice 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 sea ice ecosystem. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70175240','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70175240">Arctic sea ice decline contributes to thinning lake ice trend in northern Alaska</a> <a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Alexeev, Vladimir; Arp, Christopher D.; Jones, Benjamin M.; Cai, Lei 2016-01-01 Field measurements, satellite observations, and models document a thinning trend in seasonal Arctic lake ice growth, causing a shift from bedfast to floating ice conditions. September sea ice 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 sea ice affects lakes, we conducted model experiments to simulate winters with years of high (1991/92) and low (2007/08) sea ice extent for which we also had field measurements and satellite imagery characterizing lake ice conditions. A lake ice growth model forced with Weather Research and Forecasting model output produced a 7% decrease in lake ice growth when 2007/08 sea ice was imposed on 1991/92 climatology and a 9% increase in lake ice growth for the opposing experiment. Here, we clearly link early winter 'ocean-effect' snowfall and warming to reduced lake ice growth. Future reductions in sea ice extent will alter hydrological, biogeochemical, and habitat functioning of Arctic lakes and cause sub-lake permafrost thaw. </li> <li> <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">Sea Ice, Climate and Fram Strait</a> <a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Hunkins, K. 1984-01-01 When sea ice 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. Sea ice 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 Ice Zone Experiment (MIZEX 83 to 84) is an international, multidisciplinary study of processes controlling the edge of the ice pack in that area including the interactions between sea, air and ice. </li> <li> <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">The future of ice sheets and sea ice: between reversible retreat and unstoppable loss.</a> <a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Notz, Dirk 2009-12-08 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 sea ice and the retreat of ice sheets: Once these ice masses have shrunk below an anticipated critical extent, the ice-albedo feedback might lead to the irreversible and unstoppable loss of the remaining ice. 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 sea ice. Hence, in a cooler climate, sea ice could recover rapidly from the loss it has experienced in recent years. In addition, we discuss why this recent rapid retreat of Arctic summer sea ice might largely be a consequence of a slow shift in ice-thickness distribution, which will lead to strongly increased year-to-year variability of the Arctic summer sea-ice extent. This variability will render seasonal forecasts of the Arctic summer sea-ice extent increasingly difficult. We also discuss why, in contrast to Arctic summer sea ice, a tipping point is more likely to exist for the loss of the Greenland ice sheet and the West Antarctic ice sheet. </li> <li> <a target="_blank" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/48384','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/48384">Sulfur dioxide reactions on ice surfaces: Implications for dry deposition to snow</a> <a target="_blank" href="http://www.fs.usda.gov/treesearch/">Treesearch</a> Martha H. Conklin; Richard A. Sommerfeld; S. Kay Laird; John E. Villinski 1993-01-01 Controlled exposure of ice to a reactive gas, SO2, demonstrated the importance of the chemical composition of the ice surface on the accumulation of acidity in snow. In a series of bench-scale continuous-flow column experiments run at four temperatures (-1, -8, -30 and -60Â°C), SO2 was shown to dissolve and to react with other species in the ice-air interfacial region... </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">25</li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <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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