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Sample records for sea ice snow

  1. 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.

  2. Spring Snow Depth on Arctic Sea Ice using the IceBridge Snow Depth Product (Invited)

    NASA Astrophysics Data System (ADS)

    Webster, M.; Rigor, I. G.; Nghiem, S. V.; Kurtz, N. T.; Farrell, S. L.

    2013-12-01

    Snow has dual roles in the growth and decay of Arctic sea ice. In winter, it insulates sea ice from colder air temperatures, slowing its growth. From spring into summer, the albedo of snow determines how much insolation is transmitted through the sea ice and into the underlying ocean, ultimately impacting the progression of the summer ice melt. Knowing the snow thickness and distribution are essential for understanding and modeling sea ice thermodynamics and the surface heat budget. Therefore, an accurate assessment of the snow cover is necessary for identifying its impacts in the changing Arctic. This study assesses springtime snow conditions on Arctic sea ice using airborne snow thickness measurements from Operation IceBridge (2009-2012). The 2012 data were validated with coordinated in situ measurements taken in March 2012 during the BRomine, Ozone, and Mercury EXperiment field campaign. We find a statistically significant correlation coefficient of 0.59 and RMS error of 5.8 cm. The comparison between the IceBridge snow thickness product and the 1937, 1954-1991 Soviet drifting ice station data suggests that the snow cover has thinned by 33% in the western Arctic and 44% in the Beaufort and Chukchi Seas. A rudimentary estimation shows that a thinner snow cover in the Beaufort and Chukchi Seas translates to a mid-December surface heat flux as high as 81 W/m2 compared to 32 W/m2. The relationship between the 2009-2012 thinner snow depth distribution and later sea ice freeze-up is statistically significant, with a correlation coefficient of 0.59. These results may help us better understand the surface energy budget in the changing Arctic, and may improve our ability to predict the future state of the sea ice cover.

  3. Seasonal Evolution of Snow Cover on Antarctic Sea Ice

    NASA Astrophysics Data System (ADS)

    Maksym, T.; Leonard, K. C.; Trujillo, E.; White, S.; Wilkinson, J.; Stammerjohn, S. E.; Mei, J.

    2015-12-01

    Snow cover on Antarctic sea ice plays a key role in the evolution of ice thickness, its estimation from space-borne altimeters, and structuring of sea ice ecosystems. Yet until recently, there have been very few continuous observations of the seasonal evolution of snow cover on Antarctic sea ice. We present observations of the seasonal evolution of the snow cover from ice mass balance buoys (IMBs) deployed between 2009 and 2013 in the Weddell, Bellingshausen, and Amundsen Seas and the East Antarctic sector. In addition, automatic weather stations that provided direct observations of precipitation, accumulation, and blowing snow were deployed alongside IMBs in October, 2012 in the East Antarctic during the Sea Ice Physics and Ecosystem eXperiment II (SIPEX II), and in July and August, 2013 in the Weddell Sea during the Antarctic Winter Ecosystem and Climate Study (AWECS). These buoys show markedly different snow accumulation regimes in each sector, although accumulation is also strongly controlled by the local morphology of the ice cover through snow erosion and deposition during blowing snow and precipitations events. Comparisons of snow accumulation from these buoys with estimates from atmospheric reanalysis and the direct measurements of precipitation and blowing snow show that precipitation is generally not a good estimator of snow accumulation. Improved treatment of blowing snow is needed if sea ice models are to accurately simulate Antarctic snow and sea ice mass balance. In summer, melting of the snow pack is relatively modest in most cases. Nevertheless, it appears to play an important role in governing sea ice hydrology and sea ice surface properties, and hence may play an important role in modulating sea ice primary productivity.

  4. 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

  5. Snow, Wind, Sun, and Time - How snow-driven processes control the Arctic sea ice

    NASA Astrophysics Data System (ADS)

    Polashenski, C.; Druckenmiller, M. L.; Perovich, D. K.

    2012-12-01

    Snowfall on Arctic sea ice is important for a number of reasons. The snowpack insulates sea ice from the cold winter atmosphere, redistribution of snow alters the surface roughness of the ice, light scattering in the snow increases ice albedo and reduces light transmission, and the weight of early season snow can result in ice surface flooding. An integrated set of field observations were collected to better understand how snowfall and, particularly, snow redistribution processes impact Arctic ice mass balance. Coincident measurements of snow depth and ice thickness on un-deformed first year ice indicate that snow dunes 'lock' in place early in the winter growth season, resulting in thinner ice beneath the dunes due to lower rates of energy loss. Coincident ground-based LiDAR measurements of surface topography and snow depth show that snow dune formation is largely responsible for the topographic relief of otherwise flat first year ice. Past work has shown that pond formation during the early melt season is strongly guided by the snow-controlled relative surface heights at a given site. Here multiple study sites are examined in an effort to better understand how differing patterns of snow redistribution can impact the overall extent of melt ponds, and therefore ice albedo. The results enhance basic knowledge of how snow processes control sea ice mass balance, and evoke several questions which must be answered in order to understand how changing precipitation regimes may affect sea ice in the Arctic.

  6. Interdecadal changes in snow depth on Arctic sea ice

    NASA Astrophysics Data System (ADS)

    Webster, Melinda A.; Rigor, Ignatius G.; Nghiem, Son V.; Kurtz, Nathan T.; Farrell, Sinead L.; Perovich, Donald K.; Sturm, Matthew

    2014-08-01

    Snow plays a key role in the growth and decay of Arctic sea ice. In winter, it insulates sea ice from cold air temperatures, slowing sea ice growth. From spring to summer, the albedo of snow determines how much insolation is absorbed by the sea ice and underlying ocean, impacting ice melt processes. Knowledge of the contemporary snow depth distribution is essential for estimating sea ice thickness and volume, and for understanding and modeling sea ice thermodynamics in the changing Arctic. This study assesses spring snow depth distribution on Arctic sea ice using airborne radar observations from Operation IceBridge for 2009-2013. Data were validated using coordinated in situ measurements taken in March 2012 during the Bromine, Ozone, and Mercury Experiment (BROMEX) field campaign. We find a correlation of 0.59 and root-mean-square error of 5.8 cm between the airborne and in situ data. Using this relationship and IceBridge snow thickness products, we compared the recent results with data from the 1937, 1954-1991 Soviet drifting ice stations. The comparison shows thinning of the snowpack, from 35.1 ± 9.4 to 22.2 ± 1.9 cm in the western Arctic, and from 32.8 ± 9.4 to 14.5 ± 1.9 cm in the Beaufort and Chukchi seas. These changes suggest a snow depth decline of 37 ± 29% in the western Arctic and 56 ± 33% in the Beaufort and Chukchi seas. Thinning is negatively correlated with the delayed onset of sea ice freezeup during autumn.

  7. 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.

  8. Simulating Snow Over Sea Ice In Climate Models

    NASA Technical Reports Server (NTRS)

    Arnold, James E. (Technical Monitor); Marshall, Susan; Oglesby, Robert J.; Drobot, Sheldon; Anderson, Mark

    2002-01-01

    We have evaluated two methods of simulating the seasonal cycle of snow over sea ice in and around the Arctic: The NCAR global climate model CCM3, with its standard snow hydrology, and the snow pack model SNTHERM, forced with hourly atmospheric output from CCM3. A new dataset providing dates for the onset of snow melt over Arctic sea ice provides a means for assessing basin-wide how well the models simulate melt onset, but contains no information on how long it then takes for all the snow to melt. Use of data from the SHEBA site provides very detailed information on the behavior of the snow before and during the melt season, but only for a very limited area. Russian drift data provide climatological data on the seasonal cycle of snow water equivalent and snow density, over multi-year sea ice in the central Arctic basin. These datasets are used to compare the two modeling methods, and to see if use of the more physically-realistic SNTHERM provides any significant improvements. Conclusions obtained so far include: 1. Both CCM3 and CCM3/SNTHERM do a good job overall of matching the onset of snow melt dataset; although CCM3/SNTHERM consistently trends to underestimate the date and CCM3 to overestimate it. 2. SHEBA and ice drift data for the Arctic show that CCM3/ SNTHERM does a better job than CCM3 at simulating the total melt period. 3. Ice drift snow density and accumulation data suggest that while providing superior results, CCM3/SNTHERM may still suffer from overly vigorous melting. 4. Both the large-scale atmospheric forcing and snow pack physical processes are important in proper simulation of the snow seasonal cycle. Ongoing work includes further diagnosis of CCM3/SNTHERM, use of more observational datasets, especially from marginal seas in the pan-Arctic, and full coupling of SNTHERM into CCM3 (work to date has all been off-line simulations).

  9. Airborne Surveys of Snow Depth over Arctic Sea Ice

    NASA Technical Reports Server (NTRS)

    Kwok, R.; Panzer, B.; Leuschen, C.; Pang, S.; Markus, T.; Holt, B.; Gogineni, S.

    2011-01-01

    During the spring of 2009, an ultrawideband microwave radar was deployed as part of Operation IceBridge to provide the first cross-basin surveys of snow thickness over Arctic sea ice. In this paper, we analyze data from three approx 2000 km transects to examine detection issues, the limitations of the current instrument, and the regional variability of the retrieved snow depth. Snow depth is the vertical distance between the air \\snow and snow-ice interfaces detected in the radar echograms. Under ideal conditions, the per echogram uncertainty in snow depth retrieval is approx 4 - 5 cm. The finite range resolution of the radar (approx 5 cm) and the relative amplitude of backscatter from the two interfaces limit the direct retrieval of snow depths much below approx 8 cm. Well-defined interfaces are observed over only relatively smooth surfaces within the radar footprint of approx 6.5 m. Sampling is thus restricted to undeformed, level ice. In early April, mean snow depths are 28.5 +/- 16.6 cm and 41.0 +/- 22.2 cm over first-year and multiyear sea ice (MYI), respectively. Regionally, snow thickness is thinner and quite uniform over the large expanse of seasonal ice in the Beaufort Sea, and gets progressively thicker toward the MYI cover north of Ellesmere Island, Greenland, and the Fram Strait. Snow depth over MYI is comparable to that reported in the climatology by Warren et al. Ongoing improvements to the radar system and the utility of these snow depth measurements are discussed.

  10. Optical Properties of Snow and Sea-ice, Barrow Alaska

    NASA Astrophysics Data System (ADS)

    Reay, H. J.; France, J. L.; King, M. D.

    2009-12-01

    Sunlit snowpacks and sea-ice produce a flux of chemicals from the snow or ice to the atmosphere. The chemical flux (1) changes the oxidising capacity of the atmosphere above the snowpack (2) alters chemical concentrations in snow, via reaction with photo-generated hydroxyl radicals. Photochemistry in snow and ice affect concentration chemicals in ice cores which are used to infer past (and therefore future) climates. Impurities in snow changes the optical absorption properties of the snowpack and thus the efficiency with which they melt as highlighted by the IPCC. Measurements of the solar irradiance in the snow and above the snow were undertaken as part of the OASIS 2009 campaign Barrow, Alaska. A model has been used to compute the amount of chemistry driven by this sunlight in and above the snow and to calculate fluxes of NO, NO2 from the snow and depth integrated hydroxyl radical production rate. The values can be compared to measurements of these gases at Barrow as part of the large OASIS field campaign. We have studied the optical properties of different Arctic snowpacks at UV-visible wavelength (350-700nm) by measuring the e-folding depth and albedos of many windpacks. Optically the snowpacks can be classified into four main snowpack types: snow on sea-ice, snow inland, soft and hard windpack. The albedo was measured using nadir reflectance and the e-folding depth was measured by recording the diffuse irradiance using fibre optic probes inserted into the snow at known depths. Using the TUV-Snow radiative transfer model we have determined the optical variables for scattering and absorption. We have produce absorption spectra of the impurities in the snowpack demonstrating a combination of black carbon and humic-like material (fig1). Fig 1. Absorption spectrum of inland snow

  11. 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.

  12. Large-Scale Surveys of Snow Depth on Arctic Sea Ice from Operation IceBridge

    NASA Technical Reports Server (NTRS)

    Kurtz, Nathan T.; Farrell, Sinead L.

    2011-01-01

    We show the first results of a large ]scale survey of snow depth on Arctic sea ice from NASA fs Operation IceBridge snow radar system for the 2009 season and compare the data to climatological snow depth values established over the 1954.1991 time period. For multiyear ice, the mean radar derived snow depth is 33.1 cm and the corresponding mean climatological snow depth is 33.4 cm. The small mean difference suggests consistency between contemporary estimates of snow depth with the historical climatology for the multiyear ice region of the Arctic. A 16.5 cm mean difference (climatology minus radar) is observed for first year ice areas suggesting that the increasingly seasonal sea ice cover of the Arctic Ocean has led to an overall loss of snow as the region has transitioned away from a dominantly multiyear ice cover.

  13. 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

  14. The Influence of Platelet Ice and Snow on Antarctic Land-fast Sea Ice

    NASA Astrophysics Data System (ADS)

    Hoppmann, M.; Nicolaus, M.

    2011-12-01

    Sea ice fastened to coasts, icebergs and ice shelves is of crucial importance for climate- and ecosystems. Near Antarctic ice shelves, this land-fast sea ice exhibits two unique characteristics that distinguish it from most other sea ice: a sub-ice layer of ice platelets and a highly stratified and thick snow cover. Ice platelets are flat, plate-like ice crystals forming and growing in a layer of super-cooled water which originates from ice shelf cavities. During growth, heat is lost to the super-cooled ocean rather than conducted to the atmosphere. The crystals accumulate beneath the solid sea-ice cover, forming a layer of loose platelets and eventually becoming incorporated into the sea-ice fabric as platelet ice. Considering the fact that the amount of platelet ice contributes between 10 and 60% to the mass of the land-fast sea ice around Antarctica, very little is known about its spatial and temporal variability. A thick and partly multi-year snow cover develops on top of the Antarctic fast ice, ultimately altering the sea-ice surface and affecting the sea-ice thermodynamics and mass balance. It typically leads to snow-ice formation, surface flooding, and the development of superimposed ice from snow melt water. In order to investigate the role of platelet ice and snow for Antarctic fast ice, we have initiated a regular observation program on the land-fast sea ice of Atka Bay as part of the international Antarctic Fast Ice Network (AFIN). We performed manual measurements of sea-ice and snow thicknesses from June to December 2010 and 2011. Additionally, a mass balance buoy and an automatic weather station were deployed in 2011 and ice cores were taken. Our measurements will reveal insight into the spatial and temporal variability of sea-ice and snow thickness distributions on Atka Bay fast ice. First results show that sea-ice thickness is lowest in the eastern part of the Bay, where a thick snow cover leads to extensive surface flooding. In the West, dynamic

  15. ICESat: Sea ice freeboard, snow depth, and thickness

    NASA Astrophysics Data System (ADS)

    Kwok, R.

    2007-12-01

    Total freeboard (snow and ice) and thickness of the Arctic Ocean sea ice cover are derived from ICESat data for two 35-day periods: one during the fall (Oct-Nov) of 2005 and the other during the winter (Feb-Mar) of 2006. Our freeboard retrieval approach is based on reflectivity and the expected statistics of freeboard variability from combined analysis of RADARSAT/ICESat data. Results suggest that our retrieval procedures could provide consistent freeboard estimates along 25-km segments with uncertainties of better than several centimeters. With a climatology of snow density, ECMWF snowfall is used to construct a time-varying field of snow depth for the conversion of freeboard to sea ice thickness. The derived ice thickness estimates are compared with ice draft observations from moored upward looking sonar data and the snow depth/thickness data from mass balance buoys in the Beaufort Sea. Preliminary results show that the estimated ICESat thickness estimates are within 0.5 m of the ice drafts reported by moorings. In this talk, we highlight some of the issues associated with the process of freeboard retrieval, thickness estimation, and quality assessment due to the disparity of spatial resolution between the ICESat footprint and those from in-situ measurements.

  16. Assessment of radar-derived snow depth over Arctic sea ice

    NASA Astrophysics Data System (ADS)

    Newman, Thomas; Farrell, Sinead L.; Richter-Menge, Jacqueline; Connor, Laurence N.; Kurtz, Nathan T.; Elder, Bruce C.; McAdoo, David

    2014-12-01

    Knowledge of contemporaneous snow depth on Arctic sea ice is important both to constrain the regional climatology and to improve the accuracy of satellite altimeter estimates of sea ice thickness. We assess new data available from the NASA Operation IceBridge snow radar instrument and derive snow depth estimates across the western Arctic ice pack using a novel methodology based on wavelet techniques that define the primary reflecting surfaces within the snow pack. We assign uncertainty to the snow depth estimates based upon both the radar system parameters and sea ice topographic variability. The accuracy of the airborne snow depth estimates are examined via comparison with coincident measurements gathered in situ across a range of ice types in the Beaufort Sea. We discuss the effect of surface morphology on the derivation, and consequently the accuracy, of airborne snow depth estimates. We find that snow depths derived from the airborne snow radar using the wavelet-based technique are accurate to 1 cm over level ice. Over rougher surfaces including multiyear and ridged ice, the radar system is impacted by ice surface morphology. Across basin scales, we find the snow-radar-derived snow depth on first-year ice is at least ˜60% of the value reported in the snow climatology for the Beaufort Sea, Canada Basin, and parts of the central Arctic, since these regions were previously dominated by multiyear ice during the measurement period of the climatology. Snow on multiyear ice is more consistent with the climatology.

  17. 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

  18. Contaminants in arctic snow collected over northwest Alaskan sea ice

    USGS Publications Warehouse

    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.

  19. 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.

  20. The Impact of Snow and Ice Morphology on Radar Altimetric Determination of Sea Ice Thickness

    NASA Astrophysics Data System (ADS)

    Newman, T.; Brozena, J. M.; Ball, D.; Liang, R.; Abelev, A.; Gardner, J. M.

    2015-12-01

    Observations of the current state of Arctic sea ice indicate a trend towards a younger, thinner and more mobile pack that exhibits significant inter-annual variability. Radar returns from altimeters are impacted by the morphology of snow and ice features on the surface as well as the characteristics of radar pulse penetration through the snow pack. Together these contribute to uncertainty in the procedures for deriving sea ice freeboard from radar altimeter data. We make use of dense lidar grids and airborne snow radar measurements, collected on the sea ice pack north of Barrow, Alaska by the Naval Research Laboratory in 2014 and 2015, to investigate the effect of ice surface morphology on radar altimeter measurements. We quantify the effect of surface morphology using a nested approach that includes forward modeling, snow radar data and a comprehensive set of in situ measurements. Our results allow us to better constrain the altimetric uncertainty resulting from ice surface morphology, with respect to ice type. This will lead to an enhanced understanding of sources of uncertainty in altimeter-derived sea ice thickness products.

  1. Interannual and Regional Variability of Southern Ocean Snow on Sea Ice and its Correspondence with Sea Ice Cover and Atmospheric Circulation Patterns

    NASA Technical Reports Server (NTRS)

    Markus, T.; Cavalieri, D. J.

    2006-01-01

    Snow depth on sea ice plays a critical role in the heat exchange between ocean and atmosphere because of its thermal insulation property. Furthermore, a heavy snow load on the relatively thin Southern Ocean sea-ice cover submerges the ice floes below sea level, causing snow-to-ice conversion. Snowfall is also an important freshwater source into the weakly stratified ocean. Snow depth on sea-ice information can be used as an indirect measure of solid precipitation. Satellite passive microwave data are used to investigate the interannual and regional variability of the snow cover on sea ice. In this study we make use of 12 years (1992-2003) of Special Sensor Microwave/Imager (SSM/I) radiances to calculate average monthly snow depth on the Antarctic sea-ice cover. The results show a slight increase in snow depth and a partial eastward propagation of maximum snow depths, which may be related to the Antarctic Circumpolar Wave.

  2. Snow depth on Arctic sea ice derived from radar: In situ comparisons and time series analysis

    NASA Astrophysics Data System (ADS)

    Holt, Benjamin; Johnson, Michael P.; Perkovic-Martin, Dragana; Panzer, Ben

    2015-06-01

    The snow radar being flown on NASA's Operation IceBridge, ongoing aircraft campaigns to the Arctic and the Antarctic are providing unique observations of the depth of snow on the sea ice cover. In this paper, we focus on the radar-derived snow depth results from the 2009-2012 Arctic campaigns. We develop and evaluate the use of a distinct snow layer tracker to measure snow depth based on a Support Vector Machine (SVM) supervised learning algorithm. The snow radar is designed to detect both the air-snow and snow-ice interfaces using ultrawideband frequencies from 2 to 8 GHz. The quality, errors, and repeatability of the snow radar snow depth estimates are examined, based on comparisons with in situ data obtained during two separate sea ice field campaigns, the GreenArc 2009 and the CryoVEx 2011 campaigns off Greenland in the Lincoln Sea. Finally, we analyze 4 years (2009-2012) of three annually repeated sea ice flight lines obtained in early spring, located off Greenland and the Canadian Arctic. We examine the annual variations of snow depth differences between perennial and seasonal ice when available. Overall, the snow layer tracker produced consistent, accurate results for snow depths between 0.10 and ˜0.60 m. This was confirmed with comparisons with the two data sets from the in situ measurement campaigns as well as with the time series analysis, and is consistent with other published results.

  3. Snow thickness retrieval over thick Arctic sea ice using SMOS satellite data

    NASA Astrophysics Data System (ADS)

    Maaß, N.; Kaleschke, L.; Tian-Kunze, X.; Drusch, M.

    2013-07-01

    The microwave interferometric radiometer of the European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission measures at a frequency of 1.4 GHz in the L-band. In contrast to other microwave satellites, low frequency measurements in L-band have a large penetration depth in sea ice and thus contain information on the ice thickness. Previous ice thickness retrievals have neglected a snow layer on top of the ice. Here, we implement a snow layer in our emission model and investigate how snow influences L-band brightness temperatures and whether it is possible to retrieve snow thickness over thick Arctic sea ice from SMOS data. We find that the brightness temperatures above snow-covered sea ice are higher than above bare sea ice and that horizontal polarisation is more affected by the snow layer than vertical polarisation. In accordance with our theoretical investigations, the root mean square deviation between simulated and observed horizontally polarised brightness temperatures decreases from 20.0 K to 4.4 K, when we include the snow layer in the simulations. Under cold Arctic conditions we find brightness temperatures to increase with increasing snow thickness. Because dry snow is almost transparent in L-band, this brightness temperature's dependence on snow thickness origins from the thermal insulation of snow and its dependence on the snow layer thickness. This temperature effect allows us to retrieve snow thickness over thick sea ice. For the best simulation scenario and snow thicknesses up to 35 cm, the average snow thickness retrieved from horizontally polarised SMOS brightness temperatures agrees within 0.7 cm with the average snow thickness measured during the IceBridge flight campaign in the Arctic in spring 2012. The corresponding root mean square deviation is 6.3 cm, and the correlation coefficient is r2 = 0.55.

  4. Snow thickness retrieval over thick Arctic sea ice using SMOS satellite data

    NASA Astrophysics Data System (ADS)

    Maaß, N.; Kaleschke, L.; Tian-Kunze, X.; Drusch, M.

    2013-12-01

    The microwave interferometric radiometer of the European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission measures at a frequency of 1.4 GHz in the L-band. In contrast to other microwave satellites, low frequency measurements in L-band have a large penetration depth in sea ice and thus contain information on the ice thickness. Previous ice thickness retrievals have neglected a snow layer on top of the ice. Here, we implement a snow layer in our emission model and investigate how snow influences L-band brightness temperatures and whether it is possible to retrieve snow thickness over thick Arctic sea ice from SMOS data. We find that the brightness temperatures above snow-covered sea ice are higher than above bare sea ice and that horizontal polarisation is more affected by the snow layer than vertical polarisation. In accordance with our theoretical investigations, the root mean square deviation between simulated and observed horizontally polarised brightness temperatures decreases from 20.9 K to 4.7 K, when we include the snow layer in the simulations. Although dry snow is almost transparent in L-band, we find brightness temperatures to increase with increasing snow thickness under cold Arctic conditions. The brightness temperatures' dependence on snow thickness can be explained by the thermal insulation of snow and its dependence on the snow layer thickness. This temperature effect allows us to retrieve snow thickness over thick sea ice. For the best simulation scenario and snow thicknesses up to 35 cm, the average snow thickness retrieved from horizontally polarised SMOS brightness temperatures agrees within 0.1 cm with the average snow thickness measured during the IceBridge flight campaign in the Arctic in spring 2012. The corresponding root mean square deviation is 5.5 cm, and the coefficient of determination is r2 = 0.58.

  5. Sea salt aerosol from blowing snow on sea ice - modeling vs observation

    NASA Astrophysics Data System (ADS)

    Yang, Xin; Frey, Markus; Norris, Sarah; Brooks, Ian; Anderson, Philip; Jones, Anna; wolff, Eric; Legrand, Michel

    2016-04-01

    Blowing snow over sea ice, through a subsequent sublimation process of salt-containing blown snow particles, has been hypothesized as a significant sea salt aerosol (SSA) source in high latitudes. This mechanism has been strongly supported by a winter cruise in the Weddell Sea (during June-August 2013). The newly collected data, including both physical and chemical components, provide a unique way to test and validate the parameterisation used for describing the SSA production from blowing snow events. With updates to some key parameters such as snow salinity in a global Chemistry-transport model pTOMCAT, simulated SSA concentrations can be well compared with measured SSA data. In this presentation, I will report modeled SSA number density against collected data on board of Polarstern ship during the Weddell Sea cruise, as well as modeled SSA massive concentrations against those measured at both coastal sites such as Alert in the North and Dumont d'Urville (DDU) in the South and central Antarctic sites such as Concordia and Kohnen stations. Model experiments indicated that open ocean-sourced SSA could not explain the observed winter SSA peaks seen in most polar sites, while with sea ice-sourced SSA in the model, the winter peaks can be well improved indicating the importance of sea ice-sourced SSA as a significant contributor to the salts (Na+, Cl-) recorded in the ice core.

  6. Model Representation of Last Decade Regional Changes of Arctic Snow on Sea ice

    NASA Astrophysics Data System (ADS)

    Ricker, R.; Castro-Morales, K.; Gerdes, R.

    2015-12-01

    Present changes that Arctic snow on sea ice experience due to a warming climate have important implications to the sea ice component, precipitation, heat and radiation budgets. In this study, we analyzed the regional distribution and changes, from 2000 to 2013, of Arctic snow depth simulated with a coupled sea ice-general circulation model. For validation, we compared the modeled snow depths (hs_mod) with airborne snow depth measurements from NASA's Operation IceBridge (hs_OIB) from 2009 to 2013. As in many current sea-ice models, our model configuration consist on a single-layer snow scheme and lack of explicit snow redistribution processes. The snow is accumulated proportionally to the prescribed sea-ice thickness distribution. Despite the simple scheme, our results show that the hs_mod latitudinal distribution in the western Arctic is in good agreement to the OIB observations. The hs_mod is generally thicker than hs_OIB: for latitudes dominated by first-year ice (between 67° N and 76° N) hs_mod is on average 1.1±7.9 cm thicker than hs_OIB, while for multi-year ice dominated latitudes (> 76° N), hs_mod is on average 3.0±8.8 cm thicker than hs_OIB. By 2013, the Arctic-wide hs decreased 21 % with respect to the hs multi-annual mean (2000 to 2013) occurring mainly in first-year ice dominated areas. In a simple snow mass budget, our results show that 65 % of the yearly accumulated snow is lost by sublimation and snowmelt due to the heat transfer between the snow/ice interface and the atmosphere. Despite the yearly recovery of snow in winter, the long-term reduction in the summer sea-ice extent ultimately affects the maximum accumulation of snow in spring. Compared to snow reduction estimates from snow radar measurements, the model results underestimate this loss, and we suggest that this is partially due to the lack of explicit snow redistribution processes in the model, ratifying the need to include these in current sea-ice models to improve the snow

  7. Snow Depth and Ice Thickness Measurements From the Beaufort and Chukchi Seas Collected During the AMSR-Ice03 Campaign

    NASA Technical Reports Server (NTRS)

    Sturm, M.; Holmgren, J.; Maslanik, J. A.; Perovich, D. K.; Richter-Menge, J.; Stroeve, J. C.; Markus, T.; Heinrichs, J. F.; Tape, K.

    2006-01-01

    In March 2003, a field validation campaign was conducted on the sea ice near Barrow, AK. The goal of this campaign was to produce an extensive dataset of sea ice thickness and snow properties (depth and stratigraphy) against which remote sensing products collected by aircraft and satellite could be compared. Chief among these were products from the Polarimetric Scanning Radiometer (PSR) flown aboard a NASA P-3B aircraft and the Aqua Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E). The data were collected in four field areas: three on the coastal sea ice near Barrow, AK, and the fourth out on the open ice pack 175 km northeast of Barrow. The snow depth ranged from 9.4-20.8 cm in coastal areas (n = 9881 for three areas) with the thinnest snow on ice that had formed late in the winter. Out in the main pack ice, the snow was 20.6 cm deep (n = 1906). The ice in all four areas ranged from 138-219 cm thick (n = 1952), with the lower value again where the ice had formed late in the winter. Snow layer and grain characteristics observed in 118 snow pits indicated that 44% of observed snow layers were depth hoar; 46% were wind slab. Snow and ice measurements were keyed to photomosaics produced from low-altitude vertical aerial photographs. Using these, and a distinctive three-way relationship between ice roughness, snow surface characteristics, and snow depth, strip maps of snow depth, each about 2 km wide, were produced bracketing the traverse lines. These maps contain an unprecedented level of snow depth detail against which to compare remote sensing products. The maps are used in other papers in this special issue to examine the retrieval of snow properties from the PSR and AMSR-E sensors.

  8. Advances in Airborne Altimetric Techniques for the Measurement of Snow on Arctic Sea Ice

    NASA Astrophysics Data System (ADS)

    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.

  9. Remote Sensing of Snow-covered Sea Ice with Ultra-wideband Airborne Radars

    NASA Astrophysics Data System (ADS)

    Yan, S.; Gogineni, P. S.; Gomez-Garcia, D.; Leuschen, C.; Hale, R.; Rodriguez-Morales, F.; Paden, J. D.; Li, J.

    2015-12-01

    The extent and thickness of sea ice and snow play a critical role in the Earth's climate system. Both sea ice and snow have high albedo and control the heat exchange between the atmosphere and ocean and atmosphere and land. In terms of hydrology, the presence of sea ice and snow modulates the flow and the salinity of ocean water. This in turn can modify the weather patterns around the globe. Understanding the formation, coverage and the properties of sea ice and snow are important for both short-term and long-term climate modeling. The advancements in high-frequency electronics and digital signal processing enabled the development of ultra-wideband radars by the Center for Remote Sensing of Ice Sheets (CReSIS) for airborne measurements of snow and ice properties over large areas. CReSIS recently developed and deployed two ultra-wideband airborne radars, namely the Multichannel Coherent Radar Depth Sounder/Imager (MCoRDS/I) and the Snow Radar. The MCoRDS/I is designed to operate over the frequency range of 180-450 MHz for sounding land ice and imaging its ice-bed interface. We also took advantage of the deployment to explore the potential of UWB MCoRDS/I in sounding sea ice and collected data on flight lines flown as part of NASA Operation IceBridge mission during Spring 2015. Preliminary results show we sounded sea ice under favorable conditions. We will perform detailed processing and analysis of data over the next few months and we will compare results obtained are compared with existing altimetry-derived data products. The new snow radar, on the other hand, operating from 2 to 18 GHz, was deployed on the NRL Twin Otter aircraft in Barrow, AK. It was shown to have a vertical resolution of down to 1.5 cm which opens up the potential for thin snow measurement on both sea ice and land. Both of these new radars will be further optimized for future airborne missions to demonstrate their capabilities for sea ice and snow measurements. We will also show new technical

  10. Characteristics and distribution patterns of snow and meteoric ice in the Weddell Sea and their contribution to the mass balance of sea ice

    NASA Astrophysics Data System (ADS)

    Eicken, Hajo; Lange, Manfred A.; Wadhams, Peter

    1994-01-01

    Based on snow- and ice-thickness measurements at >11 000 points augmented by snow- and icecore studies during 4 expeditions from 1986 - 92 in the Weddell Sea, we describe characteristics and distribution patterns of snow and meteoric ice and assess their importance for the mass balance of sea ice. For first-year ice (FY) in the central and eastern Weddell Sea, mean snow depth amounts to 0.16 m (mean ice thickness 0.75 m) compared to 0.53 m (mean ice thickness 1.70 m) for second-year ice (SY) in the northwestern Weddell Sea. Ridged ice retains a thicker snow cover than level ice, with ice thickness and snow depth negatively correlated for the latter, most likely due to aeolian redistribution. During the different expeditions, 8, 15, 17 and 40% of all drill holes exhibited negative freeboard. As a result of flooding and brine seepage into the snow pack, snow salinities averaged 4‰. Through 18O measurements the distribution of meteoric ice (i.e. precipitation) in the sea-ice cover was assessed. Roughly 4% of the total ice thickness consist of meteoric ice (FY 3%, SY 5%). With a mean density of 290 kg/m3, the snow cover itself contributes 8% to total ice mass (7% FY, 11% SY). Analysis of 18O in snow indicates a local maximum in accumulation in the 65 to 75°S latitude zone. Hydrogen peroxide in the snow has proven useful as a temporal tracer and for identification of second-year floes. Drawing on accumulation data from stations at the Weddell Sea coast, it becomes clear that the onset of ice growth is important for the evolution of ice thickness and the interaction between ice and snow. Loss of snow to leads due to wind drift may be considerable, yet is reduced owing to metamorphic processes in the snow column. This is confirmed by a comparison of accumulation data from coastal stations and from snow depths over sea ice. Temporal and spatial accumulation patterns of snow are shown to be important in controlling the sea-ice cover evolution.

  11. First Results from the ASIBIA (Arctic Sea-Ice, snow, Biogeochemistry and Impacts on the Atmosphere) Sea-Ice Chamber

    NASA Astrophysics Data System (ADS)

    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

  12. Review of Electromagnetic Methods to Investigate Arctic and Antarctic Sea Ice and Snow

    NASA Astrophysics Data System (ADS)

    Pfaffling, A.; Haas, C.; Meil{\\Ae}Nder-Larsen, M.; Bishop, J.; Flinspach, D.; Otto, D.; Reid, J. E.; Worby, A. P.

    2007-12-01

    During the last 5 years we have applied a variety of near-surface electric (ie, resistivity) and electromagnetic methods to investigate sea ice and snow on sea ice in the Antarctic and Arctic. Here we present field cases and lessons learned on the applicability for resolving distinct target parameters. The geophysical challenges of sea ice include its composition of (a) homogeneous, vertically anisotropic, one-dimensional (level) ice 0.5 to 4 m thick, and (b) highly heterogeneous, partly water impregnated three-dimensional pressure ridge features 2 to 10 m thick. Snow on sea ice is generally dry (until melt onset) and spans a thickness range of some centimetres up to a few meters. We applied several different types of equipment covering the frequency range from DC to radar for different tasks and targets. Ground Penetrating Radar (GPR) proved to be fast and portable for snow thickness profiling with the limitation of a minimum snow thickness around 10 cm. Electromagnetic induction (EMI) is a classic sea ice thickness profiling method used hand held on the ice, ship-borne suspended from outrigger-like constructions as well as airborne as helicopter towed sensors. Mostly regional ice plus snow thickness is derived from EMI measurements. Attempts have been made to retrieve internal ice properties such as porosity or age (conductivity) from EM soundings. DC-resistivity sounding clearly shows the vertical conductivity anisotropy of level sea ice, due to its crystalline structure and aging processes. Electrical Resistivity Tomography was conducted on Baltic and Arctic sea ice to determine the porosity of pressure ridge keels. Our results show the potentials and limitations of the different methods for climate related and engineering sea ice studies. geophysics.com/projects

  13. On the Estimation of Snow Thickness Distributions Over Sea Ice Using the Thermal Dependence of Backscatter

    NASA Technical Reports Server (NTRS)

    Barber, D. G.; Nghiem, S. V.

    1998-01-01

    Our understanding of snow distributions in the polar regions is severly restricted due to the heterogeneity, both in space and time, of this solid precipitate. Processes such as vapor and mass fluxes across the interface are, to a large extent, controlled by the presence and geophysical state of the snow cover on sea ice.

  14. Validation of Airborne FMCW Radar Measurements of Snow Thickness Over Sea Ice in Antarctica

    NASA Technical Reports Server (NTRS)

    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.

  15. MODIS Snow and Ice Production

    NASA Technical Reports Server (NTRS)

    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.

  16. Snow Dunes: A Controlling Factor of Melt Pond Distribution on Arctic Sea Ice

    NASA Technical Reports Server (NTRS)

    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.

  17. ICESat over Arctic sea ice: Estimation of snow depth and ice thickness

    NASA Astrophysics Data System (ADS)

    Kwok, R.; Cunningham, G. F.

    2008-08-01

    Starting with retrieved freeboards from four ICESat campaigns (ON05, October/November 2005; FM06, February/March 2006; ON06, October/November 2006; and MA07, March/April 2007) we estimate their ice thicknesses using constructed fields of daily snow depth and compare them with ice drafts from moored upward-looking sonars. The methodologies, considerations, and assumptions used in the conversion of freeboard to ice thickness are discussed. The thickness distributions of the Arctic multiyear and seasonal ice covers are contrasted. Broadly, the resulting fields seem seasonally and interannually consistent in terms of thickness, growth and ice production. We find mean thicknesses of 2.15/2.46 m in ON05/FM06 and an overall thinner ice cover of 1.96/2.37 m in ON06/MA07. This represents a growth of ˜0.3 m and ˜0.4 m during the ˜4-month intervals of the ON05-FM06 and ON06-MA07 campaigns, respectively. After accounting for data gaps, we compute overall Arctic Ocean ice volumes of 11,318, 14,075, 10,626, and 13,891 km3 for the ON05, FM06, ON06, and MA07 campaigns, respectively. The higher total volume in ON05 (versus ON06) can be attributed to the higher multiyear ice coverage that fall: 37% versus 31%. However, the higher estimated ice production (less export) during the second year (3265 versus 2757 km3) is likely due to the higher growth rate over the larger expanse of seasonal sea ice during the fall and winter. Inside a 25-km radius of two mooring locations in the Beaufort Sea, the estimated mean ICESat ice drafts from ON05 and FM06 are within 0.5 m of those measured at the moorings.

  18. Phytoplankton spring bloom beneath heavily snow-covered arctic sea ice during the N-ICE2015 cruise

    NASA Astrophysics Data System (ADS)

    Assmy, Philipp; Fernández-Méndez, Mar; Olsen, Lasse M.; Kauko, Hanna; Duarte, Pedro; Mundy, Christopher J.; Hop, Haakon; Fransson, Agneta; Chierici, Melissa; Gerland, Sebastian; Granskog, Mats A.; Hudson, Stephen R.; Roesel, Anja; Meyer, Amelie; Hughes, Nick; Steen, Harald

    2016-04-01

    The arctic icescape is rapidly transforming from a thick multi-year ice cover to a thinner and largely seasonal first-year ice cover with significant consequences for Arctic primary production. Recent studies have reported extensive phytoplankton blooms beneath ponded sea ice during summer, indicating that satellite-based arctic net primary production estimates may be significantly underestimated. We studied phytoplankton seasonal dynamics under changing sea-ice and snow conditions in the drifting pack-ice north of Svalbard from 11 January to 24 June 2015 during the Norwegian Young Sea ICE cruise (N-ICE2015). N-ICE2015 provided a unique time-series of under-ice bloom dynamics during the winter-spring transition in the high Arctic pack-ice ecosystem. Phytoplankton productivity stayed low throughout winter and early spring. By late May a large under-ice bloom (>300 mg Chl a m-2) dominated by Phaeocystis pouchetii developed over the Yermak plateau underneath 1.1 - 1.3 m thick sea ice and 0.3 - 0.5 m thick snow cover. The circulation characteristics over the plateau indicate that the bloom developed in situ and was not advected. The high lead activity, characteristic for the area, apparently provided enough open or thin ice covered area for sufficient light to penetrate into the underlying water column and initiate and sustain the bloom, despite the thick snow cover. Our observation of a spring under-ice phytoplankton bloom extends the spatial and temporal scale of under-ice blooms and indicates that these phenomena might become increasingly important in the future Arctic under changing sea-ice but also snow dynamics.

  19. New snow thermodynamics for the Louvain-la-Neuve Sea Ice Model (LIM)

    NASA Astrophysics Data System (ADS)

    Lecomte, Olivier; Fichefet, Thierry

    2010-05-01

    The Louvain-la-Neuve sea Ice Model (LIM) is a three-dimensional global model for sea ice dynamics and thermodynamics that has been specifically designed for climate studies and that is fully coupled with the oceanic general circulation model OPA on the modelling platform NEMO. This study presents and assesses the skills of a new one-dimensional snow model developed for the thermodynamic component of LIM, by comparison with the former model thermodynamics and observations. Snow is a key element in sea ice physics and in the interactions between sea ice and atmosphere. Owing to its low thermal conductivity and hight albedo, the snow cover is a very efficient insulator and it contributes directly and indirectly to the sea ice mass balance. Given the high variability and heterogeneity of the snow cover above sea ice, it is necessary to represent different types of snow, depending on their characteristics. A multilayer approach has been chosen for the model, with time varying temperature, density and thermal conductivity for each layer. Vertical heat diffusion, surface and internal melt, precipitations, snow ice formation and a parameterisation for melt pond albedo are included in the model. The model has been validated at Ice Station POLarstern (ISPOL) in the western Weddell Sea during summer and at Point Barrow (Alaska) during winter. The new model simulates better temperature profiles, with an amount of good correlations between modelled and observed profiles increasing from 12% to 42% for the 2-layer and 6-layer configurations, respectively. Conductive fluxes and temperatures are highly sensitive to albedo and ocean heat flux during summer, and to the thermal conductivity parameterisation during winter. Ice ablation rate is quite insensitive to snow thermal conductivity in summer because almost all the variability at the surface is absorbed by snow, making the temperature gradient in the ice relatively small and steady. Nevertheless, during winter, when the air

  20. A Coordinated Ice-based and Airborne Snow and Ice Thickness Measurement Campaign on Arctic Sea Ice

    NASA Astrophysics Data System (ADS)

    Richter-Menge, J.; Farrell, S.; Elder, B. C.; Gardner, J. M.; Brozena, J. M.

    2011-12-01

    A rare opportunity presented itself in March 2011 when the Naval Research Laboratory (NRL) and NASA IceBridge teamed with scientists from the U.S. Army Corps of Engineers Cold Regions Research and Engineering Laboratory (CRREL) to coordinate a multi-scale approach to mapping snow depth and sea ice thickness distribution in the Arctic. Ground-truth information for calibration/validation of airborne and CryoSat-2 satellite data were collected near a manned camp deployed in support of the US Navy's Ice Expedition 2011 (ICEX 2011). The ice camp was established at a location approximately 230 km north of Prudhoe Bay, Alaska, at the edge of the perennial ice zone. The suite of measurements was strategically organized around a 9-km-long survey line that covered a wide range of ice types, including refrozen leads, deformed and undeformed first year ice, and multiyear ice. A highly concentrated set of in situ measurements of snow depth and ice thickness were taken along the survey line. Once the survey line was in place, NASA IceBridge flew a dedicated mission along the survey line, collecting data with an instrument suite that included the Airborne Topographic Mapper (ATM), a high precision, airborne scanning laser altimeter; the Digital Mapping System (DMS), nadir-viewing digital camera; and the University of Kansas ultra-wideband Frequency Modulated Continuous Wave (FMCW) snow radar. NRL also flew a dedicated mission over the survey line with complementary airborne radar, laser and photogrammetric sensors (see Brozena et al., this session). These measurements were further leveraged by a series of CryoSat-2 under flights made in the region by the instrumented NRL and NASA planes, as well as US Navy submarine underpasses of the 9-km-long survey line to collect ice draft measurements. This comprehensive suite of data provides the full spectrum of sampling resolutions from satellite, to airborne, to ground-based, to submarine and will allow for a careful determination of

  1. Sea Ice SAR Signature Dependence on Thaw and Refreeze Event in the Snow Cover

    NASA Astrophysics Data System (ADS)

    Hudier, E. J.; Tolszczuk-Leclerc, S.

    2010-12-01

    As a result of the dependence of microwaves on the dielectric properties of the material they interfere with, the microwave signature of sea ice changes dramatically with the seasons as well as overnight when the snow layer is at the freezing point While pure ice and dry snow do not cause significant scattering and can be considered transparent throughout the winter season, the presence of liquid water, later on at spring, on air-ice or air-snow interfaces or within the snow cover turns the snow layer into an opaque medium and makes the air-snow interface the main contributor of the microwave backscattered to the SAR antenna. The availability of liquid water in the snow is the result of a shift in the thermodynamic balance of the snow layer and sea ice sheet. At spring, with the irradiance and air temperature increasing, the snow media quickly becomes isothermal. The snow layer is then a tri-phasic medium in which water changes state to balance radiations (short and long waves) and conductive heat fluxes variations. As a consequence, the surface layer of the snow cover is subject to a diurnal cycle of thaw during day time and refreeze at night which translates into a parallel diurnal cycle on snow wetness content. This cycle is of major relevance to microwave remote sensing applications and specifically to sea ice morphological features extraction. Using the output of a thermodynamic model of an isothermal snow cover forced by incoming L↓ and outgoing L↑ long-wave radiations, incident S↓ and reflected S↑ short-wave radiations and a turbulent atmospheric heat flux Qatm, an evaluation of the volume and surface components of a backscattered SAR is computed as a function of the SAR incident angle. We observe that when heat fluxes (irradiative and conductive) are positive, liquid water available in the top layer of the snow cover turns the air-snow interface into a specular reflector. Conversely, with wetness decreasing overnight, more energy can penetrate the

  2. Applications of ISES for snow, ice, and sea state

    NASA Technical Reports Server (NTRS)

    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.

  3. Chemical Atmosphere-Snow-Sea Ice Interactions: defining future research in the field, lab and modeling

    NASA Astrophysics Data System (ADS)

    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.

  4. A Comparison of Sea Ice Type, Sea Ice Temperature, and Snow Thickness Distributions in the Arctic Seasonal Ice Zones with the DMSP SSM/I

    NASA Technical Reports Server (NTRS)

    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.

  5. Peculiarities of hydrocarbon distribution in the snow-ice cover of different regions of the white sea

    NASA Astrophysics Data System (ADS)

    Nemirovskaya, I. A.

    2014-03-01

    This paper presents data on the content of hydrocarbons (HCs) in the snow-ice cover of the coastal regions of the Dvina and Kandalaksha gulfs, White Sea, in 2008-2012 in comparison with the content of organic carbon, lipids, and the suspension. The accumulation of HCs in the snow-ice cover depends on the degree of pollution of the atmosphere, formation conditions of ice, and intensity of biogeochemical processes at the ice-water boundary. Thus, the highest concentrations in the water basin of Arkhangelsk are identified in snow and in the upper part of the ice. The peculiarities of formation of the snow-ice cover in Rugozero Bay of the Kandalaksha Gulf leads to the concentration of HCs in different snow and ice layers. The decreased HC content in the snow-ice cover of the White Sea, in comparison with previous studies, is caused by recession of industrial production in recent years.

  6. Estimation of Sea Ice Thickness Distributions through the Combination of Snow Depth and Satellite Laser Altimetry Data

    NASA Technical Reports Server (NTRS)

    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.

  7. Arctic Sea Salt Aerosol from Blowing Snow and Sea Ice Surfaces - a Missing Natural Source in Winter

    NASA Astrophysics Data System (ADS)

    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.

  8. Hydrocarbons in the snow-ice cover of different areas of the White Sea

    NASA Astrophysics Data System (ADS)

    Nemirovskaya, I. A.

    2014-05-01

    The data on the content of hydrocarbons (HC) are presented and compared to the contents of organic carbon, lipids, and particulate matter in the snow-ice cover of the coastal areas of Dvina and Kandalaksha bays of the White Sea (2008-2012). The accumulation of HC in the snow-ice cover depends on the degree of atmosphere contamination, the conditions of the ice formation, and the intensity of the biogeochemical processes at the ice-water interface. Because of this, the aquatic area of Arkhangelsk is characterized by the highest HC concentrations in the snow and in the upper layer of ice. The peculiarities of the formation of the snow-ice cover in Rugozero bight of Kandalaksha Bay cause the concentrating of HC in different layers of ice. The decrease of the concentration of HC in the show-ice cover of the White Sea compared to earlier studies resulted from the recession of industrial activities during the recent years.

  9. Use of Unmanned Aircraft Systems in Observations of Glaciers, Ice Sheets, Sea Ice and Snow Fields

    NASA Astrophysics Data System (ADS)

    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.

  10. The combined influences of autumnal snow and sea ice on Northern Hemisphere winters

    NASA Astrophysics Data System (ADS)

    Furtado, J. C.; Cohen, J. L.; Tziperman, E.

    2016-04-01

    Past studies have demonstrated a significant relationship between the phase and amplitude of the Northern Annular Mode (NAM) and both Arctic sea ice and high-latitude snow cover during boreal autumn. However, those studies have considered these forcings separately. Here we consider the collective effect of Arctic sea ice and snow cover variability for producing skillful subseasonal forecasts for Northern Hemisphere (NH) winter conditions. We find that these two cryospheric elements interact with the extratropical atmosphere differently through the cold season. Sea ice extent minima during November play a role in stratospheric and tropospheric circulation anomalies during November/December with a secondary maximum in late January/February. October snow cover anomalies, however, have impacts on the NAM primarily during middle to late winter. These timing differences are likely tied to differences in anomalous wave driving between the two cases, though other processes may be in play. We exploit these different influences to produce a skillful forecast model of subseasonal NH surface temperatures using both sea ice and snow cover as predictors, with large gains in skills in January. Overall, our study suggests that the Arctic has a demonstrable and detectable influence on midlatitude winter weather in the present and likely future climate.

  11. Melt Pond Development on Arctic Land-Fast Sea Ice in Relation to Snow and Ice Properties During the Ice Growth Season

    NASA Astrophysics Data System (ADS)

    Petrich, C.; Eicken, H.; Pringle, D.; Sturm, M.; Perovich, D.; Polashenski, C.; Finnegan, D.

    2008-12-01

    The dynamics of melt pond development on sea ice were studied on a well-defined patch of level land-fast sea ice off the coast of Barrow, Alaska in 2008. The pond development was correlated with both sea ice properties and the history of snow distribution during the ice growth season. In mid January, the ice was covered by an almost level snow layer of 4~cm thickness. We observed an increase in snow depth and development of snow dunes since February. At least some snow dunes stayed in place, and at the end of April ice thickness was negatively correlated with the thickness of compacted snow dunes. Snow salinity remained above 5~psu in the bottom 4 to 5~cm of the snow pack throughout the ice growth season. In comparison, snow more than 5~cm above the snow--ice interface was almost devoid of salt. The air temperature increased rapidly in early May and started to exceed 0°C on May 15. From this day on, thermistor string data show that the sea ice temperature profile deviated from linear with the lowest temperature inside the body of ice rather than at the surface. Superimposed ice was present with certainty after May 24. The superimposed ice investigated in early June exhibited a rough texture consistent with meltwater percolation columns in the snow pack. It was found only under snow dunes; no superimposed ice was observed under thin snow (2~cm) or melt ponds. Meltwater collected at topographic low points that surrounded distinct ice islands. Aerial photography and surface LiDAR measurements at various times during the early melt season showed that the location of these ice islands coincided with the locations of wind packed snow dunes that had been tracked since February. The lateral movement of surface waters was relatively slow during the very early stages of melt pond formation. However, we observed a significant lateral redistribution of meltwater under the ice surface; this redistribution happened through distinct veins. The sea ice salinity profiles showed

  12. Chemical processes in the atmosphere-snow-sea ice over the Weddell Sea, Antarctica during winter and spring

    NASA Astrophysics Data System (ADS)

    Jacobi, Hans-Werner; Jourdain, Bruno; Dommergue, Aurelien; Nerentorp Mastromonaco, Michelle; Gardfeldt, Katarina; Abrahamsson, Katarina; Granfors, Anna; Ahnhoff, Martin; Frey, Markus M.; Méjean, Guillaume; Friess, Udo; Nasse, Jan-Marcus

    2016-04-01

    Wintertime chemical processes in the atmosphere-snow-sea ice system of Antarctica are almost unknown because of a lack of in situ observations. During two cruises with the German research icebreaker R/V Polarstern we had the opportunity to perform measurements over and in the sea ice of the Weddell Sea from June to October 2013 covering the transition from winter to spring in the Southern Hemisphere. We performed atmospheric measurements of ozone, mercury, and reactive mercury compounds linked due to so-called ozone and mercury depletion events (ODEs and AMDEs), during which the two normally ubiquitous compounds ozone and mercury are efficiently removed from the atmosphere. Moreover, reactive halogenated compounds as the major cause of these depletion events were also observed in the atmosphere using remote sensing as well as in situ techniques. The observations demonstrated that the formation of reactive halogen compounds as well as depletions of ozone and mercury occurred as early as July potentially caused by a dark halogen activation mechanism. The activation of halogens further left their imprint also in the chemical composition of the snow on top of the sea ice, which showed occasionally a reduction in bromide. Elevated concentrations of halogenated compounds in the sea ice well above levels normally observed during the summer season indicate that active halogen chemistry was not limited to the atmosphere, but impacted the entire atmosphere-snow-sea ice system. Finally, aerosol measurements confirmed that the snow on sea ice constitutes an important surface for the mobilization and generation of atmospheric sea salt aerosol. As a result, sea salt aerosol significantly increased during and after blowing snow events, providing a potentially significant reservoir of atmospheric reactive halogens.

  13. Simulated effects of a snow layer on retrieval of CryoSat-2 sea ice freeboard

    NASA Astrophysics Data System (ADS)

    Kwok, R.

    2014-07-01

    The impact of a snow layer on the location of the tracking point (RP) for ranging to the sea ice surface in CryoSat-2 synthetic aperture interferometric radar altimeter waveforms is simulated. With a range resolution of ~47 cm, the response of the air-snow (a-s) interface broadens the response of the snow-ice (s-i) interface and displaces the RP toward the altimeter. This effect is largest when the strengths of their returns are comparable and when snow thicknesses are >20 cm. On the other hand, the RP is displaced away from the altimeter when the reduced propagation speed in the snow layer is not accounted for. This analysis examines the dependence of these competing corrections on snow thickness and the relative scattering strengths of the interfaces and the sensitivity of two different tracking approaches (leading edge and centroid) to these snow parameters. Expected errors depend on a better understanding of the relative scattering strengths of the interfaces and snow layer.

  14. Revisiting the relationship between Arctic sea-ice thickness and snow depth through climate-model simulations

    NASA Astrophysics Data System (ADS)

    Bunzel, Felix; Notz, Dirk; Toudal Pedersen, Leif

    2016-04-01

    The thickness of snow covering sea ice is a crucial parameter in any algorithm deriving sea-ice thickness from satellite-measured sea-ice freeboard. Here we investigate whether such snow thickness can robustly be estimated by assuming a simple correlation between snow thickness and sea-ice thickness. Such correlation is sometimes applied in schemes that aim at correcting the multi-year Warren snow climatology for the more recent past. In order to quantify the relationship between sea-ice thickness and snow depth, we analyse the correlation of ice thickness and snow depth in a multi-century pre-industrial model simulation and in a transient historical simulation performed with the Max Planck Institute Earth System Model (MPI-ESM). We find correlation coefficients to be low in the central Arctic, while they show substantial regional and temporal variations in the vicinity of the ice edge. Our results point towards possibly substantial errors in algorithms that assume too simplistic a relationship between sea-ice thickness and snow depth.

  15. Snow Radar Derived Surface Elevations and Snow Depths Multi-Year Time Series over Greenland Sea-Ice During IceBridge Campaigns

    NASA Astrophysics Data System (ADS)

    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

  16. Brine-Wetted Snow on the Surface of Sea Ice: A Potentially Vast and Overlooked Microbial Habitat

    NASA Astrophysics Data System (ADS)

    Deming, J. W.; Ewert, M.; Bowman, J. S.; Colangelo-Lillis, J.; Carpenter, S. D.

    2010-12-01

    On the hemispheric scale, snow on the surface of sea ice significantly impacts the exchange of mass and energy across the ocean-ice-atmosphere interface. The snow cover over Arctic sea ice plays a central role in Arctic photochemistry, including atmospheric depletion events at the onset of spring, and in ecosystem support, by determining the availability of photosynthetically active radiation for algal primary production at the bottom of the ice. Among the non-uniformities of snow relevant to its larger-scale roles is salt content. When snow is deposited on the surface of new sea ice, brine expelled onto the ice surface during ice formation wicks into the snow by capillary action, forming a brine-wetted or saline snow layer at the ice-snow interface. A typical salinity for this basal snow layer in the Arctic (measured on a 3-cm depth interval of melted snow) is about 20 (ppt by optical salinometer), with maxima approaching 30 ppt, thus higher than the salinity of melted surface sea ice (< 12 ppt). Although the physical-chemical properties of this brine-wetted layer have been examined in recent years, and the (assumed) air-derived microbial content of overlying low-salinity snow is known to be low in winter, basal saline snow is essentially unexplored as a microbial habitat. As part of an NSF-supported project on frost flowers, we investigated snow overlying coastal sea ice off Barrow, Alaska, in February 2010 (since snow buries frost flowers). Sterile (ethanol-rinsed) tools were used to open snow pits 60 cm wide, record temperature by thermoprobe at 3-cm depth intervals, and collect samples from newly exposed snow walls for salinity (3-cm intervals) and biological measurements (6-cm intervals). The latter included counts of bacterial abundance by epifluorescence microscopy and assays of extracellular polysaccharide substances (EPS). We also sampled snow on a larger scale to extract sufficient DNA to analyze microbial community composition (ongoing work), as well as

  17. Modelling changes in the dielectric and scattering properties of young snow-covered sea ice at GHz frequencies

    NASA Technical Reports Server (NTRS)

    Drinkwater, Mark R.; Crocker, G. B.

    1988-01-01

    Observations of the physical properties of the snow cover and underlying young fast ice in Resolute Passage, Canada, were made during the winter of 1982. Detailed measurements of snow density and ice and snow temperatures, salinities, and brine volumes were made over a period of 46 d, beginning when the ice was 0.4 m thick and about 9 d old. The recorded values are used in a theoretical mixture model to predict the dielectric properties of the snow cover over the microwave frequency range. The results of this analysis are then used to investigate the effects of the snow properties on the radar backscatter signatures of young sea ice. The results show that backscatter is a function of the incidence angle and can change significantly over short periods of time during the early evolutionary phase of ice and snow-cover development. This has important consequences for the identification of young ice forms from SAR or SLAR images.

  18. The role of blowing snow in the activation of bromine over first-year Antarctic sea ice

    NASA Astrophysics Data System (ADS)

    Lieb-Lappen, R. M.; Obbard, R. W.

    2015-07-01

    It is well known that during polar springtime halide sea salt ions, in particular Br-, are photochemically activated into reactive halogen species (e.g., Br and BrO), where they break down tropospheric ozone. This research investigated the role of blowing snow in transporting salts from the sea ice/snow surface into reactive bromine species in the air. At two different locations over first-year ice in the Ross Sea, Antarctica, collection baskets captured blowing snow at different heights. In addition, sea ice cores and surface snow samples were collected throughout the month-long campaign. Over this time, sea ice and surface snow Br- / Cl- mass ratios remained constant and equivalent to seawater, and only in lofted snow did bromide become depleted relative to chloride. This suggests that replenishment of bromide in the snowpack occurs faster than bromine activation in mid-strength wind conditions (approximately 10 m s-1) or that blowing snow represents only a small portion of the surface snowpack. Additionally, lofted snow was found to be depleted in sulfate and enriched in nitrate relative to surface snow.

  19. Soluble chromophores in marine snow, seawater, sea ice and frost flowers near Barrow, Alaska

    NASA Astrophysics Data System (ADS)

    Beine, Harry; Anastasio, Cort; Domine, Florent; Douglas, Thomas; Barret, Manuel; France, James; King, Martin; Hall, Sam; Ullmann, Kirk

    2012-07-01

    We measured light absorption in 42 marine snow, sea ice, seawater, brine, and frost flower samples collected during the OASIS field campaign between February 27 and April 15, 2009. Samples represented multiple sites between landfast ice and open pack ice in coastal areas approximately 5 km west of Barrow, Alaska. The chromophores that are most commonly measured in snow, H2O2, NO3-, and NO2-, on average account for less than 1% of sunlight absorption in our samples. Instead, light absorption is dominated by unidentified "residual" species, likely organic compounds. Light absorption coefficients for the frost flowers on first-year sea ice are, on average, 40 times larger than values for terrestrial snow samples at Barrow, suggesting very large rates of photochemical reactions in frost flowers. For our marine samples the calculated rates of sunlight absorption and OH production from known chromophores are (0.1-1.4) × 1014 (photons cm-3 s-1) and (5-70) × 10-12 (mol L-1 s-1), respectively. Our residual spectra are similar to spectra of marine chromophoric dissolved organic matter (CDOM), suggesting that CDOM is the dominant chromophore in our samples. Based on our light absorption measurements we estimate dissolved organic carbon (DOC) concentrations in Barrow seawater and frost flowers as approximately 130 and 360 μM C, respectively. We expect that CDOM is a major source of OH in our marine samples, and it is likely to have other significant photochemistry as well.

  20. Comparison of simulated spectral bidirectional reflectance function of snow-covered austral summer sea ice with measurements

    NASA Astrophysics Data System (ADS)

    Li, S.; Zhou, X.

    2003-12-01

    The bidirectional reflectance distribution function (BRDF) is an important geophysical variable that provides patterns of surface directional reflectance due to direct beam incidence. Information of BRF is required to derive surface albedo from remote sensing data sets. Also, albedo under various conditions can be evaluated by integration of BRFs. Knowledge of BRF of snow covered sea ice surface is especially important because sea ice exerts a strong positive feedback effect on the surface energy budget, and snow covered sea ice exhibits a strong anisotropic pattern when the solar incidence angle is large. However, it is difficult to obtain a complete data set of snow-covered sea ice surface BRDF through field measurement because of the general paucity of clear sky conditions and the narrow range of solar incidence angles that occur during measurement. The information gap can be filled through validation of the modeled results from radiative transfer simulations. We performed a simulation of snow covered sea ice surface BRF using a multi-layered azimuth- and zenith-dependent plane parallel radiative transfer code. Combined with Mie scattering algorithm, the code takes the measured snow grain sizes, densities and thicknesses of individual layers as input, and generates snow-covered sea ice surface spectral BRF as output. The simulated surface spectral BRF is then compared with measurements. The discrepancies between the model simulation and measurements are analyzed and causes inferred.

  1. The role of blowing snow in the activation of bromine over first-year Antarctic sea ice

    NASA Astrophysics Data System (ADS)

    Lieb-Lappen, R. M.; Obbard, R. W.

    2015-04-01

    It is well known that during polar springtime halide sea salt ions, in particular Br-, are photochemically activated into reactive halogen species (e.g. Br and BrO), where they break down tropospheric ozone. This research investigated the role of blowing snow in transporting salts from the sea ice/snow surface into reactive bromine species in the air. At two different locations over first-year ice in the Ross Sea, Antarctica, collection baskets captured blowing snow at different heights. In addition, sea ice cores and surface snow samples were collected throughout the month-long campaign. Over this time, sea ice and surface snow Cl-/Br- mass ratios remained constant and equivalent to seawater, and only in lofted snow did bromide become depleted relative to chloride. This suggests that replenishment of bromide in the snowpack occurs faster than bromine activation in mid-strength wind conditions (approximately 10 m s-1). Additionally, lofted snow was found to be depleted in sulfate and enriched in nitrate relative to surface snow.

  2. Sea ice and snow thickness and physical properties of an ice floe in the western Weddell Sea and their changes during spring warming

    NASA Astrophysics Data System (ADS)

    Haas, Christian; Nicolaus, Marcel; Willmes, Sascha; Worby, Anthony; Flinspach, David

    2008-04-01

    Helicopter-borne and ground-based electromagnetic (EM) ice thickness and ruler-stick snow thickness measurements as well as ice-core analyses of ice temperature, salinity and texture were performed over a 5-week observation period between November 27, 2004, and January 2, 2005, on an ice floe in the western Weddell Sea at approximately 67°S, 55°W. The study was part of the Ice Station Polarstern (ISPOL) expedition of German research icebreaker R.V. Polarstern, investigating changes of physical, biological, and biogeochemical properties during the spring warming as a function of atmospheric and oceanic boundary conditions. The ice floe was composed of fragments of thin and thick first-year ice and thick second-year ice, with modal total thicknesses of 1.2-1.3, 2.1, and 2.4-2.9 m, respectively. This included modal snow thicknesses of 0.2-0.5 m on first-year ice and 0.75 m on second-year ice. During the observation period, snow thickness decreased by less than 0.2 m. There was hardly any ice thinning. Warming of snow and ice between 0.1 and 1.9 °C resulted in decreased ice salinity and increased brine volume. Direct current (DC) geoelectric and electromagnetic (EM) induction depth sounding were performed to study changes of electrical ice conductivity as a result of the observed ice warming. Bulk ice conductivity increased from to 37 to 97 mS/m. Analysis of conductivity anisotropy showed that the horizontal ice conductivity changed from 9 to 70 mS/m. These conductivity changes have only negligible effects on the thickness retrieval from EM measurements.

  3. Evolution of first-year and second-year snow properties on sea ice in the Weddell Sea during spring-summer transition

    NASA Astrophysics Data System (ADS)

    Nicolaus, Marcel; Haas, Christian; Willmes, Sascha

    2009-09-01

    Observations of snow properties, superimposed ice, and atmospheric heat fluxes have been performed on first-year and second-year sea ice in the western Weddell Sea, Antarctica. Snow in this region is particular as it does usually survive summer ablation. Measurements were performed during Ice Station Polarstern (ISPOL), a 5-week drift station of the German icebreaker RV Polarstern. Net heat flux to the snowpack was 8 W m-2, causing only 0.1 to 0.2 m of thinning of both snow cover types, thinner first-year and thicker second-year snow. Snow thinning was dominated by compaction and evaporation, whereas melt was of minor importance and occurred only internally at or close to the surface. Characteristic differences between snow on first-year and second-year ice were found in snow thickness, temperature, and stratigraphy. Snow on second-year ice was thicker, colder, denser, and more layered than on first-year ice. Metamorphism and ablation, and thus mass balance, were similar between both regimes, because they depend more on surface heat fluxes and less on underground properties. Ice freeboard was mostly negative, but flooding occurred mainly on first-year ice. Snow and ice interface temperature did not reach the melting point during the observation period. Nevertheless, formation of discontinuous superimposed ice was observed. Color tracer experiments suggest considerable meltwater percolation within the snow, despite below-melting temperatures of lower layers. Strong meridional gradients of snow and sea-ice properties were found in this region. They suggest similar gradients in atmospheric and oceanographic conditions and implicate their importance for melt processes and the location of the summer ice edge.

  4. Freeboard, Snow Depth and Sea-Ice Roughness in East Antarctica from In Situ and Multiple Satellite Data

    NASA Technical Reports Server (NTRS)

    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.

  5. Refining the Parameterisation of Sea Salt Aerosol Production from Blowing Snow on Sea Ice Based on Data Collected in the Weddell Sea

    NASA Astrophysics Data System (ADS)

    Yang, X.; Frey, M. M.; Levine, J. G.; Brooks, I. M.; Anderson, P. A.; Jones, A. E.; Wolff, E. W.

    2014-12-01

    The hypothesis of blowing snow lifted snow particles, via a subsequent sublimation process, as a significant sea salt aerosol (SSA) source over sea ice has recently been strongly supported by a winter cruise through the Weddell Sea during June-August 2013. The newly collected data, including both physical and chemical components, provide a unique way to test and validate the parameterisation used to date. The observed salinity of surface and blowing snow is very low; on average more than an order in magnitude smaller than column mean value. Here we apply a low salinity of 0.27 PSU (representing an average of the top 10cm of snow plus blowing snow samples) in the p-TOMCAT model to test its effect on sea salt concentrations reaching the Antarctic. The comparison with previous model output (using column mean salinity) shows that SSA concentration in central Antarctica is insensitive to change in snow salinity, due to the compensating effect of increasing fine SSA partitioning upon reducing the salinity. We also investigate the impact of changing the number of SSA particles formed from each snow particle on SSA concentration and size distribution. Applying a ratio of 10 SSA particles per blowing snow particle, rather than one as assumed to date, greatly increases the amount of sub-micrometer SSA reaching central Antarctica. Without applying blowing snow related SSA production in the p-TOMCAT model, the observed elevated SSA in the Weddell Sea could not be reproduced.

  6. (abstract) A Polarimetric Model for Effects of Brine Infiltrated Snow Cover and Frost Flowers on Sea Ice Backscatter

    NASA Technical Reports Server (NTRS)

    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

  7. The influence of a more realistic representation of snow on sea ice: Results from a coupled, single column model

    NASA Astrophysics Data System (ADS)

    Sewall, J. O.; Lipscomb, W.; Tulaczyk, S.

    2005-12-01

    In the climate system, snow falls in discrete events and, consequently, is deposited in layers. Each layer, depending on initial properties and modification/exposure history has unique physical characteristics. The physical characteristics and number of layers of snow can have a significant influence on the surface energy budget. However, current generation sea ice models represent snow as a single layer with uniform physical properties and, consequently, have difficulty accurately representing surface fluxes over sea ice. In particular, the high-frequency variability that these models fail to capture may play an important role in the onset and end of the melt season which can, in turn, influence ice-albedo feedbacks and the entire polar climate system. We have coupled a single column version of the Los Alamos National Laboratory sea ice model (CICE) to the National Center for Atmospheric Research single column atmosphere model (SCAM). This coupled system is forced and validated with SHEBA (Surface Heat Budget of the Arctic Ocean) reanalysis and observational data to 1) identify the number of snow layers that most accurately represents surface fluxes at the ice/snow/atmosphere interface and 2) investigate the impact of updated and varying snow characteristics.

  8. Daily Accumulated Area of Snow Melt Onset on Arctic Sea Ice

    NASA Astrophysics Data System (ADS)

    Bliss, A. C.; Anderson, M. R.

    2012-12-01

    The ice and snow in the Arctic are vital components of the global climate system, which has seen record-breaking changes in recent years. Changes in the onset of melting in the Arctic during the spring and summer months greatly changes the surface albedo of snow and ice covered surfaces, impacting sea ice loss through the remainder of the melt season. The present study utilizes the date on which melting begins in the snow atop sea ice, derived from passive microwave brightness temperatures from the DMSP SMMR, SSM/I (F08-F13), and SSMIS (F17) platforms, to analyze regional and inter-annual variability in the onset of melting in the Arctic. The Advanced Horizontal Range Algorithm (AHRA) snowmelt onset dates used in this study exploit the changes between 19 GHz (18 GHz for SMMR) and 37 GHz brightness temperatures to derive snow melt onset dates over Arctic sea ice from 1979-2011. Each annual AHRA snowmelt onset date grid indicates the day from the first of the year that melting occurred at each grid point. To analyze snowmelt onset on a daily basis, the annual grids are partitioned by date. A melt onset area is calculated by summing the number of grid points experiencing melt on individual dates then multiplying by the grid resolution to produce an areal extent of melt onset for each date during the melt seasons throughout the study period. By totaling the daily areal extent of melt onset, an accumulation is calculated by summing the area of melt each day throughout the melt season. Variations observed in the melt accumulation pattern through a melt season can be attributed to the weather conditions present at the time of melt onset. Analysis of the daily accumulation of melt area indicates high variability in the timing of snowmelt onset over the 1979-2011 record and a trend towards earlier melt onset dates for the Arctic region as a whole and sub-regionally. The accumulation of melt area through the melt season shows the SMMR years (1979-1987) to generally be below

  9. An Ultra-Wideband, Microwave Radar for Measuring Snow Thickness on Sea Ice and Mapping Near-Surface Internal Layers in Polar Firn

    NASA Technical Reports Server (NTRS)

    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.

  10. NASA sea ice and snow validation plan for the Defense Meteorological Satellite Program special sensor microwave/imager

    NASA Technical Reports Server (NTRS)

    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.

  11. An AeroCom assessment of black carbon in Arctic snow and sea ice

    SciTech Connect

    Jiao, C.; Flanner, M. G.; Balkanski, Y.; Bauer, S. E.; Bellouin, N.; Berntsen, T. K.; Bian, H.; Carslaw, K. S.; Chin, M.; De Luca, N.; Diehl, T.; Ghan, S. J.; Iversen, T.; Kirkevåg, A.; Koch, D.; Liu, X.; Mann, G. W.; Penner, J. E.; Pitari, G.; Schulz, M.; Seland, Ø.; Skeie, R. B.; Steenrod, S. D.; Stier, P.; Takemura, T.; Tsigaridis, K.; van Noije, T.; Yun, Y.; Zhang, K.

    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 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-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

  12. An AeroCom Assessment of Black Carbon in Arctic Snow and Sea Ice

    NASA Technical Reports Server (NTRS)

    Jiao, C.; Flanner, M. G.; Balkanski, Y.; Bauer, S. E.; Bellouin, N.; Bernsten, T. K.; Bian, H.; Carslaw, K. S.; Chin, M.; DeLuca, N.; Diehl, T.; Ghan, S. J.; Iversen, T.; Kirkevag, A.; Koch, D.; Liu, X.; Mann, G. W.; Penner, J. E.; Pitari, G.; Schulz, M.; Seland, O; Skeie, R. B.; Steenrod, S. D.; Stier, P.; Tkemura, T.

    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

  13. An Ultra Wide-Band Radar Altimeter for Ice Sheet Surface Elevation and Snow Cover Over Sea Ice Measurement

    NASA Astrophysics Data System (ADS)

    Patel, A. E.; Gogineni, P. S.; Leuschen, C.; Rodriguez-Morales, F.; Panzer, B.

    2010-12-01

    The Ice sheets of Greenland and Antarctica are losing mass at a rapid rate and there has been significant decrease in sea ice volume over the last few years. CryoSat-II with optimized radar altimeter for ice-sheet and sea ice surface elevation measurements is launched. We developed ultra wide-band FM-CW radar that operates over the frequency range from 13-17 GHz for airborne measurements. The radar is designed to provide high-resolution surface-elevation data and also map near surface layers in polar firn with high precision. It is designed to generate an ultra linear transmit chirp using a fast settling PLL with a reference signal from Direct Digital Synthesizer (DDS). The pulse length of the transmit chirp is 240-us and pulse repetition frequency is 2-KHz. The peak transmit power of the system is 100-mW, radiated using horn antennas. The radar was deployed in Greenland and Antarctica in 2009-10 as a part of Operation Ice Bridge campaign to collect data in conjunction with other instruments including Airborne Topographic Mapper (ATM) and Digital Mapping System Camera (DMS). The radar also collected data under the Cryosat-II path. This paper will provide an overview of the Ku-Band radar design along with results from the 2009-2010 field campaigns. The data collected over polar firn shows near surface internal layers down to a depth of about 15-m with a resolution of 15-cm. When flying over sea ice the radar provides snow cover thickness data to a depth of about 0.5-m. Even over highly crevassed areas, such as outlet glaciers, the radar is able to detect large surface elevation changes of a few tens of meters with high resolution.

  14. Sea Ice, Hydrocarbon Extraction, Rain-on-Snow and Tundra Reindeer Nomadism in Arctic Russia

    NASA Astrophysics Data System (ADS)

    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

  15. Optical remote sensing of snow on sea ice: Ground measurements, satellite data analysis, and radiative transfer modeling

    NASA Astrophysics Data System (ADS)

    Zhou, Xiaobing

    2002-01-01

    The successful launch of the Terra satellite on December 18, 1999 opened a new era of earth observation from space. This thesis is motivated by the need for validation and promotion of the use of snow and sea ice products derived from MODIS, one of the main sensors aboard the Terra and Aqua satellites. Three cruises were made in the Southern Ocean, in the Ross, Amundsen and Bellingshausen seas. Measurements of all-wave albedo, spectral albedo, BRDF, snow surface temperature, snow grain size, and snow stratification etc. were carried out on pack ice floes and landfast ice. In situ measurements were also carried out concurrently with MODIS. The effect of snow physical parameters on the radiative quantities such as all-wave albedo, spectral albedo and bidirectional reflectance are studied using statistical techniques and radiative transfer modeling, including single scattering and multiple scattering. The whole thesis consists of six major parts. The first part (chapter 1) is a review of the present research work on the optical remote sensing of snow. The second part (chapter 2) describes the instrumentation and data-collection of ground measurements of all-wave albedo, spectral albedo and bidirectional reflectance distribution function (BRDF) of snow and sea ice in the visible-near-infrared (VNIR) domain in Western Antarctica. The third part (chapter 3) contains a detailed multivariate correlation and regression analysis of the measured radiative quantities with snow physical parameters such as snow density, surface temperature, single and composite grain size and number density. The fourth part (chapter 4) describes the validation of MODIS satellite data acquired concurrently with the ground measurements. The radiances collected by the MODIS sensor are converted to ground snow surface reflectances by removing the atmospheric effect using a radiative transfer algorithm (6S). Ground measured reflectance is corrected for ice concentration at the subpixel level so that

  16. Correlations between Inter-Annual Variations in Arctic Sea Ice Extent, Greenland Surface Melt, and Boreal Snow Cover

    NASA Technical Reports Server (NTRS)

    Markus, Thorstena; Stroeve, Julienne C.; Armstrong, Richard L.

    2004-01-01

    Intensification of global warming in recent decades has caused a rise of interest in year-to-year and decadal-scale climate variability in the Arctic. This is because the Arctic is believed to be one of the most sensitive and vulnerable regions to climatic changes. For over two decades satellite passive microwave observations have been utilized to continuously monitor the Arctic environment. Derived parameters include sea ice cover, snow cover and snow water equivalent over land, and Greenland melt extent and length of melt season. Most studies have primarily concentrated on trends and variations of individual variables. In this study we investigated how variations in sea ice cover, Greenland surface melt, and boreal snow cover are correlated. This was done on hemispheric as well as on regional scales. Latest results will be presented including data from the summer of 2004.

  17. Development of a one-dimensional electro-thermophysical model of the snow sea-ice system: Arctic climate processes and microwave remote sensing applications

    NASA Astrophysics Data System (ADS)

    Hanesiak, John Michael

    Snow covered sea ice plays a crucial role in the earth's climate. This includes polar biology, local, regional and world weather and ocean circulations as well as indigenous people's way of life. Recent research has indicated significant climate change in the polar regions, especially the Canadian arctic. Polar climate processes are also among the most poorly misrepresented within global circulation models (GCMs). The goal of this thesis is to improve our understanding and capability to simulate arctic climate processes in a predictive sense. An electro-thermophysical relationship exists between the thermophysical characteristics (climate variables and processes) and electrical properties (dielectrics) that control microwave remote sensing of snow-covered first- year sea ice (FYI). This work explicitly links microwave dielectrics and a thermodynamic model of snow and sea ice by addressing four key issues. These includes: (1)ensure the existing one-dimensional sea ice models treat the surface energy balance (SEB) and snow/ice thermodynamics in the appropriate time scales we see occurring in field experiments, (2)ensure the snow/ice thermodynamics are not compromised by differences in environmental and spatial representation within components of the SEB, (3)ensure the snow layer is properly handled in the modeling environment, and (4)how we can make use of satellite microwave remote sensing data within the model environment. Results suggest that diurnal processes are critical and need to be accounted for in modeling snow-covered FYI, similar to time scales acting in microwave remote sensing signatures. Output from the coupled snow sea-ice model provides the required input to microwave dielectric models of snow and sea ice to predict microwave penetration depths within the snow and sea ice (an Electro-Thermophysical model of the Snow Sea Ice System (ETSSIS)). Results suggest ETSSIS can accurately simulate microwave penetration depths in the cold dry snow season and

  18. Interannual variations of light-absorbing particles in snow on Arctic sea ice

    NASA Astrophysics Data System (ADS)

    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.

  19. Bacterial and extracellular polysaccharide content of brine-wetted snow over Arctic winter first-year sea ice

    NASA Astrophysics Data System (ADS)

    Ewert, M.; Carpenter, S. D.; Colangelo-Lillis, J.; Deming, J. W.

    2013-02-01

    During freeze-up and consolidation, sea ice rejects to its surface brine of marine origin that is incorporated into overlying snow. To evaluate the transport of biological components in brines from ice to snow, vertical profiles of temperature, salinity, bacterial abundance, and extracellular polysaccharide substances (EPS) were obtained through snow and first-year sea ice (Barrow, AK) in consecutive winters (2010, 2011). Snow profiles showed strong interannual variation, with 2010 presenting higher values and wider ranges in salinity (0.3-30.9, practical salinity), bacterial abundance (2.8 × 102-1.5 × 104 cells mL- 1), and particulate EPS (pEPS, 0.04-0.23 glucose equivalents (glu-eq) mg L- 1) than 2011 (0-11.9, 2.7 × 103-4.2 × 103 cells mL- 1 and 0.04-0.09 glu-eq mg L- 1, respectively). Surface ice also differed interannually, with 2010 presenting again higher salinity (19.4, n = 1), bacterial abundance (5.4 × 104-9.6 × 104 cells mL- 1) and pEPS (0.13-0.51 glu-eq mg L- 1) than 2011 (7.7-11.9, 1.7 × 104-2.2 × 104 cells mL- 1, and 0.01-0.09 glu-eq mg L- 1, respectively). Transport of bacteria and pEPS from sea-ice brines into snow was evident in 2010 but not 2011, a year with more extreme winter conditions of colder temperature, thinner snow, and stronger wind. By size fraction, the smallest EPS (< 0.1 µm) dominated (> 80%) total EPS in both ice and snow; the > 3 µm fraction of EPS in snow appeared to have an atmospheric source. Evaluation of membrane integrity by Live/Dead stain revealed a high percentage (85%) of live bacteria in saline snow, identifying this vast environment as a previously unrecognized microbial habitat.

  20. Recent progress in snow and ice research

    SciTech Connect

    Richter-menge, J.A.; Colbeck, S.C.; Jezek, K.C. )

    1991-01-01

    A review of snow and ice research in 1987-1990 is presented, focusing on the effects of layers in seasonal snow covers, ice mechanics on fresh water and sea ice, and remote sensig of polar ice sheets. These topics provide useful examples of general needs in snow and ice research applicable to most areas, such as better representation in models of detailed processes, controlled laboratory experiments to quantify processes, and field studies to provide the appropriate context for interpretation of processes from remote sensing.

  1. The Role of Snow Thickness over Arctic Winter Sea Ice in the Survival and Dispersal of Brine-Derived Microbes

    NASA Astrophysics Data System (ADS)

    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

  2. Projected Arctic warming, rapid sea ice loss, and snow state changes: Influence on near- surface permafrost degradation

    NASA Astrophysics Data System (ADS)

    Lawrence, D. M.; Slater, A. G.

    2008-12-01

    Projected climatic changes in the Arctic associated with increasing greenhouse gas concentrations are varied. Global climate models suggest that warming in the Arctic will be considerably stronger than the rest of the world. In the Community Climate System Model (CCSM3), 21st century terrestrial Arctic warming ranges from ~+4 to +8° C depending on emission scenario. This warming is non-linear, due in part, to periods of accelerated sea ice loss. Along with the warming, CCSM3 (and other global models) project an increase in winter snowfall and concomitant changes in snow depth, snow density, and snow-season length. Here, we evaluate the roles of Arctic warming, accelerated sea ice loss, and snow state changes on the rate and extent of soil warming and permafrost degradation. We utilize the Community Land Model (CLM) with improved permafrost dynamics to evaluate and compare the large-scale near-surface permafrost response to these climatic forcings. The strong projected warming is, not surprisingly the biggest contributor to permafrost degradation. However, we can attribute roughly 18 percent of the permafrost degradation to increasing snowfall and the resulting maintenance of the insulating snowpack even in the face of strong warming. We also find that a period of accelerated warming associated with rapid sea ice loss can accelerate soil warming and lead to rapid thaw of warmer permafrost and to increased vulnerability of colder permafrost.

  3. Climate response of fossil fuel and biofuel soot, accounting for soot's feedback to snow and sea ice albedo and emissivity

    NASA Astrophysics Data System (ADS)

    Jacobson, Mark Z.

    2004-11-01

    The first three-dimensional global model in which time-dependent spectral albedos and emissivities over snow and sea ice are predicted with a radiative transfer solution, rather than prescribed, is applied to study the climate response of fossil fuel plus biofuel black carbon plus organic matter (ff+bf BC+OM) when BC absorption in snow and sea ice is accounted for. The model treats the cycling of size-resolved BC+OM between emission and removal by dry deposition and precipitation from first principles. Particles produce and enter size-resolved clouds and precipitation by nucleation scavenging and aerosol-hydrometeor coagulation. Removal brings BC to the surface, where internally and externally mixed BC in snow and sea ice affects albedo and emissivity through radiative transfer. Climate response simulations were run with a ff+bf BC+OC emission inventory lower than that used in a previous study. The 10-year, globally averaged ff+bf BC+OM near-surface temperature response due to all feedbacks was about +0.27 K (+0.32 in the last 3 years), close to those from the previous study (5-year average of +0.3 K and fifth-year warming of +0.35 K) and its modeled range (+0.15 to +0.5 K) because warming due to soot absorption in snow and sea ice here (10-year average of +0.06 K with a modeled range of +0.03 to +0.11 K) offset reduced warming due to lower emission. BC was calculated to reduce snow and sea ice albedo by ˜0.4% in the global average and 1% in the Northern Hemisphere. The globally averaged modeled BC concentration in snow and sea ice was ˜5 ng/g; that in rainfall was ˜22 ng/g. About 98% of BC removal from the atmosphere was due to precipitation; the rest was due to dry deposition. The results here support previous findings that controlling ff+bf BC+OM and CO2 emission may slow global warming.

  4. Remote sensing of snow and ice

    NASA Technical Reports Server (NTRS)

    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.

  5. A Comparison of Snow Depth on Sea Ice Retrievals Using Airborne Altimeters and an AMSR-E Simulator

    NASA Technical Reports Server (NTRS)

    Cavalieri, D. J.; Marksu, T.; Ivanoff, A.; Miller, J. A.; Brucker, L.; Sturm, M.; Maslanik, J. A.; Heinrichs, J. F.; Gasiewski, A.; Leuschen, C.; Krabill, W.; Sonntag, J.

    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.

  6. Snow melt on sea ice surfaces as determined from passive microwave satellite data

    NASA Technical Reports Server (NTRS)

    Anderson, Mark R.

    1987-01-01

    SMMR data for the year 1979, 1980 and 1984 have been analyzed to determine the variability in the onset of melt for the Arctic seasonal sea ice zone. The results show melt commencing in either the Kara/Barents Seas or Chukchi Sea and progressing zonally towards the central Asian coast (Laptev Sea). Individual regions had interannual variations in melt onset in the 10-20 day range. To determine whether daily changes occur in the sea ice surface melt, the SMMR 18 and 37 GHz brightness temperature data are analyzed at day/night/twilight periods. Brightness temperatures illustrate diurnal variations in most regions during melt. In the East Siberian Sea, however, daily variations are observed in 1979, throughout the analysis period, well before any melt would usually have commenced. Understanding microwave responses to changing surface conditions during melt will perhaps give additional information about energy budgets during the winter to summer transition of sea ice.

  7. 2013 Arctic Sea Ice Minimum

    NASA Video Gallery

    After an unusually cold summer in the northernmost latitudes, Arctic sea ice appears to have reached its annual minimum summer extent for 2013 on Sept. 13, the NASA-supported National Snow and Ice ...

  8. Snow and ice products from Suomi NPP VIIRS

    NASA Astrophysics Data System (ADS)

    Key, Jeffrey R.; Mahoney, Robert; Liu, Yinghui; Romanov, Peter; Tschudi, Mark; Appel, Igor; Maslanik, James; Baldwin, Dan; Wang, Xuanji; Meade, Paul

    2013-12-01

    Visible Infrared Imager Radiometer Suite (VIIRS) instrument was launched in October 2011 on the satellite now known as the Suomi National Polar-orbiting Partnership. VIIRS was designed to improve upon the capabilities of the operational Advanced Very High Resolution Radiometer and provide observation continuity with NASA's Earth Observing System's Moderate Resolution Imaging Spectroradiometer (MODIS). VIIRS snow and ice products include sea ice surface temperature, sea ice concentration, sea ice characterization, a binary snow map, and fractional snow cover. Validation results with these "provisional" level maturity products show that ice surface temperature has a root-mean-square error of 0.6-1.0 K when compared to aircraft data and a similar MODIS product, the measurement accuracy and precision of ice concentration are approximately 5% and 15% when compared to passive microwave retrievals, and the accuracy of the binary snow cover (snow/no-snow) maps is generally above 90% when compared to station data. The ice surface temperature and snow cover products meet their accuracy requirements with respect to the Joint Polar Satellite System Level 1 Requirements Document. Sea Ice Characterization, which consists of two age categories, has not been observed to meet the 70% accuracy requirements of ice classification. Given their current performance, the ice surface temperature, snow cover, and sea ice concentration products should be useful for both research and operational applications, while improvements to the sea ice characterization product are needed before it can be used for these applications.

  9. Characterization of Aerosols and Bidirectional Reflectance Distribution Function from Airborne Radiation Measurements over Snow, Sea Ice, Tundra, And Clouds

    NASA Astrophysics Data System (ADS)

    Gatebe, C. K.; King, M. D.

    2009-12-01

    The Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) provides a golden opportunity to study the Arctic from ground-, airborne-, and satellite-based measurements in an integrated manner. It also provides an opportunity to validate satellite retrievals that are complicated by the highly reflecting nature of snow-covered sea ice, low sun angles, extensive cloud cover, and seasonal changes. The bidirectional reflectance distribution function (BRDF) or accurate determination of surface albedo is a key to detecting changes in the arctic environment from remote sensing measurements. The Cloud Absorption Radiometer (CAR) has been used to acquire spectral BRDF of the ocean, sea ice, snow, tundra, savanna, smoke, vegetation, desert, salt pans, and clouds, and played a key role in the ARCTAS deployment in spring and summer of 2008. This airborne sensor has a wide aperture of 190°, an instantaneous Field of View of 1°, and can capture the full BRDF, including the hotspot under low sun angle conditions commonly found in the Arctic. The instrument was developed for low- to medium-altitude aircraft and can be used to obtain data with varying spatial resolutions that are important for addressing upscaling needs for satellite validation. The instrument has a unique ability to measure almost simultaneously, both downwelling and upwelling radiance at 14 narrow spectral bands located in the atmospheric window regions of the ultraviolet, visible and near-infrared. When combined with simultaneous airborne measurements of sun/sky radiance, the CAR sky radiance measurements provide information on aerosol (size distribution, single scattering albedo, refractive index) both above and below the aircraft. The intent of this paper is to highlight some of the key results obtained from the analysis of the CAR data from ARCTAS, including retrieval of aerosols and bidirectional reflectance factors over snow and validation of satellite & model snow

  10. The Role of Snow and Ice in the Climate System

    ScienceCinema

    Barry, Roger G.

    2009-09-01

    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.

  11. The Role of Snow and Ice in the Climate System

    SciTech Connect

    Barry, Roger G.

    2007-12-19

    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.

  12. Near Real Time Sea Ice Thickness from the CryoSat-2 Satellite, and the application of a time-varying snow load

    NASA Astrophysics Data System (ADS)

    Tilling, R.; Ridout, A.; Shepherd, A.; Muir, A.

    2015-12-01

    Since October 2010, data from the European Space Agency (ESA) CryoSat-2 (CS-2) satellite has provided the means to produce sea ice thickness maps across the entire Arctic Ocean basin. These large-scale observations of Arctic sea ice thickness are required to determine trends, compare hemispheres and aid predictive models of future global climate change. However, the final ESA data product is not available until ~30 days after the satellite acquisition, and as such the use of the data for near real time (NRT), operational purposes, has not been possible. At University College London (UCL) we now produce the first NRT estimates of Arctic sea ice thickness, with a lag of only 2 days, using NRT data that has recently been released by ESA. This original, operational dataset will benefit industries such as transport and tourism, as well as the scientific community. This presentation will summarise the NRT product and the data that is avilable, investigate the differences between the NRT and final product, and analyse its reliability and data coverage in particular regions of interest (e.g. the Northwest Passage, and the Beaufort Sea). We have also developed an Arctic-wide, time-varying snow load, so that our CryoSat-2 sea ice processing no longer relies on a constant monthly snow climatology. This presentation will summarise the development, application, and benefits of the new snow load in relation to our NRT and final sea ice thickness estimates.

  13. 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

    NASA Astrophysics Data System (ADS)

    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

  14. Snow cover and short-term synoptic events drive biogeochemical dynamics in winter Weddell Sea pack ice (AWECS cruise - June to August 2013)

    NASA Astrophysics Data System (ADS)

    Tison, Jean-Louis; Delille, Bruno; Dieckmann, Gherard; de Jong, Jeroen; Janssens, Julie; Rintala, Janne; Luhtanen, Annemari; Gussone, Niklaus; Uhlig, Christiane; Nomura, Daïki; Schoemann, Véronique; Zhou, Jiayun; Carnat, Gauthier; Fripiat, François

    2014-05-01

    This paper presents the preliminary results of an integrated multidisciplinary study of pack ice biogeochemistry in the Weddell Sea during the winter 2013 (June-August). The sea ice biogeochemistry group was one of the components of the AWECS (Antarctic Winter Ecosystem and Climate Study) cruise (Polarstern ANTXXIX-6). A total of 12 stations were carried out by the sea ice biogeochemistry group, which collected a suite of variables in the fields of physics, inorganic chemistry, gas content and composition, microbiology, biogeochemistry, trace metals and the carbonate system in order to give the best possible description of the sea ice cover and its interactions at interfaces. Samples were collected in the atmosphere above (gas fluxes), in the snow cover, in the bulk ice (ice cores), in the brines (sackholes) and in the sea water below (0m, 1m, 30 m). Here we present the results of basic physico-chemical (T° , bulk ice salinity, brine volumes, brine salinity, Rayleigh numbers) and biological (Chla) measurements in order to give an overview of the general status of the Weddell Sea winter pack ice encountered, and discuss how it controls climate relevant biogeochemical processes. Our results from the first set of 9 stations, mainly sampled along the Greenwich meridian and the easternmost part of the Weddell Sea definitively refute the view of a biogeochemically 'frozen' sea ice during the Winter. This has already been demonstrated for the Spring and Summer, but we now see that sea ice sustains considerable biological stocks and activities throughout the Winter, despite the reduced amount of available PAR radiation. Accretion of the snow cover appears to play an essential role in driving biogeochemical activity, through warming from insulation, thus favouring brine transport, be it through potential convection, surface brine migration (brine tubes) or flooding. This results in a 'widening' of the internal autumn layer (quite frequent in this rafting-dominated sea ice

  15. Impact of snow accumulation on CryoSat-2 range retrievals over Arctic sea ice: An observational approach with buoy data

    NASA Astrophysics Data System (ADS)

    Ricker, Robert; Hendricks, Stefan; Perovich, Donald K.; Helm, Veit; Gerdes, Rüdiger

    2015-06-01

    Radar altimetry measurements of the current satellite mission CryoSat-2 show an increase of Arctic sea ice thickness in autumn 2013, compared to previous years but also related to March 2013. Such an increase over the melting season seems unlikely and needs to be investigated. Recent studies show that the influence of the snow cover is not negligible and can highly affect the CryoSat-2 range retrievals if it is assumed that the main scattering horizon is given by the snow-ice interface. Our analysis of Arctic ice mass balance buoy records and coincident CryoSat-2 data between 2012 and 2014 adds observational evidence to these findings. Linear trends of snow and ice freeboard measurements from buoys and nearby CryoSat-2 freeboard retrievals are calculated during accumulation events. We find a positive correlation between buoy snow freeboard and CryoSat-2 freeboard estimates, revealing that early snow accumulation might have caused a bias in CryoSat-2 sea ice thickness in autumn 2013.

  16. Sea Ice

    NASA Technical Reports Server (NTRS)

    Parkinson, Claire L.; Cavalieri, Donald J.

    2005-01-01

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

  17. Sea Ice

    NASA Technical Reports Server (NTRS)

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

    2013-01-01

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

  18. A Blowing Snow Model for Ice Shelf Rifts

    NASA Astrophysics Data System (ADS)

    Leonard, K. C.; Tremblay, L.; Macayeal, D. R.

    2005-12-01

    Ice melange (a mixture of snow, marine ice, and ice talus) may play various roles in the rates of propagation of iceberg-calving rifts through Antarctic ice shelves. This modeling study examines the role of windblown snow in the formation and maintenance of ice melange in the "nascent rift" in the Ross Ice Shelf (78 08'S, 178 29'W). The rift axis is perpendicular to the regional wind direction, allowing us to employ a two-dimensional blowing snow model. The Piektuk-Tuvaq blowing snow model (Dery and Tremblay, 2004) adapted the Piektuk blowing snow model for use in sea ice environments by including parameterization for open-water leads within the sea ice. This version of the model was used to study the initial conditions of a freshly-opened rift, as the input of blowing snow into the seawater within the rift promotes marine ice formation by cooling and freshening the surface water. We adapted the Piektuk-Tuvaq model both for the local climatic conditions and to incorporate the geometry of the rift, which is 30m deep and 100m wide (far deeper than a lead). We present the evolution of the topography within the rift for two cases. The first is an ice melange composed exclusively of snow and marine ice, the second uses an initial topography including large chunks of ice talus.

  19. The role of sea ice dynamics in global climate change

    NASA Technical Reports Server (NTRS)

    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.

  20. Snow and ice in a changing hydrological world.

    USGS Publications Warehouse

    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

  1. Primary Production in Antarctic Sea Ice

    NASA Technical Reports Server (NTRS)

    Arrigo, Kevin R.; Worthen, Denise L.; Lizotte, Michael P.; Dixon, Paul; Dieckmann, Gerhard

    1997-01-01

    A numerical model shows that in Antarctic sea ice, increased flooding in regions with thick snow cover enhances primary production in the infiltration (surface) layer. Productivity in the freeboard (sea level) layer is also determined by sea ice porosity, which varies with temperature. Spatial and temporal variation in snow thickness and the proportion of first-year ice thus determine regional differences in sea ice primary production. Model results show that of the 40 tera-grams of carbon produced annually in the Antarctic ice pack, 75 percent was associated with first-year ice and nearly 50 percent was produced in the Weddell Sea.

  2. Snow and Ice Products from the Moderate Resolution Imaging Spectroradiometer

    NASA Technical Reports Server (NTRS)

    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.

  3. Frost flowers growing in the Arctic ocean-atmosphere-sea ice-snow interface: 1. Chemical composition

    NASA Astrophysics Data System (ADS)

    Douglas, Thomas A.; Domine, Florent; Barret, Manuel; Anastasio, Cort; Beine, Harry J.; Bottenheim, Jan; Grannas, Amanda; Houdier, Stephan; Netcheva, Stoyka; Rowland, Glenn; Staebler, Ralf; Steffen, Alexandra

    2012-07-01

    Frost flowers, intricate featherlike crystals that grow on refreezing sea ice leads, have been implicated in lower atmospheric chemical reactions. Few studies have presented chemical composition information for frost flowers over time and many of the chemical species commonly associated with Polar tropospheric reactions have never been reported for frost flowers. We undertook this study on the sea ice north of Barrow, Alaska to quantify the major ion, stable oxygen and hydrogen isotope, alkalinity, light absorbance by soluble species, organochlorine, and aldehyde composition of seawater, brine, and frost flowers. For many of these chemical species we present the first measurements from brine or frost flowers. Results show that major ion and alkalinity concentrations, stable isotope values, and major chromophore (NO3- and H2O2) concentrations are controlled by fractionation from seawater and brine. The presence of these chemical species in present and future sea ice scenarios is somewhat predictable. However, aldehydes, organochlorine compounds, light absorbing species, and mercury (part 2 of this research and Sherman et al. (2012)) are deposited to frost flowers through less predictable processes that probably involve the atmosphere as a source. The present and future concentrations of these constituents in frost flowers may not be easily incorporated into future sea ice or lower atmospheric chemistry scenarios. Thinning of Arctic sea ice will likely present more open sea ice leads where young ice, brine, and frost flowers form. How these changing ice conditions will affect the interactions between ice, brine, frost flowers and the lower atmosphere is unknown.

  4. NASA Sea Ice and Snow Validation Program for the DMSP SSM/I: NASA DC-8 flight report

    NASA Technical Reports Server (NTRS)

    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.

  5. Cold, Ice, and Snow Safety (For Parents)

    MedlinePlus

    ... to Know About Zika & Pregnancy Cold, Ice, and Snow Safety KidsHealth > For Parents > Cold, Ice, and Snow Safety Print A A A Text Size What's ... a few. Plus, someone has to shovel the snow, right? Once outdoors, however, take precautions to keep ...

  6. Biogeochemistry in Sea Ice: CICE model developments

    SciTech Connect

    Jeffery, Nicole; Hunke, Elizabeth; Elliott, Scott; Turner, Adrian

    2012-06-18

    Polar primary production unfolds in a dynamic sea ice environment, and the interactions of sea ice with ocean support and mediate this production. In spring, for example, fresh melt water contributes to the shoaling of the mixed layer enhancing ice edge blooms. In contrast, sea ice formation in the fall reduces light penetration to the upper ocean slowing primary production in marine waters. Polar biogeochemical modeling studies typically consider these types of ice-ocean interactions. However, sea ice itself is a biogeochemically active medium, contributing a significant and, possibly, essential source of primary production to polar regions in early spring and fall. Here we present numerical simulations using the Los Alamos Sea Ice Model (CICE) with prognostic salinity and sea ice biogeochemistry. This study investigates the relationship between sea ice multiphase physics and sea ice productivity. Of particular emphasis are the processes of gravity drainage, melt water flushing, and snow loading. During sea ice formation, desalination by gravity drainage facilitates nutrient exchange between ocean and ice maintaining ice algal blooms in early spring. Melt water flushing releases ice algae and nutrients to underlying waters limiting ice production. Finally, snow loading, particularly in the Southern Ocean, forces sea ice below the ocean surface driving an upward flow of nutrient rich water into the ice to the benefit of interior and freeboard communities. Incorporating ice microphysics in CICE has given us an important tool for assessing the importance of these processes for polar algal production at global scales.

  7. Sea ice-albedo climate feedback mechanism

    SciTech Connect

    Schramm, J.L.; Curry, J.A.; Ebert, E.E.

    1995-02-01

    The sea ice-albedo feedback mechanism over the Arctic Ocean multiyear sea ice is investigated by conducting a series of experiments using several one-dimensional models of the coupled sea ice-atmosphere system. In its simplest form, ice-albedo feedback is thought to be associated with a decrease in the areal cover of snow and ice and a corresponding increase in the surface temperature, further decreasing the area cover of snow and ice. It is shown that the sea ice-albedo feedback can operate even in multiyear pack ice, without the disappearance of this ice, associated with internal processes occurring within the multiyear ice pack (e.g., duration of the snow cover, ice thickness, ice distribution, lead fraction, and melt pond characteristics). The strength of the ice-albedo feedback mechanism is compared for several different thermodynamic sea ice models: a new model that includes ice thickness distribution., the Ebert and Curry model, the Mayjut and Untersteiner model, and the Semtner level-3 and level-0 models. The climate forcing is chosen to be a perturbation of the surface heat flux, and cloud and water vapor feedbacks are inoperative so that the effects of the sea ice-albedo feedback mechanism can be isolated. The inclusion of melt ponds significantly strengthens the ice-albedo feedback, while the ice thickness distribution decreases the strength of the modeled sea ice-albedo feedback. It is emphasized that accurately modeling present-day sea ice thickness is not adequate for a sea ice parameterization; the correct physical processes must be included so that the sea ice parameterization yields correct sensitivities to external forcing. 22 refs., 6 figs., 1 tab.

  8. Sea ice data for all: NSIDC's Arctic Sea Ice News & Analysis

    NASA Astrophysics Data System (ADS)

    Vizcarra, N.; Stroeve, J. C.; Serreze, M. C.; Scambos, T. A.; Meier, W.

    2014-12-01

    Arctic sea ice has long been recognized as a sensitive climate indicator and has undergone a dramatic decline over the past thirty years. The National Snow and Ice Data Center's Arctic Sea Ice News & Analysis blog continues to offer the public a transparent view of sea ice data and analysis. We have expanded our interactive sea ice graph to include Antarctic sea ice in response to increased attention from the public as a result of unexpected behavior of sea ice in the south. This poster explores the blog's new features and how other researchers, the media, and the public are currently using them.

  9. 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)

    NASA Astrophysics Data System (ADS)

    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, doi:10.5194/acp-14-1587-2014, 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.

  10. Development of an autonomous sea ice tethered buoy for the study of ocean-atmosphere-sea ice-snow pack interactions: the O-buoy

    NASA Astrophysics Data System (ADS)

    Knepp, T. N.; Bottenheim, J.; Carlsen, M.; Carlson, D.; Donohoue, D.; Friederich, G.; Matrai, P. A.; Netcheva, S.; Perovich, D. K.; Santini, R.; Shepson, P. B.; Simpson, W.; Valentic, T.; Williams, C.; Wyss, P. J.

    2010-02-01

    A buoy based instrument platform (the "O-buoy") was designed, constructed, and field tested for year-round measurement of ozone, bromine monoxide, carbon dioxide, and meteorological variables over Arctic sea ice. The O-buoy operated in an autonomous manner with daily, bi-directional data transmissions using Iridium satellite communication. The O-buoy was equipped with three power sources: primary lithium-ion battery packs, rechargeable lead acid packs, and solar panels that recharge the lead acid packs, and can fully power the O-buoy during summer operation. This system was designed to operate under the harsh conditions present in the Arctic, with minimal direct human interaction, to aid in our understanding of the atmospheric chemistry that occurs in this remote region of the world. The current design requires approximately yearly maintenance limited by the lifetime of the primary power supply. The O-buoy system was field tested in Elson Lagoon, Barrow, Alaska from February to May 2009, and deployed in the Beaufort Sea in October 2009. Here, we describe the design and present preliminary data.

  11. Synoptic controls on precipitation pathways and snow delivery to high-accumulation ice core sites in the Ross Sea region, Antarctica

    NASA Astrophysics Data System (ADS)

    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.

  12. Sea ice terminology

    SciTech Connect

    Not Available

    1980-09-01

    A group of definitions of terms related to sea ice is presented, as well as a graphic representation of late winter ice zonation of the Beaufort Sea Coast. Terms included in the definition list are belt, bergy bit, bight, brash ice, calving, close pack ice, compacting, compact pack ice, concentration, consolidated pack ice, crack, diffuse ice edge, fast ice, fast-ice boundary, fast-ice edge, first-year ice, flaw, flaw lead, floe, flooded ice, fractured, fractured zone, fracturing, glacier, grey ice, grey-white ice, growler, hummock, iceberg, iceberg tongue, ice blink, ice boundary, ice cake, ice edge, ice foot, ice free, ice island, ice shelf, large fracture, lead, medium fracture, multiyear ice, nilas, old ice, open pack ice, open water, pack ice, polar ice, polynya, puddle, rafted ice, rafting, ram, ridge, rotten ice, second-year ice, shearing, shore lead, shore polynya, small fracture, strip, tabular berg, thaw holes, very close pack ice, very open pack ice, water sky, young coastal ice, and young ice.

  13. Development of an autonomous sea ice tethered buoy for the study of ocean-atmosphere-sea ice-snow pack interactions: the O-buoy

    NASA Astrophysics Data System (ADS)

    Knepp, T. N.; Bottenheim, J.; Carlsen, M.; Carlson, D.; Donohoue, D.; Friederich, G.; Matrai, P. M.; Netcheva, S.; Perovich, D. K.; Santini, R.; Shepson, P. B.; Simpson, W.; Stehle, R.; Valentic, T.; Williams, C.; Wyss, P. J.

    2009-09-01

    A buoy based instrument platform (the "O-buoy") was designed, constructed, and field tested for year-round measurement of ozone, bromine monoxide, carbon dioxide, and meteorological variables over Arctic sea ice. The O-buoy operated in an autonomous manner with daily, bi-directional data transmissions using Iridium satellite communication. The O-buoy was equipped with three power sources: primary lithium-ion battery packs, rechargeable lead acid packs, and solar panels that recharge the lead acid packs, and can fully power the O-buoy during summer operation. This system was designed to operate under the harsh conditions present in the Arctic, with minimal direct human interaction, to aid in our understanding of the atmospheric chemistry that occurs in this remote region of the world. The current design requires approximately yearly maintenance limited by the lifetime of the primary power supply. The O-buoy system was field tested in Elson Lagoon, Barrow, Alaska from February to May 2009, and here we describe the design and present preliminary data.

  14. Operational satellites and the global monitoring of snow and ice

    NASA Technical Reports Server (NTRS)

    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.

  15. Satellite and ground-based observations of patterns and seasonality of sea-ice, summer warmth, snow, and NDVI along the North America and Eurasia Arctic transects

    NASA Astrophysics Data System (ADS)

    Walker, D. A.; Epstein, H. E.; Raynolds, M. K.; Bhatt, U. S.; Bieniek, P. A.

    2011-12-01

    We analyzed vegetation, climate, and spectral data from zonal sites along two >1500 km long transects that span all five Arctic bioclimate subzones in North America and Eurasia to help interpret the long-term changes in satellite-derived trends of pattern and seasonality of vegetation greenness. Despite large differences in environment and vegetation along the two transects, there is nearly an identical logarithmic relationship between biomass and the summer maximum normalized difference vegetation index derived from AVHRR sensors (MaxNDVI) along the two transects. Summer open water in the Northern Alaska/Beaufort Sea region has increased by 39%, the summer warmth index (SWI) of the tundra increased by 14%, MaxNDVI by 28% and time-integrated NDVI (TI-NDVI) by 21%. The increased open water in the Beaufort is associated with a warming of the land and a large positive increase in the NDVI. In the eastern Kara Sea/Yamal Peninsula region, summer-fall open water has increased by 115%, the SWI decreased by -3%, MaxNDVI increased by only 6%, and TI-NDVI by 2%. The greatly reduced sea ice has affected the summer total warmth and NDVI of the Eurasia transect minimally possibly due to increased winter snow and delayed snowmelt in much of northwest Russian Arctic. In northern Alaska, there is distinctive trend of earlier snow melt at most stations; whereas the northern Yamal has seen an increase in the snow water equivalent and delayed melt on much of the Yagorsky, Yamal, Gydan, and Taimyr peninsulas. This appears to be associated with the reduction in the total summer warmth and relatively small increase in NDVI.

  16. Estimating the surface layer refractive index structure constant over snow and sea ice using Monin-Obukhov similarity theory with a mesoscale atmospheric model.

    PubMed

    Qing, Chun; Wu, Xiaoqing; Huang, Honghua; Tian, Qiguo; Zhu, Wenyue; Rao, Ruizhong; Li, Xuebin

    2016-09-01

    Since systematic direct measurements of refractive index structure constant ( Cn2) for many climates and seasons are not available, an indirect approach is developed in which Cn2 is estimated from the mesoscale atmospheric model outputs. In previous work, we have presented an approach that a state-of-the-art mesoscale atmospheric model called Weather Research and Forecasting (WRF) model coupled with Monin-Obukhov Similarity (MOS) theory which can be used to estimate surface layer Cn2 over the ocean. Here this paper is focused on surface layer Cn2 over snow and sea ice, which is the extending of estimating surface layer Cn2 utilizing WRF model for ground-based optical application requirements. This powerful approach is validated against the corresponding 9-day Cn2 data from a field campaign of the 30th Chinese National Antarctic Research Expedition (CHINARE). We employ several statistical operators to assess how this approach performs. Besides, we present an independent analysis of this approach performance using the contingency tables. Such a method permits us to provide supplementary key information with respect to statistical operators. These methods make our analysis more robust and permit us to confirm the excellent performances of this approach. The reasonably good agreement in trend and magnitude is found between estimated values and measurements overall, and the estimated Cn2 values are even better than the ones obtained by this approach over the ocean surface layer. The encouraging performance of this approach has a concrete practical implementation of ground-based optical applications over snow and sea ice. PMID:27607648

  17. Solar radiation interactions with seasonal sea ice

    NASA Astrophysics Data System (ADS)

    Ehn, Jens Kristian

    Presently, the Arctic Ocean is undergoing an escalating reduction in sea ice and a transition towards a seasonal sea ice environment. This warrants detailed investigations into improving our understanding of the seasonal evolution of sea ice and snow covers, and their representation in climate models. The interaction of solar radiation with sea ice is an important process influencing the energy balance and biological activity in polar seas, and consequently plays a key role in the earth's climate system. This thesis focuses on characterization of the optical properties---and the underlying physical properties that determine them---of seasonal sea ice during the fall freeze-up and the spring melt periods. Both periods display high spatial heterogeneity and rapid temporal changes in sea ice properties, and are therefore poorly understood. Field data were collected in Amundsen Gulf/Franklin Bay (FB), southern-eastern Beaufort Sea, in Oct.-Nov. 2003 and Apr. 2004 and in Button Bay (BB), western Hudson Bay, in Mar.-May 2005 to address (1) the temporal and spatial evolution of surface albedo and transmittance, (2) how radiative transfer in sea ice is controlled by its physical nature, and (3) the characteristics of the bottom ice algae community and its effect on the optical properties. The fall study showed the importance of surface features such as dry or slushy bare ice, frost flowers and snow cover in determining the surface albedo. Ice thickness was also important, however, mostly because surface features were associated with thickness. For example, nilas (<10 cm thick) was typically not covered by a snow layer as snow grains were dissolved or merged with the salty and warm brine skim layer on the surface, while surface conditions on thicker ice types were cold and dry enough to support a snow cover. In general, the surface albedo increased exponentially with an ice thickness increase, however, variability within ice thickness types were very large. It is apparent

  18. MODIS Collection 6 Data at the National Snow and Ice Data Center (NSIDC)

    NASA Astrophysics Data System (ADS)

    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

  19. Correlation function studies for snow and ice

    NASA Technical Reports Server (NTRS)

    Vallese, F.; Kong, J. A.

    1981-01-01

    The random medium model is used to characterize snow and ice fields in the interpretation of active and passive microwave remote sensing data. A correlation function is used to describe the random permittivity fluctuations with the associated mean and variance and correlation lengths; and several samples are investigated to determine typical correlation functions for snow and ice. It is shown that correlation functions are extracted directly from appropriate ground truth data, and an exponential correlation function is observed for snow and ice with lengths corresponding to the actual size of ice particles or air bubbles. Thus, given that a medium has spatially stationary statistics and a small medium, the random medium model can interpret remote sensing data where theoretical parameters correspond to actual physical parameters of the terrain.

  20. Bacterial diversity in snow on North Pole ice floes.

    PubMed

    Hauptmann, Aviaja L; Stibal, Marek; Bælum, Jacob; Sicheritz-Pontén, Thomas; Brunak, Søren; Bowman, Jeff S; Hansen, Lars H; Jacobsen, Carsten S; Blom, Nikolaj

    2014-11-01

    The microbial abundance and diversity in snow on ice floes at three sites near the North Pole was assessed using quantitative PCR and 454 pyrosequencing. Abundance of 16S rRNA genes in the samples ranged between 43 and 248 gene copies per millilitre of melted snow. A total of 291,331 sequences were obtained through 454 pyrosequencing of 16S rRNA genes, resulting in 984 OTUs at 97 % identity. Two sites were dominated by Cyanobacteria (72 and 61 %, respectively), including chloroplasts. The third site differed by consisting of 95 % Proteobacteria. Principal component analysis showed that the three sites clustered together when compared to the underlying environments of sea ice and ocean water. The Shannon indices ranged from 2.226 to 3.758, and the Chao1 indices showed species richness between 293 and 353 for the three samples. The relatively low abundances and diversity found in the samples indicate a lower rate of microbial input to this snow habitat compared to snow in the proximity of terrestrial and anthropogenic sources of microorganisms. The differences in species composition and diversity between the sites show that apparently similar snow habitats contain a large variation in biodiversity, although the differences were smaller than the differences to the underlying environment. The results support the idea that a globally distributed community exists in snow and that the global snow community can in part be attributed to microbial input from the atmosphere. PMID:24951969

  1. Snow and ice ecosystems: not so extreme.

    PubMed

    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. PMID:26408452

  2. Interferometric System for Measuring Thickness of Sea Ice

    NASA Technical Reports Server (NTRS)

    Hussein, Ziad; Jordan, Rolando; McDonald, Kyle; Holt, Benjamin; Huang, John; Kugo, Yasuo; Ishimaru, Akira; Jaruwatanadilok, Semsak; Akins, Torry; Gogineni, Prasad

    2006-01-01

    The cryospheric advanced sensor (CAS) is a developmental airborne (and, potentially, spaceborne) radar-based instrumentation system for measuring and mapping the thickness of sea ice. A planned future version of the system would also provide data on the thickness of snow covering sea ice. Frequent measurements of the thickness of polar ocean sea ice and its snow cover on a synoptic scale are critical to understanding global climate change and ocean circulation.

  3. Sea ice ecosystems.

    PubMed

    Arrigo, Kevin R

    2014-01-01

    Polar sea ice is one of the largest ecosystems on Earth. The liquid brine fraction of the ice matrix is home to a diverse array of organisms, ranging from tiny archaea to larger fish and invertebrates. These organisms can tolerate high brine salinity and low temperature but do best when conditions are milder. Thriving ice algal communities, generally dominated by diatoms, live at the ice/water interface and in recently flooded surface and interior layers, especially during spring, when temperatures begin to rise. Although protists dominate the sea ice biomass, heterotrophic bacteria are also abundant. The sea ice ecosystem provides food for a host of animals, with crustaceans being the most conspicuous. Uneaten organic matter from the ice sinks through the water column and feeds benthic ecosystems. As sea ice extent declines, ice algae likely contribute a shrinking fraction of the total amount of organic matter produced in polar waters. PMID:24015900

  4. Impact of snow cover on CO2 dynamics in Antarctic pack ice

    NASA Astrophysics Data System (ADS)

    Geilfus, N.-X.; Tison, J.-L.; Ackley, S. F.; Rysgaard, S.; Miller, L. A.; Delille, B.

    2014-06-01

    Temporal evolution of pCO2 profiles in sea ice in the Bellingshausen Sea, Antarctica, in October 2007 shows that the CO2 system in the ice was primarily controlled by physical and thermodynamic processes. During the survey, a succession of warming and cold events strongly influenced the physical, chemical and thermodynamic properties of the ice cover. Two sampling sites with contrasting characteristics of ice and snow thickness were sampled: one had little snow accumulation (from 8 to 25 cm) and larger temperature and salinity variations than the second site, where the snow cover was up to 38 cm thick and therefore better insulated the underlying sea ice. We confirm that each cooling/warming event was associated with an increase/decrease in the brine salinity, total alkalinity (TA), total dissolved inorganic carbon (TCO2), and in situ brine and bulk ice CO2 partial pressures (pCO2). Thicker snow covers muted these changes, suggesting that snow influences changes in the sea ice carbonate system through its impact on the temperature and salinity of the sea ice cover. During this survey, pCO2 was undersaturated with respect to the atmosphere both in situ, in the bulk ice (from 10 to 193 μatm), and in the brine (from 65 to 293 μatm), and the ice acted as a sink for atmospheric CO2 (up to 2.9 mmol m-2 d-1), despite the underlying supersaturated seawater (up to 462 μatm).

  5. Improving the WRF model's simulation over sea ice surface through coupling with a complex thermodynamic sea ice model

    NASA Astrophysics Data System (ADS)

    Yao, Y.; Huang, J.; Luo, Y.; Zhao, Z.

    2015-12-01

    Sea ice plays an important role in the air-ice-ocean interaction, but it is often represented simply in many regional atmospheric models. The Noah sea ice model, which has been widely used in the Weather Research and Forecasting (WRF) model, exhibits cold bias in simulating the Arctic sea ice temperature when validated against the Surface Heat Budget of the Arctic Ocean (SHEBA) in situ observations. According to sensitivity tests, this bias is attributed not only to the simulation of snow depth and turbulent fluxes but also to the heat conduction within snow and ice. Compared with the Noah sea ice model, the high-resolution thermodynamic snow and ice model (HIGHTSI) has smaller bias in simulating the sea ice temperature. HIGHTSI is further coupled with the WRF model to evaluate the possible added value from better resolving the heat transport and solar penetration in sea ice from a complex thermodynamic sea ice model. The cold bias in simulating the surface temperature over sea ice in winter by the original Polar WRF is reduced when HIGHTSI rather than Noah is coupled with the WRF model, and this also leads to a better representation of surface upward longwave radiation and 2 m air temperature. A discussion on the impact of specifying sea ice thickness in the WRF model is presented. Consistent with previous research, prescribing the sea ice thickness with observational information would result in the best simulation among the available methods. If no observational information is available, using an empirical method based on the relationship between sea ice concentration and sea ice thickness could mimic the large-scale spatial feature of sea ice thickness. The potential application of a thermodynamic sea ice model in predicting the change in sea ice thickness in a RCM is limited by the lack of sea ice dynamic processes in the model and the coarse assumption on the initial value of sea ice thickness.

  6. Operation IceBridge: Sea Ice Interlude

    NASA Video Gallery

    Sea ice comes in an array of shapes and sizes and has its own ephemeral beauty. Operation IceBridge studies sea ice at both poles, and also runs across interesting formations en route to other targ...

  7. First Moderate Resolution Imaging Spectroradiometer (MODIS) Snow and Ice Workshop

    NASA Technical Reports Server (NTRS)

    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.

  8. Modelling and measuring the spectral bidirectional reflectance factor of snow-covered sea ice: an intercomparison study

    NASA Astrophysics Data System (ADS)

    Li, Shusun; Zhou, Xiaobing

    2004-12-01

    Broadband albedo is a very important geophysical parameter in the Earth surface-atmosphere interaction in either global climate change or hydrological cycle and snowmelt runoff studies. To derive the broadband albedo accurately from satellite optical sensor observation at limited bands and at a single observation angle, the bidirectional reflectance factor (BRF) has to be specified quantitatively. In the present albedo derivation algorithms from the satellite radiance data, the BRF is either modelled or observed. Questions may arise as to how well a BRF model can be in the broadband albedo derivation. To help answer such questions, we studied the performance of a snow-surface BRF model for two specific cases under large solar zenith angles (65° and 85°). We measured snow-surface spectral directional reflectance under clear skies. The snow physical properties, such as snow grain size and snow density, at the same sites were also measured. In situ snow physical data are used to simulate the snow-surface BRF and hemispherical directional reflectance factor (HDRF) through a multilayered azimuth- and zenith-dependent plane-parallel radiative transfer model. The field measurements and BRF and HDRF simulations all reveal the forward-scattering nature of snow surface under large solar incidence angles, but the BRF model results depict the strongest forward-scattering patterns under such solar zenith angles. Because the HDRF is simulated through coupling of the surface BRF with radiative transfer in the atmosphere, the resulting HDRF patterns agree with the field measurements better than the simulated BRF does. The deviation of the simulated HDRF from field-based clear-sky directional reflectance (FCDR) is within +/-10% for the central (viewing zenith angle <45° ) and lateral sides of the viewing hemisphere. This level of agreement between the simulated HDRF and FCDR also implies that the simulated BRF model can provide remote-sensing estimates of spectral albedo

  9. An optical model for the microwave properties of sea ice

    NASA Technical Reports Server (NTRS)

    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.

  10. 14 CFR 139.313 - Snow and ice control.

    Code of Federal Regulations, 2010 CFR

    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 certificate holder whose airport is located where snow and icing conditions occur must prepare, maintain,...

  11. 14 CFR 139.313 - Snow and ice control.

    Code of Federal Regulations, 2013 CFR

    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 certificate holder whose airport is located where snow and icing conditions occur must prepare, maintain,...

  12. 14 CFR 139.313 - Snow and ice control.

    Code of Federal Regulations, 2011 CFR

    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 certificate holder whose airport is located where snow and icing conditions occur must prepare, maintain,...

  13. 14 CFR 139.313 - Snow and ice control.

    Code of Federal Regulations, 2012 CFR

    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 certificate holder whose airport is located where snow and icing conditions occur must prepare, maintain,...

  14. 14 CFR 139.313 - Snow and ice control.

    Code of Federal Regulations, 2014 CFR

    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 certificate holder whose airport is located where snow and icing conditions occur must prepare, maintain,...

  15. Remote sensing of snow and ice: A review of the research in the United States 1975 - 1978

    NASA Technical Reports Server (NTRS)

    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.

  16. Sea ice pCO2 dynamics and air-ice CO2 fluxes during the Sea Ice Mass Balance in the Antarctic (SIMBA) experiment - Bellingshausen Sea, Antarctica

    NASA Astrophysics Data System (ADS)

    Geilfus, N.-X.; Tison, J.-L.; Ackley, S. F.; Galley, R. J.; Rysgaard, S.; Miller, L. A.; Delille, B.

    2014-12-01

    Temporal evolution of pCO2 profiles in sea ice in the Bellingshausen Sea, Antarctica, in October 2007 shows physical and thermodynamic processes controls the CO2 system in the ice. During the survey, cyclical warming and cooling strongly influenced the physical, chemical, and thermodynamic properties of the ice cover. Two sampling sites with contrasting characteristics of ice and snow thickness were sampled: one had little snow accumulation (from 8 to 25 cm) and larger temperature and salinity variations than the second site, where the snow cover was up to 38 cm thick and therefore better insulated the underlying sea ice. We show that each cooling/warming event was associated with an increase/decrease in the brine salinity, total alkalinity (TA), total dissolved inorganic carbon (TCO2), and in situ brine and bulk ice CO2 partial pressures (pCO2). Thicker snow covers reduced the amplitude of these changes: snow cover influences the sea ice carbonate system by modulating the temperature and therefore the salinity of the sea ice cover. Results indicate that pCO2 was undersaturated with respect to the atmosphere both in the in situ bulk ice (from 10 to 193 μatm) and brine (from 65 to 293 μatm), causing the sea ice to act as a sink for atmospheric CO2 (up to 2.9 mmol m-2 d-1), despite supersaturation of the underlying seawater (up to 462 μatm).

  17. Monitoring Snow on ice as Critical Habitat for Ringed Seals

    NASA Astrophysics Data System (ADS)

    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.

  18. Record Arctic Sea Ice Loss in 2007

    NASA Technical Reports Server (NTRS)

    2007-01-01

    This image of the Arctic was produced from sea ice observations collected by the Advanced Microwave Scanning Radiometer (AMSR-E) Instrument on NASA's Aqua satellite on September 16, overlaid on the NASA Blue Marble. The image captures ice conditions at the end of the melt season. Sea ice (white, image center) stretches across the Arctic Ocean from Greenland to Russia, but large areas of open water were apparent as well. In addition to record melt, the summer of 2007 brought an ice-free opening though the Northwest Passage that lasted several weeks. The Northeast Passage did not open during the summer of 2007, however, as a substantial tongue of ice remained in place north of the Russian coast. According to the National Snow and Ice Data Center (NSIDC), on September 16, 2007, sea ice extent dropped to 4.13 million square kilometers (1.59 million square miles)--38 percent below average and 24 percent below the 2005 record.

  19. Sea-Ice Roughness, Morphogenesis and Kinematics --- Approaches to Learn from the Complexity of Sea Ice

    NASA Astrophysics Data System (ADS)

    Herzfeld, U. C.; Williams, S.; Maslanik, J.

    2007-12-01

    Recent studies of the alarming retreat of the Arctic sea ice have been largely based on observations of sea-ice coverage. This is not sufficient to capture changes in the sea-ice's mass, hence there is an increasing interest in measuring the thickness of sea-ice. However, the complexity of sea ice renders the latter a difficult task: (1) at any time, the sea ice has a complex form and appearance in remote-sensing observations, (2) due to ridging and rubbling, the mass of sea ice is not directly related to its thickness, (3) sea ice forms in a series of morphogenetic processes, and (4) sea ice moves. Here we present mathematical approaches to analyze spatial roughness of the surface of sea ice and of its snow-layer thickness, morphogenetic processes and deformation characteristics as a means to quantify and characterize sea-ice properties, processes and provinces. Applications include analyses of passive microwave data, SAR data, laser and radar elevation data and multispectral image data, from satellite, unmanned aerial vehicle and aircraft platforms, and field data.

  20. Enhanced Sea Ice Concentration and Ice Temperature Algorithms for AMSR

    NASA Technical Reports Server (NTRS)

    Comiso, Josefino C.; Manning, Will; Gersten, Robert

    1998-01-01

    Accurate quantification of sea ice concentration and ice temperature from satellite passive microwave data is important because they provide the only long term, spatially detailed and consistent data set needed to study the climatology of the polar regions. Sea ice concentration data are used to derive large-scale daily ice extents that are utilized in trend analysis of the global sea ice cover. They are also used to quantify the amount of open water and thin ice in polynya and divergence regions which together with ice temperatures are in turn needed to estimate vertical heat and salinity fluxes in these regions. Sea ice concentrations have been derived from the NASA Team and Bootstrap algorithms while a separate technique for deriving ice temperature has been reported. An integrated technique that will utilizes most of the channels of AMSR (Advanced Microwave Scanning Radiometer) has been developed. The technique uses data from the 6 GHz and 37 GHz channels at vertical polarization obtain an initial estimate of sea ice concentration and ice temperature. The derived ice temperature is then utilized to estimate the emissivities for the corresponding observations at all the other channels. A procedure for calculating the ice concentration similar to the Bootstrap technique is then used but with variables being emissivities instead of brightness temperatures to minimizes errors associated with spatial changes in ice temperatures within the ice pack. Comparative studies of ice concentration results with those from other algorithms, including the original Bootstrap algorithm and those from high resolution satellite visible and infrared data will be presented. Also, results from a simulation study that demonstrates the effectiveness of the technique in correcting for spatial variations in ice temperatures will be shown. The ice temperature results are likewise compared with satellite infrared and buoy data with the latter adjusted to account for the effects of the snow

  1. EOS Aqua AMSR-E Arctic Sea Ice Validation Program

    NASA Technical Reports Server (NTRS)

    Cavalieri, D. J.; Markus, T.; Gasiewski, A.; Klein, M.; Maslanik, J.; Sturm, M.; Stroeve, J.; Heinrichs, J.

    2004-01-01

    A coordinated Arctic sea ice validation field campaign using the NASA Wallops P-3B aircraft was successfully completed in March 2003. 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 include sea ice concentration, sea ice temperature, and snow depth on sea ice. The primary instrument on the P-3B aircraft was the NOAA ETL Polarimetric Scanning Radiometer (PSR) covering the same frequencies and polarizations as the AMSR-E. This paper describes 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. The remaining flights covered portions of the Bering Sea ice edge, the Chukchi Sea, and Norton Sound. Comparisons among the satellite and aircraft PSR data sets are presented.

  2. Estimation of Antarctic Sea Ice Thickness From Satellite Radar Altimetry

    NASA Astrophysics Data System (ADS)

    Potter, R. C. H.; Laxon, S. W.; Peacock, N.

    The spatial and temporal variability of Antarctic sea-ice extent and thickness are re- quired by the climate modelling community to understand the complex coupling be- tween sea ice and ocean-atmosphere. Recent investigations have provided estimates of Arctic sea ice thickness determined from satellite radar altimetry, which have been validated using Upward Looking Sonar data from submarines. In the present study, we aim to explore the potential for estimation of the thickness of Antarctic sea ice. In the boreal summer, the Arctic Ocean is pre-dominantly inhabited by old, multiyear sea-ice that may survive through each melt season and subsequently refreeze and in- crease in thickness under autumn cooling and winter growth. However, aside from the Weddell Sea, the Antarctic sea ice is subject to almost complete seasonal melt/freeze with the formation of pre-dominant first year ice. To estimate ice thickness from mea- surements of ice elevation it is necessary to establish the vertical origin of the radar echo's received over snow covered ice. Assuming reflection originates at the snow/ice interface, the ice freeboard can be estimated. The freeboard is converted to ice thick- ness using fixed densities for ice and seawater and a recently generated Antarctic Snow depth climatology. However, the developed altimetry techniques are designed for rela- tively thick Arctic sea ice and therefore may not be directly applicable to the relatively thin non-compacted first year Antarctic sea ice. In particular, snow loading owing to high precipitation rates is likely to be much larger compared to ice thickness. In ex- treme conditions this may lead to negative freeboard. Nevertheless, data on Antarctic ice thickness is even more sparse than the Arctic and hence information on thickness would be of significant value. We present preliminary results of Antarctic ice thickness estimates and validation using ULS data.

  3. Comparison of measurements and theory for backscatter from bare and snow-covered saline ice

    NASA Technical Reports Server (NTRS)

    Bredow, Jonathan W.; Gogineni, Sivaprasad

    1990-01-01

    C-band radar backscatter measurements were made on artificially grown sea ice during the winters of 1987-1988 and 1988-1989. These measurements were made on smooth, rough, and snow-covered saline ice. The measured sigma-deg(theta) of smooth saline ice (rms height less than 0.05 cm) disagreed with small perturbation method (SPM) surface scattering predictions. Using physical parameters of the ice in a simple layer model, it us shown that this discrepancy can be explained by scattering from beneath the surface. A thin (7-cm) dry snow cover had a significant influence on backscatter from the smooth ice sheet. This influence was due to scattering from particles within the snow, and can be predicted by a commonly used empirical layer model for snow. The results of backscatter measurements of a moderately rough saline ice sheet were found to agree with SPM predictions.

  4. Seasonal Changes of Arctic Sea Ice Physical Properties Observed During N-ICE2015: An Overview

    NASA Astrophysics Data System (ADS)

    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

  5. Trend analysis of Arctic sea ice extent

    NASA Astrophysics Data System (ADS)

    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.

  6. Diatom vertical migration within land-fast Arctic sea ice

    NASA Astrophysics Data System (ADS)

    Aumack, C. F.; Juhl, A. R.; Krembs, C.

    2014-11-01

    Light levels inside first-year, landfast sea ice were experimentally altered by manipulating overlying snow depths. Irradiance available for ice algae growing near the ice-bottom, and under the ice, was highly dependent on snow depths ranging from 0 to > 30 cm. Importantly, algal vertical distributions also changed under different irradiances. Under thick snow (low light), the majority of algae were found several cm above the ice-seawater interface, while progressively more were found nearer the interface at locations with thinner overlying snow (higher light). Short-term field experiments suggested that ice algae were able to reposition themselves within the ice column within 3 days after manipulating snow depths. Laboratory gliding rate measurements of a cultured ice diatom suggested that it is capable of daily cm-scale movement. Vertical migration may help ice diatoms balance opposing light and nutrient resource gradients, similar to strategies used by some benthic and pelagic algae. Moreover, when ice algae congregate near the ice-seawater interface, they may be especially susceptible to loss from the ice environment. Vertical repositioning in response to changing light dynamics may be a mechanism to optimize between vertically-opposing environmental factors and help explain the connection between melting snow cover and export of biomass from sea ice.

  7. The sea ice thickness distribution in the northwestern Weddell Sea

    NASA Astrophysics Data System (ADS)

    Lange, M. A.; Eicken, H.

    1991-03-01

    We present new data on distribution of snow and sea ice thicknesses in the northwestern Weddell Sea. The data were obtained through direct measurements along 19 profiles, each approximately 100 m long on 17 different floes located between 54°-46°W and 59°-64°S. The overall probability density functions (PDFs) for ice thicknesses reflect the complex mixture of first-, second-, and multi-year ice to be expected in the outflowing branch of the Weddell Gyre. Further differentiation of the data reveals four distinct thickness classes which reflect differences in the formation and subsequent histories of the ice encountered. These classes (I-IV) represent strongly deformed first year ice, less deformed first- and second-year ice, and deformed second- or multi-year ice, respectively. Each of the classes is characterized by a specific set of quantities related to ice texture and surface snow characteristics and by distinct PDFs for snow and ice thicknesses. In addition, geometric surface and bottom roughness characteristics differ significantly for each of the floe classes.

  8. Soot climate forcing via snow and ice albedos

    PubMed Central

    Hansen, James; Nazarenko, Larissa

    2004-01-01

    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/m2 in the Northern Hemisphere. The “efficacy” of this forcing is ∼2, i.e., for a given forcing it is twice as effective as CO2 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. PMID:14699053

  9. Arctic Sea Ice Maximum 2011

    NASA Video Gallery

    AMSR-E Arctic Sea Ice: September 2010 to March 2011: Scientists tracking the annual maximum extent of Arctic sea ice said that 2011 was among the lowest ice extents measured since satellites began ...

  10. 2011 Sea Ice Minimum

    NASA Video Gallery

    This video shows Arctic sea ice from March 7, 2011, to Sept. 9, 2011, ending with a comparison of the 30-year average minimum extent, shown in yellow, and the Northwest Passage, in red. (no audio) ...

  11. Record Sea Ice Minimum

    NASA Technical Reports Server (NTRS)

    2007-01-01

    Arctic sea ice reached a record low in September 2007, below the previous record set in 2005 and substantially below the long-term average. This image shows the Arctic as observed by the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) aboard NASA's Aqua satellite on September 16, 2007. In this image, blue indicates open water, white indicates high sea ice concentration, and turquoise indicates loosely packed sea ice. The black circle at the North Pole results from an absence of data as the satellite does not make observations that far north. Three contour lines appear on this image. The red line is the 2007 minimum, as of September 15, about the same time the record low was reached, and it almost exactly fits the sea ice observed by AMSR-E. The green line indicates the 2005 minimum, the previous record low. The yellow line indicates the median minimum from 1979 to 2000.

  12. Comparison of radar backscatter from Antarctic and Arctic sea ice

    NASA Technical Reports Server (NTRS)

    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.

  13. Tortuosity of the Antarctic Sea Ice over the Weddell Sea

    NASA Astrophysics Data System (ADS)

    Beard, J.; Heinrichs, J. F.

    2011-12-01

    The objective of the research was to mathematically characterize the edge of the Antarctic sea ice in the Weddell Sea. Because the sea ice may reflect processes involved in the atmosphere and ocean near the ice edge, it may suggest broader changes on the ice. The chosen method was to compare the tortuosity of the edge over time and across seasons. Because the sea ice may reflect processes involved in the atmosphere and ocean near the ice edge, it may suggest broader changes on the ice. Throughout the research, the shapefiles for the Antarctic sea ice were collected from the National Snow and Ice Data Center website and the coordinates were extracted using an add-in for the MapWindow GIS. These points were then put into Excel separated by year and then the distance factor (an approximation to the tortuosity) was calculated and compared by month over time. Preliminary data has shown that the closer to the winter months, the higher the tortuosity. Statistical analysis has shown that there is no clear relationship between tortuosity and the area of the sea ice, and the tortuosity exhibits a weak negative trend over the past 32 years.

  14. Airborne Spectral Measurements of Surface-Atmosphere Anisotropy for Arctic Sea Ice and Tundra

    NASA Technical Reports Server (NTRS)

    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%.

  15. Anomalous snow accumulation over the southeast region of the Greenland ice sheet during 2002-2003 snow season

    NASA Technical Reports Server (NTRS)

    Nghiem, S. V.; Steffen, K.; Huff, R.; Neumann, G.

    2005-01-01

    Our objective is to determine seasonal snow accumulation in the percolation zone of the Greenland ice sheet on the daily-weekly basis over the large scale. Our approach utilizes data from the Greenland Climate Network (GC-Net) and from the SeaWinds Scatterometer on the QuikSCAT satellite (QSCAT) to measure snow accumulation (SA) in the percolation zone of the Greenland ice sheet. GC-Net measurements provide crucial in-situ data to facilitate the interpretation of QSCAT backscatter signature for the development of an algorithm to map SA.

  16. Seasonal evolution of melt ponds on Arctic sea ice

    NASA Astrophysics Data System (ADS)

    Webster, Melinda A.; Rigor, Ignatius G.; Perovich, Donald K.; Richter-Menge, Jacqueline A.; Polashenski, Christopher M.; Light, Bonnie

    2015-09-01

    The seasonal evolution of melt ponds has been well documented on multiyear and landfast first-year sea ice, but is critically lacking on drifting, first-year sea ice, which is becoming increasingly prevalent in the Arctic. Using 1 m resolution panchromatic satellite imagery paired with airborne and in situ data, we evaluated melt pond evolution for an entire melt season on drifting first-year and multiyear sea ice near the 2011 Applied Physics Laboratory Ice Station (APLIS) site in the Beaufort and Chukchi seas. A new algorithm was developed to classify the imagery into sea ice, thin ice, melt pond, and open water classes on two contrasting ice types: first-year and multiyear sea ice. Surprisingly, melt ponds formed ˜3 weeks earlier on multiyear ice. Both ice types had comparable mean snow depths, but multiyear ice had 0-5 cm deep snow covering ˜37% of its surveyed area, which may have facilitated earlier melt due to its low surface albedo compared to thicker snow. Maximum pond fractions were 53 ± 3% and 38 ± 3% on first-year and multiyear ice, respectively. APLIS pond fractions were compared with those from the Surface Heat Budget of the Arctic Ocean (SHEBA) field campaign. APLIS exhibited earlier melt and double the maximum pond fraction, which was in part due to the greater presence of thin snow and first-year ice at APLIS. These results reveal considerable differences in pond formation between ice types, and underscore the importance of snow depth distributions in the timing and progression of melt pond formation.

  17. Arctic sea ice decline: Introduction

    NASA Astrophysics Data System (ADS)

    DeWeaver, Eric T.

    By any measure, the loss of Arctic sea ice cover in September 2007 was spectacular. The National Snow and Ice Data Center (NSIDC) called it a loss "the size of Alaska and Texas combined," in comparison to the 1979-2000 September mean. Record-breaking minima in sea ice extent are not unexpected, given the declining trend of the past 30 years and its recent acceleration [e.g., Meier et al., 2007; Deser and Teng, this volume]. But the 2007 minimum was remarkable even compared to the decline, a full four standard deviations below the trend line (H. Stern, quoted by Schweiger et al. [2008]). Kerr [2007] reported an Alaska-sized loss compared to the previous record low in 2005, which was itself an Alaska-sized retreat from the value at the beginning of the satellite era in 1979. Deser and Teng point out that the loss between September 2006 and September 2007 is as large as the entire September extent loss from 1979 to 2006.

  18. Heat flux through sea ice in the western Weddell Sea: Convective and conductive transfer processes

    NASA Astrophysics Data System (ADS)

    Lytle, V. I.; Ackley, S. F.

    1996-04-01

    The heat flux through the snow and sea ice cover and at the ice/ocean interface were calculated at five sites in the western Weddell Sea during autumn and early winter 1992. The ocean heat flux averaged 7 ± 2 W/m2 from late February to early June, and average ice/air heat flux in the second-year floes depended on the depth of the snow cover and ranged from 9 to 17 (±0.8) W/m2. In late February, three of the five sites had an ice surface which was depressed below sea level, resulting, at two of the sites, in a partially flooded snow cover and a slush layer at the snow/ice interface. As this slush layer froze to form snow ice, the dense brine which was rejected flowed out through brine drainage channels and was replaced by lower-salinity, nutrient-rich seawater from the ocean upper layer. We estimate that about half of the second-year ice in the region was covered with this slush layer early in the winter. As the slush layer froze, over a 2- to 3-week period, the convection within the ice transported salt from the ice to the upper ocean and increased total heat flux through the overlying ice and snow cover. On an area-wide basis, approximately 10 cm of snow ice growth occurred within second-year pack ice, primarily during a 2- to 3-week period in February and March. This ice growth, near the surface of the ice, provides a salt flux to the upper ocean equivalent to 5 cm of ice growth, despite the thick (about 1 m) ice cover, in addition to the ice growth in the small (area less than 5%), open water regions.

  19. Seafloor Control on Sea Ice

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

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

  20. Seasonality of Spectral Albedo and Transmission of Sea Ice in the Transpolar Drift, Arctic Ocean

    NASA Astrophysics Data System (ADS)

    Nicolaus, M.; Gerland, S.; Hudson, S.; Haapala, J.; Hanson, S.; Palo, T.; Perovich, D. K.

    2008-12-01

    The physical and optical properties of snow and sea ice in the Polar regions control the amount of solar short-wave radiation, reflected at the surface, scattered and absorbed within snow and ice, and transmitted into the ocean beneath. Albedo and transmissivity of snow and sea ice strongly influence heat fluxes within the coupled atmosphere-ice-ocean system, and by that the evolution of the sea ice. Spectral optical properties are crucial for primary production and evolution of sea ice related microorganisms and various bio-chemical processes. Furthermore, the increasing importance of remote sensors when studying snow and sea ice, raises the need for ground truth data of spectral optical and other physical properties of snow and sea ice. Spectral albedo and transmission were measured continuously within high spectral and temporal resolution during the transpolar drift of the drifting schooner "Tara" through the Arctic Basin between 30 April and 05 September 2007. Simultaneous in-situ measurements of snow and sea ice properties as well as a comprehensive meteorological program complement the dataset and allow common analysis and an integrated dataset. Results show significant seasonal changes and highlight key events during the transitions from spring to summer and summer to autumn; including formation, evolution, and freeze up of melt ponds. We were able to derive absolute values of energy transfer through snow and ice and into the upper ocean. The timing of changes in surface energy balance can be determined and characterized by including results from detailed snow and sea ice studies as temperature and density profiles, snow stratigraphy, and sea ice texture. Among others, they show that the melting period lasted 80 days which was about 20 days longer than on average. Interestingly, the observation period coincides with the time prior to the Arctic sea ice extent minimum in autumn 2007. Consequently, the findings might assist to understand and explain processes

  1. Arctic Sea ice model sensitivities.

    SciTech Connect

    Peterson, Kara J.; Bochev, Pavel Blagoveston; Paskaleva, Biliana Stefanova

    2010-12-01

    Arctic sea ice is an important component of the global climate system and, due to feedback effects, the Arctic ice cover is changing rapidly. Predictive mathematical models are of paramount importance for accurate estimates of the future ice trajectory. However, the sea ice components of Global Climate Models (GCMs) vary significantly in their prediction of the future state of Arctic sea ice and have generally underestimated the rate of decline in minimum sea ice extent seen over the past thirty years. One of the contributing factors to this variability is the sensitivity of the sea ice state to internal model parameters. A new sea ice model that holds some promise for improving sea ice predictions incorporates an anisotropic elastic-decohesive rheology and dynamics solved using the material-point method (MPM), which combines Lagrangian particles for advection with a background grid for gradient computations. We evaluate the variability of this MPM sea ice code and compare it with the Los Alamos National Laboratory CICE code for a single year simulation of the Arctic basin using consistent ocean and atmospheric forcing. Sensitivities of ice volume, ice area, ice extent, root mean square (RMS) ice speed, central Arctic ice thickness,and central Arctic ice speed with respect to ten different dynamic and thermodynamic parameters are evaluated both individually and in combination using the Design Analysis Kit for Optimization and Terascale Applications (DAKOTA). We find similar responses for the two codes and some interesting seasonal variability in the strength of the parameters on the solution.

  2. The ASIBIA sea-ice facility: First results from the Atmosphere-Sea-Ice-Biogeochemistry in the Arctic chamber

    NASA Astrophysics Data System (ADS)

    France, James L.; Thomas, Max

    2016-04-01

    Working in the natural ocean-ice-atmosphere system is very difficult, as conducting fieldwork on sea-ice presents many challenges ice including costs, safety, experimental controls and access. The new ASIBIA (Atmosphere-Sea-Ice-Biogeochemistry in the Arctic) coupled Ocean-Sea-Ice-(Snow)-Atmosphere chamber facility at the University of East Anglia, UK, we are aiming to perform controlled first-year sea-ice investigations in areas such as sea-ice physics, physicochemical and biogeochemical processes in sea-ice and quantification of the bi-directional flux of gases in various states of first-year sea-ice conditions. The facility is a medium sized chamber with 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 water depth can be up to 1 m (including up to 25 cm of sea-ice) and an optional 1 m tall Teflon film atmosphere on top of the sea-ice, thus creating a closed and coupled ocean-sea-ice-atmosphere mesocosm. Ice growth in the tank is well suited for studying first-year sea-ice physical properties, with in-situ ice-profile measurements of temperature, salinity, conductivity, pressure and spectral light transmission. Underwater and above ice cameras are installed to record the physical development of the sea-ice. Here, we present the data from the first suites of experiments in the ASIBIA chamber focussing on sea-ice physics and give a brief description of the capabilities of the facility going forward. The ASIBIA chamber was funded as part of an ERC consolidator grant to the late Prof. Roland von Glasow and we hope this work and further development of the facility will act as a lasting legacy.

  3. Antarctic Sea Ice Thickness From Surface Elevation: A Multi-Sensor Approach

    NASA Astrophysics Data System (ADS)

    Necsoiu, M.; Lewis, M. J.; Parra, J.; Ackley, S. F.; Weissling, B.; Hwang, B.

    2011-12-01

    Sea ice is an important component of the climate system affecting ocean-atmospheric interactions and global energy balance. The assessment of sea ice thickness using satellite and airborne laser altimetry is largely dependent upon isostatic buoyancy relationships between snow, ice, slush and ocean water. The use of these relationships in estimating sea ice thickness is complicated by a number of factors including spatial resolution, changing sea level reference, varying snow and ice density, and snow-ice interface flooding. Previous work has suggested that the effects of these factors can be reduced using a multi-sensor approach. The X-band backscatter from TerraSAR-X (TSX) is sensitive to surface roughness, snow and ice properties, and the presence of wet snow. The combined use of TSX for sea ice characterization and laser altimetry has the potential to provide more accurate estimates of sea ice thickness. In this study, we examine the feasibility of using TSX dual-polarized backscatter data to determine ice characteristics in the Bellingshausen and Amundsen Sea in the Antarctic region. Actual surface sea ice characteristics were derived from sea ice station measurements during the J.C. Ross (ICEBell) and Oden Southern Ocean (OSO) expeditions during the austral summer of 2010-11. Data from ice mass-balance buoys emplaced during the two cruises continued through summer melt and bridged the transition into fall freeze up conditions in the snow pack and ice cover. Shannon entropy derived from TSX, measures the statistical disorder of a medium illuminated by the radar, being a sum of two contributions related to intensity and the degree of polarization. A geostatistical approach is employed to correlate measured surface properties and sea ice freeboard with TSX-derived Shannon entropy. The floes are subsequently classified based on Shannon entropy and used in an empirically-based buoyancy model to estimate sea ice thickness. This approach is then compared with

  4. Global mountain snow and ice loss driven by dust and black carbon radiative forcing

    NASA Astrophysics Data System (ADS)

    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.

  5. Interannual Variability of Snow and Ice and Impact on the Carbon Cycle

    NASA Technical Reports Server (NTRS)

    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.

  6. Sea ice radiative forcing, sea ice area, and climate sensitivity

    NASA Astrophysics Data System (ADS)

    Caldeira, Ken; Cvijanovic, Ivana

    2014-05-01

    Changes in sea ice cover affect climate sensitivity by modifying albedo and surface heat flux exchange, which in turn affect the absorbed solar radiation at the surface as well as cloud cover, atmospheric water content and poleward atmospheric heat transport. Here, we use a configuration of the Community Earth System Model 1.0.4 with a slab ocean model and a thermodynamic-dynamic sea ice model to investigate the overall net effect of feedbacks associated with the sea ice loss. We analyze the strength of the overall sea ice feedback in terms of two factors: the sensitivity of sea ice area to changes in temperature, and the sensitivity of sea ice radiative forcing to changes in sea ice area. In this model configuration, sea ice area decreases by ~3 × 1012 m2 per K of global warming, while the effective global radiative forcing per square meter of sea ice loss is ~0.1 × 10-12 W m-2. The product of these two terms (~0.3 W m-2 K-1) approximately equals the difference in climate feedback parameter found in simulations with sea ice response (1.05 W m-2 K-1) and simulations without sea ice response (1.31 W m-2 K-1 or 1.35 W m-2 K-1, depending on the method used to disable changes in sea ice cover). Thus, we find that in our model simulations, sea ice response accounts for about 20% to 22% of the climate sensitivity to an imposed change in radiative forcing. In our model, the additional radiative forcing resulting from a loss of all sea ice in the 'pre-industrial' state is comparable to but somewhat less than the radiative forcing from a doubling of atmospheric CO2 content.

  7. Sea Ice Radiative Forcing, Sea Ice Area, and Climate Sensitivity

    NASA Astrophysics Data System (ADS)

    Caldeira, K.; Cvijanovic, I.

    2014-12-01

    Changes in sea ice cover affect climate sensitivity by modifying albedo and surface heat flux exchange, which in turn affect the absorbed solar radiation at the surface as well as cloud cover, atmospheric water content and poleward atmospheric heat transport. Here, we use a configuration of the Community Earth System Model 1.0.4 with a slab ocean model and a thermodynamic-dynamic sea ice model to investigate the overall net effect of feedbacks associated with the sea ice loss. We analyze the strength of the overall sea ice feedback in terms of two factors: the sensitivity of sea ice area to changes in temperature, and the sensitivity of sea ice radiative forcing to changes in sea ice area. In this model configuration, sea ice area decreases by ~3 × 1012 m2 per K of global warming, while the effective global radiative forcing per unit area of sea ice loss is ~0.1 × 10-12 W m-2. The product of these two terms (~0.3 W m-2 K-1) approximately equals the difference in climate feedback parameter found in simulations with sea ice response (1.05 W m-2 K-1) and simulations without sea ice response (1.31 W m-2 K-1 or 1.35 W m-2 K-1, depending on the method used to disable the changes in sea ice cover). Thus, we find that in our model simulations, sea ice response accounts for about 20% to 22% of the climate sensitivity to an imposed change in radiative forcing. In our model, the additional radiative forcing resulting from a loss of all sea-ice in the "pre-industrial" state is comparable to but somewhat less than the radiative forcing from a doubling of atmospheric CO2 content.

  8. Mass Balance of Arctic Sea Ice North of Svalbard during N-ICE2015

    NASA Astrophysics Data System (ADS)

    Rösel, A.; Gerland, S.; King, J.; Itkin, P.

    2015-12-01

    The N-ICE2015 cruise, led by the Norwegian Polar Institute, was a drift experiment with the research vessel R/V Lancefrom 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 during the 6 month, 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 like EM31, GEM, and EM-bird; 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. In terms of mass balance, average snow depths of 32 cm on first year ice, and 52 cm on multiyear 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 cm. During winter, we found an unusual small growth rate on multiyear ice of about 15 cm in 2 months, due to above-average snow depths and some extraordanary storm events that came along with mild temperatures. In contrast thereto, we were also able to study new ice formation and thin ice on refrozen 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. The here presented dataset is a mandatory parameter for understanding the ocean-ice-atmosphere interactions, for

  9. State of Arctic Sea Ice North of Svalbard during N-ICE2015

    NASA Astrophysics Data System (ADS)

    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

  10. Remote sensing as a research tool. [sea ice surveillance from aircraft and spacecraft

    NASA Technical Reports Server (NTRS)

    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.

  11. Passive microwave in situ observations of winter Weddell Sea ice

    NASA Technical Reports Server (NTRS)

    Comiso, J. C.; Grenfell, T. C.; Bell, D. L.; Lange, M. A.; Ackley, S. F.

    1989-01-01

    Results are presented on the microwave radiative characteristics of Antarctic sea ice measured during the 1986 Winter Weddell Sea Project with a set of portable radiometers. Radiometer measurements at 6, 10, 18, 37, and 90 GHz in vertical and horizontal polarizations were supplemented by near-simultaneous measurements of the ice physical characteristics (including ice thickness, salinity, temperature, snow cover, and density) made during two cruises, lasting 3 months each. Measurements were obtained on various types of sea ice over a large portion of the Weddell-Sea ice cover, including four transects across the entire ice pack. Data analysis shows a large variability in the multispectral microwave emissivities of different ice types, especially at 90 GHz, demonstrating a strong potential of the use of the 90-GHz channel, in combination with lower-frequency channels, for detailed characterizations of the ice cover.

  12. [Study on the basic characteristics of Bohai Sea ice reflectance spectra].

    PubMed

    Li, Ning; Xie, Feng; Gu, Wei; Cui, Wei-Jia; Huang, Shu-Qing; Liu, Zhen

    2008-02-01

    For monitoring sea ice in Bohai Sea, the present paper performed a field observation experiment on sea ice reflectance spectrum in Bohai Sea by control experiment. In the experiment, three groups of sea ice samples from the Bayuquan in Liaodong Gulf were collected, which were clean even ice of different thickness, sea ice covered by melt snow layer and sea ice with sands. According to the series of observation data during the two years, the reflectance spectrum curve of clean even ice has double peaks (a big one and a small one) when the ice thickness is less than 30 cm. The principal reflection peak is in good relation to the thickness of the sea ice. The principal reflection spectral peak of ice covered by melt snow layer is obviously higher than that of the spectrum of clean even ice without the snow layer with the same ice thickness. The principal reflection spectral peak of the sea ice with sands increases sharply, and the spectrum curve arises slightly in the wavelength rang between 675 and 725 mm and then declines. Covering snow and sands are the key factors to result in the fact that the same ice thicknesses present different spectrum characteristics and the same spectrum characteristics present different thicknesses. PMID:18479022

  13. Recent increase in snow-melt area in the Greenland Ice sheet as an indicator of the effect of reduced surface albedo by snow impurities

    NASA Astrophysics Data System (ADS)

    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

  14. Sea ice/climate studies

    NASA Technical Reports Server (NTRS)

    Parkinson, C. L.

    1988-01-01

    The objectives were to determine and analyze the annual cycle of sea ice extents in the Arctic Ocean and peripheral seas and bays over the period 1973 to 1986, looking in particular for any long term trends; to examine the relationship between local sea ice covers and the surrounding atmosphere and ocean; and to examine sea ice as a potential early indicator of climate change. The work involves creating regional and hemispheric time series of sea ice variables from satellite passive microwave data and analyzing these through various intercomparisons amongst themselves and with oceanographic and atmospheric fields.

  15. Sea ice transports in the Weddell Sea

    NASA Astrophysics Data System (ADS)

    Harms, Sabine; Fahrbach, Eberhard; Strass, Volker H.

    2001-05-01

    Time series of sea ice draft in the Weddell Sea are evaluated together with hydrographic observations, satellite passive microwave data, and ice drift for estimation of the freshwater fluxes into and out of the Weddell Sea. Ice draft is measured with moored upward looking sonars since 1990 along two transects across the Weddell Gyre. One transect, extending from the tip of the Antarctic Peninsula to Kapp Norvegia, was sampled between 1990 and 1994 and covers the flow into and out of the southern Weddell Sea. The other transect, sampled since 1996 and extending from the Antarctic continent northward along the Greenwich meridian, covers the exchange of water masses between the eastern and the western Weddell Sea. In order to relate results obtained during the different time periods, empirical relationships are established between the length of the sea ice season, derived from the satellite passive microwave data and defined as the number of days per year with the sea ice concentration exceeding 15%, and (1) the annual mean ice draft and (2) the annual mean ice volume transport. By using these empirical relationships, estimates of annual mean ice drafts and ice volume transports are derived at all mooring sites for the period February 1979 through February 1999. Wind and current force a westward ice transport in the coastal areas of the eastern Weddell Sea and a northward ice transport in the west. During the 2-year period 1991/1992 the mean ice volume export from the Weddell Sea is (50 ± 19) × 103 m3 s-1. This freshwater export is representative for a longer-term (20-year) mean and exceeds the average amount of freshwater gained by precipitation and ice shelf melt by about 19×103 m3 s-1, yielding an upper bound for the formation rate of newly ventilated bottom water in the Weddell Sea of 2.6 Sv.

  16. Sea ice and polar climate in the NCAR CSM

    SciTech Connect

    Weatherly, J.W.; Briegleb, B.P.; Large, W.G.; Maslanik, J.A.

    1998-06-01

    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 the 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.

  17. Radiative transfer in atmosphere-sea ice-ocean system

    SciTech Connect

    Jin, Z.; Stamnes, K.; Weeks, W.F.; Tsay, S.C.

    1996-04-01

    Radiative energy is critical in controlling the heat and mass balance of sea ice, which significantly affects the polar climate. In the polar oceans, light transmission through the atmosphere and sea ice is essential to the growth of plankton and algae and, consequently, to the microbial community both in the ice and in the ocean. Therefore, the study of radiative transfer in the polar atmosphere, sea ice, and ocean system is of particular importance. Lacking a properly coupled radiative transfer model for the atmosphere-sea ice-ocean system, a consistent study of the radiative transfer in the polar atmosphere, snow, sea ice, and ocean system has not been undertaken before. The radiative transfer processes in the atmosphere and in the ice and ocean have been treated separately. Because the radiation processes in the atmosphere, sea ice, and ocean depend on each other, this separate treatment is inconsistent. To study the radiative interaction between the atmosphere, clouds, snow, sea ice, and ocean, a radiative transfer model with consistent treatment of radiation in the coupled system is needed and is under development.

  18. Polarimetric Signatures of Sea Ice. Part 1; Theoretical Model

    NASA Technical Reports Server (NTRS)

    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.

  19. Polarimetric signatures of sea ice. 1: Theoretical model

    NASA Technical Reports Server (NTRS)

    Nghiem, S. V.; Kwok, R.; Yueh, S. H.; Drinkwater, M. R.

    1995-01-01

    Physical, structral, 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. Polarmetric 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 to interpretation of sea ice polarimetric signatures.

  20. Comparison of AMSR-E derived Antarctic snow-ice interface temperatures with previous surface observations

    NASA Astrophysics Data System (ADS)

    Lewis, M.; Ackley, S. F.; Xie, H.; Cicek, B.

    2006-12-01

    The AMSR-E Sea Ice Temperature (L3 25 km) data product derived from passive microwave emissions at 6.9 GHz is available from the National Snow and Ice Data Center. The Sea Ice Temperature data represents the temperature at the surface of the sea ice, or the temperature corresponding to the snow-ice interface. Antarctic sea ice images from 2005 were obtained at approximate 5-day intervals corresponding to typical days of the four seasons, winter, spring, summer and fall. Available measurements conducted during previous field campaigns were obtained from the literature. The field data of snow-ice interface temperatures roughly corresponding to the typical days of the four seasons, albeit over much more limited areas of ice cover and at times different from the satellite images, were utilized for comparison. The field measurements give insight into the physical behavior of the Antarctic ice surface temperature. These field data show: 1) during the summer season, mean ice surface temperatures invariably range from 0 to -2ºC, corresponding to an isothermal snowpack or surface flooded with ocean water; 2) during the spring season, mean ice surface temperatures are generally above -8ºC, as increases in air temperature and solar radiation result in interface temperatures that lie between the air temperature (mean above -10ºC) and the seawater temperature at the ice-water interface (-1.8ºC); 3) during fall and winter seasons, warmest interface temperatures are found beneath the deepest snow cover, which either better insulates the surface from colder air temperatures than thin snow cover or causes surface flooding from the increased overburden, leading to sea ice interface temperatures near -1.8ºC. While the field data are not a validation sensu strictu, the AMSR-E product appears to conflict with several of these generally observed properties. The coldest interface temperatures from the satellite data are reported for spring and summer, which are lower than winter

  1. Modeling of Antarctic sea ice in a general circulation model

    SciTech Connect

    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. 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. 64 refs., 15 figs., 2 tabs.

  2. Evolution of microwave sea ice signatures during early summer and midsummer in the marginal ice zone

    NASA Technical Reports Server (NTRS)

    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.

  3. Winter Ice and Snow as Models of Igneous Rock Formation.

    ERIC Educational Resources Information Center

    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)

  4. MODIS Data at the National Snow and Ice Data Center: Improvements for Collection 6

    NASA Astrophysics Data System (ADS)

    Johnston, T.; Fowler, D. K.; McAllister, M.; Hall, D. K.; Riggs, G. A.

    2012-12-01

    For more than a decade, the National Snow and Ice Data Center (NSIDC) has archived and distributed snow cover and sea ice products derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments, onboard NASA's Earth Observing System (EOS) Aqua and Terra satellites. As the MODIS science team studies and refines the algorithms that generate these products, the Earth Observing System Data and Information System (EOSDIS) periodically reprocesses an entire collection of MODIS data and produces a new suite of products incorporating the latest enhancements. Collection 6 represents the next revision to NSIDC's MODIS archive, mainly affecting the snow-cover products. Based on scores of journal papers and workshop proceedings, 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. Although 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 region, 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. Finally, Collection 6 introduces new MODIS snow products, including a daily climate modeling-grid, cloud gap-filled (CGF) snow-cover map. The CGF algorithm generates cloud-free maps by using the most recent clear observation of the surface when the current day is cloudy, and tracks cloud persistence to account for uncertainties created by the age of a snow observation. By considering prior days, the CGF dramatically increases the number of observable grid cells and can potentially improve the accuracy of other snow-cover products

  5. Spatial and Temporal Variability of Surface Snow Accumulation and Snow Chemistry at East Antarctic Ice Sheet

    NASA Astrophysics Data System (ADS)

    Motoyama, H.; Ito, K.; Hirabayashi, M.

    2014-12-01

    Snow stakes along the traverse routes have been observed for long term monitoring program 'the variation of ice sheet surface mass balance' from the 1960's by the Japanese Antarctic Research Expedition in Shirase glacier drainage basin, East Antarctica. During the traverse route between coastal S16 point (69 02'S, 40 03'E, 580m a.s.l.) to inland Dome Fuji (77 22'S, 39 42'E, 3,810m a.s.l.), the snow stake observations every 2 km have been carried out from 1993. Yearly net snow accumulations from S16 to Dome Fuji were calculated. Heavy, modern and light snow events were observed. They were different in way accumulating spatial pattern depending on places. The yearly accumulation rates were compared with seasonal change of AAO-index (SAM). As a result, yearly accumulation rate and AAO-index showed the positive correlation.Surface snow samplings were conducted every 10km along the traverse route. Generally, the snow surface features are classified into three regions. (1) the coastal region: smooth surface, high snow accumulation (2) the katabatic slope region: rough sastrugi surface and smooth glazed surface(3) the high plateau region: smooth surface, little snow accumulation The chemistry of surface snow changes from the coast to inland. Furthermore, the chemical properties of snow are different for each surface at the same area. We can classify the surface snow with fresh drifting snow, deposited drift snow, soft and hard surface snow, sustrugi, surface hoar and so on. The value of each isotope ration and ion concentration greatly varied. Sometimes, snow might deposit thick equally. But the deposited snow was redistributed by the wind. When the snowstorm occurred, the blowing snow started to deposit in a certain opportunity. As for it, the area was not the uniform. It is necessary to discuss inhomogeneity of the depositional condition quantitatively.

  6. Impact of weather events on Arctic sea ice albedo evolution

    NASA Astrophysics Data System (ADS)

    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.

  7. Radiation Transport in the Atmosphere - Sea Ice - Ocean System.

    NASA Astrophysics Data System (ADS)

    Jin, Zhonghai

    1995-01-01

    A comprehensive radiative transfer model for the coupled atmosphere-sea ice-ocean system has been developed. The theoretical work required for constructing such a coupled model is described first. This work extends the discrete ordinate method, which has been proven to be effective in studies of radiative transfer in the atmosphere, to solve the radiative transfer problem pertaining to a system consisting of two strata with different indices of refraction, such as the atmosphere-ocean system and the atmosphere -sea ice-ocean system. The relevant changes (as compared to the standard problem with constant index of refraction throughout the medium) in formulation and solution of the radiative transfer equation, including the proper application of interface and boundary conditions, are presented. This solution is then applied to the atmosphere -sea ice-ocean system to study the solar energy balance in this coupled system. The input parameters required by the model are observable physical properties (e.g., the profiles of temperature and gas concentrations in the atmosphere, and the profiles of temperature, density, and salinity in the ice). The atmosphere, sea ice and ocean are each divided into a sufficient number of layers in the vertical to adequately resolve changes in their optical properties. This model rigorously accounts for the multiple scattering and absorption by atmospheric molecules, clouds, snow and sea water, as well as inclusions in the sea ice, such as brine pockets and air bubbles. The effects of various factors on the solar energy distribution in the entire system have been studied quantitatively. These factors include the ice salinity and density variations, cloud microphysics as well as variations in melt ponds and snow cover on the ice surface. Finally, the coupled radiative transfer model is used to study the impacts of clouds, snow and ice algae on the light transport in sea ice and in the ocean, as well as to simulate spectral irradiance and

  8. Mapping of ice layer extent and snow accumulation in the percolation zone of the Greenland ice sheet

    NASA Technical Reports Server (NTRS)

    Nghiem, S. V.; Steffen, K.; Neumann, G.; Huff, R.

    2005-01-01

    The Greenland ice sheet underwent record extensive melt in 2002 and prolonged melt in 2003. The severe melting created a significant and extensive ice layer over the Greenland ice sheet. An innovative approach is developed to detect the ice layer formation using data acquired by the SeaWinds scatterometer on the QuikSCAT satellite. QuikSCAT backscatter together with in situ data from automatic weather stations of the Greenland Climate Network are used to map the extent of ice layer formation. The results reveal areas of extensive ice layer formed by the 2002 melt, which is consistent with the maximum melt extent in 2002. Moreover, during freezing seasons, QuikSCAT data show a linear decrease in backscatter (in decibels or dB) that is related to the amount of snow accumulation in the ice layer formation region. This snow accumulation signature is caused by the attenuation of radar waves in the snow layer, accumulating since the last major melt event, whose thickness appears as an exponential function in relation to the backscatter signature. We use the Greenland Climate Network data to calibrate the QuikSCAT accumulation rate in order to estimate and map snow accumulation. QuikSCAT results capture the extreme snowfall in mid-April 2003, which deposited more than 0.5 m of snow in a day as measured by the automated weather station at the NASA South East site. Large-scale QuikSCAT results show an anomalous increase of snow accumulation over the southeast region of Greenland during the 2002-2003 freezing season.

  9. Mapping of ice layer extent and snow accumulation in the percolation zone of the Greenland ice sheet

    NASA Astrophysics Data System (ADS)

    Nghiem, S. V.; Steffen, K.; Neumann, G.; Huff, R.

    2005-06-01

    The Greenland ice sheet underwent record extensive melt in 2002 and prolonged melt in 2003. The severe melting created a significant and extensive ice layer over the Greenland ice sheet. An innovative approach is developed to detect the ice layer formation using data acquired by the SeaWinds scatterometer on the QuikSCAT satellite. QuikSCAT backscatter together with in situ data from automatic weather stations of the Greenland Climate Network are used to map the extent of ice layer formation. The results reveal areas of extensive ice layer formed by the 2002 melt, which is consistent with the maximum melt extent in 2002. Moreover, during freezing seasons, QuikSCAT data show a linear decrease in backscatter (in decibels or dB) that is related to the amount of snow accumulation in the ice layer formation region. This snow accumulation signature is caused by the attenuation of radar waves in the snow layer, accumulating since the last major melt event, whose thickness appears as an exponential function in relation to the backscatter signature. We use the Greenland Climate Network data to calibrate the QuikSCAT accumulation rate in order to estimate and map snow accumulation. QuikSCAT results capture the extreme snowfall in mid-April 2003, which deposited more than 0.5 m of snow in a day as measured by the automated weather station at the NASA South East site. Large-scale QuikSCAT results show an anomalous increase of snow accumulation over the southeast region of Greenland during the 2002-2003 freezing season.

  10. EOS Aqua AMSR-E Arctic Sea Ice Validation Program: Arctic2003 Aircraft Campaign Flight Report

    NASA Technical Reports Server (NTRS)

    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.

  11. Snow and Ice Applications of AVHRR in Polar Regions: Report of a Workshop

    NASA Technical Reports Server (NTRS)

    Steffen, K.; Bindschadler, R.; Casassa, G.; Comiso, J.; Eppler, D.; Fetterer, F.; Hawkins, J.; Key, J.; Rothrock, D.; Thomas, R.; Weaver, R.; Welch, R.

    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.

  12. Microwave signatures of snow and fresh water ice

    NASA Technical Reports Server (NTRS)

    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.

  13. Interactions Between Ice Thickness, Bottom Ice Algae, and Transmitted Spectral Irradiance in the Chukchi Sea

    NASA Astrophysics Data System (ADS)

    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.

  14. Level-ice melt ponds in the Los Alamos sea ice model, CICE

    NASA Astrophysics Data System (ADS)

    Hunke, Elizabeth C.; Hebert, David A.; Lecomte, Olivier

    2013-11-01

    A new meltpond parameterization has been developed for the CICE sea ice model, taking advantage of the level ice tracer available in the model. The ponds evolve according to physically based process descriptions, assuming a depth-area ratio for changes in pond volume. A novel aspect of the new scheme is that the ponds are carried as tracers on the level ice area of each thickness category, thus limiting their spatial extent based on the simulated sea ice topography. This limiting is meant to approximate the horizontal drainage of melt water into depressions in ice floes. Simulated melt pond processes include collection of liquid melt water and rain into ponds, drainage through permeable sea ice or over the edges of floes, infiltration of snow by pond water, and refreezing of ponds. Furthermore, snow that falls on top of ponds whose top surface has refrozen blocks radiation from penetrating into the ponds and sea ice below. Along with a control simulation, we present a range of sensitivity tests to parameters related to each subprocess described by the parameterization. With the exception of one parameter that alters the albedo of snow-covered pond ice, results are not highly sensitive to these parameters unless an entire process is removed. The snow simulation itself is critical, because the volume of snow deposition and rate of snow melt largely determine the timing and extent of the simulated melt ponds. Nevertheless, compensating effects moderate the model's sensitivity to precipitation changes. For instance, infiltration of the snow by melt water postpones the appearance of ponds and the subsequent acceleration of melting through albedo feedback, while snow on top of refrozen pond ice also reduces the ponds' effect on the radiation budget. By construction, the model simulation of level and ridged ice is also important for this parameterization. We find that as sea ice thins, either through time or when comparing sensitivity tests, the area of level ice

  15. Using IceBridge data to study changes on multi- and first-year sea ice in the western Arctic between 2009-2015

    NASA Astrophysics Data System (ADS)

    Boisvert, L.; Kurtz, N. T.; Stroeve, J. C.

    2015-12-01

    Since the late 1970's there has been a marked decrease in September sea ice extent and with that the sea ice pack has changed from a predominantly multi-year ice pack to one that is predominantly first-year ice. During this same period the sea ice has thinned, however the impact of snow depth changes on the overall state of the sea ice pack are relatively uncertain. In this study we use Lagrangian tracking ice type data along with IceBridge and CryoSat sea ice thickness and snow depth data products and surface temperature to examine the changes in the multi-year and first year ice regimes in March between 2009-2015. We will show the regional and annual changes in ice thickness and snow depth on multi-year and first year sea ice (as well as their locations) in the Canadian Arctic and Beaufort Sea. We will also anlalyze links in snow depth and thickness changes based on AIRS 925 hPa air temperature, 925 hPa geopotential height, precipitable water and Calipso cloud fraction in DJF, and changes in mixed layer temperatures to freeze-up dates. Lastly, we will analyze melt onset differences between multi-year and first- year sea ice to see how snow thickness and ice type play a role.

  16. Climate Sensitivity to Realistic Solar Heating of Snow and Ice

    NASA Astrophysics Data System (ADS)

    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.

  17. Arctic sea ice freeboard heights from satellite altimetry

    NASA Astrophysics Data System (ADS)

    Renganathan, Vidyavathy

    The Arctic sea ice cover is most sensitive to climate change and variability, mainly due to the ice-albedo feedback effect. With an increase in the average temperature across the Arctic during the past few decades, sea ice has been melting rapidly. The decline in the sea ice extent was estimated as 10% per decade since satellite observations began in 1979. Sea ice thickness is an important parameter that moderates the heat exchange between the ocean and the atmosphere, extent of sea ice deformation and sea ice circulation in the Arctic Ocean. In addition, sea ice thermodynamics and dynamics depend on the thickness of the sea ice cover. In order to estimate the trend in the sea ice volume, both the extent and thickness must be known. Hence, it is important to measure the sea ice freeboard (a representative fraction of the thickness) distribution in the Arctic Ocean. In this thesis, the total ice freeboards (height of the snow/ice surface above the sea level) were derived from satellite laser altimetry. NASA's Ice Cloud and Land Elevation Satellite (ICESat) carries a Geoscience Laser Altimetry System (GLAS) onboard, and provides dense coverage of snow (or sea ice) surface heights in the Arctic Ocean up to 86° N. The total freeboard height at each ICESat footprint location was computed by removing the instantaneous sea surface height from the ice/snow surface height. In this study, the instantaneous sea surface heights were modeled using a combination of geodetic and oceanographic models. In order to improve the accuracy of the freeboard estimation, an accuracy assessment of the ocean tide models (one of the component models in the sea surface height estimation) in the Arctic Ocean was performed. The Arctic Ocean Tide Inverse Model (AOTIM-5) was found to have the best accuracy in the Arctic Ocean and was, therefore, used in the sea ice freeboard estimation. It was also shown that the present generation of ocean tide models have ignored the ice-tide interaction

  18. Sea Ice on the Southern Ocean

    NASA Technical Reports Server (NTRS)

    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

  19. Influence of ice thickness and surface properties on light transmission through Arctic sea ice.

    NASA Astrophysics Data System (ADS)

    Katlein, Christian; Arndt, Stefanie; Nicolaus, Marcel; Jakuba, Michael V.; Laney, Samuel; Elliott, Stephen; Whitcomb, Louis L.; McFarland, Christopher J.; Suman, Stefano; Gerdes, Rüdiger; Boetius, Antje; German, Christopher R.

    2015-04-01

    The observed changes in physical properties of sea ice such as decreased thickness and increased melt pond cover severely impact the energy balance of Arctic sea ice. Increased light transmission leads to increased deposition of solar energy and thus plays a crucial role for sea-ice-melt as well as for the amount and timing of under-ice primary production. Recent developments in underwater technology provide new opportunities to undertake challenging research at the largely inaccessible underside of sea ice. We measured spectral under-ice radiance and irradiance onboard the new Nereid Under-Ice (Nereid-UI) underwater robotic vehicle, during a cruise of the R/V Polarstern to 83°N 6°W in the Arctic Ocean in July 2014. Nereid-UI is a next generation hybrid remotely operated vehicle (H-ROV) designed for both remotely-piloted and autonomous surveys underneath fixed and moving sea ice. Here we present results from the first comprehensive scientific dive of Nereid-UI employing its interdisciplinary sensor suite. We combine under-ice optical measurements with three dimensional under-ice topography (multibeam sonar) and aerial images of the surface conditions. We investigate the influence of spatially varying ice-thickness and surface properties on the spatial variability of light transmittance on floe scale. Our results indicate that surface properties dominate the spatial distribution of the under-ice light field, while sea ice-thickness and snow-depth are most important for mean light levels.

  20. Cladoceran zooplankton abundance under clear and snow-covered ice

    USGS Publications Warehouse

    DeBates, T.J.; Chipps, S.R.; Ward, M.C.; Werlin, K.B.; Lorenzen, P.B.

    2003-01-01

    We described the distribution of cladoceran zooplankton under the ice in a natural, glacial lake. Local light availability apparently altered the spatial distribution of cladocerans. Light levels measured under snow-covered areas (0.178 lux) were an order of magnitude less than those measured at the same depth under clear ice (1.750 lux). Cladoceran density under snow-covered areas was significantly higher (Bosmina spp.=3.34/L; Daphnia spp.=0.61/L) than cladoceran abundance under clear ice (Bosmina spp.=0.91/L; Daphnia spp.=0.19/L).

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  2. Observations of Recent Arctic Sea Ice Volume Loss and Its Impact on Ocean-Atmosphere Energy Exchange and Ice Production

    NASA Technical Reports Server (NTRS)

    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.

  3. Sea Ice Thickness Variability in Fram Strait

    NASA Astrophysics Data System (ADS)

    Gerland, S.; Renner, A.; Haas, C.; Nicolaus, M.; Granskog, M.; Hansen, E.; Hendricks, S.; Hudson, S. R.; Beckers, J.; Goodwin, H.

    2011-12-01

    On this poster, we show results from airborne electromagnetic (EM) sea ice thickness measurements demonstrating the temporal and spatial complexity of the ice thickness distribution in Fram Strait between Greenland and Svalbard. Knowledge about the spatial and temporal sea ice thickness distribution in the Arctic Ocean is necessary to assess the state of the sea-ice cover, and to understand relevant processes and changes. Since 2003, the Norwegian Polar Institute (NPI) has been conducting systematic in situ monitoring of sea ice thickness in the western Fram Strait, using both ground and airborne techniques. Fram Strait is a key region for large-scale ice dynamics in the Arctic. It represents the main export route for sea ice from the Arctic and the only deep strait connecting the interior Arctic Ocean and the rest of the world oceans. The ice thickness distribution in this region is the result of a combination of dynamic and thermodynamic sea ice processes. Transects for airborne EM observations were flown by NPI in spring 2005, 2008, and late summer 2010, and by the Alfred Wegener Institute in spring 2009. The regional ice thickness distributions are supplemented with ground measurements including snow thickness observations taken on ice stations during ship expeditions in spring 2005, 2007, and 2008 and annually in late summer from 2003 to 2011. From all these observations, we can show the differing characteristics of the thickness distributions in spring (2005, 2008, 2009) and late summer (2010) when the ice thickness is at its annual maximum (end of the freezing period) and minimum (end of the melting period), respectively. The ice thickness distribution can also vary spatially over short distances in north-south direction. Features such as the East Greenland Polynya, which varies in size for a given time from year to year, contribute to the spatial and temporal variability on the Greenlandic Shelf. In spring 2005, a gradient is visible across Fram Strait from

  4. The Relationship Between Arctic Sea Ice Albedo and the Geophysical Parameters of the Ice Cover

    NASA Astrophysics Data System (ADS)

    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

  5. Kindergarten Explorations with Snow, Ice, and Water

    ERIC Educational Resources Information Center

    Carroll, Martha A.

    1978-01-01

    Using winter snow, kindergarten students can explore the properties of water. Students demonstrate melting, freezing, expansion, and evaporation through a number of activities involving a paper cup and a scoop of snow. Procedures and student reactions are described in detail by the teacher-author. (MA)

  6. A Model of Surface Energy Budget over Water, Snow and Ice Surfaces

    NASA Astrophysics Data System (ADS)

    Wang, J.; Bras, R. L.

    2012-12-01

    The recently developed maximum entropy production (MEP) model of turbulent and conductive heat fluxes over land surfaces is generalized to water/snow/ice surfaces. Analogous to the case of land surfaces, an analytical solution of latent, sensible and surface water/snow/ice heat flux is derived as a function of surface temperature (e.g. sea surface temperature) and surface net short- and long wave radiation. Compared to the classical bulk transfer equations based models, the MEP model does not need wind speed, near-surface air temperature and roughness lengths as input. The model is parameter parsimonious. A test of the MEP model against observations from several field experiments has suggested its usefulness and potential for predicting conductive and turbulent fluxes over water/snow/ice surfaces. The model is a suitable tool for remote sensing of the surface energy balance over oceans, snow covered Antarctica and sea ice. The model can also be incorporated into regional and global atmospheric models as an alternative algorithm for surface energy/water balance.

  7. About uncertainties in sea ice thickness retrieval from satellite radar altimetry: results from the ESA-CCI Sea Ice ECV Project Round Robin Exercise

    NASA Astrophysics Data System (ADS)

    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

  8. C-Band Backscatter Measurements of Winter Sea-Ice in the Weddell Sea, Antarctica

    NASA Technical Reports Server (NTRS)

    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

  9. Measurements of sea ice proxies from Antarctic coastal shallow cores

    NASA Astrophysics Data System (ADS)

    Maffezzoli, Niccolò; Vallelonga, Paul; Spolaor, Andrea; Barbante, Carlo; Frezzotti, Massimo

    2015-04-01

    Despite its close relationship with climate, the climatic impact of sea ice remains only partially understood: an indication of this is the Arctic sea ice which is declining at a faster rate than models predict. Thus, the need for reliable sea ice proxies is of crucial importance. Among the sea ice proxies that can be extracted from ice cores, interest has recently been shown in the halogens Iodine (I) and Bromine (Br) (Spolaor, A., et al., 2013a, 2013b). The production of sea ice is a source of Sodium and Bromine aerosols through frost flower crystal formation and sublimation of salty blowing snow, while Iodine is emitted by the algae living underneath sea ice. We present here the results of Na, Br and I measurements in Antarctic shallow cores, drilled during a traverse made in late 2013 - early 2014 from Talos Dome (72° 00'S, 159°12'E) to GV7 (70° 41'S, 158° 51'E) seeking for sea ice signature. The samples were kept frozen until the analyses, that were carried out by Sector Field Mass Spectroscopy Inductive Coupled Plasma (SFMS-ICP): special precautions and experimental steps were adopted for the detection of such elements. The coastal location of the cores allows a clear signal from the nearby sea ice masses. The multiple cores are located about 50 km from each other and can help us to infer the provenance of the sea ice that contributed to the proxy signature. Moreover, by simultaneously determining other chemical elements and compounds in the snow, it is possible to determine the relative timing of their deposition, thus helping us to understand their processes of emission and deposition.

  10. Drifting snow climate of the Antarctic and Greenland ice sheets

    NASA Astrophysics Data System (ADS)

    Lenaerts, J. T. M.

    2013-02-01

    This study presents the drifting snow climate of the Earth's ice sheets, Antarctica and Greenland. For that purpose we use a regional atmospheric climate model, RACMO2. We included a routine that is able to calculate the drifting snow fluxes and accounts for the interaction between drifting snow on the one hand and the atmosphere and snow surface on the other. RACMO2 is run at 27 km resolution for Antarctica, and 11 km resolution for Greenland, and forced at its lateral boundaries by ECMWF reanalyses (32 years for Antarctica and 52 years for Greenland). Because direct evaluation for drifting snow is challenging due to sparseness of observational data, we focussed the model evaluation on the ability of RACMO2 to represent near-surface wind climate, temperature, surface mass balance, the extent of ablation areas and remote-sensed drifting snow frequency. We show that RACMO2 is very well able to represent the present-day near-surface climate of Antarctica and Greenland. Drifting snow occurs 20-80% of the time on Antarctica, depending on the local wind climate. Highest frequencies are found in the coastal areas, where drifting snow sublimation (SUds) removes up to 150 mm water equivalent of snow, whereas the high-elevation areas experience little or no SUds. Drifting snow erosion (ER­ds) can be negative (deposition) or positive (erosion), and varies generally between -50 and 50 mm in regions where the wind field convergences and diverges, respectively. Integrated over the ice sheet, SUds removes around 165 Gt of snow, which is equivalent to ~6% of the precipitated snow. The impact of ER­ds on the Antarctic ice sheet SMB is negligible . We found several feedbacks between SUds and the atmosphere. SUds moistens the near-surface atmosphere, limiting its own potential, but also enhancing precipitation in some coastal areas. By removing mass from the snow surface, drifting snow processes increase the top snow layer density, increasing the threshold wind speed for further

  11. Online sea ice data platform: www.seaiceportal.de

    NASA Astrophysics Data System (ADS)

    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.

  12. Active microwave classification of sea ice

    NASA Technical Reports Server (NTRS)

    Onstott, Robert G.

    1989-01-01

    Radar backscatter studies of Arctic sea ice have been carried out over a number of years with the intent to acquire physical property information through the examination of microwave signatures. The breadth of these studies continues to expand; as an example, measurements are now conducted at frequencies from 500 MHz to about 100 GHz. One of the scientific goals of this work has been to develop an improved outstanding of the scattering processes at play. A second, equally important goal has been to apply the knowledge gained in examining the backscatter response of ice and snow made in conjunction with the detailed scene characterizations, the insight gained through theoretical modeling and parametric study, and the data entered into the radar signature library to develop procedures to convert microwave signal information (available in the very near future) into valuable data products. This should ultimately provide a better understanding of the environment. The author discusses what has been learned through the many efforts associated with the near-surface scatterometer measurement programs and how the knowledge gained is assisting in the development of future sea ice type satellite algorithms. The logic and mechanisms used in discriminating sea ice types are presented.

  13. Data sets for snow cover monitoring and modelling from the National Snow and Ice Data Center

    NASA Astrophysics Data System (ADS)

    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.

  14. Microwave emission characteristics of sea ice

    NASA Technical Reports Server (NTRS)

    Edgerton, A. T.; Poe, G.

    1972-01-01

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

  15. NASA IceBridge: Scientific Insights from Airborne Surveys of the Polar Sea Ice Covers

    NASA Astrophysics Data System (ADS)

    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.

  16. Physical characteristics of summer sea ice across the Arctic Ocean

    USGS Publications Warehouse

    Tucker, W. B., III; 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.

  17. Investigation of radar backscattering from second-year sea ice

    NASA Technical Reports Server (NTRS)

    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.

  18. Arctic Sea Ice Minimum, 2015

    NASA Video Gallery

    This animation shows the evolution of the Arctic sea ice cover from its wintertime maximum extent, which was reached on Feb. 25, 2015, and was the lowest on record, to its apparent yearly minimum, ...

  19. Multiple Scattering of Laser Pulses in Snow Over Ice: Modeling the Potential Bias in ICESat Altimetry

    NASA Technical Reports Server (NTRS)

    Davis, A. B.; Varnai, T.; Marshak, A.

    2010-01-01

    The primary goal of NASA's current ICESat and future ICESat2 missions is to map the altitude of the Earth's land ice with high accuracy using laser altimetry technology, and to measure sea ice freeboard. Ice however is a highly transparent optical medium with variable scattering and absorption properties. Moreover, it is often covered by a layer of snow with varying depth and optical properties largely dependent on its age. We describe a modeling framework for estimating the potential altimetry bias caused by multiple scattering in the layered medium. We use both a Monte Carlo technique and an analytical diffusion model valid for optically thick media. Our preliminary numerical results are consistent with estimates of the multiple scattering delay from laboratory measurements using snow harvested in Greenland, namely, a few cm. Planned refinements of the models are described.

  20. Snow and Ice Crust Changes over Northern Eurasia since 1966

    NASA Astrophysics Data System (ADS)

    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

  1. Black Carbon and Dust in Snow and Ice on Snow Dome, Mt. Olympus

    NASA Astrophysics Data System (ADS)

    Kaspari, S.; Delaney, I.; Skiles, M.; Dixon, D. A.

    2012-12-01

    Deposition of black carbon (BC) and dust on highly reflective snow and glacier ice causes darkening of the surface, resulting in greater absorption of solar energy, heating of the snow/ice, and accelerated snow and glacier melt. The deposition of BC and dust may be affecting the timing and availability of water resources in the Pacific Northwest where the majority of runoff comes from snow and glacier melt, but minimal related research has taken place in this region. A recent modeling study suggested that BC deposition is causing a decrease in spring snow water equivalent and a shift to earlier peak runoff in the spring in the Western United States. Additionally, limited observations made in the early 1980s in Washington State determined that light absorbing impurities (e.g., BC and dust) were reducing the snow albedo. Since 2009, we have collected snow and ice samples from glaciers and the seasonal snowpack from spatially distributed sites in Washington State to determine impurity content, and to assess how impurity concentrations vary in relation to emission source proximity. Here we present results from the summer 2012 fieldwork on Snow Dome, Mt. Olympus in Washington State. Mt. Olympus is located upwind from major regional sources of BC and dust, but may receive BC from ocean shipping and trans-Pacific transport of BC and dust from large Asian sources. We used a field spectrometer to measure spectral albedo on Snow Dome, and analyzed surface snow samples and shallow ice cores to characterize the spatial and temporal variability of impurity deposition. Total impurity load was determined gravimetrically. Dust concentrations are inferred from ICPMS analyses and BC concentrations are determined using a Single Particle Soot Photometer (SP2), with select samples also analyzed for BC using a Sunset EC-OC to facilitate method inter-comparison. We assess the role that absorbing impurities may play in accelerating melt at Snow Dome, and briefly compare our results to

  2. CO2 deposition over the multi-year ice of the western Weddell Sea

    NASA Astrophysics Data System (ADS)

    Zemmelink, H. J.; Delille, B.; Tison, J. L.; Hintsa, E. J.; Houghton, L.; Dacey, J. W. H.

    2006-07-01

    Field measurements by eddy correlation (EC) indicate an average uptake of 0.6 g CO2 m-2 d-1 by the ice-covered western Weddell Sea in December 2004. At the same time, snow that covers ice floes of the western Weddell Sea becomes undersaturated with CO2 relative to the atmosphere during early summer. Gradients of CO2 from the ice to the atmosphere do not support significant diffusive fluxes and are not strong enough to explain the observed CO2 deposition. We hypothesize that the transport of air through the snow pack is controlled by turbulence and that undersaturation of CO2 is caused by biological productivity at the ice-snow and snow-atmosphere interface. The total carbon uptake by the multi-year ice zone of the western Weddell Sea in December could have been as high as 6.6 Tg C y-1.

  3. Arctic Sea Ice, Summer 2014

    NASA Video Gallery

    An animation of daily Arctic sea ice extent in summer 2014, from March 21, 2014 to Sept. 17, 2014 – when the ice appeared to reach it’s minimum extent for the year. It’s the sixth lowest minimum se...

  4. 30 CFR 56.11016 - Snow and ice on walkways and travelways.

    Code of Federal Regulations, 2013 CFR

    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....

  5. 30 CFR 56.11016 - Snow and ice on walkways and travelways.

    Code of Federal Regulations, 2010 CFR

    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....

  6. 30 CFR 56.11016 - Snow and ice on walkways and travelways.

    Code of Federal Regulations, 2011 CFR

    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....

  7. 30 CFR 56.11016 - Snow and ice on walkways and travelways.

    Code of Federal Regulations, 2014 CFR

    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....

  8. 30 CFR 56.11016 - Snow and ice on walkways and travelways.

    Code of Federal Regulations, 2012 CFR

    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....

  9. Physically-based Ice Thickness and Surface Roughness Retrievals over Rough Deformed Sea Ice

    NASA Astrophysics Data System (ADS)

    Li, Li; Gaiser, Peter; Allard, Richard; Posey, Pamela; Hebert, David; Richter-Menge, Jacqueline; Polashenski, Christopher; Claffey, Keran

    2016-04-01

    The observations of sea ice thickness and ice surface roughness are critical for our understanding of the state of the changing Arctic. Currently, the Radar and/or LiDAR data of sea ice freeboard are used to infer sea ice thickness via isostasy. The underlying assumption is that the LiDAR signal returns at the air/snow interface and radar signal at the snow/ice interface. The elevations of these interfaces are determined based on LiDAR/Radar return waveforms. However, the commonly used threshold-based surface detection techniques are empirical in nature and work well only over level/smooth sea ice. Rough sea ice surfaces can modify the return waveforms, resulting in significant Electromagnetic (EM) bias in the estimated surface elevations, and thus large errors in the ice thickness retrievals. To understand and quantify such sea ice surface roughness effects, a combined EM rough surface and volume scattering model was developed to simulate radar returns from the rough sea ice 'layer cake' structure. A waveform matching technique was also developed to fit observed waveforms to a physically-based waveform model and subsequently correct the roughness induced EM bias in the estimated freeboard. This new EM Bias Corrected (EMBC) algorithm was able to better retrieve surface elevations and estimate the surface roughness parameter simultaneously. Both the ice thickness and surface roughness retrievals are validated using in-situ data. For the surface roughness retrievals, we applied this EMBC algorithm to co-incident LiDAR/Radar measurements collected during a Cryosat-2 under-flight by the NASA IceBridge missions. Results show that not only does the waveform model fit very well to the measured radar waveform, but also the roughness parameters derived independently from the LiDAR and radar data agree very well for both level and deformed sea ice. For sea ice thickness retrievals, validation based on in-situ data from the coordinated CRREL/NRL field campaign demonstrates

  10. Ice nucleation: elemental identification of particles in snow crystals.

    PubMed

    Parungo, F P; Pueschel, R F

    1973-06-01

    A scanning field-emission electron microscope combined with an x-ray analyzer is used to locate the ice nucleus within a three-dimensional image of a snow crystal and determine the chemical composition of the nucleus. This makes it possible to better understand the effect of nuclei in cloud seeding. PMID:17806581

  11. Melting Ice, Rising Seas

    NASA Video Gallery

    Sea level rise is an indicator that our planet is warming. Much of the world's population lives on or near the coast, and rising seas are something worth watching. Sea level can rise for two reason...

  12. Halogen-based reconstruction of Russian Arctic sea ice area from the Akademii Nauk ice core (Severnaya Zemlya)

    NASA Astrophysics Data System (ADS)

    Spolaor, A.; Opel, T.; McConnell, J. R.; Maselli, O. J.; Spreen, G.; Varin, C.; Kirchgeorg, T.; Fritzsche, D.; Saiz-Lopez, A.; Vallelonga, P.

    2016-01-01

    The role of sea ice in the Earth climate system is still under debate, although it is known to influence albedo, ocean circulation, and atmosphere-ocean heat and gas exchange. Here we present a reconstruction of 1950 to 1998 AD sea ice in the Laptev Sea based on the Akademii Nauk ice core (Severnaya Zemlya, Russian Arctic). The chemistry of halogens bromine (Br) and iodine (I) is strongly active and influenced by sea ice dynamics, in terms of physical, chemical and biological process. Bromine reacts on the sea ice surface in autocatalyzing "bromine explosion" events, causing an enrichment of the Br / Na ratio and hence a bromine excess (Brexc) in snow compared to that in seawater. Iodine is suggested to be emitted from algal communities growing under sea ice. The results suggest a connection between Brexc and spring sea ice area, as well as a connection between iodine concentration and summer sea ice area. The correlation coefficients obtained between Brexc and spring sea ice (r = 0.44) as well as between iodine and summer sea ice (r = 0.50) for the Laptev Sea suggest that these two halogens could become good candidates for extended reconstructions of past sea ice changes in the Arctic.

  13. Snow crystal imaging using scanning electron microscopy: III. Glacier ice, snow and biota

    USGS Publications Warehouse

    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

  14. Antarctic Sea ice--a habitat for extremophiles.

    PubMed

    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. PMID:11809961

  15. Antarctic Sea Ice-a Habitat for Extremophiles

    NASA Astrophysics Data System (ADS)

    Thomas, D. N.; Dieckmann, G. S.

    2002-01-01

    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.

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

    USGS Publications Warehouse

    Douglas, D.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

  17. Polar bear and walrus response to the rapid decline in Arctic sea ice

    USGS Publications Warehouse

    Oakley, K.; Whalen, M.; Douglas, D.; Udevitz, M.; Atwood, T.; 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?

  18. Roughness of Weddell Sea Ice and Estimates of the Air-Ice Drag Coefficient

    NASA Astrophysics Data System (ADS)

    Andreas, Edgar L.; Lange, Manfred A.; Ackley, Stephen F.; Wadhams, Peter

    1993-07-01

    The roughness of a sheet of sea ice encodes its deformational history and determines its aerodynamic coupling with the overlying air and underlying water. Here we report snow surface, ice surface, and ice underside roughness computed from 47 surface elevation profiles collected during a transect of the Weddell Sea. The roughness for each surface, parameterized as the standard deviation of the surface elevation, segregates according to whether or not a floe has been deformed: deformed ice has greater roughness than undeformed ice. Regardless of deformational history, the underside roughness is almost always greater than the snow surface and ice surface roughnesses, which are nearly equal. Roughness spectra for all three surfaces and for both deformed and undeformed ice roll off roughly as k-1 when the wavenumber k is between 0.1 and 3 rad m-1. The snow surface and underside spectra roll off somewhat faster than k-1, and the ice surface spectra roll off somewhat slower than k-1. Both top and underside Arctic ice roughness spectra, on the other hand, have been reported to roll off faster than k-2. We speculate that the excess spectral intensity at high wavenumbers in the Antarctic ice surface spectra results from the small-scale roughness that the ice sheet had on consolidation. This excess high-wavenumber spectral intensity persists in the ice surface spectra of second-year ice. Evidently, once formed, the ice surface remains unchanged on the microscale until the entire ice sheet melts. With a remote measurement of roughness, we should be able to decide whether an ice floe is deformed or undeformed. Our spectral analysis hints that remote sensing may also be able to differentiate between first-year and second-year ice. From the snow surface spectra, we compute a roughness scale ξ that parameterizes the air-ice momentum coupling and lets us estimate the neutral stability drag coefficient referenced to a height of 10 m, CDN10. Typical CDN10 values are 1.1-1.4 × 10

  19. Recent ice sheet snow accumulation and firn storage of meltwater inferred by ground and airborne radars

    NASA Astrophysics Data System (ADS)

    Miege, Clement

    Recent surface mass balance changes in space and time over the polar ice sheets need to be better constrained in order to estimate the ice-sheet contribution to sea-level rise. The mass balance of any ice body is obtained by subtracting mass losses from mass gains. In response to climate changes of the recent decades, ice-sheet mass losses have increased, making ice-sheet mass balance negative and raising sea level. In this work, I better quantify the mass gained by snowfall across the polar ice sheets; I target specific regions over both Greenland and West Antarctica where snow accumulation changes are occurring due to rising air temperature. Southeast Greenland receives 30% of the total snow accumulation of the Greenland ice sheet. In this work, I combine internal layers observed in ice-penetrating radar data with firn cores to derive the last 30 years of accumulation and to measure the spatial pattern of accumulation toward the southeast coastline. Below 1800 m elevation, in the percolation zone, significant surface melt is observed in the summer, which challenges both firn-core dating and internal-layer tracing. While firn-core drilling at 1500 m elevation, liquid water was found at ˜20-m depth in a firn aquifer that persisted over the winter. The presence of this water filling deeper pore space in the firn was unexpected, and has a significant impact on the ice sheet thermal state and the estimate of mass balance made using satellite altimeters. Using a 400-MHz ice-penetrating radar, the extent of this widespread aquifer was mapped on the ground, and also more extensively from the air with a 750-MHz airborne radar as part of the NASA Operation IceBridge mission. Over three IceBridge flight campaigns (2011-2013), based on radar data, the firn aquifer is estimated to cover ˜30,000 km2 area within the wet-snow zone of the ice sheet. I use repeated flightlines to understand the temporal variability of the water trapped in the firn aquifer and to simulate its

  20. The NRL 2011 Airborne Sea-Ice Thickness Campaign

    NASA Astrophysics Data System (ADS)

    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

  1. Melt ponds and marginal ice zone from new algorithm of sea ice concentration retrieval

    NASA Astrophysics Data System (ADS)

    Repina, Irina; Tikhonov, Vasiliy; Komarova, Nataliia; Raev, Mikhail; Sharkov, Evgeniy

    2016-04-01

    Studies of spatial and temporal properties of sea ice distribution in polar regions help to monitor global environmental changes and reveal their natural and anthropogenic factors, as well as make forecasts of weather, marine transportation and fishing conditions, assess perspectives of mineral mining on the continental shelf, etc. Contact methods of observation are often insufficient to meet the goals, very complicated technically and organizationally and not always safe for people involved. Remote sensing techniques are believed to be the best alternative. Its include monitoring of polar regions by means of passive microwave sensing with the aim to determine spatial distribution, types, thickness and snow cover of ice. However, the algorithms employed today to retrieve sea ice characteristics from passive microwave sensing data for different reasons give significant errors, especially in summer period and also near ice edges and in cases of open ice. A new algorithm of sea ice concentration retrieval in polar regions from satellite microwave radiometry data is discussed. Beside estimating sea ice concentration, the algorithm makes it possible to indicate ice areas with melting snow and melt ponds. Melt ponds are an important element of the Arctic climate system. Covering up to 50% of the surface of drifting ice in summer, they are characterized by low albedo values and absorb several times more incident shortwave radiation than the rest of the snow and ice cover. The change of melt ponds area in summer period 1987-2015 is investigated. The marginal ice zone (MIZ) is defined as the area where open ocean processes, including specifically ocean waves, alter significantly the dynamical properties of the sea ice cover. Ocean wave fields comprise short waves generated locally and swell propagating from the large ocean basins. Depending on factors like wind direction and ocean currents, it may consist of anything from isolated, small and large ice floes drifting over a

  2. Variability of Arctic Sea Ice as Viewed from Space

    NASA Technical Reports Server (NTRS)

    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.

  3. Processes and imagery of first-year fast sea ice during the melt season

    NASA Technical Reports Server (NTRS)

    Holt, B.; Digby, S. A.

    1985-01-01

    In June and July 1982, a field program was conducted in the Canadian Arctic on Prince Patrick Island to study sea ice during the melt season with in situ measurements and microwave instrumentation operated near the surface and from aircraft. The objective of the program was to measure physical characteristics together with microwave backscatter and emission coefficients of sea ice during this major period of transition. The present paper is concerned with a study of both surface measurements and imagery of first-year fast ice during the melt season. The melting process observed in first-year fast ice was found to begin with the gradual reduction of the snow cover. For a two- to three-day period in this melt stage, a layer of superimposed ice nodules formed at the snow/ice interface as meltwater froze around ice and snow grains.

  4. Sea Ice Concentration and Extent

    NASA Technical Reports Server (NTRS)

    Comiso, Josefino C.

    2014-01-01

    Among the most seasonal and most dynamic parameters on the surface of the Earth is sea ice which at any one time covers about 3-6% of the planet. In the Northern Hemisphere, sea ice grows in extent from about 6 x 10(exp 6) sq km to 16 x 10(exp 6) sq km, while in the Southern Hemisphere, it grows from about 3 x 10(exp 6) sq km to about 19 x 10(exp 6) sq km (Comiso, 2010; Gloersen et al., 1992). Sea ice is up to about 2-3 m thick in the Northern Hemisphere and about 1 m thick in the Southern Hemisphere (Wadhams, 2002), and compared to the average ocean depth of about 3 km, it is a relatively thin, fragile sheet that can break due to waves and winds or melt due to upwelling of warm water. Being constantly advected by winds, waves, and currents, sea ice is very dynamic and usually follows the directions of the many gyres in the polar regions. Despite its vast expanse, the sea ice cover was previously left largely unstudied and it was only in recent years that we have understood its true impact and significance as related to the Earths climate, the oceans, and marine life.

  5. Ice loss from West Antarctica to the Bellingshausen Sea

    NASA Astrophysics Data System (ADS)

    Bingham, R. G.; Smith, A.; King, E. C.; Gudmundsson, G. H.; Thomas, E. R.

    2014-12-01

    Determination of Antarctica's ice-sheet mass balance (more correctly, mass imbalance) is of paramount concern due to its impact on global sea levels. Monitoring with satellite remote sensing since the early 1990s has demonstrated that the imbalance has become progressively more negative, with losses dominated by the ocean-forced drawdown of ice from West Antarctica into the Amundsen and Bellingshausen Seas. Recent years have hosted unprecedented study and increased understanding of the ice-ocean processes contributing to Amundsen-Sea losses, leaving ocean-forced ice-dynamical losses to the Bellingshausen Sea relatively neglected. We therefore present here, with the aid of dedicated field data in austral season 2009/2010, a detailed assessment of the mass imbalance of Ferrigno Ice Stream (FIS), the dominant contributor of mass directly to the Bellingshausen Sea. We assess mass imbalance using the input-output method for (i) 1992, and (ii) 2010; the temporal markers being defined by the acquisition of the first comprehensive satellite-velocity coverage and the acquisition of the field measurements respectively. Input by snowfall is estimated using existing maps of Antarctic snow accumulation calibrated with 2010-acquired field data in the form of a 20-m ice core recovered at the upper FIS ice divide and englacial layering across the catchment imaged with 500 MHz over-snow radar. Output by discharge across the grounding line requires measurements of ice velocity and depth across a "flux gate." In 2010, we obtained flux gate measurements directly from the field using DGPS and 2 MHz over-snow radar, and we also refer to satellite-acquired ice-velocity data (MeASUREs) and airborne-acquired ice depths (Operation IceBridge) acquired at a similar time. Output from 1992 is calculated using 1992-acquired satellite ice-velocities (Rignot, 2006) and ice depth retroactively inferred from the 2010-acquired ice depth corrected for 1992-2010 surface elevation loss. We calculate

  6. Dimethylsulfide emissions over the multi-year ice of the western Weddell Sea

    NASA Astrophysics Data System (ADS)

    Zemmelink, H. J.; Dacey, J. W. H.; Houghton, L.; Hintsa, E. J.; Liss, P. S.

    2008-03-01

    This study, conducted in December 2004, is the first to present observations of DMS in a snow pack covering the multi-year sea ice of the western Weddell Sea. The snow layer is important because it is the interface through which DMS needs to be transported in order to be emitted directly from the ice to the overlying atmosphere. High concentrations of DMS, up to 6000 nmol m-3, were found during the first weeks of December but concentrations sharply decline as late spring-early summer progresses. This implies that DMS contained in sea ice is efficiently vented through the snow into the atmosphere. Indeed, field measurements by relaxed eddy accumulation indicate an average release of 11 μmol DMS m-2 d-1 from the ice and snow throughout December.

  7. Arctic sea ice freeboard from AltiKa and comparison with CryoSat-2 and Operation IceBridge

    NASA Astrophysics Data System (ADS)

    Armitage, Thomas W. K.; Ridout, Andy L.

    2015-08-01

    Satellite radar altimeters have improved our knowledge of Arctic sea ice thickness over the past decade. The main sources of uncertainty in sea ice thickness retrievals are associated with inadequate knowledge of the snow layer depth and the radar interaction with the snow pack. Here we adapt a method of deriving sea ice freeboard from CryoSat-2 to data from the AltiKa Ka band radar altimeter over the 2013-14 Arctic sea ice growth season. AltiKa measures basin-averaged freeboards between 4.4 cm and 6.9 cm larger than CryoSat-2 in October and March, respectively. Using airborne laser and radar measurements from spring 2013 and 2014, we estimate the effective scattering horizon for each sensor. While CryoSat-2 echoes penetrate to the ice surface over first-year ice and penetrate the majority (82 ± 3%) of the snow layer over multiyear ice, AltiKa echoes are scattered from roughly the midpoint (46 ± 5%) of the snow layer over both ice types.

  8. Detection of ice crust formation on snow with satellite data

    NASA Astrophysics Data System (ADS)

    Bartsch, Annett; Bulygina, Olga N.; Kumpula, Timo; Forbes, Bruce; Stammler, Florian

    2010-05-01

    Short term thawing of the snow surface and subsequent refreeze can lead to the formation of ice crusts. These events are related to specific meteorological conditions such us rain-on-snow events and/or temporary increase of air temperature above zero degree Celsius. The structure change in the snow pack has adverse effect especially on wild life and also the local community related to reindeer herding. Active microwave satellite data can be used to monitor changes of snow related to thawing. So far they have been mostly employed for spring thaw detection. Coarse spatial resolution sensors such as scatterometer feature short revisit intervals. Seawinds QuikScat (Ku-band, 25km, 1999-2009) acquired data several times per day at high latitudes. This allows precise detection of the timing of thaw events. Also the change of structure in the snow itself impacts the backscatter. Values increase significantly. A method has been developed to monitor these events at high latitudes (>60°N) on circumpolar scale. Validation is carried out based on air temperature records and snow course data over Northern Eurasia. Events during midwinter of the last nine years (November - February 2000/1 - 2008/9) have been frequent in northern Europe, European Russia and Alaska. They have occurred up to once a year in central Siberia, the Russian Far East and most of northern Canada. Monitoring is important as such events are discussed in relation to climate change especially over Northern Eurasia.

  9. Improving the WRF model's (version 3.6.1) simulation over sea ice surface through coupling with a complex thermodynamic sea ice model (HIGHTSI)

    NASA Astrophysics Data System (ADS)

    Yao, Yao; Huang, Jianbin; Luo, Yong; Zhao, Zongci

    2016-06-01

    Sea ice plays an important role in the air-ice-ocean interaction, but it is often represented simply in many regional atmospheric models. The Noah sea ice scheme, which is the only option in the current Weather Research and Forecasting (WRF) model (version 3.6.1), has a problem of energy imbalance due to its simplification in snow processes and lack of ablation and accretion processes in ice. Validated against the Surface Heat Budget of the Arctic Ocean (SHEBA) in situ observations, Noah underestimates the sea ice temperature which can reach -10 °C in winter. Sensitivity tests show that this bias is mainly attributed to the simulation within the ice when a time-dependent ice thickness is specified. Compared with the Noah sea ice model, the high-resolution thermodynamic snow and ice model (HIGHTSI) uses more realistic thermodynamics for snow and ice. Most importantly, HIGHTSI includes the ablation and accretion processes of sea ice and uses an interpolation method which can ensure the heat conservation during its integration. These allow the HIGHTSI to better resolve the energy balance in the sea ice, and the bias in sea ice temperature is reduced considerably. When HIGHTSI is coupled with the WRF model, the simulation of sea ice temperature by the original Polar WRF is greatly improved. Considering the bias with reference to SHEBA observations, WRF-HIGHTSI improves the simulation of surface temperature, 2 m air temperature and surface upward long-wave radiation flux in winter by 6, 5 °C and 20 W m-2, respectively. A discussion on the impact of specifying sea ice thickness in the WRF model is presented. Consistent with previous research, prescribing the sea ice thickness with observational information results in the best simulation among the available methods. If no observational information is available, we present a new method in which the sea ice thickness is initialized from empirical estimation and its further change is predicted by a complex thermodynamic

  10. Observed and Modeled Trends in Southern Ocean Sea Ice

    NASA Technical Reports Server (NTRS)

    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