Science.gov

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. Winter snow cover on sea ice in the Weddell Sea

    NASA Astrophysics Data System (ADS)

    Massom, Robert A.; Drinkwater, Mark R.; Haas, Christian

    1997-01-01

    Measurements of snow thickness, temperature, salinity, density, and stratigraphy acquired during the 1992 Winter Weddell Gyre Study are presented. Results indicate that the winter snow cover on sea ice in the Weddell Sea is extremely variable. Extreme fluctuations in Antarctic synoptic conditions (air temperature, precipitation, humidity, and wind speed) occur during the austral winter. They result in unique modifications and additions to the snow layer during the aging process and act to stabilize an otherwise easily wind-redistributed shallow snow cover and develop well-packed drift features. The latter occur even over relatively undeformed areas of sea ice and have a significant localized effect on the snow thickness distribution. Significant variability in snow grain size (mean 2.733.12 mm) and density (0.320.09 g cm-3) is observed as a result of cyclical switches between high- and low-temperature gradient metamorphism. Multiple icy layers indicate multiple thaw-freeze events. One such event occurred during a 3-day station, during which the air temperature rose by 22C in 12 hours (to approximately 0C). This paper also examines mechanisms for flooding of the snow-ice interface, including snow loading. Even where the latter is not a factor, the layer of snow immediately above the snow-ice interface is commonly damp and saline (>10). Limitations in the data set are discussed, and comparisons are drawn with other experiments.

  3. Interdecadal Changes in Snow Depth on Arctic Sea Ice

    NASA Technical Reports Server (NTRS)

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

    2014-01-01

    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 Ice- Bridge 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 35.169.4 to 22.261.9 cm in the western Arctic, and from 32.869.4 to 14.561.9 cm in the Beaufort and Chukchi seas. These changes suggest a snow depth decline of 37629% in the western Arctic and 56633% in the Beaufort and Chukchi seas. Thinning is negatively correlated with the delayed onset of sea ice freezeup during autumn.

  4. 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.

  5. Winter snow cover variability on East Antarctic sea ice

    NASA Astrophysics Data System (ADS)

    Massom, R. A.; Lytle, V. I.; Worby, A. P.; Allison, I.

    1998-10-01

    Analysis of the first detailed data set of snow characteristics collected over East Antarctic sea ice in winter confirms that on small scales, snow on Antarctic sea ice is highly variable in both thickness and properties. High-amplitude cyclical variability in atmospheric forcing related to the passage of storms is responsible for the high degree of textural heterogeneity observed. Changes in snow properties were examined over a 3-week period, during which a largely icy snow cover, formed at near-freezing temperatures, metamorphosed to snow in which facetted crystals and depth hoar dominated, as the air temperature plummeted. Even on flat ice, significant localized thickening of snow occurs in the form of barchan dunes. Although we observed great variability in snow thickness and properties on local scales, overall snow thickness distribution and the complex textural assemblage of snow types are similar from region to region. Similar observations were made by Sturm et al. [1998] in West Antarctica. Large-scale similarities are also apparent in mean snow density, grain size, and bulk snow salinity, although high variability is again found across individual floes. Rapid depth hoar formation is a ubiquitous process that greatly affects the density, texture, grain size, and effective thermal conductivity of the snow cover. The observed heterogeneity results in varying snow effective thermal conductivities. The mean bulk effective thermal conductivity, computed from the proportion of observed snow types, is 0.164 W m-1 K-1, significantly lower than values typically used in large-scale sea ice modeling but similar to that derived by Sturm et al. [1998] in a near-simultaneous experiment in the Bellingshausen and Ross Seas. It varies from 0.097 to 0.383 W m-1 K-1 in different snow pits. The findings support those of Sturm et al. [1998] that periodic flooding and subsequent snow ice formation, which are also ubiquitous processes, effectively diminish the degree to which basal snow processes create inhomogeneities in the snow pack.

  6. Microwave Signatures of Snow on Sea Ice: Modeling

    NASA Technical Reports Server (NTRS)

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

    2006-01-01

    Accurate knowledge of snow-depth distribution over sea ice is critical for polar climate studies. Current snow-depth-over-sea-ice retrieval algorithms do not sufficiently account for variations in snow and ice physical properties that can affect the accuracy of retrievals. For this reason, airborne microwave observations were coordinated with ground-based measurements of snow depth and snow properties in the vicinity of Barrow, AK, in March 2003. In this paper, the effects of snowpack properties and ice conditions on microwave signatures are examined using detailed surface-based measurements and airborne observations in conjunction with a thermal microwave-emission model. A comparison of the Microwave Emission Model of Layered Snowpacks (MEMLS) simulations with detailed snowpack and ice data from stakes along the Elson Lagoon and the Beaufort Sea and ra- 'diometer data taken from low-level flights using a Polarimetric Scanning Radiometer (PSR-A) shows that MEMLS can be used to simulate snow on sea ice and is a useful tool for understanding the limitations of the snow-depth algorithm. Analysis of radiance data taken over the Elson Lagoon and the Beaufort Sea using MEMLS suggests that the radiometric differences between the two locations are due to the differences in sea-ice emissivity. Furthermore, measured brightness temperatures suggest that the current snow-depth retrieval algorithm is sufficient for areas of smooth first-year sea ice, whereas new algorithm coefficients are needed for rough first-year sea ice. Snowpack grain size and density remain an unresolved issue for snow-depth retrievals using passive-microwave radiances.

  7. Microwave Signatures of Snow on Sea Ice: Observations

    NASA Technical Reports Server (NTRS)

    Markus, Thorsten; Cavalieri, Donald J.; Gasiewski, Albin J.; Klein, Marian; Maslanik, James A.; Powell, Dylan C.; Stankov, B. Boba; Stroeve, Julienne C.; Sturm, Matthew

    2006-01-01

    Part of the Earth Observing System Aqua Advanced Microwave Scanning Radiometer (AMSR-E) Arctic sea ice validation campaign in March 2003 was dedicated to the validation of snow depth on sea ice and ice temperature products. The difficulty with validating these two variables is that neither can currently be measured other than in situ. For this reason, two aircraft flights on March 13 and 19,2003, were dedicated to these products, and flight lines were coordinated with in situ measurements of snow and sea ice physical properties. One flight was in the vicinity of Barrow, AK, covering Elson Lagoon and the adjacent Chukchi and Beaufort Seas. The other flight was farther north in the Beaufort Sea (about 73 N, 147.5 W) and was coordinated with a Navy ice camp. The results confirm the AMSR-E snow depth algorithm and its coefficients for first-year ice when it is relatively smooth. For rough first-year ice and for multiyear ice, there is still a relationship between the spectral gradient ratio of 19 and 37 GHz, but a different set of algorithm coefficients is necessary. Comparisons using other AMSR-E channels did not provide a clear signature of sea ice characteristics and, hence, could not provide guidance for the choice of algorithm coefficients. The limited comparison of in situ snow-ice interface and surface temperatures with 6-GHz brightness temperatures, which are used for the retrieval of ice temperature, shows that the 6-GHz temperature is correlated with the snow-ice interface temperature to only a limited extent. For strong temperature gradients within the snow layer, it is clear that the 6-GHz temperature is a weighted average of the entire snow layer.

  8. The Effect of Excess Snow on Sea Ice in a Global Ice-Ocean Prediction System

    NASA Astrophysics Data System (ADS)

    Winter, B.; Bélair, S.; Lemieux, J. F.

    2014-12-01

    Snow cover on sea ice acts as a thermal insulator, greatly reducing the upward heat flux from the ocean through the ice, specifically through thin ice. The treatment of snow in the CICE sea ice model does not include the effects of blowing snow, thereby leading to an unrealistically thick snow layer on the ice. We investigate the consequences of this excess snow for the upward heat fluxes throughout the year, and how this impacts forecast accuracy in a global ice-ocean prediction model (GIOPS). First results will be presented, and computationally efficient solutions will be discussed.

  9. 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).

  10. 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.

  11. 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

  12. 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.

  13. 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.

  14. 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 comparison of snow depths with two weeks elapsed between passes. [1] Farrell, S.L., et al., "A First Assessment of IceBridge Snow and Ice Thickness Data Over Arctic Sea Ice," IEEE Tran. Geoscience and Remote Sensing, Vol. 50, No. 6, pp. 2098-2111, June 2012. [2] Kwok, R., and G. F. Cunningham, "ICESat over Arctic sea ice: Estimation of snow depth and ice thickness," J. Geophys. Res., 113, C08010, 2008. [3] Kwok, R., et al., "Airborne surveys of snow depth over Arctic sea ice," J. Geophys. Res., 116, C11018, 2011. [4] Panzer, B., et al., "An ultra-wideband, microwave radar for measuring snow thickness on sea ice and mapping near-surface internal layers in polar firn," Submitted to J. Glaciology, July 23, 2012. [5] Wingham, D.J., et al., "CryoSat: A Mission to Determine the Fluctuations in Earth's Land and Marine Ice Fields," Advances in Space Research, Vol. 37, No. 4, pp. 841-871, 2006. [6] Zwally, H. J., et al., "ICESat's laser measurements of polar ice, atmosphere, ocean, and land," J. Geodynamics, Vol. 34, No. 3-4, pp. 405-445, Oct-Nov 2002. [7] Zwally, H. J., et al., "ICESat measurements of sea ice freeboard and estimates of sea ice thickness in the Weddell Sea," J. Geophys. Res., 113, C02S15, 2008.

  15. 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 conditions lead to high thickness and high local variability. Ice platelets were observed regularly in the boreholes, but measurement techniques have to be improved to assess the thickness of the platelet layer.

  16. 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.

  17. Sea ice and snow evolution in Rijpfjorden, Svalbard, and the importance of superimposed ice formation

    NASA Astrophysics Data System (ADS)

    Wang, C.; Gerland, S.; Spreen, G.; Cheng, B.; Eltoft, T.

    2013-12-01

    Many Svalbard fjords are usually covered or partly covered by seasonal landfast ice during winter and spring months, which provides a stable research platform for studying sea ice properties. In winter 2010/2011 Rijpfjorden (80°N, 22°E), a fjord at the north coast of the Nordaustlandet (Svalbard), was covered by landfast sea ice from early November 2010 to 11 July 2011. To monitor spring sea ice evolution in this fjord, an Ice Mass Balance (IMB) buoy was deployed between April and June 2011. Ice cores were collected at the time when the IMB was installed and recovered. From April to June, there was no significant change at the ice bottom in terms of bottom freezing or melting. However, the ice core samples suggested a growth of superimposed ice of about 6 cm at ice/snow interface, which account for 86% of the total variation of ice thickness between April and June. A one-dimensional thermodynamic sea ice model was applied to simulate snow and ice thicknesses, and the snow/ice transition during the freezing and melting season in Rijpfjorden using external forcing from a nearby shore-based weather station and the operational analysis and short-term forecasts of the European Centre for Medium-Range Weather Forecasts (ECMWF). Atmospheric conditions under which transformation from snow to ice occur are described. The findings improve our understanding of Arctic sea ice evolution, and they also help for better interpretation of satellite ice thickness products.

  18. Tools for Accessing and Manipulating MODIS Snow & Sea Ice Products at the National Snow and Ice Data Center

    NASA Astrophysics Data System (ADS)

    Kaminski, M.; Khalsa, S.; Haran, T.; Wolfe, J.

    2004-12-01

    Snow and sea ice cover are some of the more important spatial features of the Earth's surface that can be readily measured from space. Moderate Resolution Imaging Spectroradiometer (MODIS) instruments onboard NASA's Terra and Aqua spacecraft collect spectral data that are used to routinely produce snow cover and sea ice products. With higher spatial and spectral resolution, the MODIS snow and ice products (including snow albedo and sea ice surface temperature) improve upon a long history of global coverage satellite-derived products that have been produced from polar-orbiting satellites since the early 1970s. Fully automated, quality controlled, daily global maps of snow cover and sea ice extent, produced at 500m, 1000m, and 0.05° spatial resolutions by the MODIS Land Team, are available from the National Snow and Ice Data Center (NSIDC) Distributed Active Archive Center (DAAC). The product suite will be further enhanced beginning mid-2005 with the inclusion of fractional snow cover in the daily product, addition of a daily snow product in a polar projection, and production of monthly climate modeling grid products for both snow and sea ice. Several tools are now available to streamline data acquisition and processing for users. Automated access to current data can be obtained through ingest subscriptions, data pool cache scripting, and a machine-to-machine gateway. Users can select data with targeted interfaces and the EOS Data Gateway, both with online reduced-resolution images to allow users to identify usable data prior to ordering. Integrated data manipulation tools provide subsetting, gridding, and resampling of images prior to downloading, minimizing the burden of data management by users. Collectively, the suite enables users to efficiently manage the large quantity of MODIS data available for regional and global studies.

  19. Effects of subgrid-scale snow thickness variability on radiative transfer in sea ice

    NASA Astrophysics Data System (ADS)

    Abraham, Carsten; Steiner, Nadja; Monahan, Adam; Michel, Christine

    2015-08-01

    Snow is a principal factor in controlling heat and light fluxes through sea ice. With the goal of improving radiative and heat flux estimates through sea ice in regional and global models without the need of detailed snow property descriptions, a new parameterization including subgrid-scale snow thickness variability is presented. One-parameter snow thickness distributions depending only on the gridbox-mean snow thickness are introduced resulting in analytical solutions for the fluxes of heat and light through the snow layer. As the snowpack melts, these snow thickness distributions ensure a smooth seasonal transition of the light field under sea ice. Spatially homogenous melting applied to an inhomogeneous distribution of snow thicknesses allows the appearance of bare sea ice areas and melt ponds before all snow has melted. In comparison to uniform-thickness snow used in previous models, the bias in the under sea-ice light field is halved with this parameterization. Model results from a one-dimensional ocean turbulence model coupled with a thermodynamic sea ice model are compared to observations near Resolute in the Canadian High Arctic. The simulations show substantial improvements not only to the light field at the sea ice base which will affect ice algal growth but also to the sea ice and seasonal snowpack evolution. During melting periods, the snowpack can survive longer while sea ice thickness starts to reduce earlier.

  20. 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

  1. 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.

  2. 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.

  3. Improving Surface Mass Balance Over Ice Sheets and Snow Depth on Sea Ice

    NASA Astrophysics Data System (ADS)

    Koenig, Lora; Box, Jason; Kurtz, Nathan

    2013-03-01

    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.

  4. Theoretical models for microwave remote sensing of snow-covered sea ice

    NASA Technical Reports Server (NTRS)

    Lin, F. C.; Kong, J. A.; Shin, R. T.

    1987-01-01

    The volume scattering effects of snow-covered sea ice are studied with a three-layer random medium model for microwave remote sensing. Theoretical results are illustrated by matching experimental data for dry snow-covered thick first-year sea ice at Point Barrow. The radar backscattering cross sections are seen to increase with snow cover for snow-covered sea ice, due to the increased scattering effects in the snow layer. The results derived can also be applied to passive remote sensing.

  5. Considering the optical properties of snow (and sea ice) as a function of snowpack (and sea ice) chemistry and considering photochemistry of snow (and sea ice) as a function of optical properties of the snow and sea ice -what can we learn? (Invited)

    NASA Astrophysics Data System (ADS)

    King, M. D.

    2013-12-01

    The deposition of aerosol to snowpack can change the optical properties of snowpack and provide a radiative forcing for modern climate change. Changing the optical properties of snow and sea ice will change the photochemistry occurring in snow and seaice and the atmosphere directly above them. So how will the chemistry of snow and sea ice effect modern climate change and how will modern climate change effect the photochemistry in snow and sea ice. The talk will explore the interplay between climate change, photolytic reactions in snow and sea-ice and the optical properties of snow and sea-ice. It will focus on the dependence of snow and ice optical properties on the chemistry of material deposited to the snow/sea ice and then focus on the photochemistry in the snowpack from optical properties of the snow and sea ice. Specifically: 1) The effect of deposited aerosol on the reflectivity, light penetration and photolytic reactions in snowpack responsible for fluxes of chemicals from snow to the atmosphere and production of radical species within the snow and sea ice. The transmission of photosynthetic radiation will also be considered as a function of the light absorbing material in the snow and sea ice. Simulations will be presented demonstrating that different sea ices and snowpacks respond to deposited aerosol (including black carbon, HULIS and mineral dust) differently - depending on their physical properties. How much more sensitive is a melting snowpack to deposited aerosol than a cold polar snowpack? 2) The potential effects of climate change on the optical properties of snow and sea-ice and thus the potential effects of climate change on the photolytic production of radicals and gases within the snowpack as well as the transmission of PAR through the snow and seaice will be shown. The talk will present results from simulation, using sea ice grown in tanks at RHUL (the first results) and modelling of snow and seaice optical and chemical properties.

  6. 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.

  7. Wideband radar for airborne measurements of snow thickness on sea ice

    NASA Astrophysics Data System (ADS)

    Panzer, B.; Leuschen, C.; Blake, W.; Crowe, R.; Patel, A.; Gogineni, P. S.; Markus, T.

    2010-12-01

    Ocean-ice-atmosphere interactions are modulated by snow cover on the sea ice due to the low thermal conductivity and high reflectivity of snow. Current sea ice models use climatological data to simulate a snow cover on the sea ice. Snow cover is also the main source of error in deriving sea ice thickness from freeboard height measurements made by satellite-borne radar and laser altimeters. To improve sea ice models, and, ultimately, global climate models accurate knowledge of snow thickness of sea ice over a large area, with fine spatial resolution is desired. The Center for Remote Sensing of Ice Sheets at the University of Kansas has developed a wideband, frequency-modulated, continuous-wave (FMCW) radar for measuring snow thickness on sea ice from a fast-moving, long-range aircraft. The wideband radar, referred to as the Snow Radar, has been successfully deployed on multiple NASA Operation IceBridge missions. Basic waveform parameters of the Snow Radar are a 2.0 to 6.5 GHz bandwidth with a 250-us pulse length. However, with the FMCW radar architecture intermediate frequencies in the range of 31-62 MHz are digitized. The Snow Radar was designed to operate from a nominal altitude of 1500 ft above ground level, but can withstand +/- 500 ft of altitude variation without tweaking the nominal waveform parameters. Vertical resolution of the Snow Radar in snow, assuming a density of 0.3 g/cm3 and after application of a fast-time Hann window, is approximately 5.25 cm. We will discuss radar hardware, performance specifications, signal processing, measurements attained and provide preliminary results from the 2009-2010 Operation IceBridge missions. Representative Snow Radar processing output from 04/02/09 Thule to Fairbanks flight

  8. Snow Cover on the Arctic Sea Ice: Model Validation, Sensitivity, and 21st Century Projections

    NASA Astrophysics Data System (ADS)

    Blazey, Benjamin Andrew

    The role of snow cover in controlling Arctic Ocean sea ice thickness and extent is assessed with a series of models. Investigations with the stand alone Community Ice CodE (CICE) show, first, a reduction in snow depth triggers a decrease in ice volume and area, and, second, that the impact of increased snow is heavily dependent on ice and atmospheric conditions. Hindcast snow depths on the Arctic ice, simulated by the fully coupled Community Climate System Model (CCSM) are validated with 20th century in situ snow depth measurements. The snow depths in CCSM are found to be deeper than observed, likely due to excessive precipitation produced by the component atmosphere model. The sensitivity of the ice to the thermal barrier imposed by the biased snow depth is assessed. The removal of the thermodynamic impact of the exaggerated snow depth increases ice area and volume. The initial increases in ice due to enhanced conductive flux triggers feedback mechanisms with the atmosphere and ocean, reinforcing the increase in ice. Finally, the 21st century projections of decreased Arctic Ocean snow depth in CCSM are reported and diagnosed. The changes in snow are dominated by reduced accumulation due to the lack of autumn ice cover. Without this platform, much of the early snowfall is lost directly to the ocean. While this decrease in snow results in enhanced conductive flux through the ice as in the validation sensitivity experiment, the decreased summer albedo is found to dominate, as in the CICE stand alone sensitivity experiment. As such, the decrease in snow projected by CCSM in the 21st century presents a mechanism to continued ice loss. These negative (ice growth due decreased insulation) and positive (ice melt due to decreased albedo) feedback mechanisms highlight the need for an accurate representation snow cover on the ice in order to accurately simulate the evolution of Arctic Ocean sea ice.

  9. Antarctic snow and sea ice processes: Effects on passive microwave emissions and AMSR-E sea ice products

    NASA Astrophysics Data System (ADS)

    Lewis, Michael John, Jr.

    In this research, passive microwave remote sensing products generated for the Antarctic sea ice zone from the Advance Microwave Scanning Radiometer-Earth Observing System (AMSR-E) sensor were compared with various in situ field measurements, both from previous Antarctic campaigns in the published literature and as obtained during the Sea Ice Mass Balance in the Antarctic (SIMBA) project during the International Polar Year (IPY) 2007--2008. Data gathered during the SIMBA project was used to understand the geophysical processes occurring in the sea ice and snow cover of the Bellingshausen Sea and to provide a physical basis for modeling of microwave emissions. In Chapter 2, the AMSR-E sea ice temperature product was compared with AMSR-E snow depth product and previous in situ field measurements. The comparisons were not intended to provide a strict validation of remote sensing products, but to evaluate the physical context of the remotely sensed data and examine potential trends. From examination of the data, it was found that the AMSR-E sea ice temperature product conflicted with several generally observed sea ice properties. The apparent contradictory behavior of the satellite data product is indicative of radiative temperature behavior related to changes in emissivity within the ice pack. Further comparisons of the AMSR-E sea ice temperature product with in situ temperature data from Ice Mass-balance Buoys (IMB) from two Antarctic field programs showed no correlation. However, apparent response of sea ice temperature product to snow/ice interface flooding events was noted. In Chapter 3, an important sea ice process related to the formation of "gap layers" within Antarctic sea ice was examined and modeled. Gap layers are horizontal voids that develop internally within the sea ice structure, often filled with decaying sea ice, saline slush, and a microbial biological community that thrives on the available nutrients. Gap layers are commonly observed in summer melt conditions in Antarctic sea ice, but are not widely observed in the Arctic. A thermodynamic model was developed based on a typical summer temperature gradient reversal in the snow pack and sea ice, typical salinity profile and heat flux to explain the internal melting of sea ice and formation of gap layers. The modeled rates of gap layer formation generally agreed with published field observations. In Chapter 4, an overview of the Sea Ice Mass Balance in the Antarctic (SIMBA) experiment is provided detailing various geophysical measurements and the observed snow and sea ice processes occurring during the winter-spring transition in the Bellingshausen Sea. Time series measurements were obtained for snow and sea ice conditions during a 27-day drift station through a number of atmospheric cycles of warming and cooling that are typical of the season for this region. Characteristic sites representing the range of snow and ice conditions on the drifting floe (Ice Station Belgica) were sampled at regular intervals to understand changing conditions in response to the atmospheric events. Detailed snow and ice properties and structure, including high resolution time-series records of snow and ice temperature were obtained from ice mass-balance buoys (IMBs) and other sources to record the changes. Chapter 5 presents the results of microwave emission modeling performed using the SIMBA field data, specifically processes that are commonly observed in the Antarctic sea ice zone that are considered to have an impact on passive microwave retrievals from space. In several model cases of varying snow cover thickness, the flooding of the snow-ice interface with sea water to form a saline slush layer in the snow cover was simulated. Additionally, a model case including brine wicking at the surface of first year sea ice with thin snow cover was simulated. These processes (related to Chapter 2) have been attributed to anomalous behavior in the AMSR-E sea ice temperature product and were identified as sources of error in other passive microwave sea ice products. The modeling results indicated that brightness temperature at low frequencies (6.9 and 10.7 GHz) showed a large decrease (on the order of 15 to 30 °K) and are consistent with previous laboratory experiments. Further time-series examination of microwave emissions from space, cross frequency and polarization responses, has potential to indicate areas with widespread snow/ice interface flooding. (Abstract shortened by UMI.)

  10. Properties of snow overlying the sea ice off East Antarctica in late winter, 2007

    NASA Astrophysics Data System (ADS)

    Toyota, Takenobu; Massom, Robert; Tateyama, Kazutaka; Tamura, Takeshi; Fraser, Alexander

    2011-05-01

    The properties of snow on East Antarctic sea ice off Wilkes Land were examined during the Sea Ice Physics and Ecosystem Experiment (SIPEX) in late winter of 2007, focusing on the interaction with sea ice. This observation includes 11 transect lines for the measurement of ice thickness, freeboard, and snow depth, 50 snow pits on 13 ice floes, and diurnal variation of surface heat flux on three ice floes. The detailed profiling of topography along the transects and the d 18O, salinity, and density datasets of snow made it possible to examine the snow-sea-ice interaction quantitatively for the first time in this area. In general, the snow displayed significant heterogeneity in types, thickness (mean: 0.14±0.13 m), and density (325±38 kg m -3), as reported in other East Antarctic regions. High salinity was confined to the lowest 0.1 m. Salinity and d 18O data within this layer revealed that saline water originated from the surface brine of sea ice in 20% of the total sites and from seawater in 80%. From the vertical profiles of snow density, bulk thermal conductivity of snow was estimated as 0.15 W K -1 m -1 on average, only half of the value used for numerical sea-ice models. Although the upward heat flux within snow estimated with this value was significantly lower than that within ice, it turned out that a higher value of thermal conductivity (0.3 to 0.4 W K -1 m -1) is preferable for estimating ice growth amount in current numerical models. Diurnal measurements showed that upward conductive heat flux within the snow and net long-wave radiation at the surface seem to play important roles in the formation of snow ice from slush. The detailed surface topography allowed us to compare the air-ice drag coefficients of ice and snow surfaces under neutral conditions, and to examine the possibility of the retrieval of ice thickness distribution from satellite remote sensing. It was found that overall snow cover works to enhance the surface roughness of sea ice rather than moderate it, and increases the drag coefficient by about 10%. As for thickness retrieval, mean ice thickness had a higher correlation with ice surface roughness than mean freeboard or surface elevation, which indicates the potential usefulness of satellite L-band SAR in estimating the ice thickness distribution in the seasonal sea-ice zone.

  11. The impact of snow depth, snow density and ice density on 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.

    2015-01-01

    We assess different methods and input parameters, namely snow depth, snow density and ice density, used in freeboard-to-thickness conversion of Arctic sea ice. This conversion is an important part of sea ice thickness retrieval from spaceborne altimetry. A data base is created comprising sea ice freeboard derived from satellite radar altimetry between 1993 and 2012 and co-locate observations of total (sea ice + snow) and sea ice freeboard from the Operation Ice Bridge (OIB) and CryoSat Validation Experiment (CryoVEx) airborne campaigns, of sea ice draft from moored and submarine upward looking sonar (ULS), and of snow depth from OIB campaigns, Advanced Microwave Scanning Radiometer (AMSR-E) and the Warren climatology (Warren et al., 1999). We compare the different data sets in spatiotemporal scales where satellite radar altimetry yields meaningful results. An inter-comparison of the snow depth data sets emphasizes the limited usefulness of Warren climatology snow depth for freeboard-to-thickness conversion under current Arctic Ocean conditions reported in other studies. We test different freeboard-to-thickness and freeboard-to-draft conversion approaches. The mean observed ULS sea ice draft agrees with the mean sea ice draft derived from radar altimetry within the uncertainty bounds of the data sets involved. However, none of the approaches are able to reproduce the seasonal cycle in sea ice draft observed by moored ULS. A sensitivity analysis of the freeboard-to-thickness conversion suggests that sea ice density is as important as snow depth.

  12. Evaluation of Icebridge Snow Radar Measurements over Sea Ice in the Canadian Arctic

    NASA Astrophysics Data System (ADS)

    Derksen, C.; King, J. M.; Howell, S.; Toose, P.; Silis, A.; Rutter, N.

    2014-12-01

    Recent efforts to retrieve snow depth on sea ice using the Operation IceBridge (OIB) snow radar have identified uncertainties related to the vertical heterogeneity of snow, ice deformation, and radar side lobes (e.g. Farrell, et. Al., 2012, Kurtz et. Al., 2013, Kwok and Maksym, 2014). To characterize and evaluate snow depth retrieval uncertainties as related to snow physical properties, an OIB mission was flown near Eureka, Nunavut (79°59'20"N, 85°56'27"W) within the Canadian Arctic archipelago as part of the 2014 OIB Arctic campaign. A series of 12 parallel flight lines covered a narrow swath of first year sea ice approximately 50 km in length. Immediately following the OIB mission, an intensive 10-day field campaign was completed to characterize snow and ice properties within the footprint of the OIB snow radar at multiple scales. Measurements were divided between two observation areas: (1) a primary sampling transect along the length of the flights to characterize horizontal variability in bulk snow properties and (2) a set of intensive grids (250 m x 250) to evaluate variations in snow properties sub-grid to OIB products. As part of each experiment, standard sampling methods were used to collect geo-located snow depth and snow pit measurements (stratigraphy, density, grain size, and salinity). More than 30,000 geo-located snow depth measurements were collected along the primary transect with 94% located within the snow radar footprint. The substantial volume of field measurements coincident with OIB snow radar observations provides an excellent opportunity to evaluate and advance the retrieval of radar-derived snow depth over sea ice. In this study, we present statistical analysis of the observed radar signal and measured snow properties at multiple scales to address previously identified ambiguities in the interpretation of the radar returns.

  13. Snow on Arctic sea ice: model representation and last decade changes

    NASA Astrophysics Data System (ADS)

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

    2015-10-01

    Together with sea ice, Arctic snow has experienced vast changes during the last decade due to a warming climate. Thus, it is relevant to study the past and present changes of Arctic snow to understand the implications to the sea ice component, precipitation, heat and radiation budgets. In this study, we analyze the changes of snow depth between 2000 and 2013 at regional scale represented in an Arctic coupled sea ice-general circulation model. We evaluate the model performance by direct comparison of the modeled snow depths (hs_mod) to snow depths from radar measurements from the NASA Operation IceBridge (hs_OIB) during the flight campaigns completed from 2009 to 2013. Despite the description of the snow in our model is simple (i.e. single layer without explicit snow redistribution processes) as in many current sea-ice models; the latitudinal distribution of hs_mod in the western Arctic is in good agreement to observations. The hs_mod is on average 3 cm thicker than hs_OIB in latitudes > 76° N. According to the model results, the hs in 2013 decreased 21 % with respect to the multi-year mean between 2000 and 2013. This snow reduction occurred mainly in FYI dominated areas, and is in good agreement to the year-to-year loss of sea ice, also well reproduced by the model. 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. Although the snow layer accumulates again every year, the long-term reduction in the summer sea-ice extent ultimately affects the maximum spring accumulation of snow. The model results exhibit a last decade thinning of the snowpack that is however one order of magnitude lower than previous estimates based on radar measurements. We suggest that the later is partially due to the lack of explicit snow redistribution processes in the model, emphasizing the need to include these in current sea-ice models to improve the snow representations.

  14. Evaluation of Operation IceBridge quick-look snow depth estimates on sea ice

    NASA Astrophysics Data System (ADS)

    King, Joshua; Howell, Stephen; Derksen, Chris; Rutter, Nick; Toose, Peter; Beckers, Justin F.; Haas, Christian; Kurtz, Nathan; Richter-Menge, Jacqueline

    2015-11-01

    We evaluate Operation IceBridge (OIB) "quick-look" snow depth on sea ice retrievals using in situ measurements taken over immobile first-year ice (FYI) and multiyear ice (MYI) during March of 2014. Good agreement was found over undeformed FYI (-4.5 cm mean bias) with reduced agreement over deformed FYI (-6.6 cm mean bias). Over MYI, the mean bias was -5.7 cm, but 54% of retrievals were discarded by the OIB retrieval process as compared to only 10% over FYI. Footprint scale analysis revealed a root-mean-square error (RMSE) of 6.2 cm over undeformed FYI with RMSE of 10.5 cm and 17.5 cm in the more complex deformed FYI and MYI environments. Correlation analysis was used to demonstrate contrasting retrieval uncertainty associated with spatial aggregation and ice surface roughness.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. Impact of snow and sea-ice variations on global climate change

    SciTech Connect

    Ledley, T.S.

    1992-03-01

    Recent work with a coupled energy balance climate-sea ice model has shown that sea ice has a large impact on the energy fluxes between the ocean and the atmosphere and thus on climate, especially in the polar regions. In this study the impact of the addition of snowfall on sea ice and its effect on climate is examined. The results show that the addition of snow introduces three major competing effects. The first effect is that the snow acts as an insulator, keeping the ice warm and thus thin. This would seem to produce a warming effect on the climate. The second is that snow has a lower volumetric specific heat than ice causing it to cool during the winter and warm during the summer more rapidly than ice. The third is that snow has a higher albedo than ice. This causes a reduction in the absorbed solar energy by the entire earth-atmosphere system and thus a cooling of the climate. The results described here indicate that the albedo effect is dominant, so that the addition of snow cools the climate.

  20. 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 snow medium, enhance the volume scattering contribution while turning the air-snow interface into an electromagnetically rough surface.

  1. 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 snow depth on sea ice and characterization of the regional sea ice thickness distribution. This poster will present preliminary data from the measurement campaign. This includes the in situ measurements of snow depth and ice thickness along the survey line. The NASA IceBridge airborne survey consisted of eleven parallel flight lines along the main in situ transect and two perpendicular passes at the northern and southern ends of the survey line, coincident with two corner reflectors. We will present initial IceBridge data, including ATM sea ice elevation and DMS photography which we use to estimate surface roughness and delineate sea ice provinces nearby the in situ survey. Preliminary data from the NRL over flights of the survey line will be presented in the poster by Brozena et al. (this session). The in situ and airborne data collected during the March 2011 campaign will be fully-documented and archived on the NASA IceBridge websites at NSIDC, allowing for their free access by the broad research community.

  2. 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.

  3. 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.

  4. 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.

  5. Ku-Band radar penetration into Snow over Arctic Sea Ice

    NASA Astrophysics Data System (ADS)

    Hendricks, S.; Stenseng, L.; Helm, V.; Hanson, S.; Haas, C.

    2009-12-01

    Sea ice freeboard measurements are of great interest for basin-scale ice mass balance monitoring. Typically, laser- and radar-altimeters are used for freeboard retrieval in operational systems such as aircrafts and satellites. For laser beams it can be assumed that the dominant reflector is the snow/air interface, whereas radar waves interact with the variable physical properties of the snow cover on the Arctic sea ice. In addition, radar elevation measurements may vary for different retracker algorithms, which determine the track point of the scattered echo power distribution. Since accurate knowledge of the reflection horizon is critical for sea ice thickness retrieval, validation data is necessary to investigate the penetration of radar waves into the snow for the upcoming CryoSat-2 mission. Furthermore, the combination of both optical and RF wavelengths might be used to derive snow thickness, if radar altimeters are capable of measuring the distance to the snow-ice interface reliably. We present the results of aircraft campaigns in the Arctic with a scanning laser altimeter and the Airborne SAR/Interferometric Radar Altimeter System (ASIRAS) of the European Space Agency. The elevation observations are converted into freeboard profiles, taking the different footprints into account when comparing the two systems. Based on the probability distribution of laser and radar freeboard we discuss the specific characteristics of both systems and the apparent radar penetration over sea ice in the northern Baltic Sea, the Greenland and Lincoln Sea. The results show differences in the penetration of Ku-Band radar between regions and interannual variability. In general, snow thickness could not be derived in the Arctic, whereas the penetration behavior correlates with other (QuikScat) remote sensing products.

  6. A tentative climatology of the snow load on Arctic sea ice based on satellite

    NASA Astrophysics Data System (ADS)

    Schroeder, T. M.; Pedersen, L. T.; Tonboe, R. T.

    2007-12-01

    Having a firm grasp of the sea ice extent carries over to the understanding of poleward energy transport, atmospheric heat exchange and high-latitude ocean dynamics at large. One reason to investigate the snow load is the insulation against exchange of heat. Another, regarding the intrinsic value of remote sensing, is that snow constitutes the greatest unknown in sea ice altimetry. The properties of snow can modify how deeply into the snow-ice system the altimeter signal penetrates. While Cryosat views to the ice surface, Icesat views to the snow surface. The freeboard cannot be measured and converted to ice thickness properly without compensation for the thickness and density of the snow cover. To identify the satellite channels with most information on the scenery, we made the standard assumption that the inversion of measured brightness temperature to physical parameters is sufficiently linear to converge for Gauss-Newtonian iteration. An optimal estimation scheme has been adopted and the information content in the averaging kernel matrix scrutinized for the parameters at stake. The a priori covariance and initial guess on parameters was computed by feeding the snow-ice model Memls with ERA40 atmospheric reanalysis over a range of locations, winters, and type of ice as having grown from either scratch (first-year) or not (multiyear). Each of the currently flown passive sounders under consideration, the Advanced Microwave Scanning Radiometer (AMSR), the Advanced Microwave Sounding Unit (AMSU), and the Microwave Humidity Sounder (MHS), is modelled with a measurement error taken as the sum of sensitivity and accuracy prior to launch. Covariance between the channels has been neglected. Simulation of the actual measurement discretizes the snow pack into ten numerical layers to resolve the steep temperature gradient and applies the model Rttov to represent the air column. Snow is taken to be fresh and dry, a valid assumption until melt sets in, and the density of multi-year ice is imposed a fixed decrease above the waterline. The correlation length in ice that governs scattering shifts from water content (brine) to air bubbles after the first year. The optimal set of satellite channels has been chosen, in part, by minimizing the number of platforms involved and the jumps in frequency between them. These channels provide the basis on which we intend to retrieve a snow climatology that spans the past few years. Construction requires iteration against the assumption that either type of ice alone was covering the surface pixel and then engagement with a lookup table to meet with the brightness temperature observed. Comparison of the seasonal and regional variability is made to reanalysis and in situ measurement.

  7. Evidence for a Significant Source of Sea Salt Aerosol from Blowing Snow Above Sea Ice in the Southern Ocean

    NASA Astrophysics Data System (ADS)

    Frey, M. M.; Brooks, I. M.; Anderson, P. A.; Nishimura, K.; Yang, X.; Jones, A. E.; Wolff, E. W.

    2014-12-01

    Over most of the Earth, sea salt aerosol (SSA) derives from sea spray and bubble bursting at the open ocean surface. SSA as the major component of marine aerosol contributes directly to the radiative balance and can act as cloud condensation nuclei. SSA can also significantly impact the lifetime of methane, ozone or mercury through the photochemical release of reactive halogens. A recent model study suggested that the sublimation of saline blowing snow above sea ice can generate more SSA than is produced from a similar area of open ocean. A winter cruise through the Weddell Sea during June - August 2013 provided unique access to a potential SSA source region in the Antarctic sea ice zone to test this hypothesis.Reported are first measurements of snow particle as well as aerosol concentrations, size distributions and chemical composition, during blowing snow events above sea ice. Snow particle spectra are found to be similar to those observed on the continent. Even though the salinity of surface and blowing snow was very low (<0.1 psu) a significant increase of aerosol in the SSA size range was observed during and after blowing snow events. This is consistent with model runs including a blowing snow parameterisation which suggest low sensitivity of SSA number densities to snow salinity within the observed range. First estimates of SSA flux from blowing snow using eddy correlation are significant, although falling below published values of the sea spray source function. We discuss the dependance of observed SSA production rates on ambient conditions as well as the significance to the Southern Ocean environment.

  8. 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.

  9. 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 evidence of meltwater flushing during the period of increasing melt pond coverage. At the same time, a significant amount of meltwater appeared to have drained through natural flaws (seal holes) rather than ice. Over the course of a few days, the area covered by melt ponds shrank as the meltwater table dropped toward the freeboard level. However, patches of near-impermeable ice persisted beyond this point. Laser-level transects showed that isolated puddles of elevated water level remained. The ice islands that developed during the early stages of melt persisted throughout the mature stages of ice melt. They were surrounded by ponds that typically contained dark ice patches that were apparent in the early stage of melt. Our observations on melt pond evolution may be useful in the context of interpreting and modeling regional differences in sea ice albedo and assessing the sensitivity of spring and early-summer ice albedo to changing Arctic snow and sea ice conditions.

  10. The impact of atmospheric mineral aerosol deposition on the albedo of snow and sea ice: are snow and sea ice optical properties more important than mineral aerosol optical properties?

    NASA Astrophysics Data System (ADS)

    Lamare, M. L.; Lee-Taylor, J.; King, M. D.

    2015-08-01

    Knowledge of the albedo of polar regions is crucial for understanding a range of climatic processes that have an impact on a global scale. Light absorbing impurities in atmospheric aerosols deposited on snow and sea ice by aeolian transport absorb solar radiation, reducing albedo. Here, the effects of five mineral aerosol deposits reducing the albedo of polar snow and sea ice are considered. Calculations employing a coupled atmospheric and snow/sea ice radiative-transfer model (TUV-snow) show that the effects of mineral aerosol deposits is strongly dependent on the snow or sea ice type rather than the differences between the aerosol optical characteristics. The change in albedo between five different mineral aerosol deposits with refractive indices varying by a factor of 2 reaches a maximum of 0.0788, whereas the difference between cold polar snow and melting sea ice is 0.8893 for the same mineral loading. Surprisingly, the thickness of a surface layer of snow or sea ice loaded with the same mass-ratio of mineral dust has little effect on albedo. On the contrary, multiple layers of mineral aerosols deposited during episodic events evenly distributed play a similar role in the surface albedo of snow as a loading distributed throughout, even when the layers are further apart. The impact of mineral aerosol deposits is much larger on melting sea ice than on other types of snow and sea ice. Therefore, the higher input of shortwave radiation during the summer melt cycle associated with melting sea ice accelerates the melt process.

  11. Influence of projected snow and sea-ice changes on future climate in heavy snowfall region

    NASA Astrophysics Data System (ADS)

    Matsumura, S.; Sato, T.

    2011-12-01

    Snow/ice albedo and cloud feedbacks are critical for climate change projection in cryosphere regions. However, future snow and sea-ice distributions are significantly different in each GCM. Thus, surface albedo in cryosphere regions is one of the causes of the uncertainty for climate change projection. Northern Japan is one of the heaviest snowfall regions in the world. In particular, Hokkaido is bounded on the north by the Okhotsk Sea, where is the southernmost ocean in the Northern Hemisphere that is covered with sea ice during winter. Wintertime climate around Hokkaido is highly sensitive to fluctuations in snow and sea-ice. The purpose of this study is to evaluate the influence of global warming on future climate around Hokkaido, using the Pseudo-Global-Warming method (PGW) by a regional climate model. The boundary conditions of the PGW run were obtained by adding the difference between the future (2090s) and past (1990s) climates simulated by coupled general circulation model (MIROC3.2 medres), which is from the CMIP3 multi-model dataset, into the 6-hourly NCEP reanalysis (R-2) and daily OISST data in the past climate (CTL) run. The PGW experiments show that snow depth significantly decreases over mountainous areas and snow cover mainly decreases over plain areas, contributing to higher surface warming due to the decreased snow albedo. Despite the snow reductions, precipitation mainly increases over the mountainous areas because of enhanced water vapor content. However, precipitation decreases over the Japan Sea and the coastal areas, indicating the weakening of a convergent cloud band, which is formed by convergence between cold northwesteries from the Eurasian continent and anticyclonic circulation over the Okhotsk Sea. These results suggest that Okhotsk sea-ice decline may change the atmospheric circulation and the resulting effect on cloud formation, resulting in changes in winter snow or precipitation. We will also examine another CMIP3 model (MRI-CGCM2.3.2), which sensitivity of surface albedo to surface air temperature is the lowest in the CMIP3 models.

  12. 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 land surveyed areas of Thule and Sondrestrom air bases. The radar measurements were compared against the ATM and the GPS measurements that were located in the estimated radar footprints, which resulted in an overall error of ~ 0.3 m between the radar and ATM. The agreement between ATM and GPS survey is within +/- 0.1 m. References: [1] http://www.nasa.gov/mission_pages/icebridge/ [2] Panzer, B. et. al, "An ultra-wideband, microwave radar for measuring snow thickness on sea ice and mapping near-surface internal layers in polar firn," Submitted to J. of Glaciology Instr. and Tech., July 23, 2012. [3] Krabill, William B. 2009 and 2011, updated current year. IceBridge ATM L1B Qfit Elevation and Return Strength. Boulder, Colorado USA: National Snow and Ice Data Center. Digital media. [4] Chih-Chung Chang and Chih-Jen Lin. "Libsvm: a library for support vector machines", ACM Transactions on Intelligent Systems and Technology, 2:2:27:1-27:27, 2011. [5] Krabill, William B. 2009 and 2011, updated current year. IceBridge CAMBOT L1B Geolocated Images, [2009-04-25, 2011-04-15]. Boulder, Colorado USA: National Snow and Ice Data Center. Digital media. [6] Dominguez, Roseanne. 2011, updated current year. IceBridge DMS L1B Geolocated and Orthorectified Images. Boulder, Colorado USA: National Snow and Ice Data Center. Digital media

  13. 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 underlying sea ice for comparative purposes. Results indicated presence of an areally extensive saline snow layer (salinities of 18.5-30.9 ppt) that was enriched in bacteria (0.28-1.5 x 10E4 bacteria/ml) and EPS (0.07-0.22 mg glucose equivalents/L) relative to overlying low-salinity snow (0.3-9 ppt; 2-9 x 10E2 bacteria/ml; 0.021-0.11 mg glucose equivalents/L). Analysis of content and distribution of salts, bacteria and EPS throughout the snow and underlying sea ice indicated sea-ice brines as the source of these materials in snow. Although marine bacteria appeared to have moved upwards into snow in sync with brine, EPS was subject to different transport or production and degradation pathways, perhaps connected to a detected sensitivity of bacteria in upper sea ice brines to osmotic shock. The possible passive and dynamic roles of bacteria and their exudates in these brine-wetted snows in influencing the physical-chemical properties of snow over sea ice, including later season physical and biological impacts as the snow melts and infiltrates the ice below, await further study.

  14. Comparison of a coupled snow thermodynamic and radiative transfer model with in-situ active microwave signatures of snow-covered smooth first-year sea ice

    NASA Astrophysics Data System (ADS)

    Fuller, M. C.; Geldsetzer, T.; Yackel, J.; Gill, J. P. S.

    2015-06-01

    Within the context of developing data inversion and assimilation techniques for C-band backscatter over sea ice, snow physical models may be used to drive backscatter models for comparison and optimization with satellite observations. Such modeling has potential to enhance understanding of snow on sea ice properties required for unambiguous interpretation of active microwave imagery. An end-to-end modeling suite is introduced, incorporating regional reanalysis data (NARR), a snow model (SNTHERM), and a multi-layer snow and ice active microwave backscatter model (MSIB). This modeling suite is assessed against measured snow on sea ice geophysical properties, and against measured active microwave backscatter. NARR data was input to the SNTHERM snow thermodynamic model, in order to drive the MISB model for comparison to detailed geophysical measurements and surface-based observations of C-band backscatter of snow on first-year sea ice. The NARR data was well correlated to available in-situ measurements, with the exception of long wave incoming radiation and relative humidity, which impacted SNTHERM simulations of snow temperature. SNTHERM reasonably represented snow grain size and density when compared to observations. The application of in-situ salinity profiles to one SNTHERM snow profile resulted in simulated backscatter close to that driven by in-situ snow properties. In other test cases, the simulated backscatter remained 4 to 6 dB below observed for higher incidence angles, and when compared to an average simulated backscatter of in-situ end-member snowcovers. Development of C-band inversion and assimilation schemes employing SNTHERM89.rev4 should consider sensitivity of the model to bias in incoming longwave radiation, the effects of brine, and the inability of SNTHERM89.Rev4 to simulate water accumulation and refreezing at the bottom and mid-layers of the snowpack with regard to thermodynamic response, brine wicking and volume processes, snow dielectrics, and microwave backscatter from snow on first-year sea-ice.

  15. 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.

  16. The impact of atmospheric mineral aerosol deposition on the albedo of snow & sea ice: are snow and sea ice optical properties more important than mineral aerosol optical properties?

    NASA Astrophysics Data System (ADS)

    Lamare, M. L.; Lee-Taylor, J.; King, M. D.

    2016-01-01

    Knowledge of the albedo of polar regions is crucial for understanding a range of climatic processes that have an impact on a global scale. Light-absorbing impurities in atmospheric aerosols deposited on snow and sea ice by aeolian transport absorb solar radiation, reducing albedo. Here, the effects of five mineral aerosol deposits reducing the albedo of polar snow and sea ice are considered. Calculations employing a coupled atmospheric and snow/sea ice radiative-transfer model (TUV-snow) show that the effects of mineral aerosol deposits are strongly dependent on the snow or sea ice type rather than the differences between the aerosol optical characteristics. The change in albedo between five different mineral aerosol deposits with refractive indices varying by a factor of 2 reaches a maximum of 0.0788, whereas the difference between cold polar snow and melting sea ice is 0.8893 for the same mineral loading. Surprisingly, the thickness of a surface layer of snow or sea ice loaded with the same mass ratio of mineral dust has little effect on albedo. On the contrary, the surface albedo of two snowpacks of equal depth, containing the same mineral aerosol mass ratio, is similar, whether the loading is uniformly distributed or concentrated in multiple layers, regardless of their position or spacing. The impact of mineral aerosol deposits is much larger on melting sea ice than on other types of snow and sea ice. Therefore, the higher input of shortwave radiation during the summer melt cycle associated with melting sea ice accelerates the melt process.

  17. Interactions between wind-blown snow redistribution and melt ponds in a coupled ocean-sea ice model

    NASA Astrophysics Data System (ADS)

    Lecomte, Olivier; Fichefet, Thierry; Flocco, Daniela; Schroeder, David; Vancoppenolle, Martin

    2015-03-01

    Introducing a parameterization of the interactions between wind-driven snow depth changes and melt pond evolution allows us to improve large scale models. In this paper we have implemented an explicit melt pond scheme and, for the first time, a wind dependant snow redistribution model and new snow thermophysics into a coupled ocean-sea ice model. The comparison of long-term mean statistics of melt pond fractions against observations demonstrates realistic melt pond cover on average over Arctic sea ice, but a clear underestimation of the pond coverage on the multi-year ice (MYI) of the western Arctic Ocean. The latter shortcoming originates from the concealing effect of persistent snow on forming ponds, impeding their growth. Analyzing a second simulation with intensified snow drift enables the identification of two distinct modes of sensitivity in the melt pond formation process. First, the larger proportion of wind-transported snow that is lost in leads directly curtails the late spring snow volume on sea ice and facilitates the early development of melt ponds on MYI. In contrast, a combination of higher air temperatures and thinner snow prior to the onset of melting sometimes make the snow cover switch to a regime where it melts entirely and rapidly. In the latter situation, seemingly more frequent on first-year ice (FYI), a smaller snow volume directly relates to a reduced melt pond cover. Notwithstanding, changes in snow and water accumulation on seasonal sea ice is naturally limited, which lessens the impacts of wind-blown snow redistribution on FYI, as compared to those on MYI. At the basin scale, the overall increased melt pond cover results in decreased ice volume via the ice-albedo feedback in summer, which is experienced almost exclusively by MYI.

  18. Seasonal characterization of microwave emissions from snow-covered first-year sea ice

    NASA Astrophysics Data System (ADS)

    Harouche, Isabelle P.-F.; Barber, David G.

    2001-12-01

    Brightness temperature TB data were collected with a surface-based radiometer operating on both vertical and horizontal polarizations at frequencies of 19, 37, and 85 GHz. Both microwave emissions and thermophysical data were collected as part of the Collaborative-Interdisciplinary Cryospheric Experiment between 15 May and 25 June 2000, in the Canadian High Arctic. Each season was characterized by a running variance of the time series in the microwave emissions. The seasonal analysis was conducted through observed changes in the physical characteristics of the sea ice and the overlying snow pack. Results from a k-means clustering analysis show that variability in the microwave response can be categorized into phenomenological states that were described by Livingstone et al. [IEEE Transactions on Geoscience and Remote Sensing 1987; 25(2): 174-187] as winter, early melt, melt onset and advanced melt. We describe the average thermophysical conditions associated with each one of these ablation states and interpret the relative contributions of each to the observed microwave response. Emissivities were calculated and used as part of a descriptive analysis of the seasonal variation of TB. Our results confirm other findings that the strength and pattern of the relationship are frequency dependent and relative to snow and ice dielectric properties. Useful information on the thermodynamic state of the snow-sea-ice system can be derived from passive microwave data, since the microwave emissions respond to the general seasonal changes associated with the transition from winter to a melt ponded sea ice surface.

  19. 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.

  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. Arctic climate response to forcing from light-absorbing particles in snow and sea ice in CESM

    NASA Astrophysics Data System (ADS)

    Goldenson, N.; Doherty, S. J.; Bitz, C. M.; Holland, M. M.; Light, B.; Conley, A. J.

    2012-09-01

    The presence of light-absorbing aerosol particles deposited on arctic snow and sea ice influences the surface albedo, causing greater shortwave absorption, warming, and loss of snow and sea ice, lowering the albedo further. The Community Earth System Model version 1 (CESM1) now includes the radiative effects of light-absorbing particles in snow on land and sea ice and in sea ice itself. We investigate the model response to the deposition of black carbon and dust to both snow and sea ice. For these purposes we employ a slab ocean version of CESM1, using the Community Atmosphere Model version 4 (CAM4), run to equilibrium for year 2000 levels of CO2 and fixed aerosol deposition. We construct experiments with and without aerosol deposition, with dust or black carbon deposition alone, and with varying quantities of black carbon and dust to approximate year 1850 and 2000 deposition fluxes. The year 2000 deposition fluxes of both dust and black carbon cause 1-2 C of surface warming over large areas of the Arctic Ocean and sub-Arctic seas in autumn and winter and in patches of Northern land in every season. Atmospheric circulation changes are a key component of the surface-warming pattern. Arctic sea ice thins by on average about 30 cm. Simulations with year 1850 aerosol deposition are not substantially different from those with year 2000 deposition, given constant levels of CO2. The climatic impact of particulate impurities deposited over land exceeds that of particles deposited over sea ice. Even the surface warming over the sea ice and sea ice thinning depends more upon light-absorbing particles deposited over land. For CO2 doubled relative to year 2000 levels, the climate impact of particulate impurities in snow and sea ice is substantially lower than for the year 2000 equilibrium simulation.

  2. Arctic climate response to forcing from light-absorbing particles in snow and sea ice in CESM

    NASA Astrophysics Data System (ADS)

    Goldenson, N.; Doherty, S. J.; Bitz, C. M.; Holland, M. M.; Light, B.; Conley, A. J.

    2012-02-01

    The presence of light-absorbing aerosol particles deposited on arctic snow and sea ice influences the surface albedo, causing greater shortwave absorption, warming, and loss of snow and sea ice, lowering the albedo further. The Community Earth System Model version 1 (CESM1) now includes the radiative effects of light-absorbing particles in snow on land and sea ice and in sea ice itself. We investigate the model response to the deposition of black carbon and dust to both snow and sea ice. For these purposes we employ a slab ocean version of CESM1, using the Community Atmosphere Model version 4 (CAM4), run to equilibrium for year 2000 levels of CO2 and fixed aerosol deposition. We construct experiments with and without aerosol deposition, with dust or black carbon deposition alone, and with varying quantities of black carbon and dust to approximate year 1850 and 2000 deposition fluxes. The year 2000 deposition fluxes of both dust and black carbon cause 1-2 C of surface warming over large areas of the Arctic Ocean and sub-Arctic seas in autumn and winter and in patches of Northern land in every season. Atmospheric circulation changes are a key component of the surface-warming pattern. Arctic sea ice thins by on average about 30 cm. Simulations with year 1850 aerosol deposition are not substantially different from those with year 2000 deposition, given constant levels of CO2. The climatic impact of particulate impurities deposited over land exceeds that of particles deposited over sea ice. Even the surface warming over the sea ice and sea ice thinning depends more upon light-absorbing particles deposited over land. For CO2 doubled relative to year 2000 levels, the climate impact of particulate impurities in snow and sea ice is substantially lower than for the year 2000 equilibrium simulation.

  3. 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.

  4. Comparison of a coupled snow thermodynamic and radiative transfer model with in situ active microwave signatures of snow-covered smooth first-year sea ice

    NASA Astrophysics Data System (ADS)

    Fuller, M. C.; Geldsetzer, T.; Yackel, J.; Gill, J. P. S.

    2015-11-01

    Within the context of developing data inversion and assimilation techniques for C-band backscatter over sea ice, snow physical models may be used to drive backscatter models for comparison and optimization with satellite observations. Such modeling has the potential to enhance understanding of snow on sea-ice properties required for unambiguous interpretation of active microwave imagery. An end-to-end modeling suite is introduced, incorporating regional reanalysis data (NARR), a snow model (SNTHERM89.rev4), and a multilayer snow and ice active microwave backscatter model (MSIB). This modeling suite is assessed against measured snow on sea-ice geophysical properties and against measured active microwave backscatter. NARR data were input to the SNTHERM snow thermodynamic model in order to drive the MSIB model for comparison to detailed geophysical measurements and surface-based observations of C-band backscatter of snow on first-year sea ice. The NARR variables were correlated to available in situ measurements with the exception of long-wave incoming radiation and relative humidity, which impacted SNTHERM simulations of snow temperature. SNTHERM snow grain size and density were comparable to observations. The first assessment of the forward assimilation technique developed in this work required the application of in situ salinity profiles to one SNTHERM snow profile, which resulted in simulated backscatter close to that driven by in situ snow properties. In other test cases, the simulated backscatter remained 4-6 dB below observed for higher incidence angles and when compared to an average simulated backscatter of in situ end-member snow covers. Development of C-band inversion and assimilation schemes employing SNTHERM89.rev4 should consider sensitivity of the model to bias in incoming long-wave radiation, the effects of brine, and the inability of SNTHERM89.Rev4 to simulate water accumulation and refreezing at the bottom and mid-layers of the snowpack. These impact thermodynamic response, brine wicking and volume processes, snow dielectrics, and thus microwave backscatter from snow on first-year sea ice.

  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 significantly increases the backscatter from thin saline ice and the polarimetric signature becomes closer to the isotropic characteristics. The snow cover also modifies polarimetric signatures of thin sea ice depending on the snow mixture and the interface condition.

  7. Scattering from a random layer with applications to snow, vegetation and sea ice

    NASA Technical Reports Server (NTRS)

    Fung, A. K.; Eom, H. J.

    1983-01-01

    Two approaches for computing scattering from a random layer with an irregular interface are shown using the radiative-transfer principle. One approach is applied to a random layer to develop a scattering model for snow and sea ice, while the other is used to generate a scattering model for vegetation. It is noted that to model the scattering characteristics of a special medium, it is necessary to relate the electromagnetic parameters to the measurable parameters of the scatterers in the medium. Such relations are given and used to calculate theoretical estimates to compare with measurements acquired by microwave scatterometers.

  8. 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.

  9. Simulation of the melt season using a resolved sea ice model with snow cover and melt ponds

    NASA Astrophysics Data System (ADS)

    Skyllingstad, Eric D.; Shell, Karen M.; Collins, Lee; Polashenski, Chris

    2015-07-01

    A three-dimensional sea ice model is presented with resolved snow thickness variations and melt ponds. The model calculates heating from solar radiative transfer and simulates the formation and movement of brine/melt water through the ice system. Initialization for the model is based on observations of snow topography made during the summer melt seasons of 2009, 2010, and 2012 from a location off the coast of Barrow, AK. Experiments are conducted to examine the importance of snow properties and snow and ice thickness by comparing observed and modeled pond fraction and albedo. One key process simulated by the model is the formation of frozen layers in the ice as relatively warm fresh water grid cells freeze when cooled by adjacent, cold brine-filled grid cells. These layers prevent vertical drainage and lead to flooding of melt water commonly observed at the beginning of the melt season. Flooding persists until enough heat is absorbed to melt through the frozen layer. The resulting long-term melt pond coverage is sensitive to both the spatial variability of snow cover and the minimum snow depth. For thin snow cover, initial melting results in earlier, reduced flooding with a small change in pond fraction after drainage of the melt water. Deeper snow tends to generate a delayed, larger peak pond fraction before drainage.

  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. Characterizing the sea ice algae chlorophyll a-snow depth relationship over Arctic spring melt using transmitted irradiance

    NASA Astrophysics Data System (ADS)

    Campbell, K.; Mundy, C. J.; Barber, D. G.; Gosselin, M.

    2015-07-01

    The bottom ice algae chlorophyll a (chl a)-snow depth (HS) relationship was investigated for first-year sea ice in Allen Bay, Nunavut, from 27 April to 13 June 2011. A transmitted irradiance technique was used to estimate ice algae chl a throughout the period at time series locations covered and cleared of snow. Furthermore, chl a was estimated along transects perpendicular to dominant snowdrift orientation, and at short-term snow clear experimental sites. The association between chl a and most snow depths was characterized by four phases over the spring; light limitation (negative relationship), a transitional period (no relationship), chl a decline associated with higher transmitted irradiance (positive relationship), and a final phase of chl a decline independent from HS (no relationship). Algal chl a under areas cleared of snow was lower, reached zero chl a earlier and declined faster than snow-covered control sites. Results indicated that snow removal caused these chl a responses through photoinhibition, as well as ice melt later in the spring. Based on this research we propose that weather events that can rapidly melt the snowpack could significantly deplete bottom ice chl a and cause early termination of the bloom if they occur late in the spring.

  12. Snow and Ice.

    ERIC Educational Resources Information Center

    Minneapolis Independent School District 275, Minn.

    This experimental edition provides a number of activities useful for investigating snow and ice with elementary school children. Commencing with games with ice cubes, the activities lead through studies of snowflakes, snowdrifts, effects of wind and obstacles on the shape and formation of drifts, to a study of animals living under snow. The…

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

    SciTech Connect

    Jiao, C.; Flanner, M. G.; Balkanski, Y.; Bauer, S.; Bellouin, N.; Berntsen, T.; Bian, Huisheng; Carslaw, K. S.; Chin, Mian; De Luca, N.; Diehl, Thomas; Ghan, Steven J.; Iversen, T.; Kirkevag, A.; Koch, Dorothy; Liu, Xiaohong; Mann, G. W.; Penner, Joyce E.; Pitari, G.; Schulz, M.; Seland, O.; Skeie, R. B.; Steenrod, Stephen D.; Stier, P.; Takemura, T.; Tsigaridis, Kostas; van Noije, T.; Yun, Yuxing; Zhang, Kai

    2014-03-07

    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 2004-2009, 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 the fact that most Arctic BC deposition originates from extra-Arctic emissions, these results suggest that aerosol removal processes are a leading source of variation in model performance. The multi-model mean (full range) of Arctic radiative effect from BC in snow is 0.15 (0.07-0.25) W m−2 and 0.18 (0.06-0.28) W m−2 in Phase I and Phase II models, respectively. After correcting for model biases relative to observed BC concentrations in different regions of the Arctic, we obtain a multi-model mean Arctic radiative effect of 0.17 W m−2 for the combined AeroCom ensembles. Finally, there is a high correlation between modeled BC concentrations sampled over the observational sites and the Arctic as a whole, indicating that the field campaign provided a reasonable sample of the Arctic.

  14. 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 from extra-Arctic emissions, these results suggest that aerosol removal processes are a leading source of variation in model performance. The multi-model mean (full range) of Arctic radiative effect from BC in snow is 0.15 (0.07-0.25) W/sq m and 0.18 (0.06-0.28) W/sq m in phase I and phase II models, respectively. After correcting for model biases relative to observed BC concentrations in different regions of the Arctic, we obtain a multi-model mean Arctic radiative effect of 0.17 W/sq m for the combined AeroCom ensembles. Finally, there is a high correlation between modeled BC concentrations sampled over the observational sites and the Arctic as a whole, indicating that the field campaign provided a reasonable sample of the Arctic.

  15. 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.

  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. Derivation and Validation of Snow Depth over Arctic Sea Ice by Integrating Snow Radar, Airborne Topographic Mapper, and In-Situ Measurement Data from the Greenland 2009 IceBridge Campaign

    NASA Astrophysics Data System (ADS)

    Johnson, M. P.; Perkovic, D.; Panzer, B.; Holt, B.; Leuschen, C.

    2011-12-01

    Using NASA's Operation IceBridge airborne data, this paper examines the derivation of snow depth on sea ice using measurements from two instruments, the Snow Radar and Atmospheric Topographic Mapper (ATM), taken off the northern coast of Greenland in April 2009. In-situ measurements of sea ice thickness, freeboard and snow depth obtained at the GreenArc ice camp are used as comparison points to the estimates made where possible. We also present range estimation and geolocation methodology for the Snow Radar data and analyze possible sources of error within these estimates. The Snow Radar is an ultra-wideband (2 - 6.5 GHz) Frequency Modulated Continuous-Wave (FMCW) radar that penetrates the snow layer and is able to discern both the snow-ice (SI) and the snow-air (SA) interfaces. The detected radar backscatter signature contains peaks in the return where the boundaries occur, with the SI interface having a stronger power return than the SA boundary. Level 1B data of radar echo strength range profiles are used to generate estimates of the distance from the radar antenna to the SI and SA interfaces. Aircraft position and attitude data are then used to georeference the radar range data as height estimates above the WGS-84 ellipsoid. The ATM is a conically scanning LIDAR that measures the range from the aircraft to the Earth's surface. Because the laser does not penetrate the snow or ice surface, the surface is interpreted to be the SA interface or the ice-air (IA) interface in the case of bare ice. Level 1B ATM data of WGS-84 referenced elevations are used in the comparison. Validation of the ATM-provided elevations and calibration of the Snow Radar-derived elevations were performed using data collected over GPS surveyed areas of the Thule air force base in Greenland. ATM surface height elevations will be shown to agree with the GPS surveyed area to within 10 cm. Initial calibrations of the radar estimated heights with the GPS surveyed area show an offset of approximately 1 m. When the radar measurements are corrected for the estimated offset and compared to the ATM measurements over bare ice, the two will be shown to be in very good agreement. This paper will then show how the collocated Snow Radar and ATM measurements are used to derive estimates of snow depth over sea ice, which are also compared where possible with the snow depth measurements.

  18. 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 wet snow season (funicular snow regime). Simulated penetration depths become too large in the pendular snow regime since liquid water is not generated soon enough within the snow pack in the spring season. The inclusion of salinity in the mass balance of ETSSIS will improve the simulation of penetration depths in the pendular snow regime in future implementations of the model. (Abstract shortened by UMI.)

  19. 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.

  20. 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.

  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 of -12 to 18°C, salinity range of 20 to 50), was originally isolated from Arctic marine sediments. The other isolate, the psychrotolerant and extremely halophilic bacterium Psychrobacter sp. strain 7E (temperature range of -1 [possibly lower] to 25°C, salinity range of 32 to 125), not only survived the most extreme conditions but demonstrated a potentially effective dispersal strategy of cell fragmentation and miniaturization (resulting in higher cell numbers). This extremophile was isolated from upper winter sea-ice brine in the Beaufort Sea. Bacterial survival and dispersal from sea-ice brines in Arctic winter thus appears to depend on the nature of the organisms involved and on the thickness of snow cover, which determines how dynamic and extreme are the exposure conditions. The observed species-specific reactions to extreme and fluctuating conditions may help to explain the different structures of microbial communities inhabiting the range of environments defined by the ice-snow system and provide model organisms and research directions for future work to evaluate potential activity or exchanges with other components of the system.

  2. 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.

  3. 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.

  4. Spatially-resolved mean flow and turbulence help explain observed erosion and deposition patterns of snow over Antarctic sea ice

    NASA Astrophysics Data System (ADS)

    Trujillo, E.; Giometto, M. G.; Leonard, K. C.; Maksym, T. L.; Meneveau, C. V.; Parlange, M. B.; Lehning, M.

    2014-12-01

    Sea ice-atmosphere interactions are major drivers of patterns of sea ice drift and deformations in the Polar regions, and affect snow erosion and deposition at the surface. Here, we combine analyses of sea ice surface topography at very high-resolutions (1-10 cm), and Large Eddy Simulations (LES) to study surface drag and snow erosion and deposition patterns from process scales to floe scales (1 cm - 100 m). The snow/ice elevations were obtained using a Terrestrial Laser Scanner during the SIPEX II (Sea Ice Physics and Ecosystem eXperiment II) research voyage to East Antarctica (September-November 2012). LES are performed on a regular domain adopting a mixed pseudo-spectral/finite difference spatial discretization. A scale-dependent dynamic subgrid-scale model based on Lagrangian time averaging is adopted to determine the eddy-viscosity in the bulk of the flow. Effects of larger-scale features of the surface on wind flows (those features that can be resolved in the LES) are accounted for through an immersed boundary method. Conversely, drag forces caused by subgrid-scale features of the surface should be accounted for through a parameterization. However, the effective aerodynamic roughness parameter z0 for snow/ice is not known. Hence, a novel dynamic approach is utilized, in which z0 is determined using the constraint that the total momentum flux (drag) must be independent on grid-filter scale. We focus on three ice floe surfaces. The first of these surfaces (October 6, 2012) is used to test the performance of the model, validate the algorithm, and study the spatial distributed fields of resolved and modeled stress components. The following two surfaces, scanned at the same location before and after a snow storm event (October 20/23, 2012), are used to propose an application to study how spatially resolved mean flow and turbulence relates to observed patterns of snow erosion and deposition. We show how erosion and deposition patterns are correlated with the computed stresses, with modeled stresses having higher explanatory power. Deposition is mainly occurring in wake regions of specific ridges that strongly affect wind flow patterns. These larger ridges also lock in place elongated streaks of relatively high speeds with axes along the stream-wise direction, and which are largely responsible for the observed erosion.

  5. 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.

  6. 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.

  7. 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.

  8. Snow accumulation rate retrieval across the Greenland ice facies using SeaWinds on QuikSCAT

    NASA Astrophysics Data System (ADS)

    Miller, J.; Forster, R. R.; Long, D. G.; Schröder, R.; McDonald, K. C.; Box, J. E.

    2011-12-01

    Recent accelerated mass loss from the Greenland ice sheet moderated by increased Arctic precipitation highlights the importance of a comprehensive understanding of the mechanisms controlling mass balance. Knowledge of the spatiotemporal variability of snow accumulation is critical to accurately quantify mass balance, yet the details are poorly understood on the scale of an ice sheet. Data acquired from the SeaWinds scatterometer on the QuikSCAT satellite together with spatially calibrated snow accumulation data from the Polar MM5 mesoscale climate model are used to develop a snow accumulation rate retrieval algorithm that exploits the sensitivity of Ku-band microwave radar to the unique stratigraphy within each of the Greenland ice facies. A layer of accumulating snow overlying a layer of ice exhibits an inverse relationship with radar backscatter that is approximately linear (dB) and a function of both snow accumulation rates and the microwave scattering characteristics of the underlying ice layer. Snow accumulation rates are retrieved using two types of QuikSCAT data: 1) data obtained from a single orbital pass at 25km resolution and 2) data spatial and temporally averaged using multiple orbital passes at ~2km and ~4km resolutions generated by the Scatterometer Image Reconstruction (SIR) algorithm. Regions displaying distinct scattering characteristics within each of the Greenland ice facies are threshold delineated using indices derived from parameterized layered melt and refreeze models. Freeze-up and melt onset dates are identified on a pixel-by-pixel basis using a Markov model, which follows the change in backscatter over time and classifies transitions between melting, refreezing and frozen states. Time series of twice-daily backscatter measurements over the time period 1999 - 2009 are linearly regressed from freeze-up to melt onset, negative slopes are correlated with Polar MM5 snow accumulation data and empirical relationships are established within each of the regions. Snow accumulation maps are presented at annual, winter season, and monthly time scales and comparisons are made between QuikSCAT data sets.

  9. The influence of sea ice on Antarctic ice core sulfur chemistry and on the future evolution of Arctic snow depth: Investigations using global models

    NASA Astrophysics Data System (ADS)

    Hezel, Paul J.

    Observational studies have examined the relationship between methanesulfonic acid (MSA) measured in Antarctic ice cores and sea ice extent measured by satellites with the aim of producing a proxy for past sea ice extent. MSA is an oxidation product of dimethylsulfide (DMS) and is potentially linked to sea ice based on observations of very high surface seawater DMS in the sea ice zone. Using a global chemical transport model, we present the first modeling study that specifically examines this relationship on interannual and on glacial-interglacial time scales. On interannual time scales, the model shows no robust relationship between MSA deposited in Antarctica and sea ice extent. We show that lifetimes of MSA and DMS are longer in the high latitudes than in the global mean, interannual variability of sea ice is small (<25%) as a fraction of sea ice area, and sea ice determines only a fraction of the variability (<30%) of DMS emissions from the ocean surface. A potentially larger fraction of the variability in DMS emissions is determined by surface wind speed (up to 46%) via the parameterization for ocean-to-atmosphere gas exchange. Furthermore, we find that a significant fraction (up to 74%) of MSA deposited in Antarctica originates from north of 60°S, north of the seasonal sea ice zone. We then examine the deposition of MSA and non-sea-salt sulfate (nss SO2-4 ) on glacial-interglacial time scales. Ice core observations on the East Antarctic Plateau suggest that MSA increases much more than nss SO2-4 during the last glacial maximum (LGM) compared to the modern period. It has been suggested that high MSA during the LGM is indicative of higher primary productivity and DMS emissions in the LGM compared to the modern day. Studies have also shown that MSA is subject to post-depositional volatilization, especially during the modern period. Using the same chemical transport model driven by meteorology from a global climate model, we examine the sensitivity of MSA and nss SO2-4 deposition to differences between the modern and LGM climates, including sea ice extent, sea surface temperatures, oxidant concentrations, and meteorological conditions. We are unable to find a mechanism whereby MSA deposition fluxes are higher than nss SO2-4 deposition fluxes on the East Antarctic Plateau in the LGM compared the modern period. We conclude that the observed differences between MSA and nss SO2-4 on glacial-interglacial time scales are due to post-depositional processes that affect the ice core MSA concentrations. We can not rule out the possibility of increased DMS emissions in the LGM compared to the modern day. If oceanic DMS production and ocean-to-air fluxes in the sea ice zone are significantly enhanced by the presence of sea ice as indicated by observations, we suggest that the potentially larger amplitude of the seasonal cycle in sea ice extent in the LGM implies a more important role for sea ice in modulating the sulfur cycle during the LGM compared to the modern period. We then shift our focus to study the evolution of snow depth on sea ice in global climate model simulations of the 20th and 21st centuries from the Coupled Model Intercomparison Project 5 (CMIP5). Two competing processes, decreasing sea ice extent and increasing precipitation, will affect snow accumulation on sea ice in the future, and it is not known a priori which will dominate. The decline in Arctic sea ice extent is a well-studied problem in future scenarios of climate change. Moisture convergence into the Arctic is also expected to increase in a warmer world, which may result in increasing snowfall rates. We show that the accumulated snow depth on sea ice in the spring declines as a result of decreased ice extent in the early autumn, in spite of increased winter snowfall rates. The ringed seal (Phoca hispida ) depends on accumulated snow in the spring to build subnivean birth lairs, and provides one of the motivations for this study. Using an empirical threshold of 20 cm of snow depth on level sea ice for ringed seal lair success, we estimate a decline of potential ringed seal habitat of nearly 70%.

  10. A vertically integrated snow/ice model over land/sea for climate models. I - Development. II - Impact on orbital change experiments

    NASA Technical Reports Server (NTRS)

    Neeman, Binyamin U.; Ohring, George; Joseph, Joachim H.

    1988-01-01

    A vertically integrated formulation (VIF) model for sea ice/snow and land snow is discussed which can simulate the nonlinear effects of heat storage and transfer through the layers of snow and ice. The VIF demonstates the accuracy of the multilayer formulation, while benefitting from the computational flexibility of linear formulations. In the second part, the model is implemented in a seasonal dynamic zonally averaged climate model. It is found that, in response to a change between extreme high and low summer insolation orbits, the winter orbital change dominates over the opposite summer change for sea ice. For snow over land the shorter but more pronounced summer orbital change is shown to dominate.

  11. 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.

  12. Spatial distribution and radiative effects of soot in the snow and sea ice during the SHEBA experiment

    NASA Astrophysics Data System (ADS)

    Grenfell, Thomas C.; Light, Bonnie; Sturm, Matthew

    2002-08-01

    Soot observations around the periphery of the Arctic Ocean indicate snowpack concentrations ranging from about 1 to more than 200 ng carbon/g snow (ngC/g), with typical values being near 40-50 ngC/g. Values of this magnitude would significantly affect not only the albedo and transmissivity of the ice cover but also surface melt rates and internal heat storage in the ice. During the Surface Heat Budget of the Arctic Ocean (SHEBA) drift, there was concern that soot emitted from the ship could adversely impact the heat and mass balance measurements, producing results that would not be representative of the region as a whole. To investigate this possibility, a series of soot measurements was carried out starting in the spring of 1998 during the time of maximum snowpack thickness. On the upwind side of the ship, where the heat and mass balance program was carried out, soot concentrations averaged over the depth of the snowpack spanned a range from 1 to 7 ngC/g, with average values of 4-5 ngC/g. On the downwind side, concentrations increased to 35 ngC/g and above. Measurements made up to 16 km from the ship yielded average background soot levels of approximately 4.4 ngC/g, with a standard deviation of 2.9 ngC/g evenly distributed throughout the different snow layers. These concentrations were not statistically distinguishable from the values measured in the observing areas on the upwind side of the ship. This indicates that soot concentrations in the central Arctic Basin are substantially lower than those reported for the coastal regions and are not sufficient to produce a significant decrease in the albedo. Although measurements of sea ice samples gave similarly low values, parameter studies show that the snow soot levels could be significant if the summer melt caused all the soot to be concentrated at the ice surface.

  13. 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.

  14. 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.

  15. 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 cover) and increase of the chla burden with age. Results from the second set of 3 stations in the western branch of the Weddell Sea gyre confirm that it comprises a mixture of older fast/second year ice floes with younger first-year ice floes. The older ice had the highest Chlaconcentrations of the entire cruise (>200 μgl-1), in an internal community enclosed within desalinized impermeable upper and lower layers. The first-year ice differs from that in the eastern Weddell Sea as it is dominated by columnar ice and (weak) algal communities are only found on the bottom or near the surface (no internal maximum).

  16. 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, Rdiger

    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.

  17. A model study of differences of snow thinning on Arctic and Antarctic first-year sea ice during spring and summer

    NASA Astrophysics Data System (ADS)

    Nicolaus, Marcel; Haas, Christian; Bareiss, Jörg; Willmes, Sascha

    The one-dimensional snow model SNTHERM is validated using field measurements of snow and superimposed ice thickness and surface energy fluxes. These were performed during the spring-to-summer transition in Svalbard and in the Weddell Sea, Antarctica. Both the seasonal snow-thickness decrease and the formation of superimposed ice are well reproduced by the model. During the three observation periods, observed and modeled snow thickness differ only by 13.1-27.1 mm on average. In regional studies, the model is forced with atmospheric re-analysis data (European Centre for Medium-Range Weather Forecasts) and applied to several meridional transects across the Arctic and Southern Ocean. These show fundamental regional differences in the onset, duration and magnitude of snow thinning in summer. In the central Arctic, snowmelt onset occurs within a narrow time range of ±11 days and without significant regional differences. In contrast, the snow cover on Antarctic sea ice begins to melt about 25 days earlier and the length of the Antarctic snow-thinning season increases with increasing latitude. The importance of melting and evaporation for the modeled snow-thickness decrease is very different in the two hemispheres. The ratio of evaporated snow mass to melted snow mass per unit area is derived from the model, and amounts to approximately 4.2 in the Antarctic and only 0.75 in the Arctic. This agrees with observations and model results of the surface energy balance, and illustrates the dominance of surface cooling by upward turbulent fluxes in the Antarctic.

  18. 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.

  19. 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.

  20. A Simple Scheme for Estimating Turbulent Heat Flux over Landfast Arctic Sea Ice from Dry Snow to Advanced Melt

    NASA Astrophysics Data System (ADS)

    Raddatz, R. L.; Papakyriakou, T. N.; Else, B. G.; Swystun, K.; Barber, D. G.

    2015-05-01

    We describe a dynamic-parameter aggregation scheme to estimate hourly turbulent heat fluxes over landfast sea ice during the transition from winter to spring. Hourly albedo measurements are used to track the morphology of the surface as it evolved from a fairly smooth homogeneous dry snow surface to a rougher heterogeneous surface with spatially differential melting and melt ponds. The estimates of turbulent heat fluxes for 928 h are compared with eddy-covariance measurements. The model performance metrics (W m) for sensible heat flux were found to be: mean bias , root-mean-square error 6 and absolute accuracy 4, and for latent heat flux near zero, 3 and 2, respectively. The correlation coefficient between modelled and measured sensible heat fluxes was 0.82, and for latent heat fluxes 0.88. The turbulent heat fluxes were estimated more accurately without adjustments than with adjustments for atmospheric stability based on the bulk Richardson number. Overall, and across all metrics for both sensible and latent heat fluxes, the dynamic-parameter aggregation scheme outperformed the static Community Ice (C-ICE) scheme, part of the Community Climate System model, applied to the same winter-to-spring transition period.

  1. Meteorological factors controlling year-to-year variations in the spring onset of snow melt over the Arctic sea ice

    NASA Astrophysics Data System (ADS)

    Maksimovich, E.

    2010-09-01

    The spring onset of snow melt on the Arctic sea ice shows large inter-annual variability. Surface melt triggers positive feedback mechanisms between the albedo, snow properties and thickness, as well as sea ice thickness. Hence, it is important to quantify the factors contributing to inter-annual variability of the melt onset (MO) in various parts of the Arctic Ocean. Meteorological factors controlling surface heat budget and surface melting/freezing are the shortwave and longwave radiative fluxes and the turbulent fluxes of sensible and latent heat. These fluxes depend on the weather conditions, including the radiative impact of clouds, heat advection and wind speed. We make use of SSM/I-based MO time series (Markus, Miller and Stroeve) and the ECMWF ERA Interim reanalysis on the meteorological conditions and surface fluxes, both data sets spanning the period 1989-2008 and covering recent years with a rapid sea ice decline. The advantage is that SSM/I-based MO time series are independent of the ERA-Interim data. Our objective is to investigate if there exists a physically consistent and statistically significant relationship between MO timing and corresponding meteorological conditions. Results based on the regression analysis between the MO timing and seasonal anomalies of surface longwave radiative fluxes reveal strong relationships. Synoptic scale (3-14 days) anomalies in downward longwave radiation are essential in the Western Arctic. Regarding the longer history (20-60 days) the distinct contribution from the downward longwave radiative fluxes is captured within the whole study region. Positive anomalies in the downward longwave radiation dominate over the simultaneous negative anomalies in the downward shortwave radiation. The anomalies in downward radiative fluxes are consistent with the total column water vapor, sea level pressure and 10-m wind direction. Sensible and latent heat fluxes affect surface melt timing in the Beaufort Sea and in the Atlantic sector of the Arctic Basin. Stronger winds strengthen the relationship between the turbulent fluxes and the MO timing. The turbulent surface fluxes in spring are relatively weak, of the order of 1-10W/m2, compared to the downward shortwave and longwave radiative fluxes, which are of the order of 100-150W/m2. As soon as data uncertainties are comparable to the anomaly in turbulent fluxes, statistical relationships found between MO timing and preceding anomaly in turbulent fluxes do not necessarily prove their reasonal-causal relationship. This joint study of SSM/I-based MO record and the ERA-Interim meteorological fields region-wide with a focus on the seasonal transition demonstrates their consistency in time and space. Such result could be regarded as an important indicator that both data sets have the appropriate performance of the surface state in the Arctic Ocean. Nevertheless, an important additional effort is needed for to resolve better the cloud radiative and boundary layer turbulent processes over the sea ice.

  2. 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.

  3. MODIS Snow and Ice Products from the NSIDC DAAC

    NASA Technical Reports Server (NTRS)

    Scharfen, Greg R.; Hall, Dorothy K.; Riggs, George A.

    1997-01-01

    The National Snow and Ice Data Center (NSIDC) Distributed Active Archive Center (DAAC) provides data and information on snow and ice processes, especially pertaining to interactions among snow, ice, atmosphere and ocean, in support of research on global change detection and model validation, and provides general data and information services to cryospheric and polar processes research community. The NSIDC DAAC is an integral part of the multi-agency-funded support for snow and ice data management services at NSIDC. The Moderate Resolution Imaging Spectroradiometer (MODIS) will be flown on the first Earth Observation System (EOS) platform (AM-1) in 1998. The MODIS Instrument Science Team is developing geophysical products from data collected by the MODIS instrument, including snow and ice products which will be archived and distributed by NSIDC DAAC. The MODIS snow and ice mapping algorithms will generate global snow, lake ice, and sea ice cover products on a daily basis. These products will augment the existing record of satellite-derived snow cover and sea ice products that began about 30 years ago. The characteristics of these products, their utility, and comparisons to other data set are discussed. Current developments and issues are summarized.

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

    MedlinePlus

    ... All About Food Allergies Cold, Ice, and Snow Safety KidsHealth > For Parents > Cold, Ice, and Snow Safety ... outdoors for a while. previous continue Winter Sports Safety If your kids decide to go sledding on ...

  5. 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.

  6. 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.

  7. 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.

  8. Seasonality of halogen deposition in polar snow and ice

    NASA Astrophysics Data System (ADS)

    Spolaor, A.; Vallelonga, P.; Gabrieli, J.; Martma, T.; Björkman, M. P.; Isaksson, E.; Cozzi, G.; Turetta, C.; Kjær, H. A.; Curran, M. A. J.; Moy, A. D.; Schönhardt, A.; Blechschmidt, A.-M.; Burrows, J. P.; Plane, J. M. C.; Barbante, C.

    2014-09-01

    The atmospheric chemistry of iodine and bromine in Polar regions is of interest due to the key role of halogens in many atmospheric processes, particularly tropospheric ozone destruction. Bromine is emitted from the open ocean but is enriched above first-year sea ice during springtime bromine explosion events, whereas iodine emission is attributed to biological communities in the open ocean and hosted by sea ice. It has been previously demonstrated that bromine and iodine are present in Antarctic ice over glacial-interglacial cycles. Here we investigate seasonal variability of bromine and iodine in polar snow and ice, to evaluate their emission, transport and deposition in Antarctica and the Arctic and better understand potential links to sea ice. We find that bromine and iodine concentrations and Br enrichment (relative to sea salt content) in polar ice do vary seasonally in Arctic snow and Antarctic ice. Although seasonal variability in halogen emission sources is recorded by satellite-based observations of tropospheric halogen concentrations, seasonal patterns observed in snowpack are likely also influenced by photolysis-driven processes. Peaks of bromine concentration and Br enrichment in Arctic snow and Antarctic ice occur in spring and summer, when sunlight is present. A secondary bromine peak, observed at the end of summer, is attributed to bromine deposition at the end of the polar day. Iodine concentrations are largest in winter Antarctic ice strata, contrary to contemporary observations of summer maxima in iodine emissions. These findings support previous observations of iodine peaks in winter snow strata attributed to the absence of sunlight-driven photolytic re-mobilisation of iodine from surface snow. Further investigation is required to confirm these proposed mechanisms explaining observations of halogens in polar snow and ice, and to evaluate the extent to which halogens may be applied as sea ice proxies.

  9. 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.

  10. 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.

  11. Seasonality of halogen deposition in polar snow and ice

    NASA Astrophysics Data System (ADS)

    Spolaor, A.; Vallelonga, P.; Gabrieli, J.; Martma, T.; Björkman, M. P.; Isaksson, E.; Cozzi, G.; Turetta, C.; Kjær, H. A.; Curran, M. A. J.; Moy, A. D.; Schönhardt, A.; Blechschmidt, A.-M.; Burrows, J. P.; Plane, J. M. C.; Barbante, C.

    2014-03-01

    The atmospheric chemistry of iodine and bromine in polar regions is of interest due to the key role of halogens in many atmospheric processes, particularly tropospheric ozone destruction. Bromine is emitted from the open ocean but is enriched above first-year sea ice during springtime bromine explosion events, whereas iodine is emitted from biological communities hosted by sea ice. It has been previously demonstrated that bromine and iodine are present in Antarctic ice over glacial-interglacial cycles. Here we investigate seasonal variability of bromine and iodine in polar snow and ice, to evaluate their emission, transport and deposition in Antarctica and the Arctic and better understand potential links to sea ice. We find that bromine enrichment (relative to sea salt content) and iodine concentrations in polar ice do vary seasonally in Arctic snow and Antarctic ice and we relate such variability to satellite-based observations of tropospheric halogen concentrations. Peaks of bromine enrichment in Arctic snow and Antarctic ice occur in spring and summer, when sunlight is present. Iodine concentrations are largest in winter Antarctic ice strata, contrary to contemporary observations of summer maxima in iodine emissions.

  12. Summer Arctic Atmospheric Circulation Response to Spring Eurasian Snow Cover and its Possible Linkage to Accelerated Sea Ice Decrease

    NASA Astrophysics Data System (ADS)

    Matsumura, S.; Zhang, X.; Yamazaki, K.

    2014-12-01

    Anticyclonic circulation has intensified over the Arctic Ocean in summer during recent decades. However, the underlying mechanism is, as yet, not well understood. Here we show that earlier spring Eurasian snowmelt leads to anomalously negative sea level pressure (SLP) over Eurasia and positive SLP over the Arctic, which has strong projection on the negative phase of the Northern Annular Mode (NAM) in summer through the wave-mean flow interaction. Specifically, earlier spring snowmelt over Eurasia leads to a warmer land surface, due to reduced surface albedo. The warmed surface amplifies stationary Rossby waves, leading to a deceleration of the subpolar jet. As a consequence, rising motion is enhanced over the land, and compensating subsidence and adiabatic heating occur in the Arctic troposphere, forming the negative NAM. The intensified anticyclonic circulation has played a contributing role in accelerating the sea ice decline observed during the last two decades. The results here provide important information for improving seasonal prediction of summer sea ice cover.

  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. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. Oxygen isotope composition of water and snow-ice cover of isolated lakes at various stages of separation from the White Sea

    NASA Astrophysics Data System (ADS)

    Lisitzin, A. P.; Vasil'chuk, Yu. K.; Shevchenko, V. P.; Budantseva, N. A.; Krasnova, E. D.; Pantyulin, A. N.; Filippov, A. S.; Chizhova, Ju. N.

    2013-04-01

    This study aimed to analyze the oxygen isotope composition of water, ice, and snow in water bodies isolated from the White Sea and to identify the structural peculiarities of these pools during the winter period. The studies were performed during early spring in Kandalaksha Bay of the White Sea, in Velikaya Salma Strait and in Rugoserskaya Inlet. The studied water bodies differ in their degree of isolation from the sea. In particular, Ermolinskaya Inlet has normal water exchange with the sea; the Lake on Zelenyi Cape represents the first stage of isolation; i. e., it has permanent water exchange with the sea by the tide. Kislo-Sladkoe Lake receives sea water from time to time. Trekhtsvetnoe Lake is totally isolated from the sea and is a typical meromictic lake. Finally, Nizhnee Ershovskoe Lake exhibits some features of a saline water body. The oxygen isotope profile of the water column in Trekhtsvetnoe Lake allows defining three layers; this lake may be called typically meromictic. The oxygen isotope profile of the water column in Kislo-Sladkoe Lake is even from the surface to the bottom. The variability of δ18O is minor in Lake on Zelenyi Cape. A surface layer (0-1 m) exists in Nizhnee Ershovskoe Lake, and the oxygen isotope variability is well pronounced. Deeper, where the freshwater dominates, the values of ?18Îvary insignificantly disregarding the water depth and temperature. This fresh water lake is not affected by the seawater and is not stratified according to the isotope profile. It is found that applying the values of ?18Î and profiles of temperature and salinity may appear as an effective method in defining the water sources feeding the water bodies isolated from the sea environment.

  19. 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 that a more complete treatment of brine movement towards the surface ice of the ice cover and the formation of surface features---such as frost flowers or slush layers---is required to understand the albedo of newly formed sea ice. The sea ice had reached its maximum thickness by late April in both FB and BB (˜1.8 m vs. 1.5-1.7 m). However, surface conditions differed notably as surface melting had not been initiated in FB, while melting had progressed to an advanced stage in BB, illustrating the difference in climate between the two regions (Arctic vs. sub-Arctic). The shortwave partitioning between the atmosphere, sea ice and the ocean---as well as within the sea ice---was strongly affected by diurnal freeze-thaw processes and synoptic weather events that controlled the optical characteristics of the surface. In spring, in situ measurements with a high vertical resolution were conducted within the bottom sea ice layers. The optical properties were strongly affected by ice algae present in the bottom few centimeters. Particulate absorption decreased quickly within the ice above the living algae layer, and showed characteristics of detrital matter. The optical properties for the bottom layers of the sea ice were found to significantly differ from interior ice. This is expected as the bottom ice is very porous and has a lamellar platelet structure, in addition to containing high concentrations of biological matter. These findings emphasize the importance of processes occurring near the surface and bottom boundaries in determining radiative transfer in sea ice covers. Ultimately, a focus on linking numerous aspects of sea ice physics and biology is required in order to predict the seasonal evolution of the sea ice cover in a changing climate.

  20. 2013 Arctic Sea Ice Minimum - Duration: 27 seconds.

    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 ...

  1. Volcanic deposits in Antarctic snow and ice

    NASA Astrophysics Data System (ADS)

    Delmas, Robert J.; Legrand, Michel; Aristarain, Alberto J.; Zanolini, FranOise

    1985-12-01

    Major volcanic eruptions are able to spread large amounts of sulfuric acid all over the world. Acid layers of volcanic origin were detected for the first time a few years ago by Hammer in Greenland ice. The present paper deals with volcanic deposits in the Antarctic. The different methods that can be used to find volcanic acid deposits in snow and ice cores are compared: electrical conductivity, sulfate, and acidity measurements. Numerous snow and ice samples collected at several Antarctic locations were analyzed. The results reveal that the two major volcanic events recorded by H2SO4, fallout in Antarctic ice over the last century are the eruptions of Krakatoa (1883) and Agung (1963), both located at equatorial latitudes in the southern hemisphere. The volcanic signals are found to be particularly well defined at central Antarctic locations apparently in relation to the low snow accumulation rates in these areas. It is demonstrated that volcanic sulfuric acid in snow is not even partially neutralized by ammonia. The possible influence of Antarctic volcanic activity on snow chemistry is also discussed, using the three recent eruptions of the Deception Island volcano as examples. Only one of them seems to have had a significant effect on the chemistry of snow at a location 200 km from this volcano. It is concluded that Antarctic volcanic ice records are less complicated than Greenland records because of the limited number of volcanos in the southern hemisphere and the apparently higher signal to background ratio for acidity in Antarctica than in Greenland.

  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. Amundsen Sea ice production and transport

    NASA Astrophysics Data System (ADS)

    Assmann, Karen M.; Hellmer, Hartmut H.; Jacobs, Stanley S.

    2005-12-01

    Drift and variability of sea ice in the Amundsen Sea are investigated with ice buoys deployed in March 2000 and a coupled ice-ocean model. The Bremerhaven Regional Ice Ocean Simulations (BRIOS) model results are compared with in situ ocean, atmosphere, and sea ice measurements; satellite observations; and 8-19 months of buoy drift data. We identify a zone of coastal westward drift and a band of faster eastward drift, separated by a broad transition region characterized by variable ice motions. The model represents drift events at scales approaching its resolution but is limited at smaller scales and by deficiencies in the National Centers for Environmental Prediction forcing. Two thirds of the modeled ice production in the southern Amundsen moves westward near the coast, its transport modulated by meridional wind strength, damping sea ice formation in the eastern Ross Sea. Half of the ice exported from the Ross moves eastward into the northern Amundsen Sea, a net sea ice sink that also receives more than one third of the ice generated to its south. A low rate of exchange occurs with the Bellingshausen Sea, which must have a more independent ice regime. Snow ice formation resulting from high precipitation accounts for one quarter of the ice volume in the Amundsen Sea, aiding the formation of thick ice in a region with generally divergent ice drift. Freshwater extraction by sea ice formation is roughly balanced by precipitation and ice shelf melting, but a positive trend in the surface flux is consistent with an Amundsen source for reported freshening in the Ross Sea.

  4. 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

  5. Sea Ice Ecosystems

    NASA Astrophysics Data System (ADS)

    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.

  6. 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.

  7. 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

  8. Is sea salt in ice cores a proxy of past sea ice extent?

    NASA Astrophysics Data System (ADS)

    Levine, James; Wolff, Eric; Frey, Markus; Jenkins, Hazel; Jones, Anna; Yang, Xin

    2014-05-01

    A number of marine, coastal and ice core proxies have been used to try to assess the past extent of sea ice. Sea salt has been proposed as a proxy for past ice extent, at least in the Southern Ocean. The idea is that the sea ice surface itself holds a source of sea salt, that is stronger than the source from the open ocean it replaces. That a sea ice source exists is apparent from observations of the ratio of sulphate to sodium in coastal aerosol and snow samples. While the idea behind using sea salt as a proxy is attractive, and leads to sensible inferences, many doubts remain. Firstly the exact nature of the source remains uncertain, and secondly it is not clear if ice extent, as opposed to changes in atmospheric transport and lifetime, would dominate variability in the ice core record of sea salt. Here we use a model of atmospheric transport and chemistry (p-TOMCAT) to assess the consequences of a sea ice source, focussing particularly on a source that has been proposed to arise from the sublimation of salty blowing snow. We will briefly report some new observations from a winter cruise, that will allow us to comment on the likelihood that blowing snow does pose a significant source. We will then present results from the model (implemented using existing parameters). The model has been run with seasonally and interannually varying sea ice extent and meteorology for the Antarctic, tracking, at different ice core sites, the concentration that arises from the open ocean and sea ice sources. We have already shown that the model, after tuning, is able to reproduce the magnitude and seasonal cycle of sea salt at a range of sites globally. By varying each component separately we explore which factors (sea ice presence, wind speed at source, transporting winds) and which source regions control the delivery of sea salt to sites in Antarctica. Such work suggests that sea salt cannot be used as a sea ice proxy on interannual timescales, but may be suitable on longer timescales. By employing much larger sea ice extents, such as at the last glacial maximum (LGM), we find a strong increase in concentration at ice core sites when ice extent increases. The increase in modelled sea salt concentration tails off sharply as ice approaches the LGM extent, so that the sensitivity of the proxy is greater at lower ice extents, for example in interglacials. We will discuss the implications of this work for the proposed use of sea salt as a sea ice proxy.

  9. Sea ice in the China Sea

    SciTech Connect

    Deng Shuqi

    1993-12-31

    In every winter, sea ice occurring in Bohai Sea and the North Yellow Sea is the first-year ice which is going through generating, developing and thawing processes. Therefore, it is necessary to spatially and temporally describe ice period, freezing range, thickness variations and general motion of sea ice. The purpose of this paper is to provide initial general situation and features of sea ice for forecasting and researching sea ice.

  10. 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.

  11. 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 with an uncertainty of +/-10% for the same part of the viewing hemisphere. Further improvement in BRF model performance requires better handling of single scattering properties of snow grains, surface roughness, and atmospheric correction. Also, better procedures and techniques in field measurement are necessary for more accurate assessment of the performance of BRF models. Copyright

  12. 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).

  13. 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.

  14. 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,...

  15. 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,...

  16. 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,...

  17. 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,...

  18. 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,...

  19. 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.

  20. 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.

  1. Microwave remote sensing of ice and snow

    NASA Technical Reports Server (NTRS)

    Kong, J. A.

    1974-01-01

    A composite theoretical model is proposed to account for effects on emissivity caused by layering, absorption, anisotropy, surface roughness, inhomogeneities and subsurface scattering. The emissivity as a function of frequency is calculated for a two layer model simulating ice or snow covered water or land. The theoretical results are compared with experimental data.

  2. 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.

  3. Sea-ice thickness and mass at Ice Station Belgica, Bellingshausen Sea, Antarctica

    NASA Astrophysics Data System (ADS)

    Weissling, B. P.; Lewis, M. J.; Ackley, S. F.

    2011-05-01

    Ice Station Belgica was commenced in late winter 2007 in the Bellingshausen Sea as part of Sea Ice Mass Balance in Antarctica (SIMBA), an IPY 2007 cruise on the research vessel N.B. Palmer. A primary objective was to build on the work of previous Antarctic drift station experiments to geophysically characterize sea ice in terms of thickness, surface and ice bottom morphology, and ultimately area-unitized mass. A 24 day drift station was established at approximately 70°S and 93°W in mixed first-year and multi-year ice with three geophysical study sites selected on a 5 km 2 floe. A comprehensive time series assessment of elevation-surveyed transects ranging from 100 m to 300 m in length included snow surface elevation, snow depth, electromagnetic (EM) profiling, and direct drilling for ice draft and ice freeboard. Additional work included a snow surface morphology characterization of a 100 m×300 m area between the primary time series EM transects. Correlation of EM ice thicknesses with collocated drilled ice thickness yielded equations for the correction of EM underestimation of thick deformed ice, particularly at pressure ridges. Mean ice thickness from corrected EM was compared to isostatic ice thickness calculated from surface elevation, snow depth, ice freeboard and respective snow, slush, ice, and sea water densities. Results were consistent, with mean ice thicknesses for multi-year ice of 2.35 m, 2.34 m, and 2.41 m, with similar variance, for corrected EM, drilling, and buoyancy methods respectively. Additionally, a mean ice thickness of 2.31 m was calculated from ASPeCt observations of the ice field associated with the floe, using the method incorporating mean sail heights and fractional coverage of surface deformities or ridging. Temporal series assessment of ice freeboard indicated a slightly negative mean ice freeboard (<0.04 m), with clear evidence of new snow-ice formation from the freezing of slush. The three distinct snow and ice regions assessed on the Belgica floe had mean corrected EM ice thickness of 0.52±0.04 m (±1 std. deviation), 0.92±0.17 m, and 2.35±1.37 m, and mean snow depths of 0.08±0.03 m, 0.36±0.09 m, and 0.68±0.31 m respectively. Each ice type represented a sizable fraction of the floe's total area (˜20%, 40%, and 40% respectively from visual estimates) reflecting a complex dynamic and thermodynamic history of formation, as well as the difficulty in characterizing even a single floe by a single class or mean value for thickness and snow depth. Implications of these results are discussed with regards to the resolution of satellite-based altimetry and snow depth products and efforts to generate and validate satellite sea ice and snow thickness products.

  4. Soot climate forcing via snow and ice albedos

    NASA Astrophysics Data System (ADS)

    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. aerosols | air pollution | climate change | sea level

  5. Forthcoming Northern Hemisphere Snow and Ice Earth System Data Records

    NASA Astrophysics Data System (ADS)

    Robinson, D. A.; Estilow, T. W.; Anderson, M. R.; Hall, D. K.; Henderson, G. R.; Mote, T. L.; Tschudi, M. A.

    2013-12-01

    For approximately the past five years, a multi-institutional team has been assembling satellite-derived Northern Hemisphere (NH) snow cover Earth System Data Records (ESDR). With the culmination of our NASA-supported Making Earth Science Data Records for Use in Research Environments (MEaSUREs) project come mid 2014, it is timely to bring the user community that encompasses the research community, decision-makers, and stakeholders up to date on our progress and with products soon to be available. Datasets include snow extent and melt state over NH continents, snowmelt state over Greenland, snowmelt onset and age of sea ice. Fused snow extent and melt state products over land and ice are also being generated. Visible and microwave satellite data are employed in these efforts. Datasets of both individual and integrated ESDRs will be available for downloading from the National Snow and Ice Data Center. Products are being generated at 25 km (1999-2010) or 100 km (1967-2010) resolution using the Equal-Area Scalable Earth Grid 2.0 and are available in netCDF format. Extensive metadata will accompany the datasets. Project data and information are also available at http://snowcover.org. Here, we will present examples of the development and utility of these individual and fused datasets.

  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. 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.

  8. 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.

  9. Tertiary ice sheet dynamics: The Snow Gun Hypothesis

    NASA Astrophysics Data System (ADS)

    Prentice, M. L.; Matthews, R. K.

    1991-04-01

    We observe strong negative correlation between Tertiary low- to mid-latitude planktonic foraminiferal ?18O and the difference between these data and coeval benthic foraminiferal ?18O. Late Quaternary data do not show this correlation. Coupling statistical model/?18O comparisons and evidence for Antarctic ice and ocean temperature variation, we infer that Tertiary ice volume, recorded by tropical planktonic ?18O, increased as the deep ocean warmed. Because the isotopic signatures of deepwater temperature variation and ice volume change were of opposite sign, the sum of these signals in Tertiary benthic ?18O became lost in the noise. This renders low correlation between Tertiary planktonic and benthic ?18O time series compared to late Quaternary data. We contend that Tertiary ice sheet growth was commonly driven by warming of deep water from low- to mid-latitude marginal seas (snow gun hypothesis). In contrast, late Quaternary ice sheets grew as deep water, formed at high latitude, cooled. Because tectonic forcing and orbital forcing at low-latitude primarily controlled production and temperature variations of this Warm Saline Deep Water, these influences largely dictated Tertiary ice volume fluctuations. Through the Tertiary, we infer ice volume fluctuations to be an important component of sea level history on timescales between 103 and 107 years.

  10. Arctic Sea Ice

    NASA Astrophysics Data System (ADS)

    Stroeve, J. C.; Fetterer, F.; Knowles, K.; Meier, W.; Serreze, M.; Arbetter, T.

    2004-12-01

    Of all the recent observed changes in the Arctic environment, the reduction of sea ice cover stands out most prominantly. Several independent analysis have established a trend in Arctic ice extent of -3% per decade from the late 1970s to the late 1990s, with a more pronounced trend in summer. The overall downward trend in ice cover is characterized by strong interannual variability, with a low September ice extent in one year typically followed by recovery the next September. Having two extreme minimum years, such as what was observed in 2002 and 2003 is unusual. 2004 marks the third year in a row of substantially below normal sea ice cover in the Arctic. Early summer 2004 appeared unusual in terms of ice extent, with May a record low for the satellite period (1979-present) and June also exhibiting below normal ice extent. August 2004 extent is below that of 2003 and large reductions in ice cover are observed once again off the coasts of Siberia and Alaska and the Greenland Sea. Neither the 2002 or 2003 anomaly appeared to be strongly linked to the positive phase of the Arctic Oscillation (AO) during the preceding winter. Similarly, the AO was negative during winter 2003/2004. In the previous AO framework of Rigor et al (2002), a positive winter AO implied preconditioning of the ice cover to extensive summer decay. In this hypothesis, the AO does not explain all aspects of the recent decline in Arctic ice cover, such as the extreme minima of 2002, 2003 and 2004. New analysis by Rigor and Wallace (2004) suggest that the very positive AO state from 1989-1995 can explain the recent sea ice minima in terms of changes in the Arctic surface wind field associated with the previous high AO state. However, it is also reasonable to expect that a general decrease in ice thickness accompanying warming would manifest itself as greater sensitivity of the ice pack to wind forcings and albedo feedbacks. The decrease in multiyear ice and attendant changes in ice thickness distribution could in turn precondition the Arctic ice cover to further reductions in the subsequent summer(s) regardless if the summer temperatures were anomalously warm. The NSIDC Sea Ice Index (http://nsidc.org/data/seaice_index/) can be used to view trends and anomalies from 1979 on.

  11. Soot climate forcing via snow and ice albedos.

    PubMed

    Hansen, James; Nazarenko, Larissa

    2004-01-13

    Plausible estimates for the effect of soot on snow and ice albedos (1.5% in the Arctic and 3% in Northern Hemisphere land areas) yield a climate forcing of +0.3 W/m(2) in the Northern Hemisphere. The "efficacy" of this forcing is approximately 2, i.e., for a given forcing it is twice as effective as CO(2) in altering global surface air temperature. This indirect soot forcing may have contributed to global warming of the past century, including the trend toward early springs in the Northern Hemisphere, thinning Arctic sea ice, and melting land ice and permafrost. If, as we suggest, melting ice and sea level rise define the level of dangerous anthropogenic interference with the climate system, then reducing soot emissions, thus restoring snow albedos to pristine high values, would have the double benefit of reducing global warming and raising the global temperature level at which dangerous anthropogenic interference occurs. However, soot contributions to climate change do not alter the conclusion that anthropogenic greenhouse gases have been the main cause of recent global warming and will be the predominant climate forcing in the future. PMID:14699053

  12. 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

  13. 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%.

  14. Fluid and electromagnetic transport in sea ice

    NASA Astrophysics Data System (ADS)

    Gully, Adam Spence

    Covering 7-10% of the Earth's ocean surface, sea ice is both an indicator and agent of climate change. The sea ice cover controls the exchange of heat, momentum, and gases between the ocean and atmosphere. As a material, sea ice is a polycrystalline composite consisting of a pure ice host containing brine, air, and solid salt inclusions. This dissertation examines sea ice processes that are important to climate studies. In particular, we investigate the fluid transport properties of sea ice, which mediate melt pond evolution and ice pack reflectance, snow-ice formation, nutrient replenishment for microbial communities, and the evolution of salinity profiles. We also examine the electromagnetic monitoring of these processes, which rely on some knowledge of the effective electrical properties of sea ice. Columnar sea ice is effectively impermeable to fluid flow below a 5% brine volume fraction, yet is permeable for brine volume fractions above this threshold value. In two different experiments conducted in the Arctic and Antarctic, we have found that this critical transition in fluid flow at the brine connectivity threshold displays a strong electrical signature. The sea ice conductivity data are accurately explained by percolation theory with a universal critical exponent of 2. The data also indicate marked changes in the conductivity profile with the onset of surface ponding. Further, resistance data from classical four-probe Wenner arrays on the surfaces of ice floes in Antarctica were used to indirectly reconstruct the conductivity profiles with depth, involving both the horizontal and vertical components. We note the close agreement with the actual data for some models and the inadequacy of others. Additionally, a network model for the electrical conductivity of sea ice is developed, which incorporates statistical measurements of the brine microstructure. The numerical simulations are in close agreement with direct measurements we made in Antarctica on the vertical conductivity of first year sea ice. Together, these results lay the foundation for electromagnetic monitoring of transport phenomena in sea ice and help provide a rigorous basis for electromagnetic methods to obtain sea ice thickness data. We also modify traditional percolation models for columnar sea ice, hypothesizing that granular sea ice has a percolation threshold near a 10% brine volume fraction. This modified percolation model is then in excellent agreement with our fluid permeability field data taken in Antarctica, where granular ice is a significant component of the ice cover. Here we also develop theoretical bounds on two extensive sets of effective complex permittivity sea ice data taken in the Arctic and Antarctic. The first set of bounds assumes only knowledge of the brine volume fraction or porosity, and the second set further assumes statistical isotropy of the microstructure. We obtain excellent agreement between theory and experiment, and are able to observe the apparent violation of the isotropic bounds as the vertically oriented microstructure becomes increasingly connected for higher porosities. Moreover, these bounds are inverted to obtain estimates of the porosity from the measurements of the effective complex permittivity. We find that the temporal variations of the reconstructed porosity, which is directly related to temperature, closely follow the actual behavior. Additionally, an analytic method for obtaining bounds on the effective complex permittivity of polycrystalline composite materials is developed and applied to the effective complex permittivity of sea ice. Here we use mean single crystal orientation data and single crystal complex permittivity tensor data to obtain polycrystalline forward bounds for sea ice. The single crystal complex permittivity tensor is obtained by evaluating X-ray CT data of sea ice with known ice and brine permittivites and brine volume fraction using Comsol 3.5a. Further, inverse bounds are developed and the mean single crystal orientation can be bounded from measurements of the effective complex permittivity tensor. This inverse approach helps lay the groundwork for determining ice type using remote sensing techniques.

  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. 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.

  18. Iodine emissions from the sea ice of the Weddell Sea

    NASA Astrophysics Data System (ADS)

    Atkinson, H. M.; Huang, R.-J.; Chance, R.; Roscoe, H. K.; Hughes, C.; Davison, B.; Schönhardt, A.; Mahajan, A. S.; Saiz-Lopez, A.; Hoffmann, T.; Liss, P. S.

    2012-11-01

    Iodine compounds were measured above, below and within the sea ice of the Weddell Sea during a cruise in 2009, to make progress in elucidating the mechanism of local enhancement and volatilisation of iodine. I2 mixing ratios of up to 12.4 pptv were measured 10 m above the sea ice, and up to 31 pptv was observed above surface snow on the nearby Brunt Ice Shelf - large amounts. Atmospheric IO of up to 7 pptv was measured from the ship, and the average sum of HOI and ICl was 1.9 pptv. These measurements confirm the Weddell Sea as an iodine hotspot. Average atmospheric concentrations of CH3I, C2H5I, CH2ICl, 2-C3H7I, CH2IBr and 1-C3H7I were each 0.2 pptv or less. On the Brunt Ice Shelf, enhanced concentrations of CH3I and C2H5I (up to 0.5 and 1 pptv respectively) were observed in firn air, with a diurnal profile that suggests the snow may be a source. In the sea ice brine, iodocarbons concentrations were over 10 times those of the sea water below. The sum of iodide + iodate was depleted in sea ice samples, suggesting some missing iodine chemistry. Flux calculations suggest I2 dominates the iodine atom flux to the atmosphere, but models cannot reconcile the observations and suggest either a missing iodine source or other deficiencies in our understanding of iodine chemistry. The observation of new particle formation, consistent with the model predictions, strongly suggests an iodine source. This combined study of iodine compounds is the first of its kind in this unique region of sea ice rich in biology and rich in iodine chemistry.

  19. Iodine emissions from the sea ice of the Weddell Sea

    NASA Astrophysics Data System (ADS)

    Atkinson, H. M.; Huang, R.-J.; Chance, R.; Roscoe, H. K.; Hughes, C.; Davison, B.; Schönhardt, A.; Mahajan, A. S.; Saiz-Lopez, A.; Hoffmann, T.; Liss, P. S.

    2012-05-01

    Iodine compounds were measured above, below and within the sea ice of the Weddell Sea during a cruise in 2009, to elucidate the mechanism of local enhancement and volatilisation of iodine. I2 mixing ratios of up to 12.4 pptv were measured 10 m above the sea ice, and up to 31 pptv was observed above surface snow on the nearby Brunt Ice Shelf - large amounts. Atmospheric IO of up to 7 pptv was measured from the ship, and the average sum of HOI and ICl was 1.9 pptv. These measurements confirm the Weddell Sea as an iodine hotspot. Average atmospheric concentrations of CH3I, C2H5I, CH2ICl, 2-C3H7I, CH2IBr and 1-C3H7I were each 0.2 pptv or less. On the Brunt Ice Shelf, enhanced concentrations of CH3I and C2H5I (up to 0.5 and 1 pptv, respectively) were observed in firn air, with a diurnal profile that suggests the snow may be a source. In the sea ice brine, iodocarbons concentrations were over 10 times those of the sea water below. The sum of iodide + iodate was depleted in sea ice samples, suggesting some missing iodine chemistry. Flux calculations suggest I2 dominates the iodine atom flux to the atmosphere, but models cannot reconcile the observations and suggest either a missing iodine source or other deficiencies in our understanding of iodine chemistry. The observation of new particle formation, consistent with the model predictions, strongly suggests an iodine source. This combined study of iodine compounds is the first of its kind in this unique region of sea ice rich in biology and rich in iodine chemistry.

  20. Characterizing sea ice surface morphology using high-resolution IceBridge data

    NASA Astrophysics Data System (ADS)

    Petty, A.; Farrell, S. L.; Newman, T.; Kurtz, N. T.; Richter-Menge, J.; Tsamados, M.; Feltham, D. L.

    2014-12-01

    Sea ice pressure ridges form when ice floes collide while drifting under the combined forces of atmospheric drag, oceanic drag and ice-ice interaction. Sea ice ridges, in-turn, affect the resultant form drag on the sea ice cover and thus impact the fluxes of momentum and heat between the atmosphere and ocean. Here we present initial results of a new sea ice ridge detection approach that utilizes high resolution, three-dimensional ice/snow surface elevation data from the NASA Operation IceBridge Airborne Topographic Mapper (ATM) laser altimeter merged with coincident high-resolution imagery from the Digital Mapping System (DMS). We derive novel information regarding sea ice deformation across a variety of ice types and regimes. Statistical information regarding sea ice ridges (height/frequency/orientation) and floe edges (freeboard height) are presented for several IceBridge flight lines. These novel characterizations of sea ice surface morphology will be used to validate and inform drag parameterizations in state-of-the-art sea ice models. Furthermore, they will advance our ability to quantify uncertainties introduced by pressure ridges in the estimation of sea ice freeboard/thickness from airborne and satellite altimeters.

  1. Characterizing sea ice surface morphology using high-resolution IceBridge data

    NASA Astrophysics Data System (ADS)

    Petty, Alek; Farrell, Sinead; Newman, Thomas; Kurtz, Nathan; Richter-Menge, Jacqueline; Tsamados, Michel; Feltham, Daniel

    2015-04-01

    Sea ice pressure ridges form when ice floes collide while drifting under the combined forces of atmospheric drag, oceanic drag and ice-ice interaction. Sea ice ridges, in-turn, affect the resultant form drag on the sea ice cover and thus impact the fluxes of momentum and heat between the atmosphere and ocean. Here we present initial results of a new sea ice ridge detection approach that utilizes high resolution, three-dimensional ice/snow surface elevation data from the NASA Operation IceBridge Airborne Topographic Mapper (ATM) laser altimeter merged with coincident high-resolution imagery from the Digital Mapping System (DMS). We derive novel information regarding sea ice deformation across a variety of ice types and regimes. Statistical information regarding sea ice ridges (height/frequency/orientation) and floe edges (freeboard height) are presented for several IceBridge flight lines. These novel characterizations of sea ice surface morphology will be used to validate and inform drag parameterizations in state-of-the-art sea ice models. Furthermore, they will advance our ability to quantify uncertainties introduced by pressure ridges in the estimation of sea ice freeboard/thickness from airborne and satellite altimeters.

  2. 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 linked to the strong retreat of sea ice that year.

  3. 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.

  4. 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 estimates based on isostasy with assumed values of snow and ice density.

  5. Extreme Weather in Northern Mid-latitudes Linked to Arctic Ice and Snow Losses

    NASA Astrophysics Data System (ADS)

    Tang, Qiuhong; Zhang, Xuejun; Francis, Jennifer A.

    2014-05-01

    The past decade has seen an exceptional number of unprecedented extreme weather events in northern mid-latitudes, along with record declines in both Arctic sea ice and snow cover on high-latitude land. The underlying mechanisms that link the shrinking cryosphere with the extreme weather in the mid-latitude continent, however, remain unclear. Previous studies have linked changes in winter atmospheric circulation, anomalously cold extremes and large snowfalls in mid-latitudes to rapid decline of Arctic sea ice in the preceding autumn. Using observational analyses, we show that the winter atmospheric circulation change and cold extremes are associated with winter sea ice reduction through an apparently distinct mechanism from those related to autumn sea ice loss. The associations between the increased summer extreme heat events in mid-latitudes and losses of snow and sea ice are also demonstrated using satellite observations of early summer snow cover and summer sea-ice extent. Although there is still much to learn about the interactions between a rapidly changing Arctic and large-scale circulation patterns, our results provide further evidence linking cryospheric loss with the mid-latitude extreme weather.

  6. 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.

  7. Sea Ice and Oceanographic Conditions.

    ERIC Educational Resources Information Center

    Oceanus, 1986

    1986-01-01

    The coastal waters of the Beaufort Sea are covered with ice three-fourths of the year. These waters (during winter) are discussed by considering: consolidation of coastal ice; under-ice water; brine circulation; biological energy; life under the ice (including kelp and larger animals); food chains; and ice break-up. (JN)

  8. Snow and ice surfaces measured by the Nimbus 5 microwave spectrometer

    NASA Technical Reports Server (NTRS)

    Kunzi, K. F.; Fisher, A. D.; Staelin, D. H.; Waters, J. W.

    1976-01-01

    The 22.2- and 31.4-GHz channels of the microwave spectrometer on board the Nimbus 5 earth observatory satellite provide information about the global distribution and character of various types of snow and ice. Observations for the winter and summer of 1973 are presented for both polar regions. Well-defined spectral signatures are found for snow, sea ice, and land ice in Greenland and Antarctica. A simple model with subsurface temperature gradients in a lossy homogeneous dielectric does not account for the observations; internal scattering effects appear to play a dominant role.

  9. Applied Sea Ice Research

    NASA Astrophysics Data System (ADS)

    Løset, S.

    2009-04-01

    In the late 1960s oil and gas development became an issue in the northern coastal areas of Alaska and Canada. More lately this has also become an issue in the Euroasian Arctic with the Barents and Kara Seas as example on where offshore hydrocarbon production now is being planned. In such waters the key questions prior to a development are related to water depths at the site and in case of ice, how frequent and what type of ice features will be met. Especially the ice conditions and knowledge about them are very decisive for the field development solutions to be chosen. The paper will highlight examples on development solutions where the ice conditions have played a paramount role in the field development plans. An example is the consequences of iceberg threaten in an area and the effect sudden changes in ice drift directions may have on the exploration and drilling solutions chosen. The paper will also discuss how to derive design ice actions values for such waters including scaling from nature to model ice basins.

  10. 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.

  11. 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.

  12. 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.

  13. Extreme melt-freeze processes on Antarctic sea ice: implications for evolution of perennial ice mass balance and biological communities

    NASA Astrophysics Data System (ADS)

    Maksym, T.; Pasquer, B.; Shoosmith, D.

    2008-12-01

    The evolution of Antarctic perennial sea ice is dominated by processes associated with its thick snow cover. The key processes (snow ice formation via seawater inundation and freezing and superimposed ice formation via meltwater percolation and refreezing) are distinct from those that dominate in the Arctic and are not adequately described in models. We present sea ice core data obtained in the Bellingshausen Sea in late summer, 2007. Evidence for extreme melt and refreezing of the snow cover was found in the eastern Bellingshausen Sea with as much as two meters or more of the snowpack converted into sea ice per year - far greater than has been observed before. In the western Bellingshausen, snow ice formation dominated the surface mass balance, presumably due to colder conditions and deeper snow cover. In contrast to previous observations, we find evidence for refreezing of snow meltwater in ice types other than classic superimposed ice. This hinders the unambiguous identification of ice types and may have implications for previously reported mass balance data. Highly productive gap-layer communities were widespread in the western Bellingshausen where snow ice was more prevalent, while they were less common in the warmer east where superimposed ice dominated. To examine these processes the ice core data are compared with results of a complex thermodynamic-hydraulic model. Based on these results we hypothesize that the snow cover and melt play an important role in structuring biological communities. Warmer conditions may lead to extreme meltwater percolation and refreezing that, while stabilizing the ice cover, inhibits the formation of porous gaps and limits sea ice primary productivity. We also describe plans for two research cruises in early 2009 where we will further investigate these phenomena.

  14. 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.; Vallelonga, P.

    2015-08-01

    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 AD 1950 to 1998 sea ice in the Laptev Sea based on the Akademii Nauk ice core (Severnaya Zemlya, Russian Arctic). The halogens bromine (Br) and iodine (I) are strongly influenced by sea ice processes. Bromine reacts with the sea ice surface in auto-catalyzing "Bromine explosion" events causing an enrichment of the Br / Na ratio and the bromine excess (Brexc) in snow compared to that in seawater. Iodine is 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. These two halogens are therefore good candidates for extended reconstructions of past sea ice changes in the Arctic.

  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/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.

  17. Intercomparison of the Arctic sea ice cover in global ocean-sea ice reanalyses from the ORA-IP project

    NASA Astrophysics Data System (ADS)

    Chevallier, Matthieu; Smith, Gregory C.; Dupont, Frédéric; Lemieux, Jean-François; Forget, Gael; Fujii, Yosuke; Hernandez, Fabrice; Msadek, Rym; Peterson, K. Andrew; Storto, Andrea; Toyoda, Takahiro; Valdivieso, Maria; Vernieres, Guillaume; Zuo, Hao; Balmaseda, Magdalena; Chang, You-Soon; Ferry, Nicolas; Garric, Gilles; Haines, Keith; Keeley, Sarah; Kovach, Robin M.; Kuragano, Tsurane; Masina, Simona; Tang, Yongming; Tsujino, Hiroyuki; Wang, Xiaochun

    2016-01-01

    Ocean-sea ice reanalyses are crucial for assessing the variability and recent trends in the Arctic sea ice cover. This is especially true for sea ice volume, as long-term and large scale sea ice thickness observations are inexistent. Results from the Ocean ReAnalyses Intercomparison Project (ORA-IP) are presented, with a focus on Arctic sea ice fields reconstructed by state-of-the-art global ocean reanalyses. Differences between the various reanalyses are explored in terms of the effects of data assimilation, model physics and atmospheric forcing on properties of the sea ice cover, including concentration, thickness, velocity and snow. Amongst the 14 reanalyses studied here, 9 assimilate sea ice concentration, and none assimilate sea ice thickness data. The comparison reveals an overall agreement in the reconstructed concentration fields, mainly because of the constraints in surface temperature imposed by direct assimilation of ocean observations, prescribed or assimilated atmospheric forcing and assimilation of sea ice concentration. However, some spread still exists amongst the reanalyses, due to a variety of factors. In particular, a large spread in sea ice thickness is found within the ensemble of reanalyses, partially caused by the biases inherited from their sea ice model components. Biases are also affected by the assimilation of sea ice concentration and the treatment of sea ice thickness in the data assimilation process. An important outcome of this study is that the spatial distribution of ice volume varies widely between products, with no reanalysis standing out as clearly superior as compared to altimetry estimates. The ice thickness from systems without assimilation of sea ice concentration is not worse than that from systems constrained with sea ice observations. An evaluation of the sea ice velocity fields reveals that ice drifts too fast in most systems. As an ensemble, the ORA-IP reanalyses capture trends in Arctic sea ice area and extent relatively well. However, the ensemble can not be used to get a robust estimate of recent trends in the Arctic sea ice volume. Biases in the reanalyses certainly impact the simulated air-sea fluxes in the polar regions, and questions the suitability of current sea ice reanalyses to initialize seasonal forecasts.

  18. 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.

  19. Standardization of electromagnetic-induction measurements of sea-ice thickness in polar and subpolar seas

    NASA Astrophysics Data System (ADS)

    Tateyama, K.; Shirasawa, K.; Uto, S.; Kawamura, T.; Toyota, T.; Enomoto, H.

    Electromagnetic-induction (EM) instruments can be used to estimate sea-ice thickness because of the large contrast in the conductivities of sea ice and sea water, and are currently used in investigations of sea-ice thickness. In this study we analyze several snow, ice and sea-water samples and attempt to derive an appropriate formula to transform the apparent conductivity obtained from EM measurements to the total thickness of snow and ice for all regions and seasons. This was done to simplify the EM tuning procedure. Surface EM measurement transects with the instrument at varying heights above the ice were made in the Chukchi Sea, off East Antarctica, in the Sea of Okhotsk and in Saroma-ko (lagoon). A standardized transformation formula based on a one-dimensional multi-layer model was developed that also considers the effects of water-filled gaps between deformed ice, a saline snow slush layer, and the increase in the footprint size caused by increasing the instrument height. The overall average error in ice thickness determined with the standardized transform was <7%, and the regional average errors were 2.2% for the Arctic, 7.0% for the Antarctic, 6.5% for the Sea of Okhotsk and 4.4% for Saroma-ko.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. Sensitivity studies with a sea ice-mixed layer-pycnocline model in the Weddell Sea

    SciTech Connect

    Owens, W.B. ); Lemke, P. )

    1990-06-15

    The sensitivity of a dynamic-thermodynamic sea ice model coupled to a one-dimensional mixed layer-pycnocline model to variations of dynamic and thermodynamic model parameters is investigated. Furthermore, the modifications of the model results due to the inclusion of a prognostic snow cover and the implementation of simplified sea ice rheologies are investigated. In these comparisons special emphasis is placed upon the ice-ocean boundary conditions (buoyancy fluxes) and the mixed layer properties.

  5. Arctic Sea Ice Model Sensitivities

    NASA Astrophysics Data System (ADS)

    Peterson, K. J.; Bochev, P.; Paskaleva, B.

    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. Sandia National Laboratories is a multi-program laboratory operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U. S. Department of Energy’s National Nuclear Security Administration under Contract DE-AC04-94-AL85000.

  6. 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.

  7. NASA IceBridge: Airborne surveys of the polar sea ice covers

    NASA Astrophysics Data System (ADS)

    Richter-Menge, J.; Farrell, S. L.

    2014-12-01

    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. Primary OIB sensors being used for sea ice observations include the Airborne Topographic Mapper laser altimeter, 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 campaigns and highlight key scientific accomplishments, which include: • Documented changes in the Arctic marine cryosphere since the dramatic sea ice loss of 2007 • Novel snow depth measurements over sea ice in the Arctic • Improved skill of April-to-September sea ice predictions via numerical ice/ocean models • Validation of satellite altimetry measurements (ICESat, CryoSat-2, and IceSat-2/MABEL)

  8. 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)

  9. 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.

  10. 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.

  11. 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 processes in the model parameterization, as they are not constrained by observations from sea ice covered regions. A sensitivity analysis of the freeboard estimation procedure indicates an uncertainty of ˜0.24 m over a length scale of 100 km. The estimated total ice freeboards were compared with freeboard measurements from other methods (e.g. 'lowest level'), and a good agreement was found between the two methods at regional scales. The sea ice thickness, in the multi-year ice region north of Greenland and Ellesmere Island, was also derived from the total ice freeboard heights by assuming a hydrostatic equilibrium condition. The estimated thicknesses were compared with the thickness measurements from a Helicopter-borne Electromagnetic Induction technique. The difference between the means of the two thickness distributions was ˜0.53 m, which is well below the accuracy of the thickness estimates of ˜0.98 m. The sea ice freeboard estimation procedure, demonstrated in this study, can also be applied to upcoming laser and radar altimetry missions, such as Cryosat-2 and ICESat-2, to continuously monitor the regional, seasonal and inter-annual changes in the Arctic sea ice freeboard (and thickness) distribution.

  12. 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.

  13. Albedo over rough snow and ice surfaces

    NASA Astrophysics Data System (ADS)

    Lhermitte, Stef; Abermann, Jakob; Kinnard, Christophe

    2014-05-01

    Surface albedo determines the shortwave radiation balance, arguably the largest energy balance component of snow and ice surfaces. Consequently, incorporation of the spatio-temporal variability of albedo is essential when assessing the surface energy balance of snow and ice surfaces. This can be done by using ground-based measurements or albedo data derived from remote sensing, or by modelling albedo based on radiative transfer models or empirically based parameterizations. One decisive factor when incorporating albedo data is the representativeness of surface albedo, certainly over rough surfaces where albedo measurements at a specific location (i.e., apparent albedo) can differ strongly from the material albedo or the true albedo (i.e., effective albedo) depending on the position of the sun/sensor and the surface roughness. This stresses the need for a comprehensive understanding of the effect of surface roughness on albedo and its impact when using albedo data for validation of remote sensing imagery, interpretation of automated weather station (AWS) radiation data or incorporation in energy balance models. To assess the effect of surface roughness on albedo an intra-surface radiative transfer (ISRT) model was combined with albedo measurements on a penitente field on Glaciar Tapado in the semi-arid Andes of Northern Chile. The ISRT model shows albedo reductions between 0.06 and 0.35 relative to flat surfaces with a uniform material albedo. The magnitude of these reductions primarily depends on the penitente geometry, but the shape and spatial variability of the material albedo also play a major role. Secondly, the ISRT model was used to reveal the effect of using apparent albedo to infer the effective albedo over a rough surface. This effect is especially strong for narrow penitentes, resulting in sampling biases up to ±0.05. The sampling biases are more pronounced when the sensor is low above the surface, but remain relatively constant throughout the day. Consequently, the only beneficial approach to minimize the sampling bias of surface albedo over rough surfaces is to use a large number of samples at various places. Thirdly, the temporal evolution of broadband albedo over a penitente-covered surface was analyzed to place the experiments and their uncertainty into a larger temporal context. Time series of albedo measurements at an automated weather station over two seasons reveal albedo decreases early in the ablation season. These decreases stabilize from February onwards with variations being caused by fresh snow-fall events. The 2009/2010 and 2011/2012 seasons differ notably, where the latter shows lower albedo caused by larger penitentes. Finally, a comparison of the ground-based albedo observations with Landsat and MODIS-derived albedo showed that both satellite derived albedo products capture the albedo evolution with root mean square errors of 0.08 and 0.15, respectively, but also illustrate their shortcomings related to temporal resolution and spatial heterogeneity over mountain glaciers.

  14. 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 since the late 1950's. That could have slowed the thermohaline circulation beneath the Ross Ice Shelf and the properties or volume of local bottom water production.

  15. 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.

  16. 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.

  17. 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 assimilation) have a far narrower spread in their prediction, indicating that the results of these more sophisticated methods are converging. Here we summarize and synthesize the 2014 contributions to the SIO, highlight the important questions and challenges that remain to be addressed, and present data on stakeholder uses of the SIO and related SIPN products.

  18. Interactions between Antarctic Sea Ice, Ice Sheets, and Climate Through the Cenozoic

    NASA Astrophysics Data System (ADS)

    Deconto, R.; Pollard, D.; Harwood, D.

    2004-12-01

    The seasonal distribution and thickness of Antarctic sea ice has important climatic effects on radiation balance, energy transfer between the atmosphere and ocean, moisture availability, and thermohaline circulation. Here, we explore the role of sea ice and related feedbacks in the Cenozoic evolution of Antarctic climate and ice sheets. We use a numerical climate model with explicit, dynamical representations of sea ice and grounded continental ice sheets to test: 1) the sensitivity of Southern Hemisphere sea ice to early Cenozoic climate forcing (paleogeography, CO2, orbital cycles, and ice sheet configuration); and 2) the importance of sea ice-atmosphere feedbacks on glacial mass balance in the Antarctic interior. In our model, little or no sea ice forms around the Antarctic margin with 3xCO2, regardless of orbital forcing or ice sheet configuration. At 2xCO2 seasonal sea ice distribution is shown to be highly sensitive to ice sheet size and configuration, via the ice sheet's control on Southern Ocean surface temperature and the low-level wind field. As in prior modeling studies, the growth of sea ice produces significant local-regional changes in net radiation and surface heat flux heat, with statistically significant effects on temperature, precipitation, and surface pressure over the sea ice zone and coastal areas. Only limited effects are seen in the continental interior, however, and changes in net annual snow budgets are too small to affect the pace of a growing East Antarctic ice sheet. These results suggest the Cenozoic appearance of Antarctic sea ice was a response to grounded ice volume and was not a critical factor in Paleogene and Neogene episodes of glaciation. The East Antarctic Ice Sheet's control of equatorward sea ice extent has important implications for Southern Ocean deepwater production and implies proxy reconstructions of ancient sea ice may be indicative of conditions in the continental interior. According to our model, the most persistent and thickest sea ice, prior to the development of the West Antarctic Ice Sheet, would have been located along the western margin of the shallow seaway separating east and west Antarctica, a critical area for the formation of ice shelves that could have influenced the early development of the West Antarctic Ice Sheet.

  19. 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.

  20. Sea-ice velocity fields estimation on Ross Sea with NOAA-AVHRR

    SciTech Connect

    Flores, M.M.; Maitre, H.; Parmiggiani, F.

    1995-09-01

    A complete methodology is proposed for automatic tracking of sea-ice in daylight AVHRR data. Two aspects are specially outlined: the use of partially cloudy monocular images and the estimation of ice pack trajectories along an image sequence. First, a classification technique is applied for the detection of snow-ice regions. Then, an optimal matching filter is used for the sea-ice motion estimation. The derived vector field is homogeneous and shows the ice pack motion along three days image data.

  1. 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 thinner pack ice at the eastern ice edge towards thicker pack ice on the Greenland shelf in the western part of Fram Strait with thick multiyear ice. The spring modal thickness ranged from about 2 m to 3.5 m. In contrast, the spatial variability of the modal thickness in 2008 is larger than observed in the previous campaigns with a wider range of modal ice thicknesses, predominantly due to thinner ice than in 2005. Finally, during late summer 2010 modal thicknesses in the central and eastern part of Fram Strait ranged from about 1 to 2 m. At the same time distributions were in general narrower than observed in previous years, showing a decrease of the fraction of thick pressure ridges. Thick ice was measured only in the westernmost part of Fram Strait. These observations are in agreement with a reported trend towards a generally larger amount of first-year ice versus multiyear ice in the Arctic.

  2. 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 as a snow depth with centimetre accuracy.

  3. Arctic sea ice Freeboard Heights From ICESat Laser Altimetry

    NASA Astrophysics Data System (ADS)

    Renganathan, V.; Braun, A.; Skourup, H.; Forsberg, R.

    2009-05-01

    Arctic sea ice extent has been decreasing at a rate of about 10% per decade, since the earliest satellite observations in 1979. This decline is mainly attributed to climate change and variability. The effect of climate change is more pronounced in the Arctic because of the ice-albedo feedback effect which accelerates the melting process. In order to understand the changing Arctic sea ice cover, the change in sea ice volume must be known (both extent and thickness). Sea ice thickness is an important parameter that moderates the heat exchange between the ocean and the atmosphere which affects the Earth's climate. Despite about 200 years of research and observations in the Arctic, detailed observations at large-spatial scales and long continuous time-series are not available. In this study, satellite laser altimetry data from ICESat (NASA's Ice, Cloud, and Elevation Satellite) have been used to estimate Arctic sea ice freeboard heights based on the models of geoid (EIGEN-GL04), ocean tides (AOTIM-5), and mean dynamic topography. Sea ice freeboard can be eventually converted into thickness, if the physical properties of the ice pack are known using hydrostatic equilibrium assumptions. Current limitations in this method are the lack of information on the depth of the overlying snow layer and the uncertainties in the oceanographic models. Sea ice freeboard results from ICESat for mission phases from 2003 to 2008 will be discussed.

  4. 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).

  5. 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 including sea-ice brine volume, snow and ice complex dielectric properties, and snow physical properties.

  6. Geochemical Characteristics And Zones Of Surface Snow On East Antarctic Ice sheet

    NASA Astrophysics Data System (ADS)

    Kang, J.

    2004-12-01

    Geochemical characteristics and zones of surface snow on east Antarctic Ice Sheet Jiancheng KANG1,4, Leibao LIU1, Dahe QIN2, Dali WANG1, Jiahong WEN1, Dejun TAN1, Zhongqin LI2, Jun LI3 & Xiaowei ZHANG1,4 1 Polar Research Institute of China, Shanghai 200129, China; 2 Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000, China; 3 Australian Antarctic Division and Antarctic Climate and Ecosystems CRC, Private Bag 80 Hobart, Tasmania, 7001, Australia; 4 Geography Department of Lanzhou University, Lanzhou 730000, China Correspondence should be addressed to Jiancheng KANG (email: kangjc@sh163.net, kangjc@126.com ) Abstract The surface-snow geochemical characteristics are discussed on the East Antarctic Ice Sheet, depending on the stable isotopes ratios of oxygen and hydrogen, concentration of impurities (soluble-ions and insoluble micro-particle) in surface snow collected on the ice sheet. The purpose is to study geochemical zones on the East Antarctic Ice Sheet and to research sources and transportation route of the water vapor and the impurities in surface snow. It has been found that the ratio coefficients, as S1, d1 in the equation ƒOD = S1ƒO18O + d1, are changed near the elevation 2000m on the ice sheet. The weight ratio of Cl-/Na+ at the area below the elevation of 2000m is close to the ratio in the sea salt; but it is about 2 times that of the sea salt, at the inland area up to the elevation of 2000m. The concentrations of non-sea-salt Ca2+ ion (nssCa2+) and fine-particle increase at the interior up to the elevation 2000m. At the region below the elevation of 2000m, the impurity concentration is decreasing with the elevation increasing. Near coastal region, the surface snow has a high concentration of impurity, where the elevation is below 800m. Combining the translating processes of water-vapor and impurities, it suggests that the region up to the elevation 2000m is affected by large-scale circulation with longitude-direction, and that water-vapor and impurities in surface snow come from long sources. The region below the elevation 2000m is affected by some strong cyclones acting at peripheral region of the ice sheet, the sources of water and impurities could be at high latitude sea and coast. The area below elevation 800m is affected by local coastal cyclones. Keywords: Antarctic Ice Sheet, Snow, Geochemical Zones

  7. 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.

  8. LES modeling of wind over Antarctic snow-ice formations using a dynamic surface roughness approach

    NASA Astrophysics Data System (ADS)

    Giometto, M. G.; Trujillo, E.; Leonard, K. C.; Maksym, T. L.; Meneveau, C. V.; Lehning, M.; Parlange, M. B.

    2013-12-01

    Wind surface drag over sea-ice is a primary control on sea-ice flow patterns and deformations at scales that are important for climate and weather prediction models. Here, we perform a series of Large Eddy Simulations (LES) of fully developed flow over high-resolution snow-ice surfaces of Antarctic sea ice floes to study surface drag and roughness parameters at process scales from 1 cm to 100 m. Snow/ice surface morphology was obtained using a Terrestrial Laser Scanner during the SIPEX II (Sea Ice Physics and Ecosystem experiment II) research voyage to East Antarctica (September-November 2012). LES are performed on a regular domain adopting a mixed pseudo-spectral/finite difference spatial discretization. A scale-dependent dynamic subgrid-scale model based on Lagrangian time averaging is adopted to determine the eddy-viscosity in the bulk of the flow. The effects of large-scale features of the surface on the wind flow (those features that can be resolved in LES) are accounted for through an immersed boundary method. Conversely, the drag forces caused by subgrid-scale features of the surface should be accounted for through a parameterization. However the effective aerodynamic surface roughness parameter z0 for snow ice is not known. Hence, a dynamic approach is utilized, in which this parameter is determined using the first-principles based constraint that the total momentum flux (drag) must be independent on grid-filter scale. This dynamic surface roughness model is inspired by the Germano identity, traditionally used to determine model parameters for closing subgrid-scale stresses in the bulk of a turbulent flow. This type of model has been previously applied to flow over multi-scale terrain and ocean waves but never for snow-ice surfaces. The resulting dynamic parameter will be compared with values obtained for solid terrain and ocean sea surface values, and the implications on overall drag forces on snow ice surfaces will be discussed.

  9. 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)

  10. 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.

  11. Uncertainties in Arctic sea ice thickness and volume: new estimates and implications for trends

    NASA Astrophysics Data System (ADS)

    Zygmuntowska, M.; Rampal, P.; Ivanova, N.; Smedsrud, L. H.

    2013-10-01

    Sea ice volume has been found to decrease in the last decades, evoked by changes in sea ice area and thickness. Estimates of sea ice area and thickness rely on a number of geophysical parameters which introduce large uncertainties. To quantify these uncertainties we use freeboard retrievals from ICESat and investigate different assumptions on snow depth, sea ice density and area. We find that uncertainties in ice area are of minor importance for the estimates of sea ice volume during the cold season in the Arctic basin. The choice of mean ice density used when converting sea ice freeboard into thickness mainly influences the resulting mean sea ice thickness, while snow depth on top of the ice is the main driver for the year-to-year variability, particularly in late winter. The absolute uncertainty in the mean sea ice thickness is 0.28 m in February/March and 0.21 m in October/November. The uncertainty in snow depth contributes up to 70% of the total uncertainty and the ice density 30-35%, with higher values in October/November. We find large uncertainties in the total sea ice volume and trend. The mean total sea ice volume is 10 120 ± 1278 km3 in October/November and 13 254 ± 1858 km3 in February/March for the time period 2005-2007. Based on these uncertainties we obtain trends in sea ice volume of -1445 ± 531 km^3 a-1 in October/November and -875 ± 257 km3 a-1 in February/March over the ICESat period (2003-2008). Our results indicate that, taking into account the uncertainties, the decline in sea ice volume in the Arctic between the ICESat (2003-2008) and CryoSat-2 (2010-2012) periods may have been less dramatic than reported in previous studies.

  12. Seasonal Variation of Antarctic Sea-Ice Freeboard Heights and Thicknesses from ICESat

    NASA Astrophysics Data System (ADS)

    Yi, D.; Zwally, H. J.

    2004-12-01

    The distribution of sea ice affects Earth's radiative balance and atmosphere and ocean circulation. The study of sea-ice thickness distribution and volume variation is an important part of understanding the Earth's climate system. ICESat measures the mean surface elevation of flat surfaces to better than 3 cm over its 70 m laser footprints spaced at 170 m. This provides an important tool to study sea ice. Previous knowledge of Antarctic sea-ice freeboard and thickness is based on very limited information from surface and ship-based measurements. The ICESat orbit has an inclination of 94 and its ground tracks cover all sea ice surrounding Antarctica. Using open water and thin ice as reference sea level, a novel technique has been developed to measure sea-ice freeboard using ICESat measured elevation data. With estimates of snow, brine, and sea-ice density, combined with snow depth data from AMSR-E, sea-ice thickness can be derived from the freeboard. Sea-ice freeboard and thickness were calculated along ICESat ground tracks first and then gridded to 50 x 50 km grid maps. Three periods of Antarctic sea-ice freeboard and thickness data have been studied. Sea-ice freeboard and thickness distributions show clear seasonal variation. During the Antarctic winter (Oct-Nov, 2003), sea ice grows to its seasonal maximum. Thicker sea ice surrounds the Antarctic continent; thinner sea ice is distributed near Princess Ragnhild Coast and the Amundsen and Bellingshausen Seas; the mean thickness of winter sea ice is 2.9 m. During the Antarctic summer (Feb-Mar, 2004), thinner sea ice melts away. Sea ice is mainly distributed in the Weddell Sea near the Antarctic Peninsula and Ross Sea, with a mean thickness of 2.4 m. During the Antarctic fall (May-Jun, 2004), large areas of new, thinner sea ice forms. Thinner sea ice covers large areas of the Weddell and Ross Seas, and the overall mean thickness is 1.9 m. Overall, ICESat measurements provide unprecedented accuracy and spatial and temporal coverage of sea-ice freeboard and thickness and can be used to monitor sea-ice volume, which is an indicator of climate change.

  13. 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.

  14. Formation of Singlet Molecular Oxygen on Illuminated Ice and Snow

    NASA Astrophysics Data System (ADS)

    McKellar, S. R.; Anastasio, C.

    2005-12-01

    Pollutants and other trace compounds on snow and ice are transformed both by direct photolysis as well as indirect photoreactions mediated by oxidants such as hydroxyl radical (OH). These reactions likely play a major role in the fate of environmental contaminants in regions with permanent or seasonal snow cover, but we know relatively little about which reactions are important and at what rates they transform trace pollutants. The indirect photodegradation of organics is most likely caused by oxidants such as OH and singlet molecular oxygen (1O2* ), which can be formed in the snowpack by illumination from the sun. While some recent work has characterized the formation of OH in snow, the presence of 1O2* on illuminated snow or ice has not been studied previously. In this study, our goal is to determine the steady state concentrations of singlet molecular oxygen in illuminated snow samples collected from Summit, Greenland during the summer of 2005. We add furfuryl alcohol (FFA), which acts as a chemical probe of singlet molecular oxygen, to ice pellets made from Greenland snow samples and monitor the rate of loss of FFA during illumination. Our initial results indicate that 1O2* is formed in illuminated Summit samples and that the steady-state concentration of 1O2* is much larger on ice (-10 °C) than in liquid solution (°C) using the same prepared sample. We will present our measured steady-state concentrations of 1O2* as well as the impacts of this oxidant on the lifetimes of trace organics such as PAHs and biogenic phenols in Greenland snow.

  15. Surface-based passive microwave studies of multiyear sea ice

    NASA Technical Reports Server (NTRS)

    Grenfell, T. C.

    1992-01-01

    Results are presented on surface-based multifrequency passive microwave observations of multiyear (MY) sea ice in the eastern Arctic Basin, the Beaufort Sea, the Canadian archipelago, and the northern Greenland Sea. The analyses of these data show that the magnitude of the spectral gradient of emissivity is directly related to the existence and the thickness of a decomposed surface ice layer with very high porosity. Spectra for melt ponds with a frozen surface layer closely resembled those of lake ice and showed a positive spectral gradient. The variance among emissivity spectra for MY ice was caused primarily by the distributions of melt ponds and by the presence of significant amounts of scattering inhomogeneities in the snow and the upper 20-30-cm layer of the ice.

  16. 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.

  17. 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 observations has substantially changed at that year. Therefore, this analysis includes only data of 585 Russian stations from 1966 to 2008 that have all years of data with a minimal number of missing observations. Surveys run separately along all types of environment typical for the site for 1 to 2 km, describing the current snow cover properties including characteristics of snow and ice crust. Joint analysis of these characteristics of crust together with a suite of synoptic information at the stations allows us to empirically assess the process of snow and ice crust formation and development throughout the cold season and outline major factors responsible for their dynamics. Finally, regional averaging and time series analysis of both, these factors and the crust characteristics themselves, answer the question about the regional climatic changes of snow and ice crusts over Northern Eurasia, including those crust characteristics that are of practical importance for reindeer husbandry. These results for the Russian Federation will be presented at the Meeting.

  18. 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 other sites in Washington State that are downwind of large regional emission sources.

  19. 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.

  20. 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 among models. High agreement also accompanies projections that the Chukchi Sea will be completely ice covered during February, March, and April at the end of the century. Large uncertainties, however, are associated with the timing and amount of partial ice cover during the intervening periods of melt and freeze. For the Bering Sea, median March ice extent is projected to be about 25 percent less than the 1979-1988 average by mid-century and 60 percent less by the end of the century. The ice-free season in the Bering Sea is projected to increase from its contemporary average of 5.5 months to a median of about 8.5 months by the end of the century. A 3-month longer ice- free season in the Bering Sea is attained by a 1-month advance in melt and a 2-month delay in freeze, meaning the ice edge typically will pass through the Bering Strait in May and January at the end of the century rather than June and November as presently observed.

  1. 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....

  2. 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....

  3. 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....

  4. 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....

  5. 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....

  6. 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?

  7. The sensitivity of a one-dimensional thermodynamic sea ice model to changes in cloudiness

    NASA Technical Reports Server (NTRS)

    Shine, K. P.; Crane, R. G.

    1984-01-01

    A thermodynamic sea ice-lead model is used to assess the importance of cloud cover changes to modeled ice thickness. For regions of either permanent multiyear ice or seasonal sea ice, the cloud amount variations have relatively little impact. However, for regions where the presence of summer ice is variable from year to year, the predicted ice thickness is strongly dependent on cloud cover. In general, with a snow covered surface, decreased cloud leads to surface cooling while increased cloud gives rise to a surface warming. For a melting bare ice surface, the reverse occurs. The ice model response time is too long for interannual variations in cloud amount to explain interannual variations in ice thickness and extent. Nevertheless, the implication of the results is that numerical modeling of sea ice distribution requires accurate cloud data or cloud prediction and that trends in cloud cover may lead to significant perturbations in sea ice extent and thickness.

  8. 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

  9. 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 pulse-limited radar altimeter that has a footprint that varies from a few meters to a few tens of meters depending on altitude and roughness of the reflective surface. Intercalibration of the two instruments was accomplished at leads in the ice and by multiple over-flights of four radar corner-cubes set ~ 2 m above the snow along the ground-truth line. Direct comparison of successive flights of the ground-truth line to flights done in a grid pattern over and adjacent to the line was complicated by the ~ 20-30 m drift of the ice-floe between successive flight-lines. This rapid ice movement required the laser and radar data be translated into an ice-fixed, rather than a geographic reference frame. This was facilitated by geodetic GPS receiver measurements at the ice-camp and Pt. Barrow. The NRL data set, in combination with the ground-truth line and submarine upward-looking sonar data, will aid in understanding the error budgets of our systems, the ICEBRIDGE airborne measurements (also flown over the ground-truth line), and the CRYOSAT-2 data over a wide range of ice types.

  10. Incorporation of sulfur dioxide into snow and depositing ice

    SciTech Connect

    Valdez, M.P.

    1987-01-01

    Depth profiles of S(IV) and S(VI) in snow exposed to 20-140 ppbv SO/sub 2/ for 6 to 12 hours were determined in 48 laboratory experiments. Surface deposition velocity (V/sub d/) averaged 0.06 cm s/sup -1/. Well-metamorphosed snow, longer run times, higher SO/sub 2/ concentrations and colder snow were associated with lower values of V/sub d/, and vice versa. Melting followed by draining increased v/sub d/ greatly (0.14 cm s/sup -1/). Any effect of ozone on SO/sub 2/ v/sub d/ was undetectable. Most sulfur in the snow was a S(VI), even without added ozone, indicating the presence of other oxidants, especially in new snow. The deposition of SO/sub 2/ into a snowpack is modeled as an aqueous system, where the liquid water is considered to be present on snow grain surfaces. Gas transport into the snow, air-water partitioning,and aqueous-phase reactions are explicitly considered. Experiments were also conducted on the incorporation of SO/sub 2/ into ice depositing from the vapor at -7 and -15/sup 0/C. Remarkably, SO/sub 2/ is captured in deposited ice at concentrations comparable to Henry's Law equilibrium with water at 0/sup 0/C. Ozone and HCHO appear to inhibit, not enhance, SO/sub 2/ capture. An aqueous-film model accounting for the capture of SO/sub 2/ by depositing ice was developed.

  11. 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 easily imaged and studied. The low-temperature SEM sample collecting and handling methods proved to be operable in the field; the SEM analysis is applicable to glaciological studies and reveals details unattainable by conventional light microscopic methods.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 and ice worms were also collected and imaged. 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. The SEM has a great depth of field with a wide range of magnifying capabilities.

  12. 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.

  13. Variability of Arctic Sea Ice as Viewed from Space

    NASA Technical Reports Server (NTRS)

    Parkinson, Claire L.

    1998-01-01

    Over the past 20 years, satellite passive-microwave radiometry has provided a marvelous means for obtaining information about the variability of the Arctic sea ice cover and particularly about sea ice concentrations (% areal coverages) and from them ice extents and the lengths of the sea ice season. This ability derives from the sharp contrast between the microwave emissions of sea ice versus liquid water and allows routine monitoring of the vast Arctic sea ice cover, which typically varies in extent from a minimum of about 8,000,000 sq km in September to a maximum of about 15,000,000 sq km in March, the latter value being over 1.5 times the area of either the United States or Canada. The vast Arctic ice cover has many impacts, including hindering heat, mass, and y momentum exchanges between the oceans and the atmosphere, reducing the amount of solar radiation absorbed at the Earth's surface, affecting freshwater transports and ocean circulation, and serving as a vital surface for many species of polar animals. These direct impacts also lead to indirect impacts, including effects on local and perhaps global atmospheric temperatures, effects that are being examined in general circulation modeling studies, where preliminary results indicate that changes on the order of a few percent sea ice concentration can lead to temperature changes of 1 K or greater even in local areas outside of the sea ice region. Satellite passive-microwave data for November 1978 through December 1996 reveal marked regional and interannual variabilities in both the ice extents and the lengths of the sea ice season, as well as some statistically significant trends. For the north polar ice cover as a whole, maximum ice extents varied over a range of 14,700,000 - 15,900,000 km(2), while individual regions showed much greater percentage variations, e.g., with the Greenland Sea experiencing a range of 740,000 - 1,1110,000 km(2) in its yearly maximum ice coverage. Although variations from year to 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.

  14. 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.

  15. 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 lateral flow, following the gentle surface slope (< 1°) and undulated topography of the ice sheet surface toward the ablation zone of the ice sheet. The fate of this water is currently unknown; water drainage into crevasses and at least partial runoff is inferred based on the analysis of radar profiles from different years. I also present results from a field expedition in West Antarctica, where data collection combined high-frequency (2-18 GHz) radar data and shallow (< 20 m) firn cores from Central West Antarctica, crossing the ice divide toward the Amundsen Sea. The radar-derived accumulation rates show a 75% increase (+0.20 m w.eq. y-1) of net snow accumulation from the ice divide, toward the Amundsen Sea for a 70-km transect, assuming annual isochrones being detected in the radar profile. On the Ross Sea side of the divide, with accumulation rates less than 0.25 m w.eq. y-1 and significant wind redistribution, only a multi-annual stratigraphy is detected in the radar profile. Using radar, I investigated the small-scale variability within a radius of ˜1.5 km of one firn-core site, and I find that the averaged variation in accumulation-rate in this area is 0.1 m w.eq. y-1 in the upper 25-m of the firn column, which is 20% of the average accumulation rate.

  16. Greenland Ice Sheet response to mid-Pliocene summer Arctic sea ice-free conditions

    NASA Astrophysics Data System (ADS)

    Koenig, S. J.; DeConto, R.; Pollard, D.

    2011-12-01

    A critical uncertainty in future predictions of climate and sea level is the response of the cryosphere. Proxy reconstructions for the mid-Pliocene Arctic Ocean (~ 3 Ma) are indicative of summer Arctic ice-free conditions and higher than modern sea surface temperatures, conditions that are analogous to projections for the end of the 21st century. We implement available mid-Pliocene boundary conditions into a fully-coupled Global Circulation Model with interactive vegetation. We use a 3-D thermo-mechanical ice sheet-shelf model to simulate the equilibrated response of the Greenland Ice Sheet (GIS) to the combined effect of reduced sea ice conditions and increased sea surface temperatures during the mid-Pliocene Warm Period. Reductions in Arctic sea ice are shown to enhance ocean/land-to-atmosphere fluxes, increasing heat and moisture transport in the high latitudes. In particular, changes in the North Atlantic exert a strong influence on the storm track and seasonal temperatures and precipitation over Greenland. Despite increased precipitation, warmer temperatures generally reduce snow mass balance. As a result, an initial present-day ice sheet forced by Pliocene climate undergoes rapid melting, limiting the ice sheet to the only highest elevations in South and East Greenland. Once the ice sheet is lost, local surface characteristics and associated feedbacks dominates Greenland climate, precluding the regrowth of the ice sheet. Depending on the initial state of the ice sheet, the equilibrated ice sheet loss is equivalent to between 5.8 to 6.4 m of sea level. We assess the sensitivity of the GIS to Pliocene forcing and internal feedbacks, adding to the understanding of land-ice sea-ice hysteresis in a world warmer than today.

  17. 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.

  18. 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 record of temperature increases. Still, although the patterns of the temperature and ice changes match fairly well, there is a substantial ways to go before these patterns are understood (and can be modeled) in the full context of global change.

  19. ICESat Observations of Arctic Sea Ice: A First Look

    NASA Technical Reports Server (NTRS)

    Kwok, Ron; Zwally, H. Jay; Yi, Dong-Hui

    2004-01-01

    Analysis of near-coincident ICESat and RADARSAT imagery shows that the retrieved elevations from the laser altimeter are sensitive to new openings (containing thin ice or open water) in the sea ice cover as well as to surface relief of old and first-year ice. The precision of the elevation estimates, measured over relatively flat sea ice, is approx. 2 cm Using the thickness of thin-ice in recent openings to estimate sea level references, we obtain the sea-ice free-board along the altimeter tracks. This step is necessitated by the large uncertainties in the time-varying sea surface topography compared to that required for accurate determination of free-board. Unknown snow depth introduces the largest uncertainty in the conversion of free-board to ice thickness. Surface roughness is also derived, for the first time, from the variability of successive elevation estimates along the altimeter track Overall, these ICESat measurements provide an unprecedented view of the Arctic Ocean ice cover at length scales at and above the spatial dimension of the altimeter footprint.

  20. ICESat Observations of Arctic Sea Ice: A First Look

    NASA Technical Reports Server (NTRS)

    Kwok, Ron; Zwally, H. Jay; Yi, Donghui

    2004-01-01

    Analysis of near-coincident ICESat and RADARSAT imagery shows that the retrieved elevations from the laser altimeter are sensitive to new openings (containing thin ice or open water) in the sea ice cover as well as to surface relief of old and first-year ice. The precision of the elevation estimates, measured over relatively flat sea ice, is approx. 2 cm. Using the thickness of thin-ice in recent openings to estimate sea level references, we obtain the sea-ice freeboard along the altimeter tracks. This step is necessitated by the large uncertainties in the sea surface topography compared to that required for accurate determination of freeboard. Unknown snow depth introduces the largest uncertainty in the conversion of freeboard to ice thickness. Surface roughness is also derived, for the first time, from the variability of successive elevation estimates along the altimeter track. Overall, these ICESat measurements provide an unprecedented view of the Arctic Ocean ice cover at length scales at and above the spatial dimension of the altimeter footprint of approx. 70 m.

  1. Comparison of the MASIE with Other Sea Ice Extent Products

    NASA Astrophysics Data System (ADS)

    Helfrich, S.; Jackson, B. M.; Clemente-Colon, P.; Fetterer, F. M.; Savoie, M.

    2011-12-01

    The Multisensor Analyzed Sea Ice Extent (MASIE) has been made available to the public via the National Snow and Ice Data Center (NSIDC) since 2010, with daily data covering from January 2006 on. The MASIE is based on NOAA ice and snow cover analysis utilizing nearly 30 data sources to generate an integrated daily ice cover. While the resolution of the imagery sources ranges from 100m resolution synthetic aperture radar (SAR) to coarse 48km passive microwave (PM) data, the MASIE analysis attempts to synthesize the data sources into a 4km identification of sea-ice covered areas over the Northern Hemisphere. The MASIE differs from other ice extent data sources in three key ways. First, MASIE applies multiple data sources ranging from point sources and models to imagery acquired through a wide range in the electromagnetic spectrum. Second, MASIE has a moderate resolution so it is able to account relatively well for the ice extent in smaller bays, straits, coastlines, and along the marginal ice zone, particularly when compared to passive microwave sources. And third, MASIE relies on expert identification of the ice and manual assimilation of the multiple data sources rather than on a given automated algorithm. This study compares the MASIE with other sea extent products to understand their similarities and try to explain their differences. We analyze temporal and spatial behavior between ice extents from different products over the Northern Hemisphere, as well as within selected regions of interest. This comparison will help users in the interpretation of popular ice cover products and their applications in weather forecasting, ocean and ice modeling, safe navigation, and climate monitoring.

  2. The ability of CryoSat-2 to measure Antarctic sea ice freeboard

    NASA Astrophysics Data System (ADS)

    Price, Daniel; Rack, Wolfgang; Beckers, Justin; Ricker, Robert; Kurtz, Nathan; Haas, Christian; Helm, Veit; Hendricks, Stefan; Leonard, Greg; Langhorne, Pat

    2015-04-01

    Antarctic sea ice cover has been routinely monitored since 1979 but sea ice thickness remains one of the least understood physical components of the global cryosphere. Quantification of thickness is of crucial importance, since when combined with areal data it allows the computation of sea ice volume providing insight into the heat budget of the Antarctic sea ice system and quantification of freshwater and saltwater fluxes in the Southern Ocean. The use of satellite altimetry for sea ice thickness estimation relies on the measurement of freeboard. Thickness can then be estimated based on the assumptions of hydrostatic equilibrium given densities of snow, ice, water, and snow thickness are known. Using in situ data for 2011 and 2013 we evaluate the ability of CryoSat-2 (CS-2) to retrieve sea ice freeboard over fast-ice in McMurdo Sound. European Space Agency Level 2 data (ESAL2) is compared with results of a Waveform Fitting procedure (WfF) and a Threshold-First-Maximum-Retracker-Algorithm employed at 40% (TFMRA40). A supervised freeboard retrieval procedure is used to reduce errors associated with sea surface height identification and radar velocity in snow. We find ESAL2 freeboards located between the ice and snow freeboard rather than the frequently assumed snow-ice interface. WfF is within 0.04 m of the ice freeboard but is influenced by variable snow conditions causing increased radar backscatter from the air/snow interface; in such conditions a positive bias of 0.14 m away from the ice freeboard is observed. TFMRA40 freeboards are within 0.03 m of the snow freeboard. The difference in freeboard estimates is primarily driven by different retracker assumptions, although waveform alteration by variations in snow properties and surface roughness is evident. Techniques were amended where necessary and automatic freeboard retrieval procedures for ESAL2, WfF and TFMRA40 were developed. CS-2 detects annual fast-ice freeboard trends in McMurdo Sound using all three automatic procedures that are in line with known sea ice growth rates in the region. We present a systematic validation of CS-2 in the coastal Antarctic and provide insight into the assumptions currently used to process CS-2 data.

  3. Dual Frequency Radar Observations of Snow and Ice Properties: Esa's COREH2O Candidate Satellite Mission

    NASA Astrophysics Data System (ADS)

    Duguay, C.; Rott, H.; Cline, D. W.; Essery, R.; Etchevers, P.; Hajnsek, I.; Kern, M.; Macelloni, G.; Malnes, E.; Pulliainen, J. T.; Yueh, S. H.

    2012-12-01

    The satellite mission COld REgions Hydrology High-resolution Observatory (CoReH2O) is a candidate Earth Explorer mission within the Living Planet Programme of the European Space Agency. Detailed scientific and technical feasibility studies (Phase-A) for defining the satellite mission are going on. The mission will perform spatially detailed measurements of snow and ice in order to advance the modeling and prediction of water balance and streamflow in cold regions, and to improve the parameterization of snow and ice processes for climate models and numerical weather prediction. The primary snow and ice parameters to be delivered by the satellite are the area extent and mass (the water equivalent, SWE) of snow cover on land surfaces and the mass of winter snow accumulating on glaciers. In addition, the mission will make observations of various sea ice and lake ice parameters. The grid size of the final snow and ice products will vary between 200 m and 500 m, depending on the parameter and application. The sensor will be a dual-frequency dual-polarized SAR, operating at Ku-band (17.2 GHz) and X-band (9.6 GHz), VV and VH polarizations, with a swath width of about 100 km. Two mission phases with different repeat cycles and coverage are proposed. During the first two years a three-day repeat cycle is planned providing frequent repeat coverage over limited areas, in order to match the time scale of meteorological forcing by typical mid- and high-latitude weather systems. This orbit addresses in particular the parameterization of snow and ice processes in hydrological models and mesoscale atmospheric circulation models. The second mission phase shall deliver near complete observations of the global snow and ice areas at a repeat cycle of 12 to 15 days. Primary motivations for this phase are the validation of continental-scale hydrological models and climate models, and the development of downscaling techniques for coarse resolution satellite snow measurements. A processing line for mapping snow extent and retrieving SWE has been developed and tested with simulated and experimental data. The performance of the retrieval algorithm has been tested with simulated and experimental data for wide range of conditions for snow packs and background targets. The retrieval algorithm has also been tested with data from field campaigns in Finland, Canada and Alaska, employing backscatter measurements made by ground-based scatterometers and airborne sensors. Retrievals of SWE with the experimental data are within the benchmarks for quality of SWE products specified by the scientific community. Retrievals with simulated data show on average good results, but problems for compliance are emerging under certain target conditions such as snow cover in forested areas. Measures to improve the performance in these cases are being investigated, for example by relaxing the product size from 200 m to 500 m.

  4. Export of algal biomass from the melting Arctic sea ice.

    PubMed

    Boetius, Antje; Albrecht, Sebastian; Bakker, Karel; Bienhold, Christina; Felden, Janine; Fernández-Méndez, Mar; Hendricks, Stefan; Katlein, Christian; Lalande, Catherine; Krumpen, Thomas; Nicolaus, Marcel; Peeken, Ilka; Rabe, Benjamin; Rogacheva, Antonina; Rybakova, Elena; Somavilla, Raquel; Wenzhöfer, Frank

    2013-03-22

    In the Arctic, under-ice primary production is limited to summer months and is restricted not only by ice thickness and snow cover but also by the stratification of the water column, which constrains nutrient supply for algal growth. Research Vessel Polarstern visited the ice-covered eastern-central basins between 82° to 89°N and 30° to 130°E in summer 2012, when Arctic sea ice declined to a record minimum. During this cruise, we observed a widespread deposition of ice algal biomass of on average 9 grams of carbon per square meter to the deep-sea floor of the central Arctic basins. Data from this cruise will contribute to assessing the effect of current climate change on Arctic productivity, biodiversity, and ecological function. PMID:23413190

  5. March 2003 EOS Aqua AMSR-E Arctic Sea Ice Field Campaign

    NASA Technical Reports Server (NTRS)

    Cavalieri, Donald J.; Markus, Thorsten; Maslanik, James A.; Sturm, Matthew; Lobl, Elena

    2006-01-01

    An overview of the March 2003 coordinated sea ice field campaign in the Alaskan Arctic is presented with reference to the papers in this special section. This campaign is part of the program to validate the Aqua Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) sea ice products. Standard AMSR-E sea ice products include sea ice concentration, sea ice temperature, and snow depth on sea ice. The validation program consists of three elements, namely: 1) satellite data comparisons; 2) coordinated satellite/aircraft surface measurements; and 3) modeling and sensitivity analyses. Landsat-7 and RADARSAT observations were used in comparative studies with the retrieved AMSR-E sea ice concentrations. The aircraft sensors provided high-resolution microwave imagery of the surface, atmospheric profiles of temperature and humidity, and digital records of sea ice conditions. When combined with in situ measurements, aircraft data were used to validate the AMSR-E sea ice temperature and snow-depth products. The modeling studies helped interpret the field-data comparisons, provided insight on the limitations of the AMSR-E sea ice algorithms, and suggested potential improvements to the AMSR-E retrieval algorithms.

  6. Annual sea ice. An air-sea gas exchange moderator

    SciTech Connect

    Gosink, T.A.; Kelley, J.J.

    1982-01-01

    Arctic annual sea ice, particularly when it is relatively warm (> -15/sup 0/C) permits significant gas exchange between the sea and air throughout the entire year. Sea ice, particularly annual sea ice, differs from freshwater ice with respect to its permeability to gases. The presence of brine allows for significant air-sea-ice exchange of CO/sub 2/ throughout the winter, which may significantly affect the global carbon dioxide balance. Other trace gases are also noted to be enriched in sea ice, but less is known about their importance to air-sea-interactions at this time. Both physical and biological factors cause and modify evolution of gases from the surface of sea ice. Quantitative and qualitative descriptions of the nature and physical behavior of sea ice with respect to brine and gases are discussed.

  7. Perennial snow and ice volumes on Iliamna Volcano, Alaska, estimated with ice radar and volume modeling

    USGS Publications Warehouse

    Trabant, Dennis C.

    1999-01-01

    The volume of four of the largest glaciers on Iliamna Volcano was estimated using the volume model developed for evaluating glacier volumes on Redoubt Volcano. The volume model is controlled by simulated valley cross sections that are constructed by fitting third-order polynomials to the shape of the valley walls exposed above the glacier surface. Critical cross sections were field checked by sounding with ice-penetrating radar during July 1998. The estimated volumes of perennial snow and glacier ice for Tuxedni, Lateral, Red, and Umbrella Glaciers are 8.6, 0.85, 4.7, and 0.60 cubic kilometers respectively. The estimated volume of snow and ice on the upper 1,000 meters of the volcano is about 1 cubic kilometer. The volume estimates are thought to have errors of no more than ?25 percent. The volumes estimated for the four largest glaciers are more than three times the total volume of snow and ice on Mount Rainier and about 82 times the total volume of snow and ice that was on Mount St. Helens before its May 18, 1980 eruption. Volcanoes mantled by substantial snow and ice covers have produced the largest and most catastrophic lahars and floods. Therefore, it is prudent to expect that, during an eruptive episode, flooding and lahars threaten all of the drainages heading on Iliamna Volcano. On the other hand, debris avalanches can happen any time. Fortunately, their influence is generally limited to the area within a few kilometers of the summit.

  8. A mechanism for biologically induced iodine emissions from sea ice

    NASA Astrophysics Data System (ADS)

    Saiz-Lopez, A.; Blaszczak-Boxe, C. S.; Carpenter, L. J.

    2015-09-01

    Ground- and satellite-based measurements have reported high concentrations of iodine monoxide (IO) in coastal Antarctica. The sources of such a large iodine burden in the coastal Antarctic atmosphere remain unknown. We propose a mechanism for iodine release from sea ice based on the premise that micro-algae are the primary source of iodine emissions in this environment. The emissions are triggered by the biological production of iodide (I-) and hypoiodous acid (HOI) from micro-algae (contained within and underneath sea ice) and their diffusion through sea-ice brine channels, ultimately accumulating in a thin brine layer (BL) on the surface of sea ice. Prior to reaching the BL, the diffusion timescale of iodine within sea ice is depth-dependent. The BL is also a vital component of the proposed mechanism as it enhances the chemical kinetics of iodine-related reactions, which allows for the efficient release of iodine to the polar boundary layer. We suggest that iodine is released to the atmosphere via three possible pathways: (1) emitted from the BL and then transported throughout snow atop sea ice, from where it is released to the atmosphere; (2) released directly from the BL to the atmosphere in regions of sea ice that are not covered with snowpack; or (3) emitted to the atmosphere directly through fractures in the sea-ice pack. To investigate the proposed biology-ice-atmosphere coupling at coastal Antarctica we use a multiphase model that incorporates the transport of iodine species, via diffusion, at variable depths, within brine channels of sea ice. Model simulations were conducted to interpret observations of elevated springtime IO in the coastal Antarctic, around the Weddell Sea. While a lack of experimental and observational data adds uncertainty to the model predictions, the results nevertheless show that the levels of inorganic iodine (i.e. I2, IBr, ICl) released from sea ice through this mechanism could account for the observed IO concentrations during this timeframe. The model results also indicate that iodine may trigger the catalytic release of bromine from sea ice through phase equilibration of IBr. Considering the extent of sea ice around the Antarctic continent, we suggest that the resulting high levels of iodine may have widespread impacts on catalytic ozone destruction and aerosol formation in the Antarctic lower troposphere.

  9. Microstructural Considerations of Transporting Sea Ice Samples from Polar Regions

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

    High latitude regions are at the forefront of climate change research as these regions have and will experience the greatest impact due to changing environmental conditions (e.g. Antarctic and recent Arctic stratospheric ozone holes, large temperature increases on the Antarctic Peninsula, changes in the extent and age of Arctic sea ice). One of the major challenges of polar scientific research is the preservation of frozen sea ice samples during their transport back to the laboratory and subsequent storage. Small fluctuations in temperature have been shown to have a significant effect on the microstructure of snow and ice samples. This is especially true for sea ice specimens where transport and storage temperatures are often only slightly below the eutectic point for its different constituents (i.e. salts). Furthermore, sea ice can have a 30 deg C in situ vertical temperature gradient that is lost during transport and storage. Sea ice plays a critical role in mediating the exchange of heat, gases, and chemical species across the ocean-atmosphere interface. The kinetics of these exchanges is highly dependent upon the brine channel microstructure, which is strongly coupled to temperature. To determine the degree of microstructural variation between samples shipped at different temperatures, ten samples of a single sea ice core collected in March 2012 were transported from Barrow, Alaska to Hanover, NH using two common techniques: with blue ice packs enclosed in a Styrofoam box (~ -25 deg C) and in a dry liquid nitrogen cryoshipper (~ -182 deg C). In addition, snow lying on the sea ice and blowing snow samples were collected and shipped via both techniques. All samples were then stored for analysis in a cold room maintained at ~ -33 deg C. The microstructure of both sets of samples was analyzed using x-ray micro-computed tomography (μ-CT), with samples on a Peltier cold stage to maintain a scanning temperature of -20 deg C. We compare sea ice porosity and brine channel morphology between the samples shipped at -25 deg C and those from the same core depth shipped at -182 deg C. This work informed the transport and analysis of our samples collected in Antarctica in October - November 2012.

  10. Atmospheric mercury over sea ice during the OASIS-2009 campaign

    NASA Astrophysics Data System (ADS)

    Steffen, A.; Bottenheim, J.; Cole, A.; Douglas, T. A.; Ebinghaus, R.; Friess, U.; Netcheva, S.; Nghiem, S.; Sihler, H.; Staebler, R.

    2013-07-01

    Measurements of gaseous elemental mercury (GEM), reactive gaseous mercury (RGM) and particulate mercury (PHg) were collected on the Beaufort Sea ice near Barrow, Alaska, in March 2009 as part of the Ocean-Atmosphere-Sea Ice-Snowpack (OASIS) and OASIS-Canada International Polar Year programmes. These results represent the first atmospheric mercury speciation measurements collected on the sea ice. Concentrations of PHg averaged 393.5 pg m-3 (range 47.1-900.1 pg m-3) and RGM concentrations averaged 30.1 pg m-3 (range 3.5-105.4 pg m-3) during the two-week-long study. The mean concentration of GEM during the study was 0.59 ng m-3 (range 0.01-1.51 ng m-3) and was depleted compared to annual Arctic ambient boundary layer concentrations. It is shown that when ozone (O3) and bromine oxide (BrO) chemistry were active there is a positive linear relationship between GEM and O3, a negative one between PHg and O3, a positive correlation between RGM and BrO, and none between RGM and O3. For the first time, GEM was measured simultaneously over the tundra and the sea ice. The results show a significant difference in the magnitude of the emission of GEM from the two locations, with significantly higher emission over the tundra. Elevated chloride levels in snow over sea ice are proposed to be the cause of lower GEM emissions over the sea ice because chloride has been shown to suppress photoreduction processes of RGM to GEM in snow. Since the snowpack on sea ice retains more mercury than inland snow, current models of the Arctic mercury cycle may greatly underestimate atmospheric deposition fluxes because they are based predominantly on land-based measurements. Land-based measurements of atmospheric mercury deposition may also underestimate the impacts of sea ice changes on the mercury cycle in the Arctic. The predicted changes in sea ice conditions and a more saline future snowpack in the Arctic could enhance retention of atmospherically deposited mercury and increase the amount of mercury entering the Arctic Ocean and coastal ecosystems.

  11. Distribution and biomass transport of ice amphipods in drifting sea ice around Svalbard

    NASA Astrophysics Data System (ADS)

    Hop, Haakon; Pavlova, Olga

    2008-10-01

    Diversity and distribution of ice amphipods were determined in drifting sea ice around Svalbard during May-August 2003-2005. Sea-ice concentrations were determined visually and by satellite recordings. Backward trajectories for ice drift, based on satellite observations, indicated that multi-year ice in the area had originated 3-5 years earlier in the Kara Sea and western Laptev Sea, whereas some of the younger ice (1-2 years) may have originated in Franz Josef Land area. Quantitative collections of ice amphipods were obtained by SCUBA divers from flat areas and ridges below sea ice. The abundance and biomass were generally higher on ridges, particularly for the large Gammarus wilkitzkii, whereas Apherusa glacialis was more abundant on flat areas. Abundance and biomass varied among seasons (May-August) and years, with low values in May and higher values in July. The high values were similar to abundance and biomass values from July 1996. Redundancy analysis showed that 33% and 52% of the variability in respective species abundance and biomass could be explained by environmental variables, with ice draft and snow cover being the most important. The overall mean biomass for flats (0.30±0.05 g m -2) and ridges (1.64+0.46 g m -2) were used to calculate ice-associated biomass transport based on revised mean annual ice flux through Fram Strait (662,000 km 2 yr -1) and into the Barents Sea (total 228,000 km 2 yr -1). About 478×10 3 t WW (57×10 3 t C) of ice amphipods are transported annually through Fram Strait and 194×10 3 t WW (23×10 3 t C) into the northern Barents Sea, implying that 71% of the amphipod biomass in drifting sea ice passes through Fram Strait and 29% enters the Barents Sea. Climate induced reduction in ice thickness and extent will likely decrease this southward biomass transport, and thus the current carbon input of about 80×10 3 t C yr -1 into these marginal seas. Ice amphipod populations probably cannot be sustained if the summers become ice free in the Arctic Ocean, and particularly reduction of multi-year ice in the Arctic Ocean will affect long-lived species such as Gammarus wilkitzkii.

  12. Improved Upper Ocean/Sea Ice Modeling in the GISS GCM for Investigating Climate Change

    NASA Technical Reports Server (NTRS)

    1997-01-01

    This project built on our previous results in which we highlighted the importance of sea ice in overall climate sensitivity by determining that for both warming and cooling climates, when sea ice was not allowed to change, climate sensitivity was reduced by 35-40%. We also modified the Goddard Institute for Space Studies (GISS) 8 deg x lO deg atmospheric General Circulation Model (GCM) to include an upper-ocean/sea-ice model involving the Semtner three-layer ice/snow thermodynamic model, the Price et al. (1986) ocean mixed layer model and a general upper ocean vertical advection/diffusion scheme for maintaining and fluxing properties across the pycnocline. This effort, in addition to improving the sea ice representation in the AGCM, revealed a number of sensitive components of the sea ice/ocean system. For example, the ability to flux heat through the ice/snow properly is critical in order to resolve the surface temperature properly, since small errors in this lead to unrestrained climate drift. The present project, summarized in this report, had as its objectives: (1) introducing a series of sea ice and ocean improvements aimed at overcoming remaining weaknesses in the GCM sea ice/ocean representation, and (2) performing a series of sensitivity experiments designed to evaluate the climate sensitivity of the revised model to both Antarctic and Arctic sea ice, determine the sensitivity of the climate response to initial ice distribution, and investigate the transient response to doubling CO2.

  13. Improved Upper Ocean/Sea Ice Modeling in the GISS GCM for Investigating Climate Change

    NASA Technical Reports Server (NTRS)

    1998-01-01

    This project built on our previous results in which we highlighted the importance of sea ice in overall climate sensitivity by determining that for both warming and cooling climates, when sea ice was not allowed to change, climate sensitivity was reduced by 35-40%. We also modified the GISS 8 deg x lO deg atmospheric GCM to include an upper-ocean/sea-ice model involving the Semtner three-layer ice/snow thermodynamic model, the Price et al. (1986) ocean mixed layer model and a general upper ocean vertical advection/diffusion scheme for maintaining and fluxing properties across the pycnocline. This effort, in addition to improving the sea ice representation in the AGCM, revealed a number of sensitive components of the sea ice/ocean system. For example, the ability to flux heat through the ice/snow properly is critical in order to resolve the surface temperature properly, since small errors in this lead to unrestrained climate drift. The present project, summarized in this report, had as its objectives: (1) introducing a series of sea ice and ocean improvements aimed at overcoming remaining weaknesses in the GCM sea ice/ocean representation, and (2) performing a series of sensitivity experiments designed to evaluate the climate sensitivity of the revised model to both Antarctic and Arctic sea ice, determine the sensitivity of the climate response to initial ice distribution, and investigate the transient response to doubling CO2.

  14. An inter-sensor comparison of the microwave signatures of Arctic sea ice

    NASA Technical Reports Server (NTRS)

    Onstott, R. G.

    1986-01-01

    Active and passive microwave and physical properties of Arctic sea ice in the marginal ice zone were measured during the summer. Results of an intercomparison of data acquired by an aircraft synthetic aperture radar, a passive microwave imager and a helicopter-mounted scatterometer indicate that early-to-mid summer sea ice microwave signatures are dominated by snowpack characteristics. Measurements show that the greatest contrast between thin first-year and multiyear sea ice occurs when operating actively between 5 and 10 GHz. Significant information about the state of melt of snow and ice is contained in the active and passive microwave signatures.

  15. Albedo of coastal landfast sea ice in Prydz Bay, Antarctica: Observations and parameterization

    NASA Astrophysics Data System (ADS)

    Yang, Qinghua; Liu, Jiping; Leppäranta, Matti; Sun, Qizhen; Li, Rongbin; Zhang, Lin; Jung, Thomas; Lei, Ruibo; Zhang, Zhanhai; Li, Ming; Zhao, Jiechen; Cheng, Jingjing

    2016-05-01

    The snow/sea-ice albedo was measured over coastal landfast sea ice in Prydz Bay, East Antarctica (off Zhongshan Station) during the austral spring and summer of 2010 and 2011. The variation of the observed albedo was a combination of a gradual seasonal transition from spring to summer and abrupt changes resulting from synoptic events, including snowfall, blowing snow, and overcast skies. The measured albedo ranged from 0.94 over thick fresh snow to 0.36 over melting sea ice. It was found that snow thickness was the most important factor influencing the albedo variation, while synoptic events and overcast skies could increase the albedo by about 0.18 and 0.06, respectively. The in-situ measured albedo and related physical parameters (e.g., snow thickness, ice thickness, surface temperature, and air temperature) were then used to evaluate four different snow/ice albedo parameterizations used in a variety of climate models. The parameterized albedos showed substantial discrepancies compared to the observed albedo, particularly during the summer melt period, even though more complex parameterizations yielded more realistic variations than simple ones. A modified parameterization was developed, which further considered synoptic events, cloud cover, and the local landfast sea-ice surface characteristics. The resulting parameterized albedo showed very good agreement with the observed albedo.

  16. Search for proxy indicators of young sea ice thickness

    NASA Astrophysics Data System (ADS)

    Zabel, I. H. H.; Jezek, K. C.; Gogineni, S. P.; Kanagaratnam, P.

    1996-03-01

    The determination of young sea ice thickness from space remains an elusive goal for those interested in the interaction of the oceans and the atmosphere, the thermal and chemical state of the ocean, and sea ice dynamics. Recent experiments and models have shown relationships between active and passive microwave signatures of new, growing ice and ice thickness. The two processes that dominate in determining the microwave signature are changes in dielectric properties and changes in surface roughness. In this paper we investigate the competition between these two processes in determining radar backscatter, the usefulness of surface roughness as an indicator of young ice thickness, and the optimum sensor parameters for observing changes in scattering linked to ice thickness. We present simulations that are based on radar observations made on laboratory-grown saline ice. These observations confirm that surface scattering dominates over volume scattering for 13.9 GHz radar backscatter from young, rough ice at most angles and for young, smooth ice below 30°. Although rms roughness and backscatter (at 5.3 and 13.9 GHz, 23° incidence, and VV polarization) increase together after about 10 cm of ice growth under quiet conditions, it is unlikely that surface roughness and ice thickness are simply connected in real sea ice, where surface roughness can change rapidly due to the action of wind, waves, and snow. Simulations show, however, that formation of frost flowers is detectable by spaceborne radar and can serve to classify ice of roughly 5-20 cm thickness since it is a distinct, transient event that occurs under physical conditions that constrain the thickness of the ice. Our experimental data show that future sensors operating near 12° incidence may offer potential for probing the relationship between near-surface dielectric properties and ice thickness, since the effects of variability in roughness and snowfall are minimized near this angle.

  17. A physical algorithm to measure sea ice concentration from passive microwave remote sensing data

    NASA Astrophysics Data System (ADS)

    Tikhonov, V. V.; Repina, I. A.; Raev, M. D.; Sharkov, E. A.; Ivanov, V. V.; Boyarskii, D. A.; Alexeeva, T. A.; Komarova, N. Yu.

    2015-10-01

    A conceptually new algorithm of sea ice concentration retrieval in polar regions from satellite microwave radiometry data is discussed. The algorithm design favorably contrasts with that of known modern algorithms. Its design is based on a physical emission model of the "sea surface - sea ice - snow cover - atmosphere" system. No tie-points are used in the algorithm. All the calculation expressions are derived from theoretical modeling. The design of the algorithm minimizes the impact of atmospheric variability on sea ice concentration retrieval. Beside estimating sea ice concentration, the algorithm makes it possible to indicate ice areas with melting snow and melt ponds. The algorithm is simple to use, no complicated or time consuming calculations are involved.

  18. The Sea Ice Board Game

    ERIC Educational Resources Information Center

    Bertram, Kathryn Berry

    2008-01-01

    The National Science Foundation-funded Arctic Climate Modeling Program (ACMP) provides "curriculum resource-based professional development" materials that combine current science information with practical classroom instruction embedded with "best practice" techniques for teaching science to diverse students. The Sea Ice Board Game, described…

  19. Surveying Arctic Sea Ice

    Two U.S. Coast Guard members are being transported by crane from U.S. Coast Guard Cutter Healy onto a piece of multi-year ice. This was during a scientific expedition to map the Arctic seafloor. The expedition was a joint effort using two ships, Healy and the Canadian Coast Guard Ship Louis S. St. L...

  20. Loss of sea ice in the Arctic.

    PubMed

    Perovich, Donald K; Richter-Menge, Jacqueline A

    2009-01-01

    The Arctic sea ice cover is in decline. The areal extent of the ice cover has been decreasing for the past few decades at an accelerating rate. Evidence also points to a decrease in sea ice thickness and a reduction in the amount of thicker perennial sea ice. A general global warming trend has made the ice cover more vulnerable to natural fluctuations in atmospheric and oceanic forcing. The observed reduction in Arctic sea ice is a consequence of both thermodynamic and dynamic processes, including such factors as preconditioning of the ice cover, overall warming trends, changes in cloud coverage, shifts in atmospheric circulation patterns, increased export of older ice out of the Arctic, advection of ocean heat from the Pacific and North Atlantic, enhanced solar heating of the ocean, and the ice-albedo feedback. The diminishing Arctic sea ice is creating social, political, economic, and ecological challenges. PMID:21141043

  1. 30 CFR 57.11016 - 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. 57... MINES Travelways and Escapeways Travelways-Surface and Underground § 57.11016 Snow and ice on walkways and travelways. Regularly used walkways and travelways shall be sanded, salted, or cleared of snow...

  2. 30 CFR 57.11016 - 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. 57... MINES Travelways and Escapeways Travelways-Surface and Underground § 57.11016 Snow and ice on walkways and travelways. Regularly used walkways and travelways shall be sanded, salted, or cleared of snow...

  3. 30 CFR 57.11016 - 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. 57... MINES Travelways and Escapeways Travelways-Surface and Underground § 57.11016 Snow and ice on walkways and travelways. Regularly used walkways and travelways shall be sanded, salted, or cleared of snow...

  4. 30 CFR 57.11016 - 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. 57... MINES Travelways and Escapeways Travelways-Surface and Underground § 57.11016 Snow and ice on walkways and travelways. Regularly used walkways and travelways shall be sanded, salted, or cleared of snow...

  5. 30 CFR 57.11016 - 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. 57... MINES Travelways and Escapeways Travelways-Surface and Underground § 57.11016 Snow and ice on walkways and travelways. Regularly used walkways and travelways shall be sanded, salted, or cleared of snow...

  6. Sea Ice Entrainment and Sediment Sources

    NASA Astrophysics Data System (ADS)

    Miles, S.; Darby, D. A.; Jakobsson, M.; Rigor, I.

    2007-12-01

    More than 20 sea ice sediment samples collected during the Healy-Oden Trans-Arctic Expedition (HOTRAX-'05) and the Lomonosov Ridge off Greenland Expedition (LOMROG-'07) along with 18 dirty ice samples from previous expeditions back to the early 1970's show a consistent trend of several sources especially the Laptev and Kara Seas and northern Canada. Modern sea ice back-trajectories from the coordinates of the dirty sea ice samples using past drifts of this ice from the International Buoy Drift Program indicate a close match to the Fe grain sources. Comparison with several sediment cores from across the Arctic and in Fram Strait indicate that Holocene sediment that is primarily transported by sea ice contains the same sources based on Fe oxide grain chemical fingerprint matches with circum-Arctic source areas previously characterized. Observations of encounters with dirty ice by HOTRAX and LOMROG icebreaker expeditions indicate that while a small percentage of sea ice contains sediment, this dirty ice is concentrated in bands extending several kilometers and consisting of irregularly spaced patches of dirty ice that are usually less than a 100 meters in width. Also, sea ice containing coarse sediment and/or large shells due to anchor ice are less than 10 percent of dirty sea ice but that they may contain much higher concentrations of sediment than sea ice containing finer sediment from suspension freezing.

  7. Validation of EOS Aqua AMSR Sea Ice Products for East Antarctica

    NASA Technical Reports Server (NTRS)

    Massom, Rob; Lytle, Vicky; Allison, Ian; Worby, Tony; Markus, Thorsten; Scambos, Ted; Haran, Terry; Enomoto, Hiro; Tateyama, Kazu; Pfaffling, Andi

    2004-01-01

    This paper presents results from AMSR-E validation activities during a collaborative international cruise onboard the RV Aurora Australis to the East Antarctic sea ice zone (64-65 deg.S, 110-120 deg.E) in the early Austral spring of 2003. The validation strategy entailed an IS-day survey of the statistical characteristics of sea ice and snowcover over a Lagrangian grid 100 x 50 km in size (demarcated by 9 drifting ice beacons) i.e. at a scale representative of Ah4SR pixels. Ice conditions ranged h m consolidated first-year ice to a large polynya offshore from Casey Base. Data sets collected include: snow depth and snow-ice interface temperatures on 24 (?) randomly-selected floes in grid cells within a 10 x 50 km area (using helicopters); detailed snow and ice measurements at 13 dedicated ice stations, one of which lasted for 4 days; time-series measurements of snow temperature and thickness at selected sites; 8 aerial photography and thermal-IR radiometer flights; other satellite products (SAR, AVHRR, MODIS, MISR, ASTER and Envisat MERIS); ice drift data; and ancillary meteorological (ship-based, meteorological buoys, twice-daily radiosondes). These data are applied to a validation of standard AMSR-E ice concentration, snowcover thickness and ice-temperature products. In addition, a validation is carried out of ice-surface skin temperature products h m the NOAA AVHRR and EOS MODIS datasets.

  8. Epidemic of fractures during period of snow and ice.

    PubMed

    Rális, Z A

    1981-02-21

    During four days of snow and ice in which more than 70% of pavements in the Cardiff area were covered by slippery hard snow and ice the number of patients who attended the accident and emergency department at this hospital with fractured bones increased 2.85 times as compared with those who attended during four control days with comparable hours of sunshine and four control calendar days a year later. Fractures of the arm were increased 3.7 times and of the forearm and wrist 7.3 times. For a town population of one million people who may walk on untreated slippery and icy pavements this means that on average in a single day 74 more people than usual sustain a fracture unnecessarily. This traumatic epidemic has all the characteristics of a "major accident" and should be treated as such, since mobilisation of additional facilities, staff, and reserves might be necessary. Snow and ice injuries, however, differ from injuries sustained in a major accident in one important point: they may be predicted and prevented. The mass media should warn the population about the oncoming hazards and give practical advice on safer walking on slippery surfaces. The most important aspect of prevention, however, is instant cleaning of pavements around buildings, shops, and houses, especially in town centres and other areas busy with pedestrians. PMID:6781587

  9. The U.S. Navy's Emerging Sea Ice Prediction Capabilities

    NASA Astrophysics Data System (ADS)

    Allard, Richard; Campbell, Tim; Hebert, David; Metzger, E. Joseph; Posey, Pamela; Wallcraft, Alan; Smedstad, Ole Martin; Gaberšek, Saša; Jin, Yi; Wang, Shouping

    2014-05-01

    The U.S. Navy's regional and global coupled sea ice modeling activities are described. The Arctic Cap Nowcast Forecast System (ACNFS) is a 3.5 km coupled sea ice-ocean model that produces 7 day forecasts of the Arctic sea ice state in all ice covered areas in the northern hemisphere (poleward of 40°N). The ocean component is the HYbrid Coordinate Ocean Model (HYCOM) and is coupled to the Los Alamos National Laboratory Community Ice CodE (CICE) via the Earth System Modeling Framework (ESMF). The ocean and sea ice models are run in an assimilative cycle with the Navy's Coupled Ocean Data Assimilation (NCODA) system. The ACNFS was transitioned to operations at the Naval Oceanographic Office in 2013 to serve its customer, the National Ice Center. The Global Ocean forecast System (GOFS3.1) is essentially an extension of ACNFS to the globe at 1/12° (equatorial) resolution, still 3.5 km in the Arctic, and it will provide sea ice predictions for the Arctic and Antarctic. Testing and validation is underway and an operational transition is planned for 2015, when GOFS3.1 will replace the ACNFS. A relocatable regional capability is being developed by coupling CICE to the Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS). This new system will have an advanced snow-ice albedo representation and produce coupled forecasts out to 7-10 days with resolutions for the atmosphere and sea ice models at 1-3 km. Examples of these emerging capabilities will be presented.

  10. Temporal evolution of decaying summer first-year sea ice in the Western Weddell Sea, Antarctica

    NASA Astrophysics Data System (ADS)

    Tison, J.-L.; Worby, A.; Delille, B.; Brabant, F.; Papadimitriou, S.; Thomas, D.; de Jong, J.; Lannuzel, D.; Haas, C.

    2008-04-01

    The evolution of the main physico-chemical properties of the unflooded 90-cm-thick first-year sea-ice cover at the Ice Station POLarstern (ISPOL) "clean site" is described. ISPOL was an international experiment of the German research icebreaker R.V. Polarstern. The vessel was anchored to an ice floe for an observation period of 5 weeks, during the early summer melt onset in the Western Weddell Sea. The "clean site" was specially designed and accessed so as to prevent any trace metal contamination of the sampling area. Observations were made at 5-day intervals during December 2004 in the central part of the main floe. Results show the succession of two contrasting phases in the behavior of the brine network (brine channels, pockets, and tubes). Initially, brine salinity was higher than that of sea-water, leading to brine migration and a decrease in the mean bulk salinity of the ice cover. This process is highly favored by the already high bulk porosity (14%), which ensures full connectivity of the brine network. Gravity drainage rather than convection seems to be the dominant brine transfer process. Half-way through the observation period, the brine salinity became lower than that of the sea-water throughout the ice column. The brine network therefore switched to a "stratified" regime in which exchange with sea-water was limited to molecular diffusion, strongly stabilizing the bulk mean sea-ice salinity. During the transition between the two regimes, and in areas closer to ridges, slush water (resulting from a mixture of snow meltwater and sea water accumulated at the snow-ice interface) penetrated through the growing "honeycomb-like structure" and replaced the downward draining brines. This resulted in a slight local replenishment of nutrients (as indicated by dissolved silicic acid). However, as a whole, the described decaying regime in this globally unflooded location with limited snow cover should be unfavorable to the development of healthy and active surface and internal microbial communities. The switch from gravity to diffusion controlled transport mechanisms within the ice column also should affect the efficiency of gas exchange across the sea-ice cover. The observed late build-up of a continuous, impermeable, superimposed ice layer should further significantly hamper gas exchange. Statistical estimates of the evolution of the ice thickness during the observation period and salinity trends of the under-ice water salinity down to 30 m corroborate model predictions of a moderate bottom melting (5-10 cm) from ocean heat fluxes.

  11. Finite-Element Sea Ice Model (FESIM), version 2

    NASA Astrophysics Data System (ADS)

    Danilov, S.; Wang, Q.; Timmermann, R.; Iakovlev, N.; Sidorenko, D.; Kimmritz, M.; Jung, T.; Schröter, J.

    2015-02-01

    The Finite-Element Sea-Ice Model, used as a component of the Finite-Element Sea ice Ocean Model, is presented. Version 2 includes the elastic-viscous-plastic (EVP) and viscous-plastic (VP) solvers and employs a flux corrected transport algorithm to advect the ice and snow mean thicknesses and concentration. The EVP part also includes a modified approach proposed recently by Bouillon et al., which is characterized by an improved stability compared to the standard EVP approach. The model is formulated on unstructured triangular meshes. It assumes a collocated placement of ice velocities, mean thicknesses and concentration at mesh vertices, and relies on a piecewise-linear (P1) continuous elements. Simple tests for the modified EVP and VP solvers are presented to show that they may produce very close results provided the number of iterations is sufficiently high.

  12. Finite-Element Sea Ice Model (FESIM), version 2

    NASA Astrophysics Data System (ADS)

    Danilov, S.; Wang, Q.; Timmermann, R.; Iakovlev, N.; Sidorenko, D.; Kimmritz, M.; Jung, T.; Schröter, J.

    2015-06-01

    The Finite-Element Sea Ice Model (FESIM), used as a component of the Finite-Element Sea ice Ocean Model, is presented. Version 2 includes the elastic-viscous-plastic (EVP) and viscous-plastic (VP) solvers and employs a flux corrected transport algorithm to advect the ice and snow mean thicknesses and concentration. The EVP part also includes a modified approach proposed recently by Bouillon et al. (2013), which is characterized by an improved stability compared to the standard EVP approach. The model is formulated on unstructured triangular meshes. It assumes a collocated placement of ice velocities, mean thicknesses and concentration at mesh vertices, and relies on piecewise-linear (P1) continuous elements. Simple tests for the modified EVP and VP solvers are presented to show that they may produce very close results provided the number of iterations is sufficiently high.

  13. Skillful prediction of Barents Sea ice cover

    NASA Astrophysics Data System (ADS)

    Onarheim, Ingrid H.; Eldevik, Tor; Årthun, Marius; Ingvaldsen, Randi B.; Smedsrud, Lars H.

    2015-07-01

    A main concern of present climate change is the Arctic sea ice cover. In wintertime, its observed variability is largely carried by the Barents Sea. Here we propose and evaluate a simple quantitative and prognostic framework based on first principles and rooted in observations to predict the annual mean Barents Sea ice cover, which variance is carried by the winter ice (96%). By using observed ocean heat transport and sea ice area, the proposed framework appears skillful and explains 50% of the observed sea ice variance up to 2 years in advance. The qualitative prediction of increase versus decrease in ice cover is correct 88% of the time. Model imperfections can largely be diagnosed from simultaneous meridional winds. The framework and skill are supported by a 60 year simulation from a regional ice-ocean model. We particularly predict that the winter sea ice cover for 2016 will be slightly less than 2015.

  14. Antarctic sea ice mapping using the AVHRR

    SciTech Connect

    Zibordi, G. ); Van Woert, M.L. . SeaSpace, Inc.)

    1993-08-01

    A sea ice mapping scheme based on Advanced Very High Resolution Radiometer (AVHRR) data from the National Oceanic and Atmospheric Administration (NOAA) polar orbiting satellites has been developed and applied to daylight images taken between November 1989 to January 1990 and November 1990 to January 1991 over the Weddell and the Ross Seas. After masking the continent and ice shelves, sea ice is discriminated from clouds and open sea using thresholds applied to the multidimensional space formed by AVHRR Channel 2, 3, and 4 radiances. Sea ice concentrations in cloud-free regions are then computed using the tie-point method. Results based on the analysis of more than 70 images show that the proposed scheme is capable of properly discriminating between sea ice, open sea, and clouds, under most conditions, thus allowing high resolution sea ice maps to be produced during the austral summer season.

  15. Microwave signatures of snow, ice and soil at several wavelengths

    NASA Technical Reports Server (NTRS)

    Gloersen, P.; Schmugge, T. J.; Chang, T. C.

    1974-01-01

    Analyses of data obtained from aircraft-borne radiometers have shown that the microwave signatures of various parts of the terrain depend on both the volume scattering cross-section and the dielectric loss in the medium. In soil, it has been found that experimental data fit a model in which the scattering cross section is negligible compared to the dielectric loss. On the other hand, the volume scattering cross-section in snow and continental ice was found, from analyzing data obtained with aircraft- and spacecraft-borne radiometers, to be more important than the dielectric loss or surface reflectivity in determining the observed microwave emissivity. A model which assumes Mie scattering of ice particles of various sizes was found to be the dominant volume scattering mechanism in these media. Both spectral variation in the microwave signatures of snow and ice fields, as well as the variation in the emissivity of continental ice sheets such as those covering Greenland and Antarctica appear to be consistent with this model.

  16. Drones application on snow and ice surveys in alpine areas

    NASA Astrophysics Data System (ADS)

    La Rocca, Leonardo; Bonetti, Luigi; Fioletti, Matteo; Peretti, Giovanni

    2015-04-01

    First results from Climate change are now clear in Europe, and in Italy in particular, with the natural disasters that damaged irreparably the territory and the habitat due to extreme meteorological events. The Directive 2007/60/EC highlight that an "effective natural hazards prevention and mitigation that requires coordination between Member States above all on natural hazards prevention" is necessary. A climate change adaptation strategy is identified on the basis of the guidelines of the European Community program 2007-2013. Following the directives provided in the financial instrument for civil protection "Union Civil Protection Mechanism" under Decision No. 1313/2013 / EU of the European Parliament and Council, a cross-cutting approach that takes into account a large number of implementation tools of EU policies is proposed as climate change adaptation strategy. In last 7 years a network of trans-Alpine area's authorities was created between Italy and Switzerland to define an adaptive strategy on climate change effects on natural enviroment based on non structural remedies. The Interreg IT - CH STRADA Project (STRategie di ADAttamento al cambiamento climatico) was born to join all the non structural remedies to climate change effects caused by snow and avalanches, on mountain sources, extreme hydrological events and to manage all transnational hydrological resources, involving all stakeholders from Italy and Switzerland. The STRADA project involved all civil protection authorities and all research centers in charge of snow, hydrology end civil protection. The Snow - meteorological center of the Regional Agency for Environment Protection (CNM of ARPA Lombardia) and the Civil Protection of Lombardy Region created a research team to develop tools for avalanche prediction and to observe and predict snow cover on Alpine area. With this aim a lot of aerial photo using Drone as been performed in unusual landscape. Results of all surveys were really interesting on a scientific point of view. All flight was performed by remote controlled aero models with high resolution camera. Aero models were able to take off and to ground on snow covered or icy surfaces since the specific aerodynamic configuration and specific engine used to. All winter surveys were executed flying low to obtain a tridimensional reconstruction of an High resolution Digital Elevation Model (DEM) of snow cover and ice cover and on summer as been developed the DEM were snow amass in the maximum avalanche risk period. The difference between winter and summer DEM (difference between two point clouds) let to individuate the snow depth, and it was used as input data for the snow avalanche model for the Aprica site (Bergamo - Italy).

  17. Monitoring Arctic Sea ice using ERTS imagery. [Bering Sea, Beaufort Sea, Canadian Archipelago, and Greenland Sea

    NASA Technical Reports Server (NTRS)

    Barnes, J. C.; Bowley, C. J.

    1974-01-01

    Because of the effect of sea ice on the heat balance of the Arctic and because of the expanding economic interest in arctic oil and other minerals, extensive monitoring and further study of sea ice is required. The application of ERTS data for mapping ice is evaluated for several arctic areas, including the Bering Sea, the eastern Beaufort Sea, parts of the Canadian Archipelago, and the Greenland Sea. Interpretive techniques are discussed, and the scales and types of ice features that can be detected are described. For the Bering Sea, a sample of ERTS imagery is compared with visual ice reports and aerial photography from the NASA CV-990 aircraft.

  18. Sea Ice Characteristics and the Open-Linked Data World

    NASA Astrophysics Data System (ADS)

    Khalsa, S. J. S.; McGuinness, D. L.; Duerr, R.; Pulsifer, P. L.; Fox, P. A.; Thompson, C.; Yan, R.

    2014-12-01

    The audience for sea ice data sets has broadened dramatically over the past several decades. Initially the National Snow and Ice Data Center (NSIDC) sea ice products were used primarily by sea ice specialists. However, now they are in demand by researchers in many different domains and some are used by the public. This growth in the number and type of users has presented challenges to content providers aimed particularly at supporting interdisciplinary and multidisciplinary data use. In our experience, it is generally insufficient to simply make the data available as originally formatted. New audiences typically need data in different forms; forms that meet their needs, that work with their specific tools. Moreover, simple data reformatting is rarely enough. The data needs to be aggregated, transformed or otherwise converted into forms that better serve the needs of the new audience. The Semantic Sea Ice Interoperability Initiative (SSIII) is an NSF-funded research project aimed at making sea ice data more useful to more people using semantic technologies. The team includes domain and science data experts as well as knowledge representation and linked data experts. Beginning with a series of workshops involving members of the operations, sea ice research and modeling communities, as well as members of local communities in Alaska, a suite of ontologies describing the physical characteristics of sea ice have been developed and used to provide one of NSIDC's data sets, the operational Arctic sea ice charts obtained from the Canadian Ice Center, as open-linked data. These data extend nearly a decade into the past and can now be queried either directly through a publicly available SPARQL end point (for those who are familiar with open-linked data) or through a simple Open Geospatial Consortium (OGC) standards map-based query tool. Questions like "What were the characteristics (i.e., sea ice concentration, form and stage of development) of the sea ice in the region surrounding my ship/polar bear on date X?" can now be answered. This service may be of interest within the broad polar community - especially those who already are familiar with either open-linked data or OGC services. We seek feedback, collaborators, and users.

  19. Brine-ecosystem interactions in sea ice

    NASA Astrophysics Data System (ADS)

    Vancoppenolle, M.; Bitz, C. M.; Fichefet, T.; Goosse, H.; Lancelot, C.; Tison, J.

    2010-12-01

    Microalgae grow in brine inclusions in sea ice. Previous sea ice-ecosystem models neglect brine-microalgae interactions, prescribing the location of the microbial communities. In this study, a sea ice model with explicit brine dynamics coupled to a simple nutrient-phytoplankton (N-P) module (diatoms and dissolved silicates) is introduced. The model predicts bottom and surface microalgal populations. In fall, brine convection in cooling ice supplies nutrients, which favors microalgal growth. In early summer, the vertical brine density profile in warmer ice stabilizes, nutrient supply shuts off, which prevents further biomass building. Sensitivity tests in an idealized Antarctic pack ice configuration suggest that mode of microalgal transport within brine (passive or active) induces important population differences. This study is a step toward a more realistic sea ice-ecosystem model, which is required to understand the role of sea ice and associated ecosystems in global biogeochemical cycles.

  20. The NASA IceBridge Project Quickly Delivers Snow and Ice Elevation Measurements of Dynamic Polar Landscapes

    NASA Astrophysics Data System (ADS)

    Tressel, S. S.; Kaminski, M. L.; Brodzik, M.

    2012-12-01

    NASA's Operation IceBridge was formulated to bridge the gap between the ICESat and ICESat-2 satellite missions. IceBridge data are collected by a wide variety of instrumentation aboard aircraft that trace routes around Greenland, Alaska and Antarctica, concentrating on areas experiencing accelerated change. Data parameters such as ice surface elevation, ice bottom elevation, snow and ice depth, grounding line position, sea ice distribution and freeboard are extracted at resolutions better than what can be expected by satellite. IceBridge provides the continuity of such data until the launch of the ICESat-2 satellite, expected in 2016. NSIDC manages the data distribution and makes the data available quickly and effectively to any and all interested parties. For example, the MCoRDS L1B Geolocated Radar Echo Strength Profiles data represents one of 60 total data products available through the IceBridge project. The MCoRDS L1B data for the Greenland 2012 campaign exhibit ice surface and ice bottom information for areas of Greenland between 27 March 2012 and 17 May 2012. In July of 2012, these data were made available on the NSIDC Web site, allowing users to begin analyzing the data only a couple of months after the data collection. The data are distributed in MATLAB files with associated PDF, TIFF and PNG files. Comparable data are available starting in 2009 for periodic campaigns covering both Greenland and Antarctica. These data can be combined with an array of other parameters to track the state of the most crucial areas of the Earth's cryosphere.

  1. CBSIT 2009: Airborne Validation of Envisat Radar Altimetry and In Situ Ice Camp Measurements Over Arctic Sea Ice

    NASA Technical Reports Server (NTRS)

    Connor, Laurence; Farrell, Sinead; McAdoo, David; Krabill, William; Laxon, Seymour; Richter-Menge, Jacqueline; Markus, Thorsten

    2010-01-01

    The past few years have seen the emergence of satellite altimetry as valuable tool for taking quantitative sea ice monitoring beyond the traditional surface extent measurements and into estimates of sea ice thickness and volume, parameters that arc fundamental to improved understanding of polar dynamics and climate modeling. Several studies have now demonstrated the use of both microwave (ERS, Envisat/RA-2) and laser (ICESat/GLAS) satellite altimeters for determining sea ice thickness. The complexity of polar environments, however, continues to make sea ice thickness determination a complicated remote sensing task and validation studies remain essential for successful monitoring of sea ice hy satellites. One such validation effort, the Arctic Aircraft Altimeter (AAA) campaign of2006. included underflights of Envisat and ICESat north of the Canadian Archipelago using NASA's P-3 aircraft. This campaign compared Envisat and ICESat sea ice elevation measurements with high-resolution airborne elevation measurements, revealing the impact of refrozen leads on radar altimetry and ice drift on laser altimetry. Continuing this research and validation effort, the Canada Basin Sea Ice Thickness (CBSIT) experiment was completed in April 2009. CBSIT was conducted by NOAA. and NASA as part of NASA's Operation Ice Bridge, a gap-filling mission intended to supplement sea and land ice monitoring until the launch of NASA's ICESat-2 mission. CBIST was flown on the NASA P-3, which was equipped with a scanning laser altimeter, a Ku-band snow radar, and un updated nadir looking photo-imaging system. The CB5IT campaign consisted of two flights: an under flight of Envisat along a 1000 km track similar to that flown in 2006, and a flight through the Nares Strait up to the Lincoln Sea that included an overflight of the Danish GreenArc Ice Camp off the coast of northern Greenland. We present an examination of data collected during this campaign, comparing airborne laser altimeter measurements with (1) Envisat RA-2 returns retracked optimally for sea ice and (2) in situ measurements of sea ice thickness and snow depth gathered from ice camp surveys. Particular attention is given to lead identification and classification using the continuous photo-imaging system along the Envisat underflight as well as the performance of the snow radar over the ice camp survey lines.

  2. Snow nitrate photolysis in polar regions and the mid-latitudes: Impact on boundary layer chemistry and implications for ice core records

    NASA Astrophysics Data System (ADS)

    Zatko, Maria C.

    The formation and recycling of nitrogen oxides (NOx=NO+NO 2) associated with snow nitrate photolysis has important implications for air quality and the preservation of nitrate in ice core records. This dissertation examines snow nitrate photolysis in polar and mid-latitude regions using field and laboratory based observations combined with snow chemistry column models and a global chemical transport model to explore the impacts of snow nitrate photolysis on boundary layer chemistry and the preservation of nitrate in polar ice cores. Chapter 1 describes how a global chemical transport model is used to calculate the photolysis-driven flux and redistribution of nitrogen across Antarctica, and Chapter 2 presents similar work for Greenland. Snow-sourced NOx is most dependent on the quantum yield for nitrate photolysis as well as the concentration of photolabile nitrate and light-absorbing impurities (e.g., black carbon, dust, organics) in snow. Model-calculated fluxes of snow-sourced NOx are similar in magnitude in Antarctica (0.5--7.8x108 molec cm-2 s -1) and Greenland (0.1--6.4x108 molec cm-2 s-1) because both nitrate and light-absorbing impurity concentrations in snow are higher (by factors of 2 and 10, respectively) in Greenland. Snow nitrate photolysis influences boundary layer chemistry and ice-core nitrate preservation less in Greenland compared to Antarctica largely due to Greenland's proximity to NOx-source regions. Chapter 3 describes how a snow chemistry column model combined with chemistry and optical measurements from the Uintah Basin Winter Ozone Study (UBWOS) 2014 is used to calculate snow-sourced NOx in eastern Utah. Daily-averaged fluxes of snow-sourced NOx (2.9x10 7--1.3x108 molec cm-2 s-1) are similar in magnitude to polar snow-sourced NO x fluxes, but are only minor components of the Uintah Basin boundary layer NOx budget and can be neglected when developing ozone reduction strategies for the region. Chapter 4 presents chemical and optical measurements made during the Sea Ice Physics and Ecosystems eXperiment II (SIPEXII) in the East Antarctic sea ice zone. Vertical profiles of delta15N(NO 3-) in snow suggest that snow-sourced NOx from Antarctica is transported to the sea-ice zone. These studies suggest that snow-sourced NOx fluxes are similar in magnitude globally and that their impacts on boundary layer chemistry are linked to boundary layer pollution levels.

  3. Arctic sea ice freeboard from IceBridge acquisitions in 2009: Estimates and comparisons with ICESat

    NASA Astrophysics Data System (ADS)

    Kwok, R.; Cunningham, G. F.; Manizade, S. S.; Krabill, W. B.

    2012-02-01

    During the spring of 2009, the Airborne Topographic Mapper (ATM) system on the IceBridge mission acquired cross-basin surveys of surface elevations of Arctic sea ice. In this paper, the total freeboard derived from four ˜2000 km transects are examined and compared with those from the 2009 ICESat campaign. Total freeboard, the sum of the snow and ice freeboards, is the elevation of the air-snow interface above the local sea surface. Prior to freeboard retrieval, signal dependent range biases are corrected. With data from a near co-incident outbound and return track on 21 April, we show that our estimates of the freeboard are repeatable to within ˜4 cm but dependent locally on the density and quality of sea surface references. Overall difference between the ATM and ICESat freeboards for the four transects is 0.7 (8.5) cm (quantity in bracket is standard deviation), with a correlation of 0.78 between the data sets of one hundred seventy-eight 50 km averages. This establishes a level of confidence in the use of ATM freeboards to provide regional samplings that are consistent with ICESat. In early April, mean freeboards are 41 cm and 55 cm over first year and multiyear sea ice (MYI), respectively. Regionally, the lowest mean ice freeboard (28 cm) is seen on 5 April where the flight track sampled the large expanse of seasonal ice in the western Arctic. The highest mean freeboard (71 cm) is seen in the multiyear ice just west of Ellesmere Island from 21 April. The relatively large unmodeled variability of the residual sea surface resolved by ATM elevations is discussed.

  4. A Novel and Low Cost Sea Ice Mass Balance Buoy.

    NASA Astrophysics Data System (ADS)

    Jackson, Keith; Meldrum, David; Wilkinson, Jeremy; Maksym, Ted; Beckers, Justin; Haas, Christian

    2013-04-01

    Understanding of sea ice mass balance processes requires continuous monitoring of the seasonal evolution of ice thickness. While autonomous ice mass balance buoys (IMBs) deployed over the past two decades have contributed to our understanding of ice growth and decay processes, deployment has been limited, in part, by the cost of such systems. Routine, basin-wide monitoring of the ice cover is realistically achievable through a network of reliable and affordable autonomous instrumentation. We describe the development of a novel autonomous platform and sensor that replaces the traditional thermistors string for monitoring temperature profiles in the ice and snow using a chain of inexpensive digital temperature chip sensors linked by a single-wire data bus. By incorporating a heating element on each sensor, the instrument is capable of resolving material interfaces (e.g. air-snow and ice-ocean boundaries) even under isothermal conditions. The instrument is small, low-cost and easy to deploy. Field and laboratory tests of the sensor chain demonstrate that the technology can reliably resolve material boundaries to within a few centimetres and over 50 scientific deployments have been made with encouraging results. The discrimination between different media based on sensor thermal response is weak in some deployments and efforts to optimise the measurement continue.

  5. Sea Ice Lead Distribution from High Resolution Airborne Imagery

    NASA Astrophysics Data System (ADS)

    Farrell, S. L.; Kurtz, N. T.; Onana, V.; Harbeck, J. P.; Duncan, K.

    2011-12-01

    NASA's Operation IceBridge Mission provides continuity of the sea ice thickness time series, between the now complete ICESat mission and the planned ICESat-2 mission, by utilizing airborne laser and radar altimetry measurements to improve estimates of snow and ice thickness. An essential step in deriving sea ice freeboard (and hence thickness) from altimetry measurements of sea ice elevation is the determination of local sea level. Discrimination of leads along-track is therefore critical for deriving the elevation of open water within leads and defining sea surface height. Here we provide an assessment of the lead mapping capabilities of the Digital Mapping System (DMS), a nadir-looking, high-resolution digital camera mounted on IceBridge aircraft. For a nominal aircraft operating-altitude around 500 m, the resolution of the DMS imagery is approximately 0.1 m. A novel lead detection algorithm was applied to DMS digital photography for unambiguous detection of leads within the sea ice pack and classification of lead type. The data were used to generate statistics on lead distribution and spacing, lead width, and areal coverage. We compare results from the Arctic multi-year ice pack with data gathered over the mainly seasonal ice pack of the Southern Ocean. We find that areal coverage of Antarctic leads is about 5 % and three times higher than in the Arctic (1.5 %). Both dynamic and thermodynamic modeling of the sea ice pack relies on knowledge of lead distribution to effectively model ice motion and interactions between the ocean and atmosphere. We describe the potential contribution our results can make towards the improvement of coupled ice-ocean numerical models. We discuss the application of lead discrimination for freeboard retrieval from satellite altimetry (e.g. CryoSat-2 and ICESat-2) and the use of lead distribution statistics for assessing sampling geometries employed by current airborne and future satellite laser altimeters to map the complex sea ice environment, including the multi-beam photon-counting approach proposed for ICESat-2.

  6. Operational Products Archived at the National Snow and Ice Data Center

    NASA Astrophysics Data System (ADS)

    Fetterer, F. M.; Ballagh, L.; Gergely, K.; Kovarik, J.; Wallace, A.; Windnagel, A.

    2009-12-01

    Sea ice charts for shipping interests from the Navy/NOAA/Coast Guard National Ice Center are often laboriously produced by manually interpreting and synthesizing data from many sources, both satellite and in situ. They are generally more accurate than similar products from single sources. Upward looking sonar data from U.S. Navy submarines operating in the Arctic provides information on ice thickness. Similarly extensive data were available from no other source prior to the recently established reliability of ice thickness estimates from polar orbiting instruments like the Geoscience Laser Altimeter System (GLAS). Snow Data Assimilation System (SNODAS) products from the NOAA NWS National Operational Hydrologic Remote Sensing Center give researchers the best possible estimates of snow cover and associated variables to support hydrologic modeling and analysis for the continental U.S. These and other snow and ice data products are produced by the U.S. Navy, the NOAA National Weather Service, and other agency entities to serve users who have an operational need: to get a ship safely to its destination, for example, or to predict stream flow. NOAA supports work at NSIDC with data from operational sources that can be used for climate research and change detection. We make these products available to a new user base, by archiving operational data, making data available online, providing documentation, and fielding questions from researchers about the data. These data demand special consideration: often they are advantageous because they are available on a schedule in near real time, but their use in climate studies is problematic since many are produced with regard for ‘best now’ and without regard for time series consistency. As arctic climate changes rapidly, operational and semi-operational products have an expanding science support role to play.

  7. The strength anisotropia of sea ice

    SciTech Connect

    Evdokimov, G.N.; Rogachko, S.I.

    1994-12-31

    The hydraulic-engineering structure calculations of sea ice formation force require the sea ice strength data. The strength characteristics values and the types of sea ice formations in view of water depth define the type and the design of future structures in each particular region of supposed construction. The most objective information on the sea ice physical and technical properties can be obtained by field investigations ad the existing methods of their calculations refer to a great number of errors. The accumulated bank of data on studying the sea ice formation strength properties show one that ice as a natural material is of great crystalline structure variety. The level ice fields have a number of particularities. The crystal sizes increase in ice thickness. The crystals consist of fresh-water thin plates 0.5--0.6 mm in thickness oriented by pickle-water interlayers. Difference in thickness of the sea ice cover structure is one of the main causes of the changes strength characteristics layer. Besides that the sea ice strength depends upon the destroying force direction in reference to crystal orientation which characterizes the sea ice anisotropia as a material.

  8. Predictability of the Arctic sea ice edge

    NASA Astrophysics Data System (ADS)

    Goessling, H. F.; Tietsche, S.; Day, J. J.; Hawkins, E.; Jung, T.

    2016-02-01

    Skillful sea ice forecasts from days to years ahead are becoming increasingly important for the operation and planning of human activities in the Arctic. Here we analyze the potential predictability of the Arctic sea ice edge in six climate models. We introduce the integrated ice-edge error (IIEE), a user-relevant verification metric defined as the area where the forecast and the "truth" disagree on the ice concentration being above or below 15%. The IIEE lends itself to decomposition into an absolute extent error, corresponding to the common sea ice extent error, and a misplacement error. We find that the often-neglected misplacement error makes up more than half of the climatological IIEE. In idealized forecast ensembles initialized on 1 July, the IIEE grows faster than the absolute extent error. This means that the Arctic sea ice edge is less predictable than sea ice extent, particularly in September, with implications for the potential skill of end-user relevant forecasts.

  9. USGS and NOAA Monitor Arctic Sea Ice

    USGS scientist Jonathan Childs and NOAA oceanographer Pablo Clemente-Colón, also Chief Scientist of the National Ice Center, looking out on the Arctic sea ice. This was during a scientific expedition to map the Arctic seafloor....

  10. Summer Arctic Sea Ice Intra-Seasonal Predictability Using a Vector Auto-Regressive Model

    NASA Astrophysics Data System (ADS)

    Ting, M.; Wang, L.; Yuan, X.

    2014-12-01

    Recent Arctic sea ice changes have important societal and economic impacts: the accelerated melting of Arctic sea ice in summer provides new fishery opportunities and increases the feasibility of trans-Arctic shipping, yet it may also lead to adverse effects on the Arctic ecosystem, weather and climate. Understanding the predictability of Arctic sea ice melting is thus an important task. A Vector Auto-Regressive (VAR) model is evaluated for predicting the summer time (May through September) daily Arctic sea ice concentrations. The intra-seasonal forecast skill of the Arctic sea ice is assessed using 1979-2012 satellite data provided by the National Snow & Ice Data Center (NSIDC). The cross-validated forecast skill of the VAR model is superior over persistence and climatological seasonal cycle for a lead-time of 15~60 days, especially over marginal seas. In addition to capturing the general seasonal melt of sea ice, the VAR model is also able to capture the interannual variability of the melting, from partial melt of the marginal sea ice in the beginning of the period to almost a complete melt in the later years. While the detailed mechanism leading to the high predictability of intra-seasonal sea ice concentration needs to be further examined, the study reveals for the first time that Arctic sea ice concentration can be predicted statistically with reasonable skills at the intra-seasonal time scales.

  11. The role of satellites in snow and ice measurements

    NASA Technical Reports Server (NTRS)

    Wiesnet, D. R.

    1974-01-01

    Earth-orbiting polar satellites are desirable platforms for the remote sensing of snow and ice. Geostationary satellites at a very high altitude (35,900 km) are also desirable platforms for many remote sensors, for communications relay, for flood warning systems, and for telemetry of data from unattended instrumentation in remote, inaccessible places such as the Arctic, Antarctic, or mountain tops. Optimum use of satellite platforms is achieved only after careful consideration of the temporal, spatial, and spectral requirements of the environmental mission. The National Environmental Satellite Service will maintain both types of environmental satellites as part of its mission.

  12. Distinguishing Clouds from Ice over the East Siberian Sea, Russia

    NASA Technical Reports Server (NTRS)

    2002-01-01

    As a consequence of its capability to retrieve cloud-top elevations, stereoscopic observations from the Multi-angle Imaging SpectroRadiometer (MISR) can discriminate clouds from snow and ice. The central portion of Russia's East Siberian Sea, including one of the New Siberian Islands, Novaya Sibir, are portrayed in these views from data acquired on May 28, 2002.

    The left-hand image is a natural color view from MISR's nadir camera. On the right is a height field retrieved using automated computer processing of data from multiple MISR cameras. Although both clouds and ice appear white in the natural color view, the stereoscopic retrievals are able to identify elevated clouds based on the geometric parallax which results when they are observed from different angles. Owing to their elevation above sea level, clouds are mapped as green and yellow areas, whereas land, sea ice, and very low clouds appear blue and purple. Purple, in particular, denotes elevations very close to sea level. The island of Novaya Sibir is located in the lower left of the images. It can be identified in the natural color view as the dark area surrounded by an expanse of fast ice. In the stereo map the island appears as a blue region indicating its elevation of less than 100 meters above sea level. Areas where the automated stereo processing failed due to lack of sufficient spatial contrast are shown in dark gray. The northern edge of the Siberian mainland can be found at the very bottom of the panels, and is located a little over 250 kilometers south of Novaya Sibir. Pack ice containing numerous fragmented ice floes surrounds the fast ice, and narrow areas of open ocean are visible.

    The East Siberian Sea is part of the Arctic Ocean and is ice-covered most of the year. The New Siberian Islands are almost always covered by snow and ice, and tundra vegetation is very scant. Despite continuous sunlight from the end of April until the middle of August, the ice between the island and the mainland typically remains until August or September.

    The Multi-angle Imaging SpectroRadiometer views almost the entire Earth every 9 days. These images were acquired during Terra orbit 12986 and cover an area of about 380 kilometers x 1117 kilometers. They utilize data from blocks 24 to 32 within World Reference System-2 path 117.

    MISR was built and is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Office of Earth Science, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center, Greenbelt, MD. JPL is a division of the California Institute of Technology.

  13. Impact of sea ice initialization on sea ice and atmosphere prediction skill on seasonal timescales

    NASA Astrophysics Data System (ADS)

    Guemas, V.; Chevallier, M.; Déqué, M.; Bellprat, O.; Doblas-Reyes, F.

    2016-04-01

    We present a robust assessment of the impact of sea ice initialization from reconstructions of the real state on the sea ice and atmosphere prediction skill. We ran two ensemble seasonal prediction experiments from 1979 to 2012 : one using realistic sea ice initial conditions and another where sea ice is initialized from a climatology, with two forecast systems. During the melting season in the Arctic Ocean, sea ice forecasts become skilful with sea ice initialization until 3-5 months ahead, thanks to the memory held by sea ice thickness. During the freezing season in both the Arctic and Antarctic Oceans, sea ice forecasts are skilful for 7 and 2 months, respectively, with negligible differences between the two experiments, the memory being held by the ocean heat content. A weak impact on the atmosphere prediction skill is obtained.

  14. The Antarctic sea ice concentration budget of an ocean-sea ice coupled model

    NASA Astrophysics Data System (ADS)

    Lecomte, Olivier; Goosse, Hugues; Fichefet, Thierry; Holland, Paul R.; Uotila, Petteri

    2015-04-01

    The Antarctic sea ice concentration budget of the NEMO-LIM ocean-sea ice coupled model is computed and analyzed. Following a previously developed method, the sea ice concentration balance over the autumn-winter seasons is decomposed into four terms, including the sea ice concentration change during the period of interest, advection, divergence and a residual accounting for the net contribution of thermodynamics and ice deformation. Preliminary results from this analysis show that the geographical patterns of all budget terms over 1992-2010 are in qualitative agreement with the observed ones. Sea ice thermodynamic growth is maintained by horizontal divergence near the continent and in the central ice pack, while melting close to the ice edge is led by sea ice advection. Quantitatively however, the inner ice pack divergence and associated sea ice freezing are much stronger, as compared to observations. The advection of sea ice in both the central pack and the marginal areas are likewise stronger, which corroborates the findings of a previous study in which the same methods were applied to a fully coupled climate model. Nonetheless, the seasonal evolution of sea ice area and total extent are reasonably well simulated, since enhanced sea ice freezing due to larger divergence in the central pack is compensated by intensified melting in the outer pack owing to faster advection. Those strong dynamic components in the sea ice concentration budget are due to ice velocities that tend to be biased high all around Antarctica and particularly near the ice edge. The obtained results show that the applied method is particularly well suited for assessing the skills of an ocean-sea ice coupled model in simulating the seasonal and regional evolution of Antarctic sea ice for the proper physical reasons.

  15. Sea-ice thermodynamics and brine drainage.

    PubMed

    Worster, M Grae; Rees Jones, David W

    2015-07-13

    Significant changes in the state of the Arctic ice cover are occurring. As the summertime extent of sea ice diminishes, the Arctic is increasingly characterized by first-year rather than multi-year ice. It is during the early stages of ice growth that most brine is injected into the oceans, contributing to the buoyancy flux that mediates the thermo-haline circulation. Current operational sea-ice components of climate models often treat brine rejection between sea ice and the ocean similarly to a thermodynamic segregation process, assigning a fixed salinity to the sea ice, typical of multi-year ice. However, brine rejection is a dynamical, buoyancy-driven process and the salinity of sea ice varies significantly during the first growth season. As a result, current operational models may over predict the early brine fluxes from newly formed sea ice, which may have consequences for coupled simulations of the polar oceans. Improvements both in computational power and our understanding of the processes involved have led to the emergence of a new class of sea-ice models that treat brine rejection dynamically and should enhance predictions of the buoyancy forcing of the oceans. PMID:26032321

  16. Sea Ice, Climate and Fram Strait

    NASA Technical Reports Server (NTRS)

    Hunkins, K.

    1984-01-01

    When sea ice is formed the albedo of the ocean surface increases from its open water value of about 0.1 to a value as high as 0.8. This albedo change effects the radiation balance and thus has the potential to alter climate. Sea ice also partially seals off the ocean from the atmosphere, reducing the exchange of gases such as carbon dioxide. This is another possible mechanism by which climate might be affected. The Marginal Ice Zone Experiment (MIZEX 83 to 84) is an international, multidisciplinary study of processes controlling the edge of the ice pack in that area including the interactions between sea, air and ice.

  17. ASPECTS OF ARCTIC SEA ICE OBSERVABLE BY SEQUENTIAL PASSIVE MICROWAVE OBSERVATIONS FROM THE NIMBUS-5 SATELLITE.

    USGS Publications Warehouse

    Campbell, William J.; Gloersen, Per; Zwally, H. Jay

    1984-01-01

    Observations made from 1972 to 1976 with the Electrically Scanning Microwave Radiometer on board the Nimbus-5 satellite provide sequential synoptic information of the Arctic sea ice cover. This four-year data set was used to construct a fairly continuous series of three-day average 19-GHz passive microwave images which has become a valuable source of polar information, yielding many anticipated and unanticipated discoveries of the sea ice canopy observed in its entirety through the clouds and during the polar night. Short-term, seasonal, and annual variations of key sea ice parameters, such as ice edge position, ice types, mixtures of ice types, ice concentrations, and snow melt on the ice, are presented for various parts of the Arctic.

  18. The Last Arctic Sea Ice Refuge

    NASA Astrophysics Data System (ADS)

    Pfirman, S. L.; Tremblay, B.; Newton, R.; Fowler, C.

    2010-12-01

    Summer sea ice may persist along the northern flank of Canada and Greenland for decades longer than the rest of the Arctic, raising the possibility of a naturally formed refugium for ice-associated species. Observations and models indicate that some ice in this region forms locally, while some is transported to the area by winds and ocean currents. Depending on future changes in melt patterns and sea ice transport rates, both the central Arctic and Siberian shelf seas may be sources of ice to the region. An international system of monitoring and management of the sea ice refuge, along with the ice source regions, has the potential to maintain viable habitat for ice-associated species, including polar bears, for decades into the future. Issues to consider in developing a strategy include: + the likely duration and extent of summer sea ice in this region based on observations, models and paleoenvironmental information + the extent and characteristics of the “ice shed” contributing sea ice to the refuge, including its dynamics, physical and biological characteristics as well as potential for contamination from local or long-range sources + likely assemblages of ice-associated species and their habitats + potential stressors such as transportation, tourism, resource extraction, contamination + policy, governance, and development issues including management strategies that could maintain the viability of the refuge.

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

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

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

  20. MODIS Data and Services at the National Snow and Ice Data Center (NSIDC)

    NASA Astrophysics Data System (ADS)

    McAllister, M.; Fowler, D. K.

    2010-12-01

    For nearly a decade, the National Snow and Ice Data Center (NSIDC) 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. The archive contains a wide selection of data products relevant to cryospheric science, including snow and sea ice. NSIDC offers a variety of methods for obtaining these data. Our Data Pool is an online archive which allows a user to very quickly download desired products and also has a spatial and temporal search capability. The Warehouse Inventory Search Tool (WIST) contains a complete set of metadata for all products which can be searched for and ordered. WIST also allows a user to order spatial, temporal, and parameter subsets of the data. Users can also request that they be added to our subscription list which makes it possible to have new MODIS data automatically ftp’d or staged on a local server as it is archived at NSIDC. Since MODIS products are in HDF-EOS format, NSIDC has developed a number of tools to assist with browsing, editing, reprojection, resampling, and format conversion including MODIS Swath-to-Grid Toolbox (MS2GT) and the MODIS Interactive Subsetting Tool (MIST). MS2GT was created to produce a seamless output grid from multiple input files corresponding to successively acquired, 5-minute MODIS scenes. NSIDC created the MIST to also provide subsets of certain Version 5 MODIS products, over the Greenland Climate Network (GC-Net) and the International Arctic Systems for Observing the Atmosphere (IASOA) stations.

  1. MODIS Data and Services at the National Snow and Ice Data Center (NSIDC)

    NASA Astrophysics Data System (ADS)

    McAllister, M.; Booker, L.; Fowler, D. K.; Haran, T. M.

    2014-12-01

    For close to 15 years, the National Snow and Ice Data Center (NSIDC) NASA Distributed Active Archive Center (NDAAC) 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. The archive contains a wide selection of snow and sea ice data products relevant to cryospheric science. NSIDC offers a variety of methods for obtaining these data. Users can ftp data directly from an online archive which allows for a very quick download. The Reverb Search & Order Tool contains a complete set of metadata for all products which can be searched for and ordered. Reverb allows a user to order spatial, temporal, and parameter subsets of the data. Users can also request that they be added to our subscription list which makes it possible to have new MODIS data automatically ftp'd or staged on a local server as it is archived at NSIDC. Since MODIS products are in HDF-EOS format, a number of tools have been developed to assist with browsing, editing, reprojection, resampling, and format conversion. One such service, Data Access, can be accessed through Reverb and performs subsetting, reformatting, and reprojection. This service can also be accessed via an Application Programming Interface (API) from a user-written client. Other tools include the MODIS Swath-to-Grid Toolbox (MS2GT) and the MODIS Interactive Subsetting Tool (MIST). MS2GT was created to produce a seamless output grid from multiple input files corresponding to successively acquired, 5-minute MODIS scenes. NSIDC also created the MIST to provide subsets of certain Version 5 MODIS products, over the Greenland Climate Network (GC-Net) and the International Arctic Systems for Observing the Atmosphere (IASOA) stations. Tools from other sources include HDFView from the National Center for Supercomputing Applications (NCSA), and the MODIS Reprojection Tool (MRT) and MRT Swath developed by the Land Processes DAAC (LP-DAAC).

  2. Characterization of ice binding proteins from sea ice algae.

    PubMed

    Bayer-Giraldi, Maddalena; Jin, EonSeon; Wilson, Peter W

    2014-01-01

    Several polar microalgae are able to live and thrive in the extreme environment found within sea ice, where growing ice crystals may cause mechanical damage to the cells and reduce the organisms' living space. Among the strategies adopted by these organisms to cope with the harsh conditions in their environment, ice binding proteins (IBPs) seem to play a key role and possibly contribute to their success in sea ice. IBPs have the ability to control ice crystal growth. In nature they are widespread among sea ice microalgae, and their mechanism of function is of interest for manifold potential applications. Here we describe methods for a classical determination of the IBP activity (thermal hysteresis, recrystallization inhibition) and further methods for protein characterization (ice pitting assay, determination of the nucleating temperature). PMID:24852640

  3. Iron and macro-nutrient concentrations in sea ice and their impact on the nutritional status of surface waters in the southern Okhotsk Sea

    NASA Astrophysics Data System (ADS)

    Kanna, Naoya; Toyota, Takenobu; Nishioka, Jun

    2014-08-01

    To elucidate the roles of sea ice in biogeochemical cycles in the Sea of Okhotsk, the concentrations of macro-nutrients (NO3 + NO2, PO4, SiO2, and NH4) and trace elements (Fe, Al) were measured in samples of sea ice, overlying snow, and seawater. The oxygen isotope ratio (δ18O) in the sea ice was used to distinguish between snow ice and seawater-origin ice. Except for NH4, the macro-nutrient concentrations were lower in sea ice than in surface water in the ice-covered area. A linear relationship between salinity and concentrations of NO3 + NO2, PO4, and SiO2 in the sea ice indicated that these macro-nutrients originated mainly from seawater. The Fe concentrations in sea ice were variable and several orders of magnitude higher than those in surface water in the ice-covered area. The Fe concentrations in the sea ice were positively correlated with Al concentrations, the suggestion being that the Fe contained in the sea ice originated mainly from lithogenic mineral particles. The annual Fe flux into the surface water from sea ice melting in the southern Sea of Okhotsk was estimated to be ∼740 μmol Fe m-2 yr-1. This flux is comparable to the reported annual atmospheric Fe flux (267-929 μmol Fe m-2 yr-1) in the western North Pacific. In spring, sea ice melting may slightly dilute macro-nutrient concentrations but increase Fe concentrations in surface water. These results suggest that sea ice may contribute to phytoplankton growth by release of Fe into the water column and have a large impact on biogeochemical cycles in the Sea of Okhotsk.

  4. The seasonal evolution of sea ice floe size distribution

    NASA Astrophysics Data System (ADS)

    Perovich, Donald K.; Jones, Kathleen F.

    2014-12-01

    The Arctic sea ice cover undergoes large changes over an annual cycle. In winter and spring, the ice cover consists of large, snow-covered plate-like ice floes, with very little open water. By the end of summer, the snow cover is gone and the large floes have broken into a complex mosaic of smaller, rounded floes surrounded by a lace of open water. This evolution strongly affects the distribution and fate of the solar radiation deposited in the ice-ocean system and consequently the heat budget of the ice cover. In particular, increased floe perimeter can result in enhanced lateral melting. We attempt to quantify the floe evolution process through the concept of a floe size distribution that is modified by lateral melting and floe breaking. A time series of aerial photographic surveys made during the SHEBA field experiment is analyzed to determine evolution of the floe size distribution from spring through summer. Based on earlier studies, we assume the floe size cumulative distribution could be represented by a power law D-α, where D is the floe diameter. The exponent α as well as the number density of floes Ntot are estimated from measurements of total ice area and perimeter. As summer progressed, there was an increase in α as the size distribution shifted toward smaller floes and the number of floes increased. Lateral melting causes the distribution to deviate from a power law for small floe sizes.

  5. A Unified Sea Ice Thickness Data Set for Model Validation

    NASA Astrophysics Data System (ADS)

    Lindsay, R.; Wensnahan, M.

    2007-12-01

    Can we, as a community, do better at using existing ice thickness measurements to more effectively evaluate the changing nature of the Arctic ice pack and to better evaluate the performance of our models? We think we can if we work together. We are trying to create a unified ice thickness data set by combining observations from various ice thickness measurement systems. It is designed to facilitate the intercomparison of different measurements, the evaluation of the state of the ice pack, and the validation of sea ice models. Datasets that might be included are ice draft estimates from various submarine and moored upward looking sonar instruments, ice thickness estimates from airborne electromagnetic instruments, and satellite altimeter freeboard measurements. Three principles for the proposed data set are: 1) Full documentation of data sources and characteristics, 2) Spatial and temporal averaging to approximately common scales, and 3) Common data formats. We would not mix data types and we would not interpolate to locations or times not represented in the observations. The target spatial and temporal scale for the measurements would be 50 lineal km of ice and/or one month. Point measurements are not so useful in this context. Data from both hemispheres and any body of ocean water would be included. Documentation would include locations, times, measurement methods, processing, snow depth assumptions, averaging distance and time, error characteristics, data provider, and more. The cooperation and collaboration of the various data providers is essential to the success of this project and so far we have had a very gratifying response to our overtures. We would like to hear from any who have not heard from us and who have collected sea ice thickness data at the approximate target scales. With potentially thousands of individual samples, much could be learned about the measurement systems, about the changing state of the ice cover, and about ice model performance and errors.

  6. Snow and Ice Mask for the MODIS Aerosol Products

    NASA Technical Reports Server (NTRS)

    Li, Rong-Rong; Remer, Lorraine; Kaufman, Yoram J.; Mattoo, Shana; Gao, Bo-Cai; Vermote, Eric

    2005-01-01

    The atmospheric products have been derived operationally from multichannel imaging data collected with the Moderate Resolution Imaging SpectroRadiometers (MODIS) on board the NASA Terra and Aqua spacecrafts. Preliminary validations of the products were previously reported. Through analysis of more extensive time-series of MODIS aerosol products (Collection 4), we have found that the aerosol products over land areas are slightly contaminated by snow and ice during the springtime snow-melting season. We have developed an empirical technique using MODIS near-IR channels centered near 0.86 and 1.24 pm and a thermal emission channel near 11 pm to mask out these snow-contaminated pixels over land. Improved aerosol retrievals over land have been obtained. Sample results from application of the technique to MODIS data acquired over North America, northern Europe, and northeastern Asia are presented. The technique has been implemented into the MODIS Collection 5 operational algorithm for retrieving aerosols over land from MODIS data.

  7. Monitoring Land-fast Sea Ice in the Western Antarctic Through Multi-sensor Data Fusion

    NASA Astrophysics Data System (ADS)

    Kim, M.; Im, J.; Kim, J. W.; Lee, S.; Shin, M.

    2014-12-01

    Land-fast sea ice is almost motionless and fixed to shorelines, contrary to pack ice floating on the sea. As the spatiotemporal distribution of land-fast sea ice is closely related to the global and polar climate systems, it is crucial to accurately monitor land-fast sea ice to better understand the climate systems. Remote sensing can be used to monitor land-fast sea ice as it provides data covering vast areas at high temporal resolution. While remote sensing-based land-fast sea ice monitoring has been investigated in the Arctic areas, very few studies were conducted over the Antarctic areas. In particular, no studies have been conducted in the western Antarctic due to much greater variability of sea ice and more complex topography than the eastern Antarctic. The purpose of this study was to develop an automated land-fast sea ice monitoring approach using multi-sensor data fusion and machine learning approaches in the entire Antarctic especially focusing on the western part. The basic assumptions of land-fast sea ice with almost 100% of sea ice concentration and almost 0 m/s of sea ice velocity were used. Based on these assumptions, a total of 11 variables including sea ice concentration, 8 dual polarization frequency channels from The Advanced Microwave Scanning Radiometer for EOS (AMSR-E), ice surface temperature from visible/TIR sensor such as the MODerate resolution Imaging Spectroradiometer (MODIS) and ice velocity from Special Sensor Microwave/Imager (SSM/I) were used to identify land-fast sea ice. In addition to the 11 remote sensing-based variables, previous land-fast sea ice results visually identified using MODIS data by Fraser in the eastern Antarctic were used as reference data. Two rule-based machine learning approaches including See5.0 and random forest were used to map land-fast sea ice. Long-term temporal changes of the Antarctic land-fast sea ice distribution were analyzed during the period of 2000 to 2008 at multiple time scales. National Snow & Ice Data Center (NSIDC)-provided 250m MODIS Antarctic ice shelf images and high resolution Synthetic Aperture Radar (SAR) data (Radarsat 2) were used to validate the spatial distribution of the predicted land-fast sea ice.

  8. Singlet molecular oxygen on natural snow and ice

    NASA Astrophysics Data System (ADS)

    Bower, J. P.; Anastasio, C.

    2010-12-01

    Singlet molecular oxygen (1O2*) is a reactive intermediate formed when a chromophore absorbs light and subsequently transfers energy to dissolved oxygen. As an oxidant, 1O2* reacts rapidly with a number of electron-rich environmental pollutants. In our work, we show enhanced kinetics for 1O2* in frozen solutions, where its rate of formation (Rf) and steady state concentration ([1O2*]) can be many orders of magnitude higher than found in the same unfrozen solution. Our goal here is to identify the contribution of 1O2* to the decay of pollutants on snow and ice. We conducted experiments in laboratory solutions made to simulate the concentrations and characteristics of natural snow, as well as in natural snow collected in the Sierra Nevada mountains of California and at Summit, Greenland. Natural snow contains a mixture of inorganic salts and organic species that can function as sources and/or sinks for oxidants, as well as contribute colligative control on the volume of quasi-liquid layers that occur at the surface and grain boundaries of ice. In our experiments, solutions typically contained up to five components: (1) Furfuryl alcohol (FFA), a commonly used probe for 1O2*, (2) Rose Bengal (RB), a 1O2* sensitizer, (3) HOOH, a photochemical precursor for hydroxyl radical (●OH), (4) glycerol to simulate unknown, naturally occurring sinks for ●OH, and (5) sodium sulfate to control the total concentration of solutes. We illuminated samples in a temperature-controlled solar simulator and subsequently measured the loss of FFA using high performance liquid chromatography. To differentiate reactions of 1O2* from other sinks (e.g. ●OH), selective sink species were added to determine the fraction of FFA loss due to direct photolysis, reaction with 1O2*, and reaction with ●OH. We verified reactions of 1O2* with FFA by two methods. First, we utilized the kinetic solvent isotope effect, where an enhancement of FFA loss in a mixture of D2O/water is indicative 1O2* since [1O2*] is higher in D2O than it is in pure water. Secondly, we conducted tests looking at pyranone formed from the reaction of FFA + 1O2*. A combination of these methods will allow us to determine 1O2* kinetics in natural snow, where its sources and sinks are unknown. This research will help determine the importance of 1O2* to the decay of pollutants in cold regions.

  9. A theoretical model of ultraviolet light transmission through Antarctic Sea ice

    NASA Astrophysics Data System (ADS)

    Perovich, D. K.

    1993-12-01

    Much of the region of the Earth most affected by stratospheric ozone depletion is covered by a seasonal or perennial sea ice cover, which is the habitat of a productive and extensive sea ice microbial community. To assess the impact of enhanced incident ultraviolet irradiance on this community, a knowledge of the amount of light transmitted through a sea ice cover is necessary. A two-stream radiative transfer model is used to estimate the penetration of ultraviolet radiation through Antarctic sea ice. Sea ice optical properties were used as proxies to infer scattering and absorption coefficients at ultraviolet wavelengths. Case studies are reported for sea ice in McMurdo Sound and in the Weddell Sea. Values of spectral transmittance are computed as well as integrated transmitted UV-B, UV-A, biologically effective irradiance (BEI), and photosynthetically active radiation (PAR). UV-B light levels under meter-thick ice are a few percent of incident values. The presence of a snow cover results in a large decrease in transmitted ultraviolet. Snow and ice ameliorate the biological impact of enhanced levels of incident ultraviolet radiation by reducing the BEI relative to the PAR.

  10. Unlocking a Sea Ice Secret

    SciTech Connect

    Dr. Rachel Obbard

    2013-04-22

    Dr. Rachel Obbard and her research group from Dartmouth College traveled to the Antarctic to collect samples of sea ice. Next stop: the GeoSoilEnviroCARS x-ray beamline at the Advanced Photon Source at Argonne National Laboratory in Illinois. This U.S. Department of Energy Office of Science synchrotron x-ray research facility gave the Obbard team the frontier scientific tools they needed to study the path bromide takes as it travels from the ocean to the atmosphere.

  11. Measurements of thermal infrared spectral reflectance of frost, snow, and ice

    NASA Technical Reports Server (NTRS)

    Salisbury, John W.; D'Aria, Dana M.; Wald, Andrew

    1994-01-01

    Because much of Earth's surface is covered by frost, snow, and ice, the spectral emissivities of these materials are a significant input to radiation balance calculations in global atmospheric circulation and climate change models. Until now, however, spectral emissivities of frost and snow have been calculated from the optical constants of ice. We have measured directional hemispherical reflectance spectra of frost, snow, and ice from which emissivities can be predicted using Kirchhoff's law (e = 1-R). These measured spectra show that contrary to conclusions about the emissivity of snow drawn from previously calculated spectra, snow emissivity departs significantly from blackbody behavior in the 8-14 micrometer region of the spectrum; snow emissivity decreases with both increasing particle size and increasing density due to packing or grain welding; while snow emissivity increases due to the presence of meltwater.

  12. Measurements of thermal infrared spectral reflectance of frost, snow, and ice

    NASA Astrophysics Data System (ADS)

    Salisbury, John W.; D'Aria, Dana M.; Wald, Andrew

    1994-12-01

    Because much of Earth's surface is covered by frost, snow, and ice, the spectral emissivities of these materials are a significant input to radiation balance calculations in global atmospheric circulation and climate change models. Until now, however, spectral emissivities of frost and snow have been calculated from the optical constants of ice. We have measured directional hemispherical reflectance spectra of frost, snow, and ice from which emissivities can be predicted using Kirchhoff's law (e=1-R). These measured spectra show that contrary to conclusions about the emissivity of snow drawn from previously calculated spectra, snow emissivity departs significantly from blackbody behavior in the 8-14 μm region of the spectrum; snow emissivity decreases with both incresing particle size and increasing density due to packing or grain welding; while snow emissivity increases due to the presence of meltwater.

  13. Satellite Observations of Blowing Snow in and Around Antarctica: Implications for Ice Sheet Mass Balance and Atmospheric Chemistry

    NASA Astrophysics Data System (ADS)

    Palm, S. P.; Yang, Y.; Marshak, A.

    2014-12-01

    Blowing snow in the polar regions is known to be important for a variety of reasons including ice sheet mass balance, atmospheric water vapor transport, interpretation of paleoclimate records and atmospheric chemistry. Over Antarctica, persistent katabatic winds produce extreme blowing snow events often covering 100,000 square kilometers or more and reaching heights of 300-400 meters. New techniques of blowing snow detection using active and passive satellite data are providing a new understanding of the frequency, magnitude and spatial coverage of blowing snow over and around the Antarctic continent. Current research is utilizing these methods to obtain a nearly 10 year climatology of blowing snow events over Antarctica and estimate the amount of mass being blown off the continent and sublimated into the atmosphere on an annual basis. In addition, recent research indicates that blowing snow over sea ice may be important in the process of transporting seal salt aerosol into the atmosphere where it is implicated in the production of bromine compounds that strongly influence many aspects of tropospheric chemistry.

  14. C-band radar backscatter of sea ice in the Weddell Sea, Antarctica during the austral winter of 1992

    NASA Technical Reports Server (NTRS)

    Hosseinmostafa, R.; Drinkwater, Mark R.; Gogineni, S. P.; Dierking, W.

    1993-01-01

    A C-band ship-based scatterometer was used to measure the backscatter coefficient of sea ice in the Weddell Sea during June and July 1992. These are the first microwave scatterometer data ever to be collected in the Antarctic sea ice cover during the austral winter. The instrument was a frequency-modulated continuous-wave (FM-CW) radar altimeter modified by the University of Kansas Radar Systems and Remote Sensing Laboratory to perform backscatter measurements. Measurements were taken as part of a Jet Propulsion Laboratory experiment aboard the German ice research vessel F.S. Polarstern. Backscatter measurements were performed at incidence angles ranging from 17 to 65 degrees with VV and HV polarization as the Polarstern travelled from east to west across the central Weddell Sea. Backscatter measurements were made of several different types of ice sea including pancake, dark nilas, white nilas, grey, first-year and second-year ice. Periodic external calibrations were performed with the aid of a Luneberg Lens to enable absolute values of backscatter to be derived from the data. At each radar measurement location, in-situ measurements were made of snow and sea ice. Physical and chemical analyses of ice core and snow samples, together with high magnification photography of snow crystallography provide important information with which to develop physical models of the scattering systems. Meteorological information and oceanographic conditions were also recorded throughout the experiment. Many of the stations were chosen to coincide with periods of near-simultaneous or coincident imaging by the ERS-1 satellite Synthetic Aperture Radar (SAR). This enabled spaceborne imaging by the C-band SAR of areas of sea ice in which backscatter measurements were taken. This provides a valuable tool for interpretation of satellite SAR imagery from Antarctic sea ice in terms of the physical properties of the sea ice and snow. Preliminary results of the backscatter from the various ice types and their relation to the physical properties of sea ice are presented.

  15. Comparing springtime ice-algal chlorophyll a and physical properties of multi-year and first-year sea ice from the Lincoln Sea.

    PubMed

    Lange, Benjamin A; Michel, Christine; Beckers, Justin F; Casey, J Alec; Flores, Hauke; Hatam, Ido; Meisterhans, Guillaume; Niemi, Andrea; Haas, Christian

    2015-01-01

    With near-complete replacement of Arctic multi-year ice (MYI) by first-year ice (FYI) predicted to occur within this century, it remains uncertain how the loss of MYI will impact the abundance and distribution of sea ice associated algae. In this study we compare the chlorophyll a (chl a) concentrations and physical properties of MYI and FYI from the Lincoln Sea during 3 spring seasons (2010-2012). Cores were analysed for texture, salinity, and chl a. We identified annual growth layers for 7 of 11 MYI cores and found no significant differences in chl a concentration between the bottom first-year-ice portions of MYI, upper old-ice portions of MYI, and FYI cores. Overall, the maximum chl a concentrations were observed at the bottom of young FYI. However, there were no significant differences in chl a concentrations between MYI and FYI. This suggests little or no change in algal biomass with a shift from MYI to FYI and that the spatial extent and regional variability of refrozen leads and younger FYI will likely be key factors governing future changes in Arctic sea ice algal biomass. Bottom-integrated chl a concentrations showed negative logistic relationships with snow depth and bulk (snow plus ice) integrated extinction coefficients; indicating a strong influence of snow cover in controlling bottom ice algal biomass. The maximum bottom MYI chl a concentration was observed in a hummock, representing the thickest ice with lowest snow depth of this study. Hence, in this and other studies MYI chl a biomass may be under-estimated due to an under-representation of thick MYI (e.g., hummocks), which typically have a relatively thin snowpack allowing for increased light transmission. Therefore, we suggest the on-going loss of MYI in the Arctic Ocean may have a larger impact on ice-associated production than generally assumed. PMID:25901605

  16. Short-term sea ice forecasting: An assessment of ice concentration and ice drift forecasts using the U.S. Navy's Arctic Cap Nowcast/Forecast System

    NASA Astrophysics Data System (ADS)

    Hebert, David A.; Allard, Richard A.; Metzger, E. Joseph; Posey, Pamela G.; Preller, Ruth H.; Wallcraft, Alan J.; Phelps, Michael W.; Smedstad, Ole Martin

    2015-12-01

    In this study the forecast skill of the U.S. Navy operational Arctic sea ice forecast system, the Arctic Cap Nowcast/Forecast System (ACNFS), is presented for the period February 2014 to June 2015. ACNFS is designed to provide short term, 1-7 day forecasts of Arctic sea ice and ocean conditions. Many quantities are forecast by ACNFS; the most commonly used include ice concentration, ice thickness, ice velocity, sea surface temperature, sea surface salinity, and sea surface velocities. Ice concentration forecast skill is compared to a persistent ice state and historical sea ice climatology. Skill scores are focused on areas where ice concentration changes by ±5% or more, and are therefore limited to primarily the marginal ice zone. We demonstrate that ACNFS forecasts are skilful compared to assuming a persistent ice state, especially beyond 24 h. ACNFS is also shown to be particularly skilful compared to a climatologic state for forecasts up to 102 h. Modeled ice drift velocity is compared to observed buoy data from the International Arctic Buoy Programme. A seasonal bias is shown where ACNFS is slower than IABP velocity in the summer months and faster in the winter months. In February 2015, ACNFS began to assimilate a blended ice concentration derived from Advanced Microwave Scanning Radiometer 2 (AMSR2) and the Interactive Multisensor Snow and Ice Mapping System (IMS). Preliminary results show that assimilating AMSR2 blended with IMS improves the short-term forecast skill and ice edge location compared to the independently derived National Ice Center Ice Edge product.

  17. Springtime atmospheric transport controls Arctic summer sea-ice extent

    NASA Astrophysics Data System (ADS)

    Kapsch, Marie; Graversen, Rune; Tjernström, Michael

    2013-04-01

    The sea-ice extent in the Arctic has been steadily decreasing during the satellite remote sensing era, 1979 to present, with the highest rate of retreat found in September. Contributing factors causing the ice retreat are among others: changes in surface air temperature (SAT; Lindsay and Zhang, 2005), ice circulation in response to winds/pressure patterns (Overland et al., 2008) and ocean currents (Comiso et al., 2008), as well as changes in radiative fluxes (e.g. due to changes in cloud cover; Francis and Hunter, 2006; Maksimovich and Vihma, 2012) and ocean conditions. However, large interannual variability is superimposed onto the declining trend - the ice extent by the end of the summer varies by several million square kilometer between successive years (Serreze et al., 2007). But what are the processes causing the year-to-year ice variability? A comparison of years with an anomalously large September sea-ice extent (HIYs - high ice years) with years showing an anomalously small ice extent (LIYs - low ice years) reveals that the ice variability is most pronounced in the Arctic Ocean north of Siberia (which became almost entirely ice free in September of 2007 and 2012). Significant ice-concentration anomalies of up to 30% are observed for LIYs and HIYs in this area. Focusing on this area we find that the greenhouse effect associated with clouds and water-vapor in spring is crucial for the development of the sea ice during the subsequent months. In years where the end-of-summer sea-ice extent is well below normal, a significantly enhanced transport of humid air is evident during spring into the region where the ice retreat is encountered. The anomalous convergence of humidity increases the cloudiness, resulting in an enhancement of the greenhouse effect. As a result, downward longwave radiation at the surface is larger than usual. In mid May, when the ice anomaly begins to appear and the surface albedo therefore becomes anomalously low, the net shortwave radiation anomaly becomes positive. The net shortwave radiation contributes during the rest of the melting season to an enhanced energy flux towards the surface. These findings lead to the conclusion that enhanced longwave radiation associated with positive humidity and cloud anomalies during spring plays a significant role in initiating the summer ice melt, whereas shortwave-radiation anomalies act as an amplifying feedback once the melt has started. References: Lindsay, R. and J. Zhang. The thinning of Arctic Sea Ice, 19882003: Have We Passed a Tipping Point?. J. Clim. 18, 48794894 (2005). Overland, J. E., M. Wang and S. Salo. The recent Arctic warm period. Tellus 60A, 589-597 (2008). Comiso, J. C., C. L. Parkinson, R. Gersten and L. Stock. Accelerated Decline in the Arctic sea ice cover. Geophys. Res. Lett. 35, L01703 (2008). Francis, J. A. and E. Hunter. New Insight Into the Disappearing Arctic Sea Ice. EOS T. Am. Geophys. Un. 87, 509511 (2006). Maksimovich, E. and T. Vihma. The effect of heat fluxes on interannual variability in the spring onset of snow melt in the central Arctic Ocean. J. Geophys. Res. 117, C07012 (2012). Serreze, M. C., M. M. Holland and J. Stroeve. Perspectives on the Arctic's Shrinking Sea-Ice Cover. Science 315, 1533-1536 (2007).

  18. Modeled Trends in Antarctic Sea Ice Thickness

    NASA Technical Reports Server (NTRS)

    Holland, Paul R.; Bruneau, Nicolas; Enright, Clare; Losch, Martin; Kurtz, Nathan T.; Kwok, Ron

    2014-01-01

    Unlike the rapid sea ice losses reported in the Arctic, satellite observations show an overall increase in Antarctic sea ice concentration over recent decades. However, observations of decadal trends in Antarctic ice thickness, and hence ice volume, do not currently exist. In this study a model of the Southern Ocean and its sea ice, forced by atmospheric reanalyzes, is used to assess 1992-2010 trends in ice thickness and volume. The model successfully reproduces observations of mean ice concentration, thickness, and drift, and decadal trends in ice concentration and drift, imparting some confidence in the hindcasted trends in ice thickness. The model suggests that overall Antarctic sea ice volume has increased by approximately 30 cu km/yr (0.4%/ yr) as an equal result of areal expansion (20 x 10(exp 3) sq km/yr or 0.2%/yr) and thickening (1.5 mm/yr or 0.2%/yr). This ice volume increase is an order of magnitude smaller than the Arctic decrease, and about half the size of the increased freshwater supply from the Antarctic Ice Sheet. Similarly to the observed ice concentration trends, the small overall increase in modeled ice volume is actually the residual of much larger opposing regional trends. Thickness changes near the ice edge follow observed concentration changes, with increasing concentration corresponding to increased thickness. Ice thickness increases are also found in the inner pack in the Amundsen and Weddell Seas, where the model suggests that observed ice-drift trends directed toward the coast have caused dynamical thickening in autumn and winter. Modeled changes are predominantly dynamic in origin in the Pacific sector and thermodynamic elsewhere.

  19. Optical Thickness and Effective Radius Retrievals of Liquid Water Clouds over Ice and Snow Surface

    NASA Technical Reports Server (NTRS)

    Platnick, S.; King, M. D.; Tsay, S.-C.; Arnold, G. T.; Gerber, H.; Hobbs, P. V.; Rangno, A.

    1999-01-01

    Cloud optical thickness and effective radius retrievals from solar reflectance measurements traditionally depend on a combination of spectral channels that are absorbing and non-absorbing for liquid water droplets. Reflectances in non-absorbing channels (e.g., 0.67, 0.86 micrometer bands) are largely dependent on cloud optical thickness, while longer wavelength absorbing channels (1.6, 2.1, and 3.7 micrometer window bands) provide cloud particle size information. Retrievals are complicated by the presence of an underlying ice/snow surface. At the shorter wavelengths, sea ice is both bright and highly variable, significantly increasing cloud retrieval uncertainty. However, reflectances at the longer wavelengths are relatively small and may be comparable to that of dark open water. Sea ice spectral albedos derived from Cloud Absorption Radiometer (CAR) measurements during April 1992 and June 1995 Arctic field deployments are used to illustrate these statements. A modification to the traditional retrieval technique is devised. The new algorithm uses a combination of absorbing spectral channels for which the snow/ice albedo is relatively small. Using this approach, preliminary retrievals have been made with the MODIS Airborne Simulator (MAS) imager flown aboard the NASA ER-2 during FIRE-ACE. Data from coordinated ER-2 and University of Washington CV-580 aircraft observations of liquid water stratus clouds on June 3 and June 6, 1998 have been examined. Size retrievals are compared with in situ cloud profile measurements of effective radius made with the CV-580 PMS FSSP probe, and optical thickness retrievals are compared with extinction profiles derived from the Gerber Scientific "g-meter" probe. MAS retrievals are shown to be in good agreement with the in situ measurements.

  20. Quantifying Uncertainties in the Seasonal Cycle of Arctic Sea Ice

    NASA Astrophysics Data System (ADS)

    Lucas, D. D.; Covey, C. C.; Klein, R.; Tannahill, J.; Ivanova, D. P.

    2013-12-01

    Many climate models project that the Arctic Ocean will be free of summertime sea ice within a century when forced with representative future greenhouse gas emission scenarios. To determine whether uncertainties in sea ice physics can also lead to an ice-free Arctic, we ran present-day ensemble simulations with the Community Climate System Model (CCSM4) that varied 7 parameters in the Community Ice Code (CICE4) over expert-provided ranges. The September minimum in sea ice extent computed by the ensemble ranges from 0.5 to 7.7 million km2, the lower end of which is significantly less than current observed values and lower than the models in the Coupled Model Intercomparison Project Phase 5 (CMIP5). CCSM4 can therefore simulate a summertime Arctic that is effectively free of sea ice either by increasing greenhouse gas forcing or by keeping the forcing constant and varying CICE4 parameters within recommended ranges. We identified three key CICE4 parameters related to radiative and thermal properties of snow that drive this extreme ensemble variability. Given observational data, machine learning algorithms were also used to quantify and constrain probability distribution functions for these parameters, which can be sampled to provide probabilistic assessments of sea ice characteristics simulated by CICE4. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 and was funded by the Uncertainty Quantification Strategic Initiative Laboratory Directed Research and Development Project at LLNL under project tracking code 10-SI-013 (UCRL LLNL-ABS-641752).

  1. Role of Ice Dynamics in the Sea Ice Mass Balance

    NASA Astrophysics Data System (ADS)

    Hutchings, Jennifer; Geiger, Cathleen; Roberts, Andrew; Richter-Menge, Jacqueline; Doble, Martin; Forsberg, Rene; Giles, Katharine; Haas, Christian; Hendricks, Stefan; Khambhamettu, Chandra; Laxon, Seymour; Martin, Torge; Pruis, Matthew; Thomas, Mani; Wadhams, Peter; Zwally, H. Jay

    2008-12-01

    Over the past decade, the Arctic Ocean and Beaufort Sea ice pack has been less extensive and thinner than has been observed during the previous 35 years [e.g., Wadhams and Davis, 2000; Tucker et al., 2001; Rothrock et al., 1999; Parkinson and Cavalieri, 2002; Comiso, 2002]. During the summers of 2007 and 2008, the ice extents for both the Beaufort Sea and the Northern Hemisphere were the lowest on record. Mechanisms causing recent sea ice change in the Pacific Arctic and the Beaufort Sea are under investigation on many fronts [e.g., Drobot and Maslanik, 2003; Shimada et al., 2006]; the mechanisms include increased ocean surface warming due to Pacific Ocean water inflow to the region and variability in meteorological and surface conditions. However, in most studies addressing these events, the impact of sea ice dynamics, specifically deformation, has not been measured in detail.

  2. Recent Advances in Satellite and Airborne Altimetry over Arctic Sea Ice

    NASA Astrophysics Data System (ADS)

    Farrell, S. L.; Newman, T.; Richter-Menge, J.; Haas, C.; Petty, A.; McAdoo, D. C.; Connor, L. N.

    2014-12-01

    Over the last two decades altimeters on satellite and aircraft platforms have revolutionized our understanding of Arctic sea ice mass balance. Satellite laser and radar altimeters provide unique measurements of sea ice elevation, from which ice thickness may be derived, across basin scales and interdecadal time periods. Meanwhile airborne altimetry, together with high-resolution digital imagery, provides a range of novel observations that describe key features of the ice pack including its snow cover, surface morphology and deformation characteristics. We provide an update on current Arctic sea ice thickness conditions based on IceBridge measurements, discussing these in the context of previously observed decadal change. Fundamental to the goal of understanding interannual variability, and monitoring long-term trends in sea ice volume, is the accurate characterization of measurement uncertainty. This is particularly true when linking observations from different sensors. We discuss recent advances in tracking and quantifying the major components of the altimetric sea ice thickness error budget. We pay particular attention to two major components of the error: freeboard and snow loading uncertainty. We describe novel measurement techniques that are helping to reduce measurement uncertainty and allowing, for the first time, quantification of errors with respect to ice type.

  3. Seasonal change of antarctic sea ice cover.

    PubMed

    Gordon, A L; Taylor, H W

    1975-01-31

    The winter expansion of the sea ice surrounding Antarctica and the subsequent retreat of the ice in summer may be linked with the wind stress acting on the Southern Ocean in conjunction with the heat exchange in open water regions within the ice fields. PMID:17814267

  4. Coupling GELATO 4 sea-ice model to NEMO 3: a new ocean/sea-ice model for global climate studies at CNRM

    NASA Astrophysics Data System (ADS)

    Chevallier, Matthieu; Salas-Melia, David

    2010-05-01

    A new configuration of the ocean-sea ice model in use at the Centre National de Recherches Mtorologiques (CNRM, Mto-France, France) is presented. The sea-ice component of the global coupled model is an updated version of GELATO (Salas-Melia, 2002). GELATO is a dynamic-thermodynamic model, and includes elastic-visco-plastic rheology, redistribution of ice floes of different thicknesses, and also takes into account leads, snow cover and snow ice formation. The new version of GELATO sea-ice model includes also a tracer of ice age. GELATO 4 is coupled to the NEMO3.3 global ocean model (Madec et al., 2008), a hydrostatic, primitive equation, finite difference ocean model in the 1-configuration ORCA1. In this new configuration, the straits in the Arctic Ocean are opened, leading to more realistic features in the sea-ice state compared to previous systems. Model performance is evaluated by performing a hindcast of the Arctic and Antarctic sea-ice covers, forced by the ERA40-based atmospheric forcing DFS4 (DRAKKAR Forcing Set 4, Brodeau et al., 2009) during the 1958-2004 period. To test the impact of a more refined description of melting sea-ice surface albedo, a new sea-ice albedo scheme was also implemented in GELATO. The scheme is based on Pedersen et al.(2009) parametrization, and includes melt ponds evolution. Performance with this latter refinement is also evaluated. The NEMO3.3-GELATO4 model is meant to be used at CNRM for Coupled Model Intercomparison Project phase 5 (CMIP5) experiments, and also for investigations dealing with seasonal-to-decadal predictability in the Arctic.

  5. Antarctic Sea Ice in the IPY

    NASA Astrophysics Data System (ADS)

    Ackley, S. F.; Perovich, D. K.; Geiger, C. A.

    2003-12-01

    Antarctic Sea Ice covers an area of 20 million km2 at maximum extent and therefore represents an areal coverage larger than either the Arctic ice cover or the Antarctic continent. Studies of Antarctic sea ice in the modern era were only initiated well after the IGY, with the advent of passive microwave satellite coverage in 1973, followed by the use of several countries icebreaking research vessels over the last two decades. Useful knowledge of basic ice thickness, properties and processes is being addressed by an ice observations programs and several process studies, but the scale of activity is well below that conducted for the Arctic ice cover. The absence of submarine activity in the Antarctic which has provided large scale information on the changing Arctic ice thickness distribution is particularly notable as a critical measurement in understanding climate impact. As well, only two short term drift stations (Ice Station Weddell in 1992 and Ice Station Polarstern in 2004) have or will provide limited time series information on sea ice and ocean processes compared to multiple drift stations and yearlong experiments in the Arctic, dating back to IGY. The two technologies of Autonomous Underwater Vehicles specifically designed for long-range ice operations (500km) (e.g. Autosub Under Ice) and the recently developed international icebreaking research vessel capability for the Antarctic therefore gives an opportunity for two International Polar Year programs to provide critical information for the Antartic sea ice cover commensurate with our knowledge of the Arctic. The proposed programs are: 1. A circumpolar survey of the Antarctic sea ice thickness distribution at near maximum extent using two ship-based autonomous underwater vehicles and several countries' icebreakers. 2. An International Ice Drifting Station in the Bellingshausen-Amundsen-Ross Sea using icebreakers and drifting buoys to characterize the sea ice, ocean and climate in this unknown region of Antarctic multiyear ice. These measurements will provide directly comparable measurements to those of the Arctic Ocean' ice cover as well as a year-long snapshot of ice, ocean and climate conditions useful for numerical model verification for climate change prediction. New venues for training and experience of oceanographers, climate and sea ice scientists, and numerical modelers will also be provided to examine the many future opportunites in the Antarctic.

  6. ICESat Observations of Seasonal and Interannual Variations of Sea-Ice Freeboard and Estimated Thickness in the Weddell Sea, Antarctica (2003-2009)

    NASA Technical Reports Server (NTRS)

    Yi, Donghui; Robbins, John W.

    2010-01-01

    Sea-ice freeboard heights for 17 ICESat campaign periods from 2003 to 2009 are derived from ICESat data. Freeboard is combined with snow depth from Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) data and nominal densities of snow, water and sea ice, to estimate sea-ice thickness. Sea-ice freeboard and thickness distributions show clear seasonal variations that reflect the yearly cycle of growth and decay of the Weddell Sea (Antarctica) pack ice. During October-November, sea ice grows to its seasonal maximum both in area and thickness; the mean freeboards are 0.33-0.41 m and the mean thicknesses are 2.10-2.59 m. During February-March, thinner sea ice melts away and the sea-ice pack is mainly distributed in the west Weddell Sea; the mean freeboards are 0.35-0.46 m and the mean thicknesses are 1.48-1.94 m. During May-June, the mean freeboards and thicknesses are 0.26-0.29 m and 1.32-1.37 m, respectively. The 6 year trends in sea-ice extent and volume are (0.023+/-0.051) x 10(exp 6)sq km/a (0.45%/a) and (0.007+/-1.0.092) x 10(exp 3)cu km/a (0.08%/a); however, the large standard deviations indicate that these positive trends are not statistically significant.

  7. A toy model of sea ice growth

    NASA Technical Reports Server (NTRS)

    Thorndike, Alan S.

    1992-01-01

    My purpose here is to present a simplified treatment of the growth of sea ice. By ignoring many details, it is possible to obtain several results that help to clarify the ways in which the sea ice cover will respond to climate change. Three models are discussed. The first deals with the growth of sea ice during the cold season. The second describes the cycle of growth and melting for perennial ice. The third model extends the second to account for the possibility that the ice melts away entirely in the summer. In each case, the objective is to understand what physical processes are most important, what ice properties determine the ice behavior, and to which climate variables the system is most sensitive.

  8. Antarctic sea ice thickness affects algae populations

    NASA Astrophysics Data System (ADS)

    Schultz, Colin

    2013-01-01

    In the waters off Antarctica, algae grow and live in the sea ice that surrounds the southern continent—a floating habitat sure to change as the planet warms. As with most aquatic ecosystems, microscopic algae form the base of the Southern Ocean food web. Distinct algae populations reside in the sea ice surface layers, on the ice's underside, and within the floating ice itself. The algae that reside on the floating ice's underside are particularly important for the region's krill population, while those on the interior or surface layers are less accessible. Understanding how changing sea ice properties will affect the regional biology, then, depends on understanding how algae populations interact with the ice.

  9. Uncertainty quantification and global sensitivity analysis of the Los Alamos sea ice model

    NASA Astrophysics Data System (ADS)

    Urrego-Blanco, Jorge R.; Urban, Nathan M.; Hunke, Elizabeth C.; Turner, Adrian K.; Jeffery, Nicole

    2016-04-01

    Changes in the high-latitude climate system have the potential to affect global climate through feedbacks with the atmosphere and connections with midlatitudes. Sea ice and climate models used to understand these changes have uncertainties that need to be characterized and quantified. We present a quantitative way to assess uncertainty in complex computer models, which is a new approach in the analysis of sea ice models. We characterize parametric uncertainty in the Los Alamos sea ice model (CICE) in a standalone configuration and quantify the sensitivity of sea ice area, extent, and volume with respect to uncertainty in 39 individual model parameters. Unlike common sensitivity analyses conducted in previous studies where parameters are varied one at a time, this study uses a global variance-based approach in which Sobol' sequences are used to efficiently sample the full 39-dimensional parameter space. We implement a fast emulator of the sea ice model whose predictions of sea ice extent, area, and volume are used to compute the Sobol' sensitivity indices of the 39 parameters. Main effects and interactions among the most influential parameters are also estimated by a nonparametric regression technique based on generalized additive models. A ranking based on the sensitivity indices indicates that model predictions are most sensitive to snow parameters such as snow conductivity and grain size, and the drainage of melt ponds. It is recommended that research be prioritized toward more accurately determining these most influential parameter values by observational studies or by improving parameterizations in the sea ice model.

  10. What Can Sea Ice Reconstructions Tell Us About Recent Regional Trends in Sea Ice Around Antarctica?

    NASA Astrophysics Data System (ADS)

    Abram, N.; Mulvaney, R.; Murphy, E. J.

    2014-12-01

    Satellite observations of recent sea ice changes around Antarctica reveal regionally heterogeneous trends, but with an overall increasing trend in Antarctic-wide sea ice extent. Proposed mechanisms to account for increasing sea ice extent around Antarctica include freshening of the ocean surface due to melting of land ice and northward wind drift associated with strengthening of the Southern Ocean westerly winds. In this study we use extended, regional reconstructions of Antarctic sea ice changes from ice core chemistry and reanalysis of the South Orkney fast ice series to examine long-term relationships between Antarctic regional sea ice changes and surface winds. The formation and breakout of fast ice at the South Orkney islands (Murphy et al., 2014) indicates that westerly wind strength is an important factor in determining spring sea ice retreat in the Weddell Sea region. In contrast, autumn sea ice formation is more strongly influenced by long-lived ocean temperature anomalies and sea ice migration from the previous year, highlighting the multiple influences that act at different times of the year to determine the overall extent of winter sea ice. To assess the hypothesized role of westerly wind changes in driving opposing patterns of recent sea ice change between the Ross Sea and Bellingshausen Sea, we also present a comparison of ice core MSA evidence for sea ice changes derived from the James Ross Island (Mulvaney et al., 2012) and Erebus Saddle (Rhodes et al., 2012) ice cores, and view this in the context of trends in the Southern Annular Mode (Abram et al., 2014) over the last 200 years. References: Abram et al., 2014. Evolution of the Southern Annular Mode over the past millennium. Nature Climate Change. doi: 10.1038/nclimate2235 Mulvaney et al., 2012. Recent Antarctic Peninsula warming relative to Holocene temperature and ice-shelf history. Nature. doi: 10.1038/nature11391 Murphy et al., 2014. Variability of sea ice in the northern Weddell Sea during the 20th century. Journal of Geophysical Research. doi: 10.1002/2013JC009511 Rhodes et al., 2012. Little Ice Age climate and oceanic conditions of the Ross Sea, Antarctica, from a coastal ice core record. Climate of the Past. doi: 10.5194/cp-8-1223-2012

  11. Comparing Springtime Ice-Algal Chlorophyll a and Physical Properties of Multi-Year and First-Year Sea Ice from the Lincoln Sea

    PubMed Central

    Lange, Benjamin A.; Michel, Christine; Beckers, Justin F.; Casey, J. Alec; Flores, Hauke; Hatam, Ido; Meisterhans, Guillaume; Niemi, Andrea; Haas, Christian

    2015-01-01

    With near-complete replacement of Arctic multi-year ice (MYI) by first-year ice (FYI) predicted to occur within this century, it remains uncertain how the loss of MYI will impact the abundance and distribution of sea ice associated algae. In this study we compare the chlorophyll a (chl a) concentrations and physical properties of MYI and FYI from the Lincoln Sea during 3 spring seasons (2010-2012). Cores were analysed for texture, salinity, and chl a. We identified annual growth layers for 7 of 11 MYI cores and found no significant differences in chl a concentration between the bottom first-year-ice portions of MYI, upper old-ice portions of MYI, and FYI cores. Overall, the maximum chl a concentrations were observed at the bottom of young FYI. However, there were no significant differences in chl a concentrations between MYI and FYI. This suggests little or no change in algal biomass with a shift from MYI to FYI and that the spatial extent and regional variability of refrozen leads and younger FYI will likely be key factors governing future changes in Arctic sea ice algal biomass. Bottom-integrated chl a concentrations showed negative logistic relationships with snow depth and bulk (snow plus ice) integrated extinction coefficients; indicating a strong influence of snow cover in controlling bottom ice algal biomass. The maximum bottom MYI chl a concentration was observed in a hummock, representing the thickest ice with lowest snow depth of this study. Hence, in this and other studies MYI chl a biomass may be under-estimated due to an under-representation of thick MYI (e.g., hummocks), which typically have a relatively thin snowpack allowing for increased light transmission. Therefore, we suggest the on-going loss of MYI in the Arctic Ocean may have a larger impact on ice–associated production than generally assumed. PMID:25901605

  12. Sea Ice Biogeochemistry: A Guide for Modellers

    PubMed Central

    Tedesco, Letizia; Vichi, Marcello

    2014-01-01

    Sea ice is a fundamental component of the climate system and plays a key role in polar trophic food webs. Nonetheless sea ice biogeochemical dynamics at large temporal and spatial scales are still rarely described. Numerical models may potentially contribute integrating among sparse observations, but available models of sea ice biogeochemistry are still scarce, whether their relevance for properly describing the current and future state of the polar oceans has been recently addressed. A general methodology to develop a sea ice biogeochemical model is presented, deriving it from an existing validated model application by extension of generic pelagic biogeochemistry model parameterizations. The described methodology is flexible and considers different levels of ecosystem complexity and vertical representation, while adopting a strategy of coupling that ensures mass conservation. We show how to apply this methodology step by step by building an intermediate complexity model from a published realistic application and applying it to analyze theoretically a typical season of first-year sea ice in the Arctic, the one currently needing the most urgent understanding. The aim is to (1) introduce sea ice biogeochemistry and address its relevance to ocean modelers of polar regions, supporting them in adding a new sea ice component to their modelling framework for a more adequate representation of the sea ice-covered ocean ecosystem as a whole, and (2) extend our knowledge on the relevant controlling factors of sea ice algal production, showing that beyond the light and nutrient availability, the duration of the sea ice season may play a key-role shaping the algal production during the on going and upcoming projected changes. PMID:24586604

  13. CryoVEx 2011: In-situ sea ice measurements in the high Arctic Ocean for the validation of CryoSat-2 ice thickness retrievals

    NASA Astrophysics Data System (ADS)

    Haas, C.; Willatt, R. C.; Laxon, S. W.; Giles, K. A.; Beckers, J.; Hendricks, S.; Davidson, M.

    2011-12-01

    The European Space Agency (ESA) CryoSat-2 satellite, which was launched in April 2010, is designed to measure changes in the thickness of the polar ice caps. By means of radar altimetry, CryoSat-2 performs accurate measurements of sea ice freeboard, the height of the ice surface above the water level, which is related to ice thickness via isostasy. From this, ice thickness can be estimated when assumptions are made about the density of snow and ice as well as about the thickness of snow and radar penetration into the snow. There are thus many sources of uncertainty related to the physical properties of snow and ice which may lead to significant errors in the satellite-retrieved ice thickness. Some of these uncertainties can be addressed through in-situ measurements. These were performed during CryoVEx 2011, an international project sponsored and coordinated by ESA and other funding agencies. Three sites with different ice and snow properties were studied between the coast of Ellesmere Island, Canada, and 85.5°N. These sites were visited by Twin Otter airplane landing on unprepared landing strips. At each site, corner reflectors to be used as references for airborne radar altimeter surveys were deployed and marked with drifting GPS buoys, and extensive snow and ice measurements were performed between the corner reflectors. Very high-resolution measurements were carried out in the immediate vicinity of the corner reflectors, including snow pit studies and measurements of radar penetration using a ground-based radar. Subsequently, the sites were overflown by aircraft carrying radar altimeters and ice thickness sensors. This presentation will review the validation concept implemented in the campaign and will summarize the snow and ice properties obtained at the different sites.

  14. Air- ice-snow interaction in the Northern Hemisphere under different stability conditions

    NASA Astrophysics Data System (ADS)

    Repina, Irina; Chechin, Dmitry; Artamonov, Arseny

    2013-04-01

    The traditional parameterizations of the atmospheric boundary layer are based on similarity theory and the coefficients of turbulent transfer, describing the atmospheric-surface interaction and the diffusion of impurities in the operational models of air pollution, weather forecasting and climate change. Major drawbacks of these parameterizations is that they are not applicable for the extreme conditions of stratification and currents over complex surfaces (such as sea ice, marginal ice zone or stormy sea). These problem could not be overcome within the framework of classical theory, i.e, by rectifying similarity functions or through the introduction of amendments to the traditional turbulent closure schemes. Lack of knowledge on the structure of the surface air layer and the exchange of momentum, heat and moisture between the rippling water surface and the atmosphere at different atmospheric stratifications is at present the major obstacle which impede proper functioning of the operational global and regional weather prediction models and expert models of climate and climate change. This is especially important for the polar regions, where in winter time the development of strong stable boundary layer in the presence of polynyas and leads usually occur. Experimental studies of atmosphere-ice-snow interaction under different stability conditions are presented. Strong stable and unstable conditions are discussed. Parametrizations of turbulent heat and gas exchange at the atmosphere ocean interface are developed. The dependence of the exchange coefficients and aerodynamic roughness on the atmospheric stratification over the snow and ice surface is experimentally confirmed. The drag coefficient is reduced with increasing stability. The behavior of the roughness parameter is simple. This result was obtained in the Arctic from the measurements over hummocked surface. The value of the roughness in the Arctic is much less than that observed over the snow in the middle and even high latitudes of the Northern Hemisphere because the stable conditions above Arctic ice field dominate. Under such conditions the air flow over the uneven surface behaves in the way it does over the even one. This happens because depressions between ridges are filled with heavier air up to the height of irreguralities. As a result, the air moves at the level of ridges without entering depressions. Increased heat and mass transfer over polynyas and leads through self-organization of turbulent convection is found. The work was sponsored by RFBR grants and funded by the Government of the Russian Federation grants.

  15. Simulation of a sea ice ecosystem using a hybrid model for slush layer desalination

    NASA Astrophysics Data System (ADS)

    Saenz, Benjamin T.; Arrigo, Kevin R.

    2012-05-01

    Porous, slushy layers are a common feature of Antarctic sea ice and are often colonized by high concentrations of algae. Despite its potential importance to the physics and biogeochemistry of the sea ice ecosystem, current knowledge of the evolution of sea ice slush layers is limited. Here we present a model of sea ice that is capable of reproducing the vertical biophysical evolution of sea ice that contains slush layers. The model uses a novel hybrid desalination scheme to calculate salt fluxes and brine motion during freezing using one of two different methods depending on the brine fraction of the ice. Model runs using atmospheric and snow depth forcing from the Ice Station Weddell experiment show that model is able to simulate the magnitude and timing of sea ice temperature, salinity, and associated algal growth of observed slush layers, as well as the surrounding sea ice. The model was designed with regional-scale simulations in mind and we show that the model performs well at lower vertical resolutions, as long as the slush layer is resolved. Incorporation of our model of slush ice desalination into regional and global simulations has potential to improve model estimates of salt, heat, and biochemical fluxes in polar marine environments.

  16. NOx emission from surface snow and ice over Tibetan Plateau, China

    NASA Astrophysics Data System (ADS)

    Wang, J.; Zhu, T.; Lin, W.; Wang, F.

    2010-12-01

    Photochemical reactions on the surface of snow and ice have been proved to be an important NOx source in the polar boundary layer. The exchanges of NOx between snow and air have significant impacts on the atmospheric components and photochemical processes in the overlying boundary layer, which can increase the oxidizing capacity and may impact on the environmental records that are retrieved from ice cores. The Tibetan Plateau (TP) is the main snow-covered area in the mid-latitudes of northern hemisphere. Different from the Arctic and Antarctic, TP has strong UV radiation on the surface of snow and ice due to its high altitude and the large area of snow and glaciers. With four field measurements in July 1st Glacier, Mount Everest Area, Yulong Snow Mountain, and Tianshan NO.1 Glacier, we obtained observational evidences on the release of NOx from surface snow and ice over Tibetan Plateau. The average NOx concentration during daytime was 1-5 ppbv, this is much higher than that in Arctic and Antarctic (pptv level). Besides the photochemical reaction and transfer process within snow/ice, factors such as UV radiation intensity, temperature, snow characteristics and mountain-valley winds all affect NOx release processes from those snow covered areas. The NOx fluxes during daytime in Yulong Snow Mountain and Tianshan NO.1 Glacier were about 10-45nmol m-2 h-1, this is similar as those observed in Arctic and Antarctic (15-40 nmol m-2 h-1). The contribution of NOx emission from snow/ice over Tibetan Plateau to the atmosphere oxidizing capacity needs more research.

  17. Ice Sheet and Sea Ice Observations from Unmanned Aircraft Systems

    NASA Astrophysics Data System (ADS)

    Crocker, R. I.; Maslanik, J. A.

    2011-12-01

    A suite of sensors has been assembled to map ice sheet and sea ice surface topography with fine-resolution from small unmanned aircraft systems (UAS). This payload is optimized to provide coincident surface elevation and imagery data, and with its low cost and ease of reproduction, it has the potential to become a widely-distributed observational resource to complement polar manned-aircraft and satellite missions. To date, it has been deployed to map ice sheet elevations near Jakobshavn Isbræ in Greenland, and to measure sea ice freeboard and roughness in Fram Strait off the coast of Svalbard. Data collected during these campaigns have facilitate a detailed assessment of the system's surface elevation measurement accuracy, and provide a glimpse of the summer 2009 Fram Strait sea ice conditions. These findings are presented, along with a brief overview of our future Arctic UAS operations.

  18. Physical control of chlorophyll a, POC, and TPN distributions in the pack ice of the Ross Sea, Antarctica

    NASA Astrophysics Data System (ADS)

    Arrigo, Kevin R.; Robinson, Dale H.; Dunbar, Robert B.; Leventer, Amy R.; Lizotte, Michael P.

    2003-10-01

    The pack ice ecosystem of the Ross Sea was investigated along a 1470-km north-south transect during the spring 1998 oceanographic program Research on Ocean-Atmosphere Variability and Ecosystem Response in the Ross Sea (ROAVERRS). Snow and sea ice thickness along the transect varied latitudinally, with thinner snow and ice at the northern ice edge and thin new ice in the vicinity of the Ross Sea polynya. Relative to springtime observations in other sea ice regions, algal chlorophyll a (Chl a) concentrations were low. In contrast, particulate organic carbon (POC), total particulate nitrogen (TPN), and POC:Chl a were all high, indicating either that the ice contained substantial amounts of detritus or nonphotosynthetic organisms, or that the algae had a high POC:Chl a ratio. The abundance of Chl a, POC, and TPN in the sea ice was related to ice age and thickness, as well as to snow depth: older ice had thinner snow cover and contained higher algal biomass while new ice in the polynya had lower biomass. Older pack ice was dominated by diatoms (particularly Fragilariopsis cylindrus) and had vertical distributions of Chl a, POC, and TPN that were related to salinity, with higher biomass at the ice-water interface. Fluorescence-based measurements of photosynthetic competence (Fv/Fm) were higher at ice-water interfaces, and photosynthesis-irradiance characteristics measured for bottom ice algae were comparable to those measured in pack ice communities of other regions. Nutrient concentrations in extracted sea ice brines showed depletion of silicate and nitrate, depletion or regeneration of phosphate and nitrite, and production of ammonium when normalized to seawater salinity; however, concentrations of dissolved inorganic nitrogen, phosphorous, and silica were typically above levels likely to limit algal growth. In areas where pack ice and snow cover were thickest, light levels could be limiting to algal photosynthesis. Enrichment of δ13C-POC in the sea ice was correlated with the accumulation of POC, suggesting that carbon sources for photosynthesis might shift in response to decreasing CO2 supply. Comparisons between new ice and underlying waters showed similar algal species dominance (Phaeocystis antarctica) implying incorporation of phytoplankton, with substantially higher POC and TPN concentrations in the ice.

  19. Development of a Seismic Snow Streamer and Use of Multi- Offset Reflection for Determining Glacier Ice Properties

    NASA Astrophysics Data System (ADS)

    Velez Gonzalez, Jose A.

    Glaciers and ice sheets are important to climate research due to their role in controlling worldwide weather and temperature patterns as well as their potential impact in sea level rise. Because of this, scientists are attempting to model large ice sheets and important fast flowing glaciers. These models are limited in large part to the lack of data which govern the nonlinear behavior of ice flow. Seismic data acquisition can provide high resolution data which can be used to extract information of variables like bed topography, ice temperature and preferred ice crystal orientation. But seismic data acquisition in polar environments is challenging. This is mainly due to the labor intensive process of manually hand planting geophones. In order to improve the efficiency of active source seismic reflection data acquisition in polar environments, two prototype seismic snow-streamers were constructed for this investigation and optimized for deployment in remote locations. The first snow-streamer (experimental snow-streamer) was field tested in the Jakobshavn Glacier located in central western Greenland. The experimental snow-streamer was equipped with multiple geophone configurations and two plate materials. Twenty-two variable angle records were collected using the stationary snow streamer in the center of the survey. The source consisted of 0.5 kg of explosives buried 10 m below the snow surface at 160 m intervals. The resultant data set consisted of offsets ranging from -1760 to +1600 m and the ice-bed interface as well as two internal ice layers were imaged at approximately 1.85, 1.5 and 1.7 km depth respectively. The snow-streamer data was simultaneously collected with a mirror arrangement of hand planted buried geophones in order to test for the effects of plate weight, wind noise, geophone burial and plate to snow coupling in the seismic signal. The signal analysis and the comparison of streamer vs. buried geophones showed that geophone burial can degrade the seismic signal while the wind and signal analysis revealed that the best snow-streamer configuration was a combination of aluminum plates with vertical geophones. Using these results a second 480m full scale snow-streamer was tested in the Thwaites Glacier Antarctica. The snow-streamer data was simultaneously collected with a mirrored arrangement of surface planted and buried geophones. The trace by trace comparison revealed higher signal to noise in the data collected using the snow-streamer when compared to the surface planted and buried geophones. The full scale snow-streamer was easy to maneuver, very light and could be pulled in speeds up to 15 km/h. The use of the snow-streamer proved to be an efficient data acquisition tool, yielding high quality data. Therefore the use of snow-streamers can represent a significant improvement in the efficiency of seismic data acquisition in polar environments opening the possibility of determining important ice column properties for areas of interest. An important parameter affecting glacier flow is preferred ice crystal orientation. Seismic waves in ice travel up to 5% faster along the c-axis than when travelling perpendicular to it. Therefore, reflected seismic wave slowness (inverse of the velocity) variability as a function of angle of incidence can be used to detect anisotropy in ice crystal orientation. By combining the multi-offset seismic reflection data set acquired with the experimental snow-streamer and a 2D seismic reflection profile simultaneously collected for the same location, we investigated the presence of preferred ice crystal orientation for the area of study on the Jakobshavn Glacier. The combination of both data sets allowed the approximation of the average ray velocity as a function of angle of incidence. Given that the seismic velocity varies as a function of ice crystal orientation, we can use an existing model to relate the variation of seismic velocity as a function of offset to estimate the mean ice crystal orientation for the bed and imaged internal layers in terms of a conical c-axes distribution. Based on the anisotropy analysis we concluded that the upper 1640 m of the ice column consists mostly of isotropic. The lower 300 m of the ice column is characterized by ice with preferred ice crystal orientation. These observations are consistent with laterally extensive complex ice fabric development reported over the same region of Jakobshavn Glacier.

  20. Investigation of radar discrimination of sea ice

    NASA Technical Reports Server (NTRS)

    Parashar, S. K.; Biggs, A. W.; Fung, A. K.; Moore, R. K.

    1974-01-01

    The ability of radar to discriminate sea ice types and their thickness was studied. Radar backscatter measurements at 400 MHz (multi-polarization) and 13.3 GHz (VV polarization) obtained from NASA Earth Resources Aircraft Program Mission 126 were analyzed in detail. The scatterometer data were separated into seven categories of sea ice according to age and thickness as interpreted from stereo aerial photographs. The variations of radar backscatter cross-section with sea ice thickness at various angles are presented at the two frequencies. There is a reversal of angular character of radar return from sea ice less than 18 cm thick at the two frequencies. Multi-year ice (sea ice greater than 180 cm thick) gives strongest return at 13.3 GHz. First-year ice (30 cm to 90 cm thick) gives strongest return at 400 MHz. Open water can be differentiated at both the frequencies. Four-polarization 16.5 GHz radar imagery was also obtained. Open water and three categories of sea ice can be identified on the images. The results of the imagery analysis are consistent with the radar scatterometer results.

  1. Direct measurements of DMS flux from Antarctic fast sea ice to the atmosphere by a chamber technique

    NASA Astrophysics Data System (ADS)

    Nomura, Daiki; Koga, Seizi; Kasamatsu, Nobue; Shinagawa, Hideo; Simizu, Daisuke; Wada, Makoto; Fukuchi, Mitsuo

    2012-04-01

    We present the first direct measurements of dimethylsulfide (DMS) emissions from Antarctic sea ice to the atmosphere during the seasonal warming period obtained using a chamber technique. Estimated DMS fluxes measured over the snow and superimposed ice (ice formed by the freezing of snow meltwater) were from 0.1 to 0.3 μmol m-2 d-1. The DMS fluxes measured directly over the sea-ice slush layer after removal of the snow and superimposed ice, ranged from 0.1 to 5.3 μmol m-2 d-1, were large compared to those measured over the snow and superimposed ice. The DMS concentrations in slush water ranged from 1.0 to 103.7 nM. The DMS fluxes increased with increasing DMS concentrations in slush water. Our results indicate that the potential DMS flux measured over the slush layer occurred originally from the slush layer, and was dependent on the DMS concentrations in slush water. However, snow accumulation and the formation of superimposed ice over the slush layer significantly blocks the diffusion of DMS to the atmosphere, with the result that DMS tends to accumulate in the slush layer although the removal process of DMS by photolysis reaction can modify the DMS flux from the slush layer. Hence, the slush layer has the potential to release the DMS to the atmosphere and ocean when the snow and superimposed ice melts.

  2. Geostatistical Relationships Between Freeboard and Thickness of Antarctic Sea Ice Floes Derived from Terrestrial LiDAR Surveys

    NASA Astrophysics Data System (ADS)

    Lewis, M. J.; Parra, J.; Weissling, B.; Ackley, S. F.; Maksym, T. L.; Wilkinson, J.; Wagner, T.

    2011-12-01

    Sea ice is a critical component of the Earth's climate system and is a highly complex media. The physical characteristics are important in interpretation of remote sensing data. Sea ice characteristics such as snow surface topography, snow depth and ice thickness were derived from in situ measurements obtained during the J.C. Ross (ICEBell) and Oden Southern Ocean (OSO) expeditions during the austral summer of 2010-11. Select areas of sea ice floes in the Bellingshausen, Weddell and Amundsen Seas were measured using terrestrial scanning LiDAR (TSL) and also by conventional gridded and transect surveys. Snow depths were obtained at 2-5 meter sampling intervals and ice thickness was estimated by both electromagnetic induction (EMI) and auger drilling at 2-5 meter intervals. The LiDAR data is gridded to a 10cm rasterized data set. The field data from multiple floes in different regions provide a unique three dimensional perspective of sea ice elevation, snow depth and derived freeboard. These floes are visualized in both space and spectral domains and analyzed using classic statistical and geostatistical methods to assess surface roughness, snow depth, and the effects of differing scales on data resolution. The correlation lengths needed for isostatic equilibrium of freeboard were determined. These relationships are useful in assessing radar and laser altimetry data from airborne and satellite sources.

  3. Arctic sea-ice ridges—Safe heavens for sea-ice fauna during periods of extreme ice melt?

    NASA Astrophysics Data System (ADS)

    Gradinger, Rolf; Bluhm, Bodil; Iken, Katrin

    2010-01-01

    The abundances and distribution of metazoan within-ice meiofauna (13 stations) and under-ice fauna (12 stations) were investigated in level sea ice and sea-ice ridges in the Chukchi/Beaufort Seas and Canada Basin in June/July 2005 using a combination of ice coring and SCUBA diving. Ice meiofauna abundance was estimated based on live counts in the bottom 30 cm of level sea ice based on triplicate ice core sampling at each location, and in individual ice chunks from ridges at four locations. Under-ice amphipods were counted in situ in replicate ( N=24-65 per station) 0.25 m 2 quadrats using SCUBA to a maximum water depth of 12 m. In level sea ice, the most abundant ice meiofauna groups were Turbellaria (46%), Nematoda (35%), and Harpacticoida (19%), with overall low abundances per station that ranged from 0.0 to 10.9 ind l -1 (median 0.8 ind l -1). In level ice, low ice algal pigment concentrations (<0.1-15.8 μg Chl a l -1), low brine salinities (1.8-21.7) and flushing from the melting sea ice likely explain the low ice meiofauna concentrations. Higher abundances of Turbellaria, Nematoda and Harpacticoida also were observed in pressure ridges (0-200 ind l -1, median 40 ind l -1), although values were highly variable and only medians of Turbellaria were significantly higher in ridge ice than in level ice. Median abundances of under-ice amphipods at all ice types (level ice, various ice ridge structures) ranged from 8 to 114 ind m -2 per station and mainly consisted of Apherusa glacialis (87%), Onisimus spp. (7%) and Gammarus wilkitzkii (6%). Highest amphipod abundances were observed in pressure ridges at depths >3 m where abundances were up to 42-fold higher compared with level ice. We propose that the summer ice melt impacted meiofauna and under-ice amphipod abundance and distribution through (a) flushing, and (b) enhanced salinity stress at thinner level sea ice (less than 3 m thickness). We further suggest that pressure ridges, which extend into deeper, high-salinity water, become accumulation regions for ice meiofauna and under-ice amphipods in summer. Pressure ridges thus might be crucial for faunal survival during periods of enhanced summer ice melt. Previous estimates of Arctic sea ice meiofauna and under-ice amphipods on regional and pan-Arctic scales likely underestimate abundances at least in summer because they typically do not include pressure ridges.

  4. Evidence for radionuclide transport by sea ice

    USGS Publications Warehouse

    Meese, D.A.; Reimnitz, E.; Tucker, W. B., III; Gow, A.J.; Bischof, J.; Darby, D.

    1997-01-01

    Ice and ice-borne sediments were collected across the Arctic Basin during the Arctic Ocean Section, 1994 (AOS-94), a recent US/Canada trans- Arctic expedition. Sediments were analysed for 137Cs, clay mineralogy and carbon. Concentrations of 137Cs ranged from 5 to 73 Bq kg-1 in the ice- borne sediments. Concentrations of ice samples without sediment were all less than 1 Bq m-3. The sediment sample with the highest 137Cs concentration (73 Bq kg-1)was collected in the Beaufort Sea. This concentration was significantly higher than in bottom sediments collected in the same area, indicating an ice transport mechanism from an area with correspondingly higher concentrations. Recent results from the application of ice transport models and sediment analyses indicate that it is very likely that sediments are transported by ice, from the Siberian shelf areas to the Beaufort Sea.

  5. Satellite Remote Sensing: Passive-Microwave Measurements of Sea Ice

    NASA Technical Reports Server (NTRS)

    Parkinson, Claire L.; Zukor, Dorothy J. (Technical Monitor)

    2001-01-01

    Satellite passive-microwave measurements of sea ice have provided global or near-global sea ice data for most of the period since the launch of the Nimbus 5 satellite in December 1972, and have done so with horizontal resolutions on the order of 25-50 km and a frequency of every few days. These data have been used to calculate sea ice concentrations (percent areal coverages), sea ice extents, the length of the sea ice season, sea ice temperatures, and sea ice velocities, and to determine the timing of the seasonal onset of melt as well as aspects of the ice-type composition of the sea ice cover. In each case, the calculations are based on the microwave emission characteristics of sea ice and the important contrasts between the microwave emissions of sea ice and those of the surrounding liquid-water medium.

  6. Radar backscattering from snow facies of the Greenland ice sheet: Results from the AIRSAR 1991 campaign

    NASA Technical Reports Server (NTRS)

    Rignot, Eric; Jezek, K.; Vanzyl, J. J.; Drinkwater, Mark R.; Lou, Y. L.

    1993-01-01

    In June 1991, the NASA/JPL airborne SAR (AIRSAR) acquired C- (lambda = 5.6cm), L- (lambda = 24cm), and P- (lambda = 68m) band polarimetric SAR data over the Greenland ice sheet. These data are processed using version 3.55 of the AIRSAR processor which provides radiometrically and polarimetrically calibrated images. The internal calibration of the AIRSAR data is cross-checked using the radar response from corner reflectors deployed prior to flight in one of the scenes. In addition, a quantitative assessment of the noise power level at various frequencies and polarizations is made in all the scenes. Synoptic SAR data corresponding to a swath width of about 12 by 50 km in length (compared to the standard 12 x 12 km size of high-resolution scenes) are also processed and calibrated to study transitions in radar backscatter as a function of snow facies at selected frequencies and polarizations. The snow facies on the Greenland ice sheet are traditionally categorized based on differences in melting regime during the summer months. The interior of Greenland corresponds to the dry snow zone where terrain elevation is the highest and no snow melt occurs. The lowest elevation boundary of the dry snow zone is known traditionally as the dry snow line. Beneath it is the percolation zone where melting occurs in the summer and water percolates through the snow freezing at depth to form massive ice lenses and ice pipes. At the downslope margin of this zone is the wet snow line. Below it, the wet snow zone corresponds to the lowest elevations where snow remains at the end of the summer. Ablation produces enough meltwater to create areas of snow saturated with water, together with ponds and lakes. The lowest altitude zone of ablation sees enough summer melt to remove all traces of seasonal snow accumulation, such that the surface comprises bare glacier ice.

  7. Sea ice concentration temporal variability over the Weddell Sea and its relationship with tropical sea surface temperature

    USGS Publications Warehouse

    Barreira, S.; Compagnucci, R.

    2007-01-01

    Principal Components Analysis (PCA) in S-Mode (correlation between temporal series) was performed on sea ice monthly anomalies, in order to investigate which are the main temporal patterns, where are the homogenous areas located and how are they related to the sea surface temperature (SST). This analysis provides 9 patterns (4 in the Amundsen and Bellingshausen Seas and 5 in the Weddell Sea) that represent the most important temporal features that dominated sea ice concentration anomalies (SICA) variability in the Weddell, Amundsen and Bellingshausen Seas over the 1979-2000 period. Monthly Polar Gridded Sea Ice Concentrations data set derived from satellite information generated by NASA Team algorithm and acquired from the National Snow and Ice Data Center (NSIDC) were used. Monthly means SST are provided by the National Center for Environmental Prediction reanalysis. The first temporal pattern series obtained by PCA has its homogeneous area located at the external region of the Weddell and Bellingshausen Seas and Drake Passage, mostly north of 60°S. The second region is centered in 30°W and located at the southeast of the Weddell. The third area is localized east of 30°W and north of 60°S. South of the first area, the fourth PC series has its homogenous region, between 30° and 60°W. The last area is centered at 0° W and south of 60°S. Correlation charts between the five Principal Components series and SST were performed. Positive correlations over the Tropical Pacific Ocean were found for the five PCs when SST series preceded SICA PC series. The sign of the correlation could relate the occurrence of an El Niño/Southern Oscillation (ENSO) warm (cold) event with posterior positive (negative) anomalies of sea ice concentration over the Weddell Sea.

  8. Spectral albedo and transmittance of thin young Arctic sea ice

    NASA Astrophysics Data System (ADS)

    Taskjelle, Torbjørn; Hudson, Stephen R.; Granskog, Mats A.; Nicolaus, Marcel; Lei, Ruibo; Gerland, Sebastian; Stamnes, Jakob J.; Hamre, Børge

    2016-01-01

    Spectral albedo and transmittance in the range were measured on three separate dates on less than thick new Arctic sea ice growing on Kongsfjorden, Svalbard at , . Inherent optical properties, including absorption coefficients of particulate and dissolved material, were obtained from ice samples and fed into a radiative transfer model, which was used to analyze spectral albedo and transmittance and to study the influence of clouds and snow on these. Integrated albedo and transmittance for photosynthetically active radiation () were in the range 0.17-0.21 and 0.77-0.86, respectively. The average albedo and transmittance of the total solar radiation energy were 0.16 and 0.51, respectively. Values inferred from the model indicate that the ice contained possibly up to 40% brine and only 0.6% bubbles. Angular redistribution of solar radiation by clouds and snow was found to influence both the wavelength-integrated value and the spectral shape of albedo and transmittance. In particular, local peaks and depressions in the spectral albedo and spectral transmittance were found for wavelengths within atmospheric absorption bands. Simulated and measured transmittance spectra were within 5% for most of the wavelength range, but deviated up to 25% in the vicinity of , indicating the need for more optical laboratory measurements of pure ice, or improved modeling of brine optical properties in this near-infrared wavelength region.

  9. Recent variations of sea ice and air temperature in high latitudes

    SciTech Connect

    Chapman, W.L.; Walsh, J.E. )

    1993-01-01

    Feedbacks resulting from the retreat of sea ice and snow contribute to the polar amplification of the greenhouse warming projected by global climate models. A gridded sea-ice database, for which the record length is now approaching four decades for the Arctic and two decades for the Antarctic, is summarized here. The sea-ice fluctuations derived from the data set are characterized by (1) temporal scales of several seasons to several years and (2) spatial scales of 30[degrees]-180[degrees] of longitude. The ice data are examined in conjunction with air temperature data for evidence of recent climate change in the polar regions. The arctic sea-ice variations over the past several decades are compatible with the corresponding air temperatures, which show a distinct warming that is strongest over northern land areas during the winter and spring. The temperature trends over the sub arctic seas are smaller and even negative in the southern Greenland region. Statistically significant decreases of the summer extent of arctic ice are apparent in the sea-ice data, and new summer minima have been achieved three times in the past 15 years. There is no significant trend of ice extent in the Arctic during winter or in the Antarctic during any season. The seasonal and geographical changes of sea-ice coverage are consistent with the more recent greenhouse experiments performed with coupled atmosphere-ocean models.

  10. Extracellular macromolecules in sea-ice: Effects on sea-ice structure and their implications

    NASA Astrophysics Data System (ADS)

    Ewert, M.; Bayer-Giraldi, M.

    2012-04-01

    Brine inclusions within sea-ice offer a favorable environment for certain marine microorganisms which live and thrive within the ice. These assemblages are a crucial element in the polar ecosystem. Partly entrained by ice platelets into the ice sheet, microorganisms closely interact with the liquid and solid phases of this porous environment (brine and ice), likely influencing their properties. Extracellular polysaccharide substances (EPS) and antifreeze proteins (AFP) have been identified as major elements with the potential to affect ice structure and processes, due to their capability to interact with ice crystals (selected planes in the case of AFPs) and with water molecules and salt ions present in the brine. EPS present in sea water can be selectively retained in the ice during ice formation, with implications for ice structure. Likewise, EPS and AFP released by sea-ice organisms would have a local effect, altering the microenvironment for the benefit of the organism. Macroscopic and microscopic observations showed effects on ice microstructure and a possible increase in brine fraction within the ice caused by AFPs and EPS, implicating changes in ice porosity and permeability. In the following we describe some of the interactions between sea-ice macromolecules, EPS and AFP, and the sea-ice system. We show their influence in ice structure, and discuss probable implications and consequences for microbial survival, distribution of dissolved material between sea-ice and the water column, and possible effects on the seasonal evolution of the ice. All of these could be relevant to the understanding of biogeochemical processes and the limits of habitability, as well as suggest possible applications of these substances.

  11. L-band radiometry for sea ice applications

    NASA Astrophysics Data System (ADS)

    Heygster, G.; Hedricks, S.; Mills, P.; Kaleschke, L.; Stammer, D.; Tonboe, R.

    2009-04-01

    Although sea ice remote sensing has reached the level of operational exploitation with well established retrieval methods, several important tasks are still unsolved. In particular during freezing and melting periods with mixed ice and water surfaces, estimates of ice concentration with passive and active microwave sensors remain challenging. Newly formed thin ice is also hard to distinguish from open water with radiometers for frequencies above 8 GHz. The SMOS configuration (planned launch 2009) with a radiometer at 1.4 GHz is a promising technique to complement observations at higher microwave frequencies. ESA has initiated a project to investigate the possibilities for an additional Level-2 sea ice data product based on SMOS. In detail, the project objectives are (1) to model the L band emission of sea ice, and to assess the potential (2) to retrieve sea ice parameters, especially concentration and thickness, and (3) to use cold water regions for an external calibration of SMOS. Modelling of L band emission: Several models have are investigated. All of them work on the same basic principles and have a vertically-layered, plane-parallel geometry. They are comprised of three basic components: (1) effective permittivities are calculated for each layer based on ice bulk and micro-structural properties; (2) these are integrated across the total depth to derive emitted brightness temperature; (3) scattering terms can also be added because of the granular structure of ice and snow. MEMLS (Microwave Emission Model of Layered Snowpacks (Wiesmann and Matzler 1999)) is one such model that contains all three elements in a single Matlab program. In the absence of knowledge about the internal structure of the sea ice, three-layer (air, ice and water) dielectric slab models which take as input a single effective permittivity for the ice layer are appropriate. By ignoring scattering effects one can derive a simple analytic expression for a dielectric slab as shown by Apinis and Peake (1976). This expression was used by Menashi et al. (1993) to derive the thickness of sea ice from UHF (0.6 GHz) radiometer. Second, retrieval algorithms for sea ice parameters with emphasis on ice-water discrimination from L-band observations considering the specific SMOS observations modes and geometries are investigated. A modified Menashi model with the permittivity depending on brine volume and temperature suggests a thickness sensitivity of up to 150 cm for low salinity (multi year or brackish) sea ice at low temperatures. At temperatures approaching the melting point the thickness sensitivity reduces to a few centimetres. For first year ice the modelled thickness sensitivity is roughly half a meter. Runs of the model MEMLS with input data generated from a 1-d thermodynamic sea ice model lead to similar conclusio. The results of the forward model may strongly vary with the input microphysical details. E.g. if the permittivity is modelled to depend in addition on the sea ice thickness as supported by several former field campaigns for thin ice, the model predictions change strongly. Prior to the launch of SMOS, an important source of observational data is the SMOS Sea-Ice campaign held near Kokkola, Finland, March 2007 conducted as an add-on of the POL-ICE campaign. Co-incident L-band observations taken with the EMIRAD instrument of the Technical University of Denmark, ice thickness values determined from the EM bird of AWI and in situ observations during the campaign are combined. Although the campaign data are to be use with care, for selected parts of the flights the sea ice thickness can be retrieved correctly. However, as the instrumental conditions and calibration were not optimal, more in situ data, preferably from the Arctic, will be needed before drawing clear conclusions about a future the sea ice thickness product based on SMOS data. Use of additional information from other microwave sensors like AMSR-E might be needed to constrain the conditions, e.g. on sea ice concentration and temperature. External calibration: to combine SMOS ice information with statistics on temperature and salinity variations derived from a suitable ocean model to identify ocean targets for a vicarious target calibration of the SMOS radiometer. Such a target can be identified most reliably in cold waters as suggested by Ruf (2000) before. At higher microwave frequencies the advantage of the Ruf method is that the absolute minimum of the observed brightness temperatures is a universal constant and can be used for external calibration. However, in the L band the salinity variations may shift the minimum to both directions so that suitable regions of low salinity variations need to be identified. For finding areas with fairly stable, at least known cold temperatures, one has to analyze existing prior (external) knowledge available from ocean observations (in situ and satellite) and from numerical models. From statistics based on daily AMSR SST fields and model simulations, the best area seems to be between Svalbard and Ocean Weather Ship Station (OWS) Mike, at 66N, 02E. However, variations in SST are still comparably large and the area can hardly be used for instrument calibration. It is suggested to deploy a number of drifters in a limited area representing a SMOS footprint to obtain accurate estimates of SSS and SST.

  12. Influences of sea ice on eastern Bering Sea phytoplankton

    NASA Astrophysics Data System (ADS)

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

    2015-03-01

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

  13. Inorganic carbon system dynamics in landfast Arctic sea ice during the early-melt period

    NASA Astrophysics Data System (ADS)

    Brown, Kristina A.; Miller, Lisa A.; Mundy, C. J.; Papakyriakou, Tim; Francois, Roger; Gosselin, Michel; Carnat, Gauthier; Swystun, Kyle; Tortell, Philippe D.

    2015-05-01

    We present the results of a 6 week time series of carbonate system and stable isotope measurements investigating the effects of sea ice on air-sea CO2 exchange during the early melt period in the Canadian Arctic Archipelago. Our observations revealed significant changes in sea ice and sackhole brine carbonate system parameters that were associated with increasing temperatures and the buildup of chlorophyll a in bottom ice. The warming sea-ice column could be separated into distinct geochemical zones where biotic and abiotic processes exerted different influences on inorganic carbon and pCO2 distributions. In the bottom ice, biological carbon uptake maintained undersaturated pCO2 conditions throughout the time series, while pCO2 was supersaturated in the upper ice. Low CO2 permeability of the sea ice matrix and snow cover effectively impeded CO2 efflux to the atmosphere, despite a strong pCO2 gradient. Throughout the middle of the ice column, brine pCO2 decreased significantly with time and was tightly controlled by solubility, as sea ice temperature and in situ melt dilution increased. Once the influence of melt dilution was accounted for, both CaCO3 dissolution and seawater mixing were found to contribute alkalinity and dissolved inorganic carbon to brines, with the CaCO3 contribution driving brine pCO2 to values lower than predicted from melt-water dilution alone. This field study reveals a dynamic carbon system within the rapidly warming sea ice, prior to snow melt. We suggest that the early spring period drives the ice column toward pCO2 undersaturation, contributing to a weak atmospheric CO2 sink as the melt period advances.

  14. The anisotropic scattering coefficient of sea ice

    NASA Astrophysics Data System (ADS)

    Katlein, Christian; Nicolaus, Marcel; Petrich, Chris

    2014-02-01

    Radiative transfer in sea ice is subject to anisotropic, multiple scattering. The impact of anisotropy on the light field under sea ice was found to be substantial and has been quantified. In this study, a large data set of irradiance and radiance measurements under sea ice has been acquired with a Remotely Operated Vehicle (ROV) in the central Arctic. Measurements are interpreted in the context of numerical radiative transfer calculations, laboratory experiments, and microstructure analysis. The ratio of synchronous measurements of transmitted irradiance to radiance shows a clear deviation from an isotropic under-ice light field. We find that the angular radiance distribution under sea ice is more downward directed than expected for an isotropic light field. This effect can be attributed to the anisotropic scattering coefficient within sea ice. Assuming an isotropic radiance distribution under sea ice leads to significant errors in light-field modeling and the interpretation of radiation measurements. Quantification of the light field geometry is crucial for correct conversion of radiance data acquired by Autonomous Underwater Vehicles (AUVs) and ROVs.

  15. SIPEX--Exploring the Antarctic Sea Ice Zone

    ERIC Educational Resources Information Center

    Zicus, Sandra; Dobson, Jane; Worby, Anthony

    2008-01-01

    Sea ice in the polar regions plays a key role in both regulating global climate and maintaining marine ecosystems. The international Sea Ice Physics and Ecosystem eXperiment (SIPEX) explored the sea ice zone around Antarctica in September and October 2007, investigating relationships between the physical sea ice environment and the structure of…

  16. SIPEX--Exploring the Antarctic Sea Ice Zone

    ERIC Educational Resources Information Center

    Zicus, Sandra; Dobson, Jane; Worby, Anthony

    2008-01-01

    Sea ice in the polar regions plays a key role in both regulating global climate and maintaining marine ecosystems. The international Sea Ice Physics and Ecosystem eXperiment (SIPEX) explored the sea ice zone around Antarctica in September and October 2007, investigating relationships between the physical sea ice environment and the structure of

  17. Object-based Image Classification of Arctic Sea Ice and Melt Ponds through Aerial Photos

    NASA Astrophysics Data System (ADS)

    Miao, X.; Xie, H.; Li, Z.; Lei, R.

    2013-12-01

    The last six years have marked the lowest Arctic summer sea ice extents in the modern era, with a new record summer minimum (3.4 million km2) set on 13 September 2012. It has been predicted that the Arctic could be free of summer ice within the next 25-30. The loss of Arctic summer ice could have serious consequences, such as higher water temperature due to the positive feedback of albedo, more powerful and frequent storms, rising sea levels, diminished habitats for polar animals, and more pollution due to fossil fuel exploitation and/ or increased traffic through the Northwest/ Northeast Passage. In these processes, melt ponds play an important role in Earth's radiation balance since they strongly absorb solar radiation rather than reflecting it as snow and ice do. Therefore, it is necessary to develop the ability of predicting the sea ice/ melt pond extents and space-time evolution, which is pivotal to prepare for the variation and uncertainty of the future environment, political, economic, and military needs. A lot of efforts have been put into Arctic sea ice modeling to simulate sea ice processes. However, these sea ice models were initiated and developed based on limited field surveys, aircraft or satellite image data. Therefore, it is necessary to collect high resolution sea ice aerial photo in a systematic way to tune up, validate, and improve models. Currently there are many sea ice aerial photos available, such as Chinese Arctic Exploration (CHINARE 2008, 2010, 2012), SHEBA 1998 and HOTRAX 2005. However, manually delineating of sea ice and melt pond from these images is time-consuming and labor-intensive. In this study, we use the object-based remote sensing classification scheme to extract sea ice and melt ponds efficiently from 1,727 aerial photos taken during the CHINARE 2010. The algorithm includes three major steps as follows. (1) Image segmentation groups the neighboring pixels into objects according to the similarity of spectral and texture information; (2) random forest ensemble classifier can distinguish the following objects: water, submerged ice, shadow, and ice/snow; and (3) polygon neighbor analysis can further separate melt ponds from submerged ice according to the spatial neighboring relationship. Our results illustrate the spatial distribution and morphological characters of melt ponds in different latitudes of the Arctic Pacific sector. This method can be applied to massive photos and images taken in past years and future years, in deriving the detailed sea ice and melt pond distribution and changes through years.

  18. Spatial Variability of Barrow-Area Shore-Fast Sea Ice and Its Relationships to Passive Microwave Emissivity

    NASA Technical Reports Server (NTRS)

    Maslanik, J. A.; Rivas, M. Belmonte; Holmgren, J.; Gasiewski, A. J.; Heinrichs, J. F.; Stroeve, J. C.; Klein, M.; Markus, T.; Perovich, D. K.; Sonntag, J. G.; Tape, K.

    2006-01-01

    Aircraft-acquired passive microwave data, laser radar height observations, RADARSAT synthetic aperture radar imagery, and in situ measurements obtained during the AMSR-Ice03 experiment are used to investigate relationships between microwave emission and ice characteristics over several space scales. The data fusion allows delineation of the shore-fast ice and pack ice in the Barrow area, AK, into several ice classes. Results show good agreement between observed and Polarimetric Scanning Radiometer (PSR)-derived snow depths over relatively smooth ice, with larger differences over ridged and rubbled ice. The PSR results are consistent with the effects on snow depth of the spatial distribution and nature of ice roughness, ridging, and other factors such as ice age. Apparent relationships exist between ice roughness and the degree of depolarization of emission at 10,19, and 37 GHz. This depolarization .would yield overestimates of total ice concentration using polarization-based algorithms, with indications of this seen when the NT-2 algorithm is applied to the PSR data. Other characteristics of the microwave data, such as effects of grounding of sea ice and large contrast between sea ice and adjacent land, are also apparent in the PSR data. Overall, the results further demonstrate the importance of macroscale ice roughness conditions such as ridging and rubbling on snow depth and microwave emissivity.

  19. Mirabilite solubility in equilibrium sea ice brines

    NASA Astrophysics Data System (ADS)

    Butler, Benjamin Miles; Papadimitriou, Stathys; Santoro, Anna; Kennedy, Hilary

    2016-06-01

    The sea ice microstructure is permeated by brine channels and pockets that contain concentrated seawater-derived brine. Cooling the sea ice results in further formation of pure ice within these pockets as thermal equilibrium is attained, resulting in a smaller volume of increasingly concentrated residual brine. The coupled changes in temperature and ionic composition result in supersaturation of the brine with respect to mirabilite (Na2SO4·10H2O) at temperatures below -6.38 °C, which consequently precipitates within the sea ice microstructure. Here, mirabilite solubility in natural and synthetic seawater derived brines, representative of sea ice at thermal equilibrium, has been measured in laboratory experiments between 0.2 and -20.6 °C, and hence we present a detailed examination of mirabilite dynamics within the sea ice system. Below -6.38 °C mirabilite displays particularly large changes in solubility as the temperature decreases, and by -20.6 °C its precipitation results in 12.90% and 91.97% reductions in the total dissolved Na+ and SO42- concentrations respectively, compared to that of conservative seawater concentration. Such large non-conservative changes in brine composition could potentially impact upon the measurement of sea ice brine salinity and pH, whilst the altered osmotic conditions may create additional challenges for the sympagic organisms that inhabit the sea ice system. At temperatures above -6.38 °C, mirabilite again displays large changes in solubility that likely aid in impeding its identification in field samples of sea ice. Our solubility measurements display excellent agreement with that of the FREZCHEM model, which was therefore used to supplement our measurements to colder temperatures. Measured and modelled solubility data were incorporated into a 1D model for the growth of first-year Arctic sea ice. Model results ultimately suggest that mirabilite has a near ubiquitous presence in much of the sea ice on Earth, and illustrate the spatial and temporal evolution of mirabilite within sea ice as it grows throughout an Arctic winter, reaching maximum concentrations of 2.3 g kg-1.

  20. Influence of sea ice on Arctic precipitation.

    PubMed

    Kopec, Ben G; Feng, Xiahong; Michel, Fred A; Posmentier, Eric S

    2016-01-01

    Global climate is influenced by the Arctic hydrologic cycle, which is, in part, regulated by sea ice through its control on evaporation and precipitation. However, the quantitative link between precipitation and sea ice extent is poorly constrained. Here we present observational evidence for the response of precipitation to sea ice reduction and assess the sensitivity of the response. Changes in the proportion of moisture sourced from the Arctic with sea ice change in the Canadian Arctic and Greenland Sea regions over the past two decades are inferred from annually averaged deuterium excess (d-excess) measurements from six sites. Other influences on the Arctic hydrologic cycle, such as the strength of meridional transport, are assessed using the North Atlantic Oscillation index. We find that the independent, direct effect of sea ice on the increase of the percentage of Arctic sourced moisture (or Arctic moisture proportion, AMP) is 18.2 ± 4.6% and 10.8 ± 3.6%/100,000 km(2) sea ice lost for each region, respectively, corresponding to increases of 10.9 ± 2.8% and 2.7 ± 1.1%/1 °C of warming in the vapor source regions. The moisture source changes likely result in increases of precipitation and changes in energy balance, creating significant uncertainty for climate predictions. PMID:26699509

  1. Arctic Sea Ice Maximum 2011 - Duration: 61 seconds.

    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 ...

  2. Arctic Sea Ice Thickness from Satellite Observations, Aircraft Field Campaign Measurements, and Numerical Model Simulations

    NASA Astrophysics Data System (ADS)

    Wang, X.; Kwok, R.; Zhang, J.; Liu, Y.; Key, J.

    2013-12-01

    Sea ice is an important indicator and effective modulator of regional and global climate change because it significantly affects the complex exchanges of momentum, heat, and mass between the sea and atmosphere. At present, there are datasets for Arctic sea ice thickness from satellite observations, aircraft field campaign measurements, numerical model simulations, and some in-situ measurements. Among satellite derived data sets, one satellite ice thickness product has been generated using NASA's Ice, Cloud and Land Elevation Satellite (ICESat) Geoscience Laser Altimeter System (GLAS) observations (Kwok et al., 2009), another has been produced from long-term optical (visible, near-IR, and thermal IR) imager data from NOAA Polar Orbiting Satellites (Wang et al., 2010). The approaches are completely different: the ICESat product estimates ice thickness from surface elevation; the optical imager approach estimates ice thickness by solving the surface energy budget equation. NASA's IceBridge program fills the gap between the loss of ICESat in 2010 and the launch of ICESat-2 in 2016. IceBridge employs an aircraft for altimeter and other measurements of the ice sheets and sea ice. The IceBridge Snow Radar, Digital Mapping System (DMS), Continuous Airborne Mapping By Optical Translator (CAMBOT), and Airborne Topographic Mapper (ATM) instruments can be used to estimate ice thickness with a methodology similar to that used for ICESat. Ice thickness has also been modeled with the numerical model called Pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS) (Zhang and Rothrock, 2003). Arctic sea ice thickness estimates from these different data sources will be examined and inter-compared to evaluate their consistency and validity with in-situ measurements. Arctic sea ice thickness variations over time and space will be also investigated.

  3. Measuring the sea ice floe size distribution

    NASA Technical Reports Server (NTRS)

    Rothrock, D. A.; Thorndike, A. S.

    1984-01-01

    The sea ice covering the Arctic Ocean is broken into distinct pieces,called floes. In the summer, these floes, which have diameters ranging up to 100 km, are separated from each other by a region of open water. In the winter, floes still exist, but they are less easily identified. An understanding of the geometry of the ice pack is of interest for a number of practical applications associated with transportation in ice-covered seas and with the design of offshore structures intended to survive in the presence of ice. The present investigation has the objective to clarify ideas about floe sizes and to propose techniques for measuring them. Measurements are presented with the primary aim to illustrate points of technique or approach. A preliminary discussion of the floe size distribution of sea ice is devoted to questions of definition and of measurement.

  4. Exploring the utility of quantitative network design in evaluating Arctic sea-ice thickness sampling strategies

    NASA Astrophysics Data System (ADS)

    Kaminski, T.; Kauker, F.; Eicken, H.; Karcher, M.

    2015-03-01

    We present a quantitative network design (QND) study of the Arctic sea ice-ocean system using a software tool that can evaluate hypothetical observational networks in a variational data assimilation system. For a demonstration, we evaluate two idealised flight transects derived from NASA's Operation IceBridge airborne ice surveys in terms of their potential to improve ten-day to five-month sea-ice forecasts. As target regions for the forecasts we select the Chukchi Sea, an area particularly relevant for maritime traffic and offshore resource exploration, as well as two areas related to the Barnett Ice Severity Index (BSI), a standard measure of shipping conditions along the Alaskan coast that is routinely issued by ice services. Our analysis quantifies the benefits of sampling upstream of the target area and of reducing the sampling uncertainty. We demonstrate how observations of sea-ice and snow thickness can constrain ice and snow variables in a target region and quantify the complementarity of combining two flight transects. We further quantify the benefit of improved atmospheric forecasts and a well-calibrated model.

  5. Exploring the utility of quantitative network design in evaluating Arctic sea ice thickness sampling strategies

    NASA Astrophysics Data System (ADS)

    Kaminski, T.; Kauker, F.; Eicken, H.; Karcher, M.

    2015-08-01

    We present a quantitative network design (QND) study of the Arctic sea ice-ocean system using a software tool that can evaluate hypothetical observational networks in a variational data assimilation system. For a demonstration, we evaluate two idealised flight transects derived from NASA's Operation IceBridge airborne ice surveys in terms of their potential to improve 10-day to 5-month sea ice forecasts. As target regions for the forecasts we select the Chukchi Sea, an area particularly relevant for maritime traffic and offshore resource exploration, as well as two areas related to the Barnett ice severity index (BSI), a standard measure of shipping conditions along the Alaskan coast that is routinely issued by ice services. Our analysis quantifies the benefits of sampling upstream of the target area and of reducing the sampling uncertainty. We demonstrate how observations of sea ice and snow thickness can constrain ice and snow variables in a target region and quantify the complementarity of combining two flight transects. We further quantify the benefit of improved atmospheric forecasts and a well-calibrated model.

  6. Forecasting Bering Sea ice edge behavior

    SciTech Connect

    Pritchard, R.S. ); Mueller, A.C. ); Yang, Y.S. ); Hanzlick, D.J.

    1990-01-15

    A coupled ice/ocean dynamics model is developed to provide Arctic offshore operators with 5- to 7-day forecasts of ice motions, ice conditions, and ice edge motions. An adaptive grid is introduced to follow the ice edge, and the grid may move independently of the ice motion. The grid can be Lagrangian or Eulerian at different locations away from the ice edge. Ice stress is described using an elastic-plastic model with strength determined by the ice conditions. The ocean dynamics model describes time-dependent, three-dimensional behavior, including wind-driven currents and barotropic and baroclinic flows. The thermal energy budget of the ice cover is coupled to the ocean, with mass and salt interchange accompanying freezing or melting. Near the marginal ice zone (MIZ), surface winds (determined by reducing and turning the geostrophic winds) are enhanced to reflect observed behavior. The model was tested by simulating ice edge motions observed during the 1983 Marginal Ice Zone Experiment-West and during drilling of the 1983 north Aleutian shelf Continental Offshore Stratigraphic Test well. Simulations of ice edge movement in the Bering Sea compare with observed data to within about 5 km/d. The model correctly describes mixed-layer evolution in the marginal ice zone as fresh meltwater is mixed downward by turbulence. Along-edge baroclinic flows due to density gradients across the ice edge are simulated by the model, in agreement with observations. Increased ice drift speeds generate higher melt rates due to increased turbulence levels, with the result that ice edge advance is moderated in spite of higher ice drift speeds.

  7. 2011 Sea Ice Minimum - Duration: 61 seconds.

    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) ...

  8. Floating Ice-Algal Aggregates below Melting Arctic Sea Ice

    PubMed Central

    Assmy, Philipp; Ehn, Jens K.; Fernández-Méndez, Mar; Hop, Haakon; Katlein, Christian; Sundfjord, Arild; Bluhm, Katrin; Daase, Malin; Engel, Anja; Fransson, Agneta; Granskog, Mats A.; Hudson, Stephen R.; Kristiansen, Svein; Nicolaus, Marcel; Peeken, Ilka; Renner, Angelika H. H.; Spreen, Gunnar; Tatarek, Agnieszka; Wiktor, Jozef

    2013-01-01

    During two consecutive cruises to the Eastern Central Arctic in late summer 2012, we observed floating algal aggregates in the melt-water layer below and between melting ice floes of first-year pack ice. The macroscopic (1-15 cm in diameter) aggregates had a mucous consistency and were dominated by typical ice-associated pennate diatoms embedded within the mucous matrix. Aggregates maintained buoyancy and accumulated just above a strong pycnocline that separated meltwater and seawater layers. We were able, for the first time, to obtain quantitative abundance and biomass estimates of these aggregates. Although their biomass and production on a square metre basis was small compared to ice-algal blooms, the floating ice-algal aggregates supported high levels of biological activity on the scale of the individual aggregate. In addition they constituted a food source for the ice-associated fauna as revealed by pigments indicative of zooplankton grazing, high abundance of naked ciliates, and ice amphipods associated with them. During the Arctic melt season, these floating aggregates likely play an important ecological role in an otherwise impoverished near-surface sea ice environment. Our findings provide important observations and measurements of a unique aggregate-based habitat during the 2012 record sea ice minimum year. PMID:24204642

  9. Floating ice-algal aggregates below melting arctic sea ice.

    PubMed

    Assmy, Philipp; Ehn, Jens K; Fernández-Méndez, Mar; Hop, Haakon; Katlein, Christian; Sundfjord, Arild; Bluhm, Katrin; Daase, Malin; Engel, Anja; Fransson, Agneta; Granskog, Mats A; Hudson, Stephen R; Kristiansen, Svein; Nicolaus, Marcel; Peeken, Ilka; Renner, Angelika H H; Spreen, Gunnar; Tatarek, Agnieszka; Wiktor, Jozef

    2013-01-01

    During two consecutive cruises to the Eastern Central Arctic in late summer 2012, we observed floating algal aggregates in the melt-water layer below and between melting ice floes of first-year pack ice. The macroscopic (1-15 cm in diameter) aggregates had a mucous consistency and were dominated by typical ice-associated pennate diatoms embedded within the mucous matrix. Aggregates maintained buoyancy and accumulated just above a strong pycnocline that separated meltwater and seawater layers. We were able, for the first time, to obtain quantitative abundance and biomass estimates of these aggregates. Although their biomass and production on a square metre basis was small compared to ice-algal blooms, the floating ice-algal aggregates supported high levels of biological activity on the scale of the individual aggregate. In addition they constituted a food source for the ice-associated fauna as revealed by pigments indicative of zooplankton grazing, high abundance of naked ciliates, and ice amphipods associated with them. During the Arctic melt season, these floating aggregates likely play an important ecological role in an otherwise impoverished near-surface sea ice environment. Our findings provide important observations and measurements of a unique aggregate-based habitat during the 2012 record sea ice minimum year. PMID:24204642

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

    NASA Astrophysics Data System (ADS)

    Holt, Benjamin; Digby, Susan A.

    1985-05-01

    An analysis of first-year fast sea ice during the melt season has been made by using surface measurements and aircraft radar and photographic imagery obtained during a field study near Prince Patrick Island in the Canadian Archipelago from June 13 to July 13, 1982, and satellite imagery from Landsat and Seasat. Distinct changes observed in the properties of the snow layer and the sea ice were a temporary increase in small-scale surface roughness caused by formation of nodules of ice at the snow/ice interface; extensive snow melt and surface flooding; development of surface water drainage networks and low topography around fractures and seal breathing holes; and a rapid draining of much of the surface water. From the extensive salinity profiles obtained, two zones of rapid desalination in the first-year ice were observed: one zone extending from the air/ice interface downward toward the center of the ice sheet that resulted from surface warming and drainage of the surface melt water through the ice and the other zone extending from the sea/ice interface upward toward the center of the ice sheet that resulted from heating and separation of seawater and ice caused by a layer of low-salinity meltwater beneath the ice formed from surface meltwater runoff. Aircraft radar imagery detected changes in the amount of surface water and in the development of topography surrounding drainage features. Similar changes were detected in coincident Landsat multispectral scanner (MSS) imagery of the study area and in SEASAT radar imagery and Landsat MSS imagery of the Prince of Wales Strait from July 1978.

  11. Arctic Sea-Ice Freeboard Heights and Estimated Ice Thicknesses from ICESat: Seasonal and Interannual Variations (2003-2007)

    NASA Astrophysics Data System (ADS)

    Zwally, H. J.; Yi, D.; Kwok, R.

    2007-12-01

    Sea ice freeboard heights (sea ice plus snow cover) are derived from ICESat's along-track elevation measurements made over 70 m footprints at 172 m spacings with a range precision of 2 cm. For each measurement location, an ocean reference level is selected by constructing distributions of the measured surface elevations within +- 50 km of the location and taking the average elevation of the lowest 1 percent of the elevations, which are assumed to be over open water and/or very thin ice. The method has also provided a new estimate of the ocean geoid, which has been iteratively used as the initial ocean reference level in the analysis. Snow cover estimates from both climatology and derived from ECMWF analysis are used to estimate sea-ice thicknesses from the derived sea-ice freeboards. Probability-density functions (PDF) of ice thicknesses, which are constructed on 50-km scales, show the classic patterns of thin ice, first year, multiyear ice, etc in various regions. ICESat measurements from 2003 to present have been made in the fall (Oct-Nov) and winter (Feb-Mar) and in some springs (May-Jun). The PDF's of the mean thickness in 50 km grids show typical mixtures of areas of new thin ice and areas of residual multiyear ice in fall (1.48 m mean in 2005), growth of thicker ice in winter (1.93 m mean in 2006), and continued growth and loss of thinner ice by spring (2.67 m in 2006). The mean thickness and ice volume in the fall appears to be decreasing, while the mean thickness in the winter has had significant interannual variability. In 2004, a significant decrease of thicker ice occurred in the classic region of thicker ice north of Canada and Greenland, followed by some regrowth in 2005, and then by decreases of the thicker ice in 2006 and 2007. Compared to the typical ice thickness distributions typical of the Arctic Ocean in 1980-1990's, there appears to have been a fundamental loss of much of the thicker 3 to 5 m ice in recent years.

  12. Influence of snow and ice crystal formation and accumulation on mercury deposition to the Arctic.

    PubMed

    Douglas, Thomas A; Sturm, Matthew; Simpson, William R; Blum, Joel D; Alvarez-Aviles, Laura; Keeler, Gerald J; Perovich, Donald K; Biswas, Abir; Johnson, Kelsey

    2008-03-01

    Mercury is deposited to the Polar Regions during springtime atmospheric mercury depletion events (AMDEs) but the relationship between snow and ice crystal formation and mercury deposition is not well understood. The objective of this investigation was to determine if mercury concentrations were related to the type and formation of snow and ice crystals. On the basis of almost three hundred analyses of samples collected in the Alaskan Arctic, we suggestthat kinetic crystals growing from the vapor phase, including surface hoar, frost flowers, and diamond dust, yield mercury concentrations that are typically 2-10 times higher than that reported for snow deposited during AMDEs (approximately 80 ng/L). Our results show that the crystal type and formation affect the mercury concentration in any given snow sample far more than the AMDE activity prior to snow collection. We present a conceptual model of how snow grain processes including deposition, condensation, reemission, sublimation, and turbulent diffusive uptake influence mercury concentrations in snow and ice. These processes are time dependent and operate collectively to affect the retention and fate of mercury in the cryosphere. The model highlights the importance of the formation and postdeposition crystallographic history of snow or ice crystals in determining the fate and concentration of mercury in the cryosphere. PMID:18441801

  13. ALBEDO MODELS FOR SNOW AND ICE ON A FRESHWATER LAKE. (R824801)

    EPA Science Inventory

    Abstract

    Snow and ice albedo measurements were taken over a freshwater lake in Minnesota for three months during the winter of 1996¯1997 for use in a winter lake water quality model. The mean albedo of new snow was measured as 0.83±0.028, while the...

  14. ALBEDO MODELS FOR SNOW AND ICE ON A FRESHWATER LAKE. (R824801)

    EPA Science Inventory

    Abstract

    Snow and ice albedo measurements were taken over a freshwater lake in Minnesota for three months during the winter of 19961997 for use in a winter lake water quality model. The mean albedo of new snow was measured as 0.830.028, while the...

  15. Mercury distribution and transport across the ocean-sea-ice-atmosphere interface in the Arctic Ocean.

    PubMed

    Chaulk, Amanda; Stern, Gary A; Armstrong, Debbie; Barber, David G; Wang, Feiyue

    2011-03-01

    The Arctic sea-ice environment has been undergoing dramatic changes in the past decades; to which extent this will affect the deposition, fate, and effects of chemical contaminants remains virtually unknown. Here, we report the first study on the distribution and transport of mercury (Hg) across the ocean-sea-ice-atmosphere interface in the Southern Beaufort Sea of the Arctic Ocean. Despite being sampled at different sites under various atmospheric and snow cover conditions, Hg concentrations in first-year ice cores were generally low and varied within a remarkably narrow range (0.5-4 ng L(-1)), with the highest concentration always in the surface granular ice layer which is characterized by enriched particle and brine pocket concentration. Atmospheric Hg depletion events appeared not to be an important factor in determining Hg concentrations in sea ice except for frost flowers and in the melt season when snowpack Hg leaches into the sea ice. The multiyear ice core showed a unique cyclic feature in the Hg profile with multiple peaks potentially corresponding to each ice growing/melting season. The highest Hg concentrations (up to 70 ng L(-1)) were found in sea-ice brine and decrease as the melt season progresses. As brine is the primary habitat for microbial communities responsible for sustaining the food web in the Arctic Ocean, the high and seasonally changing Hg concentrations in brine and its potential transformation may have a major impact on Hg uptake in Arctic marine ecosystems under a changing climate. PMID:21288021

  16. The impact of refreezing of melt ponds on Arctic sea ice thinning

    NASA Astrophysics Data System (ADS)

    Flocco, Daniela; Feltham, Daniel; Schroeder, David; Tsamados, Michel

    2015-04-01

    While the impact of melt ponds on the albedo-feedback mechanism of Arctic sea ice is well known, their impact in suppressing winter freeze up has been less studied. At the end of summer the melt ponds, covering a large fraction of the sea ice, start freezing and get trapped between the sea ice beneath and a thin surface layer of ice. The pond water stores latent heat that is released as they freeze. Ponds trapped under a layer of refrozen ice have been observed in the Arctic and our model results, confirmed by observations, show that the latent heat stored in the ice due to their presence slows the basal sea ice growth for over a month after a sea ice lid appears on their surface. We have developed a three layer, one-dimensional model of temperature and salinity evolution to study the refreezing process and conducted sensitivity studies to examine the factors affecting melt pond refreezing, including the presence of snow on a refreezing pond. We also show some preliminary results obtained by including this new process in the CICE model and in particular, the impact that the increased pond salinity and the refrozen pond persistence have on the sea ice basal growth.

  17. Seasonal sea ice predictions for the Arctic based on assimilation of remotely sensed observations

    NASA Astrophysics Data System (ADS)

    Kauker, F.; Kaminski, T.; Ricker, R.; Toudal-Pedersen, L.; Dybkjaer, G.; Melsheimer, C.; Eastwood, S.; Sumata, H.; Karcher, M.; Gerdes, R.

    2015-10-01

    The recent thinning and shrinking of the Arctic sea ice cover has increased the interest in seasonal sea ice forecasts. Typical tools for such forecasts are numerical models of the coupled ocean sea ice system such as the North Atlantic/Arctic Ocean Sea Ice Model (NAOSIM). The model uses as input the initial state of the system and the atmospheric boundary condition over the forecasting period. This study investigates the potential of remotely sensed ice thickness observations in constraining the initial model state. For this purpose it employs a variational assimilation system around NAOSIM and the Alfred Wegener Institute's CryoSat-2 ice thickness product in conjunction with the University of Bremen's snow depth product and the OSI SAF ice concentration and sea surface temperature products. We investigate the skill of predictions of the summer ice conditions starting in March for three different years. Straightforward assimilation of the above combination of data streams results in slight improvements over some regions (especially in the Beaufort Sea) but degrades the over-all fit to independent observations. A considerable enhancement of forecast skill is demonstrated for a bias correction scheme for the CryoSat-2 ice thickness product that uses a spatially varying scaling factor.

  18. Linking Sea Ice Physical Properties with Under-Ice and In-Ice Ecosystems

    NASA Astrophysics Data System (ADS)

    Lange, B. A.; Flores, H.; David, C. L.; Nicolaus, M.

    2012-12-01

    Impacts of climate change have been most pronounced in Polar Regions. Most alarming is the accelerating decline in Arctic sea ice cover. The changing ice cover is likely to have implications for sea ice-associated ecosystems because they rely largely on carbon produced by ice-associated algae. In order to fully understand these ecosystems and to be able to accurately represent them in models there is a need to understand both the physical and biological components of the system. The study presented here is part of AWI's research group Iceflux which takes an interdisciplinary approach to quantify the trophic carbon flux within sea ice associated ecosystems in the Arctic and Antarctic. Here we will present preliminary results from the ARK XXVII/3 Polarstern Cruise (Aug-Oct, 2012) to the Central Arctic Ocean. Biological samples will be acquired from the under-ice surface waters using the Surface and Under-Ice Trawl (SUIT) and from within the sea ice by extracting ice cores. To characterize the biophysical properties of the sea ice and under-ice environments several sensors were mounted on the SUIT including: spectral radiometer, ADCP, CTD, fluorometer, altimeter (distance to ice bottom) and video camera. Observations include ice thickness, biological diversity, biomass, light transmission, under-ice water properties and chlorophyll a content (in- and under-ice). Preliminary results will provide a description of the local- to meso-scale spatial variability of biological abundance in and under the ice and the relationship with different sea ice characteristics. The SUIT system will be deployed, for the first time, under MYI; including extensively surveyed ice station floes. The effectiveness and efficiency of the SUIT system under MYI will be presented and compared to results from previous deployments.

  19. Potential sea ice predictability and the role of stochastic sea ice strength perturbations

    NASA Astrophysics Data System (ADS)

    Juricke, Stephan; Goessling, Helge F.; Jung, Thomas

    2014-12-01

    Ensemble experiments with a climate model are carried out in order to explore how incorporating a stochastic ice strength parameterization to account for model uncertainty affects estimates of potential sea ice predictability on time scales from days to seasons. The impact of this new parameterization depends strongly on the spatial scale, lead time and the hemisphere being considered: Whereas the representation of model uncertainty increases the ensemble spread of Arctic sea ice thickness predictions generated by atmospheric initial perturbations up to about 4 weeks into the forecast, rather small changes are found for longer lead times as well as integrated quantities such as total sea ice area. The regions where initial condition uncertainty generates spread in sea ice thickness on subseasonal time scales (primarily along the ice edge) differ from that of the stochastic sea ice strength parameterization (along the coast lines and in the interior of the Arctic). For the Antarctic the influence of the stochastic sea ice strength parameterization is much weaker due to the predominance of thinner first year ice. These results suggest that sea ice data assimilation and prediction on subseasonal time scales could benefit from taking model uncertainty into account, especially in the Arctic.

  20. The contribution of mycosporine-like amino acids, chromophoric dissolved organic matter and particles to the UV protection of sea-ice organisms in the Baltic Sea.

    PubMed

    Piiparinen, Jonna; Enberg, Sara; Rintala, Janne-Markus; Sommaruga, Ruben; Majaneva, Markus; Autio, Riitta; Vähätalo, Anssi V

    2015-05-01

    The effects of ultraviolet radiation (UVR) on the synthesis of mycosporine-like amino acids (MAAs) in sea-ice communities and on the other UV-absorption properties of sea ice were studied in a three-week long in situ experiment in the Gulf of Finland, Baltic Sea in March 2011. The untreated snow-covered ice and two snow-free ice treatments, one exposed to wavelengths > 400 nm (PAR) and the other to full solar spectrum (PAR + UVR), were analysed for MAAs and absorption coefficients of dissolved (aCDOM) and particulate (ap) fractions, the latter being further divided into non-algal (anap) and algal (aph) components. Our results showed that the diatom and dinoflagellate dominated sea-ice algal community responded to UVR down to 25-30 cm depth by increasing their MAA : chlorophyll-a ratio and by extending the composition of MAA pool from shinorine and palythine to porphyra-334 and an unknown compound with absorption peaks at ca. 335 and 360 nm. MAAs were the dominant absorbing components in algae in the top 10 cm of ice, and their contribution to total absorption became even more pronounced under UVR exposure. In addition to MAAs, the high absorption by chromophoric dissolved organic matter (CDOM) and by deposited atmospheric particles provided UV-protection for sea-ice organisms in the exposed ice. Efficient UV-protection will especially be of importance under the predicted future climate conditions with more frequent snow-free conditions. PMID:25837523

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  2. Attribution of Recent Arctic Sea Ice Melting to Human Influence

    NASA Astrophysics Data System (ADS)

    Heo, Joonghyeok; Min, Seung-Ki

    2014-05-01

    During recent three decades Arctic sea ice extent (SIE) has been decreasing with its rate accelerating. There have been, however, limited studies which have identified human influence on the Arctic sea ice using a formal detection approach. This study conducts an updated detection analysis of recent Arctic SIE during 1979-2012 by comparing observed changes with those from CMIP5 (Coupled Model Intercomparison Project Phase 5) multi-model simulations. We use the NSIDC (National Snow and Ice Data Center) sea ice index as observations. The simulated Arctic SIEs are calculated from available ensembles of CMIP5 multi-models which have been performed under natural plus anthropogenic forcing (ALL: historical combined with RCP4.5, 112 runs from 40 models), natural forcing only (NAT: historicalNat, 48 runs from 10 models) and greenhouse gas forcing only (GHG: historicalGHG, 35 runs from 9 models). Anthropogenic forcing (ANT) responses are estimated from differences between ALL and NAT. We apply an optimal fingerprinting method where observations are regressed onto model-simulated signals (multi-model means of ALL, NAT, and GHG). Here the internal variability noise is estimated from historical simulations after removing multi-model averages. The observations display decreasing trends across all months with stronger amplitude in summer than other seasons, which is reasonably reproduced by CMIP5 simulations. Results from one-signal analyses show that the ALL, ANT, and GHG signals are all detected when considering four months (Mar, Jun, Sep, and Dec) together and also from September to January when looking at individual months. Results from two-signal analyses show that ANT is separable from NAT and also that GHG is separable from other non-GHG forcings. Scaling factors of the detected ANT and GHG signals include unity, indicating that observed Arctic sea ice melting during the satellite period is largely attributable to human-induced increases in GHGs.

  3. Operation IceBridge: Sea Ice Interlude - Duration: 2 minutes, 36 seconds.

    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...

  4. Estimation of the penetration effects of the Ka-band radar signal into the Arctic sea ice snowpack.

    NASA Astrophysics Data System (ADS)

    Guerreiro, Kévin; Fleury, Sara; Kouraev, Alexei; Rémy, Frédérique; Zakharova, Elena; Blumstein, Denis

    2015-04-01

    In the context of quantifying Arctic sea ice volume at global scale, altimetry provides a unique tool to estimate sea ice thickness through the freeboard method that mainly consists in evaluating the thickness of emerged sea ice. Most of the altimeters employed to retrieve sea ice thickness operate at Ku-band frequency (13.6 Ghz). Over Arctic sea ice and at this frequency, the radar signal is only slightly affected by scattering and absorbtion due to the presence of snow over the ice. Therefore, it is commonly admitted that most of the return echo comes from the ice surface. Launched in February 2013, the Saral-AltiKa mission carries a Ka-band (36.5 Ghz) altimeter that is a great opportunity to expand the study of sea ice thickness. However, unlike the Ku-band operating systems, most of the Ka-band signal does not reach the sea ice surface and is scattered by overlying snow layers. For this reason and in order to obtain the best estimate of sea ice thickness with Ka-band radar, it is crucial to evaluate the bias due to penetration of the radar signal into the snowpack at this frequency. We combine both Ku and Ka band radar observations to study the influence of radar penetration into the snow and estimate the extinction coefficient over Arctic sea ice. Our results are of the same order of magnitude of what is found in Antarctica. This research has been done in the framework of CNES TOSCA SICKays and IDEX Transversalité InHERA projects.

  5. Coastal landfast sea ice decay and breakup in northern Alaska: Key processes and seasonal prediction

    NASA Astrophysics Data System (ADS)

    Petrich, Chris; Eicken, Hajo; Zhang, Jing; Krieger, Jeremy; Fukamachi, Yasushi; Ohshima, Kay I.

    2012-02-01

    Seasonal breakup of landfast sea ice consists of movement and irreversible ice detachment in response to winds or oceanic forces in the late stages of ice decay. The breakup process of landfast sea ice in the Chukchi Sea at Barrow, Alaska, was analyzed for the years 2000 through 2010 on the basis of local observations of snow and ice conditions, weather records, image sequences obtained from cameras, coastal X band marine radar, and satellite imagery. We investigated the relation of breakup to winds, tides, and nearshore current measurements from a moored acoustic Doppler current profiler. Two breakup modes are distinguished at Barrow on the basis of the degree of ice decay. Mechanical breakup due to wind and oceanic forces follows ablation and weakening of the ice. Thermal breakup is the result of ice disintegration under melt ponds, requiring little force to induce dispersion. Grounded pressure ridges are pivotal in determining the breakup mode. The timing of thermal breakup of the nearshore ice cover was found to correlate with the measured downwelling solar radiation in June and July. This linkage allows for the development of an operational forecast of landfast ice breakup. Results from forecasts during 2 years demonstrate that thermal breakup can be predicted to within a couple of days 2 weeks in advance. The cumulative shortwave energy absorbed by the ice cover provides for a measure of the state of ice decay and potential for disintegration. Discriminating between the two modes of breakup bears the potential to greatly increase forecasting skill.

  6. Using Sea Ice Age as a Proxy for Sea Ice Thickness

    NASA Astrophysics Data System (ADS)

    Stroeve, J. C.; Tschudi, M. A.; Maslanik, J. A.

    2014-12-01

    Since the beginning of the modern satellite record starting in October 1978, the Arctic sea ice cover has been shrinking, with the largest changes observed at the end of the melt season in September. Through 2013, the September ice extent has declined at a rate of -14.0% dec-1, or -895,300 km2 dec-1. The seven lowest September extents in the satellite record have all occurred in the past seven years. This reduction in ice extent is accompanied by large reductions in winter ice thicknesses that are primarily explained by changes in the ocean's coverage of multiyear ice (MYI). Using the University of Colorado ice age product developed by J. Maslanik and C. Fowler, and currently produced by M. Tschudi we present recent changes in the distribution of ice age from the mid 1980s to present. The CU ice age product is based on (1) the use of ice motion to track areas of sea ice and thus estimate how long the ice survives within the Arctic, and (2) satellite imagery of sea ice concentration to determine when the ice disappears. Age is assigned on a yearly basis, with the age incremented by one year if the ice survives summer melt and stays within the Arctic domain. Age is counted from 1 to 10 years, with all ice older than 10 years assigned to the "10+" age category. The position of the ice is calculated on weekly time steps on NSIDC's 12.5-km EASE-grid. In the mid-1980s, MYI accounted for 70% of total winter ice extent, whereas by the end of 2012 it had dropped to less than 20%. This reflects not only a change in ice type, but also a general thinning of the ice pack, as older ice tends to be thicker ice. Thus, with older ice being replaced by thinner first-year ice, the ice pack is more susceptible to melting out than it was in 1980's. It has been suggested that ice age may be a useful proxy for long-term changes in ice thickness. To assess the relationship between ice age and thickness, and how this may be changing over time, we compare the ice age fields to several observational data sets on ice thickness. These comparisons reveal that while a near-linear relationship between age and thickness for ice up to 3m thick existed in earlier years, this relationship is changing.

  7. Comparing Field Observations of Arctic Sea Ice to SSM/I and AMSR-E Sea Ice Products 2006-2009

    NASA Astrophysics Data System (ADS)

    Orlich, A. R.; Hutchings, J. K.; Prakash, A.

    2009-12-01

    The Arctic sea ice has experienced unprecedented changes in recent years. One of the most dramatic changes is in the extent of the Arctic sea ice, which was reported to reach a recorded minimum extent during the late summer / early Fall of 2007. The National Snow and Ice Data Center (NSIDC) generated and distributed maps of Arctic sea ice extent using passive microwave remote sensing data from SSM/I sensor. During late summers of 2006 to 2009 we collected field data on the sea ice concentration, distribution, type, and thickness at hourly intervals along the track followed by Canadian Coast Guard Service (CCGS) Louis S. St. Laurent Icebreaker in the Beaufort Sea. We present our field observation and data collection strategy. We compared these field observations with the satellite passive microwave (both SSM/I and AMSR-E) derived products and observed that at several locations the field observations conformed to the passive microwave estimates of ice concentration. However, at some locations (chiefly with 90-100% first year ice coverage) the satellite data under reports ice concentration by 30% on average. The bias may be attributed to melt-ponding on the ice surface that is mis-represented in the satellite product as open water and inadequate in-situ sampling within the AMSR/E footprint in a heterogeneous ice pack. We also find that in heterogeneous ice pack, such as 60% ice in large patches or floes, that hourly ship-based visual observations are insufficient to validate large scale (6-25km) satellite sea ice products. In future we plan to develop a camera based autonomous ice observation system that will provide in-situ ice concentration data at spatial resolutions suitable for satellite product validation. We present our initial design for this system. With potentially improved spatial resolution of future sensors, and improved understanding of melt pond signal in the microwave bands, we expect field validation of passive microwave sea ice products will lead to more accurate monitoring of sea ice area during summer.

  8. Sea Ice Freeboard from Altika and Comparison with Cryosat-2 and Operation Icebridge

    NASA Astrophysics Data System (ADS)

    Armitage, T.

    2014-12-01

    The algorithm for estimating sea ice freeboard from satellite radar altimetry is adapted and applied to Ka-band radar altimetry data from the French-Indian SARAL/AltiKa mission. This data is compared with contemporary state-of-the-art CryoSat-2 freeboard estimates for a full sea ice growth season in both the Arctic and Antarctic. We find that in both hemispheres, AltiKa consistently ranges higher than CryoSat-2, as would be intuitively expected for an altimeter operating at a higher frequency. The difference between the freeboard estimated by the two missions changes throughout the growth season, pointing to the role of the evolving snow layer on top of the sea ice floes. The data are also compared with Operation IceBridge airborne laser altimeter data from the 2013 and 2014 campaigns and it is found that AltiKa ranges much closer to the air-snow interface than CryoSat-2. AltiKa provides a new avenue of investigation for the issue of radar altimeter penetration into the snowpack on sea ice and could provide new insights for estimates of sea ice thickness, particularly in the Antarctic where Ku-band altimeters have typically performed badly.

  9. Estimation of Antarctic sea ice properties using surface and space borne data

    NASA Astrophysics Data System (ADS)

    Ozsoy Cicek, Burcu

    Sea ice is a fundamental component of the Earth's systems that cannot be ignored in the large scale environmental predictions of future climate conditions. Sea ice is a complex material and has major influences on global climate with its large maximum extent and seasonal change. In this research, remote sensing validation based on comparisons with surface based data has been done for quantitative monitoring of the ice properties. Various satellite products consisting of passive microwave, active microwave, and high resolution visible imagery were used and compared with in-situ measurements collected during scientific Antarctic cruises, conducted during International Polar Year (IPY) 2007--2008. This data used to provide a quantifiable method for observing sea ice, from all regions of the Antarctic sea ice zone to develop relationships that test existing remote sensing algorithms, evaluate alternative algorithms and provide error estimates on sea ice thickness derived from existing algorithms. Chapter 2 presents the comparison of ice extent/ice edge data from the NIC and the AMSR-E (Advanced Microwave Scanning Radiometer-Earth Observing System) passive microwave products using the Antarctic Sea Ice Process and Climate (ASPeCt) ship observations from the Oden expedition in December 2006 as ground truth to verify the two products during Antarctic summer. Ice edge location comparison has also been made between the two data sets, ship ice observations and NIC daily ice edge products. NIC analyses rely more heavily on high resolution satellite imagery such as active radar and visible imagery when visibility (clouds) allows. From these comparisons, a quantitative estimate of the differences in summer ice extent between the two remotely obtained products, AMSR-E and NIC ice edge, over the larger West Antarctic sea ice zone, has been obtained. Chapter 3 evaluates the comparison of ASPeCt ship based observations (conducted during Sea Ice Mass Balance in the Antarctic (SIMBA) 2007 Antarctic cruise) with coincident satellite active and passive microwave data. We combined visual ship-based observations of sea-ice and snow properties during SIMBA with coincident active and passive microwave satellite data with the aims to (a) derive typical radar backscatter ranges for observed sea-ice types and ice type mixtures, (b) improve our knowledge about the radar backscatter of different ice types in the Bellingshausen Sea at early-middle spring, (c) interpret AMSR-E snow depth over these ice types, and (d) identify the potential of the investigated active microwave signatures for a synergy with AMSR-E data to eventually improve the snow depth retrieval. Chapter 4 presents the validation of remote sensing measurements of ice extent and concentration with ASPeCt ship-based ice observations, conducted during the SIMBA and the Sea Ice Physics and Ecosystem eXperiment (SIPEX) International Polar Year (IPY) cruises (Sept--Oct 2007). First, the total sea ice cover around the entire continent was determined for 2007--2008 from Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) passive microwave and National Ice Center (NIC) charts. Second, Antarctic Sea Ice Processes and Climate (ASPeCt) ship observations from the SIMBA and SIPEX expeditions in the austral end of winter--beginning of spring 2007 are used as ground truth to verify the AMSR-E sea ice concentration product provided by both the Enhanced NASA Team Algorithm (NT2) and Bootstrap Basic Algorithm (BBA). Chapter 5 presents supplemental analysis related to the baseline thickness of Antarctic sea ice on a circumpolar basis from field measurements. In this part, our objectives were (1) Develop statistical relationships between surface elevation (snow freeboard), ice elevation (ice freeboard) and mean sea ice thickness using previous and newly obtained Antarctic sea ice profiles and examine these relationships for any consistent regional trends, (2) Derive sea ice thickness from profile elevations, using buoyancy equation, to determine error estimates compared to measured thickness; compare error estimates between the thicknesses derived using statistical relationships (Objective 1) and buoyancy theory where the additional term for the density of the slush layer is needed, when surfaces are flooded from snow loading. (Abstract shortened by UMI.)

  10. EOS Aqua AMSR-E Arctic Sea-Ice Validation Program: Arctic2006 Aircraft Campaign Flight Report

    NASA Technical Reports Server (NTRS)

    Cavalieri, D. J.; Markus, T.

    2006-01-01

    In March 2006, a coordinated Arctic sea-ice validation field campaign using the NASA Wallops P-3B aircraft was successfully completed. This campaign was the second Alaskan Arctic field campaign for validating the Earth Observing System (EOS) Aqua Advanced Microwave Scanning Radiometer (AMSR-E) sea-ice products. The first campaign was completed in March 2003. The AMSR-E, designed and built by the Japanese Space 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. The focus of this campaign was on the validation of snow depth on sea ice and sea-ice temperature. This flight report describes the suite of instruments flown on the P-3, the objectives of each of the six flights, the Arctic regions overflown, and the coordination among satellite, aircraft, and surface-based measurements.

  11. NASA Team 2 Sea Ice Concentration Algorithm Retrieval Uncertainty

    NASA Technical Reports Server (NTRS)

    Brucker, Ludovic; Cavalieri, Donald J.; Markus, Thorsten; Ivanoff, Alvaro

    2014-01-01

    Satellite microwave radiometers are widely used to estimate sea ice cover properties (concentration, extent, and area) through the use of sea ice concentration (IC) algorithms. Rare are the algorithms providing associated IC uncertainty estimates. Algorithm uncertainty estimates are needed to assess accurately global and regional trends in IC (and thus extent and area), and to improve sea ice predictions on seasonal to interannual timescales using data assimilation approaches. This paper presents a method to provide relative IC uncertainty estimates using the enhanced NASA Team (NT2) IC algorithm. The proposed approach takes advantage of the NT2 calculations and solely relies on the brightness temperatures (TBs) used as input. NT2 IC and its associated relative uncertainty are obtained for both the Northern and Southern Hemispheres using the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) TB. NT2 IC relative uncertainties estimated on a footprint-by-footprint swath-by-swath basis were averaged daily over each 12.5-km grid cell of the polar stereographic grid. For both hemispheres and throughout the year, the NT2 relative uncertainty is less than 5%. In the Southern Hemisphere, it is low in the interior ice pack, and it increases in the marginal ice zone up to 5%. In the Northern Hemisphere, areas with high uncertainties are also found in the high IC area of the Central Arctic. Retrieval uncertainties are greater in areas corresponding to NT2 ice types ass