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Sample records for amsr-e ice concentration

  1. Assessment of the AMSR-E Sea Ice Concentration Product at the Ice Edge Using RADARSAT-1 and MODIS Imagery

    NASA Technical Reports Server (NTRS)

    Henrichs, John F.; Cavalieri, Donald J.; Markus, Thorsten

    2006-01-01

    Imagery from the C-band synthetic aperture radar (SAR) aboard RADARSAT-1 and the Moderate Resolution Imaging Spectroradiometer (MODIS) was used to evaluate the performance of the Advanced Microwave Scanning Radiometer- EOS (AMSR-E) ice concentration product near the sea ice edge in the Bering Sea for four days during March 2003, which is concurrent with the AMSR-Ice03 field/aircraft campaign. The AMSR-E products were observed to perform very well in identifying open-water and pack-ice areas, although the AMSR-E products occasionally underestimate ice concentration in areas with thin ice. The position of the ice edge determined from AMSR-E data using a 15% concentration threshold was found to be, on average, within one AMSR-E grid square (12.5 km) of the ice edge determined from the SAR data, with the AMSR-E edge tending to be outside the SAR-derived edge

  2. Assessment of EOS Aqua AMSR-E Arctic Sea Ice Concentrations using Landsat-7 and Airborne Microwave Imagery

    NASA Technical Reports Server (NTRS)

    Cavalieri, Donald J.; Markus, Thorsten; Hall, Dorothy K.; Gasiewski, Albin J.; Klein, Marian; Ivanoff, Alvaro

    2006-01-01

    An assessment of Advanced Microwave Scanning Radiometer Earth Observing System (AMSR-E) sea ice concentrations under winter conditions using ice concentrations derived from Landsat-7 Enhanced Thematic Mapper Plus (ETM+) imagery obtained during the March 2003 Arctic sea ice validation field campaign is presented. The National Oceanic and Atmospheric Administration Environmental Technology Laboratory's Airborne Polarimetric Scanning Radiometer Measurements, which were made from the National Aeronautics and Space Administration P 3B aircraft during the campaign, were used primarily as a diagnostic tool to understand the comparative results and to suggest improvements to the AMSR-E ice concentration algorithm. Based on the AMSR-E/ETM+ comparisons, a good overall agreement with little bias (approx. 1%) for areas of first year and young sea ice was found. Areas of new ice production result in a negative bias of about 5% in the AMSR-E ice concentration retrievals, with a root mean square error of 8%. Some areas of deep snow also resulted in an underestimate of the ice concentration (approx. 10%). For all ice types combined and for the full range of ice concentrations, the bias ranged from 0% to 3%, and the rms errors ranged from 1% to 7%, depending on the region. The new-ice and deep-snow biases are expected to be reduced through an adjustment of the new-ice and ice-type C algorithm tie points.

  3. Estimation of melt pond fraction over high-concentration Arctic sea ice using AMSR-E passive microwave data

    NASA Astrophysics Data System (ADS)

    Tanaka, Yasuhiro; Tateyama, Kazutaka; Kameda, Takao; Hutchings, Jennifer K.

    2016-09-01

    Melt pond fraction (MPF) on sea ice is an important factor for ice-albedo feedback throughout the Arctic Ocean. We propose an algorithm to estimate MPF using satellite passive microwave data in this study. The brightness temperature (TB) data obtained from the Advanced Microwave Scanning Radiometer-Earth observing system (AMSR-E) were compared to the ship-based MPF in the Beaufort Sea and Canadian Arctic Archipelago. The difference between the TB at horizontal and vertical polarizations of 6.9 and 89.0 GHz (MP06H-89V), respectively, depends on the MPF. The correlation between MP06H-89V and ship-based MPF was higher than that between ship-based MPF and two individual channels (6.9 and 89.0 GHz of horizontal and vertical polarizations, respectively). The MPF determined with the highest resolution channel, 89.0 GHz (5 km × 5 km), provides spatial information with more detail than the 6.9 GHz channel. The algorithm estimates the relative fraction of ice covered by water (1) over areas where sea ice concentration is higher than 95%, (2) during late summer, and (3) in areas with low atmospheric humidity. The MPF estimated from AMSR-E data (AMSR-E MPF) in early summer was underestimated at lower latitudes and overestimated at higher latitudes, compared to the MPF obtained from the Moderate Resolution Image Spectrometer (MODIS MPF). The differences between AMSR-E MPF and MODIS MPF were less than 5% in most the regions and the periods. Our results suggest that the proposal algorithm serves as a basis for building time series of MPF in regions of consolidated ice pack.

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

    NASA Technical Reports Server (NTRS)

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

    2004-01-01

    A coordinated Arctic sea ice validation field campaign using the NASA Wallops P-3B aircraft was successfully completed in March 2003. This campaign was part of the program for validating the Earth Observing System (EOS) Aqua Advanced Microwave Scanning Radiometer (AMSR-E) sea ice products. The AMSR-E, designed and built by the Japanese National Space Development Agency for NASA, was launched May 4,2002 on the EOS Aqua spacecraft. The AMSR-E sea ice products include sea ice concentration, sea ice temperature, and snow depth on sea ice. The primary instrument on the P-3B aircraft was the NOAA ETL Polarimetric Scanning Radiometer (PSR) covering the same frequencies and polarizations as the AMSR-E. This paper describes the objectives of each of the seven flights, the Arctic regions overflown, and the coordination among satellite, aircraft, and surface-based measurements. Two of the seven aircraft flights were coordinated with scientists making surface measurements of snow and ice properties including sea ice temperature and snow depth on sea ice at a study area near Barrow, AK and at a Navy ice camp located in the Beaufort Sea. The remaining flights covered portions of the Bering Sea ice edge, the Chukchi Sea, and Norton Sound. Comparisons among the satellite and aircraft PSR data sets are presented.

  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. Extracting tidal variability of sea ice concentration from AMSR-E passive microwave single-swath data: a case study of the Ross Sea

    NASA Astrophysics Data System (ADS)

    Mack, Stefanie; Padman, Laurie; Klinck, John

    2013-02-01

    Abstract The periodic divergence of stress applied by ocean tidal currents to sea <span class="hlt">ice</span> affects the time-averaged <span class="hlt">ice</span> <span class="hlt">concentration</span> (Cice) and heat and freshwater fluxes at the ocean surface. We demonstrate that, at sufficiently high latitudes, tidal variability in Cice can be extracted from single-swath data from the Advanced Microwave Scanning Radiometer-EOS (<span class="hlt">AMSR-E</span>) satellite passive microwave sensor, although time intervals between swaths are irregular. For the northwest Ross Sea where tidal currents are large, tidal divergence is the dominant cause of Cice variability in winter, with a range of ±0.2 about a mean of ~0.8. Daily-averaged Cice values vary from >0.9 at neap tides to ~0.7 at spring tides. Variability at the fundamental tidal periods is about half that expected from an inverse barotropic tide model for the Ross Sea, suggesting that the measured tidal signal in Cice may be used to diagnose sea <span class="hlt">ice</span> mechanical properties and <span class="hlt">ice</span>/ocean coupling.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20040120981','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20040120981"><span>EOS Aqua <span class="hlt">AMSR-E</span> Arctic Sea <span class="hlt">Ice</span> Validation Program: Arctic2003 Aircraft Campaign Flight Report</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Cavalieri, D. J.; Markus,T.</p> <p>2003-01-01</p> <p>In March 2003 a coordinated Arctic sea <span class="hlt">ice</span> 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 (<span class="hlt">AMSR-E</span>) sea <span class="hlt">ice</span> products. The <span class="hlt">AMSR-E</span>, designed and built by the Japanese National Space Development Agency for NASA, was launched May 4, 2002 on the EOS Aqua spacecraft. The <span class="hlt">AMSR-E</span> sea <span class="hlt">ice</span> products to be validated include sea <span class="hlt">ice</span> <span class="hlt">concentration</span>, sea <span class="hlt">ice</span> temperature, and snow depth on sea <span class="hlt">ice</span>. 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 <span class="hlt">ice</span> properties including sea <span class="hlt">ice</span> temperature and snow depth on sea <span class="hlt">ice</span> at a study area near Barrow, AK and at a Navy <span class="hlt">ice</span> 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-<span class="hlt">ice</span> processes studies of Arctic coastal polynyas. The remaining flights covered portions of the Bering Sea <span class="hlt">ice</span> edge, the Chukchi Sea, and Norton Sound.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20070034825','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20070034825"><span>Trends in the Sea <span class="hlt">Ice</span> Cover Using Enhanced and Compatible <span class="hlt">AMSR-E</span>, SSM/I and SMMR Data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Comiso, Josefino C.; Nishio, Fumihiko</p> <p>2007-01-01</p> <p>Arguably, the most remarkable manifestation of change in the polar regions is the rapid decline (of about -10 %/decade) in the Arctic perennial <span class="hlt">ice</span> cover. Changes in the global sea <span class="hlt">ice</span> cover, however, are more modest, being slightly positive in the Southern Hemisphere and slightly negative in the Northern Hemisphere, the significance of which has not been adequately assessed because of unknown errors in the satellite historical data. We take advantage of the recent and more accurate <span class="hlt">AMSR-E</span> data to evaluate the true seasonal and interannual variability of the sea <span class="hlt">ice</span> cover, assess the accuracy of historical data, and determine the real trend. Consistently derived <span class="hlt">ice</span> <span class="hlt">concentrations</span> from <span class="hlt">AMSR-E</span>, SSM/I, and SMMR data were analyzed and a slight bias is observed between <span class="hlt">AMSR-E</span> and SSM/I data mainly because of differences in resolution. Analysis of the combine SMMR, SSM/I and <span class="hlt">AMSR-E</span> data set, with the bias corrected, shows that the trends in extent and area of sea <span class="hlt">ice</span> in the Arctic region is -3.4 +/- 0.2 and -4.0 +/- 0.2 % per decade, respectively, while the corresponding values for the Antarctic region is 0.9 +/- 0.2 and 1.7 .+/- 0.3 % per decade. The higher resolution of the <span class="hlt">AMSR-E</span> provides an improved determination of the location of the <span class="hlt">ice</span> edge while the SSM/I data show an <span class="hlt">ice</span> edge about 6 to 12 km further away from the <span class="hlt">ice</span> pack. Although the current record of <span class="hlt">AMSR-E</span> is less than 5 years, the data can be utilized in combination with historical data for more accurate determination of the variability and trends in the <span class="hlt">ice</span> cover.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20070021414&hterms=impact+factor&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dimpact%2Bfactor','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20070021414&hterms=impact+factor&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dimpact%2Bfactor"><span>Impact of Surface Roughness on <span class="hlt">AMSR-E</span> Sea <span class="hlt">Ice</span> Products</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Stroeve, Julienne C.; Markus, Thorsten; Maslanik, James A.; Cavalieri, Donald J.; Gasiewski, Albin J.; Heinrichs, John F.; Holmgren, Jon; Perovich, Donald K.; Sturm, Matthew</p> <p>2006-01-01</p> <p>This paper examines the sensitivity of Advanced Microwave Scanning Radiometer (<span class="hlt">AMSR-E</span>) brightness temperatures (Tbs) to surface roughness by a using radiative transfer model to simulate <span class="hlt">AMSR-E</span> Tbs as a function of incidence angle at which the surface is viewed. The simulated Tbs are then used to examine the influence that surface roughness has on two operational sea <span class="hlt">ice</span> algorithms, namely: 1) the National Aeronautics and Space Administration Team (NT) algorithm and 2) the enhanced NT algorithm, as well as the impact of roughness on the <span class="hlt">AMSR-E</span> snow depth algorithm. Surface snow and <span class="hlt">ice</span> data collected during the AMSR-<span class="hlt">Ice</span>03 field campaign held in March 2003 near Barrow, AK, were used to force the radiative transfer model, and resultant modeled Tbs are compared with airborne passive microwave observations from the Polarimetric Scanning Radiometer. Results indicate that passive microwave Tbs are very sensitive even to small variations in incidence angle, which can cause either an over or underestimation of the true amount of sea <span class="hlt">ice</span> in the pixel area viewed. For example, this paper showed that if the sea <span class="hlt">ice</span> areas modeled in this paper mere assumed to be completely smooth, sea <span class="hlt">ice</span> <span class="hlt">concentrations</span> were underestimated by nearly 14% using the NT sea <span class="hlt">ice</span> algorithm and by 7% using the enhanced NT algorithm. A comparison of polarization ratios (PRs) at 10.7,18.7, and 37 GHz indicates that each channel responds to different degrees of surface roughness and suggests that the PR at 10.7 GHz can be useful for identifying locations of heavily ridged or rubbled <span class="hlt">ice</span>. Using the PR at 10.7 GHz to derive an "effective" viewing angle, which is used as a proxy for surface roughness, resulted in more accurate retrievals of sea <span class="hlt">ice</span> <span class="hlt">concentration</span> for both algorithms. The <span class="hlt">AMSR-E</span> snow depth algorithm was found to be extremely sensitive to instrument calibration and sensor viewing angle, and it is concluded that more work is needed to investigate the sensitivity of the gradient ratio at 37 and</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20070008103','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20070008103"><span>EOS Aqua <span class="hlt">AMSR-E</span> Arctic Sea-<span class="hlt">Ice</span> Validation Program: Arctic2006 Aircraft Campaign Flight Report</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Cavalieri, D. J.; Markus, T.</p> <p>2006-01-01</p> <p>In March 2006, a coordinated Arctic sea-<span class="hlt">ice</span> 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 (<span class="hlt">AMSR-E</span>) sea-<span class="hlt">ice</span> products. The first campaign was completed in March 2003. The <span class="hlt">AMSR-E</span>, designed and built by the Japanese Space Agency for NASA, was launched May 4, 2002 on the EOS Aqua spacecraft. The <span class="hlt">AMSR-E</span> sea-<span class="hlt">ice</span> products to be validated include sea-<span class="hlt">ice</span> <span class="hlt">concentration</span>, sea-<span class="hlt">ice</span> temperature, and snow depth on sea <span class="hlt">ice</span>. The focus of this campaign was on the validation of snow depth on sea <span class="hlt">ice</span> and sea-<span class="hlt">ice</span> 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.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007AnGla..46..409K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007AnGla..46..409K"><span>Polynya Signature Simulation Method polynya area in comparison to <span class="hlt">AMSR-E</span> 89 GHz sea-<span class="hlt">ice</span> <span class="hlt">concentrations</span> in the Ross Sea and off the Adélie Coast, Antarctica, for 2002-05: first results</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kern, Stefan; Spreen, Gunnar; Kaleschke, Lars; de La Rosa, Sara; Heygster, Georg</p> <p>2007-10-01</p> <p>The Polynya Signature Simulation Method (PSSM) is applied to Special Sensor Microwave/Imager observations from different Defense Meteorological Satellite Program spacecraft for 2002-05 to analyze the polynya area in the Ross Sea (Ross <span class="hlt">Ice</span> Shelf polynya (RISP) and Terra Nova Bay polynya (TNBP)) and off the Adélie Coast (Mertz Glacier polynya (MGP)), Antarctica, on a sub-daily scale. The RISP and the MGP exhibit similar average total polynya areas. Major area changes (>10 000 km2; TNPB: >2000 km2) occur over a range of 2-3 to 20 days in all regions. Sub-daily area changes are largest for the MGP (5800 km2) and smallest for the TNBP (800 km2), underlining the persistence of the forcing of the latter. ARTIST sea-<span class="hlt">ice</span> (ASI) algorithm <span class="hlt">concentration</span> maps obtained using 89 GHz Advanced Microwave Scanning Radiometer (<span class="hlt">AMSR-E</span>) data are compared to PSSM maps, yielding convincing agreement in the average, similarly detailed winter polynya distribution. Average ASI algorithm <span class="hlt">ice</span> <span class="hlt">concentrations</span> take values of 25-40% and 65-80% for the PSSM open-water and thin-<span class="hlt">ice</span> class, respectively. The discrepancy with expected values (0% and 100%) can be explained by the different spatial resolution and frequency used by the methods. A new land mask and a mask to flag icebergs are introduced. Comparison of PSSM maps with thermal <span class="hlt">ice</span> thickness based on AVHRR infrared temperature and ECMWF ERA-40 data suggests an upper thickness limit for the PSSM thin-<span class="hlt">ice</span> class of 20-25 cm.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.youtube.com/watch?v=DYLbDb8Y8Tw','SCIGOVIMAGE-NASA'); return false;" href="http://www.youtube.com/watch?v=DYLbDb8Y8Tw"><span>2008 Arctic Sea <span class="hlt">Ice</span> from <span class="hlt">AMSR-E</span></span></a></p> <p><a target="_blank" href="http://www.nasa.gov/multimedia/videogallery/index.html">NASA Video Gallery</a></p> <p></p> <p></p> <p>Sea <span class="hlt">ice</span> is frozen seawater floating on the surface of the ocean. Some sea <span class="hlt">ice</span> is semi-permanent, persisting from year to year, and some is seasonal, melting and refreezing from season to season. Th...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20010022375','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20010022375"><span>EOS Aqua <span class="hlt">AMSR-E</span> Sea <span class="hlt">Ice</span> Validation Program: Meltpond2000 Flight Report</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Cavalieri, Donald J.</p> <p>2000-01-01</p> <p>This flight report describes the field component of Meltpond2000, the first in a series of Arctic and Antarctic aircraft campaigns planned as part of NASA's Earth Observing System Aqua sea <span class="hlt">ice</span> validation program for the Advanced Microwave Scanning Radiometer (<span class="hlt">AMSR-E</span>). This prelaunch Arctic field campaign was carried out between June 25 and July 6, 2000 from Thule, Greenland, with the objective of quantifying the errors incurred by the <span class="hlt">AMSR-E</span> sea <span class="hlt">ice</span> algorithms resulting from the presence of melt ponds. A secondary objective of the mission was to develop a microwave capability to discriminate between melt ponds and seawater using low-frequency microwave radiometers. Meltpond2000 was a multiagency effort involving personnel from the Navy, NOAA, and NASA. The field component of the mission consisted of making five 8-hour flights from Thule Air Base with a Naval Air Warfare Center P-3 aircraft over portions of Baffin Bay and the Canadian Arctic. The aircraft sensors were provided and operated by the Microwave Radiometry Group of NOAA's Environmental TechnologyLaboratory. A Navy <span class="hlt">ice</span> observer from the National <span class="hlt">Ice</span> Center provided visual documentation of surface <span class="hlt">ice</span> conditions during each of the flights. Two of the five flights were coordinated with Canadian scientists making surface measurements of melt ponds at an <span class="hlt">ice</span> camp located near Resolute Bay, Canada. Coordination with the Canadians will provide additional information on surface characteristics and will be of great value in the interpretation of the aircraft and high-resolution satellite data sets.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20020013322','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20020013322"><span>EOS Aqua <span class="hlt">AMSR-E</span> Sea <span class="hlt">Ice</span> Validation Program: Meltpond 2000 Flight Report</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Cavalieri, Donald J.</p> <p>2000-01-01</p> <p>This flight report describes the field component of Meltpond2000, the first in a series of Arctic and Antarctic aircraft campaigns planned as part of NASA's Earth Observing System Aqua sea <span class="hlt">ice</span> validation program for the Advanced Microwave Scanning Radiometer (<span class="hlt">AMSR-E</span>). This prelaunch Arctic field campaign was carried out between June 25 and July 6, 2000 from Thule, Greenland, with the objective of quantifying the errors incurred by the <span class="hlt">AMSR-E</span> sea <span class="hlt">ice</span> algorithms resulting from the presence of melt ponds. A secondary objective of the mission was to develop a microwave capability to discriminate between melt ponds and seawater using low-frequency microwave radiometers. Meltpond2000 was a multiagency effort involving personnel from the Navy, National Oceanic and Atmospheric Administration (NOAA), and NASA. The field component of the mission consisted of making five eight-hour flights from Thule Air Base with a Naval Air Warfare Center P-3 aircraft over portions of Baffin Bay and the Canadian Arctic. The aircraft sensors were provided and operated by the Microwave Radiometry Group of NOAA's Environmental Technology Laboratory. A Navy <span class="hlt">ice</span> observer from the National <span class="hlt">Ice</span> Center provided visual documentation of surface <span class="hlt">ice</span> conditions during each of the flights. Two of the five flights were coordinated with Canadian scientists making surface measurements of melt ponds at an <span class="hlt">ice</span> camp located near Resolute Bay, Canada. Coordination with the Canadians will provide additional information on surface characteristics and will be of great value in the interpretation of the aircraft and high-resolution satellite data sets.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120012935','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120012935"><span>A Comparison of Snow Depth on Sea <span class="hlt">Ice</span> Retrievals Using Airborne Altimeters and an <span class="hlt">AMSR-E</span> Simulator</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Cavalieri, D. J.; 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.</p> <p>2011-01-01</p> <p>A comparison of snow depths on sea <span class="hlt">ice</span> was made using airborne altimeters and an Advanced Microwave Scanning Radiometer for the Earth Observing System (<span class="hlt">AMSR-E</span>) 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 <span class="hlt">AMSR-E</span> 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 <span class="hlt">AMSR-E</span> 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 <span class="hlt">AMSR-E</span> snow depths using PSR-A brightness temperatures calibrated relative to <span class="hlt">AMSR-E</span> 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.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20080015852','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20080015852"><span>Determination of <span class="hlt">Ice</span> Water Path in <span class="hlt">Ice</span>-over-Water Cloud Systems Using Combined MODIS and <span class="hlt">AMSR-E</span> Measurements</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Huang, Jianping; Minnis, Patrick; Lin, Bing; Yi, Yuhong; Fan, T.-F.; Sun-Mack, Sunny; Ayers, J. K.</p> <p>2006-01-01</p> <p>To provide more accurate <span class="hlt">ice</span> cloud properties for evaluating climate models, the updated version of multi-layered cloud retrieval system (MCRS) is used to retrieve <span class="hlt">ice</span> water path (IWP) in <span class="hlt">ice</span>-over-water cloud systems over global ocean using combined instrument data from the Aqua satellite. The liquid water path (LWP) of lower layer water clouds is estimated from the Advanced Microwave Scanning Radiometer for EOS (<span class="hlt">AMSR-E</span>) measurements. With the lower layer LWP known, the properties of the upper-level <span class="hlt">ice</span> clouds are then derived from Moderate Resolution Imaging Spectroradiometer measurements by matching simulated radiances from a two-cloud layer radiative transfer model. Comparisons with single-layer cirrus systems and surface-based radar retrievals show that the MCRS can significantly improve the accuracy and reduce the over-estimation of optical depth and <span class="hlt">ice</span> water path retrievals for <span class="hlt">ice</span> over-water cloud systems. During the period from December 2004 through February 2005, the mean daytime <span class="hlt">ice</span> cloud optical depth and IWP for overlapped <span class="hlt">ice</span>-over-water clouds over ocean from Aqua are 7.6 and 146.4 gm(sup -2), respectively, significantly less than the initial single layer retrievals of 17.3 and 322.3 gm(sup -2). The mean IWP for actual single-layer clouds was 128.2 gm(sup -2).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2003AGUFM.H32B0548M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2003AGUFM.H32B0548M"><span>Advanced Microwave Scanning Radiometer - Earth Observing System (<span class="hlt">AMSR-E</span>) Validation Data Management at the National Snow and <span class="hlt">Ice</span> Data Center (NSIDC) Distributed Active Archive Center (DAAC)</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Marquis, M. C.; Paserba, A. M.</p> <p>2003-12-01</p> <p>The National Snow and <span class="hlt">Ice</span> Data Center (NSIDC) Distributed Active Archive Center (DAAC) is supporting the Advanced Microwave Scanning Radiometer - Earth Observing System (<span class="hlt">AMSR-E</span>) validation activity. NSIDC has designed and developed a web portal to data and information collected during NASA's <span class="hlt">AMSR-E</span> Validation Program: (http://nsidc.org/data/amsr_validation/.) The <span class="hlt">AMSR-E</span> validation experiments address three disciplines: soil moisture, rainfall and cryospheric validation campaigns. This poster describes all these experiments (past, present and future). NSIDC provides documentation, e.g., user guides, as well as metadata documents (DIFS) submitted to the Global Change Master Directory (GCMD), for all the <span class="hlt">AMSR-E</span> validation experiments. NSIDC further supports the validation activities by collaborating with the <span class="hlt">AMSR-E</span> Science Investigator-led Processing System (SIPS) to provide scientists in the field (e.g., Arctic and Antarctic ship and flight campaigns) with quick, easy access to <span class="hlt">AMSR-E</span> data for their validation experiments. NSIDC provides subsets of reformatted data in a manner most convenient to the validation scientists while they conduct their experiments. The <span class="hlt">AMSR-E</span> is a mission instrument launched aboard NASA's Aqua Satellite on 4 May 2002. The Aqua mission provides a multi-disciplinary study of the Earth's atmospheric, oceanic, cryospheric, and land processes and their relationship to global change. With six instruments aboard, the Aqua Satellite will travel in a polar, sun-synchronous orbit. NSIDC will archive and distribute all <span class="hlt">AMSR-E</span> products, including Levels 1A, 2, and 3 data. Users can order Level-1A <span class="hlt">AMSR-E</span> data beginning 19 June 2003 and Level-2A data beginning 01 September 2003. Other products will be available in March 2004.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23387184','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23387184"><span>[The arctic sea <span class="hlt">ice</span> refractive index retrieval based on satellite <span class="hlt">AMSR-E</span> observations].</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Chen, Han-Yue; Bi, Hai-Bo; Niu, Zheng</p> <p>2012-11-01</p> <p>The refractive index of sea <span class="hlt">ice</span> in the polar region is an important geophysical parameter. It is needed as a vital input for some numerical climate models and is helpful to classifying sea <span class="hlt">ice</span> types. In the present study, according to Hong Approximation (HA), we retrieved the arctic sea <span class="hlt">ice</span> refractive index at 6.9, 10.7, 23, 37, and 89 GHz in different arctic climatological conditions. The refractive indices of wintertime first year (FY) sea <span class="hlt">ice</span> and summertime <span class="hlt">ice</span> were derived with average values of 1.78 - 1.75 and 1.724 - 1.70 at different frequencies respectively, which are consistent with previous studies. However, for multiyear (MY) <span class="hlt">ice</span>, the results indicated relatively large bias between modeled results since 10.7 GHz. At a higher frequency, there is larger MY <span class="hlt">ice</span> refractive index difference. This bias is mainly attributed to the volume scattering effect on MY microwave radiation due to emergence of massive small empty cavities after the brine water in MY <span class="hlt">ice</span> is discharged into sea. In addition, the retrieved sea <span class="hlt">ice</span> refractive indices can be utilized to classify <span class="hlt">ice</span> types (for example, the winter derivation at 89 GHz), to identify coastal polynyas (winter retrieval at 6.9 GHz), and to outline the areal extent of significantly melting marginal sea <span class="hlt">ice</span> zone (MIZ) (summer result at 6.9 GHz). The investigation of this study suggests an effective tool of passive microwave remote sensing in monitoring sea <span class="hlt">ice</span> refractive index variability.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011DSRII..58.1092O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011DSRII..58.1092O"><span>Intercomparisons of Antarctic sea <span class="hlt">ice</span> types from visual ship, RADARSAT-1 SAR, Envisat ASAR, QuikSCAT, and <span class="hlt">AMSR-E</span> satellite observations in the Bellingshausen Sea</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ozsoy-Cicek, Burcu; Kern, Stefan; Ackley, Stephen F.; Xie, Hongjie; Tekeli, Ahmet E.</p> <p>2011-05-01</p> <p>Antarctic Sea <span class="hlt">Ice</span> Processes and Climate (ASPeCt) visual ship-based observations were conducted in the Bellingshausen Sea during the Sea <span class="hlt">Ice</span> Mass Balance in the Antarctic (SIMBA) cruise in austral spring 2007. A total of 59 ASPeCt observations are compared to coincident satellite active and passive microwave data. Envisat and RADARSAT-1 C-Band HH-polarization radar backscatter values (called NRCS henceforth) are derived on km-scales for six individual <span class="hlt">ice</span> types and <span class="hlt">ice</span> type mixtures. C-Band HH-polarized and Ku-Band VV-polarized NRCS are extracted on several 10 km-scale areas from coincident Envisat, RADARSAT-1, and QuikSCAT radar images for areas primarily covered with multiyear, deformed first-year, and undeformed young <span class="hlt">ice</span>, as well as <span class="hlt">ice</span> of the marginal <span class="hlt">ice</span> zone (MIZ). The C-Band NRCS permits distinction between first-year, MIZ, and undeformed young <span class="hlt">ice</span>. However, NRCS of the multiyear <span class="hlt">ice</span> zone overlaps with that of the other <span class="hlt">ice</span> zones and types. Ku-Band NRCS obtained for the same <span class="hlt">ice</span> types permits discrimination of the first-year <span class="hlt">ice</span> zone only. Obtained NRCS agree with those of previous studies and suggest a high degree of deformation and considerable potential for flooding for the first-year <span class="hlt">ice</span> case. In comparison to large scale NRCS, <span class="hlt">AMSR-E</span> snow depth values form two clearly separated clusters, one for 0.24-0.35 m depth (first-year <span class="hlt">ice</span> zone) and one for 0.36-0.54 m depth (multiyear <span class="hlt">ice</span> zone). However, a comparison to ASPeCt observations suggests a remarkable underestimation of the snow depth by <span class="hlt">AMSR-E</span> in the multiyear-first-year-<span class="hlt">ice</span> transition zone and for first-year cake <span class="hlt">ice</span>. Nevertheless, a fusion of the coarse <span class="hlt">AMSR-E</span> snow depth ranges for interior pack <span class="hlt">ice</span> regions with radar imagery at large scale, appears promising for mapping the major zones (MIZ and Pack <span class="hlt">Ice</span>) and <span class="hlt">ice</span> types (first-year and multiyear) of Antarctic sea <span class="hlt">ice</span> on a circumpolar basis.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20080032364&hterms=exports&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dexports','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20080032364&hterms=exports&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dexports"><span>Summer Sea <span class="hlt">Ice</span> Motion from the 18 GHz Channel of <span class="hlt">AMSR-E</span> and the Exchange of Sea <span class="hlt">Ice</span> between the Pacific and Atlantic Sectors</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Kwok, Ronald</p> <p>2008-01-01</p> <p>We demonstrate that sea <span class="hlt">ice</span> motion in summer can be derived reliably from the 18GHz channel of the <span class="hlt">AMSR-E</span> instrument on the EOS Aqua platform. The improved spatial resolution of this channel with its lower sensitivity to atmospheric moisture seems to have alleviated various issues that have plagued summer motion retrievals from shorter wavelength observations. Two spatial filters improve retrieval quality: one reduces some of the microwave signatures associated with synoptic-scale weather systems and the other removes outliers. Compared with daily buoy drifts, uncertainties in motion are approx.3-4 km/day. Using the daily motion fields, we examine five years of summer <span class="hlt">ice</span> area exchange between the Pacific and Atlantic sectors of the Arctic Ocean. With the sea-level pressure patterns during the summer of 2006 and 2007 favoring the export of sea <span class="hlt">ice</span> into the Atlantic Sector, the regional outflow is approx.21% and approx.15% of the total sea <span class="hlt">ice</span> retreat in the Pacific sector.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li class="active"><span>1</span></li> <li><a href="#" onclick='return showDiv("page_2");'>2</a></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_1 --> <div id="page_2" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_1");'>1</a></li> <li class="active"><span>2</span></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="21"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006AGUFM.H31A1400S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006AGUFM.H31A1400S"><span><span class="hlt">AMSR-E</span>/Aqua Gridded Brightness Temperatures</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Savoie, M.; Brodzik, M. J.; Knowles, K.</p> <p>2006-12-01</p> <p>Passive microwave brightness temperature data are a major component in many geophysical models and algorithms. For many researchers, a major difficulty in using these data is transforming the satellite swath data into a model-friendly, gridded format. Two new data sets and improvements to a toolkit at the National Snow and <span class="hlt">Ice</span> Data Center (NSIDC) will help scientists incorporate these data into their research. We have produced "<span class="hlt">AMSR-E</span>/Aqua Daily EASE-Grid Brightness Temperatures" from the Advanced Microwave Scanning Radiometer - Earth Observing System (<span class="hlt">AMSR-E</span>) instrument aboard NASA's Earth Observing System (EOS) Aqua satellite. This data set will complement and extend NSIDC's existing EASE-grid brightness temperature data sets, with new data beginning June 2002 and continuing throughout the life-cycle of the instrument. Additionally, in order to respond to user demand for quarter-degree data, we are distributing "<span class="hlt">AMSR-E</span>/Aqua Daily Global Quarter-Degree Gridded Brightness Temperatures" also spanning the <span class="hlt">AMSR-E</span> time period. Researchers whose needs are not met by the above data sets can create customized grids with our <span class="hlt">AMSR-E</span> Swath to Grid Toolkit. Recent improvements to the toolkit allow subsetted swath data as input, greatly reducing the initial data volume required to produce customized grids.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20040081367&hterms=arctic+temperature&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Darctic%2Btemperature','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20040081367&hterms=arctic+temperature&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Darctic%2Btemperature"><span>EOS Aqua <span class="hlt">AMSR-E</span> Arctic Sea <span class="hlt">Ice</span> Validation Program: Intercomparison Between Modeled and Measured Sea <span class="hlt">Ice</span> Brightness Temperatures</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Stroeve, J.; Markus, T.; Cavalieri, D. J.; Maslanik, J.; Sturm, M.; Henrichs, J.; Gasiewski, A.; Klein, M.</p> <p>2004-01-01</p> <p>During March 2003, an extensive field campaign was conducted near Barrow, Alaska to validate AQUA Advanced Microwave Scanning Radiometer (AMSR) sea <span class="hlt">ice</span> products. Field, airborne and satellite data were collected over three different types of sea <span class="hlt">ice</span>: 1) first year <span class="hlt">ice</span> with little deformation, 2) first year <span class="hlt">ice</span> with various amounts of deformation and 3) mixed first year <span class="hlt">ice</span> and multi-year <span class="hlt">ice</span> with various degrees of deformation. The validation plan relies primarily on comparisons between satellite, aircraft flights and ground-based measurements. Although these efforts are important, key aspects such as the effects of atmospheric conditions, snow properties, surface roughness, melt processes, etc on the sea <span class="hlt">ice</span> algorithms are not sufficiently well understood or documented. To improve our understanding of these effects, we combined the detailed, in-situ data collection from the 2003 field campaign with radiance modeling using a radiative transfer model to simulate the top of the atmosphere AMSR brightness temperatures. This study reports on the results of the simulations for a variety of snow and <span class="hlt">ice</span> types and compares the results with the National Oceanographic and Atmospheric Administration Environmental Technology Laboratory Polarimetric Scanning Radiometer (NOAA) (ETL) (PSR) microwave radiometer that was flown on the NASA P-3.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.5966A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.5966A"><span>Use of high frequency radiometer and altimeter on board AMSU-B, <span class="hlt">AMSR-E</span> and Altika/SARAL for observations of the Antarctic <span class="hlt">ice</span> sheet surface.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Adodo, Fifi; Picard, Ghislain; Remy, Frederique</p> <p>2016-04-01</p> <p>Snow surface properties quickly evolved according to local weather conditions, therefore are climate change indicator. These snow surface properties such as grain size, density, accumulation rate etc... are very important for evaluation and monitoring of the impact of global warming on the polar <span class="hlt">ice</span> sheet. In order to retrieve these snowpack properties, we explore the high frequency microwave radiometer variable( Brightness Temperature (Tb)) on the Antarctic <span class="hlt">ice</span> sheet on-board AMSU-B , <span class="hlt">AMSR-E</span> in combination with the ALTIKA altimeter (37GHz) waveform parameters (Backscatter coefficient, Trailing edge Slope(TeS) and Leading edge Width(LeW)). We compare the radiometer brightness temperature to calculations with the DMRT- ML radiative transfer model which simulates brightness temperature in vertical and horizontal polarizations. With some assumptions, this combination allows a good retrieval of snowpack properties. We showed positive trend of the grains size on the Antarctic plateau especially at Dome C during the two last decades. This work will provide a higher accuracy of the estimation of snowpack surfaces properties and contribute to monitoring the <span class="hlt">ice</span> sheet surface mass balance, well constraining of meteorological and glaciological models.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20060044186&hterms=arctic+ice+loss&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Darctic%2Bice%2Bloss','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20060044186&hterms=arctic+ice+loss&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Darctic%2Bice%2Bloss"><span>Improvements in the estimates of <span class="hlt">ice</span> thickness and production in the Chukchi Sea polynyas derived from <span class="hlt">AMSR-E</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Martin, Seelye; Drucker, Robert; Kwok, Ronald; Holt, Benjamin</p> <p>2005-01-01</p> <p>For January-March 2003, we use 12.5-km resolution Advanced Microwave Scanning Radiometer (AMSR) data for the first time in a comparison with Synthetic Aperture Radar (SAR) and Special Sensor Microwave/Imager (SSM/I) data to study two Chukchi coast polynyas, one consisting of many, the other of only a few 25-km SSM/I pixels. Within these polynyas, the <span class="hlt">ice</span> thicknesses are derived separately from the SMM/I 37-GHz and AMSR 36-GHz channels; the heat fluxes are derived by combining thicknesses with meteorological data. Comparison with ScanSAR data shows that for the large polynya, because AMSR provides better resolution of the surrounding coastline and first-year <span class="hlt">ice</span>, the AMSR heat losses are greater than the SSM/I; for the small polynya, AMSR measures its variability even when its area is order of a single SSM/I pixel. This means that AMSR permits more accurate calculation of polynya heat losses, yielding the potential of improved estimates of Arctic polynya productivity.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20080036090&hterms=sea+boundaries&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dsea%2Bboundaries','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20080036090&hterms=sea+boundaries&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dsea%2Bboundaries"><span>Ross Sea Polynyas: Response of <span class="hlt">Ice</span> <span class="hlt">Concentration</span> Retrievals to Large Areas of Thin <span class="hlt">Ice</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Kwok, R.; Comiso, J. C.; Martin, S.; Drucker, R.</p> <p>2007-01-01</p> <p>For a 3-month period between May and July of 2005, we examine the response of the Advanced Microwave Scanning Radiometer (<span class="hlt">AMSR-E</span>) Enhanced NASA Team 2 (NT2) and <span class="hlt">AMSR-E</span> Bootstrap (ABA) <span class="hlt">ice</span> <span class="hlt">concentration</span> algorithms to large areas of thin <span class="hlt">ice</span> of the Ross Sea polynyas. Coincident Envisat Synthetic Aperture Radar (SAR) coverage of the region during this period offers a detailed look at the development of the polynyas within several hundred kilometers of the <span class="hlt">ice</span> front. The high-resolution imagery and derived <span class="hlt">ice</span> motion fields show bands of polynya <span class="hlt">ice</span>, covering up to approximately 105 km(sup 2) of the Ross Sea, that are associated with wind-forced advection. In this study, <span class="hlt">ice</span> thickness from <span class="hlt">AMSR-E</span> 36 GHz polarization information serves as the basis for examination of the response. The quality of the thickness of newly formed sea <span class="hlt">ice</span> (<10 cm) from <span class="hlt">AMSR-E</span> is first assessed with thickness estimates derived from <span class="hlt">ice</span> surface temperatures from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. The effect of large areas of thin <span class="hlt">ice</span> in lowering the <span class="hlt">ice</span> <span class="hlt">concentration</span> estimates from both NT2/ABA approaches is clearly demonstrated. Results show relatively robust relationships between retrieved <span class="hlt">ice</span> <span class="hlt">concentrations</span> and thin <span class="hlt">ice</span> thickness estimates that differ between the two algorithms. These relationships define the approximate spatial coincidence of <span class="hlt">ice</span> <span class="hlt">concentration</span> and thickness isopleths. Using the 83% (ABA) and 91% (NT2) isopleths as polynya boundaries, we show that the computed coverage compares well with that using the estimated 10-cm thickness contour. The thin <span class="hlt">ice</span> response characterized here suggests that in regions with polynyas, the retrieval results could be used to provide useful geophysical information, namely thickness and coverage.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20020023454','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20020023454"><span>Global Climate Monitoring with the EOS PM-Platform's Advanced Microwave Scanning Radiometer (<span class="hlt">AMSR-E</span>)</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Spencer, Roy W.</p> <p>2002-01-01</p> <p>The Advanced Microwave Scanning 2 Radiometer (<span class="hlt">AMSR-E</span>) is being built by NASDA to fly on NASA's PM Platform (now called Aqua) in December 2000. This is in addition to a copy of AMSR that will be launched on Japan's ADEOS-II satellite in 2001. The AMSRs improve upon the window frequency radiometer heritage of the SSM/I and SMMR instruments. Major improvements over those instruments include channels spanning the 6.9 GHz to 89 GHz frequency range, and higher spatial resolution from a 1.6 m reflector (<span class="hlt">AMSR-E</span>) and 2.0 m reflector (ADEOS-II AMSR). The ADEOS-II AMSR also will have 50.3 and 52.8 GHz channels, providing sensitivity to lower tropospheric temperature. NASA funds an <span class="hlt">AMSR-E</span> Science Team to provide algorithms for the routine production of a number of standard geophysical products. These products will be generated by the <span class="hlt">AMSR-E</span> Science Investigator-led Processing System (SIPS) at the Global Hydrology Resource Center (GHRC) in Huntsville, Alabama. While there is a separate NASDA-sponsored activity to develop algorithms and produce products from AMSR, as well as a Joint (NASDA-NASA) AMSR Science Team 3 activity, here I will review only the <span class="hlt">AMSR-E</span> Team's algorithms and how they benefit from the new capabilities that <span class="hlt">AMSR-E</span> will provide. The US Team's products will be archived at the National Snow and <span class="hlt">Ice</span> Data Center (NSIDC).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20010124072','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20010124072"><span>Comparison of DMSP SSM/I and Landsat 7 ETM+ Sea <span class="hlt">Ice</span> <span class="hlt">Concentrations</span> During Summer Melt</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Cavalieri, Donald J.; Markus, Thorsten; Ivanoff, Alvaro; Koblinsky, Chester J. (Technical Monitor)</p> <p>2001-01-01</p> <p>As part of NASA's EOS Aqua sea <span class="hlt">ice</span> validation program for the Advanced Microwave Scanning Radiometer (<span class="hlt">AMSR-E</span>), Landsat 7 Enhanced Thematic Mapper (ETM+) images were acquired to develop a sea <span class="hlt">ice</span> <span class="hlt">concentration</span> data set with which to validate <span class="hlt">AMSR-E</span> sea <span class="hlt">ice</span> <span class="hlt">concentration</span> retrievals. The standard <span class="hlt">AMSR-E</span> Arctic sea <span class="hlt">ice</span> <span class="hlt">concentration</span> product will be obtained with the enhanced NASA Team (NT2) algorithm. The goal of this study is to assess the accuracy to which the NT2 algorithm, using DMSP Special Sensor Microwave Imager radiances, retrieves sea <span class="hlt">ice</span> <span class="hlt">concentrations</span> under summer melt conditions. Melt ponds are currently the largest source of error in the determination of Arctic sea <span class="hlt">ice</span> <span class="hlt">concentrations</span> with satellite passive microwave sensors. To accomplish this goal, Landsat 7 ETM+ images of Baffin Bay were acquired under clear sky conditions on the 26th and 27th of June 2000 and used to generate high-resolution sea <span class="hlt">ice</span> <span class="hlt">concentration</span> maps with which to compare the NT2 retrievals. Based on a linear regression analysis of 116 25-km samples, we find that overall the NT2 retrievals agree well with the Landsat <span class="hlt">concentrations</span>. The regression analysis yields a correlation coefficient of 0.98. In areas of high melt ponding, the NT2 retrievals underestimate the sea <span class="hlt">ice</span> <span class="hlt">concentrations</span> by about 12% compared to the Landsat values.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20000014066','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20000014066"><span>Global Climate Monitoring with the Eos Pm-Platform's Advanced Microwave Scanning Radiometer (<span class="hlt">AMSR-E</span>)</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Spencer, Roy W.</p> <p>2000-01-01</p> <p>The Advanced Microwave Scanning Radiometer (<span class="hlt">AMSR-E</span>) is being built by NASDA to fly on NASA's PM Platform (now called "Aqua") in December 2000. This is in addition to a copy of AMSR that will be launched on Japan's ADEOS-11 satellite in 2001. The AMSRs improve upon the window frequency radiometer heritage of the SSM[l and SMMR instruments. Major improvements over those instruments include channels spanning the 6.9 GHz to 89 GHz frequency range, and higher spatial resolution from a 1.6 m reflector (<span class="hlt">AMSR-E</span>) and 2.0 m reflector (ADEOS-11 AMSR). The ADEOS-11 AMSR also will have 50.3 and 52.8 GHz channels, providing sensitivity to lower tropospheric temperature. NASA funds an <span class="hlt">AMSR-E</span> Science Team to provide algorithms for the routine production of a number of standard geophysical products. These products will be generated by the <span class="hlt">AMSR-E</span> Science Investigator-led Processing System (SIPS) at the Global Hydrology Resource Center (GHRC) in Huntsville, Alabama. While there is a separate NASDA-sponsored activity to develop algorithms and produce products from AMSR, as well as a Joint (NASDA-NASA) AMSR Science Team activity, here I will review only the <span class="hlt">AMSR-E</span> Team's algorithms and how they benefit from the new capabilities that <span class="hlt">AMSR-E</span> will provide. The U.S. Team's products will be archived at the National Snow and <span class="hlt">Ice</span> Data Center (NSIDC). Further information about <span class="hlt">AMSR-E</span> can be obtained at http://www.jzhcc.msfc.nasa.Vov/AMSR.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=309920','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=309920"><span>SCA transfer from <span class="hlt">AMSR-E</span> to AMSR2</span></a></p> <p><a target="_blank" href="http://www.ars.usda.gov/services/TekTran.htm">Technology Transfer Automated Retrieval System (TEKTRAN)</a></p> <p></p> <p></p> <p>The current <span class="hlt">AMSR-E</span> soil moisture product distributed through NSIDC is developed using the Normalized Polarization Difference (NPD) algorithm. Several validation exercises have showed performance issues with the NPD-based <span class="hlt">AMSR-E</span> product. This motivated us to re-examine the NPR approach and outline po...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20000092059','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20000092059"><span>Collaboration on Development and Validation of the <span class="hlt">AMSR-E</span> Snow Water Equivalent Algorithm</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Armstrong, Richard L.</p> <p>2000-01-01</p> <p>The National Snow and <span class="hlt">Ice</span> Data Center (NSIDC) has produced a global SMMR and SSM/I Level 3 Brightness Temperature data set in the Equal Area Scalable Earth (EASE) Grid for the period 1978 to 2000. Processing of current data is-ongoing. The EASE-Grid passive microwave data sets are appropriate for algorithm development and validation prior to the launch of <span class="hlt">AMSR-E</span>. Having the lower frequency channels of SMMR (6.6 and 10.7 GHz) and the higher frequency channels of SSM/I (85.5 GHz) in the same format will facilitate the preliminary development of applications which could potentially make use of similar frequencies from <span class="hlt">AMSR-E</span> (6.9, 10.7, 89.0 GHz).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140017491','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140017491"><span>NASA Team 2 Sea <span class="hlt">Ice</span> <span class="hlt">Concentration</span> Algorithm Retrieval Uncertainty</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Brucker, Ludovic; Cavalieri, Donald J.; Markus, Thorsten; Ivanoff, Alvaro</p> <p>2014-01-01</p> <p>Satellite microwave radiometers are widely used to estimate sea <span class="hlt">ice</span> cover properties (<span class="hlt">concentration</span>, extent, and area) through the use of sea <span class="hlt">ice</span> <span class="hlt">concentration</span> (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 <span class="hlt">ice</span> 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 (<span class="hlt">AMSR-E</span>) 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 <span class="hlt">ice</span> pack, and it increases in the marginal <span class="hlt">ice</span> 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 <span class="hlt">ice</span> types associated with deep snow and new <span class="hlt">ice</span>. Seasonal variations in uncertainty show larger values in summer as a result of melt conditions and greater atmospheric contributions. Our analysis also includes an evaluation of the NT2 algorithm sensitivity to <span class="hlt">AMSR-E</span> sensor noise. There is a 60% probability that the IC does not change (to within the computed retrieval precision of 1%) due to sensor noise, and the cumulated probability shows that there is a 90% chance that the IC varies by less than</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006AGUFM.B41C0206S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006AGUFM.B41C0206S"><span>Global Wetland Monitoring with <span class="hlt">AMSR-E</span> Passive Microwave Radiometry</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Schroeder, R.; McDonald, K.; Podest, E.; Heimann, M.; Zimmermann, R.</p> <p>2006-12-01</p> <p>Methane is the most potent green house gas in Earth's atmosphere. Recent findings have raised wide concern as to whether living plants have a significant role in producing large amounts of methane. Although such findings may contradict the common understanding of many atmospheric scientists, laboratory studies have demonstrated that it is not clear how accurately natural methane production can be measured. Our study investigates the impact of natural wetlands on variations in methane out-gassing within a global modeling construct. At a first step, we utilize newly available passive microwave measurements from the <span class="hlt">AMSR-E</span> radiometer to observe Earth's largest wetland regions and to monitor their seasonal behavior. A remote sensing technique is presented that exploits the temporal variability of daily <span class="hlt">AMSR-E</span> brightness temperature observations to detect changes in water distribution that control inundation patterns for large wetlands in Siberia, North America, and the Amazon Basin susceptible to strong seasonal shifts in surface water retention or precipitation amounts. Initial results demonstrate that our method can be applied directly and without any tuning applied to the input remote sensing signal, though careful evaluation of our product with in-situ information remains to be carried out. This work was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=10531&hterms=sea+ice&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dsea%2Bice','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=10531&hterms=sea+ice&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dsea%2Bice"><span>Record Sea <span class="hlt">Ice</span> Minimum</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p></p> <p>2007-01-01</p> <p>Arctic sea <span class="hlt">ice</span> 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 (<span class="hlt">AMSR-E</span>) aboard NASA's Aqua satellite on September 16, 2007. In this image, blue indicates open water, white indicates high sea <span class="hlt">ice</span> <span class="hlt">concentration</span>, and turquoise indicates loosely packed sea <span class="hlt">ice</span>. 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 <span class="hlt">ice</span> observed by <span class="hlt">AMSR-E</span>. The green line indicates the 2005 minimum, the previous record low. The yellow line indicates the median minimum from 1979 to 2000.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009EGUGA..11.1959A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009EGUGA..11.1959A"><span>Validation of simulated sea-<span class="hlt">ice</span> <span class="hlt">concentrations</span> from sea <span class="hlt">ice</span>-ocean models and polynya classification methods in the Laptev Sea area using satellite data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Adams, S.; Willmes, S.; Heinemann, G.</p> <p>2009-04-01</p> <p>The Laptev Sea represents one of the most significant areas of net <span class="hlt">ice</span> production in the Arctic. Most of the <span class="hlt">ice</span> production takes place in a polynya forming at the fast <span class="hlt">ice</span> edge during strong offshore wind conditions. The simulation of these polynya events is a challenge for current sea <span class="hlt">ice</span>-ocean models, and validation of simulated sea-<span class="hlt">ice</span> <span class="hlt">concentrations</span> is necessary for model improvements. High-quality data sets of sea-<span class="hlt">ice</span> <span class="hlt">concentration</span> from remote sensing data are covering the period from 1978 to the present. These data sets are well suited for the validation of model results of sea <span class="hlt">ice</span>-ocean models. Based on the brightness temperature observations obtained from the Advanced Microwave Scanning Radiometer (<span class="hlt">AMSR-E</span>), the ARTIST (Arctic Radiation and Turbulence Interaction Study) Sea <span class="hlt">Ice</span> (ASI) algorithm is used to calculate mean daily sea-<span class="hlt">ice</span> <span class="hlt">concentrations</span>. Here we use <span class="hlt">AMSR-E</span> data for the validation of sea-<span class="hlt">ice</span> <span class="hlt">concentrations</span> in the Laptev Sea, which are simulated by the coupled sea <span class="hlt">ice</span>-ocean models North Atlantic - Arctic Ocean - Sea-<span class="hlt">Ice</span> Model (NAOSIM) and Finite Element Sea <span class="hlt">Ice</span> Ocean Model (FESOM). The general distribution of the sea-<span class="hlt">ice</span> <span class="hlt">concentrations</span>, the simulation of the polynya events and the position of polynyas are examined for the period October 2007 to April 2008. In addition, the polynya signature simulation method (PSSM) was applied to classify open water, thin <span class="hlt">ice</span> and thick <span class="hlt">ice</span>. The results of the validation show that the simulated distributions of the sea-<span class="hlt">ice</span> fields show similar structures, but an underestimation of sea <span class="hlt">ice</span> <span class="hlt">concentration</span>. The simulation of the polynya-events from the two models agrees reasonably well with satellite data. However, because of the absent fast <span class="hlt">ice</span> edge in both models, the position of the polynyas is shifted to the coast line. Therefore it would be necessary to include the fast <span class="hlt">ice</span> edge for simulating polynyas at the right position. Further investigations about the position of the polynyas will be performed with simulation</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=302358','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=302358"><span><span class="hlt">AMSR-E</span>-Based soil moisture retrieval algorithms and transferability to AMSR2</span></a></p> <p><a target="_blank" href="http://www.ars.usda.gov/services/TekTran.htm">Technology Transfer Automated Retrieval System (TEKTRAN)</a></p> <p></p> <p></p> <p>The launch of the Advanced Microwave Scanning Radiometer on NASA’s Earth Observing System Aqua satellite (<span class="hlt">AMSR-E</span>) in June of 2002 has led to major advancements in the routine global mapping of soil moisture. The wide availability of <span class="hlt">AMSR-E</span> data has promoted development of a number of global soil mo...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20080032384&hterms=statistics&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dstatistics','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20080032384&hterms=statistics&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dstatistics"><span>Global Survey and Statistics of Radio-Frequency Interference in <span class="hlt">AMSR-E</span> Land Observations</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Njoku, Eni G.; Ashcroft, Peter; Chan, Tsz K.; Li, Li</p> <p>2005-01-01</p> <p>Radio-frequency interference (RFI) is an increasingly serious problem for passive and active microwave sensing of the Earth. To satisfy their measurement objectives, many spaceborne passive sensors must operate in unprotected bands, and future sensors may also need to operate in unprotected bands. Data from these sensors are likely to be increasingly contaminated by RFI as the spectrum becomes more crowded. In a previous paper we reported on a preliminary investigation of RFI observed over the United States in the 6.9-GHz channels of the Advanced Microwave Scanning Radiometer (<span class="hlt">AMSR-E</span>) on the Earth Observing System Aqua satellite. Here, we extend the analysis to an investigation of RFI in the 6.9- and 10.7-GHz <span class="hlt">AMSR-E</span> channels over the global land domain and for a one-year observation period. The spatial and temporal characteristics of the RFI are examined by the use of spectral indices. The observed RFI at 6.9 GHz is most densely <span class="hlt">concentrated</span> in the United States, Japan, and the Middle East, and is sparser in Europe, while at 10.7 GHz the RFI is <span class="hlt">concentrated</span> mostly in England, Italy, and Japan. Classification of RFI using means and standard deviations of the spectral indices is effective in identifying strong RFI. In many cases, however, it is difficult, using these indices, to distinguish weak RFI from natural geophysical variability. Geophysical retrievals using RFI-filtered data may therefore contain residual errors due to weak RFI. More robust radiometer designs and continued efforts to protect spectrum allocations will be needed in future to ensure the viability of spaceborne passive microwave sensing.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUSM.H24A..01C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUSM.H24A..01C"><span>Assessment of Errors in <span class="hlt">AMSR-E</span> Derived Soil Moisture</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Champagne, C.; McNairn, H.; Berg, A.; de Jeu, R. A.</p> <p>2009-05-01</p> <p>Soil moisture derived from passive microwave satellites provides information at a coarse spatial scale, but with temporally frequent, global coverage that can be used for monitoring applications over agricultural regions. Passive microwave satellites measure surface brightness temperature, which is largely a function of vegetation water content (which is directly related to the vegetation optical depth), surface temperature and surface soil moisture at low frequencies. Retrieval algorithms for global soil moisture data sets by necessity require limited site-specific information to derive these parameters, and as such may show variations in local accuracy. The objective of this study is to examine the errors in passive microwave soil moisture data over agricultural sites in Canada to provide guidelines on data quality assessment for using these data sets in monitoring applications. Global gridded soil moisture was acquired from the <span class="hlt">AMSR-E</span> satellite using the Land Parameter Retrieval Model, LPRM (Owe et al., 2008). The LPRM model derives surface soil moisture through an iterative optimization procedure using a polarization difference index to estimate vegetation optical depth and surface dielectric constant using frequencies at 6.9 and 10.7 GHz. The LPRM model requires no a-priori information on surface conditions, but retrieval errors are expected to increase as the amount of open water and dense vegetation within each pixel increases (Owe et al., 2008) Satellite-derived LPRM soil moisture values were used to assess changes in soil moisture retrieval accuracy over the 2007 growing season for a largely agricultural site near Guelph (Ontario), Canada. Accuracy was determined by validating LPRM soil moisture against a network of 16 in-situ monitoring sites distributed at the pixel scale for <span class="hlt">AMSR-E</span>. Changes in squared error, and pairwise correlation coefficient between satellite and in-situ surface soil moisture were assessed against changes in satellite orbit and</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006cosp...36.2221L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006cosp...36.2221L"><span>Assimilating <span class="hlt">AMSR-E</span> data for soil moisture estimation</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Li, X.; Koike, T.</p> <p></p> <p>In the last decade we see a blooming of developing and applying of land data assimilation systems LDAS This technique by integrating both in situ and remote sensing data into the dynamics of land surface model is capable of producing the evolution of land surface state such as soil moisture soil temperature and snow water equivalent in physical and spatiotemporal consistence In this paper we introduce a few numerical experiments of assimilating the Advanced Microwave Scanning Radiometer <span class="hlt">AMSR-E</span> brightness temperature data by using the LDAS we have developed The data assimilation method being used is the ensemble Kalman filter which is a Monte Carlo based sequential filter method The land model is the JMA Japan Meteorological Administration new SiB which originates from the Simple Biosphere SiB model but is reformulated with explicit snow and soil freeze thaw processes The observation operators are radiative transfer models of soil We used the semi-empirical Q h model in this study The system was tested using many observations collected during CEOP Coordinated Enhanced Observation Period a Global Energy and Water Experiment particularly at a semi-arid region site Mongolia and a cold region site Tibet-east The results showed that 1 The system can estimate land surface variables i e soil moisture soil temperature and snow much more reasonable than free-loop modeling 2 From the view point of remote sensing the soil moisture and temperature profiles can be retrieved successfully with the aid of additional information</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2003AGUFM.C42B..03K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2003AGUFM.C42B..03K"><span>Testing <span class="hlt">AMSR-E</span> Snow Retrievals With Cold Lands Processes Experiment Data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kelly, R. E.; Chang, A. T.; Foster, J. L.; Hall, D. K.; Stankov, B. B.; Gasiewaski, A. J.</p> <p>2003-12-01</p> <p>Snow cover is an important component of the global hydrological cycle. Not only does it constitute a critical seasonal and long-term storage factor but it also affects global climate mass and energy dynamics. Accurate estimation of snow mass is important, therefore, for effective characterization of the hydrological cycle at different space and time scales. Satellite passive microwave observations have been used to estimate global snow depth and snow water equivalent (SWE) since 1979. However, during this time the instruments available have been able to observe snow mass over spatial domains only at regional scales; finer scale observations have not been possible. The Advanced Microwave Scanning Radiometer - EOS launched in 2002 aboard NASA's Aqua platform, has improved spatial resolution capabilities compared with previous passive microwave instruments and, potentially, can be used to estimate snow depth and SWE with increased accuracy at the regional scale. The Cold Lands Processes Experiment (CLPX) provides an opportunity to examine the spatial variability of snow mass and to determine controls on its observability by <span class="hlt">AMSR-E</span> in complex and simple terrains. This paper investigates the characteristics of <span class="hlt">AMSR-E</span> retrievals of SWE in the CLPX study domain. Level 2A <span class="hlt">AMSR-E</span> estimates of SWE at the 25 x 25 km Equal Area Scaleable grid (EASE grid) are used in the study. The three Mesocell Study Areas (MSA), North Park, Fraser and Rabbit Ears Pass, are used as the spatial framework and data from the intensive observing periods during February and March 2003 are used for testing the <span class="hlt">AMSR-E</span> retrievals. Field measurements of SWE from the ground campaign are compared with <span class="hlt">AMSR-E</span> estimates. In North Park MSA, extensive SWE field surveys were conducted within the entire 25 x 25 km MSA to enable the characterization of SWE variability at the <span class="hlt">AMSR-E</span> grid scale. For the other two MSAs, only intensive study area measurements were made and these data cannot be used to represent the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.youtube.com/watch?v=at1N3uSvAmM','SCIGOVIMAGE-NASA'); return false;" href="http://www.youtube.com/watch?v=at1N3uSvAmM"><span>Arctic Sea <span class="hlt">Ice</span> Maximum 2011</span></a></p> <p><a target="_blank" href="http://www.nasa.gov/multimedia/videogallery/index.html">NASA Video Gallery</a></p> <p></p> <p></p> <p><span class="hlt">AMSR-E</span> Arctic Sea <span class="hlt">Ice</span>: September 2010 to March 2011: Scientists tracking the annual maximum extent of Arctic sea <span class="hlt">ice</span> said that 2011 was among the lowest <span class="hlt">ice</span> extents measured since satellites began ...</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_1");'>1</a></li> <li class="active"><span>2</span></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_2 --> <div id="page_3" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_1");'>1</a></li> <li><a href="#" onclick='return showDiv("page_2");'>2</a></li> <li class="active"><span>3</span></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="41"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFMGC51E0795Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFMGC51E0795Z"><span>Extracting Microwave Emissivity Characteristics over City using <span class="hlt">AMSR-E</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhang, T.; Zhang, L.; Jiang, L.; Li, Y.</p> <p>2010-12-01</p> <p>The spectrums of different land types are very important in the application of remote sensing. Different spectrums of different land types can be used in surface classification, change detection, and so on. The microwave emissivity over land is the foundation of land parameters retrieval using passive microwave remote sensing. It depends on land type due to different objects’ structure, moisture and roughness on the earth. It has shown that the land surface microwave emissivity contributed to atmosphere temperature and moisture retrieval. Meanwhile, it depends on land type, vegetation cover, and moisture et al.. There are many researches on microwave emissivity of various land types, such as bare soil, vegetation, snow, but city was less mentioned [1]. However, with the development of society, the process of urbanization accelerated quickly. The area of city expanded fast and the fraction of city area increased in one microwave pixel, especially in The North China Plain (about 30%). The passive microwave pixel containing city has impact on satellite observation and surface parameters retrieval then. So it is essential to study the emissivity of city in order to improve the accuracy of land surface parameters retrieval from passive microwave remote sensing. To study the microwave emissivity of city, some ‘pure’ city pixels were selected according to IGBP classification data, which was defined the fraction cover of city is larger than 85%. The city emissivity was calculated using <span class="hlt">AMSR-E</span> L2A brightness temperature and GLDAS land surface temperature data at different frequencies and polarizations over 2008 in China. Then the seasonal variation was analyzed along the year. Finally, the characteristic of city emissivity were compared with some meteorological data, seeking the relationship between city emissivity and climatic factors. The results have shown that the emissivity of city was different for different frequencies. It increased with the frequency becoming</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20070035107&hterms=Wegener+Alfred&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3DWegener%252C%2BAlfred','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20070035107&hterms=Wegener+Alfred&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3DWegener%252C%2BAlfred"><span>ARISE (Antarctic Remote <span class="hlt">Ice</span> Sensing Experiment) in the East 2003: Validation of Satellite-derived Sea-<span class="hlt">ice</span> Data Product</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Massom, Robert A.; Worby, Anthony; Lytle, Victoria; Markus, Thorsten; Allison, Ian; Scambos, Theodore; Enomoto, Hiroyuki; Tateyama, Kazutaka; Haran, Terence; Comiso, Josefino C.; Pfaffling, Andreas; Tamura, Takeshi; Muto, Atsuhiro; Kanagaratnam, Pannir; Giles, Barry; Young, Neal; Hyland, Glenn; Key, Erica</p> <p>2006-01-01</p> <p>Preliminary results are presented from the first validation of geophysical data products (<span class="hlt">ice</span> <span class="hlt">concentration</span>, snow thickness on sea <span class="hlt">ice</span> (h(sub s) and <span class="hlt">ice</span> temperature (T(sub i))fr om the NASA EOS Aqua <span class="hlt">AMSR-E</span> sensor, in East Antarctica (in September-October 2003). The challenge of collecting sufficient measurements with which to validate the coarse-resolution <span class="hlt">AMSR-E</span> data products adequately was addressed by means of a hierarchical approach, using detailed in situ measurements, digital aerial photography and other satellite data. Initial results from a circumnavigation of the experimental site indicate that, at least under cold conditions with a dry snow cover, there is a reasonably close agreement between satellite- and aerial-photo-derived <span class="hlt">ice</span> <span class="hlt">concentrations</span>, i.e. 97.2+/-.6% for NT2 and 96.5+/-2.5% for BBA algorithms vs 94.3% for the aerial photos. In general, the <span class="hlt">AMSR-E</span> <span class="hlt">concentration</span> represents a slight overestimate of the actual <span class="hlt">concentration</span>, with the largest discrepancies occurring in regions containing a relatively high proportion of thin <span class="hlt">ice</span>. The <span class="hlt">AMSR-E</span> <span class="hlt">concentrations</span> from the NT2 and BBA algorithms are similar on average, although differences of up to 5% occur in places, again related to thin-<span class="hlt">ice</span> distribution. The <span class="hlt">AMSR-E</span> <span class="hlt">ice</span> temperature (T(sub i)) product agrees with coincident surface measurements to approximately 0.5 C in the limited dataset analyzed. Regarding snow thickness, the AMSR h(sub s) retrieval is a significant underestimate compared to in situ measurements weighted by the percentage of thin <span class="hlt">ice</span> (and open water) present. For the case study analyzed, the underestimate was 46% for the overall average, but 23% compared to smooth-<span class="hlt">ice</span> measurements. The spatial distribution of the <span class="hlt">AMSR-E</span> h(sub s) product follows an expected and consistent spatial pattern, suggesting that the observed difference may be an offset (at least under freezing conditions). Areas of discrepancy are identified, and the need for future work using the more extensive dataset is</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006AGUFM.C13A..06A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006AGUFM.C13A..06A"><span><span class="hlt">AMSR-E</span> Algorithm for Snowmelt Onset Detection in Subarctic Heterogeneous Terrain</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Apgar, J. D.; Ramage, J. M.; McKenney, R. A.; Kopczynski, S. E.; Haight, S. L.; Maltais, P.</p> <p>2006-12-01</p> <p>Snowmelt onset in the mixed terrain of the upper Yukon River basin, Canada, can be derived from brightness temperatures (Tb) obtained by the Advanced Microwave Scanning Radiometer for EOS (<span class="hlt">AMSR-E</span>) on NASA's Aqua satellite. <span class="hlt">AMSR-E</span>, with a resolution of 14 x 8 km2 for the 36.5 GHz frequency and two to four observations per day, improves upon the twice-daily coverage (EASE-Grid) and 37 x 28 km2 spatial resolution of the Special Sensor Microwave Imager (SSM/I). The onset of melt within a snowpack causes an increase in the daytime 36.5 GHz vertically polarized Tb as well as a shift to high diurnal amplitude variations (DAV) as the snow melts during the day and refreezes at night. The higher temporal and spatial resolutions, as well as the timing of data acquisition, make <span class="hlt">AMSR-E</span> more sensitive than SSM/I to sub-daily Tb oscillations, resulting in DAV that show a greater daily range compared to SSM/I. Using ground- based surface temperature and snowpack wetness to verify satellite interpretations, the snowmelt thresholds of Tb > 246 K and DAV > ±10 K developed for use with SSM/I have been adjusted for detecting melt onset with <span class="hlt">AMSR-E</span> to Tb > 252 K and DAV > ±18 K. <span class="hlt">AMSR-E</span> derived snowmelt onset correspond with SSM/I observations in the small subarctic Wheaton River basin (~60°08'05"N, ~134°53'45"W) through the 2004 and 2005 spring transitions. Snowpack wetness measurements collected in the Wheaton basin during the spring of 2005 relate well with temporally-corresponding <span class="hlt">AMSR-E</span> Tb and the established snowmelt thresholds. The enhanced resolution of <span class="hlt">AMSR-E</span> is more effective than SSM/I at delineating both spatial and temporal snowmelt dynamics in the heterogeneous terrain of the upper Yukon River basin. The use of this <span class="hlt">AMSR-E</span> snowmelt onset algorithm in other areas of the subarctic will ultimately allow for a more thorough examination of the impact of spring snowmelt upon basin hydrology and regional climate.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=270985','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=270985"><span>Aqua <span class="hlt">AMSR-E</span> soil moisture retrieval: Evaluation and potential Algorithm improvement</span></a></p> <p><a target="_blank" href="http://www.ars.usda.gov/services/TekTran.htm">Technology Transfer Automated Retrieval System (TEKTRAN)</a></p> <p></p> <p></p> <p>Global estimates of soil moisture derived from the Advanced Microwave Scanning Radiometer on Aqua (<span class="hlt">AMSR-E</span>) have been an invaluable resource over the past decade for a broad spectrum of research and applications that include global hydrology, agriculture, and climate and weather forecasting. NASA, as...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20170002034&hterms=algorithms&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dalgorithms','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20170002034&hterms=algorithms&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dalgorithms"><span>A New Operational Snow Retrieval Algorithm Applied to Historical <span class="hlt">AMSR-E</span> Brightness Temperatures</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Tedesco, Marco; Jeyaratnam, Jeyavinoth</p> <p>2016-01-01</p> <p>Snow is a key element of the water and energy cycles and the knowledge of spatio-temporal distribution of snow depth and snow water equivalent (SWE) is fundamental for hydrological and climatological applications. SWE and snow depth estimates can be obtained from spaceborne microwave brightness temperatures at global scale and high temporal resolution (daily). In this regard, the data recorded by the Advanced Microwave Scanning Radiometer-Earth Orbiting System (EOS) (<span class="hlt">AMSR-E</span>) onboard the National Aeronautics and Space Administration's (NASA) AQUA spacecraft have been used to generate operational estimates of SWE and snow depth, complementing estimates generated with other microwave sensors flying on other platforms. In this study, we report the results concerning the development and assessment of a new operational algorithm applied to historical <span class="hlt">AMSR-E</span> data. The new algorithm here proposed makes use of climatological data, electromagnetic modeling and artificial neural networks for estimating snow depth as well as a spatio-temporal dynamic density scheme to convert snow depth to SWE. The outputs of the new algorithm are compared with those of the current <span class="hlt">AMSR-E</span> operational algorithm as well as in-situ measurements and other operational snow products, specifically the Canadian Meteorological Center (CMC) and GlobSnow datasets. Our results show that the <span class="hlt">AMSR-E</span> algorithm here proposed generally performs better than the operational one and addresses some major issues identified in the spatial distribution of snow depth fields associated with the evolution of effective grain size.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2005AGUSM.H33C..03L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2005AGUSM.H33C..03L"><span>Validation of Retrieved Soil Moisture From <span class="hlt">AMSR-E</span> Brightness Temperatures Over the SMEX02 Domain</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Laymon, C.; Crosson, W.; Limaye, A.</p> <p>2005-05-01</p> <p>A coupled hydrologic/radiobrightness model (H/RM) is utilized to estimate brightness temperatures at C and X bands and associated soil moisture for validation of soil moisture retrieved from the Advanced Microwave Scanning Radiometer for the Earth Observing System (<span class="hlt">AMSR-E</span>). This study is focused on the SMEX02 study area in central Iowa. The oversampling of the <span class="hlt">AMSR-E</span> instrument is exploited in an optimization algorithm to deconvolve the brightness temperature observations for each EASEgrid cell. In so doing, the influence from adjacent grid cells is much less than with conventional spatial analysis schemes. The high spatial and temporal resolution of H/RM modeling relative to <span class="hlt">AMSR-E</span> observations permits a statistical assessment of subgrid-scale characteristics. These results are combined with a sensitivity study of parameters used in the radiobrightness model to derive error statistics for the <span class="hlt">AMSR-E</span> retrievals. In addition, we examine other sources of operational validation errors, such as, a) the errors associated with using limited gravimetric soil moisture data or point-scale measurements of soil moisture from network stations to estimate footprint-scale mean soil moisture, b) the errors associated with asynchronous sampling times, and c) the relationship between surface moisture (~1 cm) and profile moisture. These analyses are necessary to characterize the accuracy of the AMSR data products at EASE-grid scale. Although <span class="hlt">AMSR-E</span> C band brightness temperatures are contaminated with radio frequency interference over the continental U.S., H/RM-estimated C and X band brightness temperatures are examined comparatively to reevaluate the value of C band retrievals elsewhere.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.H21I0824X','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.H21I0824X"><span>Atmospheric and forest decoupling from <span class="hlt">AMSR-E</span> passive microwave brightness temperature observations in snow-covered regions over North America</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Xue, Y.; Forman, B. A.</p> <p>2014-12-01</p> <p>Remotely-sensed measurements from space-borne instrumentation have been extensively utilized in order to quantify snow water equivalent (SWE) across the globe, primarily in the form of SWE retrievals derived from passive microwave (PMW) brightness temperature (Tb) measurements. However, the application of these SWE retrieval products is largely limited by wet snow, deep snow, overlying vegetation, depth hoar, <span class="hlt">ice</span> crusts, sub-grid scale lake <span class="hlt">ice</span>, snow stratigraphy, and snow morphology. Alternatively, PMW Tb can be integrated directly (i.e., without the need of a SWE retrieval algorithm) into a land surface model as part of a Tb data assimilation (DA) framework. However, it is worthwhile to first decouple non-SWE related signals from the Tb observations prior to assimilation of the SWE-related Tb information. This study addresses two significant sources of SWE-related uncertainties using the Advanced Microwave Scanning Radiometer (<span class="hlt">AMSR-E</span>) PMW Tb observations. Namely, atmospheric and overlying forest effects are decoupled using relatively simple radiative transfer models. Comparisons against independent Tb measurements collected during airborne PMW Tb surveys highlight the effectiveness of <span class="hlt">AMSR-E</span> Tb measurements decoupling with the eventual goal of enhancing estimated SWE as part of a PMW Tb data assimilation framework into an advanced land surface model.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27924293','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27924293"><span>Use of <span class="hlt">AMSR-E</span> microwave satellite data for land surface characteristics and snow cover variation.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Boori, Mukesh Singh; Ferraro, Ralph R; Choudhary, Komal; Kupriyanov, Alexander</p> <p>2016-12-01</p> <p>This data article contains data related to the research article entitled "Global land cover classification based on microwave polarization and gradient ratio (MPGR)" [1] and "Microwave polarization and gradient ratio (MPGR) for global land surface phenology" [2]. This data article presents land surface characteristics and snow cover variation information from sensors like EOS Advanced Microwave Scanning Radiometer (<span class="hlt">AMSR-E</span>). This data article use the HDF Explorer, Matlab, and ArcGIS software to process the pixel latitude, longitude, snow water equivalent (SWE), digital elevation model (DEM) and Brightness Temperature (BT) information from <span class="hlt">AMSR-E</span> satellite data to provide land surface characteristics and snow cover variation data in all-weather condition at any time. This data information is useful to discriminate different land surface cover types and snow cover variation, which is turn, will help to improve monitoring of weather, climate and natural disasters.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012EGUGA..14.3944X','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012EGUGA..14.3944X"><span>A blending snow cover data base on MODIS and <span class="hlt">AMSR-E</span> snow cover in Qinghai-Tibet Plateau</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Xiaohua, H.; Wang, J.; Che, T.; Dai, L. Y.</p> <p>2012-04-01</p> <p>The algorithms of MODIS Terra and MODIS Aqua versions of the snow products have been developed by the NASA National Snow and <span class="hlt">Ice</span> Data Center (NSIDC). The MODIS global snow-cover products have been available through the NSIDC Distributed Active Archive Center (DAAC) since February 24, 2000 to Terra and July 4, 2002 to Aqua. The MODIS snow-cover maps represent a potential improvement relative to hemispheric-scale snow maps that are available today mainly because of the improved spatial resolution and snow/cloud discrimination capabilities of MODIS, and the frequent global coverage. In China, the snow distribution is different to other regions. Their accuracy on Qinghai-Tibet Plateau (QTP), however, has not yet been established. There are some drawbacks about NSIDC global snow cover products on QTP: 1. The characteristics of snow depth distribution on QTP: Thin, discontinuous. Our research indicated the MODIS snow-cover products underestimated the snow cover area in QTP. 2. The daily snow cover product from MODIS-Terra and Aqua can include the data gaps. 3. The snow products can separate snow from most obscuring clouds. However, there are still many cloud pixels in daily snow cover products. The study developed a new blending daily snow cover algorithm through improving the NSIDC snow algorithms and combining MODIS and <span class="hlt">AMSR-E</span> data in QTP. The new snow cover products will provide daily snow cover at 500-m resolution in QTP. The new snow cover algorithm employs a grouped-criteria technique using the Normalized Difference Snow Index (NDSI) and other spectral threshold tests and image fusion technology to identify and classify snow on a pixel-by-pixel basis. The usefulness of the NDSI is based on the fact that snow and <span class="hlt">ice</span> are considerably more reflective in the visible than in the shortwave IR part of the spectrum, and the reflectance of most clouds remains high in the short-wave IR, while the reflectance of snow is low. We propose a set of three steps, based on a</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JHyd..540...26D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JHyd..540...26D"><span>Assimilation of <span class="hlt">AMSR-E</span> snow water equivalent data in a spatially-lumped snow model</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dziubanski, David J.; Franz, Kristie J.</p> <p>2016-09-01</p> <p>Accurately initializing snow model states in hydrologic prediction models is important for estimating future snowmelt, water supplies, and flooding potential. While ground-based snow observations give the most reliable information about snowpack conditions, they are spatially limited. In the north-central USA, there are no continual observations of hydrologically critical snow variables. Satellites offer the most likely source of spatial snow data, such as the snow water equivalent (SWE), for this region. In this study, we test the impact of assimilating SWE data from the Advanced Microwave Scanning Radiometer - Earth Observing System (<span class="hlt">AMSR-E</span>) instrument into the US National Weather Service (NWS) SNOW17 model for seven watersheds in the Upper Mississippi River basin. The SNOW17 is coupled with the NWS Sacramento Soil Moisture Accounting (SACSMA) model, and both simulated SWE and discharge are evaluated. The ensemble Kalman filter (EnKF) assimilation framework is applied and updating occurs on a daily cycle for water years 2006-2011. Prior to assimilation, <span class="hlt">AMSR-E</span> data is bias corrected using data from the National Operational Hydrologic Remote Sensing Center (NOHRSC) airborne snow survey program. An average <span class="hlt">AMSR-E</span> SWE bias of -17.91 mm was found for the study basins. SNOW17 and SAC-SMA model parameters from the North Central River Forecast Center (NCRFC) are used. Compared to a baseline run without assimilation, the SWE assimilation improved discharge for five of the seven study sites, in particular for high discharge magnitudes associated with snow melt runoff. SWE and discharge simulations suggest that the SNOW17 is underestimating SWE and snowmelt rates in the study basins. Deep snow conditions and periods of snowmelt may have introduced error into the assimilation due to difficulty obtaining accurate brightness temperatures under these conditions. Overall results indicate that the <span class="hlt">AMSR-E</span> data and EnKF are viable and effective solutions for improving simulations</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20110023835&hterms=luc&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAuthor-Name%26N%3D0%26No%3D10%26Ntt%3Dluc','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20110023835&hterms=luc&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAuthor-Name%26N%3D0%26No%3D10%26Ntt%3Dluc"><span>Subsurface Emission Effects in <span class="hlt">AMSR-E</span> Measurements: Implications for Land Surface Microwave Emissivity Retrieval</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Galantowicz, John F.; Moncet, Jean-Luc; Liang, Pan; Lipton, Alan E.; Uymin, Gennady; Prigent, Catherine; Grassotti, Christopher</p> <p>2011-01-01</p> <p>An analysis of land surface microwave emission time series shows that the characteristic diurnal signature associated with subsurface emission in sandy deserts carry over to arid and semi-arid region worldwide. Prior work found that diurnal variation of Special Sensor Microwave/Imager (SSM/I) brightness temperatures in deserts was small relative to International Satellite Cloud Climatology Project land surface temperature (LST) variation and that the difference varied with surface type and was largest in sand sea regions. Here we find more widespread subsurface emission effects in Advanced Microwave Scanning Radiometer-EOS (<span class="hlt">AMSR-E</span>) measurements. The <span class="hlt">AMSR-E</span> orbit has equator crossing times near 01:30 and 13 :30 local time, resulting in sampling when near-surface temperature gradients are likely to be large and amplifying the influence of emission depth on effective emitting temperature relative to other factors. <span class="hlt">AMSR-E</span> measurements are also temporally coincident with Moderate Resolution Imaging Spectroradiometer (MODIS) LST measurements, eliminating time lag as a source of LST uncertainty and reducing LST errors due to undetected clouds. This paper presents monthly global emissivity and emission depth index retrievals for 2003 at 11, 19, 37, and 89 GHz from <span class="hlt">AMSR-E</span>, MODIS, and SSM/I time series data. Retrieval model fit error, stability, self-consistency, and land surface modeling results provide evidence for the validity of the subsurface emission hypothesis and the retrieval approach. An analysis of emission depth index, emissivity, precipitation, and vegetation index seasonal trends in northern and southern Africa suggests that changes in the emission depth index may be tied to changes in land surface moisture and vegetation conditions</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20090017698&hterms=inclusion+sport&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dinclusion%2Bsport','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20090017698&hterms=inclusion+sport&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dinclusion%2Bsport"><span>Combined MODIS/<span class="hlt">AMSR-E</span> SST Composites for Regional Weather Applications</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Jedlovec, Gary; Vazquez, Jorge; Armstrong, Ed; Haines, Stephanie</p> <p>2009-01-01</p> <p>Recent applications of a high resolution MODlS composite SST product have clearly shown the importance of developing high-resolution SST data sets for coastal applications and modeling. In general, coupling between the oceans and atmospheres has been closely linked to SST gradients and fronts, indicating a need for high resolution SSTs, specifically in the areas of large gradients associated with coastal regions. Thus an accurate determination of SST gradients has become critical for determining the appropriate air-sea coupling and the influence on ocean modeling. Recent research is focused on improving the accuracy and spatial coverage of the current operational MODIS SST composite product provided by the Short-term Prediction Research and Transition (SPORT) project and distributed to the community. GHRSST-PP MODlS data and microwave <span class="hlt">AMSR-E</span> data are being combined to produce composite data sets for both the West Coast and East Coast of the United States, including the Gulf of Mexico. The use of 1 km MODIS data has explicit advantages over other SST products including its global coverage and high resolution. The <span class="hlt">AMSR-E</span> data will reduce the latency of the composites. A strategy for utilizing the error characteristics contained in the GHRSST data has been developed. This strategy will include using the error characteristics directly to calculate weights in the SST composites, uncertainty maps based on the composite biases and RMS errors, and latency products calculated in the compositing process. Recent accomplishments include the development of an enhanced compositing approach based on the error-weighted combination of recent clear MODIS SST values, where the error contributions come from measurement error, potential cloud contamination, and data latency sources. Future plans call for the inclusion of <span class="hlt">AMSR-E</span> SST values with appropriate weights based upon measurement accuracy, MODIS-<span class="hlt">AMSR-E</span> SST bias, and latency.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C41D0720R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C41D0720R"><span>Detection of Rain-on-Snow (ROS) Events Using the Advanced Microwave Scanning Radiometer-Earth Observing System (<span class="hlt">AMSR-E</span>) and Weather Station Observations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ryan, E. M.; Brucker, L.; Forman, B. A.</p> <p>2015-12-01</p> <p>During the winter months, the occurrence of rain-on-snow (ROS) events can impact snow stratigraphy via generation of large scale <span class="hlt">ice</span> crusts, e.g., on or within the snowpack. The formation of such layers significantly alters the electromagnetic response of the snowpack, which can be witnessed using space-based microwave radiometers. In addition, ROS layers can hinder the ability of wildlife to burrow in the snow for vegetation, which limits their foraging capability. A prime example occurred on 23 October 2003 in Banks Island, Canada, where an ROS event is believed to have caused the deaths of over 20,000 musk oxen. Through the use of passive microwave remote sensing, ROS events can be detected by utilizing observed brightness temperatures (Tb) from <span class="hlt">AMSR-E</span>. Tb observed at different microwave frequencies and polarizations depends on snow properties. A wet snowpack formed from an ROS event yields a larger Tb than a typical dry snowpack would. This phenomenon makes observed Tb useful when detecting ROS events. With the use of data retrieved from <span class="hlt">AMSR-E</span>, in conjunction with observations from ground-based weather station networks, a database of estimated ROS events over the past twelve years was generated. Using this database, changes in measured Tb following the ROS events was also observed. This study adds to the growing knowledge of ROS events and has the potential to help inform passive microwave snow water equivalent (SWE) retrievals or snow cover properties in polar regions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.C41B0644K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.C41B0644K"><span>A Comparison of Snow Depth from GPS-Interferometry vs. <span class="hlt">AMSR-E</span>/AMSR-2</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kim, E. J.; Patel, H.; Wu, A.; Braun, J.; Small, E. E.; Larson, K. M.</p> <p>2013-12-01</p> <p>The validation of snow data products from satellite sensors has perennially faced the challenge of finding station data that is both widely distributed and possessing sufficient spatial density to provide accurate validation statistics. Point data from ground truth stations have been widely used despite the orders-of-magnitude scale mismatch as well as the insufficient spatial density; this has persisted mainly due to the lack of better alternatives. We evaluate a novel source of validation data that uses ground-based GPS networks, by comparison against snow data products from the <span class="hlt">AMSR-E</span> sensor aboard the Aqua satellite and now the AMSR2 sensor aboard the GCOM-W1satellite. There are three advantageous features of this approach. First, the GPS networks already exist. Second, the thousands of sites are widely distributed spatially and have a higher spatial density than other stations currently used for snow validation. And third, the observed area of the GPS technique approaches 10,000 m2--much larger than point-scale station observations (1 to 10 m2). Evaluating the new GPS approach along with the more well-known <span class="hlt">AMSR-E</span>/AMSR-2 snow depth product will provide a baseline for exploiting this potentially large new validation data source in a variety of remote sensing science studies. This work is based on recent advances in GPS techniques by Larson et al that have allowed geodetic quality GPS instrumentation to be used to measure changes in soil moisture and snow depth in the region surrounding GPS antennas. These retrievals relate observed changes in ground reflected GPS signals to changes in either the soil conditions around the antenna or the depth of snow at the site. In this paper, we will focus solely on snow depth. Observations from several GPS stations from the Plate Boundary Observatory (PBO), operating in varied locations in the western United States have been compared with <span class="hlt">AMSR-E</span> and/or AMSR-2 snow retrievals. These sites span a range of climates (especially</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.H43H1623C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.H43H1623C"><span>Intercomparison of AMSR2 and <span class="hlt">AMSR-E</span> Soil Moisture Retrievals with MERRA-L data set over Australia</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Cho, E.; Choi, M.; Su, C. H.; Ryu, D.; Kim, H.; Jacobs, J. M.</p> <p>2015-12-01</p> <p>Soil moisture is an important variable in the hydrological cycle on the land surface and plays an essential role in hydrological and meteorological processes. The Advanced Microwave Scanning Radiometer for Earth Observing System (<span class="hlt">AMSR-E</span>) sensor on board the Aqua satellite offered valuable soil moisture data set from June 2002 and October 2011 and has been used in a wide range of applications. However, the <span class="hlt">AMSR-E</span> sensor stopped operation from 4 October 2011 due to a problem with its antenna. <span class="hlt">AMSR-E</span> was replaced by the Advanced Microwave Scanning Radiometer 2 (AMSR2) on the Global Climate Change Observation Mission 1 - Water (GCOM-W1) satellite in May 2012. Assessment of AMSR2 soil moisture retrievals as compared to <span class="hlt">AMSR-E</span> has not yet been extensively evaluated. This task is critical if AMSR2 soil moisture products are used as a continuous dataset continuing the legacy of <span class="hlt">AMSR-E</span>. The purpose of this study is to inter-compare AMSR2 and <span class="hlt">AMSR-E</span> microwave based soil moisture over Australia, mediated by using model-based soil moisture data set to determine statistically similar inter-comparison periods from time periods of the individual sensors. This work use NASA-VUA AMSR2 and <span class="hlt">AMSR-E</span> based soil moisture products derived by the Land Parameter Retrieval Model (LPRM) and the modelled soil moisture from NASA's MERRA-L (Modern Era Retrospective-analysis for Research and Applications-Land) re-analysis. The satellite soil moisture products are compared against the MERRA-L using traditional metrics, and the random errors in individual products are estimated using lagged instrumental variable regression analysis. Generally, the results demonstrate that the two satellite-based soil moisture retrievals have reasonable agreement with MERRA-L soil moisture data set. The error differences are notable, with the zonal error statistics are higher for AMSR2 in all climate zones, though the error maps of AMSR2 and <span class="hlt">AMSR-E</span> are spatially similar over the Australia regions. This study leads</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016ChJOL.tmp..117L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016ChJOL.tmp..117L"><span>A comparison of Argo nominal surface and near-surface temperature for validation of <span class="hlt">AMSR-E</span> SST</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Liu, Zenghong; Chen, Xingrong; Sun, Chaohui; Wu, Xiaofen; Lu, Shaolei</p> <p>2016-06-01</p> <p>Satellite SST (sea surface temperature) from the Advanced Microwave Scanning Radiometer for the Earth Observing System (<span class="hlt">AMSR-E</span>) is compared with in situ temperature observations from Argo profiling floats over the global oceans to evaluate the advantages of Argo NST (near-surface temperature: water temperature less than 1 m from the surface). By comparing Argo nominal surface temperature (~5 m) with its NST, a diurnal cycle caused by daytime warming and nighttime cooling was found, along with a maximum warming of 0.08±0.36°C during 14:00-15:00 local time. Further comparisons between Argo 5-m temperature/Argo NST and <span class="hlt">AMSR-E</span> SST retrievals related to wind speed, columnar water vapor, and columnar cloud water indicate warming biases at low wind speed (<5 m/s) and columnar water vapor >28 mm during daytime. The warming tendency is more remarkable for <span class="hlt">AMSR-E</span> SST/Argo 5-m temperature compared with <span class="hlt">AMSR-E</span> SST/Argo NST, owing to the effect of diurnal warming. This effect of diurnal warming events should be excluded before validation for microwave SST retrievals. Both <span class="hlt">AMSR-E</span> nighttime SST/Argo 5-m temperature and nighttime SST/Argo NST show generally good agreement, independent of wind speed and columnar water vapor. From our analysis, Argo NST data demonstrated their advantages for validation of satellite-retrieved SST.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20040079837&hterms=Wegener+Alfred&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3DWegener%252C%2BAlfred','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20040079837&hterms=Wegener+Alfred&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3DWegener%252C%2BAlfred"><span>Validation of EOS Aqua AMSR Sea <span class="hlt">Ice</span> Products for East Antarctica</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Massom, Rob; Lytle, Vicky; Allison, Ian; Worby, Tony; Markus, Thorsten; Scambos, Ted; Haran, Terry; Enomoto, Hiro; Tateyama, Kazu; Pfaffling, Andi</p> <p>2004-01-01</p> <p>This paper presents results from <span class="hlt">AMSR-E</span> validation activities during a collaborative international cruise onboard the RV Aurora Australis to the East Antarctic sea <span class="hlt">ice</span> 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 <span class="hlt">ice</span> and snowcover over a Lagrangian grid 100 x 50 km in size (demarcated by 9 drifting <span class="hlt">ice</span> beacons) i.e. at a scale representative of Ah4SR pixels. <span class="hlt">Ice</span> conditions ranged h m consolidated first-year <span class="hlt">ice</span> to a large polynya offshore from Casey Base. Data sets collected include: snow depth and snow-<span class="hlt">ice</span> interface temperatures on 24 (?) randomly-selected floes in grid cells within a 10 x 50 km area (using helicopters); detailed snow and <span class="hlt">ice</span> measurements at 13 dedicated <span class="hlt">ice</span> 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); <span class="hlt">ice</span> drift data; and ancillary meteorological (ship-based, meteorological buoys, twice-daily radiosondes). These data are applied to a validation of standard <span class="hlt">AMSR-E</span> <span class="hlt">ice</span> <span class="hlt">concentration</span>, snowcover thickness and <span class="hlt">ice</span>-temperature products. In addition, a validation is carried out of <span class="hlt">ice</span>-surface skin temperature products h m the NOAA AVHRR and EOS MODIS datasets.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..16.6111M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..16.6111M"><span>A Round Robin evaluation of <span class="hlt">AMSR-E</span> soil moisture retrievals</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mittelbach, Heidi; Hirschi, Martin; Nicolai-Shaw, Nadine; Gruber, Alexander; Dorigo, Wouter; de Jeu, Richard; Parinussa, Robert; Jones, Lucas A.; Wagner, Wolfgang; Seneviratne, Sonia I.</p> <p>2014-05-01</p> <p>Large-scale and long-term soil moisture observations based on remote sensing are promising data sets to investigate and understand various processes of the climate system including the water and biochemical cycles. Currently, the ESA Climate Change Initiative for soil moisture develops and evaluates a consistent global long-term soil moisture data set, which is based on merging passive and active remotely sensed soil moisture. Within this project an inter-comparison of algorithms for <span class="hlt">AMSR-E</span> and ASCAT Level 2 products was conducted separately to assess the performance of different retrieval algorithms. Here we present the inter-comparison of <span class="hlt">AMSR-E</span> Level 2 soil moisture products. These include the public data sets from University of Montana (UMT), Japan Aerospace and Space Exploration Agency (JAXA), VU University of Amsterdam (VUA; two algorithms) and National Aeronautics and Space Administration (NASA). All participating algorithms are applied to the same <span class="hlt">AMSR-E</span> Level 1 data set. Ascending and descending paths of scaled surface soil moisture are considered and evaluated separately in daily and monthly resolution over the 2007-2011 time period. Absolute values of soil moisture as well as their long-term anomalies (i.e. removing the mean seasonal cycle) and short-term anomalies (i.e. removing a five weeks moving average) are evaluated. The evaluation is based on conventional measures like correlation and unbiased root-mean-square differences as well as on the application of the triple collocation method. As reference data set, surface soil moisture of 75 quality controlled soil moisture sites from the International Soil Moisture Network (ISMN) are used, which cover a wide range of vegetation density and climate conditions. For the application of the triple collocation method, surface soil moisture estimates from the Global Land Data Assimilation System are used as third independent data set. We find that the participating algorithms generally display a better</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20100005033&hterms=impact+surroundings&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dimpact%2Bsurroundings','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20100005033&hterms=impact+surroundings&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dimpact%2Bsurroundings"><span>Evaluation of Enhanced High Resolution MODIS/<span class="hlt">AMSR-E</span> SSTs and the Impact on Regional Weather Forecast</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Schiferl, Luke D.; Fuell, Kevin K.; Case, Jonathan L.; Jedlovec, Gary J.</p> <p>2010-01-01</p> <p>Over the last few years, the NASA Short-term Prediction Research and Transition (SPoRT) Center has been generating a 1-km sea surface temperature (SST) composite derived from retrievals of the Moderate Resolution Imaging Spectroradiometer (MODIS) for use in operational diagnostics and regional model initialization. With the assumption that the day-to-day variation in the SST is nominal, individual MODIS passes aboard the Earth Observing System (EOS) Aqua and Terra satellites are used to create and update four composite SST products each day at 0400, 0700, 1600, and 1900 UTC, valid over the western Atlantic and Caribbean waters. A six month study from February to August 2007 over the marine areas surrounding southern Florida was conducted to compare the use of the MODIS SST composite versus the Real-Time Global SST analysis to initialize the Weather Research and Forecasting (WRF) model. Substantial changes in the forecast heat fluxes were seen at times in the marine boundary layer, but relatively little overall improvement was measured in the sensible weather elements. The limited improvement in the WRF model forecasts could be attributed to the diurnal changes in SST seen in the MODIS SST composites but not accounted for by the model. Furthermore, cloud contamination caused extended periods when individual passes of MODIS were unable to update the SSTs, leading to substantial SST latency and a cool bias during the early summer months. In order to alleviate the latency problems, the SPoRT Center recently enhanced its MODIS SST composite by incorporating information from the Advanced Microwave Scanning Radiometer-EOS (<span class="hlt">AMSR-E</span>) instruments as well as the Operational Sea Surface Temperature and Sea <span class="hlt">Ice</span> Analysis. These enhancements substantially decreased the latency due to cloud cover and improved the bias and correlation of the composites at available marine point observations. While these enhancements improved upon the modeled cold bias using the original MODIS SSTs</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2003AGUFM.H32B0568H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2003AGUFM.H32B0568H"><span>An Assessment of the Use of <span class="hlt">AMSR</span> <span class="hlt">E</span> 10 GHz Data for Soil Moisture Estimation in SMEX02</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hsu, A. Y.; Jackson, T. J.; O'Neill, P. E.</p> <p>2003-12-01</p> <p>The launch of the Advanced Microwave Scanning Radiometer (<span class="hlt">AMSR-E</span>) on board the NASA EOS Aqua Satellite has drawn much interest from the scientific community that has been waiting for a low frequency spaceborne microwave radiometer (< 10 GHz) capable of measuring soil moisture. The <span class="hlt">AMSR-E</span> instrument was developed by the National Space Development Agency of Japan (NASDA) and makes dual-polarized microwave measurements at six frequencies: 6.9, 10.7, 18.7, 23.8, 36.5, and 89 GHz. Early examinations of <span class="hlt">AMSR-E</span> measurements have shown evidence of extensive Radio-Frequency Interference (RFI) in the 6.9 GHz channels, especially over the continental U.S. Due to the contamination of 6.9 GHz data by RFI, it may be necessary to use the next lowest frequency, 10.7 GHz, for soil moisture retrieval. This frequency has been available on the TRMM Microwave Imager for several years; however, the TRMM sensor only provides data between 38 N to 38 S in latitude whereas <span class="hlt">AMSR-E</span> provides global coverage. We examined the impact of alternative frequencies on soil moisture retrieval using data from the Soil Moisture Experiments in 2002 (SMEX02). SMEX02 took place in Walnut Creek Watershed and surrounding region of Iowa from June 24 to July 12. The experiment focused on microwave remote sensing of soil moisture in an agricultural setting. Land cover in the Walnut Creek Watershed consists of a patchwork of corn and soybean fields, with some isolated forested zones. This presents a challenge to soil moisture retrieval using <span class="hlt">AMSR-E</span> 10 GHz data. Extensive vegetation sampling was conducted during SMEX02 to provide information to estimate vegetation parameters required by retrieval algorithm. The maps of <span class="hlt">AMSR-E</span> 10 GHz data over the SMEX02 area from July 2 to 13 show the decrease of brightness temperature (TB) due to precipitation, although the range is not as profound as expected at L band. The Normalized Difference Polarization Index (NDPI), defined as (TBv-TBh)/(TBv+TBh), computed for various</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_1");'>1</a></li> <li><a href="#" onclick='return showDiv("page_2");'>2</a></li> <li class="active"><span>3</span></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_3 --> <div id="page_4" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_2");'>2</a></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li class="active"><span>4</span></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="61"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20150023295&hterms=sea+ice&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dsea%2Bice','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20150023295&hterms=sea+ice&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dsea%2Bice"><span>Sea <span class="hlt">Ice</span> <span class="hlt">Concentration</span> and Extent</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Comiso, Josefino C.</p> <p>2014-01-01</p> <p>Among the most seasonal and most dynamic parameters on the surface of the Earth is sea <span class="hlt">ice</span> which at any one time covers about 3-6% of the planet. In the Northern Hemisphere, sea <span class="hlt">ice</span> 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 <span class="hlt">ice</span> 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 <span class="hlt">ice</span> is very dynamic and usually follows the directions of the many gyres in the polar regions. Despite its vast expanse, the sea <span class="hlt">ice</span> 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.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110007071','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110007071"><span>Potential for Monitoring Snow Cover in Boreal Forests by Combining MODIS Snow Cover and <span class="hlt">AMSR-E</span> SWE Maps</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Riggs, George A.; Hall, Dorothy K.; Foster, James L.</p> <p>2009-01-01</p> <p>Monitoring of snow cover extent and snow water equivalent (SWE) in boreal forests is important for determining the amount of potential runoff and beginning date of snowmelt. The great expanse of the boreal forest necessitates the use of satellite measurements to monitor snow cover. Snow cover in the boreal forest can be mapped with either the Moderate Resolution Imaging Spectroradiometer (MODIS) or the Advanced Microwave Scanning Radiometer for EOS (<span class="hlt">AMSR-E</span>) microwave instrument. The extent of snow cover is estimated from the MODIS data and SWE is estimated from the <span class="hlt">AMSR-E</span>. Environmental limitations affect both sensors in different ways to limit their ability to detect snow in some situations. Forest density, snow wetness, and snow depth are factors that limit the effectiveness of both sensors for snow detection. Cloud cover is a significant hindrance to monitoring snow cover extent Using MODIS but is not a hindrance to the use of the <span class="hlt">AMSR-E</span>. These limitations could be mitigated by combining MODIS and <span class="hlt">AMSR-E</span> data to allow for improved interpretation of snow cover extent and SWE on a daily basis and provide temporal continuity of snow mapping across the boreal forest regions in Canada. The purpose of this study is to investigate if temporal monitoring of snow cover using a combination of MODIS and <span class="hlt">AMSR-E</span> data could yield a better interpretation of changing snow cover conditions. The MODIS snow mapping algorithm is based on snow detection using the Normalized Difference Snow Index (NDSI) and the Normalized Difference Vegetation Index (NDVI) to enhance snow detection in dense vegetation. (Other spectral threshold tests are also used to map snow using MODIS.) Snow cover under a forest canopy may have an effect on the NDVI thus we use the NDVI in snow detection. A MODIS snow fraction product is also generated but not used in this study. In this study the NDSI and NDVI components of the snow mapping algorithm were calculated and analyzed to determine how they changed</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2005AGUFM.H13J..04B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2005AGUFM.H13J..04B"><span>Long-Term Evaluation of the <span class="hlt">AMSR-E</span> Soil Moisture Product Over the Walnut Gulch Watershed, AZ</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bolten, J. D.; Jackson, T. J.; Lakshmi, V.; Cosh, M. H.; Drusch, M.</p> <p>2005-12-01</p> <p>The Advanced Microwave Scanning Radiometer -Earth Observing System (<span class="hlt">AMSR-E</span>) was launched aboard NASA's Aqua satellite on May 4th, 2002. Quantitative estimates of soil moisture using the <span class="hlt">AMSR-E</span> provided data have required routine radiometric data calibration and validation using comparisons of satellite observations, extended targets and field campaigns. The currently applied NASA EOS Aqua ASMR-E soil moisture algorithm is based on a change detection approach using polarization ratios (PR) of the calibrated <span class="hlt">AMSR-E</span> channel brightness temperatures. To date, the accuracy of the soil moisture algorithm has been investigated on short time scales during field campaigns such as the Soil Moisture Experiments in 2004 (SMEX04). Results have indicated self-consistency and calibration stability of the observed brightness temperatures; however the performance of the moisture retrieval algorithm has been poor. The primary objective of this study is to evaluate the quality of the current version of the <span class="hlt">AMSR-E</span> soil moisture product for a three year period over the Walnut Gulch Experimental Watershed (150 km2) near Tombstone, AZ; the northern study area of SMEX04. This watershed is equipped with hourly and daily recording of precipitation, soil moisture and temperature via a network of raingages and a USDA-NRCS Soil Climate Analysis Network (SCAN) site. Surface wetting and drying are easily distinguished in this area due to the moderately-vegetated terrain and seasonally intense precipitation events. Validation of <span class="hlt">AMSR-E</span> derived soil moisture is performed from June 2002 to June 2005 using watershed averages of precipitation, and soil moisture and temperature data from the SCAN site supported by a surface soil moisture network. Long-term assessment of soil moisture algorithm performance is investigated by comparing temporal variations of moisture estimates with seasonal changes and precipitation events. Further comparisons are made with a standard soil dataset from the European</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012EGUGA..14.8603S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012EGUGA..14.8603S"><span>Estimation of mass changes caused by vegetation using <span class="hlt">AMSR-E</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Schnitzer, S.; Abelen, S.; Menzel, A.; Seitz, F.</p> <p>2012-04-01</p> <p>Vegetation is one of the most important compartments in the global ecosystem, influencing soil, water balance, atmosphere, and the climate in general. Even though this is a known fact, large areas of rain forest are still destroyed for wood production or by food industries increasing their agricultural areas for soy production and stock farming. But also wild fires devastate large amounts to vegetation. Therefore, it is essential to monitor the changes of vegetation globally. In our study we address the question how big the mass changes in vegetation are. We observe the following sources of changes: 1) wild fires, 2) clear cut and 3) seasonal variations of vegetation. For the first two items we consider only forest areas where the biggest mass variations are taking place. The third point takes the entire range of vegetation classes into account. In order to observe vegetation globally we use remote sensing data from the sensor <span class="hlt">AMSR-E</span> (Advanced Microwave Scanning Radiometer - EOS) aboard of Nasa's Aqua satellite. This sensor provides data from 2002 until 2011. The data include information about the vegetation water content and are therefore ideal for our purpose. We validate our results with the help of additional databases listings, on e.g. large fire events, from literature as well as from in-situ data. The talk is concluded with a global map of hotspots of big vegetation mass changes and their triggers.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007AGUSM.H51C..02G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007AGUSM.H51C..02G"><span>Large Scale Evaluation of <span class="hlt">AMSR-E</span> Soil Moisture Products Based on Ground Soil Moisture Network Measurements</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gruhier, C.; de Rosnay, P.; Richaume, P.; Kerr, Y.; Rudiger, C.; Boulet, G.; Walker, J. P.; Mougin, E.; Ceschia, E.; Calvet, J.</p> <p>2007-05-01</p> <p>This paper presents an evaluation of <span class="hlt">AMSR-E</span> (Advanced Microwave Scanning Radiometer for EOS) soil moisture products, based on a comparison with three ground soil moisture networks. The selected ground sites are representative of various climatic, hydrologic and environmental conditions in temperate and semi-arid areas. They are located in the south-west of France, south-east of Australia and the Gourma region of the Sahel. These sites were respectively implemented in the framework of the projects SMOSREX (Surface Monitoring Of Soil Reservoir Experiment), SASMAS/GoREx (Scaling and Assimilation of Soil Moisture and Streamflow in the Goulburn River Experimental catchment) and AMMA (African Monsoon Multidisciplinary Analysis). In all cases, the arrangement of the soil moisture measuring sites was specifically designed to address the validation of remotely sensed soil moisture in the context of the preparation of the SMOS (Soil Moisture and Ocean Salinity) project. For the purpose of this study, 25km <span class="hlt">AMSR-E</span> products were used, including brightness temperatures at 6.9 and 10.7 GHz, and derived soil moisture. The study is focused on the year 2005. It is based on ground soil moisture network measurements from 4 stations for SMOSREX extended to the SUDOUEST project of CESBIO, 12 stations for GoRex, and 4 stations for AMMA. Temporal and spatial features of soil moisture variability and stability is a critical issue to be addressed for remotely sensed soil moisture validation. While ground measurements provide information on soil moisture dynamics at local scale and high temporal resolution (hourly), satellite measurements are sparser in time (up to several days), but cover a larger region (25km x 25km for <span class="hlt">AMSR-E</span>). First, a statistical analysis, including mean relative difference and Spearman rank, is conducted for the three soil moisture networks. This method is mainly based on the approach proposed by Cosh et al. (2004) for the purpose of the use of ground networks for</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1818103Q','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1818103Q"><span>Statistical Analysis of the Correlation between Microwave Emission Anomalies and Seismic Activity Based on <span class="hlt">AMSR-E</span> Satellite Data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>qin, kai; Wu, Lixin; De Santis, Angelo; Zhang, Bin</p> <p>2016-04-01</p> <p>Pre-seismic thermal IR anomalies and ionosphere disturbances have been widely reported by using the Earth observation system (EOS). To investigate the possible physical mechanisms, a series of detecting experiments on rock loaded to fracturing were conducted. Some experiments studies have demonstrated that microwave radiation energy will increase under the loaded rock in specific frequency and the feature of radiation property can reflect the deformation process of rock fracture. This experimental result indicates the possibility that microwaves are emitted before earthquakes. Such microwaves signals are recently found to be detectable before some earthquake cases from the brightness temperature data obtained by the microwave-radiometer Advanced Microwave-Scanning Radiometer for the EOS (<span class="hlt">AMSR-E</span>) aboard the satellite Aqua. This suggested that <span class="hlt">AMSR-E</span> with vertical- and horizontal-polarization capability for six frequency bands (6.925, 10.65, 18.7, 23.8, 36.5, and 89.0 GHz) would be feasible to detect an earthquake which is associated with rock crash or plate slip. However, the statistical analysis of the correlation between satellite-observed microwave emission anomalies and seismic activity are firstly required. Here, we focus on the Kamchatka peninsula to carry out a statistical study, considering its high seismicity activity and the dense orbits covering of <span class="hlt">AMSR-E</span> in high latitudes. 8-years (2003-2010) <span class="hlt">AMSR-E</span> microwave brightness temperature data were used to reveal the spatio-temporal association between microwave emission anomalies and 17 earthquake events (M>5). Firstly, obvious spatial difference of microwave brightness temperatures between the seismic zone at the eastern side and the non-seismic zone the western side within the Kamchatka peninsula are found. Secondly, using both vertical- and horizontal-polarization to extract the temporal association, it is found that abnormal changes of microwave brightness temperatures appear generally 2 months before the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009JGRD..11420104D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009JGRD..11420104D"><span>An EKF assimilation of <span class="hlt">AMSR-E</span> soil moisture into the ISBA land surface scheme</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Draper, C. S.; Mahfouf, J.-F.; Walker, J. P.</p> <p>2009-10-01</p> <p>An Extended Kalman Filter (EKF) for the assimilation of remotely sensed near-surface soil moisture into the Interactions between Surface, Biosphere, and Atmosphere (ISBA) model is described. ISBA is the land surface scheme in Météo-France's Aire Limitée Adaptation Dynamique développement InterNational (ALADIN) Numerical Weather Prediction (NWP) model, and this work is directed toward providing initial conditions for NWP. The EKF is used to assimilate near-surface soil moisture observations retrieved from C-band Advanced Microwave Scanning Radiometer (<span class="hlt">AMSR-E</span>) brightness temperatures into ISBA. The EKF can translate near-surface soil moisture observations into useful increments to the root-zone soil moisture. If the observation and model soil moisture errors are equal, the Kalman gain for the root-zone soil moisture is typically 20-30%, resulting in a mean net monthly increment for July 2006 of 0.025 m3 m-3 over ALADIN's European domain. To test the benefit of evolving the background error, the EKF is compared to a Simplified EKF (SEKF), in which the background errors at the time of the analysis are constant. While the Kalman gains for the EKF and SEKF are derived from different model processes, they produce similar soil moisture analyses. Despite this similarity, the EKF is recommended for future work where the extra computational expense can be afforded. The method used to rescale the near-surface soil moisture data to the model climatology has a greater influence on the analysis than the error covariance evolution approach, highlighting the importance of developing appropriate methods for rescaling remotely sensed near-surface soil moisture data.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015FrEaS...3...16P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015FrEaS...3...16P"><span>a Comparison Between Two Algorithms for the Retrieval of Soil Moisture Using <span class="hlt">Amsr-E</span> Data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Paloscia, Simonetta; Santi, Emanuele; Pettinato, Simone; Mladenova, Iliana; Jackson, Tom; Cosh, Michael</p> <p>2015-04-01</p> <p>A comparison between two algorithms for estimating soil moisture with microwave satellite data was carried out by using the datasets collected on the four Agricultural Research Service (ARS) watershed sites in the US from 2002 to 2009. These sites collectively represent a wide range of ground conditions and precipitation regimes (from natural to agricultural surfaces and from desert to humid regions) and provide long-term in-situ data. One of the algorithms is the artificial neural network-based algorithm developed by the Institute of Applied Physics of the National Research Council (IFAC-CNR) (HydroAlgo) and the second one is the Single Channel Algorithm (SCA) developed by USDA-ARS (US Department of Agriculture-Agricultural Research Service). Both algorithms are based on the same radiative transfer equations but are implemented very differently. Both made use of datasets provided by the Japanese Aerospace Exploration Agency (JAXA), within the framework of Advanced Microwave Scanning Radiometer-Earth Observing System (<span class="hlt">AMSR-E</span>) and Global Change Observation Mission-Water GCOM/AMSR-2 programs. Results demonstrated that both algorithms perform better than the mission specified accuracy, with Root Mean Square Error (RMSE) ≤0.06 m3/m3 and Bias <0.02 m3/m3. These results expand on previous investigations using different algorithms and sites. The novelty of the paper consists of the fact that it is the first intercomparison of the HydroAlgo algorithm with a more traditional retrieval algorithm, which offers an approach to higher spatial resolution products.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.H31D1141L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.H31D1141L"><span><span class="hlt">AMSR-E</span> satellite observed rainforest responses during the 2005 and 2010 Amazon droughts</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Liu, Y.; McCabe, M. F.; Evans, J. P.; de Jeu, R.</p> <p>2012-12-01</p> <p>The Amazon rainforest plays an important role in the global hydrological cycle and effects the climate at both regional and global scales. Continuous large-scale deforestation and associated fire activities have been an issue of international significance over the last two decades, while in more recent times two historic droughts impacted vast areas of the Amazon in 2005 and 2010. These interrelated issues have considerable ecological response, and underline the need for a consistent observation system to comprehensively characterize the rainforest dynamics. Satellite-based remote sensing offer the only viable approach at monitoring the vegetation state at large space and time scales. Most studies examining these issues have used the Enhanced Vegetation Index (EVI), a vegetation greenness index with characteristics similar to NDVI derived from remote optical sensors. Like any optical observation, EVI is affected by water vapor, clouds and aerosols in the atmosphere, and there has been some debate about their influence on inferred vegetation changes during the recent droughts over the Amazon. Unlike optical remote sensing, passive microwave observations are not affected by such atmospheric phenomena and can measure both leaf and woody components of aboveground living biomass through a retrieved property termed the vegetation optical depth (VOD), by virtue of the sensitivity of passive microwave emissions to water in the environment. The microwave-based vegetation record therefore provides a unique opportunity to examine forest response during the 2005 and 2010 drought that is complementary to the vegetation index analysis. In this study, we apply the VOD data retrieved from the Advanced Microwave Scanning Radiometer for EOS (<span class="hlt">AMSR-E</span>), rainfall data from Tropical Rainfall Measuring Mission (TRMM), water level data obtained from in situ measurements and fire observations based on the MODIS instrument to investigate large scale forest dynamics. Results indicate that the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20110023836&hterms=Quality+Control&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3DQuality%2BControl','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20110023836&hterms=Quality+Control&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3DQuality%2BControl"><span>Land Surface Microwave Emissivities Derived from <span class="hlt">AMSR-E</span> and MODIS Measurements with Advanced Quality Control</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Moncet, Jean-Luc; Liang, Pan; Galantowicz, John F.; Lipton, Alan E.; Uymin, Gennady; Prigent, Catherine; Grassotti, Christopher</p> <p>2011-01-01</p> <p>A microwave emissivity database has been developed with data from the Advanced Microwave Scanning Radiometer-EOS (<span class="hlt">AMSR-E</span>) and with ancillary land surface temperature (LST) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the same Aqua spacecraft. The primary intended application of the database is to provide surface emissivity constraints in atmospheric and surface property retrieval or assimilation. An additional application is to serve as a dynamic indicator of land surface properties relevant to climate change monitoring. The precision of the emissivity data is estimated to be significantly better than in prior databases from other sensors due to the precise collocation with high-quality MODIS LST data and due to the quality control features of our data analysis system. The accuracy of the emissivities in deserts and semi-arid regions is enhanced by applying, in those regions, a version of the emissivity retrieval algorithm that accounts for the penetration of microwave radiation through dry soil with diurnally varying vertical temperature gradients. These results suggest that this penetration effect is more widespread and more significant to interpretation of passive microwave measurements than had been previously established. Emissivity coverage in areas where persistent cloudiness interferes with the availability of MODIS LST data is achieved using a classification-based method to spread emissivity data from less-cloudy areas that have similar microwave surface properties. Evaluations and analyses of the emissivity products over homogeneous snow-free areas are presented, including application to retrieval of soil temperature profiles. Spatial inhomogeneities are the largest in the vicinity of large water bodies due to the large water/land emissivity contrast and give rise to large apparent temporal variability in the retrieved emissivities when satellite footprint locations vary over time. This issue will be dealt with in the future by</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JHyd..547...67L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JHyd..547...67L"><span>Performance of <span class="hlt">AMSR_E</span> soil moisture data assimilation in CLM4.5 model for monitoring hydrologic fluxes at global scale</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Liu, Di; Mishra, Ashok K.</p> <p>2017-04-01</p> <p>In this study, we evaluated the performance of community land surface model (CLM4.5) to simulate the hydrologic fluxes, such as, soil moisture (SM), evapotranspiration (ET) and runoff with (without) remote sensing data assimilation. The Advanced Microwave Scanning Radiometer-Earth Observing System (<span class="hlt">AMSR_E</span>) daily SM (both ascending and descending) are incorporated into the CLM4.5 model using data assimilation (DA) technique. The GLDAS data is used to validate the <span class="hlt">AMSR_E</span> SM data and evaluate the performance of CLM4.5 simulations. The <span class="hlt">AMSR_E</span> SM data are rescaled to meet the resolution of CLM4.5 model. By assimilating the <span class="hlt">AMSR_E</span> SM data into the CLM4.5 model can improve the SM simulations, especially over the climate transition zones in Africa, East Australia, South South America, Southeast Asia, and East North America in summer season. The Local Ensemble Kalman Filter (LEnKF) technique improves the performance of CLM4.5 model compared to the directly substituted method. The improvement in ET and surface runoff simulations from CLM4.5 model assimilated with <span class="hlt">AMSR_E</span> SM data shares similar spatial patterns with SM.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://pubs.er.usgs.gov/publication/70026403','USGSPUBS'); return false;" href="http://pubs.er.usgs.gov/publication/70026403"><span>Comparison of <span class="hlt">AMSR-E</span> and SSM/I snow parameter retrievals over the Ob river basin</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Mognard, N.M.; Grippa, M.; LeToan, T.; Kelly, R.E.J.; Chang, A.T.C.; Josberger, E.G.</p> <p>2004-01-01</p> <p>Passive microwave observations from the Advanced Microwave Scanning Radiometer - EOS (<span class="hlt">AMSR-E</span>) and from the Special Sensor Microwave Imager (SSM/I) are used to analyse the evolution of the snow pack in the Ob river basin during the snow season of 2002-03. The Ob river is the biggest Russian river with respect to its watershed area (2 975 000 km2). The Ob originates in the Altai mountains and flows northward across the vast West Siberian lowland towards the Arctic Ocean. The majority of snow cover is contained in the lowlands rather than in mountainous regions and persists for six months or more. During the snow season, surface air temperatures are very cold. Therefore, the combination of cold dry snow and large areas of uniform topography is ideal for snowpack extent and water equivalent retrievals from passive microwave observations. The thermal gradient through the snow pack is estimated and used to model the growth of the snow grain size and to compute the evolution of the passive microwave derived snow depth over the region. A comparison between the <span class="hlt">AMSR-E</span> and SSM/I estimates is performed and the differences between the snow parameters from the two satellite instruments are analysed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://pubs.usgs.gov/dds/dds27/','USGSPUBS'); return false;" href="https://pubs.usgs.gov/dds/dds27/"><span>Monthly average polar sea-<span class="hlt">ice</span> <span class="hlt">concentration</span></span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Schweitzer, Peter N.</p> <p>1995-01-01</p> <p>The data contained in this CD-ROM depict monthly averages of sea-<span class="hlt">ice</span> <span class="hlt">concentration</span> in the modern polar oceans. These averages were derived from the Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave/Imager (SSM/I) instruments aboard satellites of the U.S. Air Force Defense Meteorological Satellite Program from 1978 through 1992. The data are provided as 8-bit images using the Hierarchical Data Format (HDF) developed by the National Center for Supercomputing Applications.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..15.4861L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..15.4861L"><span>Estimating mountainous snow water equivalent via ensemble Kalman filtering with improved <span class="hlt">AMSR-E</span> observation and model representation</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Li, Dongyue; Durand, Michael; Margulis, Steven</p> <p>2013-04-01</p> <p>Snowpack in the Sierra Nevada mountain ranges serves as a critical water resource and an important climate indicator. Accurately estimating snow water equivalent (SWE) and melt timing in the Sierra has both civil and scientific merits. Passive microwave remote sensing (PM) contains spatial-continuous SWE information, however its coarse resolution makes it difficult or impossible for direct SWE retrieval in mountainous regions. Physical process based land surface model (LSM) could be set up at high spatial resolution to simulate SWE, nevertheless biased meteorological forcing usually lead to significant biased and uncertain modeling results. Assimilating PM into LSM could combine the advantages of both sides, offering a path to a better SWE characterization in mountainous area. In this study, downscaled PM measurements are assimilated into a high-resolution model through Ensemble Kalman Filter (EnKF) to estimate SWE in the Sierra. The study is carried out at Kern Basin where SWE are highly variable as a result of complex terrain. SSiB3 and MEMLS are coupled to provide priori prediction. NLDAS2 data are used to force the coupled model, bias in NLDAS2 has been pre-removed via Bayesian reconstruction. <span class="hlt">AMSR-E</span> brightness temperature (Tb) is assimilated into the model to reduce the model error and uncertainty. The novelty of this study is that both modeling and PM measurements, which are two SWE information resources in EnKF, have been enhanced to contribute more signals. As there is more information in both model prediction and measurement, it is reasonable to expect an even better posterior SWE than previous EnKF PM assimilations. In this study, rather than using EASE-Grid Tb, the Tb data is obtained by processing raw <span class="hlt">AMSR-E</span> 37GHz V-pol observed Tb at its native footprint resolution (L2A) of 14 km x 8 km, which is 1/6 of the size of an EASE-Grid cell. Preliminary results show this effective rise in data resolution makes L2A Tb contains three times more information about</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.H21I0836F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.H21I0836F"><span>Transferability and prediction of AMSR2 brightness temperatures over snow-covered land based on <span class="hlt">AMSR-E</span> brightness temperatures and machine learning algorithms</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Forman, B. A.</p> <p>2014-12-01</p> <p>Recent studies [Forman et al., 2013, IEEE; Forman and Reichle, 2014, IEEE] demonstrated the capability of machine learning (ML) algorithms to predict passive microwave (PMW) brightness temperatures (Tb) over snow-covered land as measured by the Advanced Microwave Sounding Radiometer (<span class="hlt">AMSR-E</span>). The results presented here investigate the transferability of these techniques using <span class="hlt">AMSR-E</span> to predict Tb observations as measured by AMSR2. In other words, can historical <span class="hlt">AMSR-E</span> Tb observations be used to train a ML algorithm in order to predict Tb observations collected by AMSR2 at some point in the future? The NASA Catchment Land Surface Model is first used to characterize snowpack conditions. Next, the ML algorithm is trained on the 9-year record of PMW Tb observations collected by <span class="hlt">AMSR-E</span>. An additional experiment where the ML algorithm was trained on a split-sample of the 2-year record of AMSR2 PMW Tb observations was conducted for comparison. Results suggest one ML technique - the support vector machine - when trained on <span class="hlt">AMSR-E</span> observations can sufficiently reproduce AMSR2 Tb in forested and non-forested regions during both the snow accumulation and snow ablation phases of the snow season. These results suggest transferability of machine learning from the <span class="hlt">AMSR-E</span> sensor to other data records with comparable frequency and polarization characteristics. The eventual goal is to use a ML algorithm as an observation operator within an ensemble-based data assimilation framework where model estimates will be merged with PMW Tb observations in order to improve snow water equivalent (SWE) estimates across regional and continental scales.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016FrES...10..195F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016FrES...10..195F"><span>Detection of radio-frequency interference signals from <span class="hlt">AMSR-E</span> data over the United States with snow cover</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Feng, Chengcheng; Zou, Xiaolei; Zhao, Juan</p> <p>2016-06-01</p> <p>Radio Frequency Interference (RFI) causes severe contamination to passive and active microwave sensing observations and corresponding retrieval products. RFI signals should be detected and filtered before applying the microwave data to retrieval and data assimilation. It is difficult to detect RFI over land surfaces covered by snow because of the scattering effect of snow surface. The double principal component analysis (DPCA) method is adopted in this study, and its ability in identifying RFI signals in <span class="hlt">AMSR-E</span> data over snow covered regions is investigated. Results show that the DPCA method can detect RFI signals effectively in spite of the impact of snow scattering, and the detected RFI signals persistent over time. Compared to other methods, such as PCA and normalized PCA, DPCA is more robust and suitable for operational application.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..15.6082W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..15.6082W"><span>Improving Global Soil Moisture Retrievals from <span class="hlt">AMSR-E</span> through Enhanced Radiative Transfer Modeling and Parameter Calibration</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wood, Eric; Pan, Ming</p> <p>2013-04-01</p> <p>Accurate retrieval of soil moisture from satellites is always a challenge. A soil moisture retrieval product has been produced at Princeton University for last a few years from various passive microwave sensors (e. g. Advanced Microwave Scanning Radiometer - Earth Observing System: <span class="hlt">AMSR-E</span>; TRMM Microwave Imager: TMI) by inverting a single-channel single-polarization (10 GHz Horizontal polarization) forward model (Land Surface Microwave Emission Model: LSMEM). Various characteristics are noticed in this product, such as regions of zero or saturation soil moisture retrievals, indicating an under-performing forward model. Additionally, an analysis of the data set reveals a number of problems related to the vegetation optical depth (VOD) parameter and some soil parameters. To improve the VOD estimation, the previous monthly vegetation parameter (previously static from year to year) is replaced with a dynamic VOD estimation module developed at University of Montana, which derives VOD from multiple microwave channels available on <span class="hlt">AMSR-E</span> or TRMM. To improve the soil parameters, the surface roughness and soil texture parameters are calibrated to match the forward model predicted brightness temperature against the satellite observations, using one year of surface soil moisture from the VIC LSM. The new improved retrieval system that now utilizes multiple microwave channels significantly reduces the forward model bias and produces much more reasonable soil moisture estimates. Areas of active rainfall, snow cover, thick vegetation, and RFI are screened out using the microwave observations from the same platform. The new retrievals are compared to the uncalibrated LSMEM retrievals and are also assessed using soil moisture data from the NRCS SCAN and NCDC soil moisture networks.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=235394','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=235394"><span>The Impact of Standing Water and Irrigation on <span class="hlt">AMSR-E</span> Sensitivity to Soil Moisture over the NAFE'06 Experiment Area</span></a></p> <p><a target="_blank" href="http://www.ars.usda.gov/services/TekTran.htm">Technology Transfer Automated Retrieval System (TEKTRAN)</a></p> <p></p> <p></p> <p><span class="hlt">AMSR-E</span> sensitivity to soil moisture and its accuracy have been studied over a wide variety of surface conditions and weather regimes using both in situ measured data and aircraft derived soil moisture estimates. Several extensive soil moisture field campaigns involving ground and air-borne component...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=306433','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=306433"><span>Remote monitoring of soil moisture using passive microwave-based technologies – theoretical basic and overview of selected algorithms for <span class="hlt">AMSR-E</span></span></a></p> <p><a target="_blank" href="http://www.ars.usda.gov/services/TekTran.htm">Technology Transfer Automated Retrieval System (TEKTRAN)</a></p> <p></p> <p></p> <p>Satellite-based passive microwave remote sensing has been shown to be a valuable tool in mapping and monitoring global soil moisture. The Advanced Microwave Scanning Radiometer on the Aqua platform (<span class="hlt">AMSR-E</span>) has made significant contributions to this application. As the result of agency and individua...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20100010244','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20100010244"><span>Results from Assimilating <span class="hlt">AMSR-E</span> Soil Moisture Estimates into a Land Surface Model Using an Ensemble Kalman Filter in the Land Information System</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Blankenship, Clay B.; Crosson, William L.; Case, Jonathan L.; Hale, Robert</p> <p>2010-01-01</p> <p>Improve simulations of soil moisture/temperature, and consequently boundary layer states and processes, by assimilating <span class="hlt">AMSR-E</span> soil moisture estimates into a coupled land surface-mesoscale model Provide a new land surface model as an option in the Land Information System (LIS)</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_2");'>2</a></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li class="active"><span>4</span></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_4 --> <div id="page_5" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li class="active"><span>5</span></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="81"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014SPIE.9240E..03B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014SPIE.9240E..03B"><span>Sea-<span class="hlt">ice</span> distribution and variability in the East Greenland Sea, 2003-13</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Boccolari, Mauro; Guerrieri, Lorenzo; Parmiggiani, Fiorigi</p> <p>2014-10-01</p> <p>This study presents an analysis of the sea-<span class="hlt">ice</span> area time series for the East Greenland Sea for the period January 2003 - December 2013. The data used are a subset of the Arctic Sea <span class="hlt">Ice</span> <span class="hlt">Concentration</span> data set derived from the observations of the passive microwave sensors <span class="hlt">AMSR-E</span> and AMSR-2 and produced, on a daily basis, by the Inst. of Environ. Physics of the University of Bremen. The area of interest goes, approximately, from 57°N to 84°N and from 53°W to 15°E. On the basis of previous studies, the parameter Sea <span class="hlt">Ice</span> Area as the sum of all pixels whose sea <span class="hlt">ice</span> <span class="hlt">concentration</span> is above 70%, was introduced for measuring sea-<span class="hlt">ice</span> extent. A first survey of the Greenland Sea data set showed a large anomaly in year 2012; this anomaly, clearly linked with the transition period from <span class="hlt">AMSR-E</span> to AMSR-2 when re-sampled SSM/I data were used, was partially corrected with a linear regression procedure. The correlation between monthly mean Sea <span class="hlt">Ice</span> Area and other geophysical parameters, like air temperature, surface wind and cloud cover, was further investigated. High anti-correlation coefficients between air temperature, at sea level and in five different tropospheric layers, and observed <span class="hlt">ice</span> cover is confirmed. Our analysis shows that the strong decline of Arctic sea-<span class="hlt">ice</span> area in the last 10 years is not observed in the East Greenland Sea; this implies that large reductions have occurred in the Canadian and Russian Arctic. This result confirms a hypothesis recently postulated to explain the different sea-<span class="hlt">ice</span> decline in the Arctic and Antarctic regions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016TCry...10.2275T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016TCry...10.2275T"><span>The EUMETSAT sea <span class="hlt">ice</span> <span class="hlt">concentration</span> climate data record</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tonboe, Rasmus T.; Eastwood, Steinar; Lavergne, Thomas; Sørensen, Atle M.; Rathmann, Nicholas; Dybkjær, Gorm; Toudal Pedersen, Leif; Høyer, Jacob L.; Kern, Stefan</p> <p>2016-09-01</p> <p>An Arctic and Antarctic sea <span class="hlt">ice</span> area and extent dataset has been generated by EUMETSAT's Ocean and Sea <span class="hlt">Ice</span> Satellite Application Facility (OSISAF) using the record of microwave radiometer data from NASA's Nimbus 7 Scanning Multichannel Microwave radiometer (SMMR) and the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) and Special Sensor Microwave Imager and Sounder (SSMIS) satellite sensors. The dataset covers the period from October 1978 to April 2015 and updates and further developments are planned for the next phase of the project. The methodology for computing the sea <span class="hlt">ice</span> <span class="hlt">concentration</span> uses (1) numerical weather prediction (NWP) data input to a radiative transfer model for reduction of the impact of weather conditions on the measured brightness temperatures; (2) dynamical algorithm tie points to mitigate trends in residual atmospheric, sea <span class="hlt">ice</span>, and water emission characteristics and inter-sensor differences/biases; and (3) a hybrid sea <span class="hlt">ice</span> <span class="hlt">concentration</span> algorithm using the Bristol algorithm over <span class="hlt">ice</span> and the Bootstrap algorithm in frequency mode over open water. A new sea <span class="hlt">ice</span> <span class="hlt">concentration</span> uncertainty algorithm has been developed to estimate the spatial and temporal variability in sea <span class="hlt">ice</span> <span class="hlt">concentration</span> retrieval accuracy. A comparison to US National <span class="hlt">Ice</span> Center sea <span class="hlt">ice</span> charts from the Arctic and the Antarctic shows that <span class="hlt">ice</span> <span class="hlt">concentrations</span> are higher in the <span class="hlt">ice</span> charts than estimated from the radiometer data at intermediate sea <span class="hlt">ice</span> <span class="hlt">concentrations</span> between open water and 100 % <span class="hlt">ice</span>. The sea <span class="hlt">ice</span> <span class="hlt">concentration</span> climate data record is available for download at <a href=" http://www.osi-saf.org"target="_blank">www.osi-saf.org</a>, including documentation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20080045474','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20080045474"><span>Physical and Radiative Characteristic and Long-term Variability of the Okhotsk Sea <span class="hlt">Ice</span> Cover</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Nishio, Fumihiko; Comiso, Josefino C.; Gersten, Robert; Nakayama, Masashige; Ukita, Jinro; Gasiewski, Al; Stanko, Boba; Naoki, Kazuhiro</p> <p>2008-01-01</p> <p>Much of what we know about the large scale characteristics of the Okhotsk Sea <span class="hlt">ice</span> cover has been provided by <span class="hlt">ice</span> <span class="hlt">concentration</span> maps derived from passive microwave data. To understand what satellite data represent in a highly divergent and rapidly changing environment like the Okhotsk Sea, we take advantage of concurrent satellite, aircraft, and ship data acquired on 7 February and characterized the sea <span class="hlt">ice</span> cover at different scales from meters to hundreds of kilometers. Through comparative analysis of surface features using co-registered data from visible, infrared and microwave channels we evaluated the general radiative and physical characteristics of the <span class="hlt">ice</span> cover as well as quantify the distribution of different <span class="hlt">ice</span> types in the region. <span class="hlt">Ice</span> <span class="hlt">concentration</span> maps from <span class="hlt">AMSR-E</span> using the standard sets of channels, and also only the 89 GHz channel for optimal resolution, are compared with aircraft and high resolution visible data and while the standard set provides consistent results, the 89 GHz provides the means to observe mesoscale patterns and some unique features of the <span class="hlt">ice</span> cover. Analysis of MODIS data reveals that thick <span class="hlt">ice</span> types represents about 37% of the <span class="hlt">ice</span> cover indicating that young and new <span class="hlt">ice</span> types represent a large fraction of the <span class="hlt">ice</span> cover that averages about 90% <span class="hlt">ice</span> <span class="hlt">concentration</span> according to passive microwave data. These results are used to interpret historical data that indicate that the Okhotsk Sea <span class="hlt">ice</span> extent and area are declining at a rapid rate of about -9% and -12 % per decade, respectively.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2005AGUFM.C33B1132S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2005AGUFM.C33B1132S"><span>A New Look at the Northern Hemisphere Sea <span class="hlt">Ice</span> <span class="hlt">Concentration</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Stern, H.; Fetterer, F.; Fowler, C.</p> <p>2005-12-01</p> <p>Arctic sea <span class="hlt">ice</span> extent has decreased over the past 25 years by 7% in winter and 17% in summer, with record or near-record summer lows since 2002. These estimates come from satellite passive microwave (PM) data collected since 1979. In this study we use a new data set of Northern Hemisphere sea <span class="hlt">ice</span> <span class="hlt">concentration</span>, derived from weekly operational <span class="hlt">ice</span> charts (1972-2004) produced by the U.S. National <span class="hlt">Ice</span> Center (NIC), to re-examine regional variability and trends in Arctic sea <span class="hlt">ice</span> area and extent. The <span class="hlt">ice</span> charts through 1994 were quality-checked and converted to EASE-Grid format by the Arctic Climatology Project (2000). Charts for 1995-2004 were converted to EASE-Grid by us. Source data used by NIC to create the charts included visible and infrared satellite imagery, active radar imagery, PM data, aerial reconnaissance, ship and shore observations, buoys, model output, information from foreign <span class="hlt">ice</span> services, and climatology. The PM data were incorporated into the charts only when all other forms of data were not available. We divide the Arctic and sub-Arctic seas into regions and compare chart-derived monthly sea <span class="hlt">ice</span> <span class="hlt">concentration</span> in each region to that derived from PM data. We find that the <span class="hlt">ice</span> charts give a more realistic depiction of the <span class="hlt">ice</span> edge, the marginal <span class="hlt">ice</span> zone, and coastal areas. The PM data have the advantage of being available as a daily product rather than weekly or biweekly. The <span class="hlt">ice</span> charts for 1995-2004 also include <span class="hlt">concentrations</span> of multiyear <span class="hlt">ice</span>, first-year <span class="hlt">ice</span>, and new <span class="hlt">ice</span>. We present results of our analysis of these data, as well as calculations of the duration of the <span class="hlt">ice</span> season in each region, and the variability of the <span class="hlt">ice</span> edge.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006AGUFM.C21A1122S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006AGUFM.C21A1122S"><span>A New Look at the Northern Hemisphere Sea <span class="hlt">Ice</span> <span class="hlt">Concentration</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Stern, H.; Fetterer, F.; Fowler, C.</p> <p>2006-12-01</p> <p>Arctic sea <span class="hlt">ice</span> extent has decreased over the past 25 years by 7% in winter and 17% in summer, with record or near-record summer lows since 2002. These estimates come from satellite passive microwave (PM) data collected since 1979. In this study we use a new data set of Northern Hemisphere sea <span class="hlt">ice</span> <span class="hlt">concentration</span>, derived from weekly operational <span class="hlt">ice</span> charts (1972-2004) produced by the U.S. National <span class="hlt">Ice</span> Center (NIC), to re- examine regional variability and trends in Arctic sea <span class="hlt">ice</span> area and extent. The <span class="hlt">ice</span> charts through 1994 were quality-checked and converted to EASE-Grid format by the Arctic Climatology Project (2000). Charts for 1995-2004 were converted to EASE-Grid by us. Source data used by NIC to create the charts included visible and infrared satellite imagery, active radar imagery, PM data, aerial reconnaissance, ship and shore observations, buoys, model output, information from foreign <span class="hlt">ice</span> services, and climatology. The PM data were incorporated into the charts only when all other forms of data were not available. We divide the Arctic and sub-Arctic seas into regions and compare chart-derived monthly sea <span class="hlt">ice</span> <span class="hlt">concentration</span> in each region to that derived from PM data. We find that the <span class="hlt">ice</span> charts give a more realistic depiction of the <span class="hlt">ice</span> edge, the marginal <span class="hlt">ice</span> zone, and coastal areas. The PM data have the advantage of being available as a daily product rather than weekly or biweekly. The <span class="hlt">ice</span> charts for 1995-2004 also include <span class="hlt">concentrations</span> of multiyear <span class="hlt">ice</span>, first-year <span class="hlt">ice</span>, and new <span class="hlt">ice</span>. We present results of our analysis of these data, as well as calculations of the duration of the <span class="hlt">ice</span> season in each region, and the variability of the <span class="hlt">ice</span> edge.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..1710250R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..1710250R"><span>Long time series of soil moisture obtained using neural networks: application to <span class="hlt">AMSR-E</span> and SMOS</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Rodriguez-Fernandez, Nemesio J.; Kerr, Yann H.; de Jeu, Rcihard A. M.; van der Schalie, Robin; Wigneron, Jean Pierre; Ayaari, Amen al; Dolman, Han; Drusch, Matthias; Mecklenburg, Sussane</p> <p>2015-04-01</p> <p>The Soil Moisture and Ocean Salinity (SMOS) satellite is the first mission specifically designed to measure soil moisture (hereafter SM) from space. The instrument on-board SMOS is a L-band aperture synthesis radiometer, with full-polarization and multi-angular capabilities (Mecklenburg et al. 2012). The operational SM retrieval algorithm is based on a physical model (Kerr et al. 2012). In addition, Rodriguez-Fernandez et al. (2014) have recently implemented an inverse model based in neural networks using the approach of Aires & Prigent (2006), which consists in training the neural networks with numerical weather prediction models (ECMWF, Balsamo et al. 2009). In the context of an ESA funded project (de Jeu et al, this conference, session CL 5.7), we have studied this neural network approach to create a consistent soil moisture dataset from 2003 to 2014 using NASA/JAXA Advanced Scanning Microwave Radiometer (<span class="hlt">AMSR-E</span>) and ESA SMOS radiometers as input data. Two neural networks algorithms have been defined and optimized using <span class="hlt">AMSR-E</span> or SMOS as input data in the periods 2003-Oct 2011 and 2010-2014, respectively. The two missions overlapping period has been used to demonstrate the consistency of the SM dataset produced with both algorithms by comparing monthly averages of SM and by comparing with time series of in situ measurements at selected locations and other SM products such as the SMOS operational SM, ECMWF model SM, and <span class="hlt">AMSR-E</span> LPRM SM (Owe et al. 2008). Finally, the long time series of SM obtained with neural networks will be compared to in-situ measurements and ECMWF ERA-Interim SM at selected locations. This long-term soil moisture dataset can be used for hydrological and climate applications and it is the first step towards a longer dataset which will include additional sensors. References Aires, F. & Prigent, C. Toward a new generation of satellite surface products? Journal of Geophysical Research: Atmospheres (1984--2012), Wiley Online Library, 2006, 11</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..15.2137C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..15.2137C"><span>Evaluation of <span class="hlt">AMSR-E</span> Soil Moisture products and model simulations against observations from a Tibetan SMTMS network</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Chen, Yingying; Yang, Kun; Qin, Jun; Zhao, Long</p> <p>2013-04-01</p> <p>Soil moisture is a key parameter in the land-atmosphere interactions over the Tibetan Plateau (TP), which plays an essential role in the Asian monsoon processes. Validation of satellite observed and/or modeled surface soil moisture is a particularly challenging work due to the scale issues. Additional challenge in this area is the harsh environment and heavy workload to establish a Soil Moisture and Temperature Measurement System (SMTMS) network. In this presentation, a multi-scale soil moisture and temperature monitoring network, consisting of 55 SMTMS stations, has been established in central TP within a 1°×1° area. Firstly, the station-averaged surface soil moisture data from the network are employed to evaluate four retrieved products from the Advanced Microwave Scanning Radiometer-Earth Observing System (<span class="hlt">AMSR-E</span>), including the National Aeronautics and Space Administration (NASA) standard soil moisture product, the Japan Aerospace Exploration Agency (JAXA) standard soil moisture product, and both the C-band and X-band soil moisture products developed using the land parameter retrieval model (LPRM). The statistic metrics indicate that none of four <span class="hlt">AMSR-E</span> products provides reliable estimates in the unfrozen season, in terms of the mission requirement of the root mean square error (RMSE) < 0.06 m3m-3. These algorithms either much overestimate soil moisture or much underestimate it, although some of them can reflect the soil moisture dynamic range, indicating that the retrieval algorithms have much space to be improved for the cold semi-arid regions. Then, the station-averaged soil moisture observations are used to evaluate four modeled outputs by the Global Land Data Assimilation System (GLDAS). These land surface models (LSMs) are Community Land Model (CLM), Noah model, VIC model and MOSAIC model. The statistic results indicate that four GLDAS models tend to systematically underestimate the surface soil moisture (0-5 cm) while well simulate the soil moisture</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20070038189','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20070038189"><span>Physical and Radiative Characteristics and Long Term Variability of the Okhotsk Sea <span class="hlt">Ice</span> Cover</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Nishio, Fumihiko; Comiso, Josefino C.; Gersten, Robert; Nakayama, Masashige; Ukita, Jinro; Gasiewski, Al; Stanko, Boba; Naoki, Kazuhiro</p> <p>2007-01-01</p> <p>Much of what we know about the large scale characteristics of the Okhotsk Sea <span class="hlt">ice</span> cover comes from <span class="hlt">ice</span> <span class="hlt">concentration</span> maps derived from passive microwave data. To understand what these satellite data represents in a highly divergent and rapidly changing environment like the Okhotsk Sea, we analyzed concurrent satellite, aircraft, and ship data and characterized the sea <span class="hlt">ice</span> cover at different scales from meters to tens of kilometers. Through comparative analysis of surface features using co-registered data from visible, infrared and microwave channels we evaluated how the general radiative and physical characteristics of the <span class="hlt">ice</span> cover changes as well as quantify the distribution of different <span class="hlt">ice</span> types in the region. <span class="hlt">Ice</span> <span class="hlt">concentration</span> maps from <span class="hlt">AMSR-E</span> using the standard sets of channels, and also only the 89 GHz channel for optimal resolution, are compared with aircraft and high resolution visible data and while the standard set provides consistent results, the 89 GHz provides the means to observe mesoscale patterns and some unique features of the <span class="hlt">ice</span> cover. Analysis of MODIS data reveals that thick <span class="hlt">ice</span> types represents about 37% of the <span class="hlt">ice</span> cover indicating that young and new <span class="hlt">ice</span> represent a large fraction of the lice cover that averages about 90% <span class="hlt">ice</span> <span class="hlt">concentration</span>, according to passive microwave data. A rapid decline of -9% and -12 % per decade is observed suggesting warming signals but further studies are required because of aforementioned characteristics and because the length of the <span class="hlt">ice</span> season is decreasing by only 2 to 4 days per decade.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.C31A0591D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.C31A0591D"><span>Comparison of the <span class="hlt">AMSR-E</span> and SSM/I SWE Estimates in the Major Afghanistan Watersheds</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Daly, S. F.; Vuyovich, C.; Deeb, E. J.; Baldwin, T. B.; Newman, S. D.</p> <p>2011-12-01</p> <p>The <span class="hlt">AMSR-E</span> and SSM/I SWE estimates for the major Afghanistan watersheds are compared on a watershed total and pixel-by-pixel basis. Satellite remote sensing provides the only estimates of snow conditions in Afghanistan as virtually no ground observations are available. Although the Afghanistan terrain is mountainous, satellite remote sensing is particularly applicable to this area because most watersheds have little or no forest cover. We show that systematic and long term differences exist between the total SWE volumes determined by each satellite system for many but not all the watersheds. We show the influence of pixel elevation, slope, aspect and other factors on the SWE differences. The possible impacts of differences between the algorithms and native resolutions of each satellite system are discussed. The trends in SWE difference distribution with elevation throughout the winter season are described. We explore the ability to estimate the total watershed SWE difference based on the distribution of pixel elevation, slope, aspect and other factors within the watershed and its use as a means of developing confidence intervals of the consistency of SWE estimates when compared with historical observations.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2004AGUFM.C41B0202S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2004AGUFM.C41B0202S"><span>A New Look at the Northern Hemisphere Sea <span class="hlt">Ice</span> <span class="hlt">Concentration</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Stern, H.; Fowler, C.; Fetterer, F.</p> <p>2004-12-01</p> <p>It is widely recognized that the Arctic sea <span class="hlt">ice</span> cover has been shrinking over the past 25 years. Our knowledge of hemispheric sea <span class="hlt">ice</span> <span class="hlt">concentration</span> and extent comes almost entirely from satellite passive microwave (PM) data collected since 1978. In this study, we use a new data set of Northern Hemisphere sea <span class="hlt">ice</span> <span class="hlt">concentration</span>, derived from weekly operational <span class="hlt">ice</span> charts spanning more than three decades (1972-2003), to re-examine the regional variability and trends in sea <span class="hlt">ice</span> area and extent. The <span class="hlt">ice</span> charts from the U.S. National <span class="hlt">Ice</span> Center have been converted to EASE-Grid format. Source data for the charts include visible and infrared satellite imagery, active radar imagery, PM data, aerial reconnaissance, ship and shore observations, buoys, model output, information from foreign <span class="hlt">ice</span> services, and climatology. The PM data are used only when all other forms of data are not available. Thus we have a unique gridded data set that is largely independent of the popular PM products that are widely used by the sea <span class="hlt">ice</span> community. We divided the Arctic and sub-Arctic seas into regions and created monthly time series of sea <span class="hlt">ice</span> area and extent for each region. We also obtained the monthly NASA Team sea <span class="hlt">ice</span> <span class="hlt">concentration</span> products. We re-gridded these to the same EASE-Grid format as the charts, and computed time series of sea <span class="hlt">ice</span> area and extent for the same regions. We present comparisons of the regional differences and trends seen in the two data sets. We explain the differences based on the source data used in the charts, and the emissivity of sea <span class="hlt">ice</span> as detected by the PM instruments. Future work with the <span class="hlt">ice</span> chart data set includes analysis of multiyear, first-year, and new <span class="hlt">ice</span> <span class="hlt">concentrations</span> in order to understand the recent record-low summer <span class="hlt">ice</span> minima; duration of the <span class="hlt">ice</span> season, as an indicator of climate change; and analysis of the modes of variability of the <span class="hlt">ice</span> edge, in order to develop a predictive capability for sea <span class="hlt">ice</span> extent.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://pubs.er.usgs.gov/publication/70012715','USGSPUBS'); return false;" href="http://pubs.er.usgs.gov/publication/70012715"><span>Time-dependence of sea-<span class="hlt">ice</span> <span class="hlt">concentration</span> and multiyear <span class="hlt">ice</span> fraction in the Arctic Basin</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Gloersen, P.; Zwally, H.J.; Chang, A.T.C.; Hall, D.K.; Campbell, W.J.; Ramseier, R.O.</p> <p>1978-01-01</p> <p>The time variation of the sea-<span class="hlt">ice</span> <span class="hlt">concentration</span> and multiyear <span class="hlt">ice</span> fraction within the pack <span class="hlt">ice</span> in the Arctic Basin is examined, using microwave images of sea <span class="hlt">ice</span> recently acquired by the Nimbus-5 spacecraft and the NASA CV-990 airborne laboratory. The images used for these studies were constructed from data acquired from the Electrically Scanned Microwave Radiometer (ESMR) which records radiation from earth and its atmosphere at a wavelength of 1.55 cm. Data are analyzed for four seasons during 1973-1975 to illustrate some basic differences in the properties of the sea <span class="hlt">ice</span> during those times. Spacecraft data are compared with corresponding NASA CV-990 airborne laboratory data obtained over wide areas in the Arctic Basin during the Main Arctic <span class="hlt">Ice</span> Dynamics Joint Experiment (1975) to illustrate the applicability of passive-microwave remote sensing for monitoring the time dependence of sea-<span class="hlt">ice</span> <span class="hlt">concentration</span> (divergence). These observations indicate significant variations in the sea-<span class="hlt">ice</span> <span class="hlt">concentration</span> in the spring, late fall and early winter. In addition, deep in the interior of the Arctic polar sea-<span class="hlt">ice</span> pack, heretofore unobserved large areas, several hundred kilometers in extent, of sea-<span class="hlt">ice</span> <span class="hlt">concentrations</span> as low as 50% are indicated. ?? 1978 D. Reidel Publishing Company.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010SPIE.7841E..03D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010SPIE.7841E..03D"><span>Cross-platform calibration of SMMR, SSM/I and <span class="hlt">AMSR-E</span> passive microwave brightness temperature</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dai, Liyun; Che, Tao</p> <p>2010-11-01</p> <p>The long time series of passive microwave satellite data (SMMR, SSM/I and <span class="hlt">AMSR-E</span>) have provided important information about the earth surface science and climate research in the past three decades. Due to the update of satellite-based radiometers and their platforms, some systematic parameters are different, and there are biases among brightness temperature in different periods, which lead to inaccuracy of some parameters' retrieval. In order to obtain consistent brightness temperature datasets, and provide convenience for the researchers using these data, it is necessary to calibrate the brightness temperature from different sensors. Considering the difference between the variance of brightness temperature from different sensors on cold and warm region at the cross time, this paper analyzed the brightness temperature on the cold and warm region respectively. On the cold region, because the diurnal temperature variation is very small, the influence on brightness temperature caused by difference of the satellites overpass time during the overlap period can be ignored. The brightness temperature data at 18GHz and 37GHz channels of Nimbus-7 and 19GHz, 37GHz channels of DMSP on the Antarctic or the Greenland glacier during the overlap period were analyzed. On the warm region, due to the reason that the daily variance of temperature contributes a lot to the difference of brightness temperature from different sensors during the overlap period, the diurnal cycle of surface temperature on the Sahara desert region was analyzed, and base on it, the influence of temperature to brightness temperature was eliminated. Finally, considering the two regions, the cross coefficients of calibration were estimated.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19860019345','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19860019345"><span>Entrainment, transport and <span class="hlt">concentration</span> of meteorites in polar <span class="hlt">ice</span> sheets</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Drewry, D. J.</p> <p>1986-01-01</p> <p>Glaciers and <span class="hlt">ice</span> sheets act as slow-moving conveyancing systems for material added to both their upper and lower surfaces. Because the transit time for most materials is extremely long the <span class="hlt">ice</span> acts as a major global storage facility. The effects of horizontal and vertical motions on the flow patterns of Antarctic <span class="hlt">ice</span> sheets are summarized. The determination of the source areas of meteorites and their transport paths is a problem of central importance since it relates not only directly to <span class="hlt">concentration</span> mechanisms but also to the wider issues in glaciology and meteorites. The <span class="hlt">ice</span> and snow into which a meteorite falls, and which moves with it to the <span class="hlt">concentration</span> area, encodes information about the infall area. The principle environmental conditions being former elevation, temperature (also related to elevation), and age of the <span class="hlt">ice</span>. This encoded information could be used to identify the infall area.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20030110723&hterms=stranding&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dstranding','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20030110723&hterms=stranding&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dstranding"><span>The Broken Belt: Meteorite <span class="hlt">Concentrations</span> on Stranded <span class="hlt">Ice</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Harvey, R. P.</p> <p>2003-01-01</p> <p>Since the first Antarctic meteorite <span class="hlt">concentrations</span> were discovered more than 25 years ago, many theories regarding the role of iceflow in the production of meteorite <span class="hlt">concentrations</span> have been put forward, and most agree on the basic principles. These models suggest that as the East Antarctic icesheet flows toward the margins of the continent, meteorites randomly located within the volume of <span class="hlt">ice</span> are transported toward the icesheet margin. Where mountains or subsurface obstructions block glacial flow, diversion of <span class="hlt">ice</span> around or over an obstruction reduces horizontal <span class="hlt">ice</span> movement rates adjacent to the barriers and creates a vertical (upward) component of movement. If local mechanisms for <span class="hlt">ice</span> loss (ablation) exist at such sites, an equilibrium surface will develop according to the balance between <span class="hlt">ice</span> supply and loss, and the cargo of meteorites is exhumed on a blue <span class="hlt">ice</span> surface. The result is a conceptual conveyor belt bringing meteorite-bearing volumes of <span class="hlt">ice</span> from the interior of the continent to stagnant or slowmoving surfaces where <span class="hlt">ice</span> is then lost and a precious cargo is left as a lag deposit. Cassidy et al. provides an excellent overview of how this model has been adapted to several Antarctic stranding surfaces.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1811757R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1811757R"><span>Melt ponds and marginal <span class="hlt">ice</span> zone from new algorithm of sea <span class="hlt">ice</span> <span class="hlt">concentration</span> retrieval</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Repina, Irina; Tikhonov, Vasiliy; Komarova, Nataliia; Raev, Mikhail; Sharkov, Evgeniy</p> <p>2016-04-01</p> <p>Studies of spatial and temporal properties of sea <span class="hlt">ice</span> distribution in polar regions help to monitor global environmental changes and reveal their natural and anthropogenic factors, as well as make forecasts of weather, marine transportation and fishing conditions, assess perspectives of mineral mining on the continental shelf, etc. Contact methods of observation are often insufficient to meet the goals, very complicated technically and organizationally and not always safe for people involved. Remote sensing techniques are believed to be the best alternative. Its include monitoring of polar regions by means of passive microwave sensing with the aim to determine spatial distribution, types, thickness and snow cover of <span class="hlt">ice</span>. However, the algorithms employed today to retrieve sea <span class="hlt">ice</span> characteristics from passive microwave sensing data for different reasons give significant errors, especially in summer period and also near <span class="hlt">ice</span> edges and in cases of open <span class="hlt">ice</span>. A new algorithm of sea <span class="hlt">ice</span> <span class="hlt">concentration</span> retrieval in polar regions from satellite microwave radiometry data is discussed. Beside estimating sea <span class="hlt">ice</span> <span class="hlt">concentration</span>, the algorithm makes it possible to indicate <span class="hlt">ice</span> areas with melting snow and melt ponds. Melt ponds are an important element of the Arctic climate system. Covering up to 50% of the surface of drifting <span class="hlt">ice</span> in summer, they are characterized by low albedo values and absorb several times more incident shortwave radiation than the rest of the snow and <span class="hlt">ice</span> cover. The change of melt ponds area in summer period 1987-2015 is investigated. The marginal <span class="hlt">ice</span> zone (MIZ) is defined as the area where open ocean processes, including specifically ocean waves, alter significantly the dynamical properties of the sea <span class="hlt">ice</span> cover. Ocean wave fields comprise short waves generated locally and swell propagating from the large ocean basins. Depending on factors like wind direction and ocean currents, it may consist of anything from isolated, small and large <span class="hlt">ice</span> floes drifting over a</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.H31F1253T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.H31F1253T"><span>Using Large-Scale Precipitation to Validate <span class="hlt">AMSR-E</span> Satellite Soil Moisture Estimates by Means of Mutual Information</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tuttle, S. E.; Salvucci, G.</p> <p>2013-12-01</p> <p>Validation of remotely sensed soil moisture is complicated by the difference in scale between remote sensing footprints and traditional ground-based soil moisture measurements. To address this issue, a new method was developed to evaluate the useful information content of remotely sensed soil moisture data using only large-scale precipitation (i.e. without modeling). Under statistically stationary conditions [Salvucci, 2001], precipitation conditionally averaged according to soil moisture (denoted E[P|S]) results in a sigmoidal shape in a manner that reflects the dependence of drainage, runoff, and evapotranspiration on soil moisture. However, errors in satellite measurement and algorithmic conversion of satellite data to soil moisture can degrade this relationship. Thus, remotely sensed soil moisture products can be assessed by the degree to which the natural sigmoidal relationship is preserved. The metric of mutual information was used as an error-dependent measure of the strength of the sigmoidal relationship, calculated from a two-dimensional histogram of soil moisture versus precipitation estimated using Gaussian mixture models. Three <span class="hlt">AMSR-E</span> algorithms (VUA-NASA [Owe et al., 2001], NASA [Njoku et al., 2003], and U. Montana [Jones & Kimball, 2010]) were evaluated with the method for a nine-year period (2002-2011) over the contiguous United States at ¼° latitude-longitude resolution, using precipitation from the North American Land Data Assimilation System (NLDAS). The U. Montana product resulted in the highest mutual information for 57% of the region, followed by VUA-NASA and NASA at 40% and 3%, respectively. Areas where the U. Montana product yielded the maximum mutual information generally coincided with low vegetation biomass and flatter terrain, while the VUA-NASA product contained more useful information in more rugged and highly vegetated areas. Additionally, E[P|S] curves resulting from the Gaussian mixture method can potentially be decomposed into</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..16.5568R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..16.5568R"><span><span class="hlt">Concentrated</span> englacial shear over rigid basal <span class="hlt">ice</span>, West Antarctica: implications for modelling and <span class="hlt">ice</span> sheet flow</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ross, Neil; Siegert, Martin</p> <p>2014-05-01</p> <p> sheet flow. Our observations suggest that, in parts of the onset zone of the Institute <span class="hlt">Ice</span> Stream, the flow of the <span class="hlt">ice</span> sheet effectively ignores the basal topography. Instead, enhanced <span class="hlt">ice</span> flow responds to a pseudo-bed, with internal deformation <span class="hlt">concentrated</span> and terminating at an englacial rheological interface between the upper <span class="hlt">ice</span> sheet column and the massive basal <span class="hlt">ice</span>. Although we cannot entirely rule out basal accretion as the cause of the strong englacial interface and thick basal layer, discrete englacial shearing acting to realign <span class="hlt">ice</span> crystals, may be the best explanation for the basal unit in this case. Our results demonstrate that we will, at the very least, need to adapt numerical models of those parts of the <span class="hlt">ice</span> sheet with extensive and thick basal <span class="hlt">ice</span> units, and that we may even need to carefully reconsider existing schematic models of <span class="hlt">ice</span> flow, to incorporate processes associated with <span class="hlt">concentrated</span> englacial shear.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015TCry....9.1735P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015TCry....9.1735P"><span>Improving Arctic sea <span class="hlt">ice</span> edge forecasts by assimilating high horizontal resolution sea <span class="hlt">ice</span> <span class="hlt">concentration</span> data into the US Navy's <span class="hlt">ice</span> forecast systems</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Posey, P. G.; Metzger, E. J.; Wallcraft, A. J.; Hebert, D. A.; Allard, R. A.; Smedstad, O. M.; Phelps, M. W.; Fetterer, F.; Stewart, J. S.; Meier, W. N.; Helfrich, S. R.</p> <p>2015-08-01</p> <p>This study presents the improvement in <span class="hlt">ice</span> edge error within the US Navy's operational sea <span class="hlt">ice</span> forecast systems gained by assimilating high horizontal resolution satellite-derived <span class="hlt">ice</span> <span class="hlt">concentration</span> products. Since the late 1980's, the <span class="hlt">ice</span> forecast systems have assimilated near real-time sea <span class="hlt">ice</span> <span class="hlt">concentration</span> derived from the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSMI and then SSMIS). The resolution of the satellite-derived product was approximately the same as the previous operational <span class="hlt">ice</span> forecast system (25 km). As the sea <span class="hlt">ice</span> forecast model resolution increased over time, the need for higher horizontal resolution observational data grew. In 2013, a new Navy sea <span class="hlt">ice</span> forecast system (Arctic Cap Nowcast/Forecast System - ACNFS) went into operations with a horizontal resolution of ~ 3.5 km at the North Pole. A method of blending <span class="hlt">ice</span> <span class="hlt">concentration</span> observations from the Advanced Microwave Scanning Radiometer (AMSR2) along with a sea <span class="hlt">ice</span> mask produced by the National <span class="hlt">Ice</span> Center (NIC) has been developed, resulting in an <span class="hlt">ice</span> <span class="hlt">concentration</span> product with very high spatial resolution. In this study, ACNFS was initialized with this newly developed high resolution blended <span class="hlt">ice</span> <span class="hlt">concentration</span> product. The daily <span class="hlt">ice</span> edge locations from model hindcast simulations were compared against independent observed <span class="hlt">ice</span> edge locations. ACNFS initialized using the high resolution blended <span class="hlt">ice</span> <span class="hlt">concentration</span> data product decreased predicted <span class="hlt">ice</span> edge location error compared to the operational system that only assimilated SSMIS data. A second evaluation assimilating the new blended sea <span class="hlt">ice</span> <span class="hlt">concentration</span> product into the pre-operational Navy Global Ocean Forecast System 3.1 also showed a substantial improvement in <span class="hlt">ice</span> edge location over a system using the SSMIS sea <span class="hlt">ice</span> <span class="hlt">concentration</span> product alone. This paper describes the technique used to create the blended sea <span class="hlt">ice</span> <span class="hlt">concentration</span> product and the significant improvements in <span class="hlt">ice</span> edge forecasting in both of the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=1509046','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=1509046"><span>Determinants of nitrogen dioxide <span class="hlt">concentrations</span> in indoor <span class="hlt">ice</span> skating rinks.</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Levy, J I; Lee, K; Yanagisawa, Y; Hutchinson, P; Spengler, J D</p> <p>1998-01-01</p> <p>OBJECTIVES: The combination of poor ventilation and fuel-powered <span class="hlt">ice</span> resurfacers has resulted in elevated nitrogen dioxide (NO2) <span class="hlt">concentrations</span> in many indoor <span class="hlt">ice</span> skating rinks. This study examined the factors influencing <span class="hlt">concentrations</span> and the effects of various engineering controls in <span class="hlt">ice</span> rinks with different resurfacer fuels. METHODS: Indoor NO2 <span class="hlt">concentrations</span> were measured in 19 enclosed <span class="hlt">ice</span> skating rinks over 3 winters by means of passive samplers, with 1-week average measurements during the first winter pilot study and single-day working-hour measurements in the final 2 winters. Personal exposures to drivers also were assessed during the last winter. RESULTS: Rinks in which propane-fueled resurfacers were used had a daily mean indoor NO2 <span class="hlt">concentration</span> of 206 ppb, compared with 132 ppb for gasoline-fueled and 37 ppb for electric-powered resurfacers. Engineering controls, such as increased ventilation and resurfacer tuning, reduced NO2 <span class="hlt">concentrations</span> by 65% on average, but outcomes varied widely, and <span class="hlt">concentrations</span> increased in subsequent months. CONCLUSIONS: Electric <span class="hlt">ice</span> resurfacers, increased ventilation, or emission control systems are recommended to protect the health of workers and patrons, with surveillance programs proposed to track implementation and maintain an observer effect. PMID:9842374</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015OcDyn..65.1353P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015OcDyn..65.1353P"><span>The implementation of sea <span class="hlt">ice</span> model on a regional high-resolution scale</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Prasad, Siva; Zakharov, Igor; Bobby, Pradeep; McGuire, Peter</p> <p>2015-09-01</p> <p>The availability of high-resolution atmospheric/ocean forecast models, satellite data and access to high-performance computing clusters have provided capability to build high-resolution models for regional <span class="hlt">ice</span> condition simulation. The paper describes the implementation of the Los Alamos sea <span class="hlt">ice</span> model (CICE) on a regional scale at high resolution. The advantage of the model is its ability to include oceanographic parameters (e.g., currents) to provide accurate results. The sea <span class="hlt">ice</span> simulation was performed over Baffin Bay and the Labrador Sea to retrieve important parameters such as <span class="hlt">ice</span> <span class="hlt">concentration</span>, thickness, ridging, and drift. Two different forcing models, one with low resolution and another with a high resolution, were used for the estimation of sensitivity of model results. Sea <span class="hlt">ice</span> behavior over 7 years was simulated to analyze <span class="hlt">ice</span> formation, melting, and conditions in the region. Validation was based on comparing model results with remote sensing data. The simulated <span class="hlt">ice</span> <span class="hlt">concentration</span> correlated well with Advanced Microwave Scanning Radiometer for EOS (<span class="hlt">AMSR-E</span>) and Ocean and Sea <span class="hlt">Ice</span> Satellite Application Facility (OSI-SAF) data. Visual comparison of <span class="hlt">ice</span> thickness trends estimated from the Soil Moisture and Ocean Salinity satellite (SMOS) agreed with the simulation for year 2010-2011.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li class="active"><span>5</span></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_5 --> <div id="page_6" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li class="active"><span>6</span></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="101"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.A33C0228P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.A33C0228P"><span>Contribution of pollen to atmospheric <span class="hlt">ice</span> nuclei <span class="hlt">concentrations</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Petters, M. D.; Hader, J.; Wright, T.; McMeeking, G. R.</p> <p>2013-12-01</p> <p>Primary biological aerosol particles (PBAP) contribute to the <span class="hlt">concentrations</span> of <span class="hlt">ice</span> nuclei (IN) in the atmosphere. Laboratory studies have shown that pollen grains, a subset of PBAP, can serve as immersion mode <span class="hlt">ice</span> nuclei at temperatures ranging from -9 to -25 deg C. At the peak of the pollen season pollen <span class="hlt">concentrations</span> can reach surface-level <span class="hlt">concentrations</span> exceeding 1 per liter of air. Furthermore, previous studies have suggested that the <span class="hlt">ice</span> nucleating ability of some types of pollen is derived from non-proteinaceous macromolecules, which may become dispersed by the rupturing of the pollen sac during wetting and drying cycles. If true, this mechanism is expected to produce highly elevated IN <span class="hlt">concentrations</span> at temperatures warmer than -25 deg C. Here we test this hypothesis by measuring ambient IN <span class="hlt">concentrations</span> from the beginning to the end of the 2013 pollen season in Raleigh, North Carolina. Raleigh is surrounded by a dense mixed hardwood forest composed primarily of oak, hickory, and pine species. Air samples were collected using a swirling aerosol collector twice per week and the solution was analyzed for <span class="hlt">ice</span> nuclei activity using a droplet freezing assay setup. Rainwater samples were collected during rain events at the peak of the pollen season and analyzed with the drop freezing assay to compare the potentially enhanced IN <span class="hlt">concentrations</span> measured near the ground with IN <span class="hlt">concentrations</span> found aloft. Raw freezing spectra were used to probe the freezing activity of both abundant and rare IN contained in sample liquids by analysis of drops that had varying degrees of preconcentration and size (~50 to ~650 μm). Extreme value statistics is used to collapse the raw freezing data into a single <span class="hlt">ice</span> nuclei spectrum, defined as number of <span class="hlt">ice</span> nuclei per volume of air as a function of temperature, that spans ~6 orders of magnitude in IN <span class="hlt">concentration</span>. For a selected number of samples, <span class="hlt">concentrations</span> of biological and non-biological ambient aerosol and particles are</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20040081247&hterms=etl&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Detl','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20040081247&hterms=etl&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Detl"><span>Comparisons of Arctic In-Situ Snow and <span class="hlt">Ice</span> Data with Airborne Passive Microwave Measurements</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Markus, T.; Cavalien, D. J.; Gasiewski, A.; Sturm, M.; Klein, M.; Maslanik, J.; Stroeve, J.; Heinrichs, J.; Holmgren, J.; Irisov, V.</p> <p>2004-01-01</p> <p>As part of the <span class="hlt">AMSR-E</span> sea <span class="hlt">ice</span> validation campaign in March 2003, aircraft flights over the Arctic sea <span class="hlt">ice</span> were coordinated with ground measurements of snow and sea <span class="hlt">ice</span> properties. The surface-based measurements were in the vicinity of Barrow, AK, and at a Navy <span class="hlt">ice</span> camp located in the Beaufort Sea. The NASA P-3 aircraft was equipped with the NOAA ETL PSR microwave radiometer that has the same frequencies as the <span class="hlt">AMSR-E</span> sensor. The goal was to validate the standard <span class="hlt">AMSR-E</span> products <span class="hlt">ice</span> temperature and snow depth on sea <span class="hlt">ice</span>. Ground measurements are the only way to validate these parameters. The higher spatial resolution of the PSR instrument (between 30 and 500 m, depending on altitude) enables a better comparison between ground measurements and microwave data because of the expected smaller spatial variability. Maps of PSR data can then be used for further down-scaling to <span class="hlt">AMSR-E</span> pixel areas. Initial results show a good qualitative agreement between the in-situ snow depths and the PSR data. Detailed studies are underway and latest results will be presented.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AtmEn.140..381P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AtmEn.140..381P"><span>Recent increase in Antarctic Peninsula <span class="hlt">ice</span> core uranium <span class="hlt">concentrations</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Potocki, Mariusz; Mayewski, Paul A.; Kurbatov, Andrei V.; Simões, Jefferson C.; Dixon, Daniel A.; Goodwin, Ian; Carleton, Andrew M.; Handley, Michael J.; Jaña, Ricardo; Korotkikh, Elena V.</p> <p>2016-09-01</p> <p>Understanding the distribution of airborne uranium is important because it can result in both chemical and radiological toxicity. <span class="hlt">Ice</span> cores offer the most robust reconstruction of past atmospheric levels of toxic substances. Here we present the first sub-annually dated, continuously sampled <span class="hlt">ice</span> core documenting change in U levels in the Southern Hemisphere. The <span class="hlt">ice</span> core was recovered from the Detroit Plateau, northern Antarctic Peninsula, in 2007 by a joint Brazilian-Chilean-US team. It displays a significant increase in U <span class="hlt">concentration</span> that coincides with reported mining activities in the Southern Hemisphere, notably Australia. Raw U <span class="hlt">concentrations</span> in the Detroit Plateau <span class="hlt">ice</span> core increased by as much as 102 between the 1980s and 2000s accompanied by increased variability in recent years. Decadal mean U <span class="hlt">concentrations</span> increased by a factor of ∼3 from 1980 to 2007, reaching a mean of 205 pg/L from 2000 to 2007. The fact that other terrestrial source dust elements such as Ce, La, Pr, and Ti do not show a similar increase and that the increased U <span class="hlt">concentrations</span> are enriched above natural crustal levels, supports an anthropogenic source for the U as opposed to a change in atmospheric circulation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2966089','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2966089"><span>Type I Antifreeze Proteins Enhance <span class="hlt">Ice</span> Nucleation above Certain <span class="hlt">Concentrations</span></span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Wilson, Peter W.; Osterday, Katie E.; Heneghan, Aaron F.; Haymet, Anthony D. J.</p> <p>2010-01-01</p> <p>In this study, we examined the effects that antifreeze proteins have on the supercooling and <span class="hlt">ice</span>-nucleating abilities of aqueous solutions. Very little information on such nucleation currently exists. Using an automated lag time apparatus and a new analysis, we show several dilution series of Type I antifreeze proteins. Our results indicate that, above a <span class="hlt">concentration</span> of ∼8 mg/ml, <span class="hlt">ice</span> nucleation is enhanced rather than hindered. We discuss this unexpected result and present a new hypothesis outlining three components of polar fish blood that we believe affect its solution properties in certain situations. PMID:20837472</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JGRC..121.8511L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JGRC..121.8511L"><span>Sea <span class="hlt">ice</span> algae chlorophyll a <span class="hlt">concentrations</span> derived from under-<span class="hlt">ice</span> spectral radiation profiling platforms</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lange, Benjamin A.; Katlein, Christian; Nicolaus, Marcel; Peeken, Ilka; Flores, Hauke</p> <p>2016-12-01</p> <p>Multiscale sea <span class="hlt">ice</span> algae observations are fundamentally important for projecting changes to sea <span class="hlt">ice</span> ecosystems, as the physical environment continues to change. In this study, we developed upon previously established methodologies for deriving sea <span class="hlt">ice</span>-algal chlorophyll a <span class="hlt">concentrations</span> (chl a) from spectral radiation measurements, and applied these to larger-scale spectral surveys. We conducted four different under-<span class="hlt">ice</span> spectral measurements: irradiance, radiance, transmittance, and transflectance, and applied three statistical approaches: Empirical Orthogonal Functions (EOF), Normalized Difference Indices (NDI), and multi-NDI. We developed models based on <span class="hlt">ice</span> core chl a and coincident spectral irradiance/transmittance (N = 49) and radiance/transflectance (N = 50) measurements conducted during two cruises to the central Arctic Ocean in 2011 and 2012. These reference models were ranked based on two criteria: mean robustness R2 and true prediction error estimates. For estimating the biomass of a large-scale data set, the EOF approach performed better than the NDI, due to its ability to account for the high variability of environmental properties experienced over large areas. Based on robustness and true prediction error, the three most reliable models, EOF-transmittance, EOF-transflectance, and NDI-transmittance, were applied to two remotely operated vehicle (ROV) and two Surface and Under-<span class="hlt">Ice</span> Trawl (SUIT) spectral radiation surveys. In these larger-scale chl a estimates, EOF-transmittance showed the best fit to <span class="hlt">ice</span> core chl a. Application of our most reliable model, EOF-transmittance, to an 85 m horizontal ROV transect revealed large differences compared to published biomass estimates from the same site with important implications for projections of Arctic-wide <span class="hlt">ice</span>-algal biomass and primary production.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19920040056&hterms=PASSIVE+FILTER&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3DPASSIVE%2BFILTER','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19920040056&hterms=PASSIVE+FILTER&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3DPASSIVE%2BFILTER"><span>Effects of weather on the retrieval of sea <span class="hlt">ice</span> <span class="hlt">concentration</span> and <span class="hlt">ice</span> type from passive microwave data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Maslanik, J. A.</p> <p>1992-01-01</p> <p>Effects of wind, water vapor, and cloud liquid water on <span class="hlt">ice</span> <span class="hlt">concentration</span> and <span class="hlt">ice</span> type calculated from passive microwave data are assessed through radiative transfer calculations and observations. These weather effects can cause overestimates in <span class="hlt">ice</span> <span class="hlt">concentration</span> and more substantial underestimates in multi-year <span class="hlt">ice</span> percentage by decreasing polarization and by decreasing the gradient between frequencies. The effect of surface temperature and air temperature on the magnitudes of weather-related errors is small for <span class="hlt">ice</span> <span class="hlt">concentration</span> and substantial for multiyear <span class="hlt">ice</span> percentage. The existing weather filter in the NASA Team Algorithm addresses only weather effects over open ocean; the additional use of local open-ocean tie points and an alternative weather correction for the marginal <span class="hlt">ice</span> zone can further reduce errors due to weather. <span class="hlt">Ice</span> <span class="hlt">concentrations</span> calculated using 37 versus 18 GHz data show little difference in total <span class="hlt">ice</span> covered area, but greater differences in intermediate <span class="hlt">concentration</span> classes. Given the magnitude of weather-related errors in <span class="hlt">ice</span> classification from passive microwave data, corrections for weather effects may be necessary to detect small trends in <span class="hlt">ice</span> covered area and <span class="hlt">ice</span> type for climate studies.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20080040137&hterms=national+weather+service&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dnational%2Bweather%2Bservice','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20080040137&hterms=national+weather+service&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dnational%2Bweather%2Bservice"><span>Comparison of NASA Team2 and AES-York <span class="hlt">Ice</span> <span class="hlt">Concentration</span> Algorithms Against Operational <span class="hlt">Ice</span> Charts From the Canadian <span class="hlt">Ice</span> Service</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Shokr, Mohammed; Markus, Thorsten</p> <p>2006-01-01</p> <p><span class="hlt">Ice</span> <span class="hlt">concentration</span> retrieved from spaceborne passive-microwave observations is a prime input to operational sea-<span class="hlt">ice</span>-monitoring programs, numerical weather prediction models, and global climate models. Atmospheric Environment Service (AES)- York and the Enhanced National Aeronautics and Space Administration Team (NT2) are two algorithms that calculate <span class="hlt">ice</span> <span class="hlt">concentration</span> from Special Sensor Microwave/Imager observations. This paper furnishes a comparison between <span class="hlt">ice</span> <span class="hlt">concentrations</span> (total, thin, and thick types) output from NT2 and AES-York algorithms against the corresponding estimates from the operational analysis of Radarsat images in the Canadian <span class="hlt">Ice</span> Service (CIS). A new data fusion technique, which incorporates the actual sensor's footprint, was developed to facilitate this study. Results have shown that the NT2 and AES-York algorithms underestimate total <span class="hlt">ice</span> <span class="hlt">concentration</span> by 18.35% and 9.66% <span class="hlt">concentration</span> counts on average, with 16.8% and 15.35% standard deviation, respectively. However, the retrieved <span class="hlt">concentrations</span> of thin and thick <span class="hlt">ice</span> are in much more discrepancy with the operational CIS estimates when either one of these two types dominates the viewing area. This is more likely to occur when the total <span class="hlt">ice</span> <span class="hlt">concentration</span> approaches 100%. If thin and thick <span class="hlt">ice</span> types coexist in comparable <span class="hlt">concentrations</span>, the algorithms' estimates agree with CIS'S estimates. In terms of <span class="hlt">ice</span> <span class="hlt">concentration</span> retrieval, thin <span class="hlt">ice</span> is more problematic than thick <span class="hlt">ice</span>. The concept of using a single tie point to represent a thin <span class="hlt">ice</span> surface is not realistic and provides the largest error source for retrieval accuracy. While AES-York provides total <span class="hlt">ice</span> <span class="hlt">concentration</span> in slightly more agreement with CIS'S estimates, NT2 provides better agreement in retrieving thin and thick <span class="hlt">ice</span> <span class="hlt">concentrations</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012ACPD...1217295G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012ACPD...1217295G"><span>In-situ aircraft observations of <span class="hlt">ice</span> <span class="hlt">concentrations</span> within clouds over the Antarctic Peninsula and Larsen <span class="hlt">Ice</span> Shelf</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Grosvenor, D. P.; Choularton, T. W.; Lachlan-Cope, T.; Gallagher, M. W.; Crosier, J.; Bower, K. N.; Ladkin, R. S.; Dorsey, J. R.</p> <p>2012-07-01</p> <p>In-situ aircraft observations of <span class="hlt">ice</span> crystal <span class="hlt">concentrations</span> in Antarctic clouds are presented for the first time. Orographic, layer and wave clouds around the Antarctic Peninsula and Larsen <span class="hlt">Ice</span> shelf regions were penetrated by the British Antarctic Survey's Twin Otter Aircraft, which was equipped with modern cloud physics probes. The clouds studied were mostly in the free troposphere and hence <span class="hlt">ice</span> crystals blown from the surface are unlikely to have been a major source for the <span class="hlt">ice</span> phase. The temperature range covered by the experiments was 0 to -21°C. The clouds were found to contain supercooled liquid water in most regions and at heterogeneous <span class="hlt">ice</span> formation temperatures <span class="hlt">ice</span> crystal <span class="hlt">concentrations</span> (60 s averages) were often less than 0.07 l-1, although values up to 0.22 l-1 were observed. Estimates of observed aerosol <span class="hlt">concentrations</span> were used as input into the DeMott et al., 2010 <span class="hlt">ice</span> nuclei (IN) parameterisation. The observed <span class="hlt">ice</span> crystal number <span class="hlt">concentrations</span> were generally in broad agreement with the IN predictions, although on the whole the predicted values were higher. Possible reasons for this are discussed and include the lack of IN observations in this region with which to characterise the parameterisation, and/or problems in relating <span class="hlt">ice</span> <span class="hlt">concentration</span> measurements to IN <span class="hlt">concentrations</span>. Other IN parameterisations significantly overestimated the number of <span class="hlt">ice</span> particles. Generally <span class="hlt">ice</span> particle <span class="hlt">concentrations</span> were much lower than found in clouds in middle latitudes for a given temperature. Higher <span class="hlt">ice</span> crystal <span class="hlt">concentrations</span> were sometimes observed at temperatures warmer than -9 °C, with values of several per litre reached. These were attributable to secondary <span class="hlt">ice</span> particle production by the Hallett Mossop process. Even in this temperature range it was observed that there were regions with little or no <span class="hlt">ice</span> that were dominated by supercooled liquid water. It is likely that in some cases this was due to a lack of seeding <span class="hlt">ice</span> crystals to act as rimers to initiate</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012ACP....1211275G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012ACP....1211275G"><span>In-situ aircraft observations of <span class="hlt">ice</span> <span class="hlt">concentrations</span> within clouds over the Antarctic Peninsula and Larsen <span class="hlt">Ice</span> Shelf</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Grosvenor, D. P.; Choularton, T. W.; Lachlan-Cope, T.; Gallagher, M. W.; Crosier, J.; Bower, K. N.; Ladkin, R. S.; Dorsey, J. R.</p> <p>2012-12-01</p> <p>In-situ aircraft observations of <span class="hlt">ice</span> crystal <span class="hlt">concentrations</span> in Antarctic clouds are presented for the first time. Orographic, layer and wave clouds around the Antarctic Peninsula and Larsen <span class="hlt">Ice</span> shelf regions were penetrated by the British Antarctic Survey's Twin Otter aircraft, which was equipped with modern cloud physics probes. The clouds studied were mostly in the free troposphere and hence <span class="hlt">ice</span> crystals blown from the surface are unlikely to have been a major source for the <span class="hlt">ice</span> phase. The temperature range covered by the experiments was 0 to -21 °C. The clouds were found to contain supercooled liquid water in most regions and at heterogeneous <span class="hlt">ice</span> formation temperatures <span class="hlt">ice</span> crystal <span class="hlt">concentrations</span> (60 s averages) were often less than 0.07 l-1, although values up to 0.22 l-1 were observed. Estimates of observed aerosol <span class="hlt">concentrations</span> were used as input into the DeMott et al. (2010) <span class="hlt">ice</span> nuclei (IN) parameterisation. The observed <span class="hlt">ice</span> crystal number <span class="hlt">concentrations</span> were generally in broad agreement with the IN predictions, although on the whole the predicted values were higher. Possible reasons for this are discussed and include the lack of IN observations in this region with which to characterise the parameterisation, and/or problems in relating <span class="hlt">ice</span> <span class="hlt">concentration</span> measurements to IN <span class="hlt">concentrations</span>. Other IN parameterisations significantly overestimated the number of <span class="hlt">ice</span> particles. Generally <span class="hlt">ice</span> particle <span class="hlt">concentrations</span> were much lower than found in clouds in middle latitudes for a given temperature. Higher <span class="hlt">ice</span> crystal <span class="hlt">concentrations</span> were sometimes observed at temperatures warmer than -9 °C, with values of several per litre reached. These were attributable to secondary <span class="hlt">ice</span> particle production by the Hallett Mossop process. Even in this temperature range it was observed that there were regions with little or no <span class="hlt">ice</span> that were dominated by supercooled liquid water. It is likely that in some cases this was due to a lack of seeding <span class="hlt">ice</span> crystals to act as rimers to initiate</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016ESASP.740E.339K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016ESASP.740E.339K"><span>Baltic Sea <span class="hlt">Ice</span> <span class="hlt">Concentration</span> Estimation Using Sentinel-1 SAR and Microwave Radiometer Data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Karvonen, Juha</p> <p>2016-08-01</p> <p>Sea <span class="hlt">ice</span> <span class="hlt">concentration</span> (SIC) is an important sea <span class="hlt">ice</span> parameter in environmental research, weather and <span class="hlt">ice</span> forecasting and for navigation. We have developed a method for estimation of the Baltic Sea SIC using SENTINEL-1 SAR data and AMSR-2 microwave radiometer (MWR). Here we present the method and first results of January 2016. <span class="hlt">Ice</span> <span class="hlt">concentration</span> of FMI daily <span class="hlt">ice</span> charts has been used as reference data in this study.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015JGRC..120.8327H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015JGRC..120.8327H"><span>Short-term sea <span class="hlt">ice</span> forecasting: An assessment of <span class="hlt">ice</span> <span class="hlt">concentration</span> and <span class="hlt">ice</span> drift forecasts using the U.S. Navy's Arctic Cap Nowcast/Forecast System</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hebert, David A.; Allard, Richard A.; Metzger, E. Joseph; Posey, Pamela G.; Preller, Ruth H.; Wallcraft, Alan J.; Phelps, Michael W.; Smedstad, Ole Martin</p> <p>2015-12-01</p> <p>In this study the forecast skill of the U.S. Navy operational Arctic sea <span class="hlt">ice</span> forecast system, the Arctic Cap Nowcast/Forecast System (ACNFS), is presented for the period February 2014 to June 2015. ACNFS is designed to provide short term, 1-7 day forecasts of Arctic sea <span class="hlt">ice</span> and ocean conditions. Many quantities are forecast by ACNFS; the most commonly used include <span class="hlt">ice</span> <span class="hlt">concentration</span>, <span class="hlt">ice</span> thickness, <span class="hlt">ice</span> velocity, sea surface temperature, sea surface salinity, and sea surface velocities. <span class="hlt">Ice</span> <span class="hlt">concentration</span> forecast skill is compared to a persistent <span class="hlt">ice</span> state and historical sea <span class="hlt">ice</span> climatology. Skill scores are focused on areas where <span class="hlt">ice</span> <span class="hlt">concentration</span> changes by ±5% or more, and are therefore limited to primarily the marginal <span class="hlt">ice</span> zone. We demonstrate that ACNFS forecasts are skilful compared to assuming a persistent <span class="hlt">ice</span> state, especially beyond 24 h. ACNFS is also shown to be particularly skilful compared to a climatologic state for forecasts up to 102 h. Modeled <span class="hlt">ice</span> drift velocity is compared to observed buoy data from the International Arctic Buoy Programme. A seasonal bias is shown where ACNFS is slower than IABP velocity in the summer months and faster in the winter months. In February 2015, ACNFS began to assimilate a blended <span class="hlt">ice</span> <span class="hlt">concentration</span> derived from Advanced Microwave Scanning Radiometer 2 (AMSR2) and the Interactive Multisensor Snow and <span class="hlt">Ice</span> Mapping System (IMS). Preliminary results show that assimilating AMSR2 blended with IMS improves the short-term forecast skill and <span class="hlt">ice</span> edge location compared to the independently derived National <span class="hlt">Ice</span> Center <span class="hlt">Ice</span> Edge product.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016ACP....16.2185H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016ACP....16.2185H"><span>Unexpectedly high ultrafine aerosol <span class="hlt">concentrations</span> above East Antarctic sea <span class="hlt">ice</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Humphries, R. S.; Klekociuk, A. R.; Schofield, R.; Keywood, M.; Ward, J.; Wilson, S. R.</p> <p>2016-02-01</p> <p>Better characterisation of aerosol processes in pristine, natural environments, such as Antarctica, have recently been shown to lead to the largest reduction in uncertainties in our understanding of radiative forcing. Our understanding of aerosols in the Antarctic region is currently based on measurements that are often limited to boundary layer air masses at spatially sparse coastal and continental research stations, with only a handful of studies in the vast sea-<span class="hlt">ice</span> region. In this paper, the first observational study of sub-micron aerosols in the East Antarctic sea <span class="hlt">ice</span> region is presented. Measurements were conducted aboard the icebreaker Aurora Australis in spring 2012 and found that boundary layer condensation nuclei (CN3) <span class="hlt">concentrations</span> exhibited a five-fold increase moving across the polar front, with mean polar cell <span class="hlt">concentrations</span> of 1130 cm-3 - higher than any observed elsewhere in the Antarctic and Southern Ocean region. The absence of evidence for aerosol growth suggested that nucleation was unlikely to be local. Air parcel trajectories indicated significant influence from the free troposphere above the Antarctic continent, implicating this as the likely nucleation region for surface aerosol, a similar conclusion to previous Antarctic aerosol studies. The highest aerosol <span class="hlt">concentrations</span> were found to correlate with low-pressure systems, suggesting that the passage of cyclones provided an accelerated pathway, delivering air masses quickly from the free troposphere to the surface. After descent from the Antarctic free troposphere, trajectories suggest that sea-<span class="hlt">ice</span> boundary layer air masses travelled equatorward into the low-albedo Southern Ocean region, transporting with them emissions and these aerosol nuclei which, after growth, may potentially impact on the region's radiative balance. The high aerosol <span class="hlt">concentrations</span> and their transport pathways described here, could help reduce the discrepancy currently present between simulations and observations of</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..1610440J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..1610440J"><span>Sea <span class="hlt">ice</span> <span class="hlt">concentration</span> and sea <span class="hlt">ice</span> drift for the Arctic summer using C- and L-band SAR</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Johansson, Malin; Berg, Anders; Eriksson, Leif</p> <p>2014-05-01</p> <p>The decreasing amount of sea <span class="hlt">ice</span> and changes from multi-year <span class="hlt">ice</span> to first year <span class="hlt">ice</span> within the Arctic Ocean opens up for increased maritime activities. These activities include transportation, fishing and tourism. One of the major threats for the shipping is the presence of sea <span class="hlt">ice</span>. Should an oil spill occur, the search and rescue is heavily dependent on constant updates of sea <span class="hlt">ice</span> movements, both to enable a safer working environment and to potentially prevent the oil from reaching the sea <span class="hlt">ice</span>. It is therefore necessary to have accurate and updated sea <span class="hlt">ice</span> charts for the Arctic Ocean during the entire year. During the melt season that <span class="hlt">ice</span> is subject to melting conditions making satellite observations of sea <span class="hlt">ice</span> more difficult. This period coincides with the peak in marine shipping activities and therefore requires highly accurate sea <span class="hlt">ice</span> <span class="hlt">concentration</span> estimates. Synthetic Aperture Radar (SAR) are not hindered by clouds and do not require daylight. The continuous record and high temporal resolution makes C-band data preferable as input data for operational sea <span class="hlt">ice</span> mapping. However, with C-band SAR it is sometimes difficult to distinguish between a wet sea <span class="hlt">ice</span> surface and surrounding open water. L-band SAR has a larger penetration depth and has been shown to be less sensitive to less sensitive than C-band to the melt season. Inclusion of L-band data into sea chart estimates during the melt season in particular could therefore improve sea <span class="hlt">ice</span> monitoring. We compare sea <span class="hlt">ice</span> <span class="hlt">concentration</span> melt season observations using Advanced Land Observing Satellite (ALOS) L-band images with Envisat ASAR C-band images. We evaluate if L-band images can be used to improve separation of wet surface <span class="hlt">ice</span> from open water and compare with results for C-band.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.C11B0377L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.C11B0377L"><span>The melting sea <span class="hlt">ice</span> of Arctic polar cap in the summer solstice month and the role of ocean</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lee, S.; Yi, Y.</p> <p>2014-12-01</p> <p>The Arctic sea <span class="hlt">ice</span> is becoming smaller and thinner than climatological standard normal and more fragmented in the early summer. We investigated the widely changing Arctic sea <span class="hlt">ice</span> using the daily sea <span class="hlt">ice</span> <span class="hlt">concentration</span> data. Sea <span class="hlt">ice</span> data is generated from brightness temperature data derived from the sensors: Defense Meteorological Satellite Program (DMSP)-F13 Special Sensor Microwave/Imagers (SSM/Is), the DMSP-F17 Special Sensor Microwave Imager/Sounder (SSMIS) and the Advanced Microwave Scanning Radiometer - Earth Observing System (<span class="hlt">AMSR-E</span>) instrument on the NASA Earth Observing System (EOS) Aqua satellite. We tried to figure out appearance of arctic sea <span class="hlt">ice</span> melting region of polar cap from the data of passive microwave sensors. It is hard to explain polar sea <span class="hlt">ice</span> melting only by atmosphere effects like surface air temperature or wind. Thus, our hypothesis explaining this phenomenon is that the heat from deep undersea in Arctic Ocean ridges and the hydrothermal vents might be contributing to the melting of Arctic sea <span class="hlt">ice</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19890009426&hterms=PASSIVE+FILTER&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3DPASSIVE%2BFILTER','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19890009426&hterms=PASSIVE+FILTER&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3DPASSIVE%2BFILTER"><span>Estimating sea <span class="hlt">ice</span> <span class="hlt">concentration</span> from satellite passive microwave data and a physical model</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Rothrock, D. A.; Thomas, D. R.</p> <p>1988-01-01</p> <p>Sea <span class="hlt">ice</span> remote sensing and estimation of <span class="hlt">concentrations</span> of each of several <span class="hlt">ice</span> types from passive microwave satellite data is described. The approach is based on the Kalman filter; it incorporates surface temperature, <span class="hlt">ice</span> advection, and <span class="hlt">ice</span> deformation data derived from drifting buoys and uses the whole temporal microwave record to make a smoothed estimate of <span class="hlt">ice</span> <span class="hlt">concentration</span>. The method allows resolution of previously ambiguous surface types. An example using time histories of two SMMR measurements to resolve the fractional areas of four surface types: open water, first-year, second-year and older multiyear <span class="hlt">ice</span> is shown.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110023007','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110023007"><span>Improving Simulated Soil Moisture Fields Through Assimilation of <span class="hlt">AMSR-E</span> Soil Moisture Retrievals with an Ensemble Kalman Filter and a Mass Conservation Constraint</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Li, Bailing; Toll, David; Zhan, Xiwu; Cosgrove, Brian</p> <p>2011-01-01</p> <p>Model simulated soil moisture fields are often biased due to errors in input parameters and deficiencies in model physics. Satellite derived soil moisture estimates, if retrieved appropriately, represent the spatial mean of soil moisture in a footprint area, and can be used to reduce model bias (at locations near the surface) through data assimilation techniques. While assimilating the retrievals can reduce model bias, it can also destroy the mass balance enforced by the model governing equation because water is removed from or added to the soil by the assimilation algorithm. In addition, studies have shown that assimilation of surface observations can adversely impact soil moisture estimates in the lower soil layers due to imperfect model physics, even though the bias near the surface is decreased. In this study, an ensemble Kalman filter (EnKF) with a mass conservation updating scheme was developed to assimilate the actual value of Advanced Microwave Scanning Radiometer (<span class="hlt">AMSR-E</span>) soil moisture retrievals to improve the mean of simulated soil moisture fields by the Noah land surface model. Assimilation results using the conventional and the mass conservation updating scheme in the Little Washita watershed of Oklahoma showed that, while both updating schemes reduced the bias in the shallow root zone, the mass conservation scheme provided better estimates in the deeper profile. The mass conservation scheme also yielded physically consistent estimates of fluxes and maintained the water budget. Impacts of model physics on the assimilation results are discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016IJAEO..45..221M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016IJAEO..45..221M"><span>DisPATCh as a tool to evaluate coarse-scale remotely sensed soil moisture using localized in situ measurements: Application to SMOS and <span class="hlt">AMSR-E</span> data in Southeastern Australia</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Malbéteau, Yoann; Merlin, Olivier; Molero, Beatriz; Rüdiger, Christoph; Bacon, Stephan</p> <p>2016-03-01</p> <p>Validating coarse-scale satellite soil moisture data still represents a big challenge, notably due to the large mismatch existing between the spatial resolution (> 10 km) of microwave radiometers and the representativeness scale (several m) of localized in situ measurements. This study aims to examine the potential of DisPATCh (Disaggregation based on Physical and Theoretical scale Change) for validating SMOS (Soil Moisture and Ocean Salinity) and <span class="hlt">AMSR-E</span> (Advanced Microwave Scanning Radiometer-Earth observation system) level-3 soil moisture products. The ∽40-50 km resolution SMOS and <span class="hlt">AMSR-E</span> data are disaggregated at 1 km resolution over the Murrumbidgee catchment in Southeastern Australia during a one year period in 2010-2011, and the satellite products are compared with the in situ measurements of 38 stations distributed within the study area. It is found that disaggregation improves the mean difference, correlation coefficient and slope of the linear regression between satellite and in situ data in 77%, 92% and 94% of cases, respectively. Nevertheless, the downscaling efficiency is lower in winter than during the hotter months when DisPATCh performance is optimal. Consistently, better results are obtained in the semi-arid than in a temperate zone of the catchment. In the semi-arid Yanco region, disaggregation in summer increases the correlation coefficient from 0.63 to 0.78 and from 0.42 to 0.71 for SMOS and <span class="hlt">AMSR-E</span> in morning overpasses and from 0.37 to 0.63 and from 0.47 to 0.73 for SMOS and <span class="hlt">AMSR-E</span> in afternoon overpasses, respectively. DisPATCh has strong potential in low vegetated semi-arid areas where it can be used as a tool to evaluate coarse-scale remotely sensed soil moisture by explicitly representing the sub-pixel variability.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1817411S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1817411S"><span>Modeling the relative contributions of secondary <span class="hlt">ice</span> formation processes to <span class="hlt">ice</span> crystal number <span class="hlt">concentrations</span> within mixed-phase clouds</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sullivan, Sylvia; Hoose, Corinna; Nenes, Athanasios</p> <p>2016-04-01</p> <p>Measurements of in-cloud <span class="hlt">ice</span> crystal number <span class="hlt">concentrations</span> can be three or four orders of magnitude greater than the in-cloud <span class="hlt">ice</span> nuclei number <span class="hlt">concentrations</span>. This discrepancy can be explained by various secondary <span class="hlt">ice</span> formation processes, which occur after initial <span class="hlt">ice</span> nucleation, but the relative importance of these processes, and even the exact physics of each, is still unclear. A simple bin microphysics model (2IM) is constructed to investigate these knowledge gaps. 2IM extends the time-lag collision parameterization of Yano and Phillips, 2011 to include rime splintering, <span class="hlt">ice-ice</span> aggregation, and droplet shattering and to incorporate the aspect ratio evolution as in Jensen and Harrington, 2015. The relative contribution of the secondary processes under various conditions are shown. In particular, temperature-dependent efficiencies are adjusted for <span class="hlt">ice-ice</span> aggregation versus collision around -15°C, when rime splintering is no longer active, and the effect of aspect ratio on the process weighting is explored. The resulting simulations are intended to guide secondary <span class="hlt">ice</span> formation parameterizations in larger-scale mixed-phase cloud schemes.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20020074657','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20020074657"><span>Sensitivity of Lunar Resource Economic Model to Lunar <span class="hlt">Ice</span> <span class="hlt">Concentration</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Blair, Brad; Diaz, Javier</p> <p>2002-01-01</p> <p>Lunar Prospector mission data indicates sufficient <span class="hlt">concentration</span> of hydrogen (presumed to be in the form of water <span class="hlt">ice</span>) to form the basis for lunar in-situ mining activities to provide a source of propellant for near-Earth and solar system transport missions. A model being developed by JPL, Colorado School of Mines, and CSP, Inc. generates the necessary conditions under which a commercial enterprise could earn a sufficient rate of return to develop and operate a LEO propellant service for government and commercial customers. A combination of Lunar-derived propellants, L-1 staging, and orbital fuel depots could make commercial LEO/GEO development, inter-planetary missions and the human exploration and development of space more energy, cost, and mass efficient.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.A22A..08J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.A22A..08J"><span>Physical processes controlling the evolution of <span class="hlt">ice</span> <span class="hlt">concentration</span> in cirrus clouds</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Jensen, E. J.; Pfister, L.</p> <p>2011-12-01</p> <p>Several past studies have compared measured cirrus <span class="hlt">ice</span> <span class="hlt">concentrations</span> with calculations based on nucleation theory. However, such calculations only indicate the peak <span class="hlt">ice</span> <span class="hlt">concentrations</span> occurring just after nucleation events. Various cloud processes (e.g., differential sedimentation, entrainment, dispersion, and aggregation) conspire to reduce mean <span class="hlt">ice</span> <span class="hlt">concentrations</span> as the cloud evolves. Here, we use both a one-dimensional cloud model and a three-dimensional cloud-resolving model to evaluate the impact of these processes on the evolution of <span class="hlt">ice</span> <span class="hlt">concentration</span> through the lifecycle of cirrus clouds. Results are compared statistically with recent airborne measurements of <span class="hlt">ice</span> <span class="hlt">concentration</span> in the midlatitude and tropical uppermost troposphere. We will show that mean <span class="hlt">ice</span> <span class="hlt">concentrations</span> are reduced substantially by processes occurring after nucleation events, and this issue should be taken into consideration when comparing with observations that necessarily represent a range of cloud ages.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li class="active"><span>6</span></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_6 --> <div id="page_7" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li class="active"><span>7</span></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="121"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015ACPD...1535907Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015ACPD...1535907Z"><span>What controls the low <span class="hlt">ice</span> number <span class="hlt">concentration</span> in the upper troposphere?</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhou, C.; Penner, J. E.; Lin, G.; Liu, X.; Wang, M.</p> <p>2015-12-01</p> <p>Cirrus clouds in the tropical tropopause play a key role in regulating the moisture entering the stratosphere through their dehydrating effect. Low <span class="hlt">ice</span> number <span class="hlt">concentrations</span> (< 200 L-1) and high supersaturations (150-160 %) have been observed in these clouds. Different mechanisms have been proposed to explain these low <span class="hlt">ice</span> number <span class="hlt">concentrations</span>, including the inhibition of homogeneous freezing by the deposition of water vapour onto pre-existing <span class="hlt">ice</span> crystals, heterogeneous <span class="hlt">ice</span> formation on glassy organic aerosol <span class="hlt">ice</span> nuclei (IN), and limiting the formation of <span class="hlt">ice</span> number from high frequency gravity waves. In this study, we examined the effect from three different representations of updraft velocities, the effect from pre-existing <span class="hlt">ice</span> crystals, the effect from different water vapour deposition coefficients (α = 0.1 or 1), and the effect of 0.1 % of the total secondary organic aerosol (SOA) particles acting as IN. Model simulated <span class="hlt">ice</span> crystal numbers are compared against an aircraft observational dataset. Including the effect from water vapour deposition on pre-existing <span class="hlt">ice</span> particles can effectively reduce simulated in-cloud <span class="hlt">ice</span> number <span class="hlt">concentrations</span> for all model set-ups. A larger water vapour deposition coefficient (α = 1) can also efficiently reduce <span class="hlt">ice</span> number <span class="hlt">concentrations</span> at temperatures below 205 K but less so at higher temperatures. SOA acting as IN are most effective at reducing <span class="hlt">ice</span> number <span class="hlt">concentrations</span> when the effective updraft velocities are moderate (∼ 0.05-0.2 m s-1). However, the effects of including SOA as IN and using (α = 1) are diminished when the effect from pre-existing <span class="hlt">ice</span> is included. When a grid resolved large-scale updraft velocity (< 0.1 m s-1) is used, the <span class="hlt">ice</span> nucleation parameterization with homogeneous freezing only or with both homogeneous freezing and heterogeneous nucleation is able to generate low <span class="hlt">ice</span> number <span class="hlt">concentrations</span> in good agreement with observations for temperatures below 205 K as long as the pre-existing <span class="hlt">ice</span> effect is</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016ACP....1612411Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016ACP....1612411Z"><span>What controls the low <span class="hlt">ice</span> number <span class="hlt">concentration</span> in the upper troposphere?</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhou, Cheng; Penner, Joyce E.; Lin, Guangxing; Liu, Xiaohong; Wang, Minghuai</p> <p>2016-10-01</p> <p>Cirrus clouds in the tropical tropopause play a key role in regulating the moisture entering the stratosphere through their dehydrating effect. Low <span class="hlt">ice</span> number <span class="hlt">concentrations</span> ( < 200 L-1) and high supersaturations (150-160 %) have been observed in these clouds. Different mechanisms have been proposed to explain these low <span class="hlt">ice</span> number <span class="hlt">concentrations</span>, including the inhibition of homogeneous freezing by the deposition of water vapour onto pre-existing <span class="hlt">ice</span> crystals, heterogeneous <span class="hlt">ice</span> formation on glassy organic aerosol <span class="hlt">ice</span> nuclei (IN), and limiting the formation of <span class="hlt">ice</span> number from high-frequency gravity waves. In this study, we examined the effect from three different representations of updraft velocities, the effect from pre-existing <span class="hlt">ice</span> crystals, the effect from different water vapour deposition coefficients (α = 0.1 or 1), and the effect of 0.1 % of the total secondary organic aerosol (SOA) particles acting as IN. Model-simulated <span class="hlt">ice</span> crystal numbers are compared against an aircraft observational dataset.Including the effect from water vapour deposition on pre-existing <span class="hlt">ice</span> particles can effectively reduce simulated in-cloud <span class="hlt">ice</span> number <span class="hlt">concentrations</span> for all model setups. A larger water vapour deposition coefficient (α = 1) can also efficiently reduce <span class="hlt">ice</span> number <span class="hlt">concentrations</span> at temperatures below 205 K, but less so at higher temperatures. SOA acting as IN is most effective at reducing <span class="hlt">ice</span> number <span class="hlt">concentrations</span> when the effective updraft velocities are moderate ( ˜ 0.05-0.2 m s-1). However, the effects of including SOA as IN and using (α = 1) are diminished when the effect from pre-existing <span class="hlt">ice</span> is included.When a grid-resolved large-scale updraft velocity ( < 0.1 m s-1) is used, the <span class="hlt">ice</span> nucleation parameterization with homogeneous freezing only or with both homogeneous freezing and heterogeneous nucleation is able to generate low <span class="hlt">ice</span> number <span class="hlt">concentrations</span> in good agreement with observations for temperatures below 205 K as long as the pre-existing <span class="hlt">ice</span> effect is</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20070018253&hterms=klein&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAuthor-Name%26N%3D0%26No%3D60%26Ntt%3Dklein','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20070018253&hterms=klein&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAuthor-Name%26N%3D0%26No%3D60%26Ntt%3Dklein"><span>Microwave Signatures of Snow on Sea <span class="hlt">Ice</span>: Observations</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Markus, Thorsten; Cavalieri, Donald J.; Gasiewski, Albin J.; Klein, Marian; Maslanik, James A.; Powell, Dylan C.; Stankov, B. Boba; Stroeve, Julienne C.; Sturm, Matthew</p> <p>2006-01-01</p> <p>Part of the Earth Observing System Aqua Advanced Microwave Scanning Radiometer (<span class="hlt">AMSR-E</span>) Arctic sea <span class="hlt">ice</span> validation campaign in March 2003 was dedicated to the validation of snow depth on sea <span class="hlt">ice</span> and <span class="hlt">ice</span> 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 <span class="hlt">ice</span> 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 <span class="hlt">ice</span> camp. The results confirm the <span class="hlt">AMSR-E</span> snow depth algorithm and its coefficients for first-year <span class="hlt">ice</span> when it is relatively smooth. For rough first-year <span class="hlt">ice</span> and for multiyear <span class="hlt">ice</span>, 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 <span class="hlt">AMSR-E</span> channels did not provide a clear signature of sea <span class="hlt">ice</span> characteristics and, hence, could not provide guidance for the choice of algorithm coefficients. The limited comparison of in situ snow-<span class="hlt">ice</span> interface and surface temperatures with 6-GHz brightness temperatures, which are used for the retrieval of <span class="hlt">ice</span> temperature, shows that the 6-GHz temperature is correlated with the snow-<span class="hlt">ice</span> 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.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015TCD.....9.2543Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015TCD.....9.2543Y"><span>The benefit of using sea <span class="hlt">ice</span> <span class="hlt">concentration</span> satellite data products with uncertainty estimates in summer sea <span class="hlt">ice</span> data assimilation</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Yang, Q.; Losch, M.; Losa, S.; Jung, T.; Nerger, L.; Lavergne, T.</p> <p>2015-04-01</p> <p>We present sensitivity experiments in which the Ocean and Sea <span class="hlt">Ice</span> Satellite Application Facility (OSISAF) near-real time sea <span class="hlt">ice</span> <span class="hlt">concentration</span> data and the recently released Sea <span class="hlt">Ice</span> Climate Change Initiative (SICCI) data are assimilated during summer. The data assimilation system uses the MIT general circulation model (MITgcm) and a local Singular Evolutive Interpolated Kalman (LSEIK) filter. Atmospheric forcing uncertainties are modelled by using atmospheric ensemble forcing which is taken from the UK Met Office (UKMO) system available through the TIGGE (THORPEX Interactive Grand Global Ensemble) database. When a constant data uncertainty is assumed, the assimilation of SICCI <span class="hlt">concentrations</span> outperforms the assimilation of OSISAF data in both <span class="hlt">concentration</span> and thickness forecasts. This is probably because the SICCI data retrieval uses an improved processing algorithms and methodologies. For the assimilation of SICCI data, using the observation uncertainties that are provided with the data improves the ensemble mean state of <span class="hlt">ice</span> <span class="hlt">concentration</span> compared to using constant data errors, but does not improve the <span class="hlt">ice</span> thickness. This is caused by a mismatch between the SICCI <span class="hlt">concentration</span> and the modelled physical <span class="hlt">ice</span> <span class="hlt">concentration</span>. To account for this mismatch the SICCI product should feature larger uncertainties in summer. Consistently, thickness forecasts can be improved by raising the minimum observation uncertainty to inflate the underestimated data error and ensemble spread.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016ACP....1611367N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016ACP....1611367N"><span>Cloud <span class="hlt">ice</span> caused by atmospheric mineral dust - Part 1: Parameterization of <span class="hlt">ice</span> nuclei <span class="hlt">concentration</span> in the NMME-DREAM model</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Nickovic, Slobodan; Cvetkovic, Bojan; Madonna, Fabio; Rosoldi, Marco; Pejanovic, Goran; Petkovic, Slavko; Nikolic, Jugoslav</p> <p>2016-09-01</p> <p>Dust aerosols are very efficient <span class="hlt">ice</span> nuclei, important for heterogeneous cloud glaciation even in regions distant from desert sources. A new generation of <span class="hlt">ice</span> nucleation parameterizations, including dust as an <span class="hlt">ice</span> nucleation agent, opens the way towards a more accurate treatment of cold cloud formation in atmospheric models. Using such parameterizations, we have developed a regional dust-atmospheric modelling system capable of predicting, in real time, dust-induced <span class="hlt">ice</span> nucleation. We executed the model with the added <span class="hlt">ice</span> nucleation component over the Mediterranean region, exposed to moderate Saharan dust transport, over two periods lasting 15 and 9 days, respectively. The model results were compared against satellite and ground-based cloud-<span class="hlt">ice</span>-related measurements, provided by SEVIRI (Spinning Enhanced Visible and InfraRed Imager) and the CNR-IMAA Atmospheric Observatory (CIAO) in Potenza, southern Italy. The predicted <span class="hlt">ice</span> nuclei <span class="hlt">concentration</span> showed a reasonable level of agreement when compared against the observed spatial and temporal patterns of cloud <span class="hlt">ice</span> water. The developed methodology permits the use of <span class="hlt">ice</span> nuclei as input into the cloud microphysics schemes of atmospheric models, assuming that this approach could improve the predictions of cloud formation and associated precipitation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120013478','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120013478"><span>Variability and Anomalous Trends in the Global Sea <span class="hlt">Ice</span> Cover</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Comiso, Josefino C.</p> <p>2012-01-01</p> <p> MODIS, <span class="hlt">AMSR-E</span> and SSM/I data reveal that the sea <span class="hlt">ice</span> production rate at the coastal polynyas along the Ross <span class="hlt">Ice</span> Shelf has been increasing since 1992. This also means that the salinization rate and the formation of bottom water in the region are going up as well. Simulation studies indicate that the stronger production rate is likely associated with the ozone hole that has caused a deepening of the lows in the West Antarctic region and therefore stronger winds off the Ross <span class="hlt">Ice</span> Shelf. Stronger winds causes larger coastal polynyas near the shelf and hence an enhanced <span class="hlt">ice</span> production in the region during the autumn and winter period. Results of analysis of temperature data from MODIS and <span class="hlt">AMSR-E</span> shows that the area and <span class="hlt">concentration</span> of the sea <span class="hlt">ice</span> cover are highly correlated with surface temperature for both the Arctic and Antarctic, especially in the seasonal regions where the correlation coefficients are about 0.9. Abnormally high sea surface temperatures (SSTs) and surface <span class="hlt">ice</span> temperatures (SITs) were also observed in 2007 and 2011when drastic reductions in the summer <span class="hlt">ice</span> cover occurred, This phenomenon is consistent with the expected warming of the upper layer of the Arctic Ocean on account of <span class="hlt">ice</span>-albedo feedback. Changes in atmospheric circulation are also expected to have a strong influence on the sea <span class="hlt">ice</span> cover but the results of direct correlation analyses of the sea <span class="hlt">ice</span> cover with the Northern and the Southern Annular Mode indices show relatively weak correlations, This might be due in part to the complexity of the dynamics of the system that can be further altered by some phenomena like the Antarctic Circumpolar Wave and extra polar processes like the El Nino Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (POD),</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A51I0194A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A51I0194A"><span>Spatial and Temporal Variation of Boundary Layer Lapse Rate and Cloud-top-height Observed from MODIS, CALIPSO and <span class="hlt">AMSR-E</span> over Eastern Pacific</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Adhikari, L.; Xie, F.; Winning, T.</p> <p>2015-12-01</p> <p>The strong free tropospheric subsidence and the cool sea surface temperatures over the subtropical eastern Pacific Ocean often lead to a shallow and cloudy planetary boundary layer (PBL) capped by a strong inversion. These low PBL clouds are crucial for understanding the ocean-atmosphere interaction and the cloud-radiation feedback processes. However, accurate identification/representation of these clouds remains a key challenge in both satellite observations and global climate model simulations. Specifically, the cloud transition from the near-shore stratocumulus to trade-cumulus remains a huge challenge in climate models and warrants high-quality PBL observations from space. The MODIS collection 6 cloud top height vastly improves the global PBL cloud top heights (CTH) compared to collection 5. However, the MODIS collection 6 CTH still shows systematic higher CTH than CALIPSO in the subtropical subsidence region, which is likely due to the underestimation of lapse rate. This study presents the seasonal climatology of PBL lapse rate derived from multi-year CALIPSO with co-incident MODIS CTT and <span class="hlt">AMSR-E</span> SST measurements. The lapse rate climatology is validated by the high-resolution radiosonde observations and then used to derive the CTH from MODIS measurements. Comparison of the new lapse rate based MODIS CTH with CALIPSO CTH will be presented. The PBL height derived from the COSMIC (Constellation Observing System for Meteorology, Ionosphere, and Climate) GPS radio occultation (RO) will be used to evaluate the MODIS CTH as an independent dataset. The discrepancies over the transition from stratus to trade-cumuli regions (broken clouds) will also be discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19870020588','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19870020588"><span>Satellite-derived <span class="hlt">ice</span> data sets no. 2: Arctic monthly average microwave brightness temperatures and sea <span class="hlt">ice</span> <span class="hlt">concentrations</span>, 1973-1976</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Parkinson, C. L.; Comiso, J. C.; Zwally, H. J.</p> <p>1987-01-01</p> <p>A summary data set for four years (mid 70's) of Arctic sea <span class="hlt">ice</span> conditions is available on magnetic tape. The data include monthly and yearly averaged Nimbus 5 electrically scanning microwave radiometer (ESMR) brightness temperatures, an <span class="hlt">ice</span> <span class="hlt">concentration</span> parameter derived from the brightness temperatures, monthly climatological surface air temperatures, and monthly climatological sea level pressures. All data matrices are applied to 293 by 293 grids that cover a polar stereographic map enclosing the 50 deg N latitude circle. The grid size varies from about 32 X 32 km at the poles to about 28 X 28 km at 50 deg N. The <span class="hlt">ice</span> <span class="hlt">concentration</span> parameter is calculated assuming that the field of view contains only open water and first-year <span class="hlt">ice</span> with an <span class="hlt">ice</span> emissivity of 0.92. To account for the presence of multiyear <span class="hlt">ice</span>, a nomogram is provided relating the <span class="hlt">ice</span> <span class="hlt">concentration</span> parameter, the total <span class="hlt">ice</span> <span class="hlt">concentration</span>, and the fraction of the <span class="hlt">ice</span> cover which is multiyear <span class="hlt">ice</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JGRD..121.6927Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JGRD..121.6927Y"><span>Sensitivity of Arctic warming to sea <span class="hlt">ice</span> <span class="hlt">concentration</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Yim, Bo Young; Min, Hong Sik; Kim, Baek-Min; Jeong, Jee-Hoon; Kug, Jong-Seong</p> <p>2016-06-01</p> <p>We examine the sensitivity of Arctic amplification (AA) to background sea <span class="hlt">ice</span> <span class="hlt">concentration</span> (SIC) under greenhouse warming by analyzing the data sets of the historical and Representative <span class="hlt">Concentration</span> Pathway 8.5 runs of the Coupled Model Intercomparison Project Phase 5. To determine whether the sensitivity of AA for a given radiative forcing depends on background SIC state, we examine the relationship between the AA trend and mean SIC on moving 30 year windows from 1960 to 2100. It is found that the annual mean AA trend varies depending on the mean SIC condition. In particular, some models show a highly variable AA trend in relation to the mean SIC clearly. In these models, the AA trend tends to increase until the mean SIC reaches a critical level (i.e., 20-30%), and the maximum AA trend is almost 3 to 5 times larger than the trend in the early stage of global warming (i.e., 50-60%, 60-70%). However, the AA trend tends to decrease after that. Further analysis shows that the sensitivity of AA trend to mean SIC condition is closely related to the feedback processes associated with summer surface albedo and winter turbulent heat flux in the Arctic Ocean.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110008454','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110008454"><span>Freeboard, Snow Depth and Sea-<span class="hlt">Ice</span> Roughness in East Antarctica from In Situ and Multiple Satellite Data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Markus, Thorsten; Masson, Robert; Worby, Anthony; Lytle, Victoria; Kurtz, Nathan; Maksym, Ted</p> <p>2011-01-01</p> <p>In October 2003 a campaign on board the Australian icebreaker Aurora Australis had the objective to validate standard Aqua Advanced Microwave Scanning Radiometer (<span class="hlt">AMSR-E</span>) sea-<span class="hlt">ice</span> products. Additionally, the satellite laser altimeter on the <span class="hlt">Ice</span>, Cloud and land Elevation Satellite (ICESat) was in operation. To capture the large-scale information on the sea-<span class="hlt">ice</span> conditions necessary for satellite validation, the measurement strategy was to obtain large-scale sea-<span class="hlt">ice</span> statistics using extensive sea-<span class="hlt">ice</span> 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 <span class="hlt">ice</span> 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 <span class="hlt">ice</span>-drift information as well as daily estimates of thin-<span class="hlt">ice</span> fraction and rough-<span class="hlt">ice</span> vs smooth-<span class="hlt">ice</span> fractions from <span class="hlt">AMSR-E</span> 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 <span class="hlt">AMSR-E</span> snow depth algorithm significantly improves snow depth retrievals. Snow depth retrievals using a combination of <span class="hlt">AMSR-E</span> 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.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015ESDD....6.2137S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015ESDD....6.2137S"><span>Importance of open-water <span class="hlt">ice</span> growth and <span class="hlt">ice</span> <span class="hlt">concentration</span> evolution: a study based on FESOM-ECHAM6</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Shi, X.; Lohmann, G.</p> <p>2015-10-01</p> <p>A newly developed global climate model FESOM-ECHAM6 with an unstructured mesh and high resolution is applied to investigate to what degree the area-thickness distribution of new <span class="hlt">ice</span> formed in open water affects the <span class="hlt">ice</span> and ocean properties. A sensitivity experiment is performed which reduces the horizontal-to-vertical aspect ratio of open-water <span class="hlt">ice</span> growth. The resulting decrease in the Arctic winter sea-<span class="hlt">ice</span> <span class="hlt">concentration</span> strongly reduces the surface albedo, enhances the ocean heat release to the atmosphere, and increases the sea-<span class="hlt">ice</span> production. Furthermore, our simulations show a positive feedback mechanism among the Arctic sea <span class="hlt">ice</span>, the Atlantic Meridional Overturning Circulation (AMOC), and the surface air temperature in the Arctic, as the sea <span class="hlt">ice</span> transport affects the freshwater budget in regions of deep water formation. A warming over Europe, Asia and North America, associated with a negative anomaly of Sea Level Pressure (SLP) over the Arctic (positive phase of the Arctic Oscillation (AO)), is also simulated by the model. For the Southern Ocean, the most pronounced change is a warming along the Antarctic Circumpolar Current (ACC), especially for the Pacific sector. Additionally, a series of sensitivity tests are performed using an idealized 1-D thermodynamic model to further investigate the influence of the open-water <span class="hlt">ice</span> growth, which reveals similar results in terms of the change of sea <span class="hlt">ice</span> and ocean temperature. In reality, the distribution of new <span class="hlt">ice</span> on open water relies on many uncertain parameters, for example, surface albedo, wind speed and ocean currents. Knowledge of the detailed processes is currently too crude for those processes to be implemented realistically into models. Our sensitivity experiments indicate a pronounced uncertainty related to open-water sea <span class="hlt">ice</span> growth which could significantly affect the climate system.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016TCry...10.2217K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016TCry...10.2217K"><span>The impact of melt ponds on summertime microwave brightness temperatures and sea-<span class="hlt">ice</span> <span class="hlt">concentrations</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kern, Stefan; Rösel, Anja; Toudal Pedersen, Leif; Ivanova, Natalia; Saldo, Roberto; Tage Tonboe, Rasmus</p> <p>2016-09-01</p> <p>Sea-<span class="hlt">ice</span> <span class="hlt">concentrations</span> derived from satellite microwave brightness temperatures are less accurate during summer. In the Arctic Ocean the lack of accuracy is primarily caused by melt ponds, but also by changes in the properties of snow and the sea-<span class="hlt">ice</span> surface itself. We investigate the sensitivity of eight sea-<span class="hlt">ice</span> <span class="hlt">concentration</span> retrieval algorithms to melt ponds by comparing sea-<span class="hlt">ice</span> <span class="hlt">concentration</span> with the melt-pond fraction. We derive gridded daily sea-<span class="hlt">ice</span> <span class="hlt">concentrations</span> from microwave brightness temperatures of summer 2009. We derive the daily fraction of melt ponds, open water between <span class="hlt">ice</span> floes, and the <span class="hlt">ice</span>-surface fraction from contemporary Moderate Resolution Spectroradiometer (MODIS) reflectance data. We only use grid cells where the MODIS sea-<span class="hlt">ice</span> <span class="hlt">concentration</span>, which is the melt-pond fraction plus the <span class="hlt">ice</span>-surface fraction, exceeds 90 %. For one group of algorithms, e.g., Bristol and Comiso bootstrap frequency mode (Bootstrap_f), sea-<span class="hlt">ice</span> <span class="hlt">concentrations</span> are linearly related to the MODIS melt-pond fraction quite clearly after June. For other algorithms, e.g., Near90GHz and Comiso bootstrap polarization mode (Bootstrap_p), this relationship is weaker and develops later in summer. We attribute the variation of the sensitivity to the melt-pond fraction across the algorithms to a different sensitivity of the brightness temperatures to snow-property variations. We find an underestimation of the sea-<span class="hlt">ice</span> <span class="hlt">concentration</span> by between 14 % (Bootstrap_f) and 26 % (Bootstrap_p) for 100 % sea <span class="hlt">ice</span> with a melt-pond fraction of 40 %. The underestimation reduces to 0 % for a melt-pond fraction of 20 %. In presence of real open water between <span class="hlt">ice</span> floes, the sea-<span class="hlt">ice</span> <span class="hlt">concentration</span> is overestimated by between 26 % (Bootstrap_f) and 14 % (Bootstrap_p) at 60 % sea-<span class="hlt">ice</span> <span class="hlt">concentration</span> and by 20 % across all algorithms at 80 % sea-<span class="hlt">ice</span> <span class="hlt">concentration</span>. None of the algorithms investigated performs best based on our investigation of data from summer 2009. We suggest that those algorithms which are</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014TCry....8.1639K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014TCry....8.1639K"><span>A sea <span class="hlt">ice</span> <span class="hlt">concentration</span> estimation algorithm utilizing radiometer and SAR data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Karvonen, J.</p> <p>2014-09-01</p> <p>We have studied the possibility of combining the high-resolution synthetic aperture radar (SAR) segmentation and <span class="hlt">ice</span> <span class="hlt">concentration</span> estimated by radiometer brightness temperatures. Here we present an algorithm for mapping a radiometer-based <span class="hlt">concentration</span> value for each SAR segment. The <span class="hlt">concentrations</span> are estimated by a multi-layer perceptron (MLP) neural network which has the AMSR-2 (Advanced Microwave Scanning Radiometer 2) polarization ratios and gradient ratios of four radiometer channels as its inputs. The results have been compared numerically to the gridded Finnish Meteorological Institute (FMI) <span class="hlt">ice</span> chart <span class="hlt">concentrations</span> and high-resolution AMSR-2 ASI (ARTIST Sea <span class="hlt">Ice</span>) algorithm <span class="hlt">concentrations</span> provided by the University of Hamburg and also visually to the AMSR-2 bootstrap algorithm <span class="hlt">concentrations</span>, which are given in much coarser resolution. The differences when compared to FMI daily <span class="hlt">ice</span> charts were on average small. When compared to ASI <span class="hlt">ice</span> <span class="hlt">concentrations</span>, the differences were a bit larger, but still small on average. According to our comparisons, the largest differences typically occur near the <span class="hlt">ice</span> edge and sea-land boundary. The main advantage of combining radiometer-based <span class="hlt">ice</span> <span class="hlt">concentration</span> estimation and SAR segmentation seems to be a more precise estimation of the boundaries of different <span class="hlt">ice</span> <span class="hlt">concentration</span> zones.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016OcMod.105...60L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016OcMod.105...60L"><span>Impact of surface wind biases on the Antarctic sea <span class="hlt">ice</span> <span class="hlt">concentration</span> budget in climate models</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lecomte, O.; Goosse, H.; Fichefet, T.; Holland, P. R.; Uotila, P.; Zunz, V.; Kimura, N.</p> <p>2016-09-01</p> <p>We derive the terms in the Antarctic sea <span class="hlt">ice</span> <span class="hlt">concentration</span> budget from the output of three models, and compare them to observations of the same terms. Those models include two climate models from the 5th Coupled Model Intercomparison Project (CMIP5) and one ocean-sea <span class="hlt">ice</span> coupled model with prescribed atmospheric forcing. Sea <span class="hlt">ice</span> drift and wind fields from those models, in average over April-October 1992-2005, all exhibit large differences with the available observational or reanalysis datasets. However, the discrepancies between the two distinct <span class="hlt">ice</span> drift products or the two wind reanalyses used here are sometimes even greater than those differences. Two major findings stand out from the analysis. Firstly, large biases in sea <span class="hlt">ice</span> drift speed and direction in exterior sectors of the sea <span class="hlt">ice</span> covered region tend to be systematic and consistent with those in winds. This suggests that sea <span class="hlt">ice</span> errors in these areas are most likely wind-driven, so as errors in the simulated <span class="hlt">ice</span> motion vectors. The systematic nature of these biases is less prominent in interior sectors, nearer the coast, where sea <span class="hlt">ice</span> is mechanically constrained and its motion in response to the wind forcing more depending on the model rheology. Second, the intimate relationship between winds, sea <span class="hlt">ice</span> drift and the sea <span class="hlt">ice</span> <span class="hlt">concentration</span> budget gives insight on ways to categorize models with regard to errors in their <span class="hlt">ice</span> dynamics. In exterior regions, models with seemingly too weak winds and slow <span class="hlt">ice</span> drift consistently yield a lack of <span class="hlt">ice</span> velocity divergence and hence a wrong wintertime sea <span class="hlt">ice</span> growth rate. In interior sectors, too slow <span class="hlt">ice</span> drift, presumably originating from issues in the physical representation of sea <span class="hlt">ice</span> dynamics as much as from errors in surface winds, leads to wrong timing of the late winter <span class="hlt">ice</span> retreat. Those results illustrate that the applied methodology provides a valuable tool for prioritizing model improvements based on the <span class="hlt">ice</span> <span class="hlt">concentration</span> budget-<span class="hlt">ice</span> drift biases-wind biases</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20070035051','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20070035051"><span>The Influence of Sea <span class="hlt">Ice</span> on Primary Production in the Southern Ocean: A Satellite Perspective</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Smith, Walker O., Jr.; Comiso, Josefino C.</p> <p>2007-01-01</p> <p>Sea <span class="hlt">ice</span> in the Southern Ocean is a major controlling factor on phytoplankton productivity and growth, but the relationship is modified by regional differences in atmospheric and oceanographic conditions. We used the phytoplankton biomass (binned at 7-day intervals), PAR and cloud cover data from SeaWiFS, <span class="hlt">ice</span> <span class="hlt">concentrations</span> data from SSM/I and <span class="hlt">AMSR-E</span>, and sea-surface temperature data from AVHRR, in combination with a vertically integrated model to estimate primary productivity throughout the Southern Ocean (south of 60"s). We also selected six areas within the Southern Ocean and analyzed the variability of the primary productivity and trends through time, as well as the relationship of sea <span class="hlt">ice</span> to productivity. We found substantial interannual variability in productivity from 1997 - 2005 in all regions of the Southern Ocean, and this variability appeared to be driven in large part by <span class="hlt">ice</span> dynamics. The most productive regions of Antarctic waters were the continental shelves, which showed the earliest growth, the maximum biomass, and the greatest areal specific productivity. In contrast, no large, sustained blooms occurred in waters of greater depth (> 1,000 m). We suggest that this is due to the slightly greater mixed layer depths found in waters off the continental shelf, and that the interactive effects of iron and irradiance (that is, increased iron requirements in low irradiance environments) result in the limitation of phytoplankton biomass over large regions of the Southern Ocean.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1813447B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1813447B"><span>Observational uncertainty of Arctic sea-<span class="hlt">ice</span> <span class="hlt">concentration</span> significantly affects seasonal climate forecasts</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bunzel, Felix; Notz, Dirk; Baehr, Johanna; Müller, Wolfgang; Fröhlich, Kristina</p> <p>2016-04-01</p> <p>We examine how the choice of a particular satellite-retrieved sea-<span class="hlt">ice</span> <span class="hlt">concentration</span> dataset used for initialising seasonal climate forecasts impacts the prediction skill of Arctic sea-<span class="hlt">ice</span> area and Northern hemispheric 2-meter air temperatures. To do so, we performed two assimilation runs with the Max Planck Institute Earth System Model (MPI-ESM) from 1979 to 2012, where atmospheric and oceanic parameters as well as sea-<span class="hlt">ice</span> <span class="hlt">concentration</span> were assimilated using Newtonian relaxation. The two assimilation runs differ only in the sea-<span class="hlt">ice</span> <span class="hlt">concentration</span> dataset used for assimilating sea <span class="hlt">ice</span>. In the first run, we use sea-<span class="hlt">ice</span> <span class="hlt">concentrations</span> as derived by the NASA-Team algorithm, while in the second run we use sea-<span class="hlt">ice</span> <span class="hlt">concentrations</span> as derived from the Bootstrap algorithm. A major difference between these two sea-<span class="hlt">ice</span> <span class="hlt">concentration</span> data products involves the treatment of melt ponds. While for both products melt ponds appear as open water in the raw satellite data, the Bootstrap algorithm more strongly attempts to offset this systematic bias by synthetically increasing the retrieved <span class="hlt">ice</span> <span class="hlt">concentration</span> during summer months. For each year of the two assimilation runs we performed a 10-member ensemble of hindcast experiments starting on 1 May and 1 November with a hindcast length of 6 months. For hindcasts started in November, initial differences in Arctic sea-<span class="hlt">ice</span> area and surface temperature decrease rapidly throughout the freezing period. For hindcasts started in May, initial sea-<span class="hlt">ice</span> area differences increase over time. By the end of the melting period, this causes significant differences in 2-meter air temperature of regionally more than 3°C. Hindcast skill for surface temperatures over Europe and North America is higher with Bootstrap initialization during summer and with NASA Team initialisation during winter. This implies that the choice of the sea-<span class="hlt">ice</span> data product and, thus, the observational uncertainty also affects forecasts of teleconnections that depend on Northern</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014cosp...40E1409K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014cosp...40E1409K"><span>Evaluation of the operational SAR based Baltic sea <span class="hlt">ice</span> <span class="hlt">concentration</span> products</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Karvonen, Juha</p> <p></p> <p>Sea <span class="hlt">ice</span> <span class="hlt">concentration</span> is an important <span class="hlt">ice</span> parameter both for weather and climate modeling and sea <span class="hlt">ice</span> navigation. We have developed an fully automated algorithm for sea <span class="hlt">ice</span> <span class="hlt">concentration</span> retrieval using dual-polarized ScanSAR wide mode RADARSAT-2 data. RADARSAT-2 is a C-band SAR instrument enabling dual-polarized acquisition in ScanSAR mode. The swath width for the RADARSAT-2 ScanSAR mode is about 500 km, making it very suitable for operational sea <span class="hlt">ice</span> monitoring. The polarization combination used in our <span class="hlt">concentration</span> estimation is HH/HV. The SAR data is first preprocessed, the preprocessing consists of geo-rectification to Mercator projection, incidence angle correction fro both the polarization channels. and SAR mosaicking. After preprocessing a segmentation is performed for the SAR mosaics, and some single-channel and dual-channel features are computed for each SAR segment. Finally the SAR <span class="hlt">concentration</span> is estimated based on these segment-wise features. The algorithm is similar as introduced in Karvonen 2014. The <span class="hlt">ice</span> <span class="hlt">concentration</span> is computed daily using a daily RADARSAT-2 SAR mosaic as its input, and it thus gives the <span class="hlt">concentration</span> estimated at each Baltic Sea location based on the most recent SAR data at the location. The algorithm has been run in an operational test mode since January 2014. We present evaluation of the SAR-based <span class="hlt">concentration</span> estimates for the Baltic <span class="hlt">ice</span> season 2014 by comparing the SAR results with gridded the Finnish <span class="hlt">Ice</span> Service <span class="hlt">ice</span> charts and <span class="hlt">ice</span> <span class="hlt">concentration</span> estimates from a radiometer algorithm (AMSR-2 Bootstrap algorithm results). References: J. Karvonen, Baltic Sea <span class="hlt">Ice</span> <span class="hlt">Concentration</span> Estimation Based on C-Band Dual-Polarized SAR Data, IEEE Transactions on Geoscience and Remote Sensing, in press, DOI: 10.1109/TGRS.2013.2290331, 2014.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.A21E..01D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.A21E..01D"><span>Recent Field Measurements of <span class="hlt">Ice</span> Nuclei <span class="hlt">Concentration</span> Relation to Aerosol Properties</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>DeMott, P. J.; Sullivan, R. C.; McMeeking, G.; Prenni, A. J.; Hill, T. C.; Franc, G. D.; Sullivan, A. P.; Garcia, E.; Tobo, Y.; Prather, K. A.; Suski, K.; Cazorla, A.; Anderson, J. R.; Kreidenweis, S. M.</p> <p>2011-12-01</p> <p>It is expected that atmospheric variability of <span class="hlt">ice</span> nuclei <span class="hlt">concentrations</span> is governed by a variety of factors related to aerosol physical and chemical properties. Not all particles contribute equally due to the special nature of <span class="hlt">ice</span> nuclei. The "size requirement" of <span class="hlt">ice</span> nuclei (Pruppacher and Klett, 1997), partly related to the typical aerosol compositions known to act as <span class="hlt">ice</span> nuclei (e.g., mineral dust particles, certain biological particles), leads to the relation of <span class="hlt">ice</span> nuclei number <span class="hlt">concentrations</span> to larger aerosol <span class="hlt">concentrations</span> in some cases, but we emphasize here the additional relation to aerosol chemistry. Recent atmospheric <span class="hlt">ice</span> nuclei measurements focused on biomass burning, mineral dust, pollution and biological particles will be discussed to highlight new assessment of their source contributions on the basis of physical, chemical and biological analysis. Pruppacher, H. R., and J. D. Klett, 1997: Microphysics of Clouds and Precipitation (2nd Edition), Kluwer Academic Press, Dordrecht, 954 pp.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20010027899','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20010027899"><span>Studies of Antarctic Sea <span class="hlt">Ice</span> <span class="hlt">Concentrations</span> from Satellite Data and Their Applications</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Comiso, Josefino C.; Steffen, Konrad; Zukor, Dorothy J. (Technical Monitor)</p> <p>2001-01-01</p> <p>Large changes in the sea <span class="hlt">ice</span> cover have been observed recently. Because of the relevance of such changes to climate change studies it is important that key <span class="hlt">ice</span> <span class="hlt">concentration</span> data sets used for evaluating such changes are interpreted properly. High and medium resolution visible and infrared satellite data are used in conjunction with passive microwave data to study the true characteristics of the Antarctic sea <span class="hlt">ice</span> cover, assess errors in currently available <span class="hlt">ice</span> <span class="hlt">concentration</span> products, and evaluate the applications and limitations of the latter in polar process studies. Cloud-free high resolution data provide valuable information about the natural distribution, stage of formation, and composition of the <span class="hlt">ice</span> cover that enables interpretation of the large spatial and temporal variability of the microwave emissivity of Antarctic sea <span class="hlt">ice</span>. Comparative analyses of co-registered visible, infrared and microwave data were used to evaluate <span class="hlt">ice</span> <span class="hlt">concentrations</span> derived from standard <span class="hlt">ice</span> algorithms (i.e., Bootstrap and Team) and investigate the 10 to 35% difference in derived values from large areas within the <span class="hlt">ice</span> pack, especially in the Weddell Sea, Amundsen Sea, and Ross Sea regions. Landsat and OLS data show a predominance of thick consolidated <span class="hlt">ice</span> in these areas and show good agreement with the Bootstrap Algorithm. While direct measurements were not possible, the lower values from the Team Algorithm results are likely due to layering within the <span class="hlt">ice</span> and snow and/or surface flooding, which are known to affect the polarization ratio. In predominantly new <span class="hlt">ice</span> regions, the derived <span class="hlt">ice</span> <span class="hlt">concentration</span> from passive microwave data is usually lower than the true percentage because the emissivity of new <span class="hlt">ice</span> changes with age and thickness and is lower than that of thick <span class="hlt">ice</span>. However, the product provides a more realistic characterization of the sea <span class="hlt">ice</span> cover, and are more useful in polar process studies since it allows for the identification of areas of significant divergence and polynya</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014P%26SS...91...60F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014P%26SS...91...60F"><span>Amazonian mid- to high-latitude glaciation on Mars: Supply-limited <span class="hlt">ice</span> sources, <span class="hlt">ice</span> accumulation patterns, and <span class="hlt">concentric</span> crater fill glacial flow and <span class="hlt">ice</span> sequestration</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Fastook, James L.; Head, James W.</p> <p>2014-02-01</p> <p><span class="hlt">Concentric</span> crater fill (CCF) occurs in the interior of impact craters in mid- to high latitudes on Mars and is interpreted to have formed by glacial <span class="hlt">ice</span> flow and debris covering. We use the characteristics and orientation of deposits comprising CCF, the thickness of pedestal deposits in mid- to high-latitude pedestal craters (Pd), the volumes of the current polar caps, and information about regional slopes and <span class="hlt">ice</span> rheology to address questions about (1) the maximum thickness of regional <span class="hlt">ice</span> deposits during the Late Amazonian, (2) the likelihood that these deposits flowed regionally, (3) the geological regions and features most likely to induce <span class="hlt">ice</span>-flow, and (4) the locations and environments in which <span class="hlt">ice</span> is likely to have been sequestered up to the present. We find that regional <span class="hlt">ice</span> flow under Late Amazonian climate conditions requires <span class="hlt">ice</span> thicknesses exceeding many hundreds of meters for slopes typical of the vast majority of the surface of Mars, a thickness for the mid-latitudes that is well in excess of the total volume available from polar <span class="hlt">ice</span> reservoirs. This indicates that although conditions for mid- to high-latitude glaciation may have persisted for tens to hundreds of millions of years, the process is “supply limited”, with a steady state reached when the polar <span class="hlt">ice</span> cap water <span class="hlt">ice</span> supply becomes exhausted. Impact craters are by far the most abundant landform with associated slopes (interior wall and exterior rim) sufficiently high to induce glacial <span class="hlt">ice</span> flow under Late Amazonian climate conditions, and topographic slope data show that Amazonian impact craters have been clearly modified, undergoing crater interior slope reduction and floor shallowing. We show that these trends are the predictable response of <span class="hlt">ice</span> deposition and preferential accumulation and retention in mid- to high-latitude crater interiors during episodes of enhanced spin-axis obliquity. We demonstrate that flow from a single episode of an inter-crater terrain layer comparable to Pedestal</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li class="active"><span>7</span></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_7 --> <div id="page_8" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li class="active"><span>8</span></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="141"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=10539&hterms=sea+ice&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dsea%2Bice','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=10539&hterms=sea+ice&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dsea%2Bice"><span>Record Arctic Sea <span class="hlt">Ice</span> Loss in 2007</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p></p> <p>2007-01-01</p> <p>This image of the Arctic was produced from sea <span class="hlt">ice</span> observations collected by the Advanced Microwave Scanning Radiometer (<span class="hlt">AMSR-E</span>) Instrument on NASA's Aqua satellite on September 16, overlaid on the NASA Blue Marble. The image captures <span class="hlt">ice</span> conditions at the end of the melt season. Sea <span class="hlt">ice</span> (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 <span class="hlt">ice</span>-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 <span class="hlt">ice</span> remained in place north of the Russian coast. According to the National Snow and <span class="hlt">Ice</span> Data Center (NSIDC), on September 16, 2007, sea <span class="hlt">ice</span> extent dropped to 4.13 million square kilometers (1.59 million square miles)--38 percent below average and 24 percent below the 2005 record.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20030096002','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20030096002"><span>Sea <span class="hlt">Ice</span> Surface Temperature Product from the Moderate Resolution Imaging Spectroradiometer (MODIS)</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hall, Dorothy K.; Key, Jeffrey R.; Casey, Kimberly A.; Riggs, George A.; Cavalieri, Donald J.</p> <p>2003-01-01</p> <p>Global sea <span class="hlt">ice</span> products are produced from the Earth Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) on board both the Terra and Aqua satellites. Daily sea <span class="hlt">ice</span> extent and <span class="hlt">ice</span>-surface temperature (IST) products are available at 1- and 4-km resolution. Validation activities have been undertaken to assess the accuracy of the MODIS IST product at the South Pole station in Antarctica and in the Arctic Ocean using near-surface air-temperature data from a meteorological station and drifting buoys. Results from the study areas show that under clear skies, the MODIS ISTs are very close to those of the near-surface air temperatures with a bias of -1.1 and -1.2 K, and an uncertainty of 1.6 and 1.7 K, respectively. It is shown that the uncertainties would be reduced if the actual temperature of the <span class="hlt">ice</span> surface were reported instead of the near-surface air temperature. It is not possible to get an accurate IST from MODIS in the presence of even very thin clouds or fog, however using both the Advanced Microwave Scanning Radiometer-EOS (<span class="hlt">AMSR-E</span>) and the MODIS on the Aqua satellite, it may be possible to develop a relationship between MODIS-derived IST and <span class="hlt">ice</span> temperature derived from the <span class="hlt">AMSR-E</span>. Since the <span class="hlt">AMSR-E</span> measurements are generally unaffected by cloud cover, they may be used to complement the MODIS IST measurements.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28241114','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28241114"><span>A Novel Approach To Improve the Efficiency of Block Freeze <span class="hlt">Concentration</span> Using <span class="hlt">Ice</span> Nucleation Proteins with Altered <span class="hlt">Ice</span> Morphology.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Jin, Jue; Yurkow, Edward J; Adler, Derek; Lee, Tung-Ching</p> <p>2017-03-09</p> <p>Freeze <span class="hlt">concentration</span> is a separation process with high success in product quality. The remaining challenge is to achieve high efficiency with low cost. This study aims to evaluate the potential of using <span class="hlt">ice</span> nucleation proteins (INPs) as an effective method to improve the efficiency of block freeze <span class="hlt">concentration</span> while also exploring the related mechanism of <span class="hlt">ice</span> morphology. Our results show that INPs are able to significantly improve the efficiency of block freeze <span class="hlt">concentration</span> in a desalination model. Using this experimental system, we estimate that approximately 50% of the energy cost can be saved by the inclusion of INPs in desalination cycles while still meeting the EPA standard of drinking water (<500 ppm). Our investigative tools for <span class="hlt">ice</span> morphology include optical microscopy and X-ray computed tomography imaging analysis. Their use indicates that INPs promote the development of a lamellar structured <span class="hlt">ice</span> matrix with larger hydraulic diameters, which facilitates brine drainage and contains less brine entrapment as compared to control samples. These results suggest great potential for applying INPs to develop an energy-saving freeze <span class="hlt">concentration</span> method via the alteration of <span class="hlt">ice</span> morphology.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/scitech/biblio/1167648','SCIGOV-STC'); return false;" href="https://www.osti.gov/scitech/biblio/1167648"><span><span class="hlt">Ice</span> <span class="hlt">Concentration</span> Retrieval in Stratiform Mixed-phase Clouds Using Cloud Radar Reflectivity Measurements and 1D <span class="hlt">Ice</span> Growth Model Simulations</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Zhang, Damao; Wang, Zhien; Heymsfield, Andrew J.; Fan, Jiwen; Luo, Tao</p> <p>2014-10-01</p> <p>Measurement of <span class="hlt">ice</span> number <span class="hlt">concentration</span> in clouds is important but still challenging. Stratiform mixed-phase clouds (SMCs) provide a simple scenario for retrieving <span class="hlt">ice</span> number <span class="hlt">concentration</span> from remote sensing measurements. The simple <span class="hlt">ice</span> generation and growth pattern in SMCs offers opportunities to use cloud radar reflectivity (Ze) measurements and other cloud properties to infer <span class="hlt">ice</span> number <span class="hlt">concentration</span> quantitatively. To understand the strong temperature dependency of <span class="hlt">ice</span> habit and growth rate quantitatively, we develop a 1-D <span class="hlt">ice</span> growth model to calculate the <span class="hlt">ice</span> diffusional growth along its falling trajectory in SMCs. The radar reflectivity and fall velocity profiles of <span class="hlt">ice</span> crystals calculated from the 1-D <span class="hlt">ice</span> growth model are evaluated with the Atmospheric Radiation Measurements (ARM) Climate Research Facility (ACRF) ground-based high vertical resolution radar measurements. Combining Ze measurements and 1-D <span class="hlt">ice</span> growth model simulations, we develop a method to retrieve the <span class="hlt">ice</span> number <span class="hlt">concentrations</span> in SMCs at given cloud top temperature (CTT) and liquid water path (LWP). The retrieved <span class="hlt">ice</span> <span class="hlt">concentrations</span> in SMCs are evaluated with in situ measurements and with a three-dimensional cloud-resolving model simulation with a bin microphysical scheme. These comparisons show that the retrieved <span class="hlt">ice</span> number <span class="hlt">concentrations</span> are within an uncertainty of a factor of 2, statistically.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/16303165','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/16303165"><span>A method for determination of methyl chloride <span class="hlt">concentration</span> in air trapped in <span class="hlt">ice</span> cores.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Saito, Takuya; Yokouchi, Yoko; Aoki, Shuji; Nakazawa, Takakiyo; Fujii, Yoshiyuki; Watanabe, Okitsugu</p> <p>2006-05-01</p> <p>A method for measuring the <span class="hlt">concentration</span> of methyl chloride (CH3Cl) in air trapped in an <span class="hlt">ice</span> core was developed. The method combines the air extraction by milling the <span class="hlt">ice</span> core samples under vacuum and the analysis of the extracted air with a cryogenic preconcentration/gas chromatograph/mass spectrometry system. The method was applied to air from Antarctic <span class="hlt">ice</span> core samples estimated to have been formed in the pre-industrial and/or early industrial periods. The overall precision of the method deduced from duplicate <span class="hlt">ice</span> core analyses was estimated to be better than +/-20 pptv. The measured CH3Cl <span class="hlt">concentration</span> of 528+/-26 pptv was similar to the present-day <span class="hlt">concentration</span> in the remote atmosphere as well as the CH3Cl <span class="hlt">concentration</span> over the past 300 years obtained from Antarctic firn air and <span class="hlt">ice</span> core analyses.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://pubs.er.usgs.gov/publication/1013155','USGSPUBS'); return false;" href="http://pubs.er.usgs.gov/publication/1013155"><span>Seasonal comparisons of sea <span class="hlt">ice</span> <span class="hlt">concentration</span> estimates derived from SSM/I, OKEAN and RADARSAT data</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Belchansky, G.I.; Douglas, D.C.</p> <p>2002-01-01</p> <p>The SSM/I microwave satellite radiometer and its predecessor SMMR are primary sources of information for global sea-<span class="hlt">ice</span> and climate studies. However, comparisons of SSM/I, LANDSAT, AVHRR and ERS-1 SAR have shown substantial seasonal and regional differences in their estimates of sea <span class="hlt">ice</span> <span class="hlt">concentration</span>. To evaluate these differences, we compared SSM/I estimates of sea <span class="hlt">ice</span> coverage derived with the NASA Team and Bootstrap algorithms to estimates made using RADARSAT, and OKEAN-01 satellite sensor data. The study area included the Barents, Kara Sea, Laptev Sea, and adjacent parts of the Arctic Ocean, during October 1995 through October 1999. <span class="hlt">Ice</span> <span class="hlt">concentration</span> estimates from spatially and temporally near-coincident imagery were calculated using independent algorithms for each sensor type. The OKEAN algorithm implemented the satellite's two-channel active (radar) and passive microwave data in a linear mixture model based on the measured values of brightness temperature and radar backscatter. The RADARSAT algorithm utilized a segmentation approach of the measured radar backscatter, and the SSM/I <span class="hlt">ice</span> <span class="hlt">concentrations</span> were derived at National Snow and <span class="hlt">Ice</span> Data Center (NSIDC) using the NASA Team and Bootstrap algorithms. Seasonal and monthly differences between SSM/I, OKEAN, and RADARSAT <span class="hlt">ice</span> <span class="hlt">concentrations</span> were calculated and compared. Overall, total sea <span class="hlt">ice</span> <span class="hlt">concentration</span> estimates derived independently from near-coincident RADARSAT, OKEAN-01 and SSM/I satellite imagery demonstrated mean differences of less than 5.5 % (SD < 9.5%) during the winter period. Differences between the SSM/I NASA Team and the SSM/I Bootstrap <span class="hlt">concentrations</span> were no more than 3.1 % (SD < 5.4%) during this period. RADARSAT and OKEAN-01 data both yielded higher total <span class="hlt">ice</span> <span class="hlt">concentrations</span> than the NASA Team and the Bootstrap algorithms. The Bootstrap algorithm yielded higher total <span class="hlt">ice</span> <span class="hlt">concentrations</span> than the NASA Team algorithm. Total <span class="hlt">ice</span> <span class="hlt">concentrations</span> derived from OKEAN-01 and SSM/I satellite imagery were</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/AD1004224','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/AD1004224"><span>Improving Arctic Sea <span class="hlt">Ice</span> Edge Forecasts by Assimilating High Horizontal Resolution Sea <span class="hlt">Ice</span> <span class="hlt">Concentration</span> Data into the US Navy’s <span class="hlt">Ice</span> Forecast Systems</span></a></p> <p><a target="_blank" href="https://publicaccess.dtic.mil/psm/api/service/search/search">DTIC Science & Technology</a></p> <p></p> <p>2016-06-13</p> <p>error within the US Navy’s operational sea <span class="hlt">ice</span> forecast systems gained by assimilating high horizontal resolution satellite -derived <span class="hlt">ice</span> <span class="hlt">concentration</span>... Satellite Program (DMSP) Special Sensor Mi- crowave/Imager (SSMI and then SSMIS). The resolution of the satellite -derived product was approximately...effective execution of the US Navy’s daily operational missions (US Department of Navy, 2014). Since comprehensive records began with the satellite era</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27997388','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27997388"><span>Notable increases in nutrient <span class="hlt">concentrations</span> in a shallow lake during seasonal <span class="hlt">ice</span> growth.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Fang, Yang; Changyou, Li; Leppäranta, Matti; Xiaonghong, Shi; Shengnan, Zhao; Chengfu, Zhang</p> <p>2016-12-01</p> <p>Nutrients may be eliminated from <span class="hlt">ice</span> when liquid water is freezing, resulting in enhanced <span class="hlt">concentrations</span> in the unfrozen water. The nutrients diluted from the <span class="hlt">ice</span> may contribute to accumulated <span class="hlt">concentrations</span> in sediment during winter and an increased risk of algae blooms during the following spring and summer. The objective of this study was to evaluate the influence of <span class="hlt">ice</span> cover on nitrogen (N) and phosphorus (P) <span class="hlt">concentrations</span> in the water and sediment of a shallow lake, through an examination of Ulansuhai Lake, northern China, from the period of open water to <span class="hlt">ice</span> season in 2011-2013. The N and P <span class="hlt">concentrations</span> were between two and five times higher, and between two and eight times higher, than in unfrozen lakes, respectively. As the <span class="hlt">ice</span> thickness grew, contents of total N and total P showed C-shaped profiles in the <span class="hlt">ice</span>, and were lower in the middle layer and higher in the bottom and surface layers. Most of the nutrients were released from the <span class="hlt">ice</span> to liquid water. The results confirm that <span class="hlt">ice</span> can cause the nutrient <span class="hlt">concentrations</span> in water and sediment during winter to increase dramatically, thereby significantly impacting on processes in the water environment of shallow lakes.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2004AGUSM.C43A..20M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2004AGUSM.C43A..20M"><span>Snow and <span class="hlt">Ice</span> Products from the Aqua, Terra, and ICESat Satellites at the National Snow and <span class="hlt">Ice</span> Data Center</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Meier, W. N.; Marquis, M.; Kaminski, M.; Armstrong, R.; Brodzik, M.</p> <p>2004-05-01</p> <p>The National Snow and <span class="hlt">Ice</span> Data Center (NSIDC) at the University of Colorado, Boulder - one of eight NASA Distributed Active Archive Centers (DAACs) - archives and distributes several products from sensors on the suite of NASA Earth Observing System (EOS) satellites. These include the sun-synchronous polar-orbiting Aqua (launched 4 May 2002) and Terra (launched 18 December 1999) platforms and the <span class="hlt">Ice</span>, Cloud, and land Elevation Satellite (ICESat) (launched 12 January 2003). The Advanced Microwave Scanning Radiometer-EOS (<span class="hlt">AMSR-E</span>) is a multi-channel passive microwave radiometer on Aqua (http://nsidc.org/daac/amsr/). <span class="hlt">AMSR-E</span> Level 3 snow products are produced in EASE-Grid format for both the Northern and Southern Hemisphere and are available as daily, 5-day, and monthly fields. Daily <span class="hlt">AMSR-E</span> Level 3 sea <span class="hlt">ice</span> products are produced on a polar stereographic projection at gridded spatial resolutions of 6.25 km, 12.5 km and 25 km. Since April 2004, these products have been available for public distribution from NSIDC. The Moderate-resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua is a 36-channel visible/infrared sensor that produces a consistent long-term time series of fully-automated, quality-controlled data. Level 2 swath products are available for both snow cover and sea <span class="hlt">ice</span>. Daily and 8-day Level 3 gridded snow cover products are available with estimates of snow extent and albedo at 500m resolution, along with daily Level 3 gridded sea <span class="hlt">ice</span> products with estimates for sea <span class="hlt">ice</span> extent and <span class="hlt">ice</span> surface temperature at 1 km resolution. These products are currently available from NSIDC (http://nsidc.org/daac/modis/). The Geoscience Laser Altimeter System (GLAS) is the sole instrument on ICESat. The standard GLAS Level 2 <span class="hlt">ice</span> sheet altimetry product contains the <span class="hlt">ice</span> sheet elevation and elevation distribution calculated from algorithms fine-tuned for <span class="hlt">ice</span> sheet returns. The standard GLAS Level 2 sea <span class="hlt">ice</span> altimetry product contains the sea <span class="hlt">ice</span> freeboard and sea <span class="hlt">ice</span></p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20010095015&hterms=arctic+ice+melt&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Darctic%2Bice%2Bmelt','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20010095015&hterms=arctic+ice+melt&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Darctic%2Bice%2Bmelt"><span>Correlation Studies of Sea <span class="hlt">Ice</span> <span class="hlt">Concentration</span> with Surface Temperature and Meltponding</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Comiso, J. C.; Zukor, Dorothy J. (Technical Monitor)</p> <p>2001-01-01</p> <p>The spatial and temporal variability of sea <span class="hlt">ice</span> <span class="hlt">concentrations</span> derived from passive microwave data is studied in conjunction with co-registered high resolution infrared and visible satellite data. Cloud free infrared and visible data provide surface temperature and large scale surface characteristics, respectively, that can be used to better understand regional and seasonal fluctuations in <span class="hlt">ice</span> <span class="hlt">concentrations</span>. Results from correlation analysis of <span class="hlt">ice</span> <span class="hlt">concentration</span> versus surface temperature data show the intuitively expected negative relationship but the strength in the relationship is unexpectedly very strong. In the Antarctic, the correlation is consistently very high spatially when yearly anomalies are used, and not so high in some areas when seasonal anomalies are used, especially during spring and summer. In the monthly anomalies, the correlation is also good, especially in dynamically active regions. The expanse in the anomalies in surface temperature are shown to go way beyond the sea <span class="hlt">ice</span> regions into the open ocean and continental areas, suggesting strong atmospheric forcing. Weak correlations are normally found in highly consolidated areas, where large changes in temperature do not cause large changes in <span class="hlt">ice</span> <span class="hlt">concentration</span> on a short term, and in open ocean polynya areas, where the change in <span class="hlt">ice</span> <span class="hlt">concentration</span> may be cause by melt from the underside of the <span class="hlt">ice</span>. In the Arctic, strong correlations between surface temperature and <span class="hlt">ice</span> <span class="hlt">concentration</span> are evident for all seasons except during the summer. In the summer, factors such as meltponding, surface wetness, and <span class="hlt">ice</span> breakup, as detected by high resolution visible data, contributes to larger uncertainties in the determination of <span class="hlt">ice</span> <span class="hlt">concentration</span> and the lack of good correlation of the variables.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AdSpR..56..119K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AdSpR..56..119K"><span>Evaluation of the operational SAR based Baltic Sea <span class="hlt">ice</span> <span class="hlt">concentration</span> products</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Karvonen, Juha</p> <p>2015-07-01</p> <p>Sea <span class="hlt">ice</span> <span class="hlt">concentration</span> is an important <span class="hlt">ice</span> parameter both for weather and climate modeling and sea <span class="hlt">ice</span> navigation. We have developed an fully automated algorithm for sea <span class="hlt">ice</span> <span class="hlt">concentration</span> retrieval using dual-polarized ScanSAR wide mode RADARSAT-2 data. RADARSAT-2 is a C-band SAR (Synthetic Aperture Radar) instrument enabling dual-polarized acquisition in ScanSAR mode. The swath width for the RADARSAT-2 ScanSAR mode is about 500 km, making it very suitable for operational sea <span class="hlt">ice</span> monitoring. The polarization combination used in our <span class="hlt">concentration</span> estimation is HH/HV. The SAR data is first preprocessed; the preprocessing consists of geo-rectification to Mercator projection, incidence angle correction for both the polarization channels, and SAR mosaicking. After preprocessing a segmentation is performed for the SAR mosaics, and some features are computed for each SAR segment. Finally the SAR <span class="hlt">concentration</span> is estimated based on these segment-wise features. The algorithm is basically similar as introduced in Karvonen 2014. The <span class="hlt">ice</span> <span class="hlt">concentration</span> is computed daily using a daily RADARSAT-2 SAR mosaic as its input, and it thus gives the <span class="hlt">concentration</span> estimated at each grid cell (pixel) based on the most recent SAR data at the location. The algorithm has been run in an operational test mode since January 2014. We present evaluation of the SAR-based <span class="hlt">concentration</span> estimates for the Baltic <span class="hlt">ice</span> season 2014 by comparing the SAR results with gridded Finnish Meteorological Institute (FMI) <span class="hlt">ice</span> charts and <span class="hlt">ice</span> <span class="hlt">concentration</span> estimates from a radiometer algorithm.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A13B0322P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A13B0322P"><span>What Controls the Low <span class="hlt">Ice</span> Number <span class="hlt">Concentration</span> in the Upper Tropical Troposphere?</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Penner, J.; Zhou, C.; Lin, G.; Liu, X.; Wang, M.</p> <p>2015-12-01</p> <p>Cirrus clouds in the tropical tropopause play a key role in regulating the moisture entering the stratosphere through their dehydrating effect. Low <span class="hlt">ice</span> number <span class="hlt">concentrations</span> and high supersaturations were frequently were observed in these clouds. However, low <span class="hlt">ice</span> number <span class="hlt">concentrations</span> are inconsistent with cirrus cloud formation based on homogeneous freezing. Different mechanisms have been proposed to explain this discrepancy, including the inhibition of homogeneous freezing by pre-existing <span class="hlt">ice</span> crystals and/or glassy organic aerosol heterogeneous <span class="hlt">ice</span> nuclei (IN) and limiting the formation of <span class="hlt">ice</span> number from high frequency gravity waves. In this study, we examined the effect from three different parameterizations of in-cloud updraft velocities, the effect from pre-existing <span class="hlt">ice</span> crystals, the effect from different water vapor deposition coefficients (α=0.1 or 1), and the effect from 0.1% of secondary organic aerosol (SOA) acting as glassy heterogeneous <span class="hlt">ice</span> nuclei (IN) in CAM5. Model simulated <span class="hlt">ice</span> crystal numbers are compared against an aircraft observational dataset. Using grid resolved large-scale updraft velocity in the <span class="hlt">ice</span> nucleation parameterization generates <span class="hlt">ice</span> number <span class="hlt">concentrations</span> in better agreement with observations for temperatures below 205K while using updraft velocities based on the model-generated turbulence kinetic energy generates <span class="hlt">ice</span> number <span class="hlt">concentrations</span> in better agreement with observations for temperatures above 205K. A larger water vapor deposition coefficient (α=1) can efficiently reduce the <span class="hlt">ice</span> number at temperatures below 205K but less so at higher temperatures. Glassy SOA IN are most effective at reducing the <span class="hlt">ice</span> number <span class="hlt">concentrations</span> when the effective in-cloud updraft velocities are moderate (~0.05-0.2 m s-1). Including the removal of water vapor on pre-existing <span class="hlt">ice</span> can also effectively reduce the <span class="hlt">ice</span> number and diminish the effects from the additional glassy SOA heterogeneous IN. We also re-evaluate whether IN seeding in cirrus cloud is</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.A13A0203M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.A13A0203M"><span>Measurements of <span class="hlt">ice</span> nuclei <span class="hlt">concentrations</span> and compositions in the maritime tropics</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>McMeeking, G. R.; Danielczok, A.; Bingemer, H.; Klein, H.; Hill, T. C.; Franc, G. D.; Martinez, M.; Venero, I.; Mayol-Bracero, O. L.; Ardon-Dryer, K.; Levin, Z.; Anderson, J.; Twohy, C. H.; Toohey, D. W.; DeMott, P. J.</p> <p>2011-12-01</p> <p>Tropical maritime cumulus clouds represent an important component of the global water cycle, but the relative roles of primary and secondary <span class="hlt">ice</span> production in these clouds are poorly understood. Heterogeneous <span class="hlt">ice</span> nuclei (IN) are responsible for <span class="hlt">ice</span> initiation in towering tropical cumulus clouds, so information regarding their abundance, distribution, source compositions and dependence on cloud temperature is crucial to understanding the <span class="hlt">ice</span> production processes. Here we present recent measurements of <span class="hlt">ice</span> nuclei (IN) <span class="hlt">concentrations</span> measured from ground-based and airborne (NSF/NCAR C-130) platforms during the <span class="hlt">Ice</span> in Clouds-Tropical experiment, which took place in July 2011 over the Caribbean Sea near St. Croix in the US Virgin Islands. IN measurement techniques included airborne ambient and cloud particle residual measurements using a continuous flow diffusion chamber and off-line analysis of samples collected from the aircraft and two ground sites located on the island of Puerto Rico. Off-line measurements of IN <span class="hlt">concentrations</span> included analysis by the Frankfurt <span class="hlt">Ice</span> Nuclei Deposition FreezinG Experiment (FRIDGE) system and drop freezing via two methods of particles collected from filter samples. The measurement period included some periods with a strong Saharan dust influence that resulted in higher IN <span class="hlt">concentrations</span> compared to clean maritime conditions. First analysis of IN physical, chemical and biological composition, and investigation of relationships between IN <span class="hlt">concentrations</span> and total aerosol <span class="hlt">concentrations</span>, composition and size are also presented.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006AGUFM.C52A..01C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006AGUFM.C52A..01C"><span>Global Sea <span class="hlt">Ice</span> Charting at the National <span class="hlt">Ice</span> Center</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Clemente-Colon, P.</p> <p>2006-12-01</p> <p> Special Sensor Microwave/Imager (SSM/I) provide better temporal and synoptic view of the Polar Regions albeit at a significantly reduced spatial resolution compared to that of active sensors. Automated SSM/I algorithms provide for near-real time production of sea <span class="hlt">ice</span> parameters including <span class="hlt">concentration</span> and multiyear fraction. The retrieval of sea <span class="hlt">ice</span> drift vectors from passive microwave with SSM/I is operational and it is being also implemented using the Advanced Microwave Scanning Radiometer (<span class="hlt">AMSR-E</span>), a research instrument available aboard the Aqua satellite. As in the case of QuikSCAT, NIC is also exploring the use of sea <span class="hlt">ice</span> parameters retrieved from WindSat and the synergy of these observations with the WindSat wind vectors off the MIZ through a newly formed sea <span class="hlt">ice</span> algorithm working group.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..16...56A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..16...56A"><span>Global-scale evaluation of two satellite-based passive microwave soil moisture data sets (SMOS and <span class="hlt">AMSR-E</span>) with respect to modelled estimates</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Alyaari, Amen; Wigneron, Jean-Pierre; Ducharne, Agnes; Govind, Ajit; Kerr, Yann; Bitar, Ahmad Al; Jeu, Richard De.; Rosnay, Patricia; Albergel, Clement; Sabater, Joaquin; Moisy, Christophe</p> <p>2014-05-01</p> <p>Global Level-3 surface soil moisture (SSM) maps from the passive microwave Soil Moisture and Ocean Salinity satellite (SMOS)have been recently released. To further improve the Level-3 retrieval algorithm, evaluation of the accuracy of the spatio-temporal variability of the SMOS Level 3 products (referred to as SMOSL3) is necessary. In this study, a comparative analysis of SMOSL3 with a SSM product derived from the observations of the Advanced Microwave Scanning Radiometer (<span class="hlt">AMSR-E</span>) computed by implementing the Land Parameter Retrieval Model (LPRM) algorithm, referred to as AMSRM, is presented. The comparison of both products (SMOSL3 and AMSRM)was made against SSM products produced by a numerical weather prediction system (SM-DAS-2) at ECMWF (European Centre for Medium-Range Weather Forecasts) for the 03/2010-09/2011 period at the global scale. The latter product was considered here as a "reference" product for the inter-comparison of the SMOSL3 and AMSRM products. Three statistical criteria were used for the evaluation, the correlation coefficient (R), the root-mean-squared difference (RMSD), and the bias. Global maps of these criteria were averaged, taking into account vegetation information in terms of biome types and Leaf Area Index (LAI). We found that both the SMOSL3 and AMSRM products captured well the spatio-temporal variability of the SM-DAS-2 SSM products in most of the biomes. In general, the AMSRM products overestimated (i.e., wet bias) while the SMOSL3 products underestimated (i.e., dry bias) SSM in comparison to the SM-DAS-2 SSM products. In term of correlation values, the SMOSL3 products were found to better capture the SSM temporal dynamics in highly vegetated biomes ("Tropical humid", "Temperate Humid", etc.) Whereas best results for AMSRM were obtained over arid and semi-arid biomes ("Desert temperate", "Desert tropical", etc.). When removing the seasonal cycles in the SSM time variations to compute anomaly values, better correlation with the SM</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.5024A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.5024A"><span>European Marine Background <span class="hlt">Ice</span> Nucleating Particle <span class="hlt">concentrations</span> Measured at the Mace Head Station, Ireland.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Atkinson, James; Kanji, Zamin A.; Ovadnevaite, Jurgita; Ceburnis, Darius; O'Dowd, Colin</p> <p>2016-04-01</p> <p><span class="hlt">Ice</span> formation is an important process which controls cloud microphysical properties and can be critical in the creation of precipitation, therefore influencing the hydrological cycle and energy budget of the Earth. <span class="hlt">Ice</span> Nucleating Particles (INP) can greatly increase the temperature and rate of <span class="hlt">ice</span> formation, but the sources and geographical distributions of these particles is not well understood. Mace Head in Ireland is a coastal site on the north eastern edge of Europe with prevailing winds generally from the Atlantic Ocean with little continental influence. Observations of INP <span class="hlt">concentration</span> from August 2015 using the Horizontal <span class="hlt">Ice</span> Nucleation Chamber (HINC) at temperature of -30 C are presented. Correlations between the INP and meteorological conditions and aerosol compositions are made, as well as comparisons with commonly used INP <span class="hlt">concentration</span> parameterisations. Observed INP <span class="hlt">concentrations</span> are generally low, suggesting that oceanic sources in this region do not contribute significant numbers of INP to the global distribution.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28060386','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28060386"><span><span class="hlt">Concentrations</span> of a triplet excited state are enhanced in illuminated <span class="hlt">ice</span>.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Chen, Zeyuan; Anastasio, Cort</p> <p>2017-01-25</p> <p>Photochemical reactions influence the fates and lifetimes of organic compounds in snow and <span class="hlt">ice</span>, both through direct photoreactions and via photoproduced transient species such as hydroxyl radical (˙OH) and, perhaps, triplet excited states of organic compounds (i.e., triplets). While triplets can be important oxidants in atmospheric drops and surface waters, little is known of this class of oxidants in frozen samples. To investigate this, we examined the photoreaction of phenol with the triplet state of 3,4-dimethoxybenzaldehyde ((3)DMB*), a product from biomass combustion, in illuminated laboratory <span class="hlt">ices</span>. Our results show that the rate of phenol loss due to (3)DMB* is, on average, increased by a factor of 95 ± 50 in <span class="hlt">ice</span> compared to the equivalent liquid sample. We find that this experimentally measured freeze <span class="hlt">concentration</span> factor, FEXP, is independent of total solute <span class="hlt">concentration</span> and temperature, in contrast to what is expected from a liquid-like region whose composition follows freezing point depression. We also find that FEXP for triplets is independent of pH, although the rates of phenol loss increase with decreasing pH in both solution and <span class="hlt">ice</span>. The enhancement in the rate of phenol loss in/on <span class="hlt">ice</span> indicates that <span class="hlt">concentrations</span> of triplet excited states are enhanced in <span class="hlt">ice</span> relative to solution and suggests that this class of oxidants might be a significant sink for organics in snow and <span class="hlt">ice</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20040031526&hterms=Antarctic+climate&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3DAntarctic%2Bclimate','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20040031526&hterms=Antarctic+climate&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3DAntarctic%2Bclimate"><span>Using Satellite-derived <span class="hlt">Ice</span> <span class="hlt">Concentration</span> to Represent Antarctic Coastal Polynyas in Ocean Climate Models</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Stoessel, Achim; Markus, Thorsten</p> <p>2003-01-01</p> <p>The focus of this paper is on the representation of Antarctic coastal polynyas in global <span class="hlt">ice</span>-ocean general circulation models (OGCMs), in particular their local, regional, and high-frequency behavior. This is verified with the aid of daily <span class="hlt">ice</span> <span class="hlt">concentration</span> derived from satellite passive microwave data using the NASATeam 2 (NT2) and the bootstrap (BS) algorithms. Large systematic regional and temporal discrepancies arise, some of which are related to the type of convection parameterization used in the model. An attempt is made to improve the fresh-water flux associated with melting and freezing in Antarctic coastal polynyas by ingesting (assimilating) satellite <span class="hlt">ice</span> <span class="hlt">concentration</span> where it comes to determining the thermodynamics of the open-water fraction of a model grid cell. Since the NT2 coastal open-water fraction (polynyas) tends to be less extensive than the simulated one in the decisive season and region, assimilating NT2 coastal <span class="hlt">ice</span> <span class="hlt">concentration</span> yields overall reduced net freezing rates, smaller formation rates of Antarctic Bottom Water, and a stronger southward flow of North Atlantic Deep Water across 30 S. Enhanced net freezing rates occur regionally when NT2 coastal <span class="hlt">ice</span> <span class="hlt">concentration</span> is assimilated, concomitant with a more realistic <span class="hlt">ice</span> thickness distribution and accumulation of High-Salinity Shelf Water. Assimilating BS rather than NT2 coastal <span class="hlt">ice</span> <span class="hlt">concentration</span>, the differences to the non-assimilated simulation are generally smaller and of opposite sign. This suggests that the model reproduces coastal <span class="hlt">ice</span> <span class="hlt">concentration</span> in closer agreement with the BS data than with the NT2 data, while more realistic features emerge when NT2 data are assimilated.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016DSRII.131..160C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016DSRII.131..160C"><span>Effect of elevated CO2 <span class="hlt">concentration</span> on microalgal communities in Antarctic pack <span class="hlt">ice</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Coad, Thomas; McMinn, Andrew; Nomura, Daiki; Martin, Andrew</p> <p>2016-09-01</p> <p>Increased anthropogenic CO2 emissions are causing changes to oceanic pH and CO2 <span class="hlt">concentrations</span> that will impact many marine organisms, including microalgae. Phytoplankton taxa have shown mixed responses to these changes with some doing well while others have been adversely affected. Here, the photosynthetic response of sea-<span class="hlt">ice</span> algal communities from Antarctic pack <span class="hlt">ice</span> (brine and infiltration microbial communities) to a range of CO2 <span class="hlt">concentrations</span> (400 ppm to 11,000 ppm in brine algae experiments, 400 ppm to 20,000 ppm in the infiltration <span class="hlt">ice</span> algae experiment) was investigated. Incubations were conducted as part of the Sea-<span class="hlt">Ice</span> Physics and Ecosystem Experiment II (SIPEX-2) voyage, in the austral spring (September-November), 2012. In the brine incubations, maximum quantum yield (Fv/Fm) and relative electron transfer rate (rETRmax) were highest at ambient and 0.049% (experiment 1) and 0.19% (experiment 2) CO2 <span class="hlt">concentrations</span>, although, Fv/Fm was consistently between 0.53±0.10-0.68±0.01 across all treatments in both experiments. Highest rETRmax was exhibited by brine cultures exposed to ambient CO2 <span class="hlt">concentrations</span> (60.15). In a third experiment infiltration <span class="hlt">ice</span> algal communities were allowed to melt into seawater modified to simulate the changed pH and CO2 <span class="hlt">concentrations</span> of future springtime <span class="hlt">ice</span>-edge conditions. Ambient and 0.1% CO2 treatments had the highest growth rates and Fv/Fm values but only the highest CO2 <span class="hlt">concentration</span> produced a significantly lower rETRmax. These experiments, conducted on natural Antarctic sea-<span class="hlt">ice</span> algal communities, indicate a strong level of tolerance to elevated CO2 <span class="hlt">concentrations</span> and suggest that these communities might not be adversely affected by predicted changes in CO2 <span class="hlt">concentration</span> over the next century.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.C11B0359R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.C11B0359R"><span>Arctic Sea <span class="hlt">Ice</span> Extent and <span class="hlt">Concentrations</span> are Overpredicted by a Regional Coupled Ocean - Sea <span class="hlt">Ice</span> Model as Compared to Satellite Data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Reddy, T.</p> <p>2014-12-01</p> <p>It is well known that the environment of the Arctic Ocean is currently changing rapidly as a result of anthropogenic inputs of greenhouse gases into the atmosphere. The loss of sea <span class="hlt">ice</span> is one of the most dramatic and impactful aspects of change. Warming is amplified due to the open water albedo feedback effect. <span class="hlt">Ice</span> is more reflective than ocean, creating a positive feedback with negative consequences. Here I compare our knowledge of sea <span class="hlt">ice</span> in the Arctic Ocean using data from two satellites (SSM/I "NASA-team" and "Bootstrap" algorithms and MODIS MOD29 sea <span class="hlt">ice</span> extent) to a coupled numerical model of ocean circulation and sea <span class="hlt">ice</span> (Regional Ocean Modeling System, ROMS). I run the model from 1987 through 2012. Most years, the summer <span class="hlt">ice</span> extent near Greenland and Norway is fairly well simulated, but in the Alaskan and Canadian Region, satellite data show <span class="hlt">ice</span> retreating dramatically from the coast, well into the Arctic basin. This retreat is not captured in the model. During the sea <span class="hlt">ice</span> minima in September, <span class="hlt">ice</span> extent from satellite data is approximately 72% of modeled <span class="hlt">ice</span> extent (for a ten-year average from 2003 - 2012). I focus on extent, <span class="hlt">concentrations</span>, and thicknesses, three of the main <span class="hlt">ice</span> characteristics described in ROMS. The results of this model vs. satellite data comparison show that the model simulates the presence of much more <span class="hlt">ice</span>, both a larger extent and higher <span class="hlt">concentrations</span>. This overestimation of <span class="hlt">ice</span> is common among many of the models presented in the literature. Changes in <span class="hlt">ice</span> thicknesses are a major concern as multi-year <span class="hlt">ice</span> is being lost at an accelerating pace. <span class="hlt">Ice</span> thickness is a good proxy for <span class="hlt">ice</span> age, and young <span class="hlt">ice</span> is much more susceptible to melting than older <span class="hlt">ice</span>. Many polar ocean models specify <span class="hlt">ice</span> <span class="hlt">concentrations</span> and thicknesses instead of modeling them. This is problematic at present due to limited data available for <span class="hlt">ice</span> thickness. For this reason, it is key to develop models like ROMS in order to improve understanding of the Arctic ocean - <span class="hlt">ice</span></p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li class="active"><span>8</span></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_8 --> <div id="page_9" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li class="active"><span>9</span></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="161"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/scitech/biblio/508187','SCIGOV-STC'); return false;" href="https://www.osti.gov/scitech/biblio/508187"><span>Changes in Arctic sea <span class="hlt">ice</span> <span class="hlt">concentration</span>, 1988 to 1994, as detected using image trend analysis</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Derksen, C.; Piwowar, J.; Sokol, J.; LeDrew, E.</p> <p>1997-08-01</p> <p>Arctic sea <span class="hlt">ice</span> may prove to be an early indicator of global climatic change because of its high sensitivity to overlying air temperature and the predicted amplified response of the polar regions to a changing climate. Long term investigations into temporal change in variables such as Arctic sea <span class="hlt">ice</span> <span class="hlt">concentration</span> will prove to be even more significant as the accumulation of passive microwave remote sensing data continues. Hypertemporal image analysis techniques, of which image trend analysis is just one, provide methods for investigating spatial and temporal data trends through long image sequences. This study utilizes a Special Sensor Microwave/Imager dataset of monthly mean and anomaly sea <span class="hlt">ice</span> <span class="hlt">concentrations</span> to investigate changes in Arctic sea <span class="hlt">ice</span> cover over seven years. The construction of a three dimensional hypertemporal image cube of the monthly data allows trends in <span class="hlt">ice</span> <span class="hlt">concentration</span> to be isolated through a linear regression analysis of all image pixels through the time series. The slope of the trend line for each pixel is assigned to a new image to show areas of negative and positive change through time. Use of monthly anomaly data deseasonalizes and removes autocorrelation from the mean monthly averages. The interpretation of results at a regional scale with no artificial boundaries applied highlights the spatial distribution of temporal trends in <span class="hlt">ice</span> <span class="hlt">concentration</span> within the natural climate system.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AdWR...98..122C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AdWR...98..122C"><span>Using machine learning to produce near surface soil moisture estimates from deeper in situ records at U.S. Climate Reference Network (USCRN) locations: Analysis and applications to <span class="hlt">AMSR-E</span> satellite validation</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Coopersmith, Evan J.; Cosh, Michael H.; Bell, Jesse E.; Boyles, Ryan</p> <p>2016-12-01</p> <p>Surface soil moisture is a critical parameter for understanding the energy flux at the land atmosphere boundary. Weather modeling, climate prediction, and remote sensing validation are some of the applications for surface soil moisture information. The most common in situ measurement for these purposes are sensors that are installed at depths of approximately 5 cm. There are however, sensor technologies and network designs that do not provide an estimate at this depth. If soil moisture estimates at deeper depths could be extrapolated to the near surface, in situ networks providing estimates at other depths would see their values enhanced. Soil moisture sensors from the U.S. Climate Reference Network (USCRN) were used to generate models of 5 cm soil moisture, with 10 cm soil moisture measurements and antecedent precipitation as inputs, via machine learning techniques. Validation was conducted with the available, in situ, 5 cm resources. It was shown that a 5 cm estimate, which was extrapolated from a 10 cm sensor and antecedent local precipitation, produced a root-mean-squared-error (RMSE) of 0.0215 m3/m3. Next, these machine-learning-generated 5 cm estimates were also compared to <span class="hlt">AMSR-E</span> estimates at these locations. These results were then compared with the performance of the actual in situ readings against the <span class="hlt">AMSR-E</span> data. The machine learning estimates at 5 cm produced an RMSE of approximately 0.03 m3/m3 when an optimized gain and offset were applied. This is necessary considering the performance of <span class="hlt">AMSR-E</span> in locations characterized by high vegetation water contents, which are present across North Carolina. Lastly, the application of this extrapolation technique is applied to the ECONet in North Carolina, which provides a 10 cm depth measurement as its shallowest soil moisture estimate. A raw RMSE of 0.028 m3/m3 was achieved, and with a linear gain and offset applied at each ECONet site, an RMSE of 0.013 m3/m3 was possible.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.8635M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.8635M"><span>Influence of Arctic sea-<span class="hlt">ice</span> and greenhouse gas <span class="hlt">concentration</span> change on the West African Monsoon.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Monerie, Paul-Arthur; Oudar, Thomas; Sanchez-Gomez, Emilia; Terray, Laurent</p> <p>2016-04-01</p> <p>The Sahelian precipitation are projected to increase in the CNRM-CM5 coupled climate model due to a strengthening of the land-Sea temperature gradient, the increase in the North Atlantic temperature and the deepening of the Heat Low. Arctic Sea-<span class="hlt">Ice</span> loss impacts the low-level atmospheric circulation through a decrease in the northward heat transport. Some authors have linked the sea-<span class="hlt">ice</span> loss to a poleward shift of the InterTropical Convergence Zone. Within the CMIP5 models the effect of these mechanisms are not distinguishable and it is difficult to understand the effect of the Arctic sea-<span class="hlt">ice</span> loss on the West African Monsoon so far. We performed several sensitivity experiments with the CNRM-CM5 coupled climate models by modifying the arctic sea-<span class="hlt">ice</span> extent and/or the greenhouse gas <span class="hlt">concentration</span>. We then investigated separately the impact of Arctic sea-<span class="hlt">ice</span> loss and greenhouse gas <span class="hlt">concentration</span> increases on the West African Monsoon. The increase in greenhouse gas explains the northward shift and the strengthening of the monsoon. Its effect is stronger with a sea-<span class="hlt">ice</span> free Arctic that leads to an increase in North Atlantic temperature and in Sahelian precipitation at the end of the rainy season (September-October). We argue that the decrease in sea-<span class="hlt">ice</span> extent, in the context of the global warming, may moistens the Sahel during the rainy season by changing the pressure, winds and moisture fluxes at low-level.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20090035004&hterms=cirrus+clouds&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dcirrus%2Bclouds','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20090035004&hterms=cirrus+clouds&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dcirrus%2Bclouds"><span>Understanding <span class="hlt">Ice</span> Supersaturation, Particle Growth, and Number <span class="hlt">Concentration</span> in Cirrus Clouds</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Comstock, Jennifer M.; Lin, Ruei-Fong; Starr, David O'C.; Yang, Ping</p> <p>2008-01-01</p> <p>Many factors control the <span class="hlt">ice</span> supersaturation and microphysical properties in cirrus clouds. We explore the effects of dynamic forcing, <span class="hlt">ice</span> nucleation mechanisms, and <span class="hlt">ice</span> crystal growth rate on the evolution and distribution of water vapor and cloud properties in nighttime cirrus clouds using a one-dimensional cloud model with bin microphysics and remote sensing measurements obtained at the Department of Energy's Atmospheric Radiation Measurement (ARM) Climate Research Facility located near Lamont, OK. We forced the model using both large-scale vertical ascent and, for the first time, mean mesoscale velocity derived from radar Doppler velocity measurements. Both heterogeneous and homogeneous nucleation processes are explored, where a classical theory heterogeneous scheme is compared with empirical representations. We evaluated model simulations by examining both bulk cloud properties and distributions of measured radar reflectivity, lidar extinction, and water vapor profiles, as well as retrieved cloud microphysical properties. Our results suggest that mesoscale variability is the primary mechanism needed to reproduce observed quantities. Model sensitivity to the <span class="hlt">ice</span> growth rate is also investigated. The most realistic simulations as compared with observations are forced using mesoscale waves, include fast <span class="hlt">ice</span> crystal growth, and initiate <span class="hlt">ice</span> by either homogeneous or heterogeneous nucleation. Simulated <span class="hlt">ice</span> crystal number <span class="hlt">concentrations</span> (tens to hundreds particles per liter) are typically two orders of magnitude smaller than previously published results based on aircraft measurements in cirrus clouds, although higher <span class="hlt">concentrations</span> are possible in isolated pockets within the nucleation zone.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016SPIE.9999E..0TS','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016SPIE.9999E..0TS"><span>Analysis on long-term variability of sea <span class="hlt">ice</span> albedo and its relationship with sea <span class="hlt">ice</span> <span class="hlt">concentration</span> over Antarctica</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Seo, Minji; Kim, Hyun-cheol; Seong, Noh-hun; Kwon, Chaeyoung; Kim, Honghee; Han, Kyung-Soo</p> <p>2016-10-01</p> <p>Sea <span class="hlt">ice</span> is an important factor for understanding Antarctic climate change. Especially, annual change of sea <span class="hlt">ice</span> shows different trend in Antarctica and Arctic. This different variation need to continuously observe the Polar Regions. Sea <span class="hlt">Ice</span> Albedo (SIA) and Sea <span class="hlt">Ice</span> <span class="hlt">Concentration</span> (SIC) are an indicator of variation on sea <span class="hlt">ice</span>. In addition, albedo is key parameter to understand the energy budget in Antarctica. This being so, it is important to analyze long-term variation of the two factors for observing of change of Antarctic environment. In this study, we analyzed long-term variability of SIC and SIA to understand the changes of sea <span class="hlt">ice</span> over Antarctic and researched the relationship with two factors. We used the SIA data at The Satellite Application Facility on Climate Monitoring (CM SAF) and the SIC data provided by Ocean and Sea <span class="hlt">Ice</span> Satellite Application Facility (OSI-SAF) from 1982 to 2009. The study period was selected to Antarctic summer season due to polar nights. We divided study periods into two terms, Nov-Dec(ND) and Jan-Feb(JF) in order to reflect the characteristics of sea <span class="hlt">ice</span> area, which minimum extend occurred in September and maximum extend occurred in February. We analyzed the correlation between SIA and SIC. As a results, two variables have a strong positive correlation (each correlation coefficients are 0.91 in Nov-Dec and 0.90 in Jan-Feb). We performed time series analysis using linear regression to understand the spatial and temporal tendency of SIA and SIC. As a results, SIA and SIC have a same spatial trend such as Weddle sea and Ross sea sections show the positive trend and Bellingshausen Amundsen sea shows the negative trend of two factors. Moreover, annual SIA change rate is 0.26% 0.04% yr-1 over section where represent positive trend during two study periods. And annual SIA change rate is - 0.14 - 0.25 % yr-1 of in the other part where represent negative trend during two study periods.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016Sci...353.1427S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016Sci...353.1427S"><span>A Pleistocene <span class="hlt">ice</span> core record of atmospheric O2 <span class="hlt">concentrations</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Stolper, D. A.; Bender, M. L.; Dreyfus, G. B.; Yan, Y.; Higgins, J. A.</p> <p>2016-09-01</p> <p>The history of atmospheric O2 partial pressures (PO2) is inextricably linked to the coevolution of life and Earth’s biogeochemical cycles. Reconstructions of past PO2 rely on models and proxies but often markedly disagree. We present a record of PO2 reconstructed using O2/N2 ratios from ancient air trapped in <span class="hlt">ice</span>. This record indicates that PO2 declined by 7 per mil (0.7%) over the past 800,000 years, requiring that O2 sinks were ~2% larger than sources. This decline is consistent with changes in burial and weathering fluxes of organic carbon and pyrite driven by either Neogene cooling or increasing Pleistocene erosion rates. The 800,000-year record of steady average carbon dioxide partial pressures (PCO2) but declining PO2 provides distinctive evidence that a silicate weathering feedback stabilizes PCO2 on million-year time scales.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015OcMod..93...22B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015OcMod..93...22B"><span>Assimilation of sea surface temperature, sea <span class="hlt">ice</span> <span class="hlt">concentration</span> and sea <span class="hlt">ice</span> drift in a model of the Southern Ocean</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Barth, Alexander; Canter, Martin; Van Schaeybroeck, Bert; Vannitsem, Stéphane; Massonnet, François; Zunz, Violette; Mathiot, Pierre; Alvera-Azcárate, Aida; Beckers, Jean-Marie</p> <p>2015-09-01</p> <p>Current ocean models have relatively large errors and biases in the Southern Ocean. The aim of this study is to provide a reanalysis from 1985 to 2006 assimilating sea surface temperature, sea <span class="hlt">ice</span> <span class="hlt">concentration</span> and sea <span class="hlt">ice</span> drift. In the following it is also shown how surface winds in the Southern Ocean can be improved using sea <span class="hlt">ice</span> drift estimated from infrared radiometers. Such satellite observations are available since the late seventies and have the potential to improve the wind forcing before more direct measurements of winds over the ocean are available using scatterometry in the late nineties. The model results are compared to the assimilated data and to independent measurements (the World Ocean Database 2009 and the mean dynamic topography based on observations). The overall improvement of the assimilation is quantified, in particular the impact of the assimilation on the representation of the polar front is discussed. Finally a method to identify model errors in the Antarctic sea <span class="hlt">ice</span> area is proposed based on Model Output Statistics techniques using a series of potential predictors. This approach provides new directions for model improvements.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..17.5746B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..17.5746B"><span>Assimilation of sea surface temperature, sea <span class="hlt">ice</span> <span class="hlt">concentration</span> and sea <span class="hlt">ice</span> drift in a model of the Southern Ocean</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Barth, Alexander; Canter, Martin; Van Schaeybroeck, Bert; Vannitsem, Stéphane; Massonnet, François; Zunz, Violette; Mathiot, Pierre; Alvera-Azcárate, Aida; Beckers, Jean-Marie</p> <p>2015-04-01</p> <p>Current ocean models have relatively large errors and biases in the Southern Ocean. The aim of this study is to provide a reanalysis from 1985 to 2006 assimilating sea surface temperature, sea <span class="hlt">ice</span> <span class="hlt">concentration</span> and sea <span class="hlt">ice</span> drift. In the following it is also shown how surface winds in the Southern Ocean can be improved using sea <span class="hlt">ice</span> drift estimated from infrared radiometers. Such satellite observations are available since the late seventies and have the potential to improve the wind forcing before more direct measurements of winds over the ocean are available using scatterometry in the late nineties. The model results are compared to the assimilated data and to independent measurements (the World Ocean Database 2009 and the mean dynamic topography based on observations). The overall improvement of the assimilation is quantified, in particular the impact of the assimilation on the representation of the polar front is discussed. Finally a method to identify model errors in the Antarctic sea <span class="hlt">ice</span> area is proposed based on Model Output Statistics techniques using a series of potential predictors. This approach provides new directions for model improvements.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20020054184&hterms=Ice+Age&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3DIce%2BAge','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20020054184&hterms=Ice+Age&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3DIce%2BAge"><span><span class="hlt">Concentrating</span> Antarctic Meteorites on Blue <span class="hlt">ice</span> Fields: The Frontier Mountain Meteorite Trap</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Sandford, Scott A.; DeVincenzi, D. (Technical Monitor)</p> <p>2002-01-01</p> <p>The collection of meteorites in Antarctica has greatly stimulated advancement in the field of meteoritics by providing the community with significant numbers of rare and unique meteorites types and by yielding large numbers of meteorites that sample older infall epochs (Grady et al., 1998). The majority of Antarctic meteorites are found on blue <span class="hlt">ice</span> fields, where they are thought to be <span class="hlt">concentrated</span> by wind and glacial drift (cf. Cassidy et al., 1992). The basic "<span class="hlt">ice</span> flow model" describes the <span class="hlt">concentration</span> of meteorites by the stagnation or slowing of <span class="hlt">ice</span> as it moves against a barrier located in a zone with low snow accumulation. However, our limited knowledge of the details of the actual <span class="hlt">concentration</span> mechanisms prevents establishing firm conclusions concerning the past meteorite flux from the Antarctic record (Zolensky, 1998). The terrestrial ages of Antarctic meteorites indicate that their <span class="hlt">concentration</span> occurs on time scales of tens to hundreds of thousands of years (Nishiizumi et al., 1989). It is a challenge to measure a mechanism that operates so slowly, and since such time scales can span more than one glacial epoch one cannot assume that the snow accumulation rates, <span class="hlt">ice</span> velocities and directions, etc. that are measured today are representative of those extant over the age of the trap. Testing the basic "<span class="hlt">ice</span> flow model" therefore requires the careful measurement of meteorite locations, glacialogical <span class="hlt">ice</span> flow data, <span class="hlt">ice</span> thicknesses, bedrock and surface topology, <span class="hlt">ice</span> ablation and snow accumulation rates, and mass transport by wind over an extended period of time in a location where these quantities can be interpreted in the context of past glacialogical history.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1814425F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1814425F"><span>Comparing modelled and measured <span class="hlt">ice</span> crystal <span class="hlt">concentrations</span> in orographic clouds during the INUPIAQ campaign</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Farrington, Robert; Connolly, Paul J.; Lloyd, Gary; Bower, Keith N.; Flynn, Michael J.; Gallagher, Martin W.; Field, Paul R.; Dearden, Chris; Choularton, Thomas W.; Hoyle, Chris</p> <p>2016-04-01</p> <p>At temperatures between -35°C and 0°C, the presence of insoluble aerosols acting as <span class="hlt">ice</span> nuclei (IN) is the only way in which <span class="hlt">ice</span> can nucleate under atmospheric conditions. Previous field and laboratory campaigns have suggested that mineral dust present in the atmosphere act as IN at temperatures warmer than -35°C (e.g. Sassen et al. 2003); however, the cause of <span class="hlt">ice</span> nucleation at temperatures greater than -10°C is less certain. In-situ measurements of aerosol properties and cloud micro-physical processes are required to drive the improvement of aerosol-cloud processes in numerical models. As part of the <span class="hlt">Ice</span> NUcleation Process Investigation and Quantification (INUPIAQ) project, two field campaigns were conducted in the winters of 2013 and 2014 (Lloyd et al. 2014). Both campaigns included measurements of cloud micro-physical properties at the summit of Jungfraujoch in Switzerland (3580m asl), using cloud probes, including the Two-Dimensional Stereo Hydrometeor Spectrometer (2D-S), the Cloud Particle Imager 3V (CPI-3V) and the Cloud Aerosol Spectrometer with Depolarization (CAS-DPOL). The first two of these probes measured significantly higher <span class="hlt">ice</span> number <span class="hlt">concentrations</span> than those observed in clouds at similar altitudes from aircraft. In this contribution, we assess the source of the high <span class="hlt">ice</span> number <span class="hlt">concentrations</span> observed by comparing in-situ measurements at Jungfraujoch with WRF simulations applied to the region around Jungfraujoch. During the 2014 field campaign the model simulations regularly simulated <span class="hlt">ice</span> particle <span class="hlt">concentrations</span> that were 3 orders of magnitude per litre less than the observed <span class="hlt">ice</span> number <span class="hlt">concentration</span>, even taking into account the aerosol properties measured upwind. WRF was used to investigate a number of potential sources of the high <span class="hlt">ice</span> crystal <span class="hlt">concentrations</span>, including: an increased <span class="hlt">ice</span> nucleating particle (INP) <span class="hlt">concentration</span>, secondary <span class="hlt">ice</span> multiplication and the advection of surface <span class="hlt">ice</span> or snow crystals into the clouds. It was found that the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://pubs.er.usgs.gov/publication/70024509','USGSPUBS'); return false;" href="http://pubs.er.usgs.gov/publication/70024509"><span>Seasonal comparisons of sea <span class="hlt">ice</span> <span class="hlt">concentration</span> estimates derived from SSM/I, OKEAN, and RADARSAT data</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Belchansky, G.I.; Douglas, D.C.</p> <p>2002-01-01</p> <p>The Special Sensor Microwave Imager (SSM/I) microwave satellite radiometer and its predecessor SMMR are primary sources of information for global sea <span class="hlt">ice</span> and climate studies. However, comparisons of SSM/I, Landsat, AVHRR, and ERS-1 synthetic aperture radar (SAR) have shown substantial seasonal and regional differences in their estimates of sea <span class="hlt">ice</span> <span class="hlt">concentration</span>. To evaluate these differences, we compared SSM/I estimates of sea <span class="hlt">ice</span> coverage derived with the NASA Team and Bootstrap algorithms to estimates made using RADARSAT, and OKEAN-01 satellite sensor data. The study area included the Barents Sea, Kara Sea, Laptev Sea, and adjacent parts of the Arctic Ocean, during October 1995 through October 1999. <span class="hlt">Ice</span> <span class="hlt">concentration</span> estimates from spatially and temporally near-coincident imagery were calculated using independent algorithms for each sensor type. The OKEAN algorithm implemented the satellite's two-channel active (radar) and passive microwave data in a linear mixture model based on the measured values of brightness temperature and radar backscatter. The RADARSAT algorithm utilized a segmentation approach of the measured radar backscatter, and the SSM/I <span class="hlt">ice</span> <span class="hlt">concentrations</span> were derived at National Snow and <span class="hlt">Ice</span> Data Center (NSIDC) using the NASA Team and Bootstrap algorithms. Seasonal and monthly differences between SSM/I, OKEAN, and RADARSAT <span class="hlt">ice</span> <span class="hlt">concentrations</span> were calculated and compared. Overall, total sea <span class="hlt">ice</span> <span class="hlt">concentration</span> estimates derived independently from near-coincident RADARSAT, OKEAN-01, and SSM/I satellite imagery demonstrated mean differences of less than 5.5% (S.D. <9.5%) during the winter period. Differences between the SSM/I NASA Team and the SSM/I Bootstrap <span class="hlt">concentrations</span> were no more than 3.1% (S.D. <5.4%) during this period. RADARSAT and OKEAN-01 data both yielded higher total <span class="hlt">ice</span> <span class="hlt">concentrations</span> than the NASA Team and the Bootstrap algorithms. The Bootstrap algorithm yielded higher total <span class="hlt">ice</span> <span class="hlt">concentrations</span> than the NASA Team algorithm. Total <span class="hlt">ice</span></p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016TCry...10..761Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016TCry...10..761Y"><span>Brief communication: The challenge and benefit of using sea <span class="hlt">ice</span> <span class="hlt">concentration</span> satellite data products with uncertainty estimates in summer sea <span class="hlt">ice</span> data assimilation</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Yang, Qinghua; Losch, Martin; Losa, Svetlana N.; Jung, Thomas; Nerger, Lars; Lavergne, Thomas</p> <p>2016-04-01</p> <p>Data assimilation experiments that aim at improving summer <span class="hlt">ice</span> <span class="hlt">concentration</span> and thickness forecasts in the Arctic are carried out. The data assimilation system used is based on the MIT general circulation model (MITgcm) and a local singular evolutive interpolated Kalman (LSEIK) filter. The effect of using sea <span class="hlt">ice</span> <span class="hlt">concentration</span> satellite data products with appropriate uncertainty estimates is assessed by three different experiments using sea <span class="hlt">ice</span> <span class="hlt">concentration</span> data of the European Space Agency Sea <span class="hlt">Ice</span> Climate Change Initiative (ESA SICCI) which are provided with a per-grid-cell physically based sea <span class="hlt">ice</span> <span class="hlt">concentration</span> uncertainty estimate. The first experiment uses the constant uncertainty, the second one imposes the provided SICCI uncertainty estimate, while the third experiment employs an elevated minimum uncertainty to account for a representation error. Using the observation uncertainties that are provided with the data improves the ensemble mean forecast of <span class="hlt">ice</span> <span class="hlt">concentration</span> compared to using constant data errors, but the thickness forecast, based on the sparsely available data, appears to be degraded. Further investigating this lack of positive impact on the sea <span class="hlt">ice</span> thicknesses leads us to a fundamental mismatch between the satellite-based radiometric <span class="hlt">concentration</span> and the modeled physical <span class="hlt">ice</span> <span class="hlt">concentration</span> in summer: the passive microwave sensors used for deriving the vast majority of the sea <span class="hlt">ice</span> <span class="hlt">concentration</span> satellite-based observations cannot distinguish ocean water (in leads) from melt water (in ponds). New data assimilation methodologies that fully account or mitigate this mismatch must be designed for successful assimilation of sea <span class="hlt">ice</span> <span class="hlt">concentration</span> satellite data in summer melt conditions. In our study, thickness forecasts can be slightly improved by adopting the pragmatic solution of raising the minimum observation uncertainty to inflate the data error and ensemble spread.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.8815M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.8815M"><span>Closure between <span class="hlt">ice</span>-nucleating particle and <span class="hlt">ice</span> crystal number <span class="hlt">concentrations</span> in <span class="hlt">ice</span> clouds embedded in Saharan dust: Lidar observation during the BACCHUS Cyprus 2015 campaign</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mamouri, Rodanthi-Elisavet; Ansmann, Albert; Bühl, Johannes; Engelmann, Ronny; Baars, Holger; Nisantzi, Argyro; Hadjimitsis, Diofantos; Atkinson, James; Kanji, Zamin; Vrekoussis, Michalis; Sciare, Jean; Mihalopoulos, Nikos</p> <p>2016-04-01</p> <p>For the first time, we compare <span class="hlt">ice</span>-nucleating particle number <span class="hlt">concentration</span> (INPC) derived from polarization lidar (Mamouri and Ansmann, 2015) with <span class="hlt">ice</span> crystal number <span class="hlt">concentrations</span> (ICNC) in <span class="hlt">ice</span> cloud layers embedded in the observed Saharan dust layers (at heights above 6 km and corresponding temperatures from -20 to -40°C). ICNC is estimated from the respective cirrus extinction profiles obtained with the same polarization lidar in combination with Doppler lidar measurements of the <span class="hlt">ice</span> crystal sedimentation speed from which the mean size of the crystals can be estimated. Good agreement between INPC and ICNC was obtained for two case studies of the BACCHUS Cyprus 2015 field campaign with focus on INPC profiling. The campaign was organized by the Cyprus Institute, Nicosia, where a lidar was deployed. Additionaly, observations of AERONET and EALINET Lidar stations during the BACCHUS Cyprus 2015 field campaign, performed by Cyprus University of Technology in Limassol. Both, INPC and ICNC were found in the range from 10-50 1/L. Lidar-derived INPC values were also compared with in-situ INPC measurements (Horizontal <span class="hlt">Ice</span> Nucleation Chamber, HINC, ETH Zurich, deployed at Agia Marina, at 500 m a.s.l., 30 km west of the lidar site). Reasonable and partly good agreement (during dust events) was found between the two retrievals. The findings of these closure studies corroborate the applicability of available INPC parameterization schemes (DeMott et al., 2010, 2015) implemented in the lidar retrieval scheme, and more generally INPC profiling by using active remote sensing (at ground and in space with CALIPSO and EarthCARE lidars).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/scitech/biblio/944767','SCIGOV-STC'); return false;" href="https://www.osti.gov/scitech/biblio/944767"><span>Understanding <span class="hlt">Ice</span> Supersaturation, Particle Growth, and Number <span class="hlt">Concentration</span> in Cirrus Clouds</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Comstock, Jennifer M.; Lin, Ruei-Fong; Starr, David O.; Yang, P.</p> <p>2008-12-10</p> <p>Many factors control the <span class="hlt">ice</span> supersaturation and microphysical properties in cirrus clouds. We explore the effects of dynamic forcing, <span class="hlt">ice</span> nucleation mechanisms, and <span class="hlt">ice</span> crystal growth rate on the evolution and distribution of water vapor and cloud properties in cirrus clouds using a detailed microphysical model and remote sensing measurements obtained at the Department of Energy’s Atmospheric Radiation Measurement (ARM) Climate Research Facility located near Lamont, OK. To help understand dynamic scales important in cirrus formation, we force the model using both large-scale forcing derived using ARM variational analysis, and mean mesoscale velocity derived from radar Doppler velocity measurements. Both heterogeneous and homogeneous nucleation processes are explored, where we have implemented a rigorous classical theory heterogeneous nucleation scheme to compare with empirical representations. We evaluate model simulations by examining both bulk cloud properties and distributions of measured radar reflectivity, lidar extinction, and water vapor profiles, as well as retrieved cloud microphysical properties. This approach allows for independent verification of both the large and small particle modes of the particle size distribution. Our results suggest that mesoscale variability is the primary mechanism needed to reproduce observed quantities, while nucleation mechanism is secondary. Slow <span class="hlt">ice</span> crystal growth tends to overestimate the number of small <span class="hlt">ice</span> crystals, but does not seem to influence bulk properties such as <span class="hlt">ice</span> water path and cloud thickness. The most realistic simulations as compared with observations are forced using mesoscale waves, include fast <span class="hlt">ice</span> crystal growth, and initiate <span class="hlt">ice</span> by either homogeneous or heterogeneous nucleation. <span class="hlt">Ice</span> crystal number <span class="hlt">concentrations</span> on the order of 10-100 L-1 produce results consistent with both lidar and radar observations during a cirrus event observed on 7 December 1999, which has an optical depth range typical of</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014CliPa..10.1659G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014CliPa..10.1659G"><span>Dating a tropical <span class="hlt">ice</span> core by time-frequency analysis of ion <span class="hlt">concentration</span> depth profiles</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gay, M.; De Angelis, M.; Lacoume, J.-L.</p> <p>2014-09-01</p> <p><span class="hlt">Ice</span> core dating is a key parameter for the interpretation of the <span class="hlt">ice</span> archives. However, the relationship between <span class="hlt">ice</span> depth and <span class="hlt">ice</span> age generally cannot be easily established and requires the combination of numerous investigations and/or modelling efforts. This paper presents a new approach to <span class="hlt">ice</span> core dating based on time-frequency analysis of chemical profiles at a site where seasonal patterns may be significantly distorted by sporadic events of regional importance, specifically at the summit area of Nevado Illimani (6350 m a.s.l.), located in the eastern Bolivian Andes (16°37' S, 67°46' W). We used ion <span class="hlt">concentration</span> depth profiles collected along a 100 m deep <span class="hlt">ice</span> core. The results of Fourier time-frequency and wavelet transforms were first compared. Both methods were applied to a nitrate <span class="hlt">concentration</span> depth profile. The resulting chronologies were checked by comparison with the multi-proxy year-by-year dating published by de Angelis et al. (2003) and with volcanic tie points. With this first experiment, we demonstrated the efficiency of Fourier time-frequency analysis when tracking the nitrate natural variability. In addition, we were able to show spectrum aliasing due to under-sampling below 70 m. In this article, we propose a method of de-aliasing which significantly improves the core dating in comparison with annual layer manual counting. Fourier time-frequency analysis was applied to <span class="hlt">concentration</span> depth profiles of seven other ions, providing information on the suitability of each of them for the dating of tropical Andean <span class="hlt">ice</span> cores.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20000038166&hterms=PASSIVE+FILTER&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3DPASSIVE%2BFILTER','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20000038166&hterms=PASSIVE+FILTER&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3DPASSIVE%2BFILTER"><span>Passive Microwave Algorithms for Sea <span class="hlt">Ice</span> <span class="hlt">Concentration</span>: A Comparison of Two Techniques</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Comiso, Josefino C.; Cavalieri, Donald J.; Parkinson, Claire L.; Gloersen, Per</p> <p>1997-01-01</p> <p>The most comprehensive large-scale characterization of the global sea <span class="hlt">ice</span> cover so far has been provided by satellite passive microwave data. Accurate retrieval of <span class="hlt">ice</span> <span class="hlt">concentrations</span> from these data is important because of the sensitivity of surface flux(e.g. heat, salt, and water) calculations to small change in the amount of open water (leads and polynyas) within the polar <span class="hlt">ice</span> packs. Two algorithms that have been used for deriving <span class="hlt">ice</span> <span class="hlt">concentrations</span> from multichannel data are compared. One is the NASA Team algorithm and the other is the Bootstrap algorithm, both of which were developed at NASA's Goddard Space Flight Center. The two algorithms use different channel combinations, reference brightness temperatures, weather filters, and techniques. Analyses are made to evaluate the sensitivity of algorithm results to variations of emissivity and temperature with space and time. To assess the difference in the performance of the two algorithms, analyses were performed with data from both hemispheres and for all seasons. The results show only small differences in the central Arctic in but larger disagreements in the seasonal regions and in summer. In some ares in the Antarctic, the Bootstrap technique show <span class="hlt">ice</span> <span class="hlt">concentrations</span> higher than those of the Team algorithm by as much as 25%; whereas, in other areas, it shows <span class="hlt">ice</span> <span class="hlt">concentrations</span> lower by as much as 30%. The The differences in the results are caused by temperature effects, emissivity effects, and tie point differences. The Team and the Bootstrap results were compared with available Landsat, advanced very high resolution radiometer (AVHRR) and synthetic aperture radar (SAR) data. AVHRR, Landsat, and SAR data sets all yield higher <span class="hlt">concentrations</span> than the passive microwave algorithms. Inconsistencies among results suggest the need for further validation studies.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/scitech/biblio/1025075','SCIGOV-STC'); return false;" href="https://www.osti.gov/scitech/biblio/1025075"><span>Effects of <span class="hlt">ice</span> number <span class="hlt">concentration</span> on dynamics of a shallow mixed-phase stratiform cloud</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Ovchinnikov, Mikhail; Korolev, Alexei; Fan, Jiwen</p> <p>2011-09-17</p> <p>Previous modeling studies have shown a high sensitivity of simulated properties of mixed-phase clouds to <span class="hlt">ice</span> number <span class="hlt">concentration</span>, Ni, with many models losing their ability to maintain the liquid phase as Ni increases. Although models differ widely at what Ni the mixed-phase cloud becomes unstable, the transition from a mixed-phase to an <span class="hlt">ice</span> only cloud in many cases occurs over a narrow range of <span class="hlt">ice</span> <span class="hlt">concentration</span>. To gain better understanding of this non-linear model behavior, in this study, we analyze simulations of a mixed-phase stratiform Artic cloud observed on 26 April 2008 during recent Indirect and Semi-Direct Aerosol Campaign (ISDAC). The BASE simulation, in which Ni is constrained to match the measured value, produces a long-lived cloud in a quasi steady state similar to that observed. The simulation without the <span class="hlt">ice</span> (NO_<span class="hlt">ICE</span>) produces a comparable but slightly thicker cloud because more moisture is kept in the mixed layer due to lack of precipitation. When Ni is quadrupled relative to BASE (HI_<span class="hlt">ICE</span>), the cloud starts loosing liquid water almost immediately and the liquid water path is reduced by half in less than two hours. The changes in liquid water are accompanied by corresponding reduction in the radiative cooling of the layer and a slow down in the vertical mixing, confirming the important role of interactions among microphysics, radiation and dynamics in this type of clouds. Deviations of BASE and HI_<span class="hlt">ICE</span> from NO_<span class="hlt">ICE</span> are used to explore the linearity of the model response to variation in Ni. It is shown that at early stages, changes in liquid and <span class="hlt">ice</span> water as well as in radiative cooling/heating rates are proportional to the Ni change, while changes in the vertical buoyancy flux are qualitatively different in HI_<span class="hlt">ICE</span> compared to BASE. Thus, while the positive feedback between the liquid water path and radiative cooling of the cloud layer is essential for glaciation of the cloud at higher Ni, the non-linear (with respect to Ni) reduction in positive</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ACP....17.3637V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ACP....17.3637V"><span>Contribution of feldspar and marine organic aerosols to global <span class="hlt">ice</span> nucleating particle <span class="hlt">concentrations</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Vergara-Temprado, Jesús; Murray, Benjamin J.; Wilson, Theodore W.; O'Sullivan, Daniel; Browse, Jo; Pringle, Kirsty J.; Ardon-Dryer, Karin; Bertram, Allan K.; Burrows, Susannah M.; Ceburnis, Darius; DeMott, Paul J.; Mason, Ryan H.; O'Dowd, Colin D.; Rinaldi, Matteo; Carslaw, Ken S.</p> <p>2017-03-01</p> <p><span class="hlt">Ice</span>-nucleating particles (INPs) are known to affect the amount of <span class="hlt">ice</span> in mixed-phase clouds, thereby influencing many of their properties. The atmospheric INP <span class="hlt">concentration</span> changes by orders of magnitude from terrestrial to marine environments, which typically contain much lower <span class="hlt">concentrations</span>. Many modelling studies use parameterizations for heterogeneous <span class="hlt">ice</span> nucleation and cloud <span class="hlt">ice</span> processes that do not account for this difference because they were developed based on INP measurements made predominantly in terrestrial environments without considering the aerosol composition. Errors in the assumed INP <span class="hlt">concentration</span> will influence the simulated amount of <span class="hlt">ice</span> in mixed-phase clouds, leading to errors in top-of-atmosphere radiative flux and ultimately the climate sensitivity of the model. Here we develop a global model of INP <span class="hlt">concentrations</span> relevant for mixed-phase clouds based on laboratory and field measurements of <span class="hlt">ice</span> nucleation by K-feldspar (an <span class="hlt">ice</span>-active component of desert dust) and marine organic aerosols (from sea spray). The simulated global distribution of INP <span class="hlt">concentrations</span> based on these two species agrees much better with currently available ambient measurements than when INP <span class="hlt">concentrations</span> are assumed to depend only on temperature or particle size. Underestimation of INP <span class="hlt">concentrations</span> in some terrestrial locations may be due to the neglect of INPs from other terrestrial sources. Our model indicates that, on a monthly average basis, desert dusts dominate the contribution to the INP population over much of the world, but marine organics become increasingly important over remote oceans and they dominate over the Southern Ocean. However, day-to-day variability is important. Because desert dust aerosol tends to be sporadic, marine organic aerosols dominate the INP population on many days per month over much of the mid- and high-latitude Northern Hemisphere. This study advances our understanding of which aerosol species need to be included in order to</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19890049148&hterms=utopia&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dutopia','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19890049148&hterms=utopia&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dutopia"><span><span class="hlt">Concentric</span> crater fill on Mars - An aeolian alternative to <span class="hlt">ice</span>-rich mass wasting</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Zimbelman, J. R.; Clifford, S. M.; Williams, S. H.</p> <p>1989-01-01</p> <p><span class="hlt">Concentric</span> crater fill, a distinctive martian landform represented by a <span class="hlt">concentric</span> pattern of surface undulations confined within a crater rim, has been interpreted as an example of <span class="hlt">ice</span>-enhanced regolith creep at midlatitudes (e.g., Squyres and Carr, 1986). Theoretical constraints on the stability and mobility of ground <span class="hlt">ice</span> limit the applicability of an <span class="hlt">ice</span>-rich soil in effectively mobilizing downslope movement at latitudes poleward of + or - 30 deg, where <span class="hlt">concentric</span> crater fill is observed. High-resolution images of <span class="hlt">concentric</span> crater fill material in the Utopia Planitia region (45 deg N, 271 deg W) show it to be an eroded, multiple-layer deposit. Layering should not be preserved if the crater fill material moved by slow deformation throughout its thickness, as envisioned in the <span class="hlt">ice</span>-enhanced creep model. Multiple layers are also exposed in the plains material surrounding the craters, indicating a recurrent depositional process that was at least regional in extent. Mantling layers are observed in high-resolution images of many other locations around Mars, suggesting that deposition occurred on a global scale and was not limited to the Utopia Planitia region. It is suggested that an aeolian interpretation for the origin and modification of <span class="hlt">concentric</span> crater fill material is most consistent with morphologic and theoretical constraints.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFM.A21F0162C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFM.A21F0162C"><span>Measurements of Atmospheric <span class="hlt">Ice</span> Nuclei <span class="hlt">Concentrations</span> at Two Canadian Sites: Downtown Toronto and Whistler, British Columbia</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Corbin, J. C.; Leaitch, W. R.; Evans, G. J.; MacDonald, A.; Abbatt, J.</p> <p>2010-12-01</p> <p>The subset of atmospheric aerosol particles termed <span class="hlt">ice</span> nuclei (IN) facilitate heterogeneous <span class="hlt">ice</span> formation by lowering the energy barrier to <span class="hlt">ice</span> formation, thus allowing <span class="hlt">ice</span> clouds to form at temperatures above the homogeneous freezing threshold. Though <span class="hlt">ice</span> plays a major role in initiating precipitation globally, the composition and distribution of IN in the atmosphere remains poorly understood. In order to investigate potential anthropogenic contributions to atmospheric <span class="hlt">ice</span> nucleation, we measured IN <span class="hlt">concentrations</span> on a major road in Toronto, ON, using the University of Toronto Continuous Flow Diffusion Chamber (UT-CFDC). The majority of measurements were conducted close to 95% relative humidity (RH) with respect to water, but full RH scans to conditions above supersaturation with respect to liquid water were also performed. Simultaneous measurements of aerosol size (APS, SMPS) and chemical composition (Aerosol Time-of-Flight Mass Spectrometer, ATOFMS) allow us to investigate the relationship of IN to varying aerosol types. The number of IN observed was highly variable, ranging from 0-87/L. These urban data will be contrasted with similar data obtained in the coniferous forest of Whistler Mountain, BC. An intense biogenic secondary aerosol event observed at Whistler is used to estimate an upper limit for IN from organic aerosol formed from monoterpene oxidation.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li class="active"><span>9</span></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_9 --> <div id="page_10" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li class="active"><span>10</span></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="181"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015ApJ...799...14C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015ApJ...799...14C"><span>Photochemistry of Polycyclic Aromatic Hydrocarbons in Cosmic Water <span class="hlt">Ice</span>: The Role of PAH Ionization and <span class="hlt">Concentration</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Cook, Amanda M.; Ricca, Alessandra; Mattioda, Andrew L.; Bouwman, Jordy; Roser, Joseph; Linnartz, Harold; Bregman, Jonathan; Allamandola, Louis J.</p> <p>2015-01-01</p> <p>Infrared spectroscopic studies of ultraviolet (UV) irradiated, water-rich, cosmic <span class="hlt">ice</span> analogs containing small polycyclic aromatic hydrocarbons (PAHs) are described. The irradiation studies of anthracene:H2O, pyrene:H2O, and benzo[ghi]perylene:H2O <span class="hlt">ices</span> (14 K) at various <span class="hlt">concentrations</span> reported by Bouwman et al. are extended. While aromatic alcohols and ketones have been reported in residues after irradiated PAH:H2O <span class="hlt">ices</span> were warmed to 270 K, it was not known if they formed during <span class="hlt">ice</span> irradiation or during warm-up when reactants interact as H2O sublimes. Recent work has shown that they form in low temperature <span class="hlt">ice</span>. Using DFT computed IR spectra to identify photoproducts and PAH cations, we tentatively identify the production of specific alcohols [PAH(OH) n ] and quinones [PAH(O) n ] for all PAH:H2O <span class="hlt">ices</span> considered here. Little evidence is found for hydrogenation at 14 K, consistent with the findings of Gudipati & Yang. Addition of O and OH to the parent PAH is the dominant photochemical reaction, but PAH erosion to smaller PAHs (producing CO2 and H2CO) is also important. DFT spectra are used to assess the contribution of PAH-related species to interstellar absorption features from 5 to 9 μm. The case is made that PAH cations are important contributors to the C2 component and PAH(OH) n and PAH(O) n to the C5 component described by Boogert et al. Thus, interstellar <span class="hlt">ices</span> should contain neutral and ionized PAHs, alcohols, ketones and quinones at the ~2%-4% level relative to H2O. PAHs, their photoproducts, and ion-mediated processes should therefore be considered when modeling interstellar <span class="hlt">ice</span> processes.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/scitech/biblio/22364554','SCIGOV-STC'); return false;" href="https://www.osti.gov/scitech/biblio/22364554"><span>PHOTOCHEMISTRY OF POLYCYCLIC AROMATIC HYDROCARBONS IN COSMIC WATER <span class="hlt">ICE</span>: THE ROLE OF PAH IONIZATION AND <span class="hlt">CONCENTRATION</span></span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Cook, Amanda M.; Mattioda, Andrew L.; Roser, Joseph; Bregman, Jonathan; Bouwman, Jordy; Linnartz, Harold</p> <p>2015-01-20</p> <p>Infrared spectroscopic studies of ultraviolet (UV) irradiated, water-rich, cosmic <span class="hlt">ice</span> analogs containing small polycyclic aromatic hydrocarbons (PAHs) are described. The irradiation studies of anthracene:H{sub 2}O, pyrene:H{sub 2}O, and benzo[ghi]perylene:H{sub 2}O <span class="hlt">ices</span> (14 K) at various <span class="hlt">concentrations</span> reported by Bouwman et al. are extended. While aromatic alcohols and ketones have been reported in residues after irradiated PAH:H{sub 2}O <span class="hlt">ices</span> were warmed to 270 K, it was not known if they formed during <span class="hlt">ice</span> irradiation or during warm-up when reactants interact as H{sub 2}O sublimes. Recent work has shown that they form in low temperature <span class="hlt">ice</span>. Using DFT computed IR spectra to identify photoproducts and PAH cations, we tentatively identify the production of specific alcohols [PAH(OH) {sub n} ] and quinones [PAH(O) {sub n} ] for all PAH:H{sub 2}O <span class="hlt">ices</span> considered here. Little evidence is found for hydrogenation at 14 K, consistent with the findings of Gudipati and Yang. Addition of O and OH to the parent PAH is the dominant photochemical reaction, but PAH erosion to smaller PAHs (producing CO{sub 2} and H{sub 2}CO) is also important. DFT spectra are used to assess the contribution of PAH-related species to interstellar absorption features from 5 to 9 μm. The case is made that PAH cations are important contributors to the C2 component and PAH(OH) {sub n} and PAH(O) {sub n} to the C5 component described by Boogert et al. Thus, interstellar <span class="hlt">ices</span> should contain neutral and ionized PAHs, alcohols, ketones and quinones at the ∼2%-4% level relative to H{sub 2}O. PAHs, their photoproducts, and ion-mediated processes should therefore be considered when modeling interstellar <span class="hlt">ice</span> processes.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2003JGRD..108.4687R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2003JGRD..108.4687R"><span>Impact of observed sea-<span class="hlt">ice</span> <span class="hlt">concentration</span> on the Southern Hemisphere extratropical atmospheric circulation in summer</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Raphael, M. N.</p> <p>2003-11-01</p> <p>The response of the Southern Hemisphere extratropical, atmospheric circulation to extremes of sea-<span class="hlt">ice</span> <span class="hlt">concentration</span> in summer is investigated using a fully coupled climate model. Maximum and minimum sea-<span class="hlt">ice</span> extremes were obtained from satellite-derived data, and a 12-month climatology for each case was created. Two 10-year simulations for each scenario were completed, and the results for the southern summer are compared. At the surface the sea-<span class="hlt">ice</span> extremes directly affected the temperatures around Antarctica and through these the latitudinal surface temperature and pressure gradients. The midlatitude surface westerlies are weaker in the maximum scenario, while the polar easterlies expand farther north. In the middle troposphere the zonal jet strengthens slightly and shifts equatorward in the maximum scenario. Comparisons of the sea level pressure field and the 500 hPa geopotential height field for the two scenarios show that the leading mode of circulation variability, the Southern Hemisphere Annular Mode, tends toward positive polarity (lower than normal geopotential heights over Antarctica) in the minimum sea-<span class="hlt">ice</span> scenario. This tendency is associated with local differences in surface pressure gradient and temperature and large scale dynamic responses to extremes of sea-<span class="hlt">ice</span> <span class="hlt">concentration</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20010018558','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20010018558"><span>The Impact of Sea <span class="hlt">Ice</span> <span class="hlt">Concentration</span> Accuracies on Climate Model Simulations with the GISS GCM</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Parkinson, Claire L.; Rind, David; Healy, Richard J.; Martinson, Douglas G.; Zukor, Dorothy J. (Technical Monitor)</p> <p>2000-01-01</p> <p>The Goddard Institute for Space Studies global climate model (GISS GCM) is used to examine the sensitivity of the simulated climate to sea <span class="hlt">ice</span> <span class="hlt">concentration</span> specifications in the type of simulation done in the Atmospheric Modeling Intercomparison Project (AMIP), with specified oceanic boundary conditions. Results show that sea <span class="hlt">ice</span> <span class="hlt">concentration</span> uncertainties of +/- 7% can affect simulated regional temperatures by more than 6 C, and biases in sea <span class="hlt">ice</span> <span class="hlt">concentrations</span> of +7% and -7% alter simulated annually averaged global surface air temperatures by -0.10 C and +0.17 C, respectively, over those in the control simulation. The resulting 0.27 C difference in simulated annual global surface air temperatures is reduced by a third, to 0.18 C, when considering instead biases of +4% and -4%. More broadly, least-squares fits through the temperature results of 17 simulations with <span class="hlt">ice</span> <span class="hlt">concentration</span> input changes ranging from increases of 50% versus the control simulation to decreases of 50% yield a yearly average global impact of 0.0107 C warming for every 1% <span class="hlt">ice</span> <span class="hlt">concentration</span> decrease, i.e., 1.07 C warming for the full +50% to -50% range. Regionally and on a monthly average basis, the differences can be far greater, especially in the polar regions, where wintertime contrasts between the +50% and -50% cases can exceed 30 C. However, few statistically significant effects are found outside the polar latitudes, and temperature effects over the non-polar oceans tend to be under 1 C, due in part to the specification of an unvarying annual cycle of sea surface temperatures. The +/- 7% and 14% results provide bounds on the impact (on GISS GCM simulations making use of satellite data) of satellite-derived <span class="hlt">ice</span> <span class="hlt">concentration</span> inaccuracies, +/- 7% being the current estimated average accuracy of satellite retrievals and +/- 4% being the anticipated improved average accuracy for upcoming satellite instruments. Results show that the impact on simulated temperatures of imposed <span class="hlt">ice</span> <span class="hlt">concentration</span></p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19920035391&hterms=defense&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Ddefense','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19920035391&hterms=defense&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Ddefense"><span>Aircraft active and passive microwave validation of sea <span class="hlt">ice</span> <span class="hlt">concentration</span> from the Defense Meteorological Satellite Program special sensor microwave imager</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Cavalieri, D. J.; Crawford, J. P.; Drinkwater, M. R.; Eppler, D. T.; Farmer, L. D.; Jentz, R. R.; Wackerman, C. C.</p> <p>1991-01-01</p> <p>Results are presented of a series of coordinate special sensor microwave imager (SSM/I) underflights that were carried out during March 1988 with NASA and Navy aircraft over portions of the Bering, Beaufort, and Chukchi seas. NASA DC-8 AMMR data from Bering Sea <span class="hlt">ice</span> edge crossings were used to verify that the <span class="hlt">ice</span> edge location, defined as the position of the initial <span class="hlt">ice</span> bands encountered by the aircraft, corresponds to an SSM/I <span class="hlt">ice</span> <span class="hlt">concentration</span> of 15 percent. Direct comparison of SSM/I and aircraft <span class="hlt">ice</span> <span class="hlt">concentrations</span> for regions having at least 80 percent aircraft coverage reveals that the SSM/I total <span class="hlt">ice</span> <span class="hlt">concentration</span> is lower on average by 2.4 +/-2.4 percent. For multiyear <span class="hlt">ice</span>, NASA and Navy flights across the Beaufort and Chukchi seas show that the SSM/I algorithm correctly maps the large-scale distribution of multiyear <span class="hlt">ice</span>: the zone of first-year <span class="hlt">ice</span> off the Alaskan coast, the large areas of mixed first-year and multiyear <span class="hlt">ice</span>, and the region of predominantly multiyear <span class="hlt">ice</span> north of the Canadian archipelago.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/22624355','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/22624355"><span>[Characteristics of carbonaceous aerosol <span class="hlt">concentration</span> in snow and <span class="hlt">ice</span> of glaciers in Tianshan Mountains].</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Wang, Sheng-Jie; Zhang, Ming-Jun; Wang, Fei-Teng; Li, Zhong-Qin</p> <p>2012-03-01</p> <p>The snow and <span class="hlt">ice</span> samples, collected at Glacier No. 1 at the headwaters of Urumqi River (UG1) and Glacier No. 51 at Haxilegen of Kuytun River (HG51) in 2002 and 2004, were analyzed for organic carbon (OC) and element carbon (EC) by thermal/ optical reflectance (TOR). The spatio-temporal characteristics and environmental significance of OC and EC <span class="hlt">concentration</span> were discussed in details. The <span class="hlt">concentration</span> order of total carbon (TC) was: snowpack of west branch on UG1 (1 943 ng x g(-1)) > snowpack of east branch on UG1 (989 ng x g(-1)) > snowpack of HG51 (150 ng x g(-1)) > glacier <span class="hlt">ice</span> of east branch on UG1 (77 ng x g(-1)), and the <span class="hlt">concentration</span> order of OC and EC lay similar as TC. The <span class="hlt">concentration</span> of OC and EC in snowpack of Tianshan Mountains were 557 ng x g(-1) and 188 ng x g(-1), respectively. <span class="hlt">Concentration</span> peak of carbonaceous aerosol usually appeared near the dust layer at the bottom section of snowpack, but the some sudden events could increase the <span class="hlt">concentration</span> in the surface snow. Because of the seasonality of carbon emission (e. g. heating and agricultural activities) and transportation (e. g. atmospheric circulation), the <span class="hlt">concentration</span> of carbonaceous aerosol increased from July to November with fluctuations. Difference on the order of magnitude might exist between the <span class="hlt">concentration</span> in snow (firn) and glacier <span class="hlt">ice</span>, which was influenced by the glacier surroundings, sampling situation and other factors. EC on the surface snow affected the albedo significantly, and an average albedo reduction of 0.22 in the wavelength of 300-700 nm was simulated by SNICAR (snow, <span class="hlt">ice</span>, and aerosol radiative) model.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19870060026&qs=N%3D0%26Ntk%3DTitle%26Ntx%3Dmode%2Bmatchall%26Ntt%3DB','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19870060026&qs=N%3D0%26Ntk%3DTitle%26Ntx%3Dmode%2Bmatchall%26Ntt%3DB"><span>Shuttle Imaging Radar B (SIR-B) Weddell Sea <span class="hlt">ice</span> observations - A comparison of SIR-B and scanning multichannel microwave radiometer <span class="hlt">ice</span> <span class="hlt">concentrations</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Martin, Seelye; Holt, Benjamin; Cavalieri, Donald J.; Squire, Vernon</p> <p>1987-01-01</p> <p><span class="hlt">Ice</span> <span class="hlt">concentrations</span> over the Weddell Sea were studied using SIR-B data obtained during the October 1984 mission, with special attention given to the effect of ocean waves on the radar return at the <span class="hlt">ice</span> edge. Sea <span class="hlt">ice</span> <span class="hlt">concentrations</span> were derived from the SIR-B data using two image processing methods: the classification scheme at JPL and the manual classification method at Scott Polar Research Institute (SPRI), England. The SIR <span class="hlt">ice</span> <span class="hlt">concentrations</span> were compared with coincident <span class="hlt">concentrations</span> from the Nimbus-7 SMMR. For <span class="hlt">concentrations</span> greater than 40 percent, which was the smallest <span class="hlt">concentration</span> observed jointly by SIR-B and the SMMR, the mean difference between the two data sets for 12 points was 2 percent. A comparison between the JPL and the SPRI SIR-B algorithms showed that the algorithms agree to within 1 percent in the interior <span class="hlt">ice</span> pack, but the JPL algorithm gives slightly greater <span class="hlt">concentrations</span> at the <span class="hlt">ice</span> edge (due to the fact that the algorithm is affected by the wind waves in these areas).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015TCD.....9.2339P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015TCD.....9.2339P"><span>Assimilating high horizontal resolution sea <span class="hlt">ice</span> <span class="hlt">concentration</span> data into the US Navy's <span class="hlt">ice</span> forecast systems: Arctic Cap Nowcast/Forecast System (ACNFS) and the Global Ocean Forecast System (GOFS 3.1)</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Posey, P. G.; Metzger, E. J.; Wallcraft, A. J.; Hebert, D. A.; Allard, R. A.; Smedstad, O. M.; Phelps, M. W.; Fetterer, F.; Stewart, J. S.; Meier, W. N.; Helfrich, S. R.</p> <p>2015-04-01</p> <p>This study presents the improvement in the US Navy's operational sea <span class="hlt">ice</span> forecast systems gained by assimilating high horizontal resolution satellite-derived <span class="hlt">ice</span> <span class="hlt">concentration</span> products. Since the late 1980's, the <span class="hlt">ice</span> forecast systems have assimilated near real-time sea <span class="hlt">ice</span> <span class="hlt">concentration</span> derived from the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSMI and then SSMIS). The resolution of the satellite-derived product was approximately the same as the previous operational <span class="hlt">ice</span> forecast system (25 km). As the sea <span class="hlt">ice</span> forecast model resolution increased over time, the need for higher horizontal resolution observational data grew. In 2013, a new Navy sea <span class="hlt">ice</span> forecast system (Arctic Cap Nowcast/Forecast System - ACNFS) went into operations with a horizontal resolution of ~3.5 km at the North Pole. A method of blending <span class="hlt">ice</span> <span class="hlt">concentration</span> observations from the Advanced Microwave Scanning Radiometer (AMSR2) along with a sea <span class="hlt">ice</span> mask produced by the National <span class="hlt">Ice</span> Center (NIC) has been developed resulting in an <span class="hlt">ice</span> <span class="hlt">concentration</span> product with very high spatial resolution. In this study, ACNFS was initialized with this newly developed high resolution blended <span class="hlt">ice</span> <span class="hlt">concentration</span> product. The daily <span class="hlt">ice</span> edge locations from model hindcast simulations were compared against independent observed <span class="hlt">ice</span> edge locations. ACNFS initialized using the high resolution blended <span class="hlt">ice</span> <span class="hlt">concentration</span> data product decreased predicted <span class="hlt">ice</span> edge location error compared to the operational system that only assimilated SSMIS data. A second evaluation assimilating the new blended sea <span class="hlt">ice</span> <span class="hlt">concentration</span> product into the pre-operational Navy Global Ocean Forecast System 3.1 also showed a substantial improvement in <span class="hlt">ice</span> edge location over a system using the SSMIS sea <span class="hlt">ice</span> <span class="hlt">concentration</span> product alone. This paper describes the technique used to create the blended sea <span class="hlt">ice</span> <span class="hlt">concentration</span> product and the significant improvements to both of the Navy's sea <span class="hlt">ice</span> forecasting systems.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.C43B0668R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.C43B0668R"><span>Recent Increase in Elemental Carbon <span class="hlt">Concentration</span> and Deposition in a Svalbard <span class="hlt">Ice</span> Core</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ruppel, M.; Isaksson, E. D.; Ström, J.; Svensson, J.; Beaudon, E.; Korhola, A.</p> <p>2013-12-01</p> <p>Black carbon (BC) is an aerosol produced by incomplete combustion of biomass and fossil fuels. Due to its strong light absorption it warms the atmosphere. Climate effects of BC are intensified in the Arctic where its deposition on snow and <span class="hlt">ice</span> decreases surface albedo, causing earlier spring melt and associated feedbacks. Despite the significant role of BC in Arctic climate warming, there is little information on its <span class="hlt">concentrations</span> and climate effects in the Arctic in time periods preceding direct observational data. Here we present first results on BC (here operationally defined as elemental carbon (EC)) <span class="hlt">concentrations</span> and deposition on a Svalbard (European Arctic) glacier (Holtedahlfonna) from 1700 to 2004. The inner part of a 125 m deep <span class="hlt">ice</span> core was melted, filtered and analyzed for apparent elemental carbon using a thermal optical method. EC <span class="hlt">concentrations</span> (μg L-1) and the deposition (mg m-2 yr-1) were generally low in the pre-industrial era. <span class="hlt">Concentrations</span> peaked around 1910 and again around 1950, whereas only the 1910 peak was recorded in the EC deposition, followed by decreasing deposition values. Strikingly, both EC <span class="hlt">concentration</span> and deposition started to increase rapidly from the 1970s until 2004. This rise is not seen in any thus far published European or Arctic <span class="hlt">ice</span> core, and it seems to contradict atmospheric BC measurements from the Arctic which indicate decreasing atmospheric BC <span class="hlt">concentrations</span> since the beginning of the observations at the end of 1980s. However, the magnitude of the measured <span class="hlt">concentrations</span> is in accordance with previous <span class="hlt">ice</span> core EC measurements from the European Alps and a BC <span class="hlt">concentration</span> and deposition peak around 1910 has also been recorded in Greenland <span class="hlt">ice</span> cores. Work is continuing to disentangle the cause of the increasing EC values in the recent decades suggested by the present <span class="hlt">ice</span> core. Contribution from any local sources has been ruled out. Back trajectory modeling is carried out to establish the EC source areas. The present</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/scitech/biblio/7120760','SCIGOV-STC'); return false;" href="https://www.osti.gov/scitech/biblio/7120760"><span>Investigation of Antarctic sea <span class="hlt">ice</span> <span class="hlt">concentration</span> by means of selected algorithms. Final report, 1991-1992</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Lomax, A.S.</p> <p>1992-05-08</p> <p>Changes in areal extent and <span class="hlt">concentration</span> of sea <span class="hlt">ice</span> around Antarctica may serve as sensitive indicators of global warming. A comparison study was conducted between the outputs of the three main algorithms currently in use (NASA Team, Comisco, and NORSEX) and a sea-<span class="hlt">ice</span> model (Fine Resolution Antarctic Model). Data from the DMSP Special Sensor Microwave/Imager (SSM/I) were used as input algorithms for the time frame July, 1987 to June, 1990. Large disparities are apparent when comparing the NASA algorithm with the Comisco and NORSEX algorithms. Very large differences, some higher than 30 per cent, exist in the marginal <span class="hlt">ice</span> zones, along the coast, and in the Weddell and Ross Seas Heat fluxes through recurring polynyas were calculated to quantify further differences in the algorithms; however, no conclusive patterns were apparent. No significant change in the extent or area of the <span class="hlt">ice</span> pack occurred from July, 1987 through June, 1990. Antarctic Ocean, Antarctic regions, Global warming, Sea <span class="hlt">ice</span>-Antarctic regions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014JASTP.109...37O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014JASTP.109...37O"><span>Evidence of the solar Gleissberg cycle in the nitrate <span class="hlt">concentration</span> in polar <span class="hlt">ice</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ogurtsov, M. G.; Oinonen, M.</p> <p>2014-03-01</p> <p>Two sets of nitrate (NO3-) <span class="hlt">concentration</span> data, obtained from Central Greenland and East Antarctic (Dronning Maud Land) <span class="hlt">ice</span> cores, were analyzed statistically. Distinct century-scale (50-150 yr) variability was revealed in both data sets during AD 1576-1990. It was found that century-type variation in Greenland and Antarctic nitrate correlates fairly significantly with the corresponding Gleissberg cycle: (a) in sunspot number over 1700-1970 AD; (b) in 10Be <span class="hlt">concentration</span> in Central and South Greenland over 1576-1970 AD. Thus, presence of century-scale relationship between polar nitrate and solar activity was confirmed over the last 4 centuries. That proves that NO3- <span class="hlt">concentration</span> in polar <span class="hlt">ice</span> caps could serve as indicator of long-term solar variability.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19900044612&hterms=ice+melt&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dice%2Bmelt','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19900044612&hterms=ice+melt&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dice%2Bmelt"><span>Investigation of the effects of summer melt on the calculation of sea <span class="hlt">ice</span> <span class="hlt">concentration</span> using active and passive microwave data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Cavalieri, Donald J.; Burns, Barbara A.; Onstott, Robert G.</p> <p>1990-01-01</p> <p>The effects of <span class="hlt">ice</span> surface melt on microwave signatures and errors in the calculation of sea <span class="hlt">ice</span> <span class="hlt">concentration</span> are examined, using active and passive microwave data sets from the Marginal <span class="hlt">Ice</span> Zone Experiment aircraft flights in the Fram Strait region. Consideration is given to the possibility of using SAR to supplement passive microwave data to unambiguously discriminate between open water areas and ponded floes. Coincident active multichannel microwave radiometer and SAR measurements of individual floes are used to describe the effects of surface melt on sea <span class="hlt">ice</span> <span class="hlt">concentration</span> calculations.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19940007290&hterms=Ice+cover+Arctic+Ocean&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3DIce%2Bcover%2BArctic%2BOcean','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19940007290&hterms=Ice+cover+Arctic+Ocean&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3DIce%2Bcover%2BArctic%2BOcean"><span>Summer Arctic <span class="hlt">ice</span> <span class="hlt">concentrations</span> and characteristics from SAR and SSM/I data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Comiso, Joey C.; Kwok, Ron</p> <p>1993-01-01</p> <p>The extent and <span class="hlt">concentration</span> of the Summer minima provide indirect information about the long term ability of the perennial portion of the <span class="hlt">ice</span> pack to survive the Arctic atmosphere and ocean system. Both active and passive microwave data were used with some success for monitoring the <span class="hlt">ice</span> cover during the Summer, but they both suffer from similar problems caused by the presence of meltponding, surface wetness, flooding, and freeze/thaw cycles associated with periodic changes in surface air temperatures. A comparative analysis of <span class="hlt">ice</span> conditions in the Arctic region using coregistered ERS-1 SAR (Synthetic Aperture Radar) and SSM/I (Special Sensor Microwave/Imager) data was made. The analysis benefits from complementary information from the two systems, the good spatial resolution of SAR data, and the good time resolution of and global coverage by SSM/I data. The results show that in many areas <span class="hlt">ice</span> <span class="hlt">concentrations</span> derived from SAR data are significantly different (usually higher) than those derived from passive microwave data. Additional insights about surface conditions can be inferred depending on the nature of the discrepancies.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18..639C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18..639C"><span>Robustness of the large-scale modes of variability of winter Arctic sea <span class="hlt">ice</span> <span class="hlt">concentration</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Close, Sally; Houssais, Marie-Noëlle; Herbaut, Christophe</p> <p>2016-04-01</p> <p>The dominant mode of variability of Arctic winter sea <span class="hlt">ice</span> <span class="hlt">concentration</span> has previously been suggested to be represented by a double-dipole structure, with the loading pattern of the first empirical orthogonal mode having phase of one sign in the Sea of Okhotsk and Barents Sea and opposing sign in the Labrador and Bering Seas. In this study, we build on this previous work, examining the robustness of the primary modes of large-scale variability of the winter sea <span class="hlt">ice</span> <span class="hlt">concentration</span> in the Arctic based on the satellite data record. We find that the double-dipole structure does not emerge as a robust mode of variability: rather, the primary mode can be considered as a tripole, explaining significant variability only in the Sea of Okhotsk, Barents and Bering Seas. In contrast, the Labrador Sea emerges in isolation in the second empirical orthogonal mode. The relative magnitude of the poles of variability in the empirical orthogonal function loading patterns are sensitive to the detrending of the data; however, the isolation of the variability of the Labrador Sea <span class="hlt">ice</span> remains a robust feature. We find that there is no significant interannual-scale co-variability amongst the sea <span class="hlt">ice</span> areas of the four seas comprising the double-dipole after low-frequency variability has been removed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19980076134&hterms=Parkinson&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3DParkinson','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19980076134&hterms=Parkinson&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3DParkinson"><span>Arctic and Antarctic Sea <span class="hlt">Ice</span> <span class="hlt">Concentrations</span> from Multichannel Passive-Microwave Satellite Data Sets: User's Guide</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Cavalieri, Donald J.; Parkinson, Claire L.; Gloersen, Per; Zwally, H. Jay</p> <p>1997-01-01</p> <p>Satellite multichannel passive-microwave sensors have provided global radiance measurements with which to map, monitor, and study the Arctic and Antarctic polar sea <span class="hlt">ice</span> covers. The data span over 18 years (as of April 1997), starting with the launch of the Scanning Multichannel Microwave Radiometer (SMMR) on NASA's SeaSat A and Nimbus 7 in 1978 and continuing with the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSMI) series beginning in 1987. It is anticipated that the DMSP SSMI series will continue into the 21st century. The SSMI series will be augmented by new, improved sensors to be flown on Japanese and U.S. space platforms. This User's Guide provides a description of a new sea <span class="hlt">ice</span> <span class="hlt">concentration</span> data set generated from observations made by three of these multichannel sensors. The data set includes gridded daily <span class="hlt">ice</span> <span class="hlt">concentrations</span> (every-other-day for the SMMR data) for both the north and south polar regions from October 26, 1978 through September 30, 1995, with the one exception of a 6-week data gap from December 3, 1987 through January 12, 1988. The data have been placed on two CD-ROMs that include a ReadMeCD file giving the technical details on the file format, file headers, north and south polar grids, ancillary data sets, and directory structure of the CD-ROM. The CD-ROMS will be distributed by the National Snow and <span class="hlt">Ice</span> Data Center in Boulder, CO.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2004AGUFM.U23A..08S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2004AGUFM.U23A..08S"><span>``Pre-Vostok'' Greenhouse Gas <span class="hlt">Concentrations</span> Reconstructed From the EPICA Dome C <span class="hlt">Ice</span> Core</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Stocker, T. F.; Siegenthaler, U.; Spahni, R.; Chappellaz, J.; Fischer, H.</p> <p>2004-12-01</p> <p>The new deep <span class="hlt">ice</span> core recovered from Dome Concordia in the framework of EPICA, the European Project of <span class="hlt">Ice</span> Coring in Antarctica, contains a continuous climate history of the past 740,000 years [EPICA Community Members, 2004]. We present the current status of measurements of CO2, CH4 and N2O on air trapped in the bubbles of the Dome C <span class="hlt">ice</span> core. CO2 is measured using laser absorption spectroscopy on samples of less than 10 g of <span class="hlt">ice</span> which are mechanically crushed or milled. CH4 and N2O are extracted using a melt-refreeze technique and then measured by gas chromatography. The <span class="hlt">ice</span> core contains an uncontaminated climate record down to Marine Isotope Stage 14 (MIS 14) as verified by a consistent gas age/<span class="hlt">ice</span> age difference determined at terminations V and VI. CO2 and CH4 results from MIS 11 show that the normal levels of greenhouse gases prevailed during this exceptionally long interglacial. This demonstrates that the length of the interglacial was not due to exceptionally high greenhouse gas levels. MIS 13 and earlier interglacials, however, show significantly colder interglacials. In addition, the glacials are shorter which results in a more balanced sequence of cold and warm phases. Measurements of the greenhouse gas <span class="hlt">concentrations</span> are central in understanding the mechanisms in the climate system which cause the significant change of character of the <span class="hlt">ice</span> age cycles at around 400 kyr BP. We will present greenhouse gas measurements covering the first of the "pre-Vostok" interglacials from MIS 11 to MIS 14 (410 to 550 kyr BP) for CO2, and from MIS 11 to MIS 16 (410 to 620 kyr BP) for CH4. These measurements will resolve the "EPICA Challenge" [Wolff et al., 2004] put out to modelers to predict the expected greenhouse gas levels prior to 400 kyr BP based on the knowledge of the orbital parameters, and known paleoclimatic proxies (sea level from marine sediment records, dust load and isotopic <span class="hlt">concentration</span> of precipitation in Antarctica from the EPICA Dome C <span class="hlt">ice</span> core</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.4259W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.4259W"><span>Immersion freezing in <span class="hlt">concentrated</span> solution droplets for a variety of <span class="hlt">ice</span> nucleating particles</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wex, Heike; Kohn, Monika; Grawe, Sarah; Hartmann, Susan; Hellner, Lisa; Herenz, Paul; Welti, Andre; Lohmann, Ulrike; Kanji, Zamin; Stratmann, Frank</p> <p>2016-04-01</p> <p>The measurement campaign LINC (Leipzig <span class="hlt">Ice</span> Nucleation counter Comparison) was conducted in September 2015, during which <span class="hlt">ice</span> nucleation measurements as obtained with the following instruments were compared: - LACIS (Leipzig Aerosol Cloud Interaction Simulator, see e.g. Wex et al., 2014) - PIMCA-PINC (Portable Immersion Mode Cooling Chamber together with PINC) - PINC (Portable <span class="hlt">Ice</span> Nucleation Chamber, Chou et al., 2011) - SPIN (SPectrometer for <span class="hlt">Ice</span> Nuclei, Droplet Measurement Technologies) While LACIS and PIMCA-PINC measured immersion freezing, PINC and SPIN varied the super-saturation during the measurements and collected data also for relative humidities below 100% RHw. A suite of different types of <span class="hlt">ice</span> nucleating particles were examined, where particles were generated from suspensions, subsequently dried and size selected. For the following samples, data for all four instruments are available: K-feldspar, K-feldspar treated with nitric acid, Fluka-kaolinite and birch pollen. Immersion freezing measurements by LACIS and PIMCA-PINC were in excellent agreement. Respective parameterizations from these measurement were used to model the <span class="hlt">ice</span> nucleation behavior below water vapor saturation, assuming that the process can be described as immersion freezing in <span class="hlt">concentrated</span> solutions. This is equivalent to simply including a <span class="hlt">concentration</span> dependent freezing point depression in the immersion freezing parameterization, as introduced for coated kaolinite particles in Wex et al. (2014). Overall, measurements performed below water vapor saturation were reproduced by the model, and it will be discussed in detail, why deviations were observed in some cases. Acknowledgement: Part of this work was funded by the DFG Research Unit FOR 1525 INUIT, grant WE 4722/1-2. Literature: Chou, C., O. Stetzer, E. Weingartner, Z. Juranyi, Z. A. Kanji, and U. Lohmann (2011), <span class="hlt">Ice</span> nuclei properties within a Saharan dust event at the Jungfraujoch in the Swiss Alps, Atmos. Chem. Phys., 11(10), 4725</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014A%26A...562A..22C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014A%26A...562A..22C"><span>Photochemistry of PAHs in cosmic water <span class="hlt">ice</span>. The effect of <span class="hlt">concentration</span> on UV-VIS spectroscopy and ionization efficiency</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Cuylle, Steven H.; Allamandola, Louis J.; Linnartz, Harold</p> <p>2014-02-01</p> <p>Context. Observations and models show that polycyclic aromatic hydrocarbons (PAHs) are ubiquitous in the interstellar medium. Like other molecules in dense clouds, PAHs accrete onto interstellar dust grains, where they are embedded in an <span class="hlt">ice</span> matrix dominated by water. In the laboratory, mixed molecular <span class="hlt">ices</span> (not containing PAHs) have been extensively studied using Fourier transform infrared absorption spectroscopy. Experiments including PAHs in <span class="hlt">ices</span> have started, however, the <span class="hlt">concentrations</span> used are typically much higher than the <span class="hlt">concentrations</span> expected for interstellar <span class="hlt">ices</span>. Optical spectroscopy offers a sensitive alternative. Aims: We report an experimental study of the effect PAH <span class="hlt">concentration</span> has on the electronic spectra and the vacuum UV (VUV) driven processes of PAHs in water-rich <span class="hlt">ices</span>. The goal is to apply the outcome to cosmic <span class="hlt">ices</span>. Methods: Optical spectroscopic studies allow us to obtain in-situ and quasi real-time electronic solid state spectra of two prototypical PAHs (pyrene and coronene) embedded in water <span class="hlt">ice</span> under VUV photoprocessing. The study is carried out on PAH:H2O <span class="hlt">concentrations</span> in the range of 1:30 000 to pure PAH, covering the temperature range from 12 to 125 K. Results: PAH <span class="hlt">concentration</span> strongly influences the efficiency of PAH cation formation. At low <span class="hlt">concentrations</span>, ionization efficiencies are over 60% dropping to about 15% at 1:1000. Increasing the PAH <span class="hlt">concentration</span> reveals spectral broadening in neutral and cation PAH spectra attributed to PAH clustering inside the <span class="hlt">ice</span>. At the PAH <span class="hlt">concentrations</span> expected for interstellar <span class="hlt">ices</span>, some 10 to 20% may be present as cations. The presence of PAHs in neutral and ion form will add distinctive absorption bands to cosmic <span class="hlt">ice</span> optical spectra and this may serve as a tool to determine PAH <span class="hlt">concentrations</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23785068','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23785068"><span>Multi-plate freeze <span class="hlt">concentration</span>: Recovery of solutes occluded in the <span class="hlt">ice</span> and determination of thawing time.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Gulfo, Rafael; Auleda, Josep M; Moreno, Fabián Leonardo; Ruiz, Yolanda; Hernández, Eduard; Raventós, Mercè</p> <p>2014-09-01</p> <p>The retention of solutes in the <span class="hlt">ice</span> formed in a falling-film freeze <span class="hlt">concentrator</span> (multi-plate freeze-<span class="hlt">concentrator</span>) was analysed. Solutions of fructose, glucose and sucrose and a simulated juice with initial <span class="hlt">concentrations</span> of 5, 10, 15 and 20 °Brix were freeze <span class="hlt">concentrated</span>. The <span class="hlt">ice</span> produced in the four steps of the process retains solutes at levels of 1.0-8.8 °Brix (expressed as solute mass fraction in the <span class="hlt">ice</span>). The recovery of these solutes during thawing can increase overall system efficiency. All thawing steps were carried out dividing the sample in 10 fractions at 20 ℃. The first thawed fractions showed solute <span class="hlt">concentrations</span> that were 1.9-3.3 times higher than the mean solute mass fraction in the <span class="hlt">ice</span>, while the last fractions of <span class="hlt">ice</span> showed very low levels of retained solutes, less than 0.2 times the mean solute mass fraction in the <span class="hlt">ice</span>. It was found that fractionated thawing can recover most of the solute content in the <span class="hlt">ice</span>. The procedure presented in the present study allows the determination of the solute <span class="hlt">concentration</span> achieved in the various thawing fractions and predicts the thawing time required for a given form factor, melting temperature and initial solute mass fraction in the <span class="hlt">ice</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20150011077','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20150011077"><span>Verification of a New NOAA/NSIDC Passive Microwave Sea-<span class="hlt">Ice</span> <span class="hlt">Concentration</span> Climate Record</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Meier, Walter N.; Peng, Ge; Scott, Donna J.; Savoie, Matt H.</p> <p>2014-01-01</p> <p>A new satellite-based passive microwave sea-<span class="hlt">ice</span> <span class="hlt">concentration</span> product developed for the National Oceanic and Atmospheric Administration (NOAA)Climate Data Record (CDR) programme is evaluated via comparison with other passive microwave-derived estimates. The new product leverages two well-established <span class="hlt">concentration</span> algorithms, known as the NASA Team and Bootstrap, both developed at and produced by the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC). The sea <span class="hlt">ice</span> estimates compare well with similar GSFC products while also fulfilling all NOAA CDR initial operation capability (IOC) requirements, including (1) self describing file format, (2) ISO 19115-2 compliant collection-level metadata,(3) Climate and Forecast (CF) compliant file-level metadata, (4) grid-cell level metadata (data quality fields), (5) fully automated and reproducible processing and (6) open online access to full documentation with version control, including source code and an algorithm theoretical basic document. The primary limitations of the GSFC products are lack of metadata and use of untracked manual corrections to the output fields. Smaller differences occur from minor variations in processing methods by the National Snow and <span class="hlt">Ice</span> Data Center (for the CDR fields) and NASA (for the GSFC fields). The CDR <span class="hlt">concentrations</span> do have some differences from the constituent GSFC <span class="hlt">concentrations</span>, but trends and variability are not substantially different.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li class="active"><span>10</span></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_10 --> <div id="page_11" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li class="active"><span>11</span></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="201"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/22053829','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/22053829"><span>Control of <span class="hlt">ice</span> chromatographic retention mechanism by changing temperature and dopant <span class="hlt">concentration</span>.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Tasaki, Yuiko; Okada, Tetsuo</p> <p>2011-12-15</p> <p>A liquid phase coexists with solid water <span class="hlt">ice</span> in a typical binary system, such as NaCl-water, in the temperature range between the freezing point and the eutectic point (t(eu)) of the system. In <span class="hlt">ice</span> chromatography with salt-doped <span class="hlt">ice</span> as the stationary phase, both solid and liquid phase can contribute to solute retention in different fashions; that is, the solid <span class="hlt">ice</span> surface acts as an adsorbent, while a solute can be partitioned into the liquid phase. Thus, both adsorption and partition mechanisms can be utilized for <span class="hlt">ice</span> chromatographic separation. An important feature in this approach is that the liquid phase volume can be varied by changing the temperature and the <span class="hlt">concentration</span> of a salt incorporated into the <span class="hlt">ice</span> stationary phase. Thus, we can control the relative contribution from the partition mechanism in the entire retention because the liquid phase volume can be estimated from the freezing depression curve. Separation selectivity can thereby be modified. The applicability of this concept has been confirmed for the solutes of different adsorption and partition abilities. The predicted retention based on thermodynamics basically agrees well with the corresponding experimental retention. However, one important inconsistency has been found. The calculation predicts a step-like discontinuity of the solute retention at t(eu) because the phase diagram suggests that the liquid phase abruptly appears at t(eu) when the temperature increases. In contrast, the corresponding experimental plots are continuous over the wider range including the subeutectic temperatures. This discrepancy is explained by the existence of the liquid phase below t(eu). A difference between predicted and measured retention factors allows the estimation of the volume of the subeutectic liquid phase.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/18349223','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/18349223"><span>High hydrostatic pressure modification of whey protein <span class="hlt">concentrate</span> for improved body and texture of lowfat <span class="hlt">ice</span> cream.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Lim, S-Y; Swanson, B G; Ross, C F; Clark, S</p> <p>2008-04-01</p> <p>Previous research demonstrated that application of high hydrostatic pressure (HHP), particularly at 300 MPa for 15 min, can enhance foaming properties of whey protein <span class="hlt">concentrate</span> (WPC). The purpose of this research was to determine the practical impact of HHP-treated WPC on the body and texture of lowfat <span class="hlt">ice</span> cream. Washington State University (WSU)-WPC was produced by ultrafiltration of fresh separated whey received from the WSU creamery. Commercial whey protein <span class="hlt">concentrate</span> 35 (WPC 35) powder was reconstituted to equivalent total solids as WSU-WPC (8.23%). Three batches of lowfat <span class="hlt">ice</span> cream mix were produced to contain WSU-WPC without HHP, WSU-WPC with HHP (300 MPa for 15 min), and WPC 35 without HHP. All lowfat <span class="hlt">ice</span> cream mixes contained 10% WSU-WPC or WPC 35. Overrun and foam stability of <span class="hlt">ice</span> cream mixes were determined after whipping for 15 min. <span class="hlt">Ice</span> creams were produced using standard <span class="hlt">ice</span> cream ingredients and processing. The hardness of <span class="hlt">ice</span> creams was determined with a TA-XT2 texture analyzer. Sensory evaluation by balanced reference duo-trio test was carried out using 52 volunteers. The <span class="hlt">ice</span> cream mix containing HHP-treated WSU-WPC exhibited the greatest overrun and foam stability, confirming the effect of HHP on foaming properties of whey proteins in a complex system. <span class="hlt">Ice</span> cream containing HHP-treated WSU-WPC exhibited significantly greater hardness than <span class="hlt">ice</span> cream produced with untreated WSU-WPC or WPC 35. Panelists were able to distinguish between <span class="hlt">ice</span> cream containing HHP-treated WSU-WPC and <span class="hlt">ice</span> cream containing untreated WPC 35. Improvements of overrun and foam stability were observed when HHP-treated whey protein was used at a <span class="hlt">concentration</span> as low as 10% (wt/wt) in <span class="hlt">ice</span> cream mix. The impact of HHP on the functional properties of whey proteins was more pronounced than the impact on sensory properties.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C11C0785F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C11C0785F"><span>Estimating Trapped Gas <span class="hlt">Concentrations</span> as Bubbles Within Lake <span class="hlt">Ice</span> Using Ground Penetrating Radar</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Fantello, N.; Parsekian, A.; Walter Anthony, K. M.</p> <p>2015-12-01</p> <p>Climate warming is currently one of the most important issues that we are facing. The degradation of permafrost beneath thermokarst lakes has been associated with enhanced methane emissions and it presents a positive feedback to climate warming. Thermokarst lakes release methane to the atmosphere mainly by ebullition (bubbling) but there are a large number of uncertainties regarding the magnitude and variability of these emissions. Here we present a methodology to estimate the amount of gas released from thermokarst lakes through ebullition using ground-penetrating radar (GPR). This geophysical technique is well suited for this type of problem because it is non-invasive, continuous, and requires less effort and time than the direct visual inspection. We are studying GPR data collected using 1.2 GHz frequency antennas in Brooklyn Lake, Laramie, WY, in order to quantify the uncertainties in the method. Although this is not a thermokarst lake, gas bubbles are trapped in the <span class="hlt">ice</span> and spatial variability in bubble <span class="hlt">concentration</span> within the <span class="hlt">ice</span> is evident. To assess the variability in bulk physical properties of the <span class="hlt">ice</span> due to bubbles, we gathered GPR data from different types of <span class="hlt">ice</span>. We compared the velocity of the groundwave and reflection obtained from radargrams, and found on each case a larger value for the groundwave velocity suggesting a non-homogeneous medium and that the <span class="hlt">concentration</span> of bubbles is prone to be near the surface instead of at greater depths. We use a multi-phase dielectric-mixing model to estimate the amount of gas present in a sample of volume of <span class="hlt">ice</span> and found an uncertainty in relative permittivity (estimated using reflection velocity) of 0.0294, which translates to an uncertainty of 1.1% in gas content; and employing groundwave velocity we found 0.0712 and 2.9%, respectively. If locations of gas seeps in lakes could be detected and quantified using GPR along with field measurements, this could help to constrain future lake-source carbon gas</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015ACPD...1529125H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015ACPD...1529125H"><span>Unexpectedly high ultrafine aerosol <span class="hlt">concentrations</span> above East Antarctic sea-<span class="hlt">ice</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Humphries, R. S.; Klekociuk, A. R.; Schofield, R.; Keywood, M.; Ward, J.; Wilson, S. R.</p> <p>2015-10-01</p> <p>The effect of aerosols on clouds and their radiative properties is one of the largest uncertainties in our understanding of radiative forcing. A recent study has concluded that better characterisation of pristine, natural aerosol processes leads to the largest reduction in these uncertainties. Antarctica, being far from anthropogenic activities, is an ideal location for the study of natural aerosol processes. Aerosol measurements in Antarctica are often limited to boundary layer air-masses at spatially sparse coastal and continental research stations, with only a handful of studies in the sea <span class="hlt">ice</span> region. In this paper, the first observational study of sub-micron aerosols in the East Antarctic sea <span class="hlt">ice</span> region is presented. Measurements were conducted aboard the <span class="hlt">ice</span>-breaker Aurora Australis in spring 2012 and found that boundary layer condensation nuclei (CN3) <span class="hlt">concentrations</span> exhibited a five-fold increase moving across the Polar Front, with mean Polar Cell <span class="hlt">concentrations</span> of 1130 cm-3 - higher than any observed elsewhere in the Antarctic and Southern Ocean region. The absence of evidence for aerosol growth suggested that nucleation was unlikely to be local. Air parcel trajectories indicated significant influence from the free troposphere above the Antarctic continent, implicating this as the likely nucleation region for surface aerosol, a similar conclusion to previous Antarctic aerosol studies. The highest aerosol <span class="hlt">concentrations</span> were found to correlate with low pressure systems, suggesting that the passage of cyclones provided an accelerated pathway, delivering air-masses quickly from the free-troposphere to the surface. After descent from the Antarctic free troposphere, trajectories suggest that sea <span class="hlt">ice</span> boundary layer air-masses travelled equator-ward into the low albedo Southern Ocean region, transporting with them emissions and these aerosol nuclei where, after growth, may potentially impact on the region's radiative balance. The high aerosol <span class="hlt">concentrations</span> and</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23772704','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23772704"><span>Effects of locust bean gum and mono- and diglyceride <span class="hlt">concentrations</span> on particle size and melting rates of <span class="hlt">ice</span> cream.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Cropper, S L; Kocaoglu-Vurma, N A; Tharp, B W; Harper, W J</p> <p>2013-06-01</p> <p>The objective of this study was to determine how varying <span class="hlt">concentrations</span> of the stabilizer, locust bean gum (LBG), and different levels of the emulsifier, mono- and diglycerides (MDGs), influenced fat aggregation and melting characteristics of <span class="hlt">ice</span> cream. <span class="hlt">Ice</span> creams were made containing MDGs and LBG singly and in combination at <span class="hlt">concentrations</span> ranging between 0.0% to 0.14% and 0.0% to 0.23%, respectively. Particle size analysis, conducted on both the mixes and <span class="hlt">ice</span> cream, and melting rate testing on the <span class="hlt">ice</span> cream were used to determine fat aggregation. No significant differences (P < 0.05) were found between particle size values for experimental <span class="hlt">ice</span> cream mixes. However, higher <span class="hlt">concentrations</span> of both LBG and MDG in the <span class="hlt">ice</span> creams resulted in values that were larger than the control. This study also found an increase in the particle size values when MDG levels were held constant and LBG amounts were increased in the <span class="hlt">ice</span> cream. <span class="hlt">Ice</span> creams with higher <span class="hlt">concentrations</span> of MDG and LBG together had the greatest difference in the rate of melting than the control. The melting rate decreased with increasing LBG <span class="hlt">concentrations</span> at constant MDG levels. These results illustrated that fat aggregation may not only be affected by emulsifiers, but that stabilizers may play a role in contributing to the destabilization of fat globules.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007AGUFM.A53B1146B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007AGUFM.A53B1146B"><span>Singlet Molecular Oxygen on <span class="hlt">Ice</span>: Rates of Formation and Steady State <span class="hlt">Concentrations</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bower, J. P.; Anastasio, C.</p> <p>2007-12-01</p> <p>Singlet molecular oxygen (1O2*), the first electronically excited state of molecular oxygen, reacts rapidly with certain types of environmental pollutants such as furans, phenols, and polycyclic aromatic hydrocarbons (PAHs). Its formation requires the absorption of light by a chromophore (a.k.a. sensitizer), which subsequently transfers energy to ground state molecular oxygen. In the environment, 1O2* chemistry has been studied primarily in the aqueous phase, such as in surface waters or cloud and fog drops. In this work, we expand our current understanding by investigating the rate of formation (Rf) and steady state <span class="hlt">concentration</span> ([1O2*]) of 1O2* on <span class="hlt">ice</span>. To investigate 1O2* kinetics, we use a chemical probe technique in which photoformed 1O2* reacts with furfuryl alcohol (FFA). To generate 1O2*, we illuminated frozen samples containing a sensitizer (Rose Bengal, RB) at 549 nm. The <span class="hlt">concentration</span> of total solutes in each sample was controlled using sodium sulfate (Na2SO4). Following illumination, the decay of FFA was measured using high performance liquid chromatography (HPLC). <span class="hlt">Ice</span> tests were conducted at 253, 263, and 268 K. Liquid tests for comparison were conducted at 278 K. Results showed dramatically faster (~104) FFA decay on <span class="hlt">ice</span> than in liquid samples prepared from the same solutions, in agreement with the calculated solute <span class="hlt">concentration</span> factor in the quasi-liquid layer (QLL) on <span class="hlt">ice</span> compared to bulk solution. Varying the <span class="hlt">concentration</span> of RB resulted in similar changes in both Rf and [1O2*], with magnitudes of change close to those expected. Changing temperature and total solutes, both of which control the volume of the QLL on <span class="hlt">ice</span>, revealed two model regimes: FFA as a major (1) or minor (2) sink of 1O2*. Experimental results from the former regime show good agreement with expected values for both Rf and [1O2*]. Experiments in the later regime are currently in progress. We will also discuss the potential implications of 1O2* to the chemistry of naturally</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.2924G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.2924G"><span>Detection and Analysis of High <span class="hlt">Ice</span> <span class="hlt">Concentration</span> Events and Supercooled Drizzle from IAGOS Commercial Aircraft</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gallagher, Martin; Baumgardner, Darrel; Lloyd, Gary; Beswick, Karl; Freer, Matt; Durant, Adam</p> <p>2016-04-01</p> <p>Hazardous encounters with high <span class="hlt">ice</span> <span class="hlt">concentrations</span> that lead to temperature and airspeed sensor measurement errors, as well as engine rollback and flameout, continue to pose serious problems for flight operations of commercial air carriers. Supercooled liquid droplets (SLD) are an additional hazard, especially for smaller commuter aircraft that do not have sufficient power to fly out of heavy <span class="hlt">icing</span> conditions or heat to remove the <span class="hlt">ice</span>. New regulations issued by the United States and European regulatory agencies are being implemented that will require aircraft below a certain weight class to carry sensors that will detect and warn of these types of <span class="hlt">icing</span> conditions. Commercial aircraft do not currently carry standard sensors to detect the presence of <span class="hlt">ice</span> crystals in high <span class="hlt">concentrations</span> because they are typical found in sizes that are below the detection range of aircraft weather radar. Likewise, the sensors that are currently used to detect supercooled water do not respond well to drizzle-sized drops. Hence, there is a need for a sensor that can fill this measurement void. In addition, the forecast models that are used to predict regions of <span class="hlt">icing</span> rely on pilot observations as the only means to validate the model products and currently there are no forecasts for the prevalence of high altitude <span class="hlt">ice</span> crystals. Backscatter Cloud Probes (BCP) have been flying since 2011 under the IAGOS project on six Airbus commercial airliners operated by Lufthansa, Air France, China Air, Iberia and Cathay Pacific, and measure cloud droplets, <span class="hlt">ice</span> crystals and aerosol particles larger than 5 μm. The BCP can detect these particles and measures an optical equivalent diameter (OED) but is not able to distinguish the type of particle, i.e. whether they are droplets, <span class="hlt">ice</span> crystals, dust or ash. However, some qualification can be done based on measured temperature to discriminate between liquid water and <span class="hlt">ice</span>. The next generation BCP (BCPD, Backscatter Cloud Probe with polarization detection) is</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008JGRC..113.6008N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008JGRC..113.6008N"><span>Bulk heat transfer coefficient in the <span class="hlt">ice</span>-upper ocean system in the <span class="hlt">ice</span> melt season derived from <span class="hlt">concentration</span>-temperature relationship</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Nihashi, Sohey; Ohshima, Kay I.</p> <p>2008-06-01</p> <p>The bulk heat transfer coefficient in the <span class="hlt">ice</span>-upper ocean system (Kb) in the <span class="hlt">ice</span> melt season is estimated by a new method at 18 areas that cover much of the Antarctic seasonal <span class="hlt">ice</span> zone. The method is based on a model in which <span class="hlt">ice</span> melting is caused only by heat input through open water and is treated in a bulk fashion in the <span class="hlt">ice</span>-upper ocean system. Kb is estimated by fitting a convergent curve derived from the model to an observed <span class="hlt">ice</span> <span class="hlt">concentration</span>-temperature plot (CT-plot). Estimated Kb is 1.15 ± 0.72 × 10-4 m s-1 on average. If Kb can be expressed by the product of the heat transfer coefficient (ch) and the friction velocity (uτ), ch is 0.0113 ± 0.0055. This value is about two times larger than that estimated at the <span class="hlt">ice</span> bottom. The relationship between Kb and the geostrophic wind speed (Uw), which is roughly proportional to uτ, shows a significant positive correlation, as expected. Further, Kb seems more likely to be proportional to the square or cube of Uw rather than a linear relationship. Since Kb estimated from our method is associated with <span class="hlt">ice</span> melting in a bulk fashion in the <span class="hlt">ice</span>-upper ocean system, this relationship likely indicates both the mixing process of heat in the upper ocean (proportional to uτ3) and the local heat transfer process at the <span class="hlt">ice</span>-ocean interface (proportional to uτ).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014TCD.....8.1517K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014TCD.....8.1517K"><span>About uncertainties in sea <span class="hlt">ice</span> thickness retrieval from satellite radar altimetry: results from the ESA-CCI Sea <span class="hlt">Ice</span> ECV Project Round Robin Exercise</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kern, S.; Khvorostovsky, K.; Skourup, H.; Rinne, E.; Parsakhoo, Z. S.; Djepa, V.; Wadhams, P.; Sandven, S.</p> <p>2014-03-01</p> <p>One goal of the European Space Agency Climate Change Initiative sea <span class="hlt">ice</span> Essential Climate Variable project is to provide a quality controlled 20 year long data set of Arctic Ocean winter-time sea <span class="hlt">ice</span> thickness distribution. An important step to achieve this goal is to assess the accuracy of sea <span class="hlt">ice</span> thickness retrieval based on satellite radar altimetry. For this purpose a data base is created comprising sea <span class="hlt">ice</span> freeboard derived from satellite radar altimetry between 1993 and 2012 and collocated observations of snow and sea <span class="hlt">ice</span> freeboard from Operation <span class="hlt">Ice</span> Bridge (OIB) and CryoSat Validation Experiment (CryoVEx) air-borne campaigns, of sea <span class="hlt">ice</span> draft from moored and submarine Upward Looking Sonar (ULS), and of snow depth from OIB campaigns, Advanced Microwave Scanning Radiometer aboard EOS (<span class="hlt">AMSR-E</span>) and the Warren Climatology (Warren et al., 1999). An inter-comparison of the snow depth data sets stresses the limited usefulness of Warren climatology snow depth for freeboard-to-thickness conversion under current Arctic Ocean conditions reported in other studies. This is confirmed by a comparison of snow freeboard measured during OIB and CryoVEx and snow freeboard computed from radar altimetry. For first-year <span class="hlt">ice</span> the agreement between OIB and <span class="hlt">AMSR-E</span> snow depth within 0.02 m suggests <span class="hlt">AMSR-E</span> snow depth as an appropriate alternative. Different freeboard-to-thickness and freeboard-to-draft conversion approaches are realized. The mean observed ULS sea <span class="hlt">ice</span> draft agrees with the mean sea <span class="hlt">ice</span> draft computed from radar altimetry within the uncertainty bounds of the data sets involved. However, none of the realized approaches is able to reproduce the seasonal cycle in sea <span class="hlt">ice</span> draft observed by moored ULS satisfactorily. A sensitivity analysis of the freeboard-to-thickness conversion suggests: in order to obtain sea <span class="hlt">ice</span> thickness as accurate as 0.5 m from radar altimetry, besides a freeboard estimate with centimetre accuracy, an <span class="hlt">ice</span>-type dependent sea <span class="hlt">ice</span> density is as mandatory</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017TCry...11...47D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017TCry...11...47D"><span>Satellite microwave assessment of Northern Hemisphere lake <span class="hlt">ice</span> phenology from 2002 to 2015</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Du, Jinyang; Kimball, John S.; Duguay, Claude; Kim, Youngwook; Watts, Jennifer D.</p> <p>2017-01-01</p> <p>A new automated method enabling consistent satellite assessment of seasonal lake <span class="hlt">ice</span> phenology at 5 km resolution was developed for all lake pixels (water coverage ≥ 90 %) in the Northern Hemisphere using 36.5 GHz H-polarized brightness temperature (Tb) observations from the Advanced Microwave Scanning Radiometer for EOS and Advanced Microwave Scanning Radiometer 2 (<span class="hlt">AMSR-E</span>/2) sensors. The lake phenology metrics include seasonal timing and duration of annual <span class="hlt">ice</span> cover. A moving t test (MTT) algorithm allows for automated lake <span class="hlt">ice</span> retrievals with daily temporal fidelity and 5 km resolution gridding. The resulting <span class="hlt">ice</span> phenology record shows strong agreement with available ground-based observations from the Global Lake and River <span class="hlt">Ice</span> Phenology Database (95.4 % temporal agreement) and favorable correlations (R) with alternative <span class="hlt">ice</span> phenology records from the Interactive Multisensor Snow and <span class="hlt">Ice</span> Mapping System (R = 0.84 for water clear of <span class="hlt">ice</span> (WCI) dates; R = 0.41 for complete freeze over (CFO) dates) and Canadian <span class="hlt">Ice</span> Service (R = 0.86 for WCI dates; R = 0.69 for CFO dates). Analysis of the resulting 12-year (2002-2015) <span class="hlt">AMSR-E</span>/2 <span class="hlt">ice</span> record indicates increasingly shorter <span class="hlt">ice</span> cover duration for 43 out of 71 (60.6 %) Northern Hemisphere lakes examined, with significant (p < 0.05) regional trends toward earlier <span class="hlt">ice</span> melting for only five lakes. Higher-latitude lakes reveal more widespread and larger trends toward shorter <span class="hlt">ice</span> cover duration than lower-latitude lakes, consistent with enhanced polar warming. This study documents a new satellite-based approach for rapid assessment and regional monitoring of seasonal <span class="hlt">ice</span> cover changes over large lakes, with resulting accuracy suitable for global change studies.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2000NIMPB.172..847S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2000NIMPB.172..847S"><span>7Be and 10Be <span class="hlt">concentrations</span> in recent firn and <span class="hlt">ice</span> at Law Dome, Antarctica</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Smith, A. M.; Fink, D.; Child, D.; Levchenko, V. A.; Morgan, V. I.; Curran, M.; Etheridge, D. M.; Elliott, G.</p> <p>2000-10-01</p> <p>Over the past three years, the Australian National Tandem for Applied Research (ANTARES) AMS facility at ANSTO has been expanding its sample preparation and measurement capability, particularly for 10Be, 26Al and 36Cl. During this time, ANSTO has continued its collaboration with the AAD and CSIRO Atmospheric Research on the measurement of cosmogenic isotopes from Law Dome, Antarctica. This research program has been supported by the construction of a dedicated geochemistry laboratory for the processing of <span class="hlt">ice</span> and rock samples for the preparation of AMS targets. Here we present our first results for 10Be <span class="hlt">concentrations</span> measured in <span class="hlt">ice</span> cores from three sites at Law Dome and describe the sample processing protocol and aspects of the AMS measurement procedure. These sites are characterised by an eightfold difference in accumulation rate with a common precipitation source. In combination with an established <span class="hlt">ice</span> chronology, this has enabled some preliminary findings concerning the relationship between the snow accumulation rate and the measured 10Be <span class="hlt">concentration</span> for Law Dome during recent times. Additionally, we present 7Be and 10Be/ 7Be measurements made for a few surface snow samples from Law Dome and Australia.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AtmEn..89..683K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AtmEn..89..683K"><span>Recent increase in Ba <span class="hlt">concentrations</span> as recorded in a South Pole <span class="hlt">ice</span> core</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Korotkikh, Elena V.; Mayewski, Paul A.; Dixon, Daniel; Kurbatov, Andrei V.; Handley, Michael J.</p> <p>2014-06-01</p> <p>Here we present high-resolution (∼9.4 samples/year) records of Ba <span class="hlt">concentrations</span> for the period from 1541 to 1999 A.D. obtained from an <span class="hlt">ice</span> core recovered at the South Pole (US ITASE-02-6) site. We note a significant increase in Ba <span class="hlt">concentration</span> (by a factor of ∼23) since 1980 A.D. The Ba crustal enrichment factor (EFc) values rise from ∼3 before 1980 A.D. to ∼32 after 1980 A.D. None of the other measured major and trace elements reveal such significant increases in <span class="hlt">concentrations</span> and EFc values. Comparison with previously reported Antarctic Ba records suggests that significant increases in Ba <span class="hlt">concentrations</span> at South Pole since 1980 A.D. are most likely caused by local source pollution. The core was collected in close proximity to Amundsen-Scott South Pole Station; therefore activities at the station, such as diesel fuel burning and intense aircraft activity, most likely caused the observed increase in Ba <span class="hlt">concentrations</span> and its EFc values in the South Pole <span class="hlt">ice</span> core record.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2004AGUFM.C41A0189M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2004AGUFM.C41A0189M"><span>A Record of Dissolved Metal <span class="hlt">Concentrations</span> in the Lena River During the Period of <span class="hlt">Ice</span> Breakup</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Monson, O. D.; Guay, C. K.; Holmes, R. M.; Zhulidov, A. V.</p> <p>2004-12-01</p> <p>The PARTNERS project is a 5-year research program (2002-2007) funded by the Arctic System Science Program of the U.S. National Science Foundation. The objective of the PARTNERS project is to measure several biogeochemical parameters in the six largest rivers that drain the watershed of the Arctic Ocean (Yenisey, Lena, Ob, Mackenzie, Yukon, and Kolyma) as a means to study the origins and fates of continental runoff. As part of the PARTNERS field program for 2004, samples were collected on the Lena River in the spring (May-June) during the period of peak discharge and <span class="hlt">ice</span> breakup. Samples were collected from the bank at the town of Zhigansk (66.75 N, 23.38 E) once daily from May 28th through June 7th, 2004. The river was completely <span class="hlt">ice</span> covered at the beginning of this period. The river level rose dramatically each day until <span class="hlt">ice</span> breakup, which occurred on May 30th. Following breakup, the river level began to drop steadily. Visual observation of daily water samples indicated a darkening of the tannic brown color of the river water as discharge levels increased up until breakup, suggesting an increase in DOC <span class="hlt">concentrations</span> associated with the peak discharge and <span class="hlt">ice</span> breakup period. Water samples for metals analyses were syringe filtered in the field through 0.45 um polypropylene and 0.02 um Anotop filter discs and acidified under clean conditions upon return to the laboratory. The samples were analyzed by high-resolution ICPMS for a suite of metals including Ba, Cd, Ce, Co, Cr, Cs, Cu, Fe, Li, Mn, Mo, Ni, Pb, Rb, Re, Sr, Tl, U, V, and Zn. Here we report the results from these analyses as a daily time series of metal <span class="hlt">concentrations</span> bracketing the <span class="hlt">ice</span> breakup and peak discharge events. During this relatively short amount of time, significant fluctuations in metal <span class="hlt">concentrations</span> were observed, which are likely related to concurrent fluctuations in DOC <span class="hlt">concentrations</span> and other changes in river chemistry occurring during this dynamic period of the annual hydrologic cycle in</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013ACPD...13.1767H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013ACPD...13.1767H"><span>High <span class="hlt">concentrations</span> of biological aerosol particles and <span class="hlt">ice</span> nuclei during and after rain</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Huffman, J. A.; Pöhlker, C.; Prenni, A. J.; DeMott, P. J.; Mason, R. H.; Robinson, N. H.; Fröhlich-Nowoisky, J.; Tobo, Y.; Després, V. R.; Garcia, E.; Gochis, D. J.; Harris, E.; Müller-Germann, I.; Ruzene, C.; Schmer, B.; Sinha, B.; Day, D. A.; Andreae, M. O.; Jimenez, J. L.; Gallagher, M.; Kreidenweis, S. M.; Bertram, A. K.; Pöschl, U.</p> <p>2013-01-01</p> <p>Bioaerosols are relevant for public health and may play an important role in the climate system, but their atmospheric abundance, properties and sources are not well understood. Here we show that the <span class="hlt">concentration</span> of airborne biological particles in a forest ecosystem increases dramatically during rain and that bioparticles are closely correlated with atmospheric <span class="hlt">ice</span> nuclei (IN). The greatest increase of bioparticles and IN occurred in the size range of 2-6 μm, which is characteristic for bacterial aggregates and fungal spores. By DNA analysis we found high diversities of airborne bacteria and fungi, including human and plant pathogens (mildew, smut and rust fungi, molds, Enterobacteraceae, Pseudomonadaceae). In addition to known bacterial and fungal IN (Pseudomonas sp., Fusarium sporotrichioides), we discovered two species of IN-active fungi that were not previously known as biological <span class="hlt">ice</span> nucleators (Isaria farinosa and Acremonium implicatum). Our findings suggest that atmospheric bioaerosols, IN and rainfall are more tightly coupled than previously assumed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..15.5514H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..15.5514H"><span>High <span class="hlt">concentrations</span> of biological aerosol particles and <span class="hlt">ice</span> nuclei during and after rain</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Huffman, J. Alex; Pöhlker, Christopher; Prenni, Anthony; DeMott, Paul; Mason, Ryan; Robinson, Niall; Fröhlich-Nowoisky, Janine; Tobo, Yutaka; Després, Viviane; Garcia, Elvin; Gochis, David; Sinha, Bärbel; Day, Douglas; Andreae, Meinrat; Jimenez, Jose; Gallagher, Martin; Kreidenweis, Sonia; Bertram, Allan; Pöschl, Ulrich</p> <p>2013-04-01</p> <p>Bioaerosols are relevant for public health and may play an important role in the climate system, but their atmospheric abundance, properties and sources are not well understood. Here we show that the <span class="hlt">concentration</span> of airborne biological particles in a forest ecosystem increases dramatically during rain and that bioparticles are closely correlated with atmospheric <span class="hlt">ice</span> nuclei (IN). The greatest increase of bioparticles and IN occurred in the size range of 2-6 µm, which is characteristic for bacterial aggregates and fungal spores. By DNA analysis we found high diversities of airborne bacteria and fungi, including human and plant pathogens (mildew, smut and rust fungi, molds, Enterobacteraceae, Pseudomonadaceae). In addition to known bacterial and fungal IN (Pseudomonas sp., Fusarium sporotrichioides), we discovered two species of IN-active fungi that were not previously known as biological <span class="hlt">ice</span> nucleators (Isaria farinosa and Acremonium implicatum). Our findings suggest that atmospheric bioaerosols, IN and rainfall are more tightly coupled than previously assumed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19820009689','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19820009689"><span>Satellite-derived <span class="hlt">ice</span> data sets no. 1: Antarctic monthly average microwave brightness temperatures and sea-<span class="hlt">ice</span> <span class="hlt">concentrations</span>, 1973 - 1976</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Zwally, H. J.</p> <p>1981-01-01</p> <p>A summary data set concerning 4 years of Antarctic sea-<span class="hlt">ice</span> conditions was created and is available on magnetic tape. The data were derived from electrically scanning microwave radiometer brightness temperatures and were mapped into a polar stereographic grid enclosing the 50 deg S latitude circle. The grid size varies from about 32 by 32 sq km at the poles to about 28 by 28 sq km at 50 deg S. The microwave brightness temperatures of Antarctic sea <span class="hlt">ice</span> are predominantly characteristic of first-year <span class="hlt">ice</span> with an emissivity of 0.92 at 19 GHz frequency. Sea <span class="hlt">ice</span> <span class="hlt">concentrations</span> were calculated from the brightness temperature data for each grid element with an algorithm that uses an emissivity value of 0.92 and an <span class="hlt">ice</span> physical temperature estimate from climatological surface air temperatures. Monthly, multiyear monthly, and yearly maps of brightness temperatures and sea <span class="hlt">ice</span> <span class="hlt">concentrations</span> were created for the 4 years, except for 7 months for which useable data were insufficient.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFM.P21B1223L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFM.P21B1223L"><span>Laboratory measurements of <span class="hlt">ice</span> tensile strength dependence on density and <span class="hlt">concentration</span> of silicate and polymer impurities at low temperatures</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Litwin, K. L.; Beyeler, J. D.; Polito, P. J.; Zygielbaum, B. R.; Sklar, L. S.; Collins, G. C.</p> <p>2009-12-01</p> <p>The tensile strength of <span class="hlt">ice</span> bedrock on Titan should strongly influence the effectiveness of the erosional processes responsible for carving the extensive fluvial drainage networks and other surface features visible in images returned by the Cassini and Huygens probes. Recent measurements of the effect of temperature on the tensile strength of low-porosity, polycrystalline <span class="hlt">ice</span>, without impurities, suggest that <span class="hlt">ice</span> bedrock at the Titan surface temperature of 93 K may be as much as five times stronger than <span class="hlt">ice</span> at terrestrial surface temperatures. However, <span class="hlt">ice</span> bedrock on Titan and other outer solar system bodies may have significant porosity, and impurities such silicates or polymers are possible in such <span class="hlt">ices</span>. In this laboratory investigation we are exploring the dependence of tensile strength on the density and <span class="hlt">concentration</span> of impurities, for polycrystalline <span class="hlt">ice</span> across a wide range of temperatures. We use the Brazilian tensile splitting test to measure strength, and control temperature with dry <span class="hlt">ice</span> and liquid nitrogen. The 50 mm diameter <span class="hlt">ice</span> cores are made from a log-normally distributed seed crystal mixture with a median size of 1.4 mm. To control <span class="hlt">ice</span> density and porosity we vary the packing density of the seed grains in core molds and vary the degree of saturation of the matrix with added near-freezing distilled water. We also vary <span class="hlt">ice</span> density by blending in a similarly-sized mixture of angular fragments of two types of impurities, a fine-grained volcanic rock and a polyethylene polymer. Because both types of impurities have greater tensile strength than <span class="hlt">ice</span> at Earth surface temperatures, we expect higher <span class="hlt">concentrations</span> of impurities to correlate with increased strength for <span class="hlt">ice</span>-rock and <span class="hlt">ice</span>-polymer mixtures. However, at the ultra-cold temperatures of the outer planets, we expect significant divergence in the temperature dependence of <span class="hlt">ice</span> tensile strength for the various mixtures and resulting densities. These measurements will help constrain the range of possible</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFMPP22A..08M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFMPP22A..08M"><span>Recent and past dust <span class="hlt">concentrations</span> and fluxes from a developing array of Antarctic <span class="hlt">ice</span> cores</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>McConnell, J. R.; Anschütz, H.; Baggenstos, D.; Das, S. B.; Isaksson, E. D.; Lawrence, R.; Layman, L.; Maselli, O.; Severinghaus, J. P.; Sigl, M.; Petit, J. R.; Grente, B.</p> <p>2012-12-01</p> <p>Continental dust is an important component of climate forcing, both because of its interaction with incoming solar and outgoing long wave radiation and because of its impact on albedo when deposited on bright surfaces such as fresh snow. Continental dust may also play an important role in ocean fertilization and carbon sequestration. Because the lifetime of dust aerosol in the atmosphere is only on the order of days to weeks, spatial and temporal variability in <span class="hlt">concentrations</span> and fluxes is high and understanding of recent and long term changes is limited. Here we present and discuss detailed continuous, high depth resolution measurements of a range of dust proxies in a developing array of Antarctic <span class="hlt">ice</span> cores. Included are traditional proxies such as non-sea-salt (nss) calcium and insoluble particle number and size distribution as well as less traditional proxies such as aluminum, vanadium, manganese, rare earth elements, and nss uranium which together provide important insights into how dust sources and transport may have changed in the past. The array includes a number of new shallow <span class="hlt">ice</span> core records from East and West Antarctica spanning recent centuries to millennia, as well as Last Glacial Maximum to early Holocene records from the deep WAIS Divide and Taylor Glacier Horizontal <span class="hlt">ice</span> cores.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016ISPAr41B8..459C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016ISPAr41B8..459C"><span>Forecasting Antarctic Sea <span class="hlt">Ice</span> <span class="hlt">Concentrations</span> Using Results of Temporal Mixture Analysis</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Chi, Junhwa; Kim, Hyun-Cheol</p> <p>2016-06-01</p> <p>Sea <span class="hlt">ice</span> <span class="hlt">concentration</span> (SIC) data acquired by passive microwave sensors at daily temporal frequencies over extended areas provide seasonal characteristics of sea <span class="hlt">ice</span> dynamics and play a key role as an indicator of global climate trends; however, it is typically challenging to study long-term time series. Of the various advanced remote sensing techniques that address this issue, temporal mixture analysis (TMA) methods are often used to investigate the temporal characteristics of environmental factors, including SICs in the case of the present study. This study aims to forecast daily SICs for one year using a combination of TMA and time series modeling in two stages. First, we identify temporally meaningful sea <span class="hlt">ice</span> signatures, referred to as temporal endmembers, using machine learning algorithms, and then we decompose each pixel into a linear combination of temporal endmembers. Using these corresponding fractional abundances of endmembers, we apply a autoregressive model that generally fits all Antarctic SIC data for 1979 to 2013 to forecast SIC values for 2014. We compare our results using the proposed approach based on daily SIC data reconstructed from real fractional abundances derived from a pixel unmixing method and temporal endmember signatures. The proposed method successfully forecasts new fractional abundance values, and the resulting images are qualitatively and quantitatively similar to the reference data.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27344387','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27344387"><span>Whey protein phospholipid <span class="hlt">concentrate</span> and delactosed permeate: Applications in caramel, <span class="hlt">ice</span> cream, and cake.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Levin, M A; Burrington, K J; Hartel, R W</p> <p>2016-09-01</p> <p>Whey protein phospholipid <span class="hlt">concentrate</span> (WPPC) and delactosed permeate (DLP) are 2 coproducts of cheese whey processing that are currently underutilized. Past research has shown that WPPC and DLP can be used together as a functional dairy ingredient in foods such as <span class="hlt">ice</span> cream, soup, and caramel. However, the scope of the research has been limited to a single WPPC supplier. The variability of the composition and functionality of WPPC was previously studied. The objective of this research was to expand on the previous study and examine the potential applications of WPPC and DLP blends in foods. In <span class="hlt">ice</span> cream, WPPC was added as a natural emulsifier to replace synthetic emulsifiers. The WPPC decreased the amount of partially coalesced fat and increased the drip-through rate. In caramel, DLP and WPPC replaced sweetened condensed skim milk and lecithin. Cold flow increased significantly, and hardness and stickiness decreased. In cake, DLP and WPPC were added as a total replacement of eggs, with no change in yield, color, or texture. Overall, WPPC and DLP can be utilized as functional dairy ingredients at a lower cost in <span class="hlt">ice</span> cream and cake but not in chewy caramel.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li class="active"><span>11</span></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_11 --> <div id="page_12" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li class="active"><span>12</span></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="221"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19950048007&hterms=high+resolution+melt&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dhigh%2Bresolution%2Bmelt','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19950048007&hterms=high+resolution+melt&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dhigh%2Bresolution%2Bmelt"><span>Arctic sea <span class="hlt">ice</span> <span class="hlt">concentrations</span> from special sensor microwave imager and advanced very high resolution radiometer satellite data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Emery, W. J.; Fowler, C.; Maslanik, J.</p> <p>1994-01-01</p> <p>Nearly coincident data from the special sensor microwave imager (SSM/I) and the advanced very high resolution radiometer (AVHRR) are used to compute and compare Arctic sea <span class="hlt">ice</span> <span class="hlt">concentrations</span> for different regions and times of the year. To help determine overall accuracies and to highlight sources of differences between passive microwave, optical wavelength, and thermal wavelength data, <span class="hlt">ice</span> <span class="hlt">concentrations</span> are estimated using two operational SSM/I <span class="hlt">ice</span> <span class="hlt">concentration</span> algorithms and with visible- and thermal-infrared wavelength AVHRR data. All algorithms capture the seasonal patterns of <span class="hlt">ice</span> growth and melt. The ranges of differences fall within the general levels of uncertainty expected for each method and are similar to previous accuracy estimates. The estimated <span class="hlt">ice</span> <span class="hlt">concentrations</span> are all highly correlated, with uniform biases, although differences between individual pairs of observations can be large. On average, the NASA Team algorithm yielded 5% higher <span class="hlt">ice</span> <span class="hlt">concentrations</span> than the Bootstrap algorithm, while during nonmelt periods the two SSM/I algorithms agree to within 0.5%. These seasonal differences are consistent with the ways that the 19-GHz and 37-GHz microwave channels are used in the algorithms. When compared to the AVHRR-derived <span class="hlt">ice</span> <span class="hlt">concentrations</span>, the Team-algorithm results are more similar on average in terms of correlation and mean differences. However, the Team algorithm underestimates <span class="hlt">concentrations</span> relative to the AVHRR output by 6% during cold months and overestimates by 3% during summer. Little seasonal difference exists between the Bootstrap and AVHRR results, with a mean difference of about 5%. Although the mean differences are less between the SSM/I-derived <span class="hlt">concentrations</span> and <span class="hlt">concentrations</span> estimated using AVHRR channel 1, the correlations appear substantially better between the SSM/I data and <span class="hlt">concentrations</span> derived from AVHRR channel 4, particularly for the Team algorithm output.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFM.B13D0545S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFM.B13D0545S"><span>Sensitivity of Oxygen Isotopes of Sulfate in <span class="hlt">Ice</span> Cores to Past Changes in Atmospheric Oxidant <span class="hlt">Concentrations</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sofen, E. D.; Alexander, B.; Kunasek, S. A.; Mickley, L.; Murray, L. T.; Kaplan, J. O.</p> <p>2009-12-01</p> <p>The oxygen isotopic composition (Δ17O) of sulfate from <span class="hlt">ice</span> cores allows for a quantitative assessment of the past oxidative capacity of the atmosphere, which has implications for the lifetime of pollutants (e.g. CO) and greenhouse gases (e.g. CH4), and changes in the sulfur budget on various timescales. Using Δ17O of sulfate measurements from the WAIS-Divide, Antarctica and Site-A, Greenland <span class="hlt">ice</span> cores as constraints, we use the GEOS-Chem global three-dimensional chemical transport model to study changes in the <span class="hlt">concentrations</span> of OH, O3, and H2O2 and their impact on sulfate Δ17O between the preindustrial and present-day. The Greenland <span class="hlt">ice</span> core sulfate oxygen isotope observations are insensitive to changes in oxidant <span class="hlt">concentrations</span> on the preindustrial-industrial timescale due to the rising importance of metal catalyzed S(IV) oxidation in mid- to high-northern latitudes resulting from anthropogenic metal emissions. The small change in Antarctic <span class="hlt">ice</span> core sulfate Δ17O observations on this timescale is consistent with simultaneous increases in boundary layer O3 (32%) and H2O2 (49%) <span class="hlt">concentrations</span> in the Southern Hemisphere, which have opposing effects on the sulfate O-isotope anomaly. Sulfate Δ17O is insensitive to the relatively small (-12%) decrease in Southern Hemisphere OH <span class="hlt">concentrations</span> on this timescale due to the dominance of in-cloud versus gas-phase formation of sulfate in the mid-to-high southern latitudes. We find that the fraction of sulfate formed globally through gas-phase oxidation has not changed substantially between preindustrial and present times, however the total amount of sulfate formed in the gas-phase has nearly quadrupled due to rising anthropogenic emissions of sulfur dioxide. Measurements over a glacial-interglacial cycle from the Vostok core indicate dramatic changes in the Δ17O of sulfate on this timescale, which provide a strong constraint for glacial-era atmospheric chemistry modeling efforts. We will present preliminary results of</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.C23A0482H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.C23A0482H"><span>Modeled methanesulfonic acid (MSA) <span class="hlt">concentrations</span> in Antarctica: the influence of meteorology in explaining modern versus LGM differences in <span class="hlt">ice</span> cores</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hezel, P. J.; Alexander, B.; Bitz, C. M.; Steig, E. J.</p> <p>2011-12-01</p> <p>Methanesulfonic acid (MSA) <span class="hlt">concentrations</span> measured in <span class="hlt">ice</span> cores in Antarctica for the last glacial maximum (LGM) are higher than modern day <span class="hlt">concentrations</span> on the East Antarctic Plateau (Vostok), but are lower than modern <span class="hlt">concentrations</span> in West Antarctica (Siple Dome). MSA <span class="hlt">concentrations</span> measured in <span class="hlt">ice</span> cores have been interpreted as an indicator of both local sea <span class="hlt">ice</span> extent (via modulation of dimethylsulfide (DMS) emissions) and regional circulation on decadal time scales, but there has been no assessment of the importance of these two processes in determining MSA <span class="hlt">concentrations</span> on glacial-interglacial time scales. Explanations for the modern - LGM MSA differences at Vostok invoke increased DMS emissions caused by increased dust fertilization in the LGM (Legrand et al., 1991). Saltzman et al. (2006) show that the MSA measurements at Siple Dome do not corroborate stronger DMS emissions in the Pacific sector during the LGM. We use the GEOS-Chem chemical transport model forced with GISS-ModelE meteorology from modern and LGM boundary conditions to simulate Antarctic MSA <span class="hlt">concentrations</span>. We estimate the contribution of transport and precipitation to the modern-LGM difference at each location. Changes in DMS emissions, sea <span class="hlt">ice</span> extent, and oxidant <span class="hlt">concentrations</span> are evaluated as additional important factors in explaining modern versus LGM MSA <span class="hlt">concentrations</span> in Antarctic <span class="hlt">ice</span> cores.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFMPP13A2058W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFMPP13A2058W"><span>Major Ion <span class="hlt">concentrations</span> in the new NEEM <span class="hlt">ice</span> core in Greenland</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wegner, A.; Azuma, K. G.; Hirabayashi, M.; Schmidt, K.; Hansson, M.; Twarloh, B.</p> <p>2012-12-01</p> <p>The drilling of the new deep <span class="hlt">ice</span> core in NEEM (77.45°N 51.06°W) was terminated in 2010. Using a continuous flow analysis system (CFA), discrete samples were filled and analyzed for major ion <span class="hlt">concentrations</span> (Na, K, Mg, Ca, Cl, SO_4 and NO_3) using Ion Chromatography (IC). The samples were measured at Alfred Wegener Institute for Polar and Marine Research (Germany) and National Institute of Polar Research (Japan). Here we present preliminary results of the major Ion <span class="hlt">concentrations</span>. We found highest variations in <span class="hlt">concentrations</span> of Calcium and Magnesium which are mainly originating from terrestrial sources with <span class="hlt">concentrations</span> between 5-10 ppb and 4 ppb during the Holocene compared to 800 ppb and 80 ppb during the LGM. This is in line with measurements of particulate dust <span class="hlt">concentrations</span>. Sulphate <span class="hlt">concentrations</span> closely follow DO events and vary between 25 ppb during the Holocene and ~400 ppb during the LGM. Sodium <span class="hlt">concentrations</span> vary between ~ 8 ppb during the Holocene and up to 100 ppb during the LGM. We discuss influences of changes in the source areas and atmospheric transport intensity on the different time scales.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4389209','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4389209"><span>Small Molecule <span class="hlt">Ice</span> Recrystallization Inhibitors Enable Freezing of Human Red Blood Cells with Reduced Glycerol <span class="hlt">Concentrations</span></span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Capicciotti, Chantelle J.; Kurach, Jayme D. R.; Turner, Tracey R.; Mancini, Ross S.; Acker, Jason P.; Ben, Robert N.</p> <p>2015-01-01</p> <p>In North America, red blood cells (RBCs) are cryopreserved in a clinical setting using high glycerol <span class="hlt">concentrations</span> (40% w/v) with slow cooling rates (~1°C/min) prior to storage at −80°C, while European protocols use reduced glycerol <span class="hlt">concentrations</span> with rapid freezing rates. After thawing and prior to transfusion, glycerol must be removed to avoid intravascular hemolysis. This is a time consuming process requiring specialized equipment. Small molecule <span class="hlt">ice</span> recrystallization inhibitors (IRIs) such as β-PMP-Glc and β-pBrPh-Glc have the ability to prevent <span class="hlt">ice</span> recrystallization, a process that contributes to cellular injury and decreased cell viability after cryopreservation. Herein, we report that addition of 110 mM β-PMP-Glc or 30 mM β-pBrPh-Glc to a 15% glycerol solution increases post-thaw RBC integrity by 30-50% using slow cooling rates and emphasize the potential of small molecule IRIs for the preservation of cells. PMID:25851700</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25851700','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25851700"><span>Small molecule <span class="hlt">ice</span> recrystallization inhibitors enable freezing of human red blood cells with reduced glycerol <span class="hlt">concentrations</span>.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Capicciotti, Chantelle J; Kurach, Jayme D R; Turner, Tracey R; Mancini, Ross S; Acker, Jason P; Ben, Robert N</p> <p>2015-04-08</p> <p>In North America, red blood cells (RBCs) are cryopreserved in a clinical setting using high glycerol <span class="hlt">concentrations</span> (40% w/v) with slow cooling rates (~1°C/min) prior to storage at -80°C, while European protocols use reduced glycerol <span class="hlt">concentrations</span> with rapid freezing rates. After thawing and prior to transfusion, glycerol must be removed to avoid intravascular hemolysis. This is a time consuming process requiring specialized equipment. Small molecule <span class="hlt">ice</span> recrystallization inhibitors (IRIs) such as β-PMP-Glc and β-pBrPh-Glc have the ability to prevent <span class="hlt">ice</span> recrystallization, a process that contributes to cellular injury and decreased cell viability after cryopreservation. Herein, we report that addition of 110 mM β-PMP-Glc or 30 mM β-pBrPh-Glc to a 15% glycerol solution increases post-thaw RBC integrity by 30-50% using slow cooling rates and emphasize the potential of small molecule IRIs for the preservation of cells.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012EGUGA..14.6668G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012EGUGA..14.6668G"><span>Variations of ion <span class="hlt">concentrations</span> in the deep <span class="hlt">ice</span> core and surface snow at NEEM, Greenland</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Goto-Azuma, K.; Wegner, A.; Hansson, M.; Hirabayashi, M.; Kuramoto, T.; Miyake, T.; Motoyama, H.; NEEM Aerosol Consortium members</p> <p>2012-04-01</p> <p>Discrete samples were collected from the CFA (Continuous Flow Analysis) melt fractions during the field campaign carried out at NEEM, Greenland in 2009-2011, and were distributed to different laboratories. Ionic species were analyzed at National Institute of Polar Research (Japan) and Alfred Wegener Institute for Polar and Marine Research (Germany). Here we present and compare the ion <span class="hlt">concentration</span> data obtained by both institutes. Most of the ions show good agreement between the two institutes. As is indicated with the CFA data (Bigler and the NEEM Aerosol Consortium members, EGU 2012), ion chromatograph data also display that calcium and sodium, mainly originated from terrestrial dust and sea-salt, respectively, show large variations associated with Dansgaard-Oeschger (DO) events. Chloride, fluoride, sulfate, sodium, potassium and magnesium also show such variations, as has been already reported for other Greenland <span class="hlt">ice</span> cores. New ion data obtained from the NEEM deep core also show large variability of oxalate and phosphate <span class="hlt">concentrations</span> during DO events. Acetate, which is thought to be mainly derived from biomass burning, as is oxalate, appears to show variability associated with DO events, but to a lesser extent. On the other hand, nitrate, ammonium and methanesulfonate do not show such variations. Together with ion data from the deep <span class="hlt">ice</span> core, we present those from the pits dug during the NEEM field campaign to discuss seasonal variations of ionic species. The seasonal and millennial scale variations of ions are thought to be caused by changes in atmospheric circulation and source strength.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24081467','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24081467"><span>Effect of freezing rate and dendritic <span class="hlt">ice</span> formation on <span class="hlt">concentration</span> profiles of proteins frozen in cylindrical vessels.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Rodrigues, Miguel A; Miller, Maria A; Glass, Matt A; Singh, Satish K; Johnston, Keith P</p> <p>2011-04-01</p> <p>The process of freezing protein solutions can perturb the conformation of the protein and potentially lead to aggregate formation during long-term storage in the frozen state. Radial macroscopic freeze <span class="hlt">concentration</span> and temperature profiles for bovine serum albumin (BSA) solutions in small cylindrical stainless steel vessels were determined for various freezing rates. The measured <span class="hlt">concentrations</span> of both BSA and immunoglobulin G2, as well as trehalose in sampled <span class="hlt">ice</span> sections, increased by up to twofold to threefold toward the bottom and radial center for slow freezing rates produced in stagnant air freezers. The <span class="hlt">concentration</span> and temperature profiles result in density gradients that transport solutes by convective flow. For faster external cooling by either forced convection of air or a liquid coolant, the increased freezing rate raised the <span class="hlt">ice</span> front velocity resulting in enhanced dendritic <span class="hlt">ice</span> growth. The <span class="hlt">ice</span> trapped the solutes more effectively before they were removed from the <span class="hlt">ice</span> front by diffusion and convection, resulting in more uniform solute <span class="hlt">concentration</span> profiles. The dynamic temperature profiles from multiple radial thermocouples were consistent with the independently measured freeze <span class="hlt">concentration</span> profiles. The ability to control the protein <span class="hlt">concentration</span> profile in the frozen state offers the potential to improve stability of protein in long-term frozen storage.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010EGUGA..1210513D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010EGUGA..1210513D"><span>Estimation of <span class="hlt">ice</span> thickness on large lakes from passive microwave and radar altimeter data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Duguay, Claude; Kang, Kyung-Kuk; Kouraev, Alexei; Mercier, Franck</p> <p>2010-05-01</p> <p>Lake <span class="hlt">ice</span> grows steadily between the end of freeze-up period and the onset of break-up period as a result of the thermodynamics of freezing water as well as dynamic <span class="hlt">ice</span> motion on the surface. In thermodynamic thickening, the conductive heat flow controls the <span class="hlt">ice</span> growth rate and the <span class="hlt">ice</span> thickness, and the <span class="hlt">ice</span> thickens downward as a result of heat loss at the top of the <span class="hlt">ice</span> cover. There has been some demonstration of the potential of brightness temperature from passive microwave airborne radiometers to estimate <span class="hlt">ice</span> thickness. The value of passive microwave and radar altimeter data from current satellite missions merits to be examined in this respect. The major objective of this study was estimate <span class="hlt">ice</span> thickness from brightness temperature (TB) at 10.65 and 18.70 GHz from <span class="hlt">AMSR-E</span> channels and the 19.35 GHz frequency channel from SSM/I on large lakes of the Northern Hemisphere (e.g. Great Bear Lake, Great Slave Lake, Lake Baikal). The evolution of horizontally and vertically polarized TB derived from <span class="hlt">AMSR-E</span> level 2A raw brightness temperature and EASE Grid Level-3 SSM/I products was compared with <span class="hlt">ice</span> thicknesses obtained with a previously validated thermodynamic lake <span class="hlt">ice</span> model and in situ observations over the course of seven winter seasons (2002 and 2009), as well as with recent estimates from the Jason-2 Ku-band radar altimeter data (since 2008). Results show that both passive microwave and radar altimeter data acquired in the 10-19 GHz frequency range offer a promising means for estimating <span class="hlt">ice</span> thickness from large northern lakes.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016APJAS..52..467K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016APJAS..52..467K"><span>Development of statistical seasonal prediction models of Arctic Sea <span class="hlt">Ice</span> <span class="hlt">concentration</span> using CERES absorbed solar radiation</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kim, Yoojin; Kim, Ha-Rim; Choi, Yong-Sang; Kim, WonMoo; Kim, Hye-Sil</p> <p>2016-11-01</p> <p>Statistical seasonal prediction models for the Arctic sea <span class="hlt">ice</span> <span class="hlt">concentration</span> (SIC) were developed for the late summer (August-October) when the downward trend is dramatic. The absorbed solar radiation (ASR) at the top of the atmosphere in June has a significant seasonal leading role on the SIC. Based on the lagged ASR-SIC relationship, two simple statistical models were established: the Markovian stochastic and the linear regression models. Crossvalidated hindcasts of SIC from 1979 to 2014 by the two models were compared with each other and observation. The hindcasts showed general agreement between the models as they share a common predictor, ASR in June and the observed SIC was well reproduced, especially over the relatively thin-<span class="hlt">ice</span> regions (of one- or multi-year sea <span class="hlt">ice</span>). The robust predictability confirms the functional role of ASR in the prediction of SIC. In particular, the SIC prediction in October was quite promising probably due to the pronounced icealbedo feedback. The temporal correlation coefficients between the predicted SIC and the observed SIC were 0.79 and 0.82 by the Markovian and regression models, respectively. Small differences were observed between the two models; the regression model performed slightly better in August and September in terms of temporal correlation coefficients. Meanwhile, the prediction skills of the Markovian model in October were higher in the north of Chukchi, the East Siberian, and the Laptev Seas. A strong non-linear relationship between ASR in June and SIC in October in these areas would have increased the predictability of the Markovian model.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.6297D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.6297D"><span>Interactions between Arctic sea <span class="hlt">ice</span> drift, <span class="hlt">concentration</span> and thickness modeled by NEMO-LIM3 at different resolutions</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Docquier, David; Massonnet, François; Raulier, Jonathan; Lecomte, Olivier; Fichefet, Thierry</p> <p>2016-04-01</p> <p>Sea <span class="hlt">ice</span> <span class="hlt">concentration</span> and thickness have substantially decreased in the Arctic since the beginning of the satellite era. As a result, mechanical strength has decreased allowing more fracturing and leading to increased sea <span class="hlt">ice</span> drift. However, recent studies have highlighted that the interplay between sea <span class="hlt">ice</span> thermodynamics and dynamics is poorly represented in contemporary global climate model (GCM) simulations. Thus, the considerable inter-model spread in terms of future sea <span class="hlt">ice</span> extent projections could be reduced by better understanding the interactions between drift, <span class="hlt">concentration</span> and thickness. This study focuses on the results coming from the global coupled ocean-sea <span class="hlt">ice</span> model NEMO-LIM3 between 1979 and 2012. Three different simulations are forced by the Drakkar Forcing Set (DFS) 5.2 and run on the global tripolar ORCA grid at spatial resolutions of 0.25, 1° and 2°. The relation between modeled sea <span class="hlt">ice</span> drift, <span class="hlt">concentration</span> and thickness is further analyzed, compared to observations and discussed in the framework of the above-mentioned poor representation. It is proposed as a process-based metric for evaluating model performance. This study forms part of the EU Horizon 2020 PRIMAVERA project aiming at developing a new generation of advanced and well-evaluated high-resolution GCMs.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C41D0756R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C41D0756R"><span>An Intercomparison of Predicted Sea <span class="hlt">Ice</span> <span class="hlt">Concentration</span> from Global Ocean Forecast System & Arctic Cap Nowcast/Forecast System</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Rosemond, K.</p> <p>2015-12-01</p> <p>The objective of this research is to provide an evaluation of improvements in marginal <span class="hlt">ice</span> zone (MIZ) and pack <span class="hlt">ice</span> estimations from the Global Ocean Forecast System (GOFS) model compared to the current operational model, the Arctic Cap Nowcast/Forecast System (ACNFS). This will be determined by an intercomparison between the subjectively estimated operational <span class="hlt">ice</span> <span class="hlt">concentration</span> data from the National <span class="hlt">Ice</span> Center (NIC) MIZ analysis and the <span class="hlt">ice</span> <span class="hlt">concentration</span> estimates from GOFS and ACNFS. This will help ascertain which nowcast from the models compares best to the NIC operational data stream needed for vessel support. It will also provide a quantitative assessment of GOFS and ACNFS performance and be used in the Operational Evaluation (OPEVAL) report from the NIC to NRL. The intercomparison results are based on statistical evaluations through a series of map overlays from both models ACNFS, GOFS with the NIC's MIZ data. All data was transformed to a common grid and difference maps were generated to determine which model had the greatest difference compared to the MIZ <span class="hlt">ice</span> <span class="hlt">concentrations</span>. This was provided daily for both the freeze-up and meltout seasons. Results indicated the GOFS model surpassed the ACNFS model, however both models were comparable. These results will help US Navy and NWS Anchorage <span class="hlt">ice</span> forecasters understand model biases and know which model guidance is likely to provide the best estimate of future <span class="hlt">ice</span> conditions.The objective of this research is to provide an evaluation of improvements in marginal <span class="hlt">ice</span> zone (MIZ) and pack <span class="hlt">ice</span> estimations from the Global Ocean Forecast System (GOFS) model compared to the current operational model, the Arctic Cap Nowcast/Forecast System (ACNFS). This will be determined by an intercomparison between the subjectively estimated operational <span class="hlt">ice</span> <span class="hlt">concentration</span> data from the National <span class="hlt">Ice</span> Center (NIC) MIZ analysis and the <span class="hlt">ice</span> <span class="hlt">concentration</span> estimates from GOFS and ACNFS. This will help ascertain which nowcast from the models</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013ACP....13.6151H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013ACP....13.6151H"><span>High <span class="hlt">concentrations</span> of biological aerosol particles and <span class="hlt">ice</span> nuclei during and after rain</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Huffman, J. A.; Prenni, A. J.; DeMott, P. J.; Pöhlker, C.; Mason, R. H.; Robinson, N. H.; Fröhlich-Nowoisky, J.; Tobo, Y.; Després, V. R.; Garcia, E.; Gochis, D. J.; Harris, E.; Müller-Germann, I.; Ruzene, C.; Schmer, B.; Sinha, B.; Day, D. A.; Andreae, M. O.; Jimenez, J. L.; Gallagher, M.; Kreidenweis, S. M.; Bertram, A. K.; Pöschl, U.</p> <p>2013-07-01</p> <p>Bioaerosols are relevant for public health and may play an important role in the climate system, but their atmospheric abundance, properties, and sources are not well understood. Here we show that the <span class="hlt">concentration</span> of airborne biological particles in a North American forest ecosystem increases significantly during rain and that bioparticles are closely correlated with atmospheric <span class="hlt">ice</span> nuclei (IN). The greatest increase of bioparticles and IN occurred in the size range of 2-6 μm, which is characteristic for bacterial aggregates and fungal spores. By DNA analysis we found high diversities of airborne bacteria and fungi, including groups containing human and plant pathogens (mildew, smut and rust fungi, molds, Enterobacteriaceae, Pseudomonadaceae). In addition to detecting known bacterial and fungal IN (Pseudomonas sp., Fusarium sporotrichioides), we discovered two species of IN-active fungi that were not previously known as biological <span class="hlt">ice</span> nucleators (Isaria farinosa and Acremonium implicatum). Our findings suggest that atmospheric bioaerosols, IN, and rainfall are more tightly coupled than previously assumed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.P51B1736S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.P51B1736S"><span>Optimal Electromagnetic (EM) Geophysical Techniques to Map the <span class="hlt">Concentration</span> of Subsurface <span class="hlt">Ice</span> and Adsorbed Water on Mars and the Moon</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Stillman, D. E.; Grimm, R. E.</p> <p>2013-12-01</p> <p>Water <span class="hlt">ice</span> is ubiquitous in our Solar System and is a probable target for planetary exploration. Mapping the lateral and vertical <span class="hlt">concentration</span> of subsurface <span class="hlt">ice</span> from or near the surface could determine the origin of lunar and martian <span class="hlt">ice</span> and quantify a much-needed resource for human exploration. Determining subsurface <span class="hlt">ice</span> <span class="hlt">concentration</span> on Earth is not trivial and has been attempted previously with electrical resistivity tomography (ERT), ground penetrating radar (GPR), airborne EM (AEM), and nuclear magnetic resonance (NMR). These EM geophysical techniques do not actually detect <span class="hlt">ice</span>, but rather the absence of unfrozen water. This causes a non-unique interpretation of frozen and dry subsurface sediments. This works well in the arctic because most locations are not dry. However, for planetary exploration, liquid water is exceedingly rare and subsurface mapping must discriminate between an <span class="hlt">ice</span>-rich and a dry subsurface. Luckily, nature has provided a unique electrical signature of <span class="hlt">ice</span>: its dielectric relaxation. The dielectric relaxation of <span class="hlt">ice</span> creates a temperature and frequency dependence of the electrical properties and varies the relative dielectric permittivity from ~3.1 at radar frequencies to >100 at low frequencies. On Mars, sediments smaller than silt size can hold enough adsorbed unfrozen water to complicate the measurement. This is because the presence of absorbed water also creates frequency-dependent electrical properties. The dielectric relaxation of adsorbed water and <span class="hlt">ice</span> can be separated as they have different shapes and frequency ranges as long as a spectrum spanning the two relaxations is measured. The volume <span class="hlt">concentration</span> of <span class="hlt">ice</span> and adsorbed water is a function of the strength of their relaxations. Therefore, we suggest that capacitively-coupled dielectric spectroscopy (a.k.a. spectral induced polarization or complex resistivity) can detect the <span class="hlt">concentration</span> of both <span class="hlt">ice</span> and adsorbed water in the subsurface. To prove this concept we have collected</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AdAtS..34..509Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AdAtS..34..509Y"><span>Observational evidence of high <span class="hlt">ice</span> <span class="hlt">concentration</span> in a shallow convective cloud embedded in stratiform cloud over North China</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Yang, Jiefan; Lei, Hengchi; Hou, Tuanjie</p> <p>2017-04-01</p> <p>In this study we observed the microphysical properties, including the vertical and horizontal distributions of <span class="hlt">ice</span> particles, liquid water content and <span class="hlt">ice</span> habit, in different regions of a slightly supercooled stratiform cloud. Using aircraft instrument and radar data, the cloud top temperature was recorded as higher than -15°C, behind a cold front, on 9 September 2015 in North China. During the flight sampling, the high <span class="hlt">ice</span> number <span class="hlt">concentration</span> area was located in the supercooled part of a shallow convective cloud embedded in a stratiform cloud, where the ambient temperature was around -3°C. In this area, the maximum number <span class="hlt">concentrations</span> of particles with diameter greater than 100 μm and 500 μm ( N 100 and N 500) exceeded 300 L-1 and 30 L-1, respectively, and were related to large supercooled water droplets with diameter greater than 24 μm derived from cloud-aerosol spectrometer probe measurements. The <span class="hlt">ice</span> particles types in this region were predominantly columnar, needle, graupel, and some freezing drops, suggesting that the occurrence of high <span class="hlt">ice</span> number <span class="hlt">concentrations</span> was likely related to the Hallett-Mossop mechanism, although many other <span class="hlt">ice</span> multiplication processes cannot be totally ruled out. The maximum <span class="hlt">ice</span> number <span class="hlt">concentration</span> obtained during the first penetration was around two to three orders of magnitude larger than that predicted by the Demott and Fletcher schemes when assuming the cloud top temperature was around -15°C. During the second penetration conducted within the stratiform cloud, N 100 and N 500 decreased by a factor of five to ten, and the presence of columnar and needle-like crystals became very rare.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009EGUGA..1113752H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009EGUGA..1113752H"><span>L-band radiometry for sea <span class="hlt">ice</span> applications</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Heygster, G.; Hedricks, S.; Mills, P.; Kaleschke, L.; Stammer, D.; Tonboe, R.</p> <p>2009-04-01</p> <p> Peake (1976). This expression was used by Menashi et al. (1993) to derive the thickness of sea <span class="hlt">ice</span> from UHF (0.6 GHz) radiometer. Second, retrieval algorithms for sea <span class="hlt">ice</span> parameters with emphasis on <span class="hlt">ice</span>-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 <span class="hlt">ice</span> at low temperatures. At temperatures approaching the melting point the thickness sensitivity reduces to a few centimetres. For first year <span class="hlt">ice</span> the modelled thickness sensitivity is roughly half a meter. Runs of the model MEMLS with input data generated from a 1-d thermodynamic sea <span class="hlt">ice</span> 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 <span class="hlt">ice</span> thickness as supported by several former field campaigns for thin <span class="hlt">ice</span>, the model predictions change strongly. Prior to the launch of SMOS, an important source of observational data is the SMOS Sea-<span class="hlt">Ice</span> campaign held near Kokkola, Finland, March 2007 conducted as an add-on of the POL-<span class="hlt">ICE</span> campaign. Co-incident L-band observations taken with the EMIRAD instrument of the Technical University of Denmark, <span class="hlt">ice</span> 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 <span class="hlt">ice</span> 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 <span class="hlt">ice</span> thickness product based on SMOS data. Use of additional information from other microwave sensors like <span class="hlt">AMSR-E</span> might be needed to constrain the conditions, e</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19900047009&hterms=Nimbus&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3DNimbus','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19900047009&hterms=Nimbus&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3DNimbus"><span>Observations of winter polynyas and fractures using NOAA AVHRR TIR images and Nimbus-7 SMMR sea <span class="hlt">ice</span> <span class="hlt">concentration</span> charts</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Dey, B.; Feldman, Uri</p> <p>1989-01-01</p> <p>The validity of the daily sea <span class="hlt">ice</span> <span class="hlt">concentration</span> charts obtained from Nimbus-7 SMMR data is tested against thermal IR NOAA AVHRR-4 images with a 1.1 x 1.1 km resolution. Polynyas and fractures recorded in both data sets are compared for the same times over the same areas. Although the coarser resolution of SMMR data leads to a loss of detail, it is found that the <span class="hlt">ice</span> <span class="hlt">concentration</span> charts provide valuable data on openings in the <span class="hlt">ice</span>. The SMMR data on the location, orientation, and size of polynyas and fractures are shown to be in good agreement with the AVHRR data. Also, the results suggest that the location and orientation of plynyas and fractures are related to the direction of surface winds.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015TCry....9...37K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015TCry....9...37K"><span>The impact of snow depth, snow density and <span class="hlt">ice</span> density on sea <span class="hlt">ice</span> thickness retrieval from satellite radar altimetry: results from the ESA-CCI Sea <span class="hlt">Ice</span> ECV Project Round Robin Exercise</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kern, S.; Khvorostovsky, K.; Skourup, H.; Rinne, E.; Parsakhoo, Z. S.; Djepa, V.; Wadhams, P.; Sandven, S.</p> <p>2015-01-01</p> <p>We assess different methods and input parameters, namely snow depth, snow density and <span class="hlt">ice</span> density, used in freeboard-to-thickness conversion of Arctic sea <span class="hlt">ice</span>. This conversion is an important part of sea <span class="hlt">ice</span> thickness retrieval from spaceborne altimetry. A data base is created comprising sea <span class="hlt">ice</span> freeboard derived from satellite radar altimetry between 1993 and 2012 and co-locate observations of total (sea <span class="hlt">ice</span> + snow) and sea <span class="hlt">ice</span> freeboard from the Operation <span class="hlt">Ice</span> Bridge (OIB) and CryoSat Validation Experiment (CryoVEx) airborne campaigns, of sea <span class="hlt">ice</span> draft from moored and submarine upward looking sonar (ULS), and of snow depth from OIB campaigns, Advanced Microwave Scanning Radiometer (<span class="hlt">AMSR-E</span>) 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 <span class="hlt">ice</span> draft agrees with the mean sea <span class="hlt">ice</span> 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 <span class="hlt">ice</span> draft observed by moored ULS. A sensitivity analysis of the freeboard-to-thickness conversion suggests that sea <span class="hlt">ice</span> density is as important as snow depth.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/17833720','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/17833720"><span><span class="hlt">Ice</span> crystal <span class="hlt">concentration</span> in cumulus clouds: influence of the drop spectrum.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Mossop, S C; Hallett, J</p> <p>1974-11-15</p> <p>Secondary <span class="hlt">ice</span> crystals are thrown off when supercooled cloud drops are captured and freeze on a moving target in a cloud at -5 degrees C. The rate of production of these <span class="hlt">ice</span> crystals is proportional to the rate of accretion of drops of the diameter >/=24 micrometers.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140013408','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140013408"><span>A Long-Term and Reproducible Passive Microwave Sea <span class="hlt">Ice</span> <span class="hlt">Concentration</span> Data Record for Climate Studies and Monitoring</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Peng, G.; Meier, W. N.; Scott, D. J.; Savoie, M. H.</p> <p>2013-01-01</p> <p>A long-term, consistent, and reproducible satellite-based passive microwave sea <span class="hlt">ice</span> <span class="hlt">concentration</span> climate data record (CDR) is available for climate studies, monitoring, and model validation with an initial operation capability (IOC). The daily and monthly sea <span class="hlt">ice</span> <span class="hlt">concentration</span> data are on the National Snow and <span class="hlt">Ice</span> Data Center (NSIDC) polar stereographic grid with nominal 25 km × 25 km grid cells in both the Southern and Northern Hemisphere polar regions from 9 July 1987 to 31 December 2007. The data files are available in the NetCDF data format at http://nsidc.org/data/g02202.html and archived by the National Climatic Data Center (NCDC) of the National Oceanic and Atmospheric Administration (NOAA) under the satellite climate data record program (http://www.ncdc.noaa.gov/cdr/operationalcdrs.html). The description and basic characteristics of the NOAA/NSIDC passive microwave sea <span class="hlt">ice</span> <span class="hlt">concentration</span> CDR are presented here. The CDR provides similar spatial and temporal variability as the heritage products to the user communities with the additional documentation, traceability, and reproducibility that meet current standards and guidelines for climate data records. The data set, along with detailed data processing steps and error source information, can be found at http://dx.doi.org/10.7265/N5B56GN3.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li class="active"><span>12</span></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_12 --> <div id="page_13" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li class="active"><span>13</span></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="241"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/20338422','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/20338422"><span>Short communication: low-fat <span class="hlt">ice</span> cream flavor not modified by high hydrostatic pressure treatment of whey protein <span class="hlt">concentrate</span>.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Chauhan, J M; Lim, S-Y; Powers, J R; Ross, C F; Clark, S</p> <p>2010-04-01</p> <p>The purpose of this study was to examine flavor binding of high hydrostatic pressure (HHP)-treated whey protein <span class="hlt">concentrate</span> (WPC) in a real food system. Fresh Washington State University (WSU, Pullman) WPC, produced by ultrafiltration of separated Cheddar cheese whey, was treated at 300 MPa for 15 min. Commercial WPC 35 powder was reconstituted to equivalent total solids as WSU WPC (8.23%). Six batches of low-fat <span class="hlt">ice</span> cream were produced: A) HHP-treated WSU WPC without diacetyl; B) and E) WSU WPC with 2 mg/L of diacetyl added before HHP; C) WSU WPC with 2 mg/L of diacetyl added after HHP; D) untreated WSU WPC with 2 mg/L of diacetyl; and F) untreated commercial WPC 35 with 2 mg/L of diacetyl. The solution of WSU WPC or commercial WPC 35 contributed 10% to the mix formulation. <span class="hlt">Ice</span> creams were produced by using standard <span class="hlt">ice</span> cream ingredients and processes. Low-fat <span class="hlt">ice</span> creams containing HHP-treated WSU WPC and untreated WSU WPC were analyzed using headspace-solid phase microextraction-gas chromatography. Sensory evaluation by balanced reference duo-trio test was carried out using 50 untrained panelists in 2 sessions on 2 different days. The headspace-solid phase microextraction-gas chromatography analysis revealed that <span class="hlt">ice</span> cream containing HHP-treated WSU WPC had almost 3 times the <span class="hlt">concentration</span> of diacetyl compared with <span class="hlt">ice</span> cream containing untreated WSU WPC at d 1 of storage. However, diacetyl was not detected in <span class="hlt">ice</span> creams after 14 d of storage. Eighty percent of panelists were able to distinguish between low-fat <span class="hlt">ice</span> creams containing untreated WSU WPC with and without diacetyl, confirming panelists' ability to detect diacetyl. However, panelists were not able to distinguish between low-fat <span class="hlt">ice</span> creams containing untreated and HHP-treated WSU WPC with diacetyl. These results show that WPC diacetyl-binding properties were not enhanced by 300-MPa HHP treatment for 15 min, indicating that HHP may not be suitable for such applications.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFMPP21A1309G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFMPP21A1309G"><span>Late Quaternary Advance and Retreat of an East Antarctic <span class="hlt">Ice</span> Shelf System: Insights from Sedimentary Beryllium-10 <span class="hlt">Concentrations</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Guitard, M. E.; Shevenell, A.; Domack, E. W.; Rosenheim, B. E.; Yokoyama, Y.</p> <p>2014-12-01</p> <p>Observed retreat of Antarctica's marine-based glaciers and the presence of warm (~2°C) modified Circumpolar Deep Water on Antarctica's continental shelves imply ocean temperatures may influence Antarctic cryosphere stability. A paucity of information regarding Late Quaternary East Antarctic cryosphere-ocean interactions makes assessing the variability, timing, and style of deglacial retreat difficult. Marine sediments from Prydz Bay, East Antarctica contain hemipelagic siliceous mud and ooze units (SMO) alternating with glacial marine sediments. The record suggests Late Quaternary variability of local outlet glacier systems, including the Lambert Glacier/Amery <span class="hlt">Ice</span> Shelf system that drains 15% of the East Antarctic <span class="hlt">Ice</span> Sheet. We present a refined radiocarbon chronology and beryllium-10 (10Be) record of Late Quaternary depositional history in Prydz Channel, seaward of the Amery <span class="hlt">Ice</span> Shelf system, which provides insight into the timing and variability of this important outlet glacier system. We focus on three piston cores (NBP01-01, JPC 34, 35, 36; 750 m water depth) that contain alternating SMO and granulated units uninterrupted by glacial till; the record preserves a succession of glacial marine deposits that pre-date the Last Glacial Maximum. We utilize the ramped pyrolysis preparatory method to improve the bulk organic carbon 14C-based chronology for Prydz Channel. To determine if the SMO intervals reflect open water conditions or sub-<span class="hlt">ice</span> shelf advection, we measured sedimentary 10Be <span class="hlt">concentrations</span>. Because <span class="hlt">ice</span> cover affects 10Be pathways through the water column, sedimentary <span class="hlt">concentrations</span> should provide information on past depositional environments in Prydz Channel. In Prydz Channel sediments, 10Be <span class="hlt">concentrations</span> are generally higher in SMO units and lower in glacial units, suggesting Late Quaternary fluctuations in the Amery <span class="hlt">Ice</span> Shelf. Improved chronologic constraints indicate that these fluctuations occurred on millennial timescales during the Last Glacial</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007AGUFMPP31E..01C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007AGUFMPP31E..01C"><span>Greenhouse Gas <span class="hlt">Concentration</span> Records Extended Back to 800,000 Years From the EPICA Dome C <span class="hlt">Ice</span> Core</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Chappellaz, J.; Luethi, D.; Loulergue, L.; Barnola, J.; Bereiter, B.; Blunier, T.; Jouzel, J.; Lefloch, M.; Lemieux, B.; Masson-Delmotte, V.; Raynaud, D.; Schilt, A.; Siegenthaler, U.; Spahni, R.; Stocker, T.</p> <p>2007-12-01</p> <p>The deep <span class="hlt">ice</span> core recovered from Dome Concordia in the framework of EPICA, the European Project for <span class="hlt">Ice</span> Coring in Antarctica, has extended the record of Antarctic climate history back to 800,000 years [Jouzel et al., 2007]. We present the current status of measurements of CO2, CH4 and N2O on air trapped in the bubbles of the Dome C <span class="hlt">ice</span> core. CO2 is measured in two laboratories using different techniques (laser absorption spectroscopy or gas chromatography on samples of 8 and 40 g of <span class="hlt">ice</span> which are mechanically crushed or milled, respectively). CH4 and N2O are extracted using a melt-refreeze technique and then measured by gas chromatography (in two laboratories for CH4). The greenhouse gas <span class="hlt">concentrations</span> have now been measured on the lowest 200 m of the Dome C core, going back to Marine Isotope Stage 20 (MIS 20) as verified by a consistent gas age/<span class="hlt">ice</span> age difference determined at termination IX [Jouzel et al., 2007]. The atmospheric CO2 <span class="hlt">concentration</span> mostly lagged the Antarctic temperature with a rather strong correlation throughout the eight and a half glacial cycles, but with significantly lower CO2 values between 650 and 750 kyr BP. Its lowest level ever measured in <span class="hlt">ice</span> cores (172 ppmv) is observed during MIS 16 (minimum centered at 667 kyr BP according to the EDC3 chronology) redetermining the natural span of CO2 to 172-300 ppmv. With 2245 individual measurements, the CH4 <span class="hlt">concentration</span> is now reconstructed over 800,000 years from a single core, with an average time resolution of 380 years. Spectral analyses of the CH4 signal show an increasing contribution of precession during the last four climatic cycles compared with the four older ones, suggesting an increasing impact of low latitudes sources/sinks. Millennial scale features in this very detailed signal allows us to compare their occurrence with <span class="hlt">ice</span> volume reconstructions and the isotopic composition of precipitation over the East Antarctic plateau. N2O is still affected by glaciological artefacts involving</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A22A..06K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A22A..06K"><span>A new single-moment microphysics scheme for cloud-resolving models using observed dependence of <span class="hlt">ice</span> <span class="hlt">concentration</span> on temperature.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Khairoutdinov, M.</p> <p>2015-12-01</p> <p>The representation of microphysics, especially <span class="hlt">ice</span> microphysics, remains one of the major uncertainties in cloud-resolving models (CRMs). Most of the cloud schemes use the so-called bulk microphysics approach, in which a few moments of such distributions are used as the prognostic variables. The System for Atmospheric Modeling (SAM) is the CRM that employs two such schemes. The single-moment scheme, which uses only mass for each of the water phases, and the two-moment scheme, which adds the particle <span class="hlt">concentration</span> for each of the hydrometeor category. Of the two, the single-moment scheme is much more computationally efficient as it uses only two prognostic microphysics variables compared to ten variables used by the two-moment scheme. The efficiency comes from a rather considerable oversimplification of the microphysical processes. For instance, only a sum of the liquid and icy cloud water is predicted with the temperature used to diagnose the mixing ratios of different hydrometeors. The main motivation for using such simplified microphysics has been computational efficiency, especially in the applications of SAM as the super-parameterization in global climate models. Recently, we have extended the single-moment microphysics by adding only one additional prognostic variable, which has, nevertheless, allowed us to separate the cloud <span class="hlt">ice</span> from liquid water. We made use of some of the recent observations of <span class="hlt">ice</span> microphysics collected at various parts of the world to parameterize several aspects of <span class="hlt">ice</span> microphysics that have not been explicitly represented before in our sing-moment scheme. For example, we use the observed broad dependence of <span class="hlt">ice</span> <span class="hlt">concentration</span> on temperature to diagnose the <span class="hlt">ice</span> <span class="hlt">concentration</span> in addition to prognostic mass. Also, there is no artificial separation between the pristine <span class="hlt">ice</span> and snow, often used by bulk models. Instead we prescribed the <span class="hlt">ice</span> size spectrum as the gamma distribution, with the distribution shape parameter controlled by the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010ACPD...1020607S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010ACPD...1020607S"><span>The sensitivity of the oxygen isotopes of <span class="hlt">ice</span> core sulfate to changing oxidant <span class="hlt">concentrations</span> since the preindustrial</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sofen, E. D.; Alexander, B.; Kunasek, S. A.</p> <p>2010-08-01</p> <p>Changes in tropospheric oxidant <span class="hlt">concentrations</span> since preindustrial times have implications for the ozone radiative forcing, lifetimes of reduced trace gases, aerosol formation, and human health but are highly uncertain. Measurements of the triple oxygen isotopes of sulfate in <span class="hlt">ice</span> cores (described by Δ17OSO4 = δ17O - 0.52 × δ18O) provide one of the few constraints on paleo-oxidants. We use the GEOS-Chem global atmospheric chemical transport model to simulate changes in oxidant <span class="hlt">concentrations</span> and the Δ17OSO4 between 1850 and 1990 to assess the sensitivity of Δ17OSO4 measurements in Greenland and Antarctic <span class="hlt">ice</span> cores to changing tropospheric oxidant <span class="hlt">concentrations</span>. The model indicates a 42% increase in the <span class="hlt">concentration</span> of global mean tropospheric O3, a 10% decrease in OH, and a 58% increase in H2O2 between the preindustrial and present. Modeled Δ17OSO4 is consistent with measurements from <span class="hlt">ice</span> core and aerosol samples. Model results indicate that the observed decrease in the Arctic Δ17OSO4 in spite of increasing O3 is due to the combined effects of increased sulfate formation by O2 catalyzed by anthropogenic transition metals and increased cloud water acidity. In Antarctica, the Δ17OSO4 is sensitive to relative changes of oxidant <span class="hlt">concentrations</span>, but in a nonlinear fashion. Sensitivity studies explore the uncertainties in preindustrial emissions of oxidant precursors.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27664024','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27664024"><span>Freezing and glass transitions upon cooling and warming and <span class="hlt">ice/freeze-concentration</span>-solution morphology of emulsified aqueous citric acid.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Bogdan, Anatoli; Molina, Mario J; Tenhu, Heikki</p> <p>2016-12-01</p> <p>Although freeze-induced phase separation and the <span class="hlt">ice</span>/FCS (freeze-<span class="hlt">concentration</span> solution) morphology of aqueous solutions play an important role in fields ranging from life sciences and biotechnology to geophysics and high-altitude <span class="hlt">ice</span> clouds, their understanding is far from complete. Herein, using differential scanning calorimetry (DSC) and optical cryo-microscope (OC-M), we have studied the freezing and glass transition behavior and the <span class="hlt">ice</span>/FCS morphology of emulsified 10-60wt% CA (citric acid) solutions in the temperature region of ∼308and153K. We have obtained a lot of new result which are understandable and unclear. The most essential understandable results are as follows: (i) similar to bulk CA/H2O, emulsified CA/H2O also freezes upon cooling and warming and (ii) the <span class="hlt">ice</span>/FCS morphology of frozen drops smaller than ∼3-4μm is less ramified than that of frozen bulk solutions. Unclear results, among others, are as follows: (i) in contrast to bulk solutions, which produce one freezing event, emulsified CA/H2O produces two freezing events and (ii) in emulsions, drop <span class="hlt">concentration</span> is not uniform. Our results demonstrate that DSC thermograms and OC-M images/movies are mutually supplementary and allow us to extract important information which cannot be gained when DSC and OC-M techniques are used alone.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://pubs.usgs.gov/of/2007/1047/srp/srp029/of2007-1047srp029.pdf','USGSPUBS'); return false;" href="https://pubs.usgs.gov/of/2007/1047/srp/srp029/of2007-1047srp029.pdf"><span>Sea <span class="hlt">ice</span> <span class="hlt">concentration</span> temporal variability over the Weddell Sea and its relationship with tropical sea surface temperature</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Barreira, S.; Compagnucci, R.</p> <p>2007-01-01</p> <p>Principal Components Analysis (PCA) in S-Mode (correlation between temporal series) was performed on sea <span class="hlt">ice</span> monthly anomalies, in order to investigate which are the main temporal patterns, where are the homogenous areas located and how are they related to the 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 <span class="hlt">ice</span> <span class="hlt">concentration</span> anomalies (SICA) variability in the Weddell, Amundsen and Bellingshausen Seas over the 1979-2000 period. Monthly Polar Gridded Sea <span class="hlt">Ice</span> <span class="hlt">Concentrations</span> data set derived from satellite information generated by NASA Team algorithm and acquired from the National Snow and <span class="hlt">Ice</span> Data Center (NSIDC) were used. Monthly means SST are provided by the National Center for Environmental Prediction reanalysis. The first temporal pattern series obtained by PCA has its homogeneous area located at the external region of the Weddell and Bellingshausen 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 <span class="hlt">ice</span> <span class="hlt">concentration</span> over the Weddell Sea.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19920035390&hterms=defense&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Ddefense','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19920035390&hterms=defense&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Ddefense"><span>NASA team algorithm for sea <span class="hlt">ice</span> <span class="hlt">concentration</span> retrieval from Defense Meteorological Satellite Program special sensor microwave imager - Comparison with Landsat satellite imagery</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Steffen, Konrad; Schweiger, Axel</p> <p>1991-01-01</p> <p>The present study describes the validation of the the NASA team algorithm for the determination of sea <span class="hlt">ice</span> <span class="hlt">concentrations</span> from the Defense Meteorological Satellite Program special sensor microwave imager (SSM/I). A total of 28 cloud-free Landsat scenes were selected to permit validation of the passive microwave <span class="hlt">ice</span> <span class="hlt">concentration</span> algorithm for a range of <span class="hlt">ice</span> <span class="hlt">concentrations</span> and <span class="hlt">ice</span> types. The sensitivity of the NASA team algorithm to the selection of locally and seasonally adjusted algorithm parameters is discussed. Mean absolute differences between SSM/I and Landsat <span class="hlt">ice</span> <span class="hlt">concentrations</span> are within 1 percent during fall using local and global tie points (standard deviations of the difference are +/-3.1 and +/-6.2 percent, respectively). In areas with greater amounts of nilas and young <span class="hlt">ice</span>, the NASA team algorithm was found to underestimate <span class="hlt">ice</span> <span class="hlt">concentrations</span> by as much as 9 percent. It is inferred that the standard deviation between SSM/I and Landsat <span class="hlt">ice</span> <span class="hlt">concentrations</span> decreases from +/-7 to +/-5 percent with local tie points compared to the global ones for spring and fall.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011ACP....11.3459S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011ACP....11.3459S"><span>The effect of sea <span class="hlt">ice</span> loss on sea salt aerosol <span class="hlt">concentrations</span> and the radiative balance in the Arctic</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Struthers, H.; Ekman, A. M. L.; Glantz, P.; Iversen, T.; Kirkevåg, A.; Mårtensson, E. M.; Seland, Ø.; Nilsson, E. D.</p> <p>2011-04-01</p> <p>Understanding Arctic climate change requires knowledge of both the external and the local drivers of Arctic climate as well as local feedbacks within the system. An Arctic feedback mechanism relating changes in sea <span class="hlt">ice</span> extent to an alteration of the emission of sea salt aerosol and the consequent change in radiative balance is examined. A set of idealized climate model simulations were performed to quantify the radiative effects of changes in sea salt aerosol emissions induced by prescribed changes in sea <span class="hlt">ice</span> extent. The model was forced using sea <span class="hlt">ice</span> <span class="hlt">concentrations</span> consistent with present day conditions and projections of sea <span class="hlt">ice</span> extent for 2100. Sea salt aerosol emissions increase in response to a decrease in sea <span class="hlt">ice</span>, the model results showing an annual average increase in number emission over the polar cap (70-90° N) of 86 × 106 m-2 s-1 (mass emission increase of 23 μg m-2 s-1). This in turn leads to an increase in the natural aerosol optical depth of approximately 23%. In response to changes in aerosol optical depth, the natural component of the aerosol direct forcing over the Arctic polar cap is estimated to be between -0.2 and -0.4 W m-2 for the summer months, which results in a negative feedback on the system. The model predicts that the change in first indirect aerosol effect (cloud albedo effect) is approximately a factor of ten greater than the change in direct aerosol forcing although this result is highly uncertain due to the crude representation of Arctic clouds and aerosol-cloud interactions in the model. This study shows that both the natural aerosol direct and first indirect effects are strongly dependent on the surface albedo, highlighting the strong coupling between sea <span class="hlt">ice</span>, aerosols, Arctic clouds and their radiative effects.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C13A0803S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C13A0803S"><span>Separating Continental Mineral Dust from Cosmic Dust using Platinum Group Element <span class="hlt">Concentrations</span> and Osmium Isotopes in Ancient Polar <span class="hlt">Ice</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Seo, J. H.; Jackson, B.; Osterberg, E. C.; Sharma, M.</p> <p>2015-12-01</p> <p>The platinum group element (PGEs: Pt, Pd, Rh, Ir, Os, and Ru) accumulation in ancient polar archives have been argued to trace cosmic dust and "smoke" from larger meteors but the PGE <span class="hlt">concentration</span> data lack specificity. For example, the extent to which the terrestrial volcanism/dust has contributed to the PGE inventory of polar <span class="hlt">ice</span> cannot be readily evaluated. Since the Os isotope compositions (187Os/188Os ratio) of the terrestrial and extraterrestrial sources are distinctly different from each other, the PGE <span class="hlt">concentrations</span> when combined with Os isotope composition have the potential to untangle contributions from these sources. Platinum group element <span class="hlt">concentration</span> determinations in polar <span class="hlt">ice</span> cores are highly challenging due to their extremely low <span class="hlt">concentrations</span> (down to 10-15 g/g or fg/g). Here, a new procedure is presented that allows PGEs and Os isotope compositions to be determined from a ~50 g sample of polar <span class="hlt">ice</span>. Decontaminated <span class="hlt">ice</span>-melt is spiked with 101Ru, 106Pd, 190Os, 191Ir, and 198Pt and frozen at -20 °C in quartz-glass ampoules. A mixture of purified HNO3 and H2O2 is then added and the sample is heated to 300 °C at 128bar using a High Pressure Asher. This allows all spikes to be equilibrated with the sample PGEs and all Os species are oxidized to OsO4. The resulting OsO4 is extracted using distillation, purified, and measured using negative thermal ionization mass spectrometry. PGEs are then separated and purified using two stage column chromatography and their <span class="hlt">concentrations</span> determined by isotope dilution using a triple quadruople inductively coupled plasma mass spectrometer coupled to an Apex de-solvation nebulizer. The developed method was applied to modern Greenland firn and snow. The PGE <span class="hlt">concentrations</span> of the firn are 4.0 fg/g for Ir, 20 fg/g for Ru, 590 fg/g for Pt, 38 fg/g for Pd, and 1.3 fg/g for Os, while those of the snow are 3.0 fg/g for Ir, 53 fg/g for Ru, 360 fg/g for Pt, 32 fg/g for Pd, and 0.4 fg/g for Os, respectively. A comparison</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016ACP....16..927L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016ACP....16..927L"><span>Influence of the ambient humidity on the <span class="hlt">concentration</span> of natural deposition-mode <span class="hlt">ice</span>-nucleating particles</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>López, M. L.; Ávila, E. E.</p> <p>2016-01-01</p> <p>This study reports measurements of deposition-mode <span class="hlt">ice</span>-nucleating particle (INP) <span class="hlt">concentrations</span> at ground level during the period July-December 2014 in Córdoba, Argentina. Ambient air was sampled into a cloud chamber where the INP <span class="hlt">concentration</span> was measured at a temperature of -25 °C and a 15 % supersaturation over <span class="hlt">ice</span>. Measurements were performed on days with different thermodynamic conditions, including rainy days. The effect of the relative humidity at ground level (RHamb) on the INP <span class="hlt">concentration</span> was analyzed. The number of INPs activated varied from 1 L-1 at RHamb of 25 % to 30 L-1 at RHamb of 90 %. In general, a linear trend between the INP <span class="hlt">concentration</span> and the RHamb was found, suggesting that this variability must be related to the effectiveness of the aerosols acting as INPs. From the backward trajectories analysis, it was found that the link between INP <span class="hlt">concentration</span> and RHamb is independent of the origin of the air masses. The role of biological INPs and nucleation occurring in pores and cavities was discussed as a possible mechanism to explain the increase of the INP <span class="hlt">concentration</span> during high ambient relative humidity events. This work provides valuable measurements of deposition-mode INP <span class="hlt">concentrations</span> from the Southern Hemisphere where INP data are sparse so far.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016CliPa..12.1829K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016CliPa..12.1829K"><span>The effect of greenhouse gas <span class="hlt">concentrations</span> and <span class="hlt">ice</span> sheets on the glacial AMOC in a coupled climate model</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Klockmann, Marlene; Mikolajewicz, Uwe; Marotzke, Jochem</p> <p>2016-09-01</p> <p>Simulations with the Max Planck Institute Earth System Model (MPI-ESM) are used to study the sensitivity of the AMOC and the deep-ocean water masses during the Last Glacial Maximum to different sets of forcings. Analysing the individual contributions of the glacial forcings reveals that the <span class="hlt">ice</span> sheets cause an increase in the overturning strength and a deepening of the North Atlantic Deep Water (NADW) cell, while the low greenhouse gas (GHG) <span class="hlt">concentrations</span> cause a decrease in overturning strength and a shoaling of the NADW cell. The effect of the orbital configuration is negligible. The effects of the <span class="hlt">ice</span> sheets and the GHG reduction balance each other in the deep ocean so that no shoaling of the NADW cell is simulated in the full glacial state. Experiments in which different GHG <span class="hlt">concentrations</span> with linearly decreasing radiative forcing are applied to a setup with glacial <span class="hlt">ice</span> sheets and orbital configuration show that GHG <span class="hlt">concentrations</span> below the glacial level are necessary to cause a shoaling of the NADW cell with respect to the pre-industrial state in MPI-ESM. For a pCO2 of 149 ppm, the simulated overturning state and the deep-ocean water masses are in best agreement with the glacial state inferred from proxy data. Sensitivity studies confirm that brine release and shelf convection in the Southern Ocean are key processes for the shoaling of the NADW cell. Shoaling occurs only when Southern Ocean shelf water contributes significantly to the formation of Antarctic Bottom Water.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20090038693','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20090038693"><span>Estimation of Sea <span class="hlt">Ice</span> Thickness Distributions through the Combination of Snow Depth and Satellite Laser Altimetry Data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Kurtz, Nathan T.; Markus, Thorsten; Cavalieri, Donald J.; Sparling, Lynn C.; Krabill, William B.; Gasiewski, Albin J.; Sonntag, John G.</p> <p>2009-01-01</p> <p>Combinations of sea <span class="hlt">ice</span> freeboard and snow depth measurements from satellite data have the potential to provide a means to derive global sea <span class="hlt">ice</span> 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-<span class="hlt">ice</span> 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 <span class="hlt">ice</span> allowing the development of a method for estimating sea <span class="hlt">ice</span> thickness from satellite laser altimetry data at their full spatial resolution. This method is used to estimate snow and <span class="hlt">ice</span> thicknesses for the Arctic basin through the combination of freeboard data from ICESat, snow depth data over first-year <span class="hlt">ice</span> from <span class="hlt">AMSR-E</span>, and snow depth over multiyear <span class="hlt">ice</span> from climatological data. Due to the non-linear dependence of heat flux on <span class="hlt">ice</span> thickness, the impact on heat flux calculations when maintaining the full resolution of the ICESat data for <span class="hlt">ice</span> thickness estimates is explored for typical winter conditions. Calculations of the basin-wide mean heat flux and <span class="hlt">ice</span> growth rate using snow and <span class="hlt">ice</span> 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 <span class="hlt">ice</span> thickness values.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28298529','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28298529"><span>Deep-sea coral evidence for lower Southern Ocean surface nitrate <span class="hlt">concentrations</span> during the last <span class="hlt">ice</span> age.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Wang, Xingchen Tony; Sigman, Daniel M; Prokopenko, Maria G; Adkins, Jess F; Robinson, Laura F; Hines, Sophia K; Chai, Junyi; Studer, Anja S; Martínez-García, Alfredo; Chen, Tianyu; Haug, Gerald H</p> <p>2017-03-28</p> <p>The Southern Ocean regulates the ocean's biological sequestration of CO2 and is widely suspected to underpin much of the <span class="hlt">ice</span> age decline in atmospheric CO2 <span class="hlt">concentration</span>, but the specific changes in the region are debated. Although more complete drawdown of surface nutrients by phytoplankton during the <span class="hlt">ice</span> ages is supported by some sediment core-based measurements, the use of different proxies in different regions has precluded a unified view of Southern Ocean biogeochemical change. Here, we report measurements of the (15)N/(14)N of fossil-bound organic matter in the stony deep-sea coral Desmophyllum dianthus, a tool for reconstructing surface ocean nutrient conditions. The central robust observation is of higher (15)N/(14)N across the Southern Ocean during the Last Glacial Maximum (LGM), 18-25 thousand years ago. These data suggest a reduced summer surface nitrate <span class="hlt">concentration</span> in both the Antarctic and Subantarctic Zones during the LGM, with little surface nitrate transport between them. After the <span class="hlt">ice</span> age, the increase in Antarctic surface nitrate occurred through the deglaciation and continued in the Holocene. The rise in Subantarctic surface nitrate appears to have had both early deglacial and late deglacial/Holocene components, preliminarily attributed to the end of Subantarctic iron fertilization and increasing nitrate input from the surface Antarctic Zone, respectively.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AIPC.1531..103K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AIPC.1531..103K"><span>Retrieval of volcanic ash and <span class="hlt">ice</span> cloud physical properties together with gas <span class="hlt">concentration</span> from IASI measurements using the AVL model</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kochenova, S.; De Mazière, M.; Kumps, N.; Vandenbussche, S.; Kerzenmacher, T.</p> <p>2013-05-01</p> <p>Observation and tracking of volcanic aerosols are important for preventing possible aviation hazards and determining the influence of aerosols on climate. The useful information primary includes the <span class="hlt">concentration</span>, particle size and altitude of aerosol load. Moreover, volcanic eruptions are usually accompanied by strong emissions of SO2 and enhanced <span class="hlt">concentrations</span> of H2O in the atmosphere. Volcanic ash particles can also catalyze the formation of <span class="hlt">ice</span> clouds by serving as cloud nuclei. Hyperspectral infrared sounders, such as IASI (Infrared Atmospheric Sounding Interferometer), have proven to be powerful tools for capturing volcanic aerosol and <span class="hlt">ice</span> cloud signatures and enhanced volcanic gas <span class="hlt">concentrations</span>. Information on atmospheric constituents is extracted from such hyperspectral measurements with the help of radiative transfer (RT) codes capable of solving both direct and inverse RT problems. We will demonstrate the retrieval of aerosol and <span class="hlt">ice</span> cloud physical properties together with gas <span class="hlt">concentration</span> from IASI measurements with the help of the AVL RT model. AVL is one of the 'code combination packages' which are becoming more and more popular in the scientific domain. It consists of several codes, each of which handles a specific set of physics-related tasks. The codes function smoothly as a whole due to the use of a special interface. AVL is perfectly suitable (i) to model the propagation of UV-visible-IR radiation through a coupled atmosphere-surface system for a wide range of atmospheric, spectral and geometrical conditions; and (ii) to retrieve vertical gas profiles and aerosol <span class="hlt">concentration</span> through the use of its embedded retrieval algorithm on the basis of an optimal estimation method (OEM). The retrievals are performed for IASI measurements (radiance, Level 1C product) carried out over Eyjafjallajökull volcano, Iceland, in April 2010.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFM.A21A0107K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFM.A21A0107K"><span>Recent Increase in Black Carbon <span class="hlt">Concentrations</span> from a Mt. Everest <span class="hlt">Ice</span> Core Spanning 1860-2000 AD</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kaspari, S.; Schwikowski, M.; Gysel, M.; Mayewski, P. A.; Kang, S.; Hou, S.</p> <p>2009-12-01</p> <p>Black carbon produced by the incomplete combustion of biomass, coal and diesel fuels can significantly contribute to climate change by altering the Earth’s radiative balance. Black carbon in the atmosphere absorbs light and causes atmospheric heating, whereas black carbon deposited on snow and <span class="hlt">ice</span> can significantly reduce the surface albedo, resulting in rapid melting of snow and <span class="hlt">ice</span>. Historical records of black carbon <span class="hlt">concentration</span> and distribution in the atmosphere are needed to determine the role of black carbon in climate change, however most studies have relied on estimated inventories based on wood and/or fossil fuel consumption data. Reconstructing black carbon <span class="hlt">concentrations</span> in Asia is particularly important because this region has some of the largest black carbon sources globally, which negatively impact climate, water resources, agriculture and human health. We analyzed a Mt. Everest <span class="hlt">ice</span> core for black carbon using a single particle soot photometer (SP2). The high-resolution black carbon data demonstrates strong seasonality, with peak <span class="hlt">concentrations</span> during the winter-spring, and low <span class="hlt">concentrations</span> during the summer monsoon season. Black carbon <span class="hlt">concentrations</span> from 1975-2000 relative to 1860-1975 have increased approximately threefold, and the timing of this increase is consistent with black carbon emission inventory data from South Asia. It is notable that there is no increasing trend in iron (used as a proxy for dust) since 1860. This is significant because it suggests that if the recent retreat of glaciers in the region is due, at least in part, to the effect of impurities on snow albedo, the reduced albedo is due to changes in black carbon emissions, not dust.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://pubs.er.usgs.gov/publication/70026040','USGSPUBS'); return false;" href="http://pubs.er.usgs.gov/publication/70026040"><span>Oxygen-18 <span class="hlt">concentrations</span> in recent precipitation and <span class="hlt">ice</span> cores on the Tibetan Plateau</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Tian, L.; Yao, T.; Schuster, P.F.; White, J.W.C.; Ichiyanagi, K.; Pendall, Elise; Pu, J.; Yu, W.</p> <p>2003-01-01</p> <p>A detailed study of the climatic significance of ??18O in precipitation was completed on a 1500 km southwest-northeast transect of the Tibetan Plateau in central Asia. Precipitation samples were collected at four meteorological stations for up to 9 years. This study shows that the gradual impact of monsoon precipitation affects the spatial variation of ??18O-T relationship along the transect. Strong monsoon activity in the southern Tibetan Plateau results in high precipitation rates and more depleted heavy isotopes. This depletion mechanism is described as a precipitation "amount effect" and results in a poor ??18O-T relationship at both seasonal and annual scales. In the middle of the Tibetan Plateau, the effects of the monsoon are diminished but continue to cause a reduced correlation of ??18O and temperature at the annual scale. At the monthly scale, however, a significant ??18O-T relationship does exist. To the north of the Tibetan Plateau beyond the extent of the effects of monsoon precipitation, ??18O in precipitation shows a strong temperature dependence. ??18O records from two shallow <span class="hlt">ice</span> cores and historic air temperature data were compared to verify the modern ??18O-T relationship. ??18O in Dunde <span class="hlt">ice</span> core was positively correlated with air temperature from a nearby meteorological station in the north of the plateau. The ??18O variation in an <span class="hlt">ice</span> core from the southern Plateau, however, was inversely correlated with precipitation amount at a nearby meteorological station and also the accumulation record in the <span class="hlt">ice</span> core. The long-term variation of ??18O in the <span class="hlt">ice</span> core record in the monsoon regions of the southern Tibetan Plateau suggest past monsoon seasons were probably more expansive. It is still unclear, however, how changes in large-scale atmosphere circulation might influence summer monsoon precipitation on the Tibetan Plateau.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AtmEn..75..188B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AtmEn..75..188B"><span>Measuring a 10,000-fold enhancement of singlet molecular oxygen (1O2*) <span class="hlt">concentration</span> on illuminated <span class="hlt">ice</span> relative to the corresponding liquid solution</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bower, Jonathan P.; Anastasio, Cort</p> <p>2013-08-01</p> <p>Much attention has focused on the highly reactive hydroxyl radical in the oxidation of trace organic compounds on snow and <span class="hlt">ice</span> (and subsequent release of volatile organics to the atmospheric boundary layer) but other oxidants are likely also important in this processing. Here we examine the <span class="hlt">ice</span> chemistry of singlet molecular oxygen (1O2*), which can be significant in atmospheric water drops but has not been examined in <span class="hlt">ice</span> or snow. To examine 1O2* on <span class="hlt">ice</span> we illuminate laboratory <span class="hlt">ices</span> containing Rose Bengal (RB) as the source of 1O2*, furfuryl alcohol (FFA) as the probe, and Na2SO4 to control the total solute <span class="hlt">concentration</span>. We find that the 1O2*-mediated loss of FFA (and, thus, the 1O2* <span class="hlt">concentration</span>) is up to 11,000 times greater on <span class="hlt">ice</span> than in the equivalent liquid sample at the same photon flux. We attribute this large increase in the 1O2* steady-state <span class="hlt">concentration</span> to the freeze-<span class="hlt">concentration</span> of solutes into liquid-like regions (LLRs) in/on <span class="hlt">ice</span>: compared to the initial solution, in the LLRs of <span class="hlt">ice</span> the sources for 1O2* are highly <span class="hlt">concentrated</span>, while the <span class="hlt">concentration</span> of the dominant sink for 1O2* (i.e., water) remains largely unchanged. Similar to results expected in liquid solution, rates of FFA loss in <span class="hlt">ice</span> depend on both the initial sensitizer <span class="hlt">concentration</span> and temperature, providing evidence that these reactions occur in LLRs. However, we find that the enhancement in 1O2* <span class="hlt">concentrations</span> on <span class="hlt">ice</span> does not follow predictions from freezing-point depression, likely because experiments were conducted below the eutectic temperature for sodium sulfate, where all of the salt should have precipitated. We also explore a method for separating 1O2* and rad OH contributions to FFA oxidation in laboratory <span class="hlt">ices</span> and show its application to two natural snow samples. We find that 1O2* <span class="hlt">concentrations</span> in these snows are approximately 100 times higher than observed in polluted, mid-latitude fog waters, showing that the enhancement of 1O2* on <span class="hlt">ice</span> is environmentally relevant and that</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20050179461','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20050179461"><span>Sea <span class="hlt">Ice</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Parkinson, Claire L.; Cavalieri, Donald J.</p> <p>2005-01-01</p> <p>Sea <span class="hlt">ice</span> covers vast areas of the polar oceans, with <span class="hlt">ice</span> 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 <span class="hlt">ice</span> 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 <span class="hlt">ice</span> 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 <span class="hlt">ice</span> covers, and many studies suggest possible connections between the <span class="hlt">ice</span> 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 <span class="hlt">ice</span> coverage in the Arctic and increased <span class="hlt">ice</span> coverage in the Antarctic from late 1978 through the end of 2003, with the Antarctic <span class="hlt">ice</span> increases following marked decreases in the Antarctic <span class="hlt">ice</span> during the 1970s. For a detailed picture of the seasonally varying <span class="hlt">ice</span> cover at the start of the 21st century, this chapter includes <span class="hlt">ice</span> <span class="hlt">concentration</span> 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 <span class="hlt">ice</span> covers from the 1970s through 2003.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016ESASP.740E.336B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016ESASP.740E.336B"><span>Singular Value Decomposition Analysis of Cloud Fraction Cover and Sea <span class="hlt">Ice</span> <span class="hlt">Concentration</span> over the Arctic Region, 1982-2009</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Boccolari, Mauro; Parmiggiani, Flavio</p> <p>2016-08-01</p> <p>In this study, the coupled spatial and temporal variability between seasonal data of Cloud Fraction Cover (CFC) and Sea <span class="hlt">Ice</span> <span class="hlt">Concentration</span> (SIC) in the Arctic Ocean for the 1982-2009 period were investigated by using the Singular Value Decomposition (SVD) method.The spatial patterns of CFCs related to the first mode of co-variability, identify the maximum covariance, for all seasons, in the Barents Sea and in the Arctic Ocean Canada, while the SIC and 'found in the Chukchi Sea in autumn (in according to the maximum sea <span class="hlt">ice</span> melting) and the Barents sea during both the winter and spring.CFC spatial patterns related to the first mode of co- variability, locate maximum covariance, for all seasons, in the Barents Sea and in the Canadian side of the Arctic Ocean, while for SIC is found in the Chukchi Sea during autumn (corresponding to the maximum sea <span class="hlt">ice</span> melting) and in the Barents Sea during both the winter and spring.Finally, the correlation between the seasonal time series of expansion coefficients derived from the SVD analysis, for both CFC and SIC fields, with the seasonal time series of some relevant climate indices for the Arctic (NAO, AO, PDO and PNA). Statistically significant values for both fields were found during summer with the AO, and during autumn with the PNA.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li class="active"><span>13</span></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_13 --> <div id="page_14" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li class="active"><span>14</span></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="261"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20080047000&hterms=exports&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dexports','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20080047000&hterms=exports&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dexports"><span>Baffin Bay <span class="hlt">Ice</span> Drift and Export: 2002-2007</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Kwok, Ron</p> <p>2007-01-01</p> <p>Multiyear estimates of sea <span class="hlt">ice</span> drift in Baffin Bay and Davis Strait are derived for the first time from the 89 GHz channel of the <span class="hlt">AMSR-E</span> instrument. Uncertainties in the drift estimates, assessed with Envisat <span class="hlt">ice</span> motion, are approximately 2-3 km/day. A persistent atmospheric trough, between the coast of Greenland and Baffin Island, drives the prevailing southward drift pattern with average daily displacements in excess of 18-20 km during winter. Over the 5-year record, the <span class="hlt">ice</span> export ranges between 360 and 675 x 10(exp 3) km(exp 2), with an average of 530 x 10(exp 3) km(exp 2). Sea <span class="hlt">ice</span> area inflow from the Nares Strait, Lancaster Sound and Jones Sound potentially contribute up to a third of the net area outflow while <span class="hlt">ice</span> production at the North Water Polynya contributes the balance. Rough estimates of annual volume export give approximately 500-800 km(exp 3). Comparatively, these are approximately 70% and approximately 30% of the annual area and Strait.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://pubs.er.usgs.gov/publication/70012918','USGSPUBS'); return false;" href="http://pubs.er.usgs.gov/publication/70012918"><span><span class="hlt">Concentrations</span> and source areas of <span class="hlt">ice</span> nuclei in the Alaskan atmosphere.</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Fountain, A.G.; Ohtake, T.</p> <p>1985-01-01</p> <p>The results indicate a seasonal variation in nucleus <span class="hlt">concentration</span> with a winter minimum and a north-to-south trend in the increasing average <span class="hlt">concentration</span>. Some episodes of high <span class="hlt">concentrations</span> were correlated with 500 mb isobaric transport from Eurasia and 700 mb cyclogenesis over Alaska. These results suggest that local nucleus sources play a dominant role in the seasonal variation, while some individual episodes are caused by external or regional influences. -from Authors</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/19729005','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/19729005"><span>Measurement of the size of intracellular <span class="hlt">ice</span> crystals in mouse oocytes using a melting point depression method and the influence of intracellular solute <span class="hlt">concentrations</span>.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Han, Xu; Critser, John K</p> <p>2009-12-01</p> <p>Characterization of intracellular <span class="hlt">ice</span> formed during the cooling procedures of cells significantly benefits the development and optimization design of cryopreservation or cryosurgery techniques. In this study, we investigated the influence of the <span class="hlt">concentration</span> of extracellular non-permeable and permeable solutes on the melting points of the intracellular <span class="hlt">ice</span> in mouse oocytes using cryomicroscopy. The results showed that the melting points of the intracellular <span class="hlt">ice</span> are always lower than the extracellular <span class="hlt">ice</span>. Based on this observation and the Gibbs-Thomson relation, we established a physical model to calculate the size of intracellular <span class="hlt">ice</span> crystals and described its relationship with the <span class="hlt">concentrations</span> of intracellular permeating solutes and macromolecules. This model predicts that the increased <span class="hlt">concentration</span> of macromolecules in cells, by increasing the extracellular non-permeating solute <span class="hlt">concentration</span>, can significantly lower the required <span class="hlt">concentration</span> of permeable solutes for intracellular vitrification. The prediction was tested through the cryomicroscopic observation of the co-existence of intracellular vitrification and extracellular crystallization during cooling at 100 degrees C/min when the extracellular solutions contain 5 molal (m) ethylene glycol and 0.3 to 0.6m NaCl.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27794227','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27794227"><span>Sea <span class="hlt">ice</span>-associated decline in body condition leads to increased <span class="hlt">concentrations</span> of lipophilic pollutants in polar bears (Ursus maritimus) from Svalbard, Norway.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Tartu, Sabrina; Bourgeon, Sophie; Aars, Jon; Andersen, Magnus; Polder, Anuschka; Thiemann, Gregory W; Welker, Jeffrey M; Routti, Heli</p> <p>2017-01-15</p> <p>Global climate changes are magnified in the Arctic and are having an especially dramatic effect on the spatial and temporal distribution and the thickness traits of sea <span class="hlt">ice</span>. Decline of Arctic sea <span class="hlt">ice</span> may lead to qualitative and/or quantitative changes in diet and reduced body condition (i.e. adipose tissue stores) of <span class="hlt">ice</span>-associated apex predators such as polar bears (Ursus maritimus). This may further affect their tissue <span class="hlt">concentrations</span> of lipophilic pollutants. We determined how variations in adipose tissue stores associated to both breeding status and spatial changes in sea <span class="hlt">ice</span> conditions and diet influence <span class="hlt">concentrations</span> and biotransformation of lipophilic persistent organic pollutants (POPs). We collected 112 blood and fat samples from female polar bears (Ursus maritimus) of different breeding status (alone, with cubs of the year, or with yearlings) during two seasons (April and September) in 2012 and 2013 at three locations of Svalbard, Norway, with contrasted sea <span class="hlt">ice</span> conditions. We inferred diet from nitrogen and carbon stable isotope ratios in red blood cells and fatty acid composition in adipose tissue. Relative to diet, body condition, which was negatively related to sea <span class="hlt">ice</span> extent at both temporal and spatial scales, was the most important predictor for <span class="hlt">concentrations</span> of POPs in plasma and fat, whereas diet showed a minor influence. Additionally, fatter females were more efficient at biotransforming PCBs than were leaner ones. Breeding status influenced the <span class="hlt">concentrations</span> of less lipophilic compounds such as β-hexachlorocyclohexane, which were lower in females with yearlings, probably due to excretion into milk and subsequent offloading to young. In conclusion, our results indicate that declining sea <span class="hlt">ice</span> indirectly leads to increased <span class="hlt">concentrations</span> of lipophilic pollutants in polar bears mediated through reduced feeding opportunities and declining body condition rather than changes in diet composition.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011E%26PSL.307..334S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011E%26PSL.307..334S"><span>On the suitability of partially clathrated <span class="hlt">ice</span> for analysis of <span class="hlt">concentration</span> and δ 13C of palaeo-atmospheric CO 2</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Schaefer, Hinrich; Lourantou, Anna; Chappellaz, Jérôme; Lüthi, Dieter; Bereiter, Bernhard; Barnola, Jean-Marc</p> <p>2011-07-01</p> <p>The stable carbon isotopic signature of carbon dioxide (δ 13CO 2) measured in the air occlusions of polar <span class="hlt">ice</span> provides important constraints on the carbon cycle in past climates. In order to exploit this information for previous glacial periods, one must use deep, clathrated <span class="hlt">ice</span>, where the occluded air is preserved not in bubbles but in the form of air hydrates. Therefore, it must be established whether the original atmospheric δ 13CO 2 signature can be reconstructed from clathrated <span class="hlt">ice</span>. We present a comparative study using coeval bubbly <span class="hlt">ice</span> from Berkner Island and <span class="hlt">ice</span> from the bubble-clathrate transformation zone (BCTZ) of EPICA Dome C (EDC). In the EDC samples the gas is partitioned into clathrates and remaining bubbles as shown by erroneously low and scattered CO 2 <span class="hlt">concentration</span> values, presenting a worst-case test for δ 13CO 2 reconstructions. Even so, the reconstructed atmospheric δ 13CO 2 values show only slightly larger scatter. The difference to data from coeval bubbly <span class="hlt">ice</span> is statistically significant. However, the 0.16‰ magnitude of the offset is small for practical purposes, especially in light of uncertainty from non-uniform corrections for diffusion related fractionation that could contribute to the discrepancy. Our results are promising for palaeo-atmospheric studies of δ 13CO 2 using a ball mill dry extraction technique below the BCTZ of <span class="hlt">ice</span> cores, where gas is not subject to fractionation into microfractures and between clathrate and bubble reservoirs.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24268400','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24268400"><span>Physicochemical, bioactive, and sensory properties of persimmon-based <span class="hlt">ice</span> cream: technique for order preference by similarity to ideal solution to determine optimum <span class="hlt">concentration</span>.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Karaman, Safa; Toker, Ömer Said; Yüksel, Ferhat; Çam, Mustafa; Kayacier, Ahmed; Dogan, Mahmut</p> <p>2014-01-01</p> <p>In the present study, persimmon puree was incorporated into the <span class="hlt">ice</span> cream mix at different <span class="hlt">concentrations</span> (8, 16, 24, 32, and 40%) and some physicochemical (dry matter, ash, protein, pH, sugar, fat, mineral, color, and viscosity), textural (hardness, stickiness, and work of penetration), bioactive (antiradical activity and total phenolic content), and sensory properties of samples were investigated. The technique for order preference by similarity to ideal solution approach was used for the determination of optimum persimmon puree <span class="hlt">concentration</span> based on the sensory and bioactive characteristics of final products. Increase in persimmon puree resulted in a decrease in the dry matter, ash, fat, protein contents, and viscosity of <span class="hlt">ice</span> cream mix. Glucose, fructose, sucrose, and lactose were determined to be major sugars in the <span class="hlt">ice</span> cream samples including persimmon and increase in persimmon puree <span class="hlt">concentration</span> increased the fructose and glucose content. Better melting properties and textural characteristics were observed for the samples with the addition of persimmon. Magnesium, K, and Ca were determined to be major minerals in the samples and only K <span class="hlt">concentration</span> increased with the increase in persimmon content. Bioactive properties of <span class="hlt">ice</span> cream samples improved and, in general, acetone-water extracts showed higher bioactivity compared with ones obtained using methanol-water extracts. The technique for order preference by similarity to ideal solution approach showed that the most preferred sample was the <span class="hlt">ice</span> cream containing 24% persimmon puree.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.C11B..05N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.C11B..05N"><span>Freeze <span class="hlt">concentration</span> effects on <span class="hlt">ice</span> (photo) chemical kinetics investigated by UV-Vis spectroscopy</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Newberg, J. T.; Arble, C.; Zhang, J.</p> <p>2013-12-01</p> <p>We will describe the setup of a fiber coupled UV-Vis spectrometer to investigate the chemistry and photochemistry of aqueous solutions before and after freezing. The photochemical degradation of pyranine at the isosbestic point was investigated. Direct photochemical degradation was minor compared to indirect degradation through hydroxyl radical (OH) attack at room temperature. At -10 C indirect OH degradation was increased relative to room temperature studies, and has been attributed to the freeze <span class="hlt">concentration</span> effect. The reaction of bromate with bromide in the presence of acid to form molecular bromine was investigated. Upon freezing the formation rate of bromine significantly increases, which we attribute to the freeze <span class="hlt">concentration</span> effect.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015ACP....15.2313B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015ACP....15.2313B"><span>Persistent after-effects of heavy rain on <span class="hlt">concentrations</span> of <span class="hlt">ice</span> nuclei and rainfall suggest a biological cause</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bigg, E. K.; Soubeyrand, S.; Morris, C. E.</p> <p>2015-03-01</p> <p>Rainfall is one of the most important aspects of climate, but the extent to which atmospheric <span class="hlt">ice</span> nuclei (IN) influence its formation, quantity, frequency, and location is not clear. Microorganisms and other biological particles are released following rainfall and have been shown to serve as efficient IN, in turn impacting cloud and precipitation formation. Here we investigated potential long-term effects of IN on rainfall frequency and quantity. Differences in IN <span class="hlt">concentrations</span> and rainfall after and before days of large rainfall accumulation (i.e., key days) were calculated for measurements made over the past century in southeastern and southwestern Australia. Cumulative differences in IN <span class="hlt">concentrations</span> and daily rainfall quantity and frequency as a function of days from a key day demonstrated statistically significant increasing logarithmic trends (R2 > 0.97). Based on observations that cumulative effects of rainfall persisted for about 20 days, we calculated cumulative differences for the entire sequence of key days at each site to create a historical record of how the differences changed with time. Comparison of pre-1960 and post-1960 sequences most commonly showed smaller rainfall totals in the post-1960 sequences, particularly in regions downwind from coal-fired power stations. This led us to explore the hypothesis that the increased leaf surface populations of IN-active bacteria due to rain led to a sustained but slowly diminishing increase in atmospheric <span class="hlt">concentrations</span> of IN that could potentially initiate or augment rainfall. This hypothesis is supported by previous research showing that leaf surface populations of the <span class="hlt">ice</span>-nucleating bacterium Pseudomonas syringae increased by orders of magnitude after heavy rain and that microorganisms become airborne during and after rain in a forest ecosystem. At the sites studied in this work, aerosols that could have initiated rain from sources unrelated to previous rainfall events (such as power stations) would</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/19185125','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/19185125"><span>An ultra-clean technique for accurately analysing Pb isotopes and heavy metals at high spatial resolution in <span class="hlt">ice</span> cores with sub-pg g(-1) Pb <span class="hlt">concentrations</span>.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Burn, Laurie J; Rosman, Kevin J R; Candelone, Jean-Pierre; Vallelonga, Paul; Burton, Graeme R; Smith, Andrew M; Morgan, Vin I; Barbante, Carlo; Hong, Sungmin; Boutron, Claude F</p> <p>2009-02-23</p> <p>Measurements of Pb isotope ratios in <span class="hlt">ice</span> containing sub-pg g(-1) <span class="hlt">concentrations</span> are easily compromised by contamination, particularly where limited sample is available. Improved techniques are essential if Antarctic <span class="hlt">ice</span> cores are to be analysed with sufficient spatial resolution to reveal seasonal variations due to climate. This was achieved here by using stainless steel chisels and saws and strict protocols in an ultra-clean cold room to decontaminate and section <span class="hlt">ice</span> cores. Artificial <span class="hlt">ice</span> cores, prepared from high purity water were used to develop and refine the procedures and quantify blanks. Ba and In, two other important elements present at pg g(-1) and fg g(-1) <span class="hlt">concentrations</span> in Polar <span class="hlt">ice</span>, were also measured. The final blank amounted to 0.2+/-0.2 pg of Pb with (206)Pb/(207)Pb and (208)Pb/(207)Pb ratios of 1.16+/-0.12 and 2.35+/-0.16, respectively, 1.5+/-0.4 pg of Ba and 0.6+/-2.0 fg of In, most of which probably originates from abrasion of the steel saws by the <span class="hlt">ice</span>. The procedure was demonstrated on a Holocene Antarctic <span class="hlt">ice</span> core section and was shown to contribute blanks of only approximately 5%, approximately 14% and approximately 0.8% to monthly resolved samples with respective Pb, Ba and In <span class="hlt">concentrations</span> of 0.12 pg g(-1), 0.3 pg g(-1) and 2.3 fg g(-1). Uncertainties in the Pb isotopic ratio measurements were degraded by only approximately 0.2%.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012ACP....12..727G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012ACP....12..727G"><span>On the observation of unusual high <span class="hlt">concentration</span> of small chain-like aggregate <span class="hlt">ice</span> crystals and large <span class="hlt">ice</span> water contents near the top of a deep convective cloud during the CIRCLE-2 experiment</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gayet, J.-F.; Mioche, G.; Bugliaro, L.; Protat, A.; Minikin, A.; Wirth, M.; Dörnbrack, A.; Shcherbakov, V.; Mayer, B.; Garnier, A.; Gourbeyre, C.</p> <p>2012-01-01</p> <p>During the CIRCLE-2 experiment carried out over Western Europe in May 2007, combined in situ and remote sensing observations allowed to describe microphysical and optical properties near-top of an overshooting convective cloud (11 080 m/-58 °C). The airborne measurements were performed with the DLR Falcon aircraft specially equipped with a unique set of instruments for the extensive in situ cloud measurements of microphysical and optical properties (Polar Nephelometer, FSSP-300, Cloud Particle Imager and PMS 2-D-C) and nadir looking remote sensing observations (DLR WALES Lidar). Quasi-simultaneous space observations from MSG/SEVIRI, CALIPSO/CALIOP-WFC-IIR and CloudSat/CPR combined with airborne RASTA radar reflectivity from the French Falcon aircraft flying above the DLR Falcon depict very well convective cells which overshoot by up to 600 m the tropopause level. Unusual high values of the <span class="hlt">concentration</span> of small <span class="hlt">ice</span> particles, extinction, <span class="hlt">ice</span> water content (up to 70 cm-3, 30 km-1 and 0.5 g m-3, respectively) are experienced. The mean effective diameter and the maximum particle size are 43 μm and about 300 μm, respectively. This very dense cloud causes a strong attenuation of the WALES and CALIOP lidar returns. The SEVIRI retrieved parameters confirm the occurrence of small <span class="hlt">ice</span> crystals at the top of the convective cell. Smooth and featureless phase functions with asymmetry factors of 0.776 indicate fairly uniform optical properties. Due to small <span class="hlt">ice</span> crystals the power-law relationship between <span class="hlt">ice</span> water content (IWC) and radar reflectivity appears to be very different from those usually found in cirrus and anvil clouds. For a given equivalent reflectivity factor, IWCs are significantly larger for the overshooting cell than for the cirrus. Assuming the same prevalent microphysical properties over the depth of the overshooting cell, RASTA reflectivity profiles scaled into <span class="hlt">ice</span> water content show that retrieved IWC up to 1 g m-3 may be observed near the cloud top</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2003EAEJA....12815H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2003EAEJA....12815H"><span>Data sets for snow cover monitoring and modelling from the National Snow and <span class="hlt">Ice</span> Data Center</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Holm, M.; Daniels, K.; Scott, D.; McLean, B.; Weaver, R.</p> <p>2003-04-01</p> <p>A wide range of snow cover monitoring and modelling data sets are pending or are currently available from the National Snow and <span class="hlt">Ice</span> Data Center (NSIDC). In-situ observations support validation experiments that enhance the accuracy of remote sensing data. In addition, remote sensing data are available in near-real time, providing coarse-resolution snow monitoring capability. Time series data beginning in 1966 are valuable for modelling efforts. NSIDC holdings include SMMR and SSM/I snow cover data, MODIS snow cover extent products, in-situ and satellite data collected for NASA's recent Cold Land Processes Experiment, and soon-to-be-released ASMR-E passive microwave products. The <span class="hlt">AMSR-E</span> and MODIS sensors are part of NASA's Earth Observing System flying on the Terra and Aqua satellites Characteristics of these NSIDC-held data sets, appropriateness of products for specific applications, and data set access and availability will be presented.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A13D0371W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A13D0371W"><span>Impacts of alternative fuels in aviation on microphysical aerosol properties and predicted <span class="hlt">ice</span> nuclei <span class="hlt">concentration</span> at aircraft cruise altitude</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Weinzierl, B.; D'Ascoli, E.; Sauer, D. N.; Kim, J.; Scheibe, M.; Schlager, H.; Moore, R.; Anderson, B. E.; Ullrich, R.; Mohler, O.; Hoose, C.</p> <p>2015-12-01</p> <p>In the past decades air traffic has been substantially growing affecting air quality and climate. According to the International Civil Aviation Authority (ICAO), in the next few years world passenger and freight traffic is expected to increase annually by 6-7% and 4-5%, respectively. One possibility to reduce aviation impacts on the atmosphere and climate might be the replacement of fossil fuels by alternative fuels. However, so far the effects of alternative fuels on particle emissions from aircraft engines and their ability to form contrails remain uncertain. To study the effects of alternative fuels on particle emissions and the formation of contrails, the Alternative Fuel Effects on Contrails and Cruise Emissions (ACCESS) field experiment was conducted in California. In May 2014, the DLR Falcon 20 and the NASA HU-25 jet aircraft were instrumented with an extended aerosol and trace gas payload probing different types of fuels including JP-8 and JP-8 blended with HEFA (Hydroprocessed Esters and Fatty Acids) while the NASA DC8 aircraft acted as the source aircraft for ACCESS-2. Emission measurements were taken in the DC8 exhaust plumes at aircraft cruise level between 9-12 km altitude and at distances between 50 m and 20 km behind the DC8 engines. Here, we will present results from the ACCESS-2 aerosol measurements which show a 30-60% reduction of the non-volatile (mainly black carbon) particle number <span class="hlt">concentration</span> in the aircraft exhaust for the HEFA-blend compared to conventional JP-8 fuel. Size-resolved particle emission indices show the largest reductions for larger particle sizes suggesting that the HEFA blend contains fewer and smaller black carbon particles. We will combine the airborne measurements with a parameterization of deposition nucleation developed during a number of <span class="hlt">ice</span> nucleation experiments at the AIDA chamber in Karlsruhe and discuss the impact of alternative fuels on the abundance of potential <span class="hlt">ice</span> nuclei at cruise conditions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1992Metic..27Q.298T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1992Metic..27Q.298T"><span>Proposed <span class="hlt">Ice</span> Flow, Given 200m and 400m Additional <span class="hlt">Ice</span> in the Allan Hills Region, Antarctica: Implications for Meteorite <span class="hlt">Concentration</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Traub-Metlay, S.; Cassidy, W. A.</p> <p>1992-07-01</p> <p>The Allan Hills-David Glacier region contains some of the most highly populated meteorite stranding surfaces in Antarctica. Nearly 2000 meteorites have to date been collected from the icefields associated with the Allan Hills, and nearly 1500 from areas around Elephant Moraine. While much attention has been focused on the current geological and glaciological conditions of these stranding surfaces, less work has been done concerning what they may have looked like in the past, when <span class="hlt">ice</span> thicknesses may have been greater. In this study, conjectural maps of the current Allan Hills area with 200 meters and 400 meters of additional <span class="hlt">ice</span> cover each are analyzed for probable regional and local <span class="hlt">ice</span> flow patterns. A dramatic decrease in <span class="hlt">ice</span> thickness over a relatively brief period of time could result either from climatic change or a geologically rapid regional uplift. Delisle and Sievers (1991) noted that the valley between the Allan Hills Main Icefield and the Allan Hills resembles a half-graben resulting from east-west extensional tectonics, and that the mesa-like bedrock features associated with the Near Western and Mid Western Icefields resemble fault blocks. They concluded that the Allan Hills area icefields may have become active stranding surfaces as a result of a regional uplift within the past 1-2 million years, assuming a current rate of uplift in the Allan Hills region of ~100 meters/million years. Whether the cause was climatic or tectonic, generalized maps of current <span class="hlt">ice</span> contours plus 400 and 200 meters <span class="hlt">ice</span> may provide views of what the Allan Hills region looked like just before activation of the modern meteorite stranding surfaces (Figs. 1 and 2). At an <span class="hlt">ice</span> thickness greater by 400 meters, <span class="hlt">ice</span> could flow smoothly over the Allan Hills and would drain down to the Mawson Glacier via the Odell Glacier, east of the Allan Hills; down the Manhaul Bay depression between the east and west arms of Allan Hills; and down the half-graben discovered by Delisle and Sievers</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20070016601&hterms=Ecological+zones&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DEcological%2Bzones','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20070016601&hterms=Ecological+zones&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DEcological%2Bzones"><span>Variations in the Sea <span class="hlt">Ice</span> Edge and the Marginal <span class="hlt">Ice</span> Zone on Different Spatial Scales as Observed from Different Satellite Sensor</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Markus, Thorsten; Henrichs, John</p> <p>2006-01-01</p> <p>The Marginal sea <span class="hlt">Ice</span> Zone (MIZ) and the sea <span class="hlt">ice</span> edge are the most dynamic areas of the sea <span class="hlt">ice</span> cover. Knowledge of the sea <span class="hlt">ice</span> edge location is vital for routing shipping in the polar regions. The <span class="hlt">ice</span> edge is the location of recurrent plankton blooms, and is the habitat for a number of animals, including several which are under severe ecological threat. Polar lows are known to preferentially form along the sea <span class="hlt">ice</span> edge because of induced atmospheric baroclinicity, and the <span class="hlt">ice</span> edge is also the location of both vertical and horizontal ocean currents driven by thermal and salinity gradients. Finally, sea <span class="hlt">ice</span> is both a driver and indicator of climate change and monitoring the position of the <span class="hlt">ice</span> edge accurately over long time periods enables assessment of the impact of global and regional warming near the poles. Several sensors are currently in orbit that can monitor the sea <span class="hlt">ice</span> edge. These sensors, though, have different spatial resolutions, different limitations, and different repeat frequencies. Satellite passive microwave sensors can monitor the <span class="hlt">ice</span> edge on a daily or even twice-daily basis, albeit with low spatial resolution - 25 km for the Special Sensor Microwave Imager (SSM/I) or 12.5 km for the Advanced Microwave Scanning Radiometer (<span class="hlt">AMSR-E</span>). Although special methods exist that allow the detection of the sea <span class="hlt">ice</span> edge at a quarter of that nominal resolution (PSSM). Visible and infrared data from the Advanced Very High Resolution Radiometer (AVHRR) and from the Moderate Resolution Imaging Spectroradiometer (MODIS) provide daily coverage at 1 km and 250 m, respectively, but the surface observations me limited to cloud-free periods. The Landsat 7 Enhanced Thematic Mapper (ETM+) has a resolution of 15 to 30 m but is limited to cloud-free periods as well, and does not provide daily coverage. Imagery from Synthetic Aperture Radar (SAR) instruments has resolutions of tens of meters to 100 m, and can be used to distinguish open water and sea <span class="hlt">ice</span> on the basis of surface</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMPP34A..02E','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMPP34A..02E"><span>Separating the Effects of Northern Hemisphere <span class="hlt">Ice</span>-Sheets, CO2 <span class="hlt">Concentrations</span> and Orbital Parameters on Global Precipitation During the Late Pleistocene Glacial Cycles</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Elison Timm, O.; Friedrich, T.; Timmermann, A.; Ganopolski, A.</p> <p>2015-12-01</p> <p>Global-scale changes in the hydrological cycle have been reconstructed in many parts of the world using various archives of proxy information. The signals found in proxies allow us to study the complex response of the global hydrological cycle to the combined forcing and feedback mechanisms. However, it remains a challenge to attribute the observed variations to specific causes, in particular, it is difficult to distinguish CO2 and <span class="hlt">ice</span>-sheet response in time series. Here, we present new results from a set of transient paleoclimate simulation of the last eight glacial cycles (784,000 years) using accelerated forcing. In order to isolate the <span class="hlt">ice</span>-sheet forcing from the CO2 -driven response and orbital forcing, we made use of additional transient experiments with varying forcing combinations covering the last 408,000 years: (a) keeping CO2 <span class="hlt">concentrations</span> constant, (b) keeping the <span class="hlt">ice</span>-sheet fixed, (c) orbital forcing only. The simulations show that orbital forcing has strongest impact in the tropical and subtropical regions. The northern hemisphere <span class="hlt">ice</span>-sheets stamp a characteristic spatial footprint on the global precipitation variability. The <span class="hlt">ice</span>-sheets mainly affect the extratropical northern hemisphere, but the cone of influence extends further into the North African monsoon regions, and to a weaker extent into the Asian monsoon. In an attempt to validate our model-specific results we compared our results with existing hydrological paleo proxy records. Despite the growing number of proxy archives, the aim to identify the <span class="hlt">ice</span>-sheet influence in spatially limited networks of proxy time series remains as challenge. More records that cover at least two full glacial cycles could significantly increase the signal separation. In conclusion, our results suggest that the northern hemisphere <span class="hlt">ice</span>-sheets played an important role in modulating the global hydrological cycle.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110005552','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110005552"><span>ICESat Observations of Seasonal and Interannual Variations of Sea-<span class="hlt">Ice</span> Freeboard and Estimated Thickness in the Weddell Sea, Antarctica (2003-2009)</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Yi, Donghui; Robbins, John W.</p> <p>2010-01-01</p> <p>Sea-<span class="hlt">ice</span> 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 (<span class="hlt">AMSR-E</span>) data and nominal densities of snow, water and sea <span class="hlt">ice</span>, to estimate sea-<span class="hlt">ice</span> thickness. Sea-<span class="hlt">ice</span> freeboard and thickness distributions show clear seasonal variations that reflect the yearly cycle of growth and decay of the Weddell Sea (Antarctica) pack <span class="hlt">ice</span>. During October-November, sea <span class="hlt">ice</span> 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 <span class="hlt">ice</span> melts away and the sea-<span class="hlt">ice</span> 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-<span class="hlt">ice</span> 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.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..1512562R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..1512562R"><span>Two-way coupled <span class="hlt">ice</span> sheet-earth system simulations: Consequences of raising CO2 <span class="hlt">concentration</span> for Greenland and the interacting climate system</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Rodehacke, Christian; Vizcaino, Miren; Mikolajewicz, Uwe</p> <p>2013-04-01</p> <p>The observed distinct warming in the Arctic and the northward flow of tropical water masses seem to trigger enhanced melting of the Greenland <span class="hlt">ice</span> sheet, which adds more fresh water into the ambient ocean. A continuation of the observed accelerated melting during the last decade would stabilize the water column in the adjacent deep water formation sides. With our fully coupled <span class="hlt">ice</span> sheet-earth system model we approach the questions if this weakens the formation of deep water masses and reduces the thermohaline driven meridional overturning circulation (MOC). We have performed idealized future projections to investigate the response of the interaction under raising atmospheric carbon dioxide <span class="hlt">concentration</span> with our two-way coupled <span class="hlt">ice</span> sheet-earth system model system. We will present the building blocks of our fully coupled system, which includes a physical based calculation of the <span class="hlt">ice</span> sheet's surface mass balance and <span class="hlt">ice</span> sheet-ocean interaction; The ESM instead is subject to orographic changes and receives fresh water fluxes, for example. Since the behavior of an <span class="hlt">ice</span> sheet in the near future is controlled by both the external forcing and by its initial conditions, we have performed Latin Hyper Cube (LHC) simulations with the <span class="hlt">ice</span> sheet model over more than one glacial-interglacial cycle utilizing standard techniques to obtain a reasonable initial state. According to several quantities the best performing LHC member is exposed afterwards to boundary conditions determined from energy balance calculations again obtained from simulated forcing fields. Finally the fully coupled system is brought into a quasi-equilibrium under pre-industrial conditions before idealized scenarios have been started. In contrast to commonly used strategies, our coupled <span class="hlt">ice</span> sheet inherits the memory of a glacial cycle simulations obtain exclusively from ESM fields. Furthermore we use a mass conserving scheme, do neither apply flux corrections nor utilize anomaly coupling. Under different CO2</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA551010','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA551010"><span>Real-time Data Assimilation of Satellite Derived <span class="hlt">Ice</span> <span class="hlt">Concentration</span> into the Arctic Cap Nowcast/Forecast System (ACNFS)</span></a></p> <p><a target="_blank" href="https://publicaccess.dtic.mil/psm/api/service/search/search">DTIC Science & Technology</a></p> <p></p> <p>2011-09-01</p> <p>North America , Technology Solutions Group Stennis Space Center, MS 39529 USA M.W. Phelps Jacobs Engineering Stennis Space Center, MS 39529 USA...precipitation rates (i.e., snowfall ); a model of <span class="hlt">ice</span> dynamics that predicts the velocity field of the <span class="hlt">ice</span> pack based on a model of the material strength of the...the Data Assimilation and Model Evaluation Experiments North Atlantic data, the International Bathymetric Chart of the Arctic Ocean data, the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/19842493','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/19842493"><span><span class="hlt">Ice</span> growth in supercooled solutions of a biological "antifreeze", AFGP 1-5: an explanation in terms of adsorption rate for the <span class="hlt">concentration</span> dependence of the freezing point.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Knight, C A; DeVries, A L</p> <p>2009-07-21</p> <p>It is widely accepted, and we agree, that the lowering of the temperature at which <span class="hlt">ice</span> can grow in a water solution of one of the biological antifreezes is a result of adsorption of the antifreeze molecules at the <span class="hlt">ice</span> surface. However, how this can produce a well-defined "freezing point" that varies with the solution <span class="hlt">concentration</span> has remained problematical. The results of a series of measurements of <span class="hlt">ice</span> growing in supercooled solutions of an effective antifreeze are reported and interpreted in terms of this fundamental problem. It seemed that the solution of the problem would have to rely upon adsorption rate, because that appeared to be the only way for the <span class="hlt">concentration</span> in solution to be so important. The crystal growth results are most unusual, and appear to confirm this. The growth rates over a wide range of antifreeze <span class="hlt">concentration</span> in solution (about 0.05 to 9 mg ml(-1)) are zero from the thermodynamic freezing point down to the "non-equilibrium" freezing point, where there is a very sudden increase to a plateau value that then remains about constant as the supercooling is increased by about 2 degrees C. The plateau values of growth rate are faster than those from pure water at the lower-supercooling ends of the plateaus, but slower at higher supercooling, until the growth rate starts rising toward that from pure water. These plateau values of growth rate increase markedly with increasing <span class="hlt">concentration</span> of the antifreeze in solution. Along with these changes there are complex changes in the growth orientations, from c-axis spicules in the plateaus to those more characteristic of growth from pure water at greater supercooling. We conclude that the non-equilibrium freezing point is determined by the adsorption rate. It is the warmest temperature at which the <span class="hlt">ice</span> growth rate on the basal plane (where the antifreeze does not adsorb) is fast enough to prevent the area of basal face on a growing <span class="hlt">ice</span> crystal from becoming too small to grow, which is determined in</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26297465','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26297465"><span>Rapid measurement of perchlorate in polar <span class="hlt">ice</span> cores down to sub-ng L(-1) levels without pre-<span class="hlt">concentration</span>.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Peterson, Kari; Cole-Dai, Jihong; Brandis, Derek; Cox, Thomas; Splett, Scott</p> <p>2015-10-01</p> <p>An ion chromatography-electrospray ionization-tandem mass spectrometry (IC-ESI-MS/MS) method has been developed for rapid and accurate measurement of perchlorate in polar snow and <span class="hlt">ice</span> core samples in which perchlorate <span class="hlt">concentrations</span> are expected to be as low as 0.1 ng L(-1). Separation of perchlorate from major inorganic species in snow is achieved with an ion chromatography system interfaced to an AB SCIEX triple quadrupole mass spectrometer operating in multiple reaction monitoring mode. Under optimized conditions, the limit of detection and lower limit of quantification without pre-<span class="hlt">concentration</span> have been determined to be 0.1 and 0.3 ng L(-1), respectively, with a linear dynamic range of 0.3-10.0 ng L(-1) in routine measurement. These represent improvements over previously reported methods using similar analytical techniques. The improved method allows fast, accurate, and reproducible perchlorate quantification down to the sub-ng L(-1) level and will facilitate perchlorate measurement in the study of natural perchlorate production with polar <span class="hlt">ice</span> cores in which perchlorate <span class="hlt">concentrations</span> are anticipated to vary in the low and sub-ng L(-1) range. Initial measurements of perchlorate in <span class="hlt">ice</span> core samples from central Greenland show that typical perchlorate <span class="hlt">concentrations</span> in snow dated prior to the Industrial Revolution are about 0.8 ng L(-1), while perchlorate <span class="hlt">concentrations</span> are significantly higher in recent (post-1980) snow, suggesting that anthropogenic sources are a significant contributor to perchlorate in the current environment.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li class="active"><span>14</span></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_14 --> <div id="page_15" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li class="active"><span>15</span></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="281"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA205022','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA205022"><span>Predictability of <span class="hlt">Ice</span> <span class="hlt">Concentration</span> Anomalies in the High Latitudes of the North Atlantic Using a Statistical Approach</span></a></p> <p><a target="_blank" href="https://publicaccess.dtic.mil/psm/api/service/search/search">DTIC Science & Technology</a></p> <p></p> <p>1988-12-01</p> <p>However, effects discussed by Ramage (1984), such as insolation, heating from the ship and cloud cover biases are not taken into account. 4. Duplication...Long-term climatic changes, or trends, may adversely influence the statistical analyses of data. Since Oort (1987) detected long-term cooling of SST...84 Naval Oceanography Command D.tachment, Asheville, N. C., Sea <span class="hlt">Ice</span> Climatic Atlas: Volume II Arctic East, pp. I-,47 Oort A. H., and others</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016ESASP.740E.341M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016ESASP.740E.341M"><span>Sensitivity Analysis of Automated <span class="hlt">Ice</span> Edge Detection</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Moen, Mari-Ann N.; Isaksem, Hugo; Debien, Annekatrien</p> <p>2016-08-01</p> <p>The importance of highly detailed and time sensitive <span class="hlt">ice</span> charts has increased with the increasing interest in the Arctic for oil and gas, tourism, and shipping. Manual <span class="hlt">ice</span> charts are prepared by national <span class="hlt">ice</span> services of several Arctic countries. Methods are also being developed to automate this task. Kongsberg Satellite Services uses a method that detects <span class="hlt">ice</span> edges within 15 minutes after image acquisition. This paper describes a sensitivity analysis of the <span class="hlt">ice</span> edge, assessing to which <span class="hlt">ice</span> <span class="hlt">concentration</span> class from the manual <span class="hlt">ice</span> charts it can be compared to. The <span class="hlt">ice</span> edge is derived using the <span class="hlt">Ice</span> Tracking from SAR Images (ITSARI) algorithm. RADARSAT-2 images of February 2011 are used, both for the manual <span class="hlt">ice</span> charts and the automatic <span class="hlt">ice</span> edges. The results show that the KSAT <span class="hlt">ice</span> edge lies within <span class="hlt">ice</span> <span class="hlt">concentration</span> classes with very low <span class="hlt">ice</span> <span class="hlt">concentration</span> or open water.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26758589','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26758589"><span>Exploring the Effects of Subfreezing Temperature and Salt <span class="hlt">Concentration</span> on <span class="hlt">Ice</span> Growth Inhibition of Antarctic Gram-Negative Bacterium Marinomonas Primoryensis Using Coarse-Grained Simulation.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Nguyen, Hung; Dac Van, Thanh; Tran, Nhut; Le, Ly</p> <p>2016-04-01</p> <p>The aim of this work is to study the freezing process of water molecules surrounding Antarctic Gram-negative bacterium Marinomonas primoryensis antifreeze protein (MpAFP) and the MpAFP interactions to the surface of <span class="hlt">ice</span> crystals under various marine environments (at different NaCl <span class="hlt">concentrations</span> of 0.3, 0.6, and 0.8 mol/l). Our result indicates that activating temperature region of MpAFPs reduced as NaCl <span class="hlt">concentration</span> increased. Specifically, MpAFP was activated and functioned at 0.6 mol/l with temperatures equal or larger 278 K, and at 0.8 mol/l with temperatures equal or larger 270 K. Additionally, MpAFP was inhibited by <span class="hlt">ice</span> crystal network from 268 to 274 K and solid-liquid hybrid from 276 to 282 K at 0.3 mol/l <span class="hlt">concentration</span>. Our results shed lights on structural dynamics of MpAFP among different marine environments.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006P%26SS...54..331H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006P%26SS...54..331H"><span>Digging deep for <span class="hlt">ice</span> in Isidis Planitia—New constraints on subsurface volatile <span class="hlt">concentrations</span> from thermal modeling</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Helbert, J.; Benkhoff, J.</p> <p>2006-04-01</p> <p>The Isidis Planitia region on Mars usually is regarded as a comparably attractive site for landing missions based on engineering constraints such as elevation and smooth regional topography. The Mars Express landed element Beagle 2 was deployed to this area, and the southern margin of the basin was selected as one of the backup landing sites for the NASA Mars Exploration Rovers. Especially in the context of the Beagle 2 mission, Isidis Planitia has been discussed as a place which might have experienced a volatile-rich history with associated potential for biological activity [e.g. Bridges et al., 2003. Selection of the landing site in Isidis Planitia of Mars Probe Beagle 2. J. Geophys. Res. 108(E1), 5001, doi: 10.1029/2001JE001820]. However the measurements of by the GRS instrument on Mars Odyssey indicate a maximum inferred water abundance of only 3 wt% in the upper few meters of the surface [Feldman et al., 2004. Global distribution of near-surface hydrogen on Mars. J. Geophys. Res. 109, E09006, doi: 10.1029/2003JE002160]. Based on these measurements this area seems to be one of the driest spots in the equatorial region of Mars. To support future landing site selections we took a more detailed look at the minimum burial depth of stable <span class="hlt">ice</span> deposits in this area, focusing as an example on the planned Beagle 2 landing site. We are especially interested in the likelihood of ground <span class="hlt">ice</span> deposits within the range of proposed subsurface sampling tools as drills or 'mole'-like devices [Richter et al., 2002. Development and testing of subsurface sampling devices for the Beagle 2 Lander. Planet. Space Sci. 50, 903-913] given reasonable physical constraints for the surface and near surface material. For a mission like ExoMars [Kminek, G., Vago, J.L., 2005. The Aurora Exploration Program - The ExoMars Mission. In: Proceedings of the 35th Lunar and Planetary Science Conference, abstract no. 1111, 15-19 March 2004, League City, TX] with a focus on finding traces of fossil life</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/scitech/biblio/1049650','SCIGOV-STC'); return false;" href="https://www.osti.gov/scitech/biblio/1049650"><span>The dependence of <span class="hlt">ice</span> microphysics on aerosol <span class="hlt">concentration</span> in arctic mixed-phase stratus clouds during ISDAC and M-PACE</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Jackson, Robert C.; McFarquhar, Greg; Korolev, Alexei; Earle, Michael; Liu, Peter S.; Lawson, R. P.; Brooks, Sarah D.; Wolde, Mengistu; Laskin, Alexander; Freer, Matthew</p> <p>2012-08-14</p> <p>Cloud and aerosol data acquired by the National Research Council of Canada (NRC) Convair-580 aircraft in, above, and below single-layer arctic stratocumulus cloud during the Indirect and Semi-Direct Aerosol Campaign (ISDAC) in April 2008 were used to test three aerosol indirect effects hypothesized to act in mixed-phase clouds: the riming indirect effect, the glaciation indirect effect, and the cold second indirect effect. The data showed a correlation of R= 0.75 between liquid drop number <span class="hlt">concentration</span>, Nliq, inside cloud and ambient aerosol number <span class="hlt">concentration</span> NPCASP below cloud. This, combined with increasing liquid water content LWC with height above cloud base and the nearly constant profile of Nliq, suggested that liquid drops were nucleated from aerosol at cloud base. No strong evidence of a riming indirect effect was observed, but a strong correlation of R = 0.69 between <span class="hlt">ice</span> crystal number <span class="hlt">concentration</span> Ni and NPCASP above cloud was noted. Increases in <span class="hlt">ice</span> nuclei (IN) <span class="hlt">concentration</span> with NPCASP above cloud combined with the subadiabatic LWC profiles suggest possible mixing of IN from cloud top consistent with the glaciation indirect effect. The higher Nice and lower effective radius rel for the more polluted ISDAC cases compared to data collected in cleaner single-layer stratocumulus conditions during the Mixed-Phase Arctic Cloud Experiment is consistent with the operation of the cold second indirect effect. However, more data in a wider variety of meteorological and surface conditions, with greater variations in aerosol forcing, are required to identify the dominant aerosol forcing mechanisms in mixed-phase arctic clouds.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19830068495&hterms=ice+caps&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dice%2Bcaps','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19830068495&hterms=ice+caps&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dice%2Bcaps"><span><span class="hlt">Ice</span> crystal and <span class="hlt">ice</span> nucleus measurements in cap clouds</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Vali, G.; Rogers, D. C.; Deshler, T. L.</p> <p>1982-01-01</p> <p><span class="hlt">Ice</span> nucleation in cap clouds over a mountain in Wyoming was examined with airborne instrumentation. Crosswind and wind parallel passes were made through the clouds, with data being taken on the <span class="hlt">ice</span> crystal <span class="hlt">concentrations</span> and sizes. A total of 141 penetrations of 26 separate days in temperatures ranging from -7 to -24 C were performed. Subsequent measurements were also made 100 km away from the mountain. The <span class="hlt">ice</span> crystal <span class="hlt">concentrations</span> measured showed good correlation with the <span class="hlt">ice</span> nucleus content in winter time, midcontinental air masses in Wyoming. Further studies are recommended to determine if the variations in the <span class="hlt">ice</span> nucleus population are the cause of the variability if <span class="hlt">ice</span> crystal content.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUFMED33A0619H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUFMED33A0619H"><span><span class="hlt">Ice</span>, <span class="hlt">Ice</span>, Baby!</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hamilton, C.</p> <p>2008-12-01</p> <p>The Center for Remote Sensing of <span class="hlt">Ice</span> Sheets (CReSIS) has developed an outreach program based on hands-on activities called "<span class="hlt">Ice</span>, <span class="hlt">Ice</span>, Baby". These lessons are designed to teach the science principles of displacement, forces of motion, density, and states of matter. These properties are easily taught through the interesting topics of glaciers, icebergs, and sea level rise in K-8 classrooms. The activities are fun, engaging, and simple enough to be used at science fairs and family science nights. Students who have participated in "<span class="hlt">Ice</span>, <span class="hlt">Ice</span>, Baby" have successfully taught these to adults and students at informal events. The lessons are based on education standards which are available on our website www.cresis.ku.edu. This presentation will provide information on the activities, survey results from teachers who have used the material, and other suggested material that can be used before and after the activities.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFMPP23B1846K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFMPP23B1846K"><span>Seasonal to centennial-scale variability of microparticle <span class="hlt">concentration</span> and size distribution in the WAIS Divide <span class="hlt">ice</span> core over the past 2.4 ka</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kreutz, K. J.; Koffman, B. G.; Breton, D. J.; Dunbar, N. W.; Kurbatov, A.</p> <p>2011-12-01</p> <p>We present results from continuous analysis of mineral dust in the upper 577 m (2.4 ka) of the WAIS Divide deep <span class="hlt">ice</span> core, WDC06A. The core was melted using the UMaine WAIS Melt Monitor system, which allows accurate mm-scale depth co-registration of electrical conductivity and particle data, with subsequent collection of discrete samples for expanded particle, glaciochemical and geochemical analysis. The <span class="hlt">concentration</span> and size distribution of microparticles were measured using a flow-through Klotz Abakus laser particle detector, developed by Ruth et al (2002) and calibrated with Coulter-Counter measurements. We found that background dust <span class="hlt">concentrations</span> during the past two millennia have been low, comparable to other sites in interior Antarctica. Particle <span class="hlt">concentration</span> ranges seasonally from ~20-1000 particles/ml. Particle deposition generally shows an annual signal, although the phasing varies relative to seasonal chemical indicators such as nssSO42-. Dust deposition on decadal to centennial timescales appears to be linked to hemispheric-scale climate variability during the late Holocene, and particularly to the Southern Annular Mode (SAM) climate oscillation. We compared the coarse particle percentage (5-10 μm diameter relative to 1-10 μm diameter) to a proxy record of the SAM developed using sea salt <span class="hlt">concentrations</span> in the Law Dome, East Antarctica, <span class="hlt">ice</span> core (Goodwin et al, 2004). Spectral characteristics of the coarse particle percentage at WAIS Divide seem to match the Law Dome proxy for the SAM. This suggests a coherent signal for the SAM and the potential to develop a particle size distribution proxy for the strength of the circum-Antarctic atmospheric circulation. Within the past two centuries of dust deposition, there were several dusty decades in the early-to-mid 1900s followed by a dramatic increase around 1980. Given that the particle size distribution does not show significant coeval change, we infer that this increased dust deposition has been driven</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20050174634','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20050174634"><span>Prospecting for Martian <span class="hlt">Ice</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>McBride, S. A.; Allen, C. C.; Bell, M. S.</p> <p>2005-01-01</p> <p>During high Martian obliquity, <span class="hlt">ice</span> is stable to lower latitudes than predicted by models of present conditions and observed by the Gamma Ray Spectrometer (approx. 60 deg N). An <span class="hlt">ice</span>-rich layer deposited at mid-latitudes could persist to the present day; ablation of the top 1 m of <span class="hlt">ice</span> leaving a thin insulating cover could account for lack of its detection by GRS. The presence of an <span class="hlt">ice</span>-layer in the mid-latitudes is suggested by a network of polygons, interpreted as <span class="hlt">ice</span>-wedge cracks. This study focuses on an exceptional <span class="hlt">concentration</span> of polygons in Western Utopia (section of Casius quadrangle, roughly 40 deg - 50 deg N, 255 deg - 300 deg W). We attempt to determine the thickness and age of this <span class="hlt">ice</span> layer through crater-polygons relations.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.C14A..02T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.C14A..02T"><span>Climate Data Records (CDRs) for <span class="hlt">Ice</span> Motion and <span class="hlt">Ice</span> Age</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tschudi, M. A.; Fowler, C.; Maslanik, J. A.; Stroeve, J. C.</p> <p>2011-12-01</p> <p> and longwave radiation, first year, multiyear, and total <span class="hlt">ice</span> <span class="hlt">concentration</span>, and passive microwave brightness temperatures. The combination of sea <span class="hlt">ice</span> motion and sea <span class="hlt">ice</span> surface properties can therefore be utilized to observe the evolution of these properties as the <span class="hlt">ice</span> ages. Using this dataset, we observe that the evolution of albedo through the summer months varies between first year and mutliyear <span class="hlt">ice</span> types, resulting in a greater amount of shortwave radiation absorbed per unit area over first-year <span class="hlt">ice</span> through the melt season vs. multiyear <span class="hlt">ice</span>. Given that a larger portion of the <span class="hlt">ice</span> cover is now first-year <span class="hlt">ice</span>, the total shortwave energy absorbed by the pack through the melt season has increased from two decades ago, a feedback associated with the change in predominant <span class="hlt">ice</span> type.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20130013431','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20130013431"><span>On the <span class="hlt">Ice</span> Nucleation Spectrum</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Barahona, D.</p> <p>2012-01-01</p> <p>This work presents a novel formulation of the <span class="hlt">ice</span> nucleation spectrum, i.e. the function relating the <span class="hlt">ice</span> crystal <span class="hlt">concentration</span> to cloud formation conditions and aerosol properties. The new formulation is physically-based and explicitly accounts for the dependency of the <span class="hlt">ice</span> crystal <span class="hlt">concentration</span> on temperature, supersaturation, cooling rate, and particle size, surface area and composition. This is achieved by introducing the concepts of <span class="hlt">ice</span> nucleation coefficient (the number of <span class="hlt">ice</span> germs present in a particle) and nucleation probability dispersion function (the distribution of <span class="hlt">ice</span> nucleation coefficients within the aerosol population). The new formulation is used to generate <span class="hlt">ice</span> nucleation parameterizations for the homogeneous freezing of cloud droplets and the heterogeneous deposition <span class="hlt">ice</span> nucleation on dust and soot <span class="hlt">ice</span> nuclei. For homogeneous freezing, it was found that by increasing the dispersion in the droplet volume distribution the fraction of supercooled droplets in the population increases. For heterogeneous <span class="hlt">ice</span> nucleation the new formulation consistently describes singular and stochastic behavior within a single framework. Using a fundamentally stochastic approach, both cooling rate independence and constancy of the <span class="hlt">ice</span> nucleation fraction over time, features typically associated with singular behavior, were reproduced. Analysis of the temporal dependency of the <span class="hlt">ice</span> nucleation spectrum suggested that experimental methods that measure the <span class="hlt">ice</span> nucleation fraction over few seconds would tend to underestimate the <span class="hlt">ice</span> nuclei <span class="hlt">concentration</span>. It is shown that inferring the aerosol heterogeneous <span class="hlt">ice</span> nucleation properties from measurements of the onset supersaturation and temperature may carry significant error as the variability in <span class="hlt">ice</span> nucleation properties within the aerosol population is not accounted for. This work provides a simple and rigorous <span class="hlt">ice</span> nucleation framework where theoretical predictions, laboratory measurements and field campaign data can be</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26653482','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26653482"><span>Method for determination of levoglucosan in snow and <span class="hlt">ice</span> at trace <span class="hlt">concentration</span> levels using ultra-performance liquid chromatography coupled with triple quadrupole mass spectrometry.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>You, Chao; Song, Lili; Xu, Baiqing; Gao, Shaopeng</p> <p>2016-02-01</p> <p>A method is developed for determination of levoglucosan at trace <span class="hlt">concentration</span> levels in complex matrices of snow and <span class="hlt">ice</span> samples. This method uses an injection mixture comprising acetonitrile and melt sample at a ratio of 50/50 (v/v). Samples are analyzed using ultra-performance liquid chromatography system combined with triple tandem quadrupole mass spectrometry (UPLC-MS/MS). Levoglucosan is analyzed on BEH Amide column (2.1 mm × 100 mm, 1.7 um), and a Z-spray electrospray ionization source is used for levoglucosan ionization. The polyether sulfone filter is selected for filtrating insoluble particles due to less impact on levoglucosan. The matrix effect is evaluated by using a standard addition method. During the method validation, limit of detection (LOD), linearity, recovery, repeatability and reproducibility were evaluated using standard addition method. The LOD of this method is 0.11 ng mL(-1). Recoveries vary from 91.2% at 0.82 ng mL(-1) to 99.3% at 4.14 ng mL(-1). Repeatability ranges from 17.9% at a <span class="hlt">concentration</span> of 0.82 ng mL(-1) to 2.8% at 4.14 ng mL(-1). Reproducibility ranges from 15.1% at a <span class="hlt">concentration</span> of 0.82 ng mL(-1) to 1.9% at 4.14 ng mL(-1). This method can be implemented using less than 0.50 mL sample volume in low and middle latitude regions like the Tibetan Plateau.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA616446','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA616446"><span>Wave-<span class="hlt">Ice</span> Interaction in the Marginal <span class="hlt">Ice</span> Zone: Toward a Wave-Ocean-<span class="hlt">Ice</span> Coupled Modeling System</span></a></p> <p><a target="_blank" href="https://publicaccess.dtic.mil/psm/api/service/search/search">DTIC Science & Technology</a></p> <p></p> <p>2014-09-30</p> <p>conference paper (Rogers and Zieger 2014). This hindcast used <span class="hlt">ice</span> <span class="hlt">concentration</span> and thickness from the NRL Arctic Cap Nowcast Forecast System, improved for...Wave- <span class="hlt">ice</span> interaction...in the Marginal <span class="hlt">Ice</span> Zone: toward a wave-ocean- <span class="hlt">ice</span> coupled modeling system W. E. Rogers Naval Research Laboratory, Code 7322, Stennis Space Center</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015PrOce.136..241M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015PrOce.136..241M"><span>The relationship between sea <span class="hlt">ice</span> <span class="hlt">concentration</span> and the spatio-temporal distribution of vocalizing bearded seals (Erignathus barbatus) in the Bering, Chukchi, and Beaufort Seas from 2008 to 2011</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>MacIntyre, Kalyn Q.; Stafford, Kathleen M.; Conn, Paul B.; Laidre, Kristin L.; Boveng, Peter L.</p> <p>2015-08-01</p> <p>Bearded seals (Erignathus barbatus) are widely distributed in the Arctic and sub-Arctic; the Beringia population is found throughout the Bering, Chukchi and Beaufort Seas (BCB). Bearded seals are highly vocal, using underwater calls to advertise their breeding condition and maintain aquatic territories. They are also closely associated with pack <span class="hlt">ice</span> for reproductive activities, molting, and resting. Sea <span class="hlt">ice</span> habitat for this species varies spatially and temporally throughout the year due to differences in underlying physical and oceanographic features across its range. To test the hypothesis that the vocal activity of bearded seals is related to variations in sea <span class="hlt">ice</span>, passive acoustic data were collected from nine locations throughout the BCB from 2008 to 2011. Recording instruments sampled on varying duty cycles ranging from 20% to 100% of each hour, and recorded frequencies up to 8192 Hz. Spectrograms of acoustic data were analyzed manually to calculate the daily proportion of hours with bearded seal calls at each sampling location, and these call activity proportions were correlated with daily satellite-derived estimates of sea <span class="hlt">ice</span> <span class="hlt">concentration</span>. Bearded seals were vocally active nearly year-round in the Beaufort and Chukchi Seas with peak activity occurring from mid-March to late June during the mating season. The duration of call activity in the Bering Sea was shorter, lasting typically only five months, and peaked from mid-March to May at the northernmost recorders. In all areas, call activity was significantly correlated with higher sea <span class="hlt">ice</span> <span class="hlt">concentrations</span> (p < 0.01). These results suggest that losses in <span class="hlt">ice</span> cover may negatively impact bearded seals, not just by loss of habitat but also by altering the behavioral ecology of the BCB population.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4371753','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4371753"><span>Microbial abundance in surface <span class="hlt">ice</span> on the Greenland <span class="hlt">Ice</span> Sheet</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Stibal, Marek; Gözdereliler, Erkin; Cameron, Karen A.; Box, Jason E.; Stevens, Ian T.; Gokul, Jarishma K.; Schostag, Morten; Zarsky, Jakub D.; Edwards, Arwyn; Irvine-Fynn, Tristram D. L.; Jacobsen, Carsten S.</p> <p>2015-01-01</p> <p>Measuring microbial abundance in glacier <span class="hlt">ice</span> and identifying its controls is essential for a better understanding and quantification of biogeochemical processes in glacial ecosystems. However, cell enumeration of glacier <span class="hlt">ice</span> samples is challenging due to typically low cell numbers and the presence of interfering mineral particles. We quantified for the first time the abundance of microbial cells in surface <span class="hlt">ice</span> from geographically distinct sites on the Greenland <span class="hlt">Ice</span> Sheet (GrIS), using three enumeration methods: epifluorescence microscopy (EFM), flow cytometry (FCM), and quantitative polymerase chain reaction (qPCR). In addition, we reviewed published data on microbial abundance in glacier <span class="hlt">ice</span> and tested the three methods on artificial <span class="hlt">ice</span> samples of realistic cell (102–107 cells ml−1) and mineral particle (0.1–100 mg ml−1) <span class="hlt">concentrations</span>, simulating a range of glacial <span class="hlt">ice</span> types, from clean subsurface <span class="hlt">ice</span> to surface <span class="hlt">ice</span> to sediment-laden basal <span class="hlt">ice</span>. We then used multivariate statistical analysis to identify factors responsible for the variation in microbial abundance on the <span class="hlt">ice</span> sheet. EFM gave the most accurate and reproducible results of the tested methodologies, and was therefore selected as the most suitable technique for cell enumeration of <span class="hlt">ice</span> containing dust. Cell numbers in surface <span class="hlt">ice</span> samples, determined by EFM, ranged from ~ 2 × 103 to ~ 2 × 106 cells ml−1 while dust <span class="hlt">concentrations</span> ranged from 0.01 to 2 mg ml−1. The lowest abundances were found in <span class="hlt">ice</span> sampled from the accumulation area of the <span class="hlt">ice</span> sheet and in samples affected by fresh snow; these samples may be considered as a reference point of the cell abundance of precipitants that are deposited on the <span class="hlt">ice</span> sheet surface. Dust content was the most significant variable to explain the variation in the abundance data, which suggests a direct association between deposited dust particles and cells and/or by their provision of limited nutrients to microbial communities on the GrIS. PMID:25852678</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3682747','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3682747"><span><span class="hlt">Ice</span> sheets and nitrogen</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Wolff, Eric W.</p> <p>2013-01-01</p> <p>Snow and <span class="hlt">ice</span> play their most important role in the nitrogen cycle as a barrier to land–atmosphere and ocean–atmosphere exchanges that would otherwise occur. The inventory of nitrogen compounds in the polar <span class="hlt">ice</span> sheets is approximately 260 Tg N, dominated by nitrate in the much larger Antarctic <span class="hlt">ice</span> sheet. <span class="hlt">Ice</span> cores help to inform us about the natural variability of the nitrogen cycle at global and regional scale, and about the extent of disturbance in recent decades. Nitrous oxide <span class="hlt">concentrations</span> have risen about 20 per cent in the last 200 years and are now almost certainly higher than at any time in the last 800 000 years. Nitrate <span class="hlt">concentrations</span> recorded in Greenland <span class="hlt">ice</span> rose by a factor of 2–3, particularly between the 1950s and 1980s, reflecting a major change in NOx emissions reaching the background atmosphere. Increases in <span class="hlt">ice</span> cores drilled at lower latitudes can be used to validate or constrain regional emission inventories. Background ammonium <span class="hlt">concentrations</span> in Greenland <span class="hlt">ice</span> show no significant recent trend, although the record is very noisy, being dominated by spikes of input from biomass burning events. Neither nitrate nor ammonium shows significant recent trends in Antarctica, although their natural variations are of biogeochemical and atmospheric chemical interest. Finally, it has been found that photolysis of nitrate in the snowpack leads to significant re-emissions of NOx that can strongly impact the regional atmosphere in snow-covered areas. PMID:23713125</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23713125','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23713125"><span><span class="hlt">Ice</span> sheets and nitrogen.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Wolff, Eric W</p> <p>2013-07-05</p> <p>Snow and <span class="hlt">ice</span> play their most important role in the nitrogen cycle as a barrier to land-atmosphere and ocean-atmosphere exchanges that would otherwise occur. The inventory of nitrogen compounds in the polar <span class="hlt">ice</span> sheets is approximately 260 Tg N, dominated by nitrate in the much larger Antarctic <span class="hlt">ice</span> sheet. <span class="hlt">Ice</span> cores help to inform us about the natural variability of the nitrogen cycle at global and regional scale, and about the extent of disturbance in recent decades. Nitrous oxide <span class="hlt">concentrations</span> have risen about 20 per cent in the last 200 years and are now almost certainly higher than at any time in the last 800 000 years. Nitrate <span class="hlt">concentrations</span> recorded in Greenland <span class="hlt">ice</span> rose by a factor of 2-3, particularly between the 1950s and 1980s, reflecting a major change in NOx emissions reaching the background atmosphere. Increases in <span class="hlt">ice</span> cores drilled at lower latitudes can be used to validate or constrain regional emission inventories. Background ammonium <span class="hlt">concentrations</span> in Greenland <span class="hlt">ice</span> show no significant recent trend, although the record is very noisy, being dominated by spikes of input from biomass burning events. Neither nitrate nor ammonium shows significant recent trends in Antarctica, although their natural variations are of biogeochemical and atmospheric chemical interest. Finally, it has been found that photolysis of nitrate in the snowpack leads to significant re-emissions of NOx that can strongly impact the regional atmosphere in snow-covered areas.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010DSRII..57...86G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010DSRII..57...86G"><span>Arctic sea-<span class="hlt">ice</span> ridges—Safe heavens for sea-<span class="hlt">ice</span> fauna during periods of extreme <span class="hlt">ice</span> melt?</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gradinger, Rolf; Bluhm, Bodil; Iken, Katrin</p> <p>2010-01-01</p> <p>The abundances and distribution of metazoan within-<span class="hlt">ice</span> meiofauna (13 stations) and under-<span class="hlt">ice</span> fauna (12 stations) were investigated in level sea <span class="hlt">ice</span> and sea-<span class="hlt">ice</span> ridges in the Chukchi/Beaufort Seas and Canada Basin in June/July 2005 using a combination of <span class="hlt">ice</span> coring and SCUBA diving. <span class="hlt">Ice</span> meiofauna abundance was estimated based on live counts in the bottom 30 cm of level sea <span class="hlt">ice</span> based on triplicate <span class="hlt">ice</span> core sampling at each location, and in individual <span class="hlt">ice</span> chunks from ridges at four locations. Under-<span class="hlt">ice</span> 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 <span class="hlt">ice</span>, the most abundant <span class="hlt">ice</span> 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 <span class="hlt">ice</span>, low <span class="hlt">ice</span> algal pigment <span class="hlt">concentrations</span> (<0.1-15.8 μg Chl a l -1), low brine salinities (1.8-21.7) and flushing from the melting sea <span class="hlt">ice</span> likely explain the low <span class="hlt">ice</span> meiofauna <span class="hlt">concentrations</span>. 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 <span class="hlt">ice</span> than in level <span class="hlt">ice</span>. Median abundances of under-<span class="hlt">ice</span> amphipods at all <span class="hlt">ice</span> types (level <span class="hlt">ice</span>, various <span class="hlt">ice</span> 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 <span class="hlt">ice</span>. We propose that the summer <span class="hlt">ice</span> melt impacted meiofauna and under-<span class="hlt">ice</span> amphipod abundance and distribution through (a) flushing, and (b) enhanced salinity stress at thinner level sea <span class="hlt">ice</span> (less than 3 m thickness). We further suggest that pressure ridges, which extend into deeper, high</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1811585W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1811585W"><span>Geochemical and isotopic signatures of <span class="hlt">ice</span> shelves and <span class="hlt">ice</span> shelf circulation in marine sediments</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>White, Duanne; Fink, David; Simon, Krista; Post, Alix; Galton-Fenzi, Ben; Yokoyama, Yusuke</p> <p>2016-04-01</p> <p><span class="hlt">Ice</span> shelves are a key component of the <span class="hlt">ice</span> sheet drainage network. Most <span class="hlt">ice</span> lost from the present day Antarctic <span class="hlt">ice</span> sheet occurs via <span class="hlt">ice</span> shelves, so <span class="hlt">ice</span> shelf processes (e.g. calving and basal melt) modulate <span class="hlt">ice</span> sheet mass balance. Knowledge of the past distribution and geometry of <span class="hlt">ice</span> shelves will help understand their sensitivity to climate forcing, and the response of <span class="hlt">ice</span> sheets to changes and loss of <span class="hlt">ice</span> shelves. However, detecting the presence or absence of past <span class="hlt">ice</span> shelves in the sedimentary record is challenging. In this study, we compare <span class="hlt">concentrations</span> of elemental and isotopic tracers in modern sediments in open water in Prydz Bay to those being deposited underneath the Amery <span class="hlt">Ice</span> Shelf at ten sites across the region. Our results suggest that sub-<span class="hlt">ice</span> shelf and open water sediments differ in their acid-extractable elemental <span class="hlt">concentrations</span>. Also, meteoric Be-10 <span class="hlt">concentrations</span> are on average lower in sub-<span class="hlt">ice</span> shelf settings than they are in open water environments. However, the Be-10 <span class="hlt">concentration</span> is modulated by sub-<span class="hlt">ice</span> shelf ocean circulation, so that there is overlap between the sediment <span class="hlt">concentrations</span> in these two environments. In combination, we suggest that these tracers can be used as proxies to reconstruct former <span class="hlt">ice</span> shelf geometries and sub-shelf circulation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C31B..02L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C31B..02L"><span>Rain-on-snow and <span class="hlt">ice</span> layer formation detection using passive microwave radiometry: An arctic perspective</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Langlois, A.; Royer, A.; Montpetit, B.; Johnson, C. A.; Brucker, L.; Dolant, C.; Richards, A.; Roy, A.</p> <p>2015-12-01</p> <p>With the current changes observed in the Arctic, an increase in occurrence of rain-on-snow (ROS) events has been reported in the Arctic (land) over the past few decades. Several studies have established that strong linkages between surface temperatures and passive microwaves do exist, but the contribution of snow properties under winter extreme events such as rain-on-snow events (ROS) and associated <span class="hlt">ice</span> layer formation need to be better understood that both have a significant impact on ecosystem processes. In particular, <span class="hlt">ice</span> layer formation is known to affect the survival of ungulates by blocking their access to food. Given the current pronounced warming in northern regions, more frequent ROS can be expected. However, one of the main challenges in the study of ROS in northern regions is the lack of meteorological information and in-situ measurements. The retrieval of ROS occurrence in the Arctic using satellite remote sensing tools thus represents the most viable approach. Here, we present here results from 1) ROS occurrence formation in the Peary caribou habitat using an empirically developed ROS algorithm by our group based on the gradient ratio, 2) <span class="hlt">ice</span> layer formation across the same area using a semi-empirical detection approach based on the polarization ratio spanning between 1978 and 2013. A detection threshold was adjusted given the platform used (SMMR, SSM/I and <span class="hlt">AMSR-E</span>), and initial results suggest high-occurrence years as: 1981-1982, 1992-1993; 1994-1995; 1999-2000; 2001-2002; 2002-2003; 2003-2004; 2006-2007; 2007-2008. A trend in occurrence for Banks Island and NW Victoria Island and linkages to caribou population is presented.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li class="active"><span>15</span></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_15 --> <div id="page_16" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li class="active"><span>16</span></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="301"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.youtube.com/watch?v=5ujicxo6tF4','SCIGOVIMAGE-NASA'); return false;" href="http://www.youtube.com/watch?v=5ujicxo6tF4"><span>Over <span class="hlt">Ice</span></span></a></p> <p><a target="_blank" href="http://www.nasa.gov/multimedia/videogallery/index.html">NASA Video Gallery</a></p> <p></p> <p></p> <p>All about NASA's <span class="hlt">Ice</span>Bridge P-3B plane and its <span class="hlt">Ice</span>Bridge retrofit. Upgraded with 21st century "special modifications", the aircraft is less a cold war relic and more like the Space Agency's Millenni...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUFM.C41C0536K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUFM.C41C0536K"><span><span class="hlt">Concentration</span> and 14C Content of Total Organic Carbon and Black Carbon in Small (<100 ug C) Samples from Low-Latitude Alpine <span class="hlt">Ice</span> Cores</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kehrwald, N. M.; Czimczik, C. I.; Santos, G. M.; Thompson, L. G.; Ziolkowski, L.</p> <p>2008-12-01</p> <p>Many low latitude glaciers are receding with consequences for the regional energy budget and hydrology. <span class="hlt">Ice</span> loss has been linked to climate change and the deposition of organic aerosols such as black carbon (BC) which is formed during incomplete combustion. Little is known about how the contents of BC and total organic carbon (TOC) in aerosols change over time and how anthropogenic activities (e.g. land-use change) impact this variability. Low-latitude <span class="hlt">ice</span> cores are located closer to population centers than polar <span class="hlt">ice</span> caps and can provide a regional synthesis of TOC and BC variability. Radiocarbon (14C) may be used to partition BC aerosols into fossil (>50 kyrs) and modern sources (e.g. fossil-fuels vs. wildfires). We quantified TOC, BC, and their 14C content in three low-latitude <span class="hlt">ice</span> cores: Naimona'nyi (30°27'N, 81°91'E) and Dasuopu (28°23'N, 85°43'E), Tibet, and Quelccaya (13°56'S; 70°50'W), Peru. Aerosols (52-256 g <span class="hlt">ice</span> on filters) were separated into TOC and BC using thermal oxidation (CTO- 375). 14C was measured by AMS. TOC contents were 0.11-0.87, 0.05-0.43, and 0.06-0.19 μg C (g <span class="hlt">ice</span>) -1 for Naimona'nyi, Dasuopu, and Quelccaya, respectively. BC contents were 18±8, 27±4, and 29±12 %TOC. Procedural blanks were 0.8 ± 0.4 μg C (TOC) and 1.2 ± 0.6 μg C (BC). In <span class="hlt">ice</span> cores well dated through annual layer counting and/or independent ages (e.g. volcanic horizons) such as Quelccaya, the ability to separate BC from TOC, as well as partition BC into fossil and modern contributions has potential for reconstructing pre- and post-industrial changes in aerosol composition and their impact on the energy budget.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/16011939','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/16011939"><span>Granular flow in the marginal <span class="hlt">ice</span> zone.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Feltham, Daniel L</p> <p>2005-07-15</p> <p>The region of sea <span class="hlt">ice</span> near the edge of the sea <span class="hlt">ice</span> pack is known as the marginal <span class="hlt">ice</span> zone (MIZ), and its dynamics are complicated by ocean wave interaction with the <span class="hlt">ice</span> cover, strong gradients in the atmosphere and ocean and variations in sea <span class="hlt">ice</span> rheology. This paper focuses on the role of sea <span class="hlt">ice</span> rheology in determining the dynamics of the MIZ. Here, sea <span class="hlt">ice</span> is treated as a granular material with a composite rheology describing collisional <span class="hlt">ice</span> floe interaction and plastic interaction. The collisional component of sea <span class="hlt">ice</span> rheology depends upon the granular temperature, a measure of the kinetic energy of flow fluctuations. A simplified model of the MIZ is introduced consisting of the along and across momentum balance of the sea <span class="hlt">ice</span> and the balance equation of fluctuation kinetic energy. The steady solution of these equations is found to leading order using elementary methods. This reveals a <span class="hlt">concentrated</span> region of rapid <span class="hlt">ice</span> flow parallel to the <span class="hlt">ice</span> edge, which is in accordance with field observations, and previously called the <span class="hlt">ice</span> jet. Previous explanations of the <span class="hlt">ice</span> jet relied upon the existence of ocean currents beneath the <span class="hlt">ice</span> cover. We show that an <span class="hlt">ice</span> jet results as a natural consequence of the granular nature of sea <span class="hlt">ice</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.osti.gov/scitech/servlets/purl/1068688','SCIGOV-STC'); return false;" href="http://www.osti.gov/scitech/servlets/purl/1068688"><span>Determination of Large-Scale Cloud <span class="hlt">Ice</span> Water <span class="hlt">Concentration</span> by Combining Surface Radar and Satellite Data in Support of ARM SCM Activities</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Liu, Guosheng</p> <p>2013-03-15</p> <p>Single-column modeling (SCM) is one of the key elements of Atmospheric Radiation Measurement (ARM) research initiatives for the development and testing of various physical parameterizations to be used in general circulation models (GCMs). The data required for use with an SCM include observed vertical profiles of temperature, water vapor, and condensed water, as well as the large-scale vertical motion and tendencies of temperature, water vapor, and condensed water due to horizontal advection. Surface-based measurements operated at ARM sites and upper-air sounding networks supply most of the required variables for model inputs, but do not provide the horizontal advection term of condensed water. Since surface cloud radar and microwave radiometer observations at ARM sites are single-point measurements, they can provide the amount of condensed water at the location of observation sites, but not a horizontal distribution of condensed water contents. Consequently, observational data for the large-scale advection tendencies of condensed water have not been available to the ARM cloud modeling community based on surface observations alone. This lack of advection data of water condensate could cause large uncertainties in SCM simulations. Additionally, to evaluate GCMs cloud physical parameterization, we need to compare GCM results with observed cloud water amounts over a scale that is large enough to be comparable to what a GCM grid represents. To this end, the point-measurements at ARM surface sites are again not adequate. Therefore, cloud water observations over a large area are needed. The main goal of this project is to retrieve <span class="hlt">ice</span> water contents over an area of 10 x 10 deg. surrounding the ARM sites by combining surface and satellite observations. Built on the progress made during previous ARM research, we have conducted the retrievals of 3-dimensional <span class="hlt">ice</span> water content by combining surface radar/radiometer and satellite measurements, and have produced 3-D cloud <span class="hlt">ice</span></p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012EGUGA..14.3174F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012EGUGA..14.3174F"><span>Validation and Interpretation of a new sea <span class="hlt">ice</span> Glob<span class="hlt">Ice</span> dataset using buoys and the CICE sea <span class="hlt">ice</span> model</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Flocco, D.; Laxon, S. W.; Feltham, D. L.; Haas, C.</p> <p>2012-04-01</p> <p>The Glob<span class="hlt">Ice</span> project has provided high resolution sea <span class="hlt">ice</span> product datasets over the Arctic derived from SAR data in the ESA archive. The products are validated sea <span class="hlt">ice</span> motion, deformation and fluxes through straits. Glob<span class="hlt">Ice</span> sea <span class="hlt">ice</span> velocities, deformation data and sea <span class="hlt">ice</span> <span class="hlt">concentration</span> have been validated using buoy data provided by the International Arctic Buoy Program (IABP). Over 95% of the Glob<span class="hlt">Ice</span> and buoy data analysed fell within 5 km of each other. The Glob<span class="hlt">Ice</span> Eulerian image pair product showed a high correlation with buoy data. The sea <span class="hlt">ice</span> <span class="hlt">concentration</span> product was compared to SSM/I data. An evaluation of the validity of the Glob<span class="hlt">ICE</span> data will be presented in this work. Glob<span class="hlt">ICE</span> sea <span class="hlt">ice</span> velocity and deformation were compared with runs of the CICE sea <span class="hlt">ice</span> model: in particular the mass fluxes through the straits were used to investigate the correlation between the winter behaviour of sea <span class="hlt">ice</span> and the sea <span class="hlt">ice</span> state in the following summer.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19890018778','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19890018778"><span>Analysis of sea <span class="hlt">ice</span> dynamics</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Zwally, J.</p> <p>1988-01-01</p> <p>The ongoing work has established the basis for using multiyear sea <span class="hlt">ice</span> <span class="hlt">concentrations</span> from SMMR passive microwave for studies of largescale advection and convergence/divergence of the Arctic sea <span class="hlt">ice</span> pack. Comparisons were made with numerical model simulations and buoy data showing qualitative agreement on daily to interannual time scales. Analysis of the 7-year SMMR data set shows significant interannual variations in the total area of multiyear <span class="hlt">ice</span>. The scientific objective is to investigate the dynamics, mass balance, and interannual variability of the Arctic sea <span class="hlt">ice</span> pack. The research emphasizes the direct application of sea <span class="hlt">ice</span> parameters derived from passive microwave data (SMMR and SSMI) and collaborative studies using a sea <span class="hlt">ice</span> dynamics model. The possible causes of observed interannual variations in the multiyear <span class="hlt">ice</span> area are being examined. The relative effects of variations in the large scale advection and convergence/divergence within the <span class="hlt">ice</span> pack on a regional and seasonal basis are investigated. The effects of anomolous atmospheric forcings are being examined, including the long-lived effects of synoptic events and monthly variations in the mean geostrophic winds. Estimates to be made will include the amount of new <span class="hlt">ice</span> production within the <span class="hlt">ice</span> pack during winter and the amount of <span class="hlt">ice</span> exported from the pack.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19900031872&hterms=largest+crystals&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dlargest%2Bcrystals','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19900031872&hterms=largest+crystals&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dlargest%2Bcrystals"><span>Antarctic stratospheric <span class="hlt">ice</span> crystals</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Goodman, J.; Toon, O. B.; Pueschel, R. F.; Snetsinger, K. G.; Verma, S.</p> <p>1989-01-01</p> <p><span class="hlt">Ice</span> crystals were replicated over the Palmer Peninsula at approximately 72 deg S on six occasions during the 1987 Airboirne Antarctic Ozone Experiment. The sampling altitude was between 12.5 and 18.5 km (45-65 thousand ft pressure altitude) with the temperature between 190 and 201 K. The atmosphere was subsaturated with respect to <span class="hlt">ice</span> in all cases. The collected crystals were predominantly solid and hollow columns. The largest crystals were sampled at lower altitudes where the potential temperature was below 400 K. While the crystals were larger than anticipated, their low <span class="hlt">concentration</span> results in a total surface area that is less than one tenth of the total aerosol surface area. The large <span class="hlt">ice</span> crystals may play an important role in the observed stratospheric dehydration processes through sedimentation. Evidence of scavenging of submicron particles further suggests that the <span class="hlt">ice</span> crystals may be effective in the removal of stratospheric chemicals.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19860050808&hterms=Hakkinen&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3DHakkinen','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19860050808&hterms=Hakkinen&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3DHakkinen"><span><span class="hlt">Ice</span> banding as a response of the coupled <span class="hlt">ice</span>-ocean system to temporally varying winds</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hakkinen, S.</p> <p>1986-01-01</p> <p>This study models formation of <span class="hlt">ice</span> bands in the marginal <span class="hlt">ice</span> zones. A one-dimensional coupled <span class="hlt">ice</span>-ocean model is used in which the <span class="hlt">ice</span> model is coupled to a reduced gravity ocean model through interfacial stresses. The internal <span class="hlt">ice</span> stresses are important only at high <span class="hlt">ice</span> <span class="hlt">concentrations</span> (90-100 percent); otherwise, the main balance for the <span class="hlt">ice</span> motion is between the air-<span class="hlt">ice</span> stress and the <span class="hlt">ice</span>-water stress, i.e., free drift. The drag coefficients were chosen so that the air-<span class="hlt">ice</span> momentum flux is 3 times greater than the air-ocean momentum flux. Thus the Ekman transport is larger under the <span class="hlt">ice</span> than in the open water, so that winds parallel to the <span class="hlt">ice</span> edge, with the <span class="hlt">ice</span> on the right, produce upwelling. The upwelling simulation was extended to include temporally varying forcing, which was chosen to vary sinusoidally with a 4-day period. This forcing resembles successive cyclone passings perpendicular to the <span class="hlt">ice</span> edge. When the oceanic upper layer was thin, which means that the dynamics are strongly nonlinear, the <span class="hlt">ice</span> bands were formed. The up/downwelling signals do not disappear in wind reversals because of nonlinear advection. This leads to convergences and divergences in oceanic and <span class="hlt">ice</span> velocities that manifest themselves as <span class="hlt">ice</span> banding. At least one wind reversal is needed to produce one <span class="hlt">ice</span> band.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMGC23D1173L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMGC23D1173L"><span>Sparse <span class="hlt">ice</span>: Geophysical, biological and Indigenous knowledge perspectives on a habitat for <span class="hlt">ice</span>-associated fauna</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lee, O. A.; Eicken, H.; Weyapuk, W., Jr.; Adams, B.; Mohoney, A. R.</p> <p>2015-12-01</p> <p>The significance of highly dispersed, remnant Arctic sea <span class="hlt">ice</span> as a platform for marine mammals and indigenous hunters in spring and summer may have increased disproportionately with changes in the <span class="hlt">ice</span> cover. As dispersed remnant <span class="hlt">ice</span> becomes more common in the future it will be increasingly important to understand its ecological role for upper trophic levels such as marine mammals and its role for supporting primary productivity of <span class="hlt">ice</span>-associated algae. Potential sparse <span class="hlt">ice</span> habitat at sea <span class="hlt">ice</span> <span class="hlt">concentrations</span> below 15% is difficult to detect using remote sensing data alone. A combination of high resolution satellite imagery (including Synthetic Aperture Radar), data from the Barrow sea <span class="hlt">ice</span> radar, and local observations from indigenous sea <span class="hlt">ice</span> experts was used to detect sparse sea <span class="hlt">ice</span> in the Alaska Arctic. Traditional knowledge on sea <span class="hlt">ice</span> use by marine mammals was used to delimit the scales where sparse <span class="hlt">ice</span> could still be used as habitat for seals and walrus. Potential sparse <span class="hlt">ice</span> habitat was quantified with respect to overall spatial extent, size of <span class="hlt">ice</span> floes, and density of floes. Sparse <span class="hlt">ice</span> persistence offshore did not prevent the occurrence of large coastal walrus haul outs, but the lack of sparse <span class="hlt">ice</span> and early sea <span class="hlt">ice</span> retreat coincided with local observations of ringed seal pup mortality. Observations from indigenous hunters will continue to be an important source of information for validating remote sensing detections of sparse <span class="hlt">ice</span>, and improving understanding of marine mammal adaptations to sea <span class="hlt">ice</span> change.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110023761','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110023761"><span>An Overview of NASA Engine <span class="hlt">Ice</span>-Crystal <span class="hlt">Icing</span> Research</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Addy, Harold E., Jr.; Veres, Joseph P.</p> <p>2011-01-01</p> <p><span class="hlt">Ice</span> accretions that have formed inside gas turbine engines as a result of flight in clouds of high <span class="hlt">concentrations</span> of <span class="hlt">ice</span> crystals in the atmosphere have recently been identified as an aviation safety hazard. NASA s Aviation Safety Program (AvSP) has made plans to conduct research in this area to address the hazard. This paper gives an overview of NASA s engine <span class="hlt">ice</span>-crystal <span class="hlt">icing</span> research project plans. Included are the rationale, approach, and details of various aspects of NASA s research.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140005670','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140005670"><span>Sea <span class="hlt">Ice</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Perovich, D.; Gerland, S.; Hendricks, S.; Meier, Walter N.; Nicolaus, M.; Richter-Menge, J.; Tschudi, M.</p> <p>2013-01-01</p> <p>During 2013, Arctic sea <span class="hlt">ice</span> 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 <span class="hlt">ice</span> through the summer. Sea <span class="hlt">ice</span> thickness and volume remained near record-low levels, though indications are of slightly thicker <span class="hlt">ice</span> compared to the record low of 2012.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..17.9532T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..17.9532T"><span>Reconstructing the atmospheric <span class="hlt">concentration</span> and emissions of CF4, C2F6 and C3F8 prior to direct atmospheric measurements, using air from polar firn and <span class="hlt">ice</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Trudinger, Cathy; Etheridge, David; Sturges, William; Vollmer, Martin; Miller, Benjamin; Worton, David; Rigby, Matt; Krummel, Paul; Martinerie, Patricia; Witrant, Emmanuel; Rayner, Peter; Battle, Mark; Blunier, Thomas; Fraser, Paul; Laube, Johannes; Mani, Frances; Mühle, Jens; O'Doherty, Simon; Schwander, Jakob; Steele, Paul</p> <p>2015-04-01</p> <p>Perfluorocarbons are very potent and long-lived greenhouse gases in the atmosphere, released predominantly during aluminium production, electronic chip manufacture and refrigeration. Mühle et al. (2010) presented records of the <span class="hlt">concentration</span> and inferred emissions of CF4 (PFC-14), C2F6 (PFC-116) and C3F8 (PFC-218) from the 1970s up to 2008, using measurements from the Cape Grim Air Archive and a suite of tanks with old Northern Hemisphere air, and the AGAGE in situ network. Mühle et al. (2010) also estimated pre-industrial <span class="hlt">concentrations</span> of these compounds from a small number of polar firn and <span class="hlt">ice</span> core samples. Here we present measurements of air from polar firn at four sites (DSSW20K, EDML, NEEM and South Pole) and from air bubbles trapped in <span class="hlt">ice</span> at two sites (DE08 and DE08-2), along with recent atmospheric measurements to give a continuous record of <span class="hlt">concentration</span> from preindustrial levels up to the present. We estimate global emissions (with uncertainties) consistent with the <span class="hlt">concentration</span> records. The uncertainty analysis takes into account uncertainties in characterisation of the age of air in firn and <span class="hlt">ice</span> by the use of two different (independently-calibrated) firn models (the CSIRO and LGGE-GIPSA firn models). References Mühle, J., A.L. Ganesan, B.R. Miller, P.K. Salameh, C.M. Harth, B.R. Greally, M. Rigby, L.W. Porter, L. P. Steele, C.M. Trudinger, P.B. Krummel, S. O'Doherty, P.J. Fraser, P.G. Simmonds, R.G. Prinn, and R.F. Weiss, Perfluorocarbons in the global atmosphere: tetrafluoromethane, hexafluoroethane, and octafluoropropane, Atmos. Chem. Phys., 10, 5145-5164, doi:10.5194/acp-10-5145-2010, 2010.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.9252S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.9252S"><span>Strong coupling among Antarctic <span class="hlt">ice</span> shelves, ocean circulation and sea <span class="hlt">ice</span> in a global sea-<span class="hlt">ice</span> - ocean circulation model</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sergienko, Olga</p> <p>2016-04-01</p> <p>The thermodynamic effects of Antarctic <span class="hlt">ice</span> shelf interaction with ocean circulation are investigated using a global, high-resolution, isopycnal ocean-circulation model coupled to a sea-<span class="hlt">ice</span> model. The model uses NASA MERRA Reanalysis from 1992 to 2011 as atmospheric forcing. The simulated long-period variability of <span class="hlt">ice</span>-shelf melting/freezing rates differ across geographic locations. The <span class="hlt">ice</span> shelves in Antarctic Peninsula, Amundsen and Bellingshausen sea embayments and the Amery <span class="hlt">Ice</span> Shelf experience an increase in melting starting from 2005. This increase in melting is due to an increase in the subsurface (100-500 m) ocean heat content in the embayments of these <span class="hlt">ice</span> shelves, which is caused by an increase in sea-<span class="hlt">ice</span> <span class="hlt">concentration</span> after 2005, and consequent reduction of the heat loss to the atmosphere. Our simulations provide a strong evidence for a coupling between ocean circulation, sea <span class="hlt">ice</span> and <span class="hlt">ice</span> shelves.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFMIN11D1487G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFMIN11D1487G"><span>Open-Source Python Modules to Estimate Level <span class="hlt">Ice</span> Thickness from <span class="hlt">Ice</span> Charts</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Geiger, C. A.; Deliberty, T. L.; Bernstein, E. R.; Helfrich, S.</p> <p>2012-12-01</p> <p>A collaborative research effort between the University of Delaware (UD) and National <span class="hlt">Ice</span> Center (NIC) addresses the task of providing open-source translations of sea <span class="hlt">ice</span> stage-of-development into level <span class="hlt">ice</span> thickness estimates on a 4km grid for the Interactive Multisensor Snow and <span class="hlt">Ice</span> Mapping System (IMS). The characteristics for stage-of-development are quantified from remote sensing imagery with estimates of level <span class="hlt">ice</span> thickness categories originating from World Meteorological Organization (WMO) egg coded <span class="hlt">ice</span> charts codified since the 1970s. Conversions utilize Python scripting modules which transform electronic <span class="hlt">ice</span> charts with WMO egg code characteristics into five level <span class="hlt">ice</span> thickness categories, in centimeters, (0-10, 10-30, 30-70, 70-120, >120cm) and five <span class="hlt">ice</span> types (open water, first year pack <span class="hlt">ice</span>, fast <span class="hlt">ice</span>, multiyear <span class="hlt">ice</span>, and glacial <span class="hlt">ice</span> with a reserve slot for deformed <span class="hlt">ice</span> fractions). Both level <span class="hlt">ice</span> thickness categories and <span class="hlt">ice</span> <span class="hlt">concentration</span> fractions are reported with uncertainties propagated based on WMO <span class="hlt">ice</span> stage ranges which serve as proxy estimates for standard deviation. These products are in preparation for use by NCEP, CMC, and NAVO by 2014 based on their modeling requirements for daily products in near-real time. In addition to development, continuing research tests the value of these estimated products against in situ observations to improve both value and uncertainty estimates.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19860019340','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19860019340"><span>Meteorite <span class="hlt">concentration</span> mechanisms in Antarctica</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Annexstad, J. O.</p> <p>1986-01-01</p> <p>The location of most Antarctic meteorite finds is on stagnant, highly ablative surfaces known as blue <span class="hlt">ice</span>. The role of blue <span class="hlt">ice</span> as transporter, <span class="hlt">concentrator</span>, and preserver of specimens from the time of fall until find is discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2005AGUFM.A33E..03D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2005AGUFM.A33E..03D"><span><span class="hlt">Ice</span> Nuclei Variability and <span class="hlt">Ice</span> Formation in Mixed-phase Clouds</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Demott, P. J.; Twohy, C. H.; Prenni, A. J.; Kreidenweis, S. M.; Brooks, S. D.; Rogers, D. C.</p> <p>2005-12-01</p> <p>While it is expected that <span class="hlt">ice</span> nuclei impose a critical role in <span class="hlt">ice</span> initiation in clouds, there are relatively few validations of direct relations between <span class="hlt">ice</span> nuclei <span class="hlt">concentrations</span> and <span class="hlt">ice</span> crystal <span class="hlt">concentrations</span>. Further, very little is known about the spatial and temporal distribution of <span class="hlt">ice</span> nuclei, let alone their sources. Such knowledge is critical for understanding precipitation formation, cloud lifetimes, the existence of aircraft <span class="hlt">icing</span> hazards, and the impacts of changing atmospheric aerosol particle <span class="hlt">concentrations</span> and compositions on cold cloud processes. In this study, we document measurements of <span class="hlt">ice</span> nuclei in relation to the presence and <span class="hlt">concentrations</span> of <span class="hlt">ice</span> crystals in modestly supercooled clouds and also consider the implications of differences in <span class="hlt">ice</span> nuclei <span class="hlt">concentrations</span> measured at different locations and times during several studies. In the first part of this presentation, we show results from measurements made in the Alliance <span class="hlt">Icing</span> Research Study II, conducted in late Fall 2003 over the Northeast U.S. and Eastern Canada. A counterflow virtual impactor was used for selectively sampling cloud particles during aircraft measurements of clouds. Measurements were made on the evaporated residual aerosol particles, including re-processing at controlled temperatures and relative humidities to determine their <span class="hlt">ice</span> nucleating behavior for conditions of direct relevance to the clouds using a continuous flow <span class="hlt">ice</span>-thermal diffusion chamber (CFDC). Comparing to measurements of <span class="hlt">ice</span> crystals in clouds, a clear correlation between the presence or absence of <span class="hlt">ice</span> nuclei and <span class="hlt">ice</span> crystals was demonstrated in some cases. However, the <span class="hlt">concentrations</span> of the two populations did not correlate as well. Reasons for this may reflect different (or not assessed) <span class="hlt">ice</span> formation processes, redistribution of <span class="hlt">ice</span> in clouds, and potential artifacts of the sampling procedure. Since these results and those of Prenni et al. (this meeting), describing the vital role of <span class="hlt">ice</span> nuclei in affecting</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19830045130&hterms=reduced-gravity+model&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dreduced-gravity%2Bmodel','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19830045130&hterms=reduced-gravity+model&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dreduced-gravity%2Bmodel"><span>A coupled <span class="hlt">ice</span>-ocean model of upwelling in the marginal <span class="hlt">ice</span> zone</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Roed, L. P.; Obrien, J. J.</p> <p>1983-01-01</p> <p>A dynamical coupled <span class="hlt">ice</span>-ocean numerical model for the marginal <span class="hlt">ice</span> zone (MIZ) is suggested and used to study upwelling dynamics in the MIZ. The nonlinear sea <span class="hlt">ice</span> model has a variable <span class="hlt">ice</span> <span class="hlt">concentration</span> and includes internal <span class="hlt">ice</span> stress. The model is forced by stresses on the air/ocean and air/<span class="hlt">ice</span> surfaces. The main coupling between the <span class="hlt">ice</span> and the ocean is in the form of an interfacial stress on the <span class="hlt">ice</span>/ocean interface. The ocean model is a linear reduced gravity model. The wind stress exerted by the atmosphere on the ocean is proportional to the fraction of open water, while the interfacial stress <span class="hlt">ice</span>/ocean is proportional to the <span class="hlt">concentration</span> of <span class="hlt">ice</span>. A new mechanism for <span class="hlt">ice</span> edge upwelling is suggested based on a geostrophic equilibrium solution for the sea <span class="hlt">ice</span> medium. The upwelling reported in previous models invoking a stationary <span class="hlt">ice</span> cover is shown to be replaced by a weak downwelling due to the <span class="hlt">ice</span> motion. Most of the upwelling dynamics can be understood by analysis of the divergence of the across <span class="hlt">ice</span> edge upper ocean transport. On the basis of numerical model, an analytical model is suggested that reproduces most of the upwelling dynamics of the more complex numerical model.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.3020R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.3020R"><span>Determining the <span class="hlt">ice</span> seasons severity during 1982-2015 using the <span class="hlt">ice</span> extents sum as a new characteristic</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Rjazin, Jevgeni; Pärn, Ove</p> <p>2016-04-01</p> <p>Sea <span class="hlt">ice</span> is a key climate factor and it restricts considerably the winter navigation in sever seasons on the Baltic Sea. So determining <span class="hlt">ice</span> conditions severity and describing <span class="hlt">ice</span> cover behaviour at severe seasons interests scientists, engineers and navigation managers. The present study is carried out to determine the <span class="hlt">ice</span> seasons severity degree basing on the <span class="hlt">ice</span> seasons 1982 to 2015. A new integrative characteristic is introduced to describe the <span class="hlt">ice</span> season severity. It is the sum of <span class="hlt">ice</span> extents of the <span class="hlt">ice</span> season id est the daily <span class="hlt">ice</span> extents of the season are summed. The commonly used procedure to determine the <span class="hlt">ice</span> season severity degree by the maximal <span class="hlt">ice</span> extent is in this research compared to the new characteristic values. The remote sensing data on the <span class="hlt">ice</span> <span class="hlt">concentrations</span> on the Baltic Sea published in the European Copernicus Programme are used to obtain the severity characteristic values. The <span class="hlt">ice</span> extents are calculated on these <span class="hlt">ice</span> <span class="hlt">concentration</span> data. Both the maximal <span class="hlt">ice</span> extent of the season and a newly introduced characteristic - the <span class="hlt">ice</span> extents sum are used to classify the winters with respect of severity. The most severe winter of the reviewed period is 1986/87. Also the <span class="hlt">ice</span> seasons 1981/82, 1984/85, 1985/86, 1995/96 and 2002/03 are classified as severe. Only three seasons of this list are severe by both the criteria. They are 1984/85, 1985/86 and 1986/87. We interpret this coincidence as the evidence of enough-during extensive <span class="hlt">ice</span> cover in these three seasons. In several winters, for example 2010/11 <span class="hlt">ice</span> cover extended enough for some time, but did not endure. At few other <span class="hlt">ice</span> seasons as 2002/03 the Baltic Sea was <span class="hlt">ice</span>-covered in moderate extent, but the <span class="hlt">ice</span> cover stayed long time. At 11 winters the <span class="hlt">ice</span> extents sum differed considerably (> 10%) from the maximal <span class="hlt">ice</span> extent. These winters yield one third of the studied <span class="hlt">ice</span> seasons. The maximal <span class="hlt">ice</span> extent of the season is simple to use and enables to reconstruct the <span class="hlt">ice</span> cover history and to predict maximal <span class="hlt">ice</span></p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017GeoRL..44.1574L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017GeoRL..44.1574L"><span>On the role of <span class="hlt">ice</span>-nucleating aerosol in the formation of <span class="hlt">ice</span> particles in tropical mesoscale convective systems</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ladino, Luis A.; Korolev, Alexei; Heckman, Ivan; Wolde, Mengistu; Fridlind, Ann M.; Ackerman, Andrew S.</p> <p>2017-02-01</p> <p>Over the decades, the cloud physics community has debated the nature and role of aerosol particles in <span class="hlt">ice</span> initiation. The present study shows that the measured <span class="hlt">concentration</span> of <span class="hlt">ice</span> crystals in tropical mesoscale convective systems exceeds the <span class="hlt">concentration</span> of <span class="hlt">ice</span> nucleating particles (INPs) by several orders of magnitude. The <span class="hlt">concentration</span> of INPs was assessed from the measured aerosol particle <span class="hlt">concentration</span> in the size range of 0.5 to 1 µm. The observations from this study suggest that primary <span class="hlt">ice</span> crystals formed on INPs make only a minor contribution to the total <span class="hlt">concentration</span> of <span class="hlt">ice</span> crystals in tropical mesoscale convective systems. This is found by comparing the predicted INP number <span class="hlt">concentrations</span> with in situ <span class="hlt">ice</span> particle number <span class="hlt">concentrations</span>. The obtained measurements suggest that <span class="hlt">ice</span> multiplication is the likely explanation for the observed high <span class="hlt">concentrations</span> of <span class="hlt">ice</span> crystals in this type of convective system.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.C21B0341S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.C21B0341S"><span>Using Sea <span class="hlt">Ice</span> Age as a Proxy for Sea <span class="hlt">Ice</span> Thickness</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Stroeve, J. C.; Tschudi, M. A.; Maslanik, J. A.</p> <p>2014-12-01</p> <p>Since the beginning of the modern satellite record starting in October 1978, the Arctic sea <span class="hlt">ice</span> cover has been shrinking, with the largest changes observed at the end of the melt season in September. Through 2013, the September <span class="hlt">ice</span> 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 <span class="hlt">ice</span> extent is accompanied by large reductions in winter <span class="hlt">ice</span> thicknesses that are primarily explained by changes in the ocean's coverage of multiyear <span class="hlt">ice</span> (MYI). Using the University of Colorado <span class="hlt">ice</span> age product developed by J. Maslanik and C. Fowler, and currently produced by M. Tschudi we present recent changes in the distribution of <span class="hlt">ice</span> age from the mid 1980s to present. The CU <span class="hlt">ice</span> age product is based on (1) the use of <span class="hlt">ice</span> motion to track areas of sea <span class="hlt">ice</span> and thus estimate how long the <span class="hlt">ice</span> survives within the Arctic, and (2) satellite imagery of sea <span class="hlt">ice</span> <span class="hlt">concentration</span> to determine when the <span class="hlt">ice</span> disappears. Age is assigned on a yearly basis, with the age incremented by one year if the <span class="hlt">ice</span> survives summer melt and stays within the Arctic domain. Age is counted from 1 to 10 years, with all <span class="hlt">ice</span> older than 10 years assigned to the "10+" age category. The position of the <span class="hlt">ice</span> 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 <span class="hlt">ice</span> extent, whereas by the end of 2012 it had dropped to less than 20%. This reflects not only a change in <span class="hlt">ice</span> type, but also a general thinning of the <span class="hlt">ice</span> pack, as older <span class="hlt">ice</span> tends to be thicker <span class="hlt">ice</span>. Thus, with older <span class="hlt">ice</span> being replaced by thinner first-year <span class="hlt">ice</span>, the <span class="hlt">ice</span> pack is more susceptible to melting out than it was in 1980's. It has been suggested that <span class="hlt">ice</span> age may be a useful proxy for long-term changes in <span class="hlt">ice</span> thickness. To assess the relationship between <span class="hlt">ice</span> age and thickness, and how this may be changing over time, we compare the <span class="hlt">ice</span> age fields to several</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li class="active"><span>16</span></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_16 --> <div id="page_17" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li class="active"><span>17</span></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="321"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.C33F..01P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.C33F..01P"><span>Contributing factors to an enhanced <span class="hlt">ice</span> albedo feedback in Arctic sea <span class="hlt">ice</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Perovich, D. K.; Jones, K. F.; Light, B.; Holland, M. M.</p> <p>2012-12-01</p> <p>The Arctic sea <span class="hlt">ice</span> cover is in decline. In recent years there has been a decrease in summer <span class="hlt">ice</span> area; a thinning of the <span class="hlt">ice</span> cover; an increase in the amount of seasonal <span class="hlt">ice</span>; an earlier onset of summer melt; and a later start of fall freeze up. Decreases in <span class="hlt">ice</span> <span class="hlt">concentration</span> substantially increase solar heat input to the ocean. Earlier dates of melt onset reduce <span class="hlt">ice</span> albedo during a period when incident solar irradiance is large increasing solar heat input to the <span class="hlt">ice</span>. Seasonal sea <span class="hlt">ice</span> typically has a smaller albedo than perennial <span class="hlt">ice</span> throughout the melt season. Thus, the observed shift to a seasonal <span class="hlt">ice</span> cover causes greater solar heat input to the <span class="hlt">ice</span> and more melting thereby accelerating <span class="hlt">ice</span> decay. Thinner <span class="hlt">ice</span> results in greater transmission of solar heat to the upper ocean, where it contributes to bottom melting, lateral melting, and warming of the water. All of these changes enhance the amount of solar energy deposited in the <span class="hlt">ice</span> ocean system, and increasing <span class="hlt">ice</span> melt. We will examine the relative magnitude of each of these changes individually as well as their collective contribution to the <span class="hlt">ice</span> albedo feedback.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19930061882&hterms=Hakkinen&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3DHakkinen','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19930061882&hterms=Hakkinen&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3DHakkinen"><span>Wave effects on ocean-<span class="hlt">ice</span> interaction in the marginal <span class="hlt">ice</span> zone</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Liu, Antony K.; Hakkinen, Sirpa; Peng, Chih Y.</p> <p>1993-01-01</p> <p>The effects of wave train on <span class="hlt">ice</span>-ocean interaction in the marginal <span class="hlt">ice</span> zone are studied through numerical modeling. A coupled two-dimensional <span class="hlt">ice</span>-ocean model has been developed to include wave effects and wind stress for the predictions of <span class="hlt">ice</span> edge dynamics. The sea <span class="hlt">ice</span> model is coupled to the reduced-gravity ocean model through interfacial stresses. The main dynamic balance in the <span class="hlt">ice</span> momentum is between water-<span class="hlt">ice</span> stress, wind stress, and wave radiation stresses. By considering the exchange of momentum between waves and <span class="hlt">ice</span> pack through radiation stress for decaying waves, a parametric study of the effects of wave stress and wind stress on <span class="hlt">ice</span> edge dynamics has been performed. The numerical results show significant effects from wave action. The <span class="hlt">ice</span> edge is sharper, and <span class="hlt">ice</span> edge meanders form in the marginal <span class="hlt">ice</span> zone owing to forcing by wave action and refraction of swell system after a couple of days. Upwelling at the <span class="hlt">ice</span> edge and eddy formation can be enhanced by the nonlinear effects of wave action; wave action sharpens the <span class="hlt">ice</span> edge and can produce <span class="hlt">ice</span> meandering, which enhances local Ekman pumping and pycnocline anomalies. The resulting <span class="hlt">ice</span> <span class="hlt">concentration</span>, pycnocline changes, and flow velocity field are shown to be consistent with previous observations.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19860025697&hterms=Ice+cover+Arctic+Ocean&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3DIce%2Bcover%2BArctic%2BOcean','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19860025697&hterms=Ice+cover+Arctic+Ocean&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3DIce%2Bcover%2BArctic%2BOcean"><span>Satellite observations of sea <span class="hlt">ice</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Cavalieri, D. J.; Zwally, H. J.</p> <p>1985-01-01</p> <p>An overview is presented of Antarctic and Arctic sea <span class="hlt">ice</span> studies using data from the Nimbus-5 ESMR and the Nimbus-7 SMMR passive microwave radiometers. Four years (1973-1976) of ESMR data for the Antarctic Ocean define the characteristics of the seasonal cycle including regional contrasts and interannual variations. Major advances include the discovery of the Weddell polynya and the presence of substantial areas of open water in the Antarctic winter pack <span class="hlt">ice</span>. Regional differences in sea <span class="hlt">ice</span> extent on time-scales of about a month are shown to be associated with variations in surface-wind fields. In the Arctic, the computation of sea <span class="hlt">ice</span> <span class="hlt">concentration</span> is complicated by the presence of multiyear <span class="hlt">ice</span>, but the amount of multiyear <span class="hlt">ice</span> becomes an important measurable quantity with dual-polarized, multifrequency passive microwave sensors. Analysis of SMMR data demonstrates its advantage for studying the spatial and temporal variability of the Arctic <span class="hlt">ice</span> cover. Large observed interannual variations in the distribution of the multiyear pack <span class="hlt">ice</span> and the presence of significant divergent areas in the central Arctic during winter contrast markedly with the classical view of the Arctic pack <span class="hlt">ice</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/scitech/biblio/1054037','SCIGOV-STC'); return false;" href="https://www.osti.gov/scitech/biblio/1054037"><span>Climate Impacts of <span class="hlt">Ice</span> Nucleation</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Gettelman, A.; Liu, Xiaohong; Barahona, Donifan; Lohmann, U.; Chen, Chih-Chieh</p> <p>2012-10-19</p> <p>[1] Several different <span class="hlt">ice</span> nucleation parameterizations in two different General Circulation Models (GCMs) are used to understand the effects of <span class="hlt">ice</span> nucleation on the mean climate state, and the Aerosol Indirect Effects (AIE) of cirrus clouds on climate. Simulations have a range of <span class="hlt">ice</span> microphysical states that are consistent with the spread of observations, but many simulations have higher present-day <span class="hlt">ice</span> crystal number <span class="hlt">concentrations</span> than in-situ observations. These different states result from different parameterizations of <span class="hlt">ice</span> cloud nucleation processes, and feature different balances of homogeneous and heterogeneous nucleation. Black carbon aerosols have a small (-0.06 Wm<sup>-2</sup>) and not statistically significant AIE when included as <span class="hlt">ice</span> nuclei, for nucleation efficiencies within the range of laboratory measurements. Indirect effects of anthropogenic aerosols on cirrus clouds occur as a consequence of increasing anthropogenic sulfur emissions with different mechanisms important in different models. In one model this is due to increases in homogeneous nucleation fraction, and in the other due to increases in heterogeneous nucleation with coated dust. The magnitude of the effect is the same however. The resulting <span class="hlt">ice</span> AIE does not seem strongly dependent on the balance between homogeneous and heterogeneous <span class="hlt">ice</span> nucleation. Regional effects can reach several Wm<sup>-2</sup>. Indirect effects are slightly larger for those states with less homogeneous nucleation and lower <span class="hlt">ice</span> number <span class="hlt">concentration</span> in the base state. The total <span class="hlt">ice</span> AIE is estimated at 0.27 ± 0.10 Wm<sup>-2</sup> (1σ uncertainty). Finally, this represents a 20% offset of the simulated total shortwave AIE for <span class="hlt">ice</span> and liquid clouds of -1.6 Wm<sup>-2</sup>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140001045','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140001045"><span>Climate Impacts of <span class="hlt">Ice</span> Nucleation</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Gettelman, Andrew; Liu, Xiaohong; Barahona, Donifan; Lohmann, Ulrike; Chen, Celia</p> <p>2012-01-01</p> <p>Several different <span class="hlt">ice</span> nucleation parameterizations in two different General Circulation Models (GCMs) are used to understand the effects of <span class="hlt">ice</span> nucleation on the mean climate state, and the Aerosol Indirect Effects (AIE) of cirrus clouds on climate. Simulations have a range of <span class="hlt">ice</span> microphysical states that are consistent with the spread of observations, but many simulations have higher present-day <span class="hlt">ice</span> crystal number <span class="hlt">concentrations</span> than in-situ observations. These different states result from different parameterizations of <span class="hlt">ice</span> cloud nucleation processes, and feature different balances of homogeneous and heterogeneous nucleation. Black carbon aerosols have a small (0.06 Wm(exp-2) and not statistically significant AIE when included as <span class="hlt">ice</span> nuclei, for nucleation efficiencies within the range of laboratory measurements. Indirect effects of anthropogenic aerosols on cirrus clouds occur as a consequence of increasing anthropogenic sulfur emissions with different mechanisms important in different models. In one model this is due to increases in homogeneous nucleation fraction, and in the other due to increases in heterogeneous nucleation with coated dust. The magnitude of the effect is the same however. The resulting <span class="hlt">ice</span> AIE does not seem strongly dependent on the balance between homogeneous and heterogeneous <span class="hlt">ice</span> nucleation. Regional effects can reach several Wm2. Indirect effects are slightly larger for those states with less homogeneous nucleation and lower <span class="hlt">ice</span> number <span class="hlt">concentration</span> in the base state. The total <span class="hlt">ice</span> AIE is estimated at 0.27 +/- 0.10 Wm(exp-2) (1 sigma uncertainty). This represents a 20% offset of the simulated total shortwave AIE for <span class="hlt">ice</span> and liquid clouds of 1.6 Wm(sup-2).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20070016598&hterms=feedback&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dfeedback','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20070016598&hterms=feedback&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dfeedback"><span>Observational Evidence of a Hemispheric-wide <span class="hlt">Ice</span>-ocean Albedo Feedback Effect on Antarctic Sea-<span class="hlt">ice</span> Decay</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Nihashi, Sohey; Cavalieri, Donald J.</p> <p>2007-01-01</p> <p>The effect of <span class="hlt">ice</span>-ocean albedo feedback (a kind of <span class="hlt">ice</span>-albedo feedback) on sea-<span class="hlt">ice</span> decay is demonstrated over the Antarctic sea-<span class="hlt">ice</span> zone from an analysis of satellite-derived hemispheric sea <span class="hlt">ice</span> <span class="hlt">concentration</span> and European Centre for Medium-Range Weather Forecasts (ERA-40) atmospheric data for the period 1979-2001. Sea <span class="hlt">ice</span> <span class="hlt">concentration</span> in December (time of most active melt) correlates better with the meridional component of the wind-forced <span class="hlt">ice</span> drift (MID) in November (beginning of the melt season) than the MID in December. This 1 month lagged correlation is observed in most of the Antarctic sea-<span class="hlt">ice</span> covered ocean. Daily time series of <span class="hlt">ice</span> , <span class="hlt">concentration</span> show that the <span class="hlt">ice</span> <span class="hlt">concentration</span> anomaly increases toward the time of maximum sea-<span class="hlt">ice</span> melt. These findings can be explained by the following positive feedback effect: once <span class="hlt">ice</span> <span class="hlt">concentration</span> decreases (increases) at the beginning of the melt season, solar heating of the upper ocean through the increased (decreased) open water fraction is enhanced (reduced), leading to (suppressing) a further decrease in <span class="hlt">ice</span> <span class="hlt">concentration</span> by the oceanic heat. Results obtained fi-om a simple <span class="hlt">ice</span>-ocean coupled model also support our interpretation of the observational results. This positive feedback mechanism explains in part the large interannual variability of the sea-<span class="hlt">ice</span> cover in summer.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20000070377&hterms=melting+arctic+ice&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dmelting%2Barctic%2Bice','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20000070377&hterms=melting+arctic+ice&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dmelting%2Barctic%2Bice"><span>Arctic Summer <span class="hlt">Ice</span> Processes</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Holt, Benjamin</p> <p>1999-01-01</p> <p>The primary objective of this study is to estimate the flux of heat and freshwater resulting from sea <span class="hlt">ice</span> melt in the polar seas. The approach taken is to examine the decay of sea <span class="hlt">ice</span> in the summer months primarily through the use of spaceborne Synthetic Aperture Radar (SAR) imagery. The improved understanding of the dynamics of the melt process can be usefully combined with <span class="hlt">ice</span> thermodynamic and upper ocean models to form more complete models of <span class="hlt">ice</span> melt. Models indicate that more heat is absorbed in the upper ocean when the <span class="hlt">ice</span> cover is composed of smaller rather than larger floes and when there is more open water. Over the course of the summer, floes disintegrate by physical forcing and heating, melting into smaller and smaller sizes. By measuring the change in distribution of floes together with open water over a summer period, we can make estimates of the amount of heating by region and time. In a climatic sense, these studies are intended to improve the understanding of the Arctic heat budget which can then be eventually incorporated into improved global climate models. This work has two focus areas. The first is examining the detailed effect of storms on floe size and open water. A strong Arctic low pressure storm has been shown to loosen up the pack <span class="hlt">ice</span>, increase the open water <span class="hlt">concentration</span> well into the pack <span class="hlt">ice</span>, and change the distribution of floes toward fewer and smaller floes. This suggests episodic melting and the increased importance of horizontal (lateral) melt during storms. The second focus area is related to an extensive ship-based experiment that recently took place in the Arctic called Surface Heat Budget of the Arctic (SHEBA). An icebreaker was placed purposely into the older pack <span class="hlt">ice</span> north of Alaska in September 1997. The ship served as the base for experimenters who deployed extensive instrumentation to measure the atmosphere, ocean, and <span class="hlt">ice</span> during a one-year period. My experiment will be to derive similar measurements (floe size, open</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C21A0690W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C21A0690W"><span>Impact of <span class="hlt">ice</span>-shelf sediment content on the dynamics of plumes under melting <span class="hlt">ice</span> shelves</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wells, A.</p> <p>2015-12-01</p> <p>When a floating <span class="hlt">ice</span> shelf melts into an underlying warm salty ocean, the resulting fresh meltwater can rise in a buoyant <span class="hlt">Ice</span>-Shelf-Water plume under the <span class="hlt">ice</span>. In certain settings, <span class="hlt">ice</span> flowing across the grounding line carries a basal layer of debris rich <span class="hlt">ice</span>, entrained via basal freezing around till in the upstream <span class="hlt">ice</span> sheet. Melting of this debris-laden <span class="hlt">ice</span> from floating <span class="hlt">ice</span> shelves provides a flux of dense sediment to the ocean, in addition to the release of fresh buoyant meltwater. This presentation considers the impact of the resulting suspended sediment on the dynamics of <span class="hlt">ice</span> shelf water plumes, and identifies two key flow regimes depending on the sediment <span class="hlt">concentration</span> frozen into the basal <span class="hlt">ice</span> layer. For large sediment <span class="hlt">concentration</span>, melting of the debris-laden <span class="hlt">ice</span> shelf generates dense convectively unstable waters that drive convective overturning into the underlying ocean. For lower sediment <span class="hlt">concentration</span>, the sediment initially remains suspended in a buoyant meltwater plume rising along the underside of the <span class="hlt">ice</span> shelf, before slowly depositing into the underlying ocean. A theoretical plume model is used to evaluate the significance of the negatively buoyant sediment on circulation strength and the feedbacks on melting rate, along with the expected depositional patterns under the <span class="hlt">ice</span> shelf.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMMR21B2612G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMMR21B2612G"><span>Dielectric Signatures of Annealing in Glacier <span class="hlt">Ice</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Grimm, R. E.; Stillman, D. E.; MacGregor, J. A.</p> <p>2015-12-01</p> <p>We analyzed the dielectric spectra of 49 firn and <span class="hlt">ice</span> samples from <span class="hlt">ice</span> sheets and glaciers to better understand how differing <span class="hlt">ice</span> formation and evolution affect electrical properties. The dielectric relaxation of <span class="hlt">ice</span> is well known and its characteristic frequency increases with the <span class="hlt">concentration</span> of soluble impurities in the <span class="hlt">ice</span> lattice. We found that meteoric <span class="hlt">ice</span> and firn generally possess two such relaxations, indicating distinct crystal populations or zonation. Typically, one population is consistent with that of relatively pure <span class="hlt">ice</span>, and the other is significantly more impure. However, high temperatures (e.g., temperate <span class="hlt">ice</span>), long residence times (e.g., ancient <span class="hlt">ice</span> from Mullins Glacier, Antarctica), or anomalously high impurity <span class="hlt">concentrations</span> favor the development of a single relaxation. These relationships suggest that annealing causes two dielectrically distinct populations to merge into one population. The dielectric response of temperate <span class="hlt">ice</span> samples indicates increasing purity with increasing depth, suggesting final rejection of impurities from the lattice. Separately, subglacially frozen samples from the Vostok 5G <span class="hlt">ice</span> core possess a single relaxation whose variable characteristic frequency likely reflects the composition of the source water. Multi-frequency electrical measurements on cores and in the field can track annealing of glacier <span class="hlt">ice</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..1511437P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..1511437P"><span>New Greenland MSA and Na <span class="hlt">ice</span> core records: reliable proxies for Arctic sea <span class="hlt">ice</span> changes?</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Pol, Katy; Wolff, Eric; Abram, Nerilie; McConnell, Joseph R.; Mulvaney, Robert; Fleet, Louise</p> <p>2013-04-01</p> <p>MSA (methanesulfonic acid, derived from marine biogenic emissions) <span class="hlt">concentrations</span> in coastal Antarctic <span class="hlt">ice</span> cores have been suggested to record changes in sea <span class="hlt">ice</span> extent of the previous winter over recent decades. Using post-1979 satellite-derived sea <span class="hlt">ice</span> and meteorological data, the reliability of MSA as sea <span class="hlt">ice</span> proxy has indeed been demonstrated in the Indian Ocean and Bellinghausen Sea sectors, but not in the Weddell Sea one. Recently, it has also been argued that the sea <span class="hlt">ice</span> surface, not open water, is the dominant source of sea salt (including Na) over the Antarctic continent. Sea salt <span class="hlt">ice</span> core records may thus provide an alternative to MSA for the reconstruction of past sea <span class="hlt">ice</span> changes. Using new MSA and Na <span class="hlt">ice</span> core records from two Greenland sites, we here investigate the potential of those two chemical species as indicators of recent sea <span class="hlt">ice</span> changes in the Arctic sector.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20010037604','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20010037604"><span>Satellite Remote Sensing: Passive-Microwave Measurements of Sea <span class="hlt">Ice</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Parkinson, Claire L.; Zukor, Dorothy J. (Technical Monitor)</p> <p>2001-01-01</p> <p>Satellite passive-microwave measurements of sea <span class="hlt">ice</span> have provided global or near-global sea <span class="hlt">ice</span> data for most of the period since the launch of the Nimbus 5 satellite in December 1972, and have done so with horizontal resolutions on the order of 25-50 km and a frequency of every few days. These data have been used to calculate sea <span class="hlt">ice</span> <span class="hlt">concentrations</span> (percent areal coverages), sea <span class="hlt">ice</span> extents, the length of the sea <span class="hlt">ice</span> season, sea <span class="hlt">ice</span> temperatures, and sea <span class="hlt">ice</span> velocities, and to determine the timing of the seasonal onset of melt as well as aspects of the <span class="hlt">ice</span>-type composition of the sea <span class="hlt">ice</span> cover. In each case, the calculations are based on the microwave emission characteristics of sea <span class="hlt">ice</span> and the important contrasts between the microwave emissions of sea <span class="hlt">ice</span> and those of the surrounding liquid-water medium.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.youtube.com/watch?v=KHpG67esIlY','SCIGOVIMAGE-NASA'); return false;" href="http://www.youtube.com/watch?v=KHpG67esIlY"><span>Operation <span class="hlt">Ice</span>Bridge: Sea <span class="hlt">Ice</span> Interlude</span></a></p> <p><a target="_blank" href="http://www.nasa.gov/multimedia/videogallery/index.html">NASA Video Gallery</a></p> <p></p> <p></p> <p>Sea <span class="hlt">ice</span> comes in an array of shapes and sizes and has its own ephemeral beauty. Operation <span class="hlt">Ice</span>Bridge studies sea <span class="hlt">ice</span> at both poles, and also runs across interesting formations en route to other targ...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012GeCoA..90..110L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012GeCoA..90..110L"><span>Improvement of the determination of element <span class="hlt">concentrations</span> in quartz-hosted fluid inclusions by LA-ICP-MS and Pitzer thermodynamic modeling of <span class="hlt">ice</span> melting temperature</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Leisen, Mathieu; Dubessy, Jean; Boiron, Marie-Christine; Lach, Philippe</p> <p>2012-08-01</p> <p>Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) has become an essential analytical tool for the study of paleofluid chemistry through the analysis of individual fluid inclusions. The calculation of major and trace element <span class="hlt">concentrations</span> in fluid inclusions is usually based on empirical equations whose significance and accuracy are questionable. In addition, methods for estimation of analytical uncertainties element <span class="hlt">concentration</span> in individual fluid inclusions are lacking. This study describes a method based upon Pitzer's thermodynamic model for the calculation of major element (Na, K, Mg and Ca) <span class="hlt">concentrations</span> in low-to moderate-salinity fluid inclusions. A signal processing protocol, used in combination with the new method is also developed to calculate the <span class="hlt">concentration</span>, for each inclusion, and uncertainty for each major and trace element. In order to validate the proposed method, synthetic and natural fluid inclusions (from Alpine quartz veins) were ablated with a 193 nm ArF excimer laser and analyzed with a quadrupole ICP-MS, equipped with an octopole collision-reaction cell. The difference between the calculated and actual element <span class="hlt">concentration</span> (i.e. accuracy) does not exceed 20% and the calculated relative standard deviation (i.e. precision) for all element <span class="hlt">concentrations</span> is ˜10% in standards (glasses, solutions in capillary tubes and synthetic fluid inclusions). The element <span class="hlt">concentrations</span> obtained with this new method for the Alpine fluid inclusions are in good agreement with those previously measured using Laser Induced Breakdown Spectroscopy (LIBS) or crush-leach methods. Finally, the calculated <span class="hlt">concentrations</span> and associated uncertainties determined for each element in individual fluid inclusions show that the sensitivity of LA-ICP-MS analysis is high enough to reflect small variations of major and trace element <span class="hlt">concentrations</span> in the Alpine paleofluid, initially considered to have a constant chemistry. The new approach presented in</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017CliPa..13...39M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017CliPa..13...39M"><span>Sea <span class="hlt">ice</span> and pollution-modulated changes in Greenland <span class="hlt">ice</span> core methanesulfonate and bromine</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Maselli, Olivia J.; Chellman, Nathan J.; Grieman, Mackenzie; Layman, Lawrence; McConnell, Joseph R.; Pasteris, Daniel; Rhodes, Rachael H.; Saltzman, Eric; Sigl, Michael</p> <p>2017-01-01</p> <p>Reconstruction of past changes in Arctic sea <span class="hlt">ice</span> extent may be critical for understanding its future evolution. Methanesulfonate (MSA) and bromine <span class="hlt">concentrations</span> preserved in <span class="hlt">ice</span> cores have both been proposed as indicators of past sea <span class="hlt">ice</span> conditions. In this study, two <span class="hlt">ice</span> cores from central and north-eastern Greenland were analysed at sub-annual resolution for MSA (CH3SO3H) and bromine, covering the time period 1750-2010. We examine correlations between <span class="hlt">ice</span> core MSA and the HadISST1 <span class="hlt">ICE</span> sea <span class="hlt">ice</span> dataset and consult back trajectories to infer the likely source regions. A strong correlation between the low-frequency MSA and bromine records during pre-industrial times indicates that both chemical species are likely linked to processes occurring on or near sea <span class="hlt">ice</span> in the same source regions. The positive correlation between <span class="hlt">ice</span> core MSA and bromine persists until the mid-20th century, when the acidity of Greenland <span class="hlt">ice</span> begins to increase markedly due to increased fossil fuel emissions. After that time, MSA levels decrease as a result of declining sea <span class="hlt">ice</span> extent but bromine levels increase. We consider several possible explanations and ultimately suggest that increased acidity, specifically nitric acid, of snow on sea <span class="hlt">ice</span> stimulates the release of reactive Br from sea <span class="hlt">ice</span>, resulting in increased transport and deposition on the Greenland <span class="hlt">ice</span> sheet.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA216574','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA216574"><span>Studies of Cubic <span class="hlt">Ice</span> Crystals</span></a></p> <p><a target="_blank" href="https://publicaccess.dtic.mil/psm/api/service/search/search">DTIC Science & Technology</a></p> <p></p> <p>1989-12-11</p> <p>the nitrate ion <span class="hlt">concentration</span> in the <span class="hlt">ice</span>. We hypothesize that Br- was oxidized to bromine (Br2), hypobromous acid (HOBr), or bromic acid (HBr03). The...Crystals grown from solutions of ammonium carbonate at -16°C 35 10 Crystals grown from solutions of sulfuric acid at -16°C 36 11 <span class="hlt">Ice</span> crystal aspect ratios...elaborate crystals. When we compare this with the results of Workman and Reynolds for acid solutions, which all yielded negligible freezing potentials, we</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/22880966','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/22880966"><span><span class="hlt">Ice</span>-structuring mechanism for zirconium acetate.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Deville, Sylvain; Viazzi, Céline; Guizard, Christian</p> <p>2012-10-23</p> <p>The control of <span class="hlt">ice</span> nucleation and growth is critical in many natural and engineering situations. However, very few compounds are able to interact directly with the surface of <span class="hlt">ice</span> crystals. <span class="hlt">Ice</span>-structuring proteins, found in certain fish, plants, and insects, bind to the surface of <span class="hlt">ice</span>, thereby controlling their growth. We recently revealed the <span class="hlt">ice</span>-structuring properties of zirconium acetate, which are similar to those of <span class="hlt">ice</span>-structuring proteins. Because zirconium acetate is a salt and therefore different from proteins having <span class="hlt">ice</span>-structuring properties, its <span class="hlt">ice</span>-structuring mechanism remains unelucidated. Here we investigate this <span class="hlt">ice</span>-structuring mechanism through the role of the <span class="hlt">concentration</span> of zirconium acetate and the <span class="hlt">ice</span> crystal growth velocity. We then explore other compounds presenting similar functional groups (acetate, hydroxyl, or carboxylic groups). On the basis of these results, we propose that zirconium acetate adopts a hydroxy-bridged polymer structure that can bind to the surface of the <span class="hlt">ice</span> crystals through hydrogen bonding, thereby slowing down the <span class="hlt">ice</span> crystal growth.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C41B0701R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C41B0701R"><span>The Relationship Between Arctic Sea <span class="hlt">Ice</span> Albedo and the Geophysical Parameters of the <span class="hlt">Ice</span> Cover</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Riihelä, A.</p> <p>2015-12-01</p> <p>The Arctic sea <span class="hlt">ice</span> cover is thinning and retreating. Remote sensing observations have also shown that the mean albedo of the remaining <span class="hlt">ice</span> cover is decreasing on decadal time scales, albeit with significant annual variability (Riihelä et al., 2013, Pistone et al., 2014). Attribution of the albedo decrease between its different drivers, such as decreasing <span class="hlt">ice</span> <span class="hlt">concentration</span> and enhanced surface melt of the <span class="hlt">ice</span>, remains an important research question for the forecasting of future conditions of the <span class="hlt">ice</span> cover. A necessary step towards this goal is understanding the relationships between Arctic sea <span class="hlt">ice</span> albedo and the geophysical parameters of the <span class="hlt">ice</span> cover. Particularly the question of the relationship between sea <span class="hlt">ice</span> albedo and <span class="hlt">ice</span> age is both interesting and not widely studied. The recent changes in the Arctic sea <span class="hlt">ice</span> zone have led to a substantial decrease of its multi-year sea <span class="hlt">ice</span>, as old <span class="hlt">ice</span> melts and is replaced by first-year <span class="hlt">ice</span> during the next freezing season. It is generally known that younger sea <span class="hlt">ice</span> tends to have a lower albedo than older <span class="hlt">ice</span> because of several reasons, such as wetter snow cover and enhanced melt ponding. However, the quantitative correlation between sea <span class="hlt">ice</span> age and sea <span class="hlt">ice</span> albedo has not been extensively studied to date, excepting in-situ measurement based studies which are, by necessity, focused on a limited area of the Arctic Ocean (Perovich and Polashenski, 2012).In this study, I analyze the dependencies of Arctic sea <span class="hlt">ice</span> albedo relative to the geophysical parameters of the <span class="hlt">ice</span> field. I use remote sensing datasets such as the CM SAF CLARA-A1 (Karlsson et al., 2013) and the NASA MeaSUREs (Anderson et al., 2014) as data sources for the analysis. The studied period is 1982-2009. The datasets are spatiotemporally collocated and analysed. The changes in sea <span class="hlt">ice</span> albedo as a function of sea <span class="hlt">ice</span> age are presented for the whole Arctic Ocean and for potentially interesting marginal sea cases. This allows us to see if the the albedo of the older sea</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.C14B..02H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.C14B..02H"><span>The Seasonality of Antarctic Sea <span class="hlt">Ice</span> Trends</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Holland, P.</p> <p>2014-12-01</p> <p>Unlike the strong decline in Arctic sea <span class="hlt">ice</span>, Antarctic sea <span class="hlt">ice</span> is experiencing a weak overall increase in area that is the residual of opposing regional trends. This study considers the seasonal pattern of these trends. In addition to traditional <span class="hlt">ice</span> <span class="hlt">concentration</span> and <span class="hlt">ice</span> area, temporal rates of change of these quantities are investigated ("intensification" and "expansion," respectively). This is crucial to the attribution of the Antarctic sea <span class="hlt">ice</span> trends, since changes in wind or thermal forcing directly affect <span class="hlt">ice</span> areal change, rather than <span class="hlt">ice</span> area itself. The study shows that diverse regional trends all contribute significantly to the overall Antarctic sea-<span class="hlt">ice</span> increase. In contrast to the widely-held view of a 'south Pacific dipole', trends in the Weddell and Amundsen-Bellingshausen regions are found to best compensate in magnitude and seasonality. Perhaps most importantly, the largest <span class="hlt">concentration</span> trends, in autumn, are actually caused by intensification trends during spring. Autumn intensification trends directly oppose autumn <span class="hlt">concentration</span> trends in most places, seemingly as a result of <span class="hlt">ice</span> and ocean feedbacks. Further study of changes during the spring melting season is therefore required to unravel the Antarctic sea <span class="hlt">ice</span> increase.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20160002943','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20160002943"><span>Sensitivity of Cirrus Properties to <span class="hlt">Ice</span> Nuclei Abundance</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Jensen, Eric</p> <p>2014-01-01</p> <p>The relative importance of heterogeneous and homogeneous <span class="hlt">ice</span> nucleation for cirrus formation remains an active area of debate in the cloud physics community. From a theoretical perspective, a number of modeling studies have investigated the sensitivity of <span class="hlt">ice</span> number <span class="hlt">concentration</span> to the nucleation mechanism and the abundance of <span class="hlt">ice</span> nuclei. However, these studies typically only addressed <span class="hlt">ice</span> <span class="hlt">concentration</span> immediately after <span class="hlt">ice</span> nucleation. Recent modeling work has shown that the high <span class="hlt">ice</span> <span class="hlt">concentrations</span> produced by homogeneous freezing may not persist very long, which is consistent with the low frequency of occurrence of high <span class="hlt">ice</span> <span class="hlt">concentrations</span> indicated by cirrus measurements. Here, I use idealized simulations to investigate the impact of <span class="hlt">ice</span> nucleation mechanism and <span class="hlt">ice</span> nuclei abundance on the full lifecycle of cirrus clouds. The primary modeling framework used includes different modes of <span class="hlt">ice</span> nucleation, deposition growth/sublimation, aggregation, sedimentation, and radiation. A limited number of cloud-resolving simulations that treat radiation/dynamics interactions will also been presented. I will show that for typical synoptic situations with mesoscale waves present, the time-averaged cirrus <span class="hlt">ice</span> crystal size distributions and bulk cloud properties are less sensitive to <span class="hlt">ice</span> nucleation processes than might be expected from the earlier simple <span class="hlt">ice</span> nucleation calculations. I will evaluate the magnitude of the <span class="hlt">ice</span> nuclei impact on cirrus for a range of temperatures and mesoscale wave specifications, and I will discuss the implications for cirrus aerosol indirect effects in general.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1990DSRA...37.1311K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1990DSRA...37.1311K"><span>Bacterial biomass and production in pack <span class="hlt">ice</span> of Antarctic marginal <span class="hlt">ice</span> edge zones</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kottmeier, Steven T.; Sullivan, Cornelius W.</p> <p>1990-08-01</p> <p>Bacterial biomass and production in pack <span class="hlt">ice</span> is little known even though the pack accounts for the majority of the 20 million square kilometer Antarctic sea <span class="hlt">ice</span> habitat. On three cruises in marginal <span class="hlt">ice</span> edge zones, spring 1983 (AMERIEZ I), autumn 1986 (AMERIEZ II), and late winter 1985 (Wintercruise I), considerable bacterial biomass and production was found throughout <span class="hlt">ice</span> floes up to 2.22 m thick. We hypothesize that bacteria accumulate in pack <span class="hlt">ice</span> as a result of both physical and biological processes. During the formation and growth of <span class="hlt">ice</span>, physical processes act to <span class="hlt">concentrate</span> and accumulate bacteria within the <span class="hlt">ice</span> matrix. This is followed by in situ growth along physiochemical gradients found in several sea <span class="hlt">ice</span> microhabitats. Bacterial biomass and production in <span class="hlt">ice</span> were equal to that present in several meters of underlying seawater during all seasons. Among microhabitats, highest bacterial production and most rapid rates of growth ( >1 d -1) were found in saline ponds on the surface of floes and porewater in the interior of floes. Bacterial carbon production ranged from 2% of primary production in surface brash to 45-221% of primary production in surface ponds and porewater. Bacterial growth and microalgal photosynthetic metabolism in pack <span class="hlt">ice</span> appear to be coupled in a fashion similar to that described for fast <span class="hlt">ice</span>. The presence of substantial numbers of active, feeding protozoans and metazoans in pack <span class="hlt">ice</span> suggests, albeit indirectly, that bacterial production supports microheterotrophs of the microbial loop, which in turn may support organisms at higher trophic levels. Bacterial growth in pack <span class="hlt">ice</span> may be important to the potential for primary production. Thus <span class="hlt">ice</span> bacteria may provide remineralized inorganic nutrients necessary for continued microalgal growth in localized microhabitats within the <span class="hlt">ice</span> or they may compete with algae for nutrients. Upon release from melting <span class="hlt">ice</span>, actively growing bacteria also contribute to microbial biomass in seawater. From these</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li class="active"><span>17</span></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_17 --> <div id="page_18" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li class="active"><span>18</span></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="341"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=312689','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=312689"><span>A comparison between two algorithms for the retrieval of soil moisture using <span class="hlt">AMSR-E</span> data</span></a></p> <p><a target="_blank" href="http://www.ars.usda.gov/services/TekTran.htm">Technology Transfer Automated Retrieval System (TEKTRAN)</a></p> <p></p> <p></p> <p>A comparison between two algorithms for estimating soil moisture with microwave satellite data was carried out by using the datasets collected on the four Agricultural Research Service (ARS) watershed sites in the US from 2002 to 2009. These sites collectively represent a wide range of ground condit...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120008162','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120008162"><span>The Impact of <span class="hlt">AMSR-E</span> Soil Moisture Assimilation on Evapotranspiration Estimation</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Peters-Lidard, Christa D.; Kumar, Sujay; Mocko, David; Tian, Yudong</p> <p>2012-01-01</p> <p>An assessment ofETestimates for current LDAS systems is provided along with current research that demonstrates improvement in LSM ET estimates due to assimilating satellite-based soil moisture products. Using the Ensemble Kalman Filter in the Land Information System, we assimilate both NASA and Land Parameter Retrieval Model (LPRM) soil moisture products into the Noah LSM Version 3.2 with the North American LDAS phase 2 CNLDAS-2) forcing to mimic the NLDAS-2 configuration. Through comparisons with two global reference ET products, one based on interpolated flux tower data and one from a new satellite ET algorithm, over the NLDAS2 domain, we demonstrate improvement in ET estimates only when assimilating the LPRM soil moisture product.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/AD0749247','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/AD0749247"><span>Cationic Analysis of the Byrd Station, Antarctica, <span class="hlt">Ice</span> Core.</span></a></p> <p><a target="_blank" href="https://publicaccess.dtic.mil/psm/api/service/search/search">DTIC Science & Technology</a></p> <p></p> <p></p> <p>Eighty-five <span class="hlt">ice</span> samples taken from the Byrd Station, Antarctica, <span class="hlt">ice</span> core were analyzed for Na(+), K(+), Ca(2+), and Mg(2+) <span class="hlt">concentrations</span> by atomic absorption spectroscopy . The depth measured was from 168 to 2090 m.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016GeoRL..43.1642G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016GeoRL..43.1642G"><span>Predictability of the Arctic sea <span class="hlt">ice</span> edge</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Goessling, H. F.; Tietsche, S.; Day, J. J.; Hawkins, E.; Jung, T.</p> <p>2016-02-01</p> <p>Skillful sea <span class="hlt">ice</span> forecasts from days to years ahead are becoming increasingly important for the operation and planning of human activities in the Arctic. Here we analyze the potential predictability of the Arctic sea <span class="hlt">ice</span> edge in six climate models. We introduce the integrated <span class="hlt">ice</span>-edge error (IIEE), a user-relevant verification metric defined as the area where the forecast and the "truth" disagree on the <span class="hlt">ice</span> <span class="hlt">concentration</span> being above or below 15%. The IIEE lends itself to decomposition into an absolute extent error, corresponding to the common sea <span class="hlt">ice</span> extent error, and a misplacement error. We find that the often-neglected misplacement error makes up more than half of the climatological IIEE. In idealized forecast ensembles initialized on 1 July, the IIEE grows faster than the absolute extent error. This means that the Arctic sea <span class="hlt">ice</span> edge is less predictable than sea <span class="hlt">ice</span> extent, particularly in September, with implications for the potential skill of end-user relevant forecasts.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/12154613','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/12154613"><span>Ecology of southern ocean pack <span class="hlt">ice</span>.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Brierley, Andrew S; Thomas, David N</p> <p>2002-01-01</p> <p>Around Antarctica the annual five-fold growth and decay of sea <span class="hlt">ice</span> is the most prominent physical process and has a profound impact on marine life there. In winter the pack <span class="hlt">ice</span> canopy extends to cover almost 20 million square kilometres--some 8% of the southern hemisphere and an area larger than the Antarctic continent itself (13.2 million square kilometres)--and is one of the largest, most dynamic ecosystems on earth. Biological activity is associated with all physical components of the sea-<span class="hlt">ice</span> system: the sea-<span class="hlt">ice</span> surface; the internal sea-<span class="hlt">ice</span> matrix and brine channel system; the underside of sea <span class="hlt">ice</span> and the waters in the vicinity of sea <span class="hlt">ice</span> that are modified by the presence of sea <span class="hlt">ice</span>. Microbial and microalgal communities proliferate on and within sea <span class="hlt">ice</span> and are grazed by a wide range of proto- and macrozooplankton that inhabit the sea <span class="hlt">ice</span> in large <span class="hlt">concentrations</span>. Grazing organisms also exploit biogenic material released from the sea <span class="hlt">ice</span> at <span class="hlt">ice</span> break-up or melt. Although rates of primary production in the underlying water column are often low because of shading by sea-<span class="hlt">ice</span> cover, sea <span class="hlt">ice</span> itself forms a substratum that provides standing stocks of bacteria, algae and grazers significantly higher than those in <span class="hlt">ice</span>-free areas. Decay of sea <span class="hlt">ice</span> in summer releases particulate and dissolved organic matter to the water column, playing a major role in biogeochemical cycling as well as seeding water column phytoplankton blooms. Numerous zooplankton species graze sea-<span class="hlt">ice</span> algae, benefiting additionally because the overlying sea-<span class="hlt">ice</span> ceiling provides a refuge from surface predators. Sea <span class="hlt">ice</span> is an important nursery habitat for Antarctic krill, the pivotal species in the Southern Ocean marine ecosystem. Some deep-water fish migrate to shallow depths beneath sea <span class="hlt">ice</span> to exploit the elevated <span class="hlt">concentrations</span> of some zooplankton there. The increased secondary production associated with pack <span class="hlt">ice</span> and the sea-<span class="hlt">ice</span> edge is exploited by many higher predators, with seals, seabirds and whales</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA524685','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA524685"><span>Long-Range Forecasting of Arctic Sea <span class="hlt">Ice</span></span></a></p> <p><a target="_blank" href="https://publicaccess.dtic.mil/psm/api/service/search/search">DTIC Science & Technology</a></p> <p></p> <p>2010-06-01</p> <p>19 1. Sea <span class="hlt">Ice</span> <span class="hlt">Concentrations</span> from Nimbus -7 SMMR and DMSP SSM/I Passive...LEFT BLANK 19 II. DATA AND METHODS A. DATA SETS 1. Sea <span class="hlt">Ice</span> <span class="hlt">Concentrations</span> from Nimbus -7 SMMR and DMSP SSM/I Passive Microwave Data The sea <span class="hlt">ice</span>...for Arctic sea <span class="hlt">ice</span> research in the past. (e.g., Deser and Teng 2008). The data set is generated from brightness temperature derived from Nimbus -7</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AMTD....8.2223M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AMTD....8.2223M"><span>The micro-orifice uniform deposit impactor-droplet freezing technique (MOUDI-DFT) for measuring <span class="hlt">concentrations</span> of <span class="hlt">ice</span> nucleating particles as a function of size: improvements and initial validation</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mason, R. H.; Chou, C.; McCluskey, C. S.; Levin, E. J. T.; Schiller, C. L.; Hill, T. C. J.; Huffman, J. A.; DeMott, P. J.; Bertram, A. K.</p> <p>2015-02-01</p> <p>The micro-orifice uniform deposit impactor-droplet freezing technique (MOUDI-DFT) combines particle collection by inertial impaction (via the MOUDI) and a microscope-based immersion freezing apparatus (the DFT) to measure atmospheric <span class="hlt">concentrations</span> of <span class="hlt">ice</span> nucleating particles (INPs) as a function of size and temperature. In the first part of this study we improved upon this recently introduced technique. Using optical microscopy, we investigated the non-uniformity of MOUDI aerosol deposits at spatial resolutions of 1, 0.25 mm, and for some stages when necessary 0.10 mm. The results from these measurements show that at a spatial resolution of 1 mm and less, the <span class="hlt">concentration</span> of particles along the MOUDI aerosol deposit can vary by an order of magnitude or more. Since the total area of a MOUDI aerosol deposit ranges from 425 to 605 mm2 and the area analyzed by the DFT is approximately 1.2 mm2, this non-uniformity needs to be taken into account when using the MOUDI-DFT to determine atmospheric <span class="hlt">concentrations</span> of INPs. Measurements of the non-uniformity of the MOUDI aerosol deposits were used to select positions on the deposits that had relatively small variations in particle <span class="hlt">concentration</span> and to build substrate holders for the different MOUDI stages. These substrate holders improve reproducibility by holding the substrate in the same location for each measurement and ensure that DFT analysis is only performed on substrate regions with relatively small variations in particle <span class="hlt">concentration</span>. In addition, the deposit non-uniformity was used to determine correction factors that take the non-uniformity into account when determining atmospheric <span class="hlt">concentrations</span> of INPs. In the second part of this study, the MOUDI-DFT utilizing the new substrate holders was compared to the continuous flow diffusion chamber (CFDC) technique of Colorado State University. The intercomparison was done using INP <span class="hlt">concentrations</span> found by the two instruments during ambient measurements of continental</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AMT.....8.2449M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AMT.....8.2449M"><span>The micro-orifice uniform deposit impactor-droplet freezing technique (MOUDI-DFT) for measuring <span class="hlt">concentrations</span> of <span class="hlt">ice</span> nucleating particles as a function of size: improvements and initial validation</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mason, R. H.; Chou, C.; McCluskey, C. S.; Levin, E. J. T.; Schiller, C. L.; Hill, T. C. J.; Huffman, J. A.; DeMott, P. J.; Bertram, A. K.</p> <p>2015-06-01</p> <p>The micro-orifice uniform deposit impactor-droplet freezing technique (MOUDI-DFT) combines particle collection by inertial impaction (via the MOUDI) and a microscope-based immersion freezing apparatus (the DFT) to measure atmospheric <span class="hlt">concentrations</span> of <span class="hlt">ice</span> nucleating particles (INPs) as a function of size and temperature. In the first part of this study we improved upon this recently introduced technique. Using optical microscopy, we investigated the non-uniformity of MOUDI aerosol deposits at spatial resolutions of 1, 0.25 mm, and for some stages when necessary 0.10 mm. The results from these measurements show that at a spatial resolution of 1 mm and less, the <span class="hlt">concentration</span> of particles along the MOUDI aerosol deposits can vary by an order of magnitude or more. Since the total area of a MOUDI aerosol deposit ranges from 425 to 605 mm2 and the area analyzed by the DFT is approximately 1.2 mm2, this non-uniformity needs to be taken into account when using the MOUDI-DFT to determine atmospheric <span class="hlt">concentrations</span> of INPs. Measurements of the non-uniformity of the MOUDI aerosol deposits were used to select positions on the deposits that had relatively small variations in particle <span class="hlt">concentration</span> and to build substrate holders for the different MOUDI stages. These substrate holders improve reproducibility by holding the substrate in the same location for each measurement and ensure that DFT analysis is only performed on substrate regions with relatively small variations in particle <span class="hlt">concentration</span>. In addition, the deposit non-uniformity was used to determine correction factors that take the non-uniformity into account when determining atmospheric <span class="hlt">concentrations</span> of INPs. In the second part of this study, the MOUDI-DFT utilizing the new substrate holders was compared to the continuous flow diffusion chamber (CFDC) technique of Colorado State University. The intercomparison was done using INP <span class="hlt">concentrations</span> found by the two instruments during ambient measurements of continental</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://pubs.er.usgs.gov/publication/70014695','USGSPUBS'); return false;" href="http://pubs.er.usgs.gov/publication/70014695"><span>Remote sensing of the Fram Strait marginal <span class="hlt">ice</span> zone</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Shuchman, R.A.; Burns, B.A.; Johannessen, O.M.; Josberger, E.G.; Campbell, W.J.; Manley, T.O.; Lannelongue, N.</p> <p>1987-01-01</p> <p>Sequential remote sensing images of the Fram Strait marginal <span class="hlt">ice</span> zone played a key role in elucidating the complex interactions of the atmosphere, ocean, and sea <span class="hlt">ice</span>. Analysis of a subset of these images covering a 1-week period provided quantitative data on the mesoscale <span class="hlt">ice</span> morphology, including <span class="hlt">ice</span> edge positions, <span class="hlt">ice</span> <span class="hlt">concentrations</span>, floe size distribution, and <span class="hlt">ice</span> kinematics. The analysis showed that, under light to moderate wind conditions, the morphology of the marginal <span class="hlt">ice</span> zone reflects the underlying ocean circulation. High-resolution radar observations showed the location and size of ocean eddies near the <span class="hlt">ice</span> edge. <span class="hlt">Ice</span> kinematics from sequential radar images revealed an ocean eddy beneath the interior pack <span class="hlt">ice</span> that was verified by in situ oceanographic measurements.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA242491','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA242491"><span>SSM/I Sea <span class="hlt">Ice</span> Products Validation</span></a></p> <p><a target="_blank" href="https://publicaccess.dtic.mil/psm/api/service/search/search">DTIC Science & Technology</a></p> <p></p> <p>1991-06-01</p> <p>4.0 presents both a coarse resolution <span class="hlt">ice</span> classification algorithm designed to separate different <span class="hlt">ice</span> types from highly multilooked SAR imagery, along...algorithms. The coarse resolution algorithm uses SAR data which is highly multilooked to reduce the effects of the multiplicative noise inherent to all...data. This paper will present comparisons between these SSM/I derived <span class="hlt">ice</span> <span class="hlt">concentration</span> estimates and estimates derived from high resolution SAR data</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2003SPIE.4883..141D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2003SPIE.4883..141D"><span>SAR observations of waves in <span class="hlt">ice</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>De Carolis, Giacomo</p> <p>2003-03-01</p> <p>Ocean waves properties propagating in grease <span class="hlt">ice</span> composed of frazil and pancakes as observed by SAR images are discussed. An ERS-2 SAR scene relevant to the Greenland Sea in an area where the Odden <span class="hlt">ice</span> tongue developed in 1997 is considered as case study. The scene includes open sea and <span class="hlt">ice</span> covered waters where a wave field is traveling from the open sea region. Wind induced features known as "wind rolls" can be distinguished, allowing the estimation of the wind vector. Hence the related wind generated ocean waves can be retrieved using a SAR spectral inversion procedure. The wave field is tracked while it propagates inside the <span class="hlt">ice</span> field, thus allowing the estimation of the wave changes. Under the assumption of continuum medium, physical <span class="hlt">ice</span> properties are then retrieved using a special SAR inversion procedure in conjunction with a recently developed wave propagation model in sea <span class="hlt">ice</span>. The model assumes both the <span class="hlt">ice</span> layer and the water beneath it as a system of viscous fluids. As a result, the changes suffered by the ocean wave spectrum in terms of wave dispersion and energy attenuation are related to sea <span class="hlt">ice</span> properties such as <span class="hlt">concentration</span> and thickness. Although the free parameters to be inverted are the <span class="hlt">ice</span> thickness and viscosity and the water viscosity, the <span class="hlt">ice</span> thickness is the only parameter of geophysical interest. Results are finally compared with external <span class="hlt">ice</span> parameters information.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19850005139','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19850005139"><span>Dynamics of coupled <span class="hlt">ice</span>-ocean system in the marginal <span class="hlt">ice</span> zone: Study of the mesoscale processes and of constitutive equations for sea <span class="hlt">ice</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hakkinen, S.</p> <p>1984-01-01</p> <p>This study is aimed at the modelling of mesoscale processed such as up/downwelling and <span class="hlt">ice</span> edge eddies in the marginal <span class="hlt">ice</span> zones. A 2-dimensional coupled <span class="hlt">ice</span>-ocean model is used for the study. The <span class="hlt">ice</span> model is coupled to the reduced gravity ocean model (f-plane) through interfacial stresses. The constitutive equations of the sea <span class="hlt">ice</span> are formulated on the basis of the Reiner-Rivlin theory. The internal <span class="hlt">ice</span> stresses are important only at high <span class="hlt">ice</span> <span class="hlt">concentrations</span> (90-100%), otherwise the <span class="hlt">ice</span> motion is essentially free drift, where the air-<span class="hlt">ice</span> stress is balanced by the <span class="hlt">ice</span>-water stress. The model was tested by studying the upwelling dynamics. Winds parallel to the <span class="hlt">ice</span> edge with the <span class="hlt">ice</span> on the right produce upwilling because the air-<span class="hlt">ice</span> momentum flux is much greater that air-ocean momentum flux, and thus the Ekman transport is bigger under the <span class="hlt">ice</span> than in the open water. The upwelling simulation was extended to include temporally varying forcing, which was chosen to vary sinusoidally with a 4 day period. This forcing resembles successive cyclone passings. In the model with a thin oceanic upper layer, <span class="hlt">ice</span> bands were formed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.C23E0542F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.C23E0542F"><span>Validation and Interpretation of a New Sea <span class="hlt">Ice</span> Globice Dataset Using Buoys and the Cice Sea <span class="hlt">Ice</span> Model</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Flocco, D.; Laxon, S. W.; Feltham, D. L.; Haas, C.</p> <p>2011-12-01</p> <p>The Glob<span class="hlt">Ice</span> project has provided high resolution sea <span class="hlt">ice</span> product datasets over the Arctic derived from SAR data in the ESA archive. The products are validated sea <span class="hlt">ice</span> motion, deformation and fluxes through straits. Glob<span class="hlt">Ice</span> sea <span class="hlt">ice</span> velocities, deformation data and sea <span class="hlt">ice</span> <span class="hlt">concentration</span> have been validated using buoy data provided by the International Arctic Buoy Program (IABP). Over 95% of the Glob<span class="hlt">Ice</span> and buoy data analysed fell within 5 km of each other. The Glob<span class="hlt">Ice</span> Eulerian image pair product showed a high correlation with buoy data. The sea <span class="hlt">ice</span> <span class="hlt">concentration</span> product was compared to SSM/I data. An evaluation of the validity of the Glob<span class="hlt">ICE</span> data will be presented in this work. Glob<span class="hlt">ICE</span> sea <span class="hlt">ice</span> velocity and deformation were compared with runs of the CICE sea <span class="hlt">ice</span> model: in particular the mass fluxes through the straits were used to investigate the correlation between the winter behaviour of sea <span class="hlt">ice</span> and the sea <span class="hlt">ice</span> state in the following summer.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUFM.C11A0465M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUFM.C11A0465M"><span>Characteristics of basal <span class="hlt">ice</span> and subglacial water at Dome Fuji, Antarctica <span class="hlt">ice</span> sheet</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Motoyama, H.; Uemura, R.; Hirabayashi, M.; Miyake, T.; Kuramoto, T.; Tanaka, Y.; Dome Fuji Ice Core Project, M.</p> <p>2008-12-01</p> <p> than the cutting chips has been collected. When the drilling passed 3033.46m, the amount of <span class="hlt">ice</span> chip was decreased. But the amount of <span class="hlt">ice</span> chip collected increase again from 3034.59m and many large <span class="hlt">ices</span> have taken the upper part of <span class="hlt">ice</span> core. The temperature of <span class="hlt">ice</span> sheet near the bedrock is the pressure melting point. So the liquid water can exist easy there. The water like groundwater infiltrated into the borehole and froze in drilling liquid from 3031.44m to 3033.46m. Under 3034.59m, the subglacial water infiltrated into the borehole and froze in drilling liquid. The existence of water channel in the <span class="hlt">ice</span> core was found. We think that the liquid water has been flowing through the boundary of <span class="hlt">ice</span> crystal. (Characteristics of chemical constituents): The melted <span class="hlt">ice</span> was analyzed every 10cm per 50cm from 2400m to 3028m and continuously every 10cm from 3028m to 3034m. The analytical items were water isotopes (d18O and dD), micro particles (dust) and major ion components. The variations of water isotope and dust in <span class="hlt">ice</span> near the bedrock have no conspicuous change. But, the <span class="hlt">concentrations</span> of Cl- and Na+ ions had interesting behavior. The <span class="hlt">concentration</span> of Cl- ion increased and Na+ ion was decreased deeper than 3020m. Further the <span class="hlt">concentrations</span> of all ions were decreased suddenly deeper than 3034m. The <span class="hlt">concentration</span> of ions will be decrease in turn according to the solubility of the ion. home/</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20090022254','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20090022254"><span>Novel <span class="hlt">Ice</span> Mitigation Methods</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p></p> <p>2008-01-01</p> <p>After the loss of Columbia, there was great concern in the Space Shuttle program for the impact of debris against the leading edges of the Orbiter wings. It was quickly recognized that, in addition to impacts by foam, <span class="hlt">ice</span> that formed on the liquid-oxygen bellows running down the outside of the External Tank could break free during launch and hit this sensitive area. A Center Director s Discretionary Fund (CDDF) project would <span class="hlt">concentrate</span> on novel ideas that were potentially applicable. The most successful of the new concepts for <span class="hlt">ice</span> mitigation involved shape memory alloy materials. These materials can be bent into a given shape and, when heated, will return to their original shape.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://pubs.er.usgs.gov/publication/70175240','USGSPUBS'); return false;" href="http://pubs.er.usgs.gov/publication/70175240"><span>Arctic sea <span class="hlt">ice</span> decline contributes to thinning lake <span class="hlt">ice</span> trend in northern Alaska</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Alexeev, Vladimir; Arp, Christopher D.; Jones, Benjamin M.; Cai, Lei</p> <p>2016-01-01</p> <p>Field measurements, satellite observations, and models document a thinning trend in seasonal Arctic lake <span class="hlt">ice</span> growth, causing a shift from bedfast to floating <span class="hlt">ice</span> conditions. September sea <span class="hlt">ice</span> <span class="hlt">concentrations</span> in the Arctic Ocean since 1991 correlate well (r = +0.69,p < 0.001) to this lake regime shift. To understand how and to what extent sea <span class="hlt">ice</span> affects lakes, we conducted model experiments to simulate winters with years of high (1991/92) and low (2007/08) sea <span class="hlt">ice</span> extent for which we also had field measurements and satellite imagery characterizing lake <span class="hlt">ice</span> conditions. A lake <span class="hlt">ice</span> growth model forced with Weather Research and Forecasting model output produced a 7% decrease in lake <span class="hlt">ice</span> growth when 2007/08 sea <span class="hlt">ice</span> was imposed on 1991/92 climatology and a 9% increase in lake <span class="hlt">ice</span> growth for the opposing experiment. Here, we clearly link early winter 'ocean-effect' snowfall and warming to reduced lake <span class="hlt">ice</span> growth. Future reductions in sea <span class="hlt">ice</span> extent will alter hydrological, biogeochemical, and habitat functioning of Arctic lakes and cause sub-lake permafrost thaw.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016ERL....11g4022A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016ERL....11g4022A"><span>Arctic sea <span class="hlt">ice</span> decline contributes to thinning lake <span class="hlt">ice</span> trend in northern Alaska</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Alexeev, Vladimir A.; Arp, Christopher D.; Jones, Benjamin M.; Cai, Lei</p> <p>2016-07-01</p> <p>Field measurements, satellite observations, and models document a thinning trend in seasonal Arctic lake <span class="hlt">ice</span> growth, causing a shift from bedfast to floating <span class="hlt">ice</span> conditions. September sea <span class="hlt">ice</span> <span class="hlt">concentrations</span> in the Arctic Ocean since 1991 correlate well (r = +0.69, p < 0.001) to this lake regime shift. To understand how and to what extent sea <span class="hlt">ice</span> affects lakes, we conducted model experiments to simulate winters with years of high (1991/92) and low (2007/08) sea <span class="hlt">ice</span> extent for which we also had field measurements and satellite imagery characterizing lake <span class="hlt">ice</span> conditions. A lake <span class="hlt">ice</span> growth model forced with Weather Research and Forecasting model output produced a 7% decrease in lake <span class="hlt">ice</span> growth when 2007/08 sea <span class="hlt">ice</span> was imposed on 1991/92 climatology and a 9% increase in lake <span class="hlt">ice</span> growth for the opposing experiment. Here, we clearly link early winter ‘ocean-effect’ snowfall and warming to reduced lake <span class="hlt">ice</span> growth. Future reductions in sea <span class="hlt">ice</span> extent will alter hydrological, biogeochemical, and habitat functioning of Arctic lakes and cause sub-lake permafrost thaw.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012TRACE..22..429Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012TRACE..22..429Y"><span>A Study on Generation <span class="hlt">Ice</span> Containing Ozone</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Yoshimura, Kenji; Koyama, Shigeru; Yamamoto, Hiromi</p> <p></p> <p>Ozone has the capability of sterilization and deodorization due to high oxidation power. It is also effective for the conservation of perishable foods and purification of water. However, ozone has a disadvantage, that is, conservation of ozone is difficult because it changes back into oxygen. Recently, <span class="hlt">ice</span> containing ozone is taken attention for the purpose of its conservation. The use of <span class="hlt">ice</span> containing ozone seems to keep food fresher when we conserve and transport perishable foods due to effects of cooling and sterilization of <span class="hlt">ice</span> containing ozone. In the present study, we investigated the influence of temperatures of water dissolving ozone on the timewise attenuations of ozone <span class="hlt">concentration</span> in water. We also investigated the influence of cooling temperature, <span class="hlt">ice</span> diameter, initial temperatures of water dissolving ozone and container internal pressure of the water dissolving ozone on ozone <span class="hlt">concentration</span> in the <span class="hlt">ice</span>. In addition, we investigated the influence of the <span class="hlt">ice</span> diameter on the timewise attenuations of ozone <span class="hlt">concentration</span> in the <span class="hlt">ice</span>. It was confirmed that the solidification experimental data can be adjusted by a correlation between ozone <span class="hlt">concentration</span> in the <span class="hlt">ice</span> and solidification time.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.C11B0364K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.C11B0364K"><span>The variability of sea <span class="hlt">ice</span> motion in Antarctic</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kim, C. S.; Kim, T. W.; Kim, H. C.; Lee, S.</p> <p>2014-12-01</p> <p>As well known, sea <span class="hlt">ice</span> is a vital component in the marginal <span class="hlt">ice</span> zone as well as the global climate system. Antarctic sea <span class="hlt">ice</span> is reported to be sensitive to surface wind forcing. We used a simplified linear formula to understand the relationship between the <span class="hlt">ice</span> motion and wind as Kimura (2004). These previous study was evaluated relationship using speed reduction factor and turning angle in the Southern Ocean. We use the two types gridded daily sea <span class="hlt">ice</span> products by the National Snow and <span class="hlt">Ice</span> Data Center (NSIDC) ; Sea <span class="hlt">Ice</span> <span class="hlt">Concentrations</span> from Nimbus-7 SMMR and DMSP SSM/I-SSMIS Passive Microwave Data and sea <span class="hlt">ice</span> motion from Polar Pathfinder Daily 25 km EASE-Grid Sea <span class="hlt">Ice</span> Motion Vectors. Satellite-observed sea <span class="hlt">ice</span> data was compared with ERA interim reanalysis wind data. In this study, we evaluate the variability of the sea <span class="hlt">ice</span> <span class="hlt">concentration</span> and motion in the Southern Ocean in order to investigate the effects of wind on the spatial and temporal variability of the sea <span class="hlt">ice</span> motion. Moreover, we need to know the change in the sea <span class="hlt">ice</span> motion in accordance with the sea <span class="hlt">ice</span> characteristics in Antarctic.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20040034050','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20040034050"><span>African Dust Aerosols as Atmospheric <span class="hlt">Ice</span> Nuclei</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>DeMott, Paul J.; Brooks, Sarah D.; Prenni, Anthony J.; Kreidenweis, Sonia M.; Sassen, Kenneth; Poellot, Michael; Rogers, David C.; Baumgardner, Darrel</p> <p>2003-01-01</p> <p>Measurements of the <span class="hlt">ice</span> nucleating ability of aerosol particles in air masses over Florida having sources from North Africa support the potential importance of dust aerosols for indirectly affecting cloud properties and climate. The <span class="hlt">concentrations</span> of <span class="hlt">ice</span> nuclei within dust layers at particle sizes below 1 pn exceeded 1/cu cm; the highest ever reported with our device at temperatures warmer than homogeneous freezing conditions. These measurements add to previous direct and indirect evidence of the <span class="hlt">ice</span> nucleation efficiency of desert dust aerosols, but also confirm their contribution to <span class="hlt">ice</span> nuclei populations at great distances from source regions.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li class="active"><span>18</span></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_18 --> <div id="page_19" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li class="active"><span>19</span></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="361"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3773465','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3773465"><span>In Situ Spectroscopic Quantification of Protein–<span class="hlt">Ice</span> Interactions</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Twomey, Alan; Less, Rebekah; Kurata, Kosaku; Takamatsu, Hiroshi; Aksan, Alptekin</p> <p>2013-01-01</p> <p>FTIR and confocal Raman microspectroscopy were used to measure interactions between albumin and <span class="hlt">ice</span> in situ during quasi-equilibrium freezing in dimethyl sulfoxide (DMSO) solutions. At temperatures of −4 and −6 °C, albumin was found to be preferentially excluded from the <span class="hlt">ice</span> phase during near-equilibrium freezing. This behavior reversed at lower temperatures. Instead, DMSO was preferentially excluded from the <span class="hlt">ice</span> phase, resulting in an albumin <span class="hlt">concentration</span> in the freeze-<span class="hlt">concentrated</span> liquid phase that was lower than predicted. It is hypothesized that this was caused by the albumin in the freeze-<span class="hlt">concentrated</span> liquid getting adsorbed onto the <span class="hlt">ice</span> surface or becoming entrapped in the <span class="hlt">ice</span> phase. It was observed that, under certain freezing protocols, as much as 20% of the albumin in solutions with starting <span class="hlt">concentrations</span> of 32–53 mg/mL may be adsorbed onto the <span class="hlt">ice</span> interface or entrapped in the <span class="hlt">ice</span> phase. PMID:23742723</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23742723','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23742723"><span>In situ spectroscopic quantification of protein-<span class="hlt">ice</span> interactions.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Twomey, Alan; Less, Rebekah; Kurata, Kosaku; Takamatsu, Hiroshi; Aksan, Alptekin</p> <p>2013-07-03</p> <p>FTIR and confocal Raman microspectroscopy were used to measure interactions between albumin and <span class="hlt">ice</span> in situ during quasi-equilibrium freezing in dimethyl sulfoxide (DMSO) solutions. At temperatures of -4 and -6 °C, albumin was found to be preferentially excluded from the <span class="hlt">ice</span> phase during near-equilibrium freezing. This behavior reversed at lower temperatures. Instead, DMSO was preferentially excluded from the <span class="hlt">ice</span> phase, resulting in an albumin <span class="hlt">concentration</span> in the freeze-<span class="hlt">concentrated</span> liquid phase that was lower than predicted. It is hypothesized that this was caused by the albumin in the freeze-<span class="hlt">concentrated</span> liquid getting adsorbed onto the <span class="hlt">ice</span> surface or becoming entrapped in the <span class="hlt">ice</span> phase. It was observed that, under certain freezing protocols, as much as 20% of the albumin in solutions with starting <span class="hlt">concentrations</span> of 32-53 mg/mL may be adsorbed onto the <span class="hlt">ice</span> interface or entrapped in the <span class="hlt">ice</span> phase.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=PIA10906&hterms=ice+jet&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dice%2Bjet','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=PIA10906&hterms=ice+jet&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dice%2Bjet"><span>Disappearing <span class="hlt">Ice</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p></p> <p>2008-01-01</p> <p><p/> These images were acquired by NASA's Phoenix Mars Lander's Surface Stereo Imager on the 21st and 25th days of the mission, or Sols 20 and 24 (June 15 and 18, 2008). <p/> These images show sublimation of <span class="hlt">ice</span> in the trench informally called 'Dodo-Goldilocks' over the course of four days. <p/> In the lower left corner, lumps disappear, similar to the process of evaporation. <p/> The Phoenix Mission is led by the University of Arizona, Tucson, on behalf of NASA. Project management of the mission is by NASA's Jet Propulsion Laboratory, Pasadena, Calif. Spacecraft development is by Lockheed Martin Space Systems, Denver.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JGRE..121...21W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JGRE..121...21W"><span>Modeling of <span class="hlt">ice</span> pinnacle formation on Callisto</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>White, Oliver L.; Umurhan, Orkan M.; Moore, Jeffrey M.; Howard, Alan D.</p> <p>2016-01-01</p> <p>Callisto's pinnacle terrain has been interpreted to form through sublimation weathering of bedrock and subsequent deposition of the sublimated <span class="hlt">ice</span> in local cold traps on peaks and crater rims. To investigate how these processes are affected by environmental parameters, including solar illumination and the composition and <span class="hlt">concentration</span> of <span class="hlt">ices</span> in the crust, we employ the MARSSIM landform evolution model and advance its treatment of the physics that underlies the relevant processes. Both <span class="hlt">ice</span> sublimation and deposition are controlled by surface temperature, which we calculate based on energy contributions from both insolation and thermal reradiation from the surrounding landscape. We perform 4.5 Gyr duration simulations whereby we separately consider and model CO2 and H2O as the crustal <span class="hlt">ice</span> species. We find that sublimating a crustal content of 10% CO2 <span class="hlt">ice</span> (a reasonable but arbitrarily selected value) yields present-day landform degradation and regolith coverage that is comparable to what is observed on Callisto. In our H2O <span class="hlt">ice</span> simulations we reproduce the essential features of pinnacle <span class="hlt">ice</span> distribution at both the equator and midlatitudes. Our present nominal crustal H2O <span class="hlt">ice</span> content is 33%, which produces a maximum pinnacle <span class="hlt">ice</span> thickness of 64 m. Pinnacle height is likely limited by collapse or mass wasting of the <span class="hlt">ice</span> once it reaches a certain thickness.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1995EOSTr..76..477B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1995EOSTr..76..477B"><span>Interpreting natural climate signals in <span class="hlt">ice</span> cores</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bales, Roger C.; Wolff, Eric W.</p> <p></p> <p>Polar <span class="hlt">ice</span> caps preserve information about atmospheric composition over the past tens of thousands to hundreds of thousands of years. They contain a rich history of the Earth's volcanic activity, terrestrial dust sources, sea <span class="hlt">ice</span> location, terrestrial and marine biological activity, pollution, and atmospheric oxidation capacity. Differences in <span class="hlt">concentrations</span> of CO2 and CH4 in air extracted from <span class="hlt">ice</span> of various ages, changes in temperature inferred from d18O in <span class="hlt">ice</span>, and differences in the dust or acid loading of <span class="hlt">ice</span> are all used to deduce major changes in the global environment [Oeschger and Langway, 1989]. These temporal patterns of physical properties and chemical species that are recorded in <span class="hlt">ice</span> offer an opportunity to study the cause and effect relationships of environmental change.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016GeCoA.174..156F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016GeCoA.174..156F"><span>Potassium chloride-bearing <span class="hlt">ice</span> VII and <span class="hlt">ice</span> planet dynamics</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Frank, Mark R.; Scott, Henry P.; Aarestad, Elizabeth; Prakapenka, Vitali B.</p> <p>2016-02-01</p> <p>Accurate modeling of planetary interiors requires that the pressure-volume-temperature (PVT) properties of phases present within the body be well understood. The high-pressure polymorphs of H2O have been studied extensively due to the abundance of <span class="hlt">ice</span> phases in icy moons and, likely, vast number of extra-solar planetary bodies, with only select studies evaluating impurity-laden <span class="hlt">ices</span>. In this study, <span class="hlt">ice</span> formed from a 1.6 mol percent KCl-bearing aqueous solution was studied up to 32.89 ± 0.19 GPa and 625 K, and the incorporation of K+ and Cl- ionic impurities into the <span class="hlt">ice</span> VII structure was documented. The compression data at 295 K were fit with a third order Birch-Murnaghan equation of state and yielded a bulk modulus (KT0), its pressure derivative (KT0 ‧), and zero pressure volume (V0) of 24.7 ± 0.9 GPa, 4.44 ± 0.09, and 39.2 ± 0.2 Å3, respectively. The impurity-laden <span class="hlt">ice</span> was found to be 6-8% denser than <span class="hlt">ice</span> VII formed from pure H2O. Thermal expansion coefficients were also determined for several isothermal compression curves at elevated temperatures, and a PVT equation of state was obtained. The melting curve of <span class="hlt">ice</span> VII with incorporated K+ and Cl- was estimated by fitting experimental data up to 10.2 ± 0.4 GPa, where melting occurred at 625 K, to the Simon-Glatzel equation. The melting curve of this impurity-laden <span class="hlt">ice</span> is systematically depressed relative to that of pure H2O by approximately 45 K and 80 K at 4 and 11 GPa, respectively. A portion of the K+ and Cl- contained within the <span class="hlt">ice</span> VII structure was observed to exsolve with increasing temperature. This suggests that an internal differentiating process could <span class="hlt">concentrate</span> a K-rich phase deep within H2O-rich planets, and we speculate that this could supply an additional source of heat through the radioactive decay of 40K. Our data illustrate <span class="hlt">ice</span> VII can incorporate significant <span class="hlt">concentrations</span> of K+ and Cl- and increasing the possibility of deep-sourced and solute-rich plumes in moderate to large sized H2O</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27889953','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27889953"><span>Ecology under lake <span class="hlt">ice</span>.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Hampton, Stephanie E; Galloway, Aaron W E; Powers, Stephen M; Ozersky, Ted; Woo, Kara H; Batt, Ryan D; Labou, Stephanie G; O'Reilly, Catherine M; Sharma, Sapna; Lottig, Noah R; Stanley, Emily H; North, Rebecca L; Stockwell, Jason D; Adrian, Rita; Weyhenmeyer, Gesa A; Arvola, Lauri; Baulch, Helen M; Bertani, Isabella; Bowman, Larry L; Carey, Cayelan C; Catalan, Jordi; Colom-Montero, William; Domine, Leah M; Felip, Marisol; Granados, Ignacio; Gries, Corinna; Grossart, Hans-Peter; Haberman, Juta; Haldna, Marina; Hayden, Brian; Higgins, Scott N; Jolley, Jeff C; Kahilainen, Kimmo K; Kaup, Enn; Kehoe, Michael J; MacIntyre, Sally; Mackay, Anson W; Mariash, Heather L; McKay, Robert M; Nixdorf, Brigitte; Nõges, Peeter; Nõges, Tiina; Palmer, Michelle; Pierson, Don C; Post, David M; Pruett, Matthew J; Rautio, Milla; Read, Jordan S; Roberts, Sarah L; Rücker, Jacqueline; Sadro, Steven; Silow, Eugene A; Smith, Derek E; Sterner, Robert W; Swann, George E A; Timofeyev, Maxim A; Toro, Manuel; Twiss, Michael R; Vogt, Richard J; Watson, Susan B; Whiteford, Erika J; Xenopoulos, Marguerite A</p> <p>2017-01-01</p> <p>Winter conditions are rapidly changing in temperate ecosystems, particularly for those that experience periods of snow and <span class="hlt">ice</span> cover. Relatively little is known of winter ecology in these systems, due to a historical research focus on summer 'growing seasons'. We executed the first global quantitative synthesis on under-<span class="hlt">ice</span> lake ecology, including 36 abiotic and biotic variables from 42 research groups and 101 lakes, examining seasonal differences and connections as well as how seasonal differences vary with geophysical factors. Plankton were more abundant under <span class="hlt">ice</span> than expected; mean winter values were 43.2% of summer values for chlorophyll a, 15.8% of summer phytoplankton biovolume and 25.3% of summer zooplankton density. Dissolved nitrogen <span class="hlt">concentrations</span> were typically higher during winter, and these differences were exaggerated in smaller lakes. Lake size also influenced winter-summer patterns for dissolved organic carbon (DOC), with higher winter DOC in smaller lakes. At coarse levels of taxonomic aggregation, phytoplankton and zooplankton community composition showed few systematic differences between seasons, although literature suggests that seasonal differences are frequently lake-specific, species-specific, or occur at the level of functional group. Within the subset of lakes that had longer time series, winter influenced the subsequent summer for some nutrient variables and zooplankton biomass.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://pubs.er.usgs.gov/publication/70035046','USGSPUBS'); return false;" href="http://pubs.er.usgs.gov/publication/70035046"><span>A prelanding assessment of the <span class="hlt">ice</span> table depth and ground <span class="hlt">ice</span> characteristics in Martian permafrost at the Phoenix landing site</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Mellon, M.T.; Boynton, W.V.; Feldman, W.C.; Arvidson, R. E.; Titus, Joshua T.N.; Bandfield, L.; Putzig, N.E.; Sizemore, H.G.</p> <p>2009-01-01</p> <p>We review multiple estimates of the <span class="hlt">ice</span> table depth at potential Phoenix landing sites and consider the possible state and distribution of subsurface <span class="hlt">ice</span>. A two-layer model of <span class="hlt">ice</span>-rich material overlain by <span class="hlt">ice</span>-free material is consistent with both the observational and theoretical lines of evidence. Results indicate ground <span class="hlt">ice</span> to be shallow and ubiquitous, 2-6 cm below the surface. Undulations in the <span class="hlt">ice</span> table depth are expected because of the thermodynamic effects of rocks, slopes, and soil variations on the scale of the Phoenix Lander and within the digging area, which can be advantageous for analysis of both dry surficial soils and buried <span class="hlt">ice</span>-rich materials. The ground <span class="hlt">ice</span> at the <span class="hlt">ice</span> table to be sampled by the Phoenix Lander is expected to be geologically young because of recent climate oscillations. However, estimates of the ratio of soil to <span class="hlt">ice</span> in the <span class="hlt">ice</span>-rich subsurface layer suggest that that the <span class="hlt">ice</span> content exceeds the available pore space, which is difficult to reconcile with existing ground <span class="hlt">ice</span> stability and dynamics models. These high <span class="hlt">concentrations</span> of <span class="hlt">ice</span> may be the result of either the burial of surface snow during times of higher obliquity, initially high-porosity soils, or the migration of water along thin films. Measurement of the D/H ratio within the <span class="hlt">ice</span> at the <span class="hlt">ice</span> table and of the soil-to-<span class="hlt">ice</span> ratio, as well as imaging <span class="hlt">ice</span>-soil textures, will help determine if the <span class="hlt">ice</span> is indeed young and if the models of the effects of climate change on the ground <span class="hlt">ice</span> are reasonable. Copyright 2008 by the American Geophysical Union.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015GMDD....810305Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015GMDD....810305Y"><span>Improving the WRF model's simulation over sea <span class="hlt">ice</span> surface through coupling with a complex thermodynamic sea <span class="hlt">ice</span> model</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Yao, Y.; Huang, J.; Luo, Y.; Zhao, Z.</p> <p>2015-12-01</p> <p>Sea <span class="hlt">ice</span> plays an important role in the air-<span class="hlt">ice</span>-ocean interaction, but it is often represented simply in many regional atmospheric models. The Noah sea <span class="hlt">ice</span> model, which has been widely used in the Weather Research and Forecasting (WRF) model, exhibits cold bias in simulating the Arctic sea <span class="hlt">ice</span> 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 <span class="hlt">ice</span>. Compared with the Noah sea <span class="hlt">ice</span> model, the high-resolution thermodynamic snow and <span class="hlt">ice</span> model (HIGHTSI) has smaller bias in simulating the sea <span class="hlt">ice</span> 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 <span class="hlt">ice</span> from a complex thermodynamic sea <span class="hlt">ice</span> model. The cold bias in simulating the surface temperature over sea <span class="hlt">ice</span> 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 <span class="hlt">ice</span> thickness in the WRF model is presented. Consistent with previous research, prescribing the sea <span class="hlt">ice</span> 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 <span class="hlt">ice</span> <span class="hlt">concentration</span> and sea <span class="hlt">ice</span> thickness could mimic the large-scale spatial feature of sea <span class="hlt">ice</span> thickness. The potential application of a thermodynamic sea <span class="hlt">ice</span> model in predicting the change in sea <span class="hlt">ice</span> thickness in a RCM is limited by the lack of sea <span class="hlt">ice</span> dynamic processes in the model and the coarse assumption on the initial value of sea <span class="hlt">ice</span> thickness.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.A13I0299F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.A13I0299F"><span><span class="hlt">Ice</span> Nuclei Production in Volcanic Clouds</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Few, A. A.</p> <p>2012-12-01</p> <p>The paper [Durant et al., 2008] includes a review of research on <span class="hlt">ice</span> nucleation in explosive volcanic clouds in addition to reporting their own research on laboratory measurements focused on single-particle <span class="hlt">ice</span> nucleation. Their research as well as the research they reviewed were concerned with the freezing of supercooled water drops (250 to 260 K) by volcanic ash particles acting as <span class="hlt">ice</span> freezing nuclei. Among their conclusions are: Fine volcanic ash particles are very efficient <span class="hlt">ice</span> freezing nuclei. Volcanic clouds likely contain fine ash <span class="hlt">concentrations</span> 104 to 105 times greater than found in meteorological clouds. This overabundance of <span class="hlt">ice</span> nuclei will produce a cloud with many small <span class="hlt">ice</span> crystals that will not grow larger as they do in meteorological clouds because the cloud water content is widely distributed among the numerous small <span class="hlt">ice</span> crystals. The small <span class="hlt">ice</span> crystals have a small fall velocity, thus volcanic clouds are very stable. The small <span class="hlt">ice</span> crystals are easily lofted into the stratosphere transporting water and adsorbed trace gasses. In this paper we examine the mechanism for the production of the small <span class="hlt">ice</span> nuclei and develop a simple model for calculating the size of the <span class="hlt">ice</span> nuclei based upon the distribution of magma around imbedded bubbles. We also have acquired a volcanic bomb that exhibits bubble remnants on its entire surface. The naturally occurring fragments from the volcanic bomb reveal a size distribution consistent with that predicted by the simple model. Durant, A. J., R. A. Shaw, W. I. Rose, Y. Mi, and G. G. J. Ernst (2008), <span class="hlt">Ice</span> nucleation and overseeding of <span class="hlt">ice</span> in volcanic clouds, J. Geophys. Res., 113, D09206, doi:10.1029/2007JD009064.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016ClDy..tmp...27C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016ClDy..tmp...27C"><span>Intercomparison of the Arctic sea <span class="hlt">ice</span> cover in global ocean-sea <span class="hlt">ice</span> reanalyses from the ORA-IP project</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>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</p> <p>2016-01-01</p> <p>Ocean-sea <span class="hlt">ice</span> reanalyses are crucial for assessing the variability and recent trends in the Arctic sea <span class="hlt">ice</span> cover. This is especially true for sea <span class="hlt">ice</span> volume, as long-term and large scale sea <span class="hlt">ice</span> thickness observations are inexistent. Results from the Ocean ReAnalyses Intercomparison Project (ORA-IP) are presented, with a focus on Arctic sea <span class="hlt">ice</span> 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 <span class="hlt">ice</span> cover, including <span class="hlt">concentration</span>, thickness, velocity and snow. Amongst the 14 reanalyses studied here, 9 assimilate sea <span class="hlt">ice</span> <span class="hlt">concentration</span>, and none assimilate sea <span class="hlt">ice</span> thickness data. The comparison reveals an overall agreement in the reconstructed <span class="hlt">concentration</span> 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 <span class="hlt">ice</span> <span class="hlt">concentration</span>. However, some spread still exists amongst the reanalyses, due to a variety of factors. In particular, a large spread in sea <span class="hlt">ice</span> thickness is found within the ensemble of reanalyses, partially caused by the biases inherited from their sea <span class="hlt">ice</span> model components. Biases are also affected by the assimilation of sea <span class="hlt">ice</span> <span class="hlt">concentration</span> and the treatment of sea <span class="hlt">ice</span> thickness in the data assimilation process. An important outcome of this study is that the spatial distribution of <span class="hlt">ice</span> volume varies widely between products, with no reanalysis standing out as clearly superior as compared to altimetry estimates. The <span class="hlt">ice</span> thickness from systems without assimilation of sea <span class="hlt">ice</span> <span class="hlt">concentration</span> is not worse than that from systems constrained with sea <span class="hlt">ice</span> observations. An evaluation of the sea <span class="hlt">ice</span> velocity fields reveals that <span class="hlt">ice</span> drifts too fast in most systems. As an ensemble, the ORA-IP reanalyses capture trends in Arctic sea <span class="hlt">ice</span> area and extent</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011ACP....11...53J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011ACP....11...53J"><span>Manchester <span class="hlt">Ice</span> Nucleus Counter (MINC) measurements from the 2007 International workshop on Comparing <span class="hlt">Ice</span> nucleation Measuring Systems (ICIS-2007)</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Jones, H. M.; Flynn, M. J.; Demott, P. J.; Möhler, O.</p> <p>2011-01-01</p> <p>An <span class="hlt">ice</span> nucleus counter was developed and constructed to enable investigation of potential <span class="hlt">ice</span> nucleating materials. The Manchester <span class="hlt">Ice</span> Nucleus Chamber (MINC) is a <span class="hlt">concentric</span>-cylinder continuous flow diffusion chamber (CFDC). A full explanation of the MINC instrument is given here, along with first results and a comparison to an established instrument of similar design (Colorado State University CFDC) during sampling of common <span class="hlt">ice</span> nucleating aerosols at the 2007 International workshop on Comparing <span class="hlt">Ice</span> nucleation Measuring Systems (ICIS-2007). MINC and CSU-CFDC detected the onset of <span class="hlt">ice</span> nucleation under similar conditions of temperature and supersaturation for several different types of <span class="hlt">ice</span> nuclei. Comparisons of the ratio of <span class="hlt">ice</span> nuclei to total aerosol <span class="hlt">concentrations</span> as a function of supersaturation with respect to water (SSw) showed agreement within one order of magnitude. Possible reasons for differences between the two instruments relating to differences in their design are discussed, along with suggestions to future improvements to the current design.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010ACPD...1019277J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010ACPD...1019277J"><span>Manchester <span class="hlt">Ice</span> Nucleus Counter (MINC) measurements from the 2007 International workshop on Comparing <span class="hlt">Ice</span> nucleation Measuring Systems (ICIS-2007)</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Jones, H. M.; Flynn, M. J.; Demott, P. J.; Möhler, O.</p> <p>2010-08-01</p> <p>An <span class="hlt">ice</span> nucleus counter was developed and constructed to enable investigation of potential <span class="hlt">ice</span> nucleating materials. The Manchester <span class="hlt">Ice</span> Nucleus Chamber (MINC) is a <span class="hlt">concentric</span>-cylinder continuous flow diffusion chamber (CFDC). A full explanation of the MINC instrument is given here, along with first results and a comparison to an established instrument of similar design (Colorado State University CFDC) during sampling of common <span class="hlt">ice</span> nucleating aerosols at the 2007 International workshop on Comparing <span class="hlt">Ice</span> nucleation Measuring Systems (ICIS-2007). Both instruments detected the onset of <span class="hlt">ice</span> nucleation under similar conditions of temperature and supersaturation for several different types of <span class="hlt">ice</span> nuclei. Comparisons of the ratio of <span class="hlt">ice</span> nuclei to total aerosol <span class="hlt">concentrations</span> as a function of relative humidity (RH) showed agreement within one order of magnitude. Possible reasons for differences between the two instruments relating to differences in their design are discussed, along with suggestions to future improvements to the current design.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19830068474&hterms=elk&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Delk','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19830068474&hterms=elk&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Delk"><span>Contact <span class="hlt">ice</span> nucleation by submicron atmospheric aerosols</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Deshler, T.</p> <p>1982-01-01</p> <p>An apparatus designed to measure the <span class="hlt">concentrations</span> of submicron contact <span class="hlt">ice</span> nuclei is described. Here, natural forces transfer nuclei to supercooled sample drops suspended in an aerosol stream. Experimental measurements of the scavenging rate of the sample drops for several humidities and aerosol sizes are found to be in agreement with theory to within a factor of two. This fact, together with the statistical tests showing a difference between the data and control samples, is seen as indicating that a reliable measurement of the <span class="hlt">concentrations</span> of submicron contact <span class="hlt">ice</span> nuclei has been effected. A figure is included showing the <span class="hlt">ice</span> nucleus <span class="hlt">concentrations</span> as a function of temperature and assumed aerosol radius. For a 0.01 micron radius, the average is 1/liter at -15 C and 3/liter at -18 C. It is noted that the measurements are in fair agreement with <span class="hlt">ice</span> crystal <span class="hlt">concentrations</span> in stable winter clouds measured over Elk Mountain, WY (Vali et al., 1982).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006AGUFM.C21C1184F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006AGUFM.C21C1184F"><span>National <span class="hlt">Ice</span> Center Arctic Sea <span class="hlt">Ice</span> Charts and Climatologies In Gridded and GIS Format</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Fetterer, F.; Fowler, C.; Ballagh, L. M.; Street, T.; Meier, W. N.; Clemente-Colon, P.</p> <p>2006-12-01</p> <p>The U.S. National <span class="hlt">Ice</span> Center (NIC) is a joint Navy, NOAA, and Coast Guard sea <span class="hlt">ice</span> analysis and forecasting center. Since 1972, NIC has produced weekly Arctic and Antarctic sea <span class="hlt">ice</span> charts for operational uses including mission planning and safety of navigation. Arctic charts include information on sea <span class="hlt">ice</span> <span class="hlt">concentration</span> and edge position as well as (since about 1995) information on <span class="hlt">ice</span> type. The charts are constructed by analysts using available in situ, remotely sensed, and model data sources. Data sources and methods of chart construction have evolved since 1972 resulting in inconsistencies in the data record; a characteristic shared with most operational products. However the arctic-wide charts are the product of manual interpretation and data fusion, informed by the analyst's expertise and by ancillary products such as climatologies and <span class="hlt">ice</span> information shared by foreign operational <span class="hlt">ice</span> services. They are therefore often more accurate, especially since the addition of synthetic aperture radar to data sources in the mid 1990s, than are the passive microwave derived sea <span class="hlt">ice</span> data sets commonly used by researchers. This is especially true for <span class="hlt">ice</span> edge location because of its operational importance. NIC provides charts free of charge on their Web site. These charts are not easy for most researchers to use, however, because they are in a proprietary GIS format and the <span class="hlt">ice</span> <span class="hlt">concentration</span> and type information is encoded in polygon attributes that follow World Meteorological Organization coding conventions. We converted the charts to a gridded raster format (Equal Area Scalable Earth, or EASE-Grid) and created monthly climatology products (median, maximum, minimum, first quartile, and third quartile <span class="hlt">concentrations</span> as well as frequency of occurrence of <span class="hlt">ice</span> at any <span class="hlt">concentration</span> for 33 year, 10 year, and 5 year periods.) Charts and climatologies are available at the National Snow and <span class="hlt">Ice</span> Data Center. The products cover 1972-2004, and we plan to update the collection yearly.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=PIA01401&hterms=url&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Durl','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=PIA01401&hterms=url&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Durl"><span>Scrambled <span class="hlt">Ice</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p></p> <p>1998-01-01</p> <p>This complex area on the side of Europa which faces away from Jupiter shows several types of features which are formed by disruptions of Europa's icy crust. North is to the top of the image, taken by NASA's Galileo spacecraft, and the Sun illuminates the surface from the left. The prominent wide, dark bands are up to 20 kilometers (12 miles) wide and over 50 kilometers (30 miles) long. They are believed to have formed when Europa's icy crust fractured, separated and filled in with darker, 'dirtier' <span class="hlt">ice</span> or slush from below. A relatively rare type of feature on Europa is the 15-kilometer-diameter (9.3-mile) impact crater in the lower left corner. The small number of impact craters on Europa's surface is an indication of its relatively young age. A region of chaotic terrain south of this impact crater contains crustal plates which have broken apart and rafted into new positions. Some of these '<span class="hlt">ice</span> rafts' are nearly 1 kilometer (about half a mile) across. Other regions of chaotic terrain are visible and indicate heating and disruption of Europa's icy crust from below. The youngest features in this scene are the long, narrow cracks in the <span class="hlt">ice</span> which cut across all other features. One of these cracks is about 30 kilometers (18 miles) to the right of the impact crater and extends for hundreds of miles from the top to the bottom of the image.<p/>The image, centered near 23 degrees south latitude and 179 degrees longitude, covers an area about 240 by 215 kilometers (150 by 130 miles) across. The finest details that can be discerned in this picture are about 460 meters (500 yards) across. The image was taken as Galileo flew by Europa on March 29, 1998. The image was taken by the onboard solid state imaging system camera from an altitude of 23,000 kilometers (14,000 miles).<p/>The Jet Propulsion Laboratory, Pasadena, CA manages the Galileo mission for NASA's Office of Space Science, Washington, DC. JPL is an operating division of California Institute of Technology (Caltech</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016ISPAr41B8..513L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016ISPAr41B8..513L"><span>Study on the Retrieval of Snow Depth from FY3B/MWRI in the Atctic</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Li, Lele; Chen, Haihua; Guan, Lei</p> <p>2016-06-01</p> <p>temperatures. Given the high albedo and low thermal conductivity, snow is regarded as one of the key reasons for the amplification of the warming in polar regions. The distributions of sea <span class="hlt">ice</span> and snow depth are essential to the whole thermal conduction in the Arctic. This study focused on the retrieval of snow depth on sea <span class="hlt">ice</span> from brightness temperatures of the MicroWave Radiometer Imager (MWRI) onboard the FengYun (FY)-3B satellite during the period from December 1, 2010 to April 30, 2011. After cross calibrated to the Advanced Microwave Scanning Radiometer-EOS (<span class="hlt">AMSR-E</span>) Level 2A data, the MWRI brightness temperatures were applied to calculate the sea <span class="hlt">ice</span> <span class="hlt">concentrations</span> based on the Arctic Radiation and Turbulence Interaction Study Sea <span class="hlt">Ice</span> (ASI) algorithm. According to the proportional relationship between the snow depth and the surface scattering in 18.7 and 36.5 GHz, the snow depths were derived. In order to eliminate the influence of uncertainties in grain sizes of snow as well as sporadic weather effects, the seven-day averaged snow depths were calculated. Then the results were compared with the snow depths from the <span class="hlt">AMSR-E</span> Level 3 Sea <span class="hlt">Ice</span> products. The bias of differences between the MWRI and the <span class="hlt">AMSR-E</span> Level 3 products are ranged between -1.09 and -0.32 cm while the standard deviations and the correlation coefficients are ranged from 2.47 to 2.88 cm and from 0.78 to 0.90 for different months. As a result, it could be summarized that FY3B/MWRI showed a promising prospect in retrieving snow depth on sea <span class="hlt">ice</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA489793','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA489793"><span>Software Design Description for the Polar <span class="hlt">Ice</span> Prediction System (PIPS) Version 3.0</span></a></p> <p><a target="_blank" href="https://publicaccess.dtic.mil/psm/api/service/search/search">DTIC Science & Technology</a></p> <p></p> <p>2008-11-05</p> <p>THICKNESS AND TEMPERATURE FOR THE TWO EXTREMA IN SNOW DEPTH. MAXIMUM SNOW DEPTH IS CALCULATED BASED ON ARCHIMEDES ’ PRINCIPLE FOR THE GIVEN <span class="hlt">ICE</span>...have the <span class="hlt">ice</span> <span class="hlt">concentration</span> as a multiplicative factor to be consistent with the formal theory of free drift in low <span class="hlt">ice</span> <span class="hlt">concentration</span> areas. A...<span class="hlt">ice</span> thickness and temperature for the two extrema in snow depth. Maximum snow depth is calculated based on Archimedes ’ Principle for the given <span class="hlt">ice</span></p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19990064613&hterms=arctic+ice+melt&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Darctic%2Bice%2Bmelt','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19990064613&hterms=arctic+ice+melt&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Darctic%2Bice%2Bmelt"><span>Variability of Arctic Sea <span class="hlt">Ice</span> as Determined from Satellite Observations</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Parkinson, Claire L.</p> <p>1999-01-01</p> <p>The compiled, quality-controlled satellite multichannel passive-microwave record of polar sea <span class="hlt">ice</span> now spans over 18 years, from November 1978 through December 1996, and is revealing considerable information about the Arctic sea <span class="hlt">ice</span> cover and its variability. The information includes data on <span class="hlt">ice</span> <span class="hlt">concentrations</span> (percent areal coverages of <span class="hlt">ice</span>), <span class="hlt">ice</span> extents, <span class="hlt">ice</span> melt, <span class="hlt">ice</span> velocities, the seasonal cycle of the <span class="hlt">ice</span>, the interannual variability of the <span class="hlt">ice</span>, the frequency of <span class="hlt">ice</span> coverage, and the length of the sea <span class="hlt">ice</span> season. The data reveal marked regional and interannual variabilities, as well as some statistically significant trends. For the north polar <span class="hlt">ice</span> cover as a whole, maximum <span class="hlt">ice</span> extents varied over a range of 14,700,000 - 15,900,000 sq km, while individual regions experienced much greater percent variations, for instance, with the Greenland Sea having a range of 740,000 - 1,110,000 sq km in its yearly maximum <span class="hlt">ice</span> coverage. In spite of the large variations from year to year and region to region, overall the Arctic <span class="hlt">ice</span> extents showed a statistically significant, 2.80% / decade negative trend over the 18.2-year period. <span class="hlt">Ice</span> season lengths, which vary from only a few weeks near the <span class="hlt">ice</span> margins to the full year in the large region of perennial <span class="hlt">ice</span> coverage, also experienced interannual variability, along with spatially coherent overall trends. Linear least squares trends show the sea <span class="hlt">ice</span> season to have lengthened in much of the Bering Sea, Baffin Bay, the Davis Strait, and the Labrador Sea, but to have shortened over a much larger area, including the Sea of Okhotsk, the Greenland Sea, the Barents Sea, and the southeastern Arctic.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016PApGe.173.3141K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016PApGe.173.3141K"><span>Importance of Chemical Composition of <span class="hlt">Ice</span> Nuclei on the Formation of Arctic <span class="hlt">Ice</span> Clouds</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Keita, Setigui Aboubacar; Girard, Eric</p> <p>2016-09-01</p> <p><span class="hlt">Ice</span> clouds play an important role in the Arctic weather and climate system but interactions between aerosols, clouds and radiation remain poorly understood. Consequently, it is essential to fully understand their properties and especially their formation process. Extensive measurements from ground-based sites and satellite remote sensing reveal the existence of two Types of <span class="hlt">Ice</span> Clouds (TICs) in the Arctic during the polar night and early spring. TICs-1 are composed by non-precipitating small (radar-unseen) <span class="hlt">ice</span> crystals of less than 30 μm in diameter. The second type, TICs-2, are detected by radar and are characterized by a low <span class="hlt">concentration</span> of large precipitating <span class="hlt">ice</span> crystals <span class="hlt">ice</span> crystals (>30 μm). To explain these differences, we hypothesized that TIC-2 formation is linked to the acidification of aerosols, which inhibits the <span class="hlt">ice</span> nucleating properties of <span class="hlt">ice</span> nuclei (IN). As a result, the IN <span class="hlt">concentration</span> is reduced in these regions, resulting to a lower <span class="hlt">concentration</span> of larger <span class="hlt">ice</span> crystals. Water vapor available for deposition being the same, these crystals reach a larger size. Current weather and climate models cannot simulate these different types of <span class="hlt">ice</span> clouds. This problem is partly due to the parameterizations implemented for <span class="hlt">ice</span> nucleation. Over the past 10 years, several parameterizations of homogeneous and heterogeneous <span class="hlt">ice</span> nucleation on IN of different chemical compositions have been developed. These parameterizations are based on two approaches: stochastic (that is nucleation is a probabilistic process, which is time dependent) and singular (that is nucleation occurs at fixed conditions of temperature and humidity and time-independent). The best approach remains unclear. This research aims to better understand the formation process of Arctic TICs using recently developed <span class="hlt">ice</span> nucleation parameterizations. For this purpose, we have implemented these <span class="hlt">ice</span> nucleation parameterizations into the Limited Area version of the Global Multiscale Environmental Model</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li class="active"><span>19</span></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_19 --> <div id="page_20" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li class="active"><span>20</span></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="381"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JGRC..121.6009H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JGRC..121.6009H"><span>Large flux of iron from the Amery <span class="hlt">Ice</span> Shelf marine <span class="hlt">ice</span> to Prydz Bay, East Antarctica</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Herraiz-Borreguero, L.; Lannuzel, D.; van der Merwe, P.; Treverrow, A.; Pedro, J. B.</p> <p>2016-08-01</p> <p>The Antarctic continental shelf supports a high level of marine primary productivity and is a globally important carbon dioxide (CO2) sink through the photosynthetic fixation of CO2 via the biological pump. Sustaining such high productivity requires a large supply of the essential micronutrient iron (Fe); however, the pathways for Fe delivery to these zones vary spatially and temporally. Our study is the first to report a previously unquantified source of <span class="hlt">concentrated</span> bioavailable Fe to Antarctic surface waters. We hypothesize that Fe derived from subglacial processes is delivered to euphotic waters through the accretion (Fe storage) and subsequent melting (Fe release) of a marine-accreted layer of <span class="hlt">ice</span> at the base of the Amery <span class="hlt">Ice</span> Shelf (AIS). Using satellite-derived Chlorophyll-a data, we show that the soluble Fe supplied by the melting of the marine <span class="hlt">ice</span> layer is an order of magnitude larger than the required Fe necessary to sustain the large annual phytoplankton bloom in Prydz Bay. Our finding of high <span class="hlt">concentrations</span> of Fe in AIS marine <span class="hlt">ice</span> and recent data on increasing rates of <span class="hlt">ice</span> shelf basal melt in many of Antarctica's <span class="hlt">ice</span> shelves should encourage further research into glacial and marine sediment transport beneath <span class="hlt">ice</span> shelves and their sensitivity to current changes in basal melt. Currently, the distribution, volume, and Fe <span class="hlt">concentration</span> of Antarctic marine <span class="hlt">ice</span> is poorly constrained. This uncertainty, combined with variable forecasts of increased rates of <span class="hlt">ice</span> shelf basal melt, limits our ability to predict future Fe supply to Antarctic coastal waters.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/scitech/biblio/484365','SCIGOV-STC'); return false;" href="https://www.osti.gov/scitech/biblio/484365"><span>Modeling of Antarctic sea <span class="hlt">ice</span> in a general circulation model</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Wu, Xingren; Budd, W.F.; Simmonds, I.</p> <p>1997-04-01</p> <p>A dynamic-thermodynamic sea <span class="hlt">ice</span> model is developed and coupled with the Melbourne University general circulation model to simulate the seasonal cycle of the Antarctic sea <span class="hlt">ice</span> distributions The model is efficient, rapid to compute, and useful for a range of climate studies. The thermodynamic part of the sea <span class="hlt">ice</span> model is similar to that developed by Parkinson and Washington, the dynamics contain a simplified <span class="hlt">ice</span> rheology that resists compression. The thermodynamics is based on energy conservation at the top surface of the <span class="hlt">ice</span>/snow, the <span class="hlt">ice</span>/water interface, and the open water area to determine the <span class="hlt">ice</span> formation, accretion, and ablation. A lead parameterization is introduced with an effective partitioning scheme for freezing between and under the <span class="hlt">ice</span> floes. The dynamic calculation determines the motion of <span class="hlt">ice</span>, which is forced with the atmospheric wind, taking account of <span class="hlt">ice</span> resistance and rafting. The simulated sea <span class="hlt">ice</span> distribution compares reasonably well with observations. The seasonal cycle of <span class="hlt">ice</span> extent is well simulated in phase as well as in magnitude. Simulated sea <span class="hlt">ice</span> thickness and <span class="hlt">concentration</span> 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 <span class="hlt">ice</span> distribution. 64 refs., 15 figs., 2 tabs.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/3386720','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/3386720"><span>Inhibition of bacterial <span class="hlt">ice</span> nucleators by fish antifreeze glycoproteins.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Parody-Morreale, A; Murphy, K P; Di Cera, E; Fall, R; DeVries, A L; Gill, S J</p> <p>1988-06-23</p> <p>Certain bacteria promote the formation of <span class="hlt">ice</span> in super-cooled water by means of <span class="hlt">ice</span> nucleators which contain a unique protein associated with the cell membrane. <span class="hlt">Ice</span> nucleators in general are believed to act by mimicking the structure of an <span class="hlt">ice</span> crystal surface, thus imposing an <span class="hlt">ice</span>-like arrangement on the water molecules in contact with the nucleating surface and lowering the energy necessary for the initiation of <span class="hlt">ice</span> formation. Quantitative investigation of the bacterial <span class="hlt">ice</span>-nucleating process has recently been made possible by the discovery of certain bacteria that shed stable membrane vesicles with <span class="hlt">ice</span> nucleating activity. The opposite effect, inhibition of <span class="hlt">ice</span> formation, has been described for a group of glycoproteins found in different fish and insect species. This group of substances, termed antifreeze glycoproteins (AFGPs), promotes the supercooling of water with no appreciable effect on the equilibrium freezing point or melting temperature. Substantial evidence now indicates that AFGPs act by binding to a growing <span class="hlt">ice</span> crystal and slowing crystal growth. As the <span class="hlt">ice</span>-nucleating protein surface is believed to have a structure similar to an embryonic <span class="hlt">ice</span> crystal, AFGPs might be predicted to interact directly with a bacterial <span class="hlt">ice</span>-nucleating site. We report here that AFGPs from the antarctic fish Dissostichus mawsoni inhibit the <span class="hlt">ice</span>-nucleating activity of membrane vesicles from the bacterium Erwinia herbicola. The inhibition effect shows saturation at high <span class="hlt">concentration</span> of AFGP and conforms to a simple binding reaction between the AFGP and the nucleation centre.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2005PhDT........43L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2005PhDT........43L"><span>Modelling water isotopes in polar <span class="hlt">ice</span> sheets</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lhomme, Nicolas</p> <p>2005-07-01</p> <p><span class="hlt">Concentrations</span> of water isotopes in marine sediments and <span class="hlt">ice</span> cores are a key indicator for estimating global and regional fluctuations of past temperatures. Interpreting these <span class="hlt">concentrations</span> requires an understanding of the storage capacity and exchanges among the ocean, atmosphere and cryosphere as well as an understanding of the dynamical behaviour of these reservoirs. The contribution of the latter remains poorly established because of the paucity of deep <span class="hlt">ice</span> cores in Greenland and Antarctica and the difficulty of interpreting these cores. To obtain the water isotope composition of polar <span class="hlt">ice</span> sheets and gain an understanding of their stratigraphy, I develop a tracer transport method first proposed by Clarke and Marshall (2002) and significantly improve it by introducing an interpolation technique that accounts for the particular age-depth relationship of <span class="hlt">ice</span> sheets. I combine the tracers with numerical models of <span class="hlt">ice</span> dynamics to predict the fine layering of polar <span class="hlt">ice</span> masses such that it is locally validated at <span class="hlt">ice</span> core sites, hence setting a new method to constrain reconstructions of <span class="hlt">ice</span> sheets' climatic and dynamic histories. This framework is first applied and tested with the UBC <span class="hlt">Ice</span> Sheet Model of Marshall and Clarke (1997). I predict the three-dimensional time-evolving stratigraphy of the Greenland <span class="hlt">Ice</span> Sheet and use the <span class="hlt">ice</span> core records predicted at GRIP, Dye 3 and Camp Century to better determine the minimal <span class="hlt">ice</span> extent during the Eemian, 127 kyr ago, when the Earth's climate was somewhat similar to the present. I suggest that 3.5--4.5 m of sea level rise could be attributed to melting in Greenland. Tracers are also applied to Antarctica with the LGGE <span class="hlt">Ice</span> Sheet Model of Ritz et al. (2001). The three-dimensional model is compared to simple flow models at the deep <span class="hlt">ice</span> core sites of Dome C, Vostok and Dome Fuji to test the hypotheses on depositional and dynamical conditions used for interpreting <span class="hlt">ice</span> cores. These studies lead to a well-constrained stratigraphic</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19970017671','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19970017671"><span>Modern Airfoil <span class="hlt">Ice</span> Accretions</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Addy, Harold E., Jr.; Potapczuk, Mark G.; Sheldon, David W.</p> <p>1997-01-01</p> <p>This report presents results from the first <span class="hlt">icing</span> tests performed in the Modem Airfoils program. Two airfoils have been subjected to <span class="hlt">icing</span> tests in the NASA Lewis <span class="hlt">Icing</span> Research Tunnel (IRT). Both airfoils were two dimensional airfoils; one was representative of a commercial transport airfoil while the other was representative of a business jet airfoil. The <span class="hlt">icing</span> test conditions were selected from the FAR Appendix C envelopes. Effects on aerodynamic performance are presented including the effects of varying amounts of glaze <span class="hlt">ice</span> as well as the effects of approximately the same amounts of glaze, mixed, and rime <span class="hlt">ice</span>. Actual <span class="hlt">ice</span> shapes obtained in these tests are also presented for these cases. In addition, comparisons are shown between <span class="hlt">ice</span> shapes from the tests and <span class="hlt">ice</span> shapes predicted by the computer code, LEWICE for similar conditions. Significant results from the tests are that relatively small amounts of <span class="hlt">ice</span> can have nearly as much effect on airfoil lift coefficient as much greater amounts of <span class="hlt">ice</span> and that glaze <span class="hlt">ice</span> usually has a more detrimental effect than either rime or mixed <span class="hlt">ice</span>. LEWICE predictions of <span class="hlt">ice</span> shapes, in general, compared reasonably well with <span class="hlt">ice</span> shapes obtained in the IRT, although differences in details of the <span class="hlt">ice</span> shapes were observed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19870053374&hterms=sonar&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dsonar','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19870053374&hterms=sonar&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dsonar"><span>Remote sensing as a research tool. [sea <span class="hlt">ice</span> surveillance from aircraft and spacecraft</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Carsey, F. D.; Zwally, H. J.</p> <p>1986-01-01</p> <p>The application of aircraft and spacecraft remote sensing techniques to sea <span class="hlt">ice</span> surveillance is evaluated. The effects of <span class="hlt">ice</span> in the air-sea-<span class="hlt">ice</span> system are examined. The measurement principles and characteristics of remote sensing methods for aircraft and spacecraft surveillance of sea <span class="hlt">ice</span> are described. Consideration is given to ambient visible light, IR, passive microwave, active microwave, and laser altimeter and sonar systems. The applications of these systems to sea <span class="hlt">ice</span> surveillance are discussed and examples are provided. Particular attention is placed on the use of microwave data and the relation between <span class="hlt">ice</span> thickness and sea <span class="hlt">ice</span> interactions. It is noted that spacecraft and aircraft sensing techniques can successfully measure snow cover; <span class="hlt">ice</span> thickness; <span class="hlt">ice</span> type; <span class="hlt">ice</span> <span class="hlt">concentration</span>; <span class="hlt">ice</span> velocity field; ocean temperature; surface wind vector field; and air, snow, and <span class="hlt">ice</span> surface temperatures.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=64923&keyword=LAKE+AND+ICE&actType=&TIMSType=+&TIMSSubTypeID=&DEID=&epaNumber=&ntisID=&archiveStatus=Both&ombCat=Any&dateBeginCreated=&dateEndCreated=&dateBeginPublishedPresented=&dateEndPublishedPresented=&dateBeginUpdated=&dateEndUpdated=&dateBeginCompleted=&dateEndCompleted=&personID=&role=Any&journalID=&publisherID=&sortBy=revisionDate&count=50&CFID=90758774&CFTOKEN=92528598','EPA-EIMS'); return false;" href="http://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=64923&keyword=LAKE+AND+ICE&actType=&TIMSType=+&TIMSSubTypeID=&DEID=&epaNumber=&ntisID=&archiveStatus=Both&ombCat=Any&dateBeginCreated=&dateEndCreated=&dateBeginPublishedPresented=&dateEndPublishedPresented=&dateBeginUpdated=&dateEndUpdated=&dateBeginCompleted=&dateEndCompleted=&personID=&role=Any&journalID=&publisherID=&sortBy=revisionDate&count=50&CFID=90758774&CFTOKEN=92528598"><span>CARBON TRACE GASES IN LAKE AND BEAVER POND <span class="hlt">ICE</span> NEAR THOMPSON, MANITOBA, CANADA</span></a></p> <p><a target="_blank" href="http://oaspub.epa.gov/eims/query.page">EPA Science Inventory</a></p> <p></p> <p></p> <p><span class="hlt">Concentrations</span> of CO2, CO, and CH4 were measured in beaver pond and lake <span class="hlt">ice</span> in April 1996 near Thompson, Manitoba to derive information on possible impacts of <span class="hlt">ice</span> melting on corresponding atmospheric trace gas <span class="hlt">concentrations</span>. CH4 <span class="hlt">concentrations</span> in beaver pond and lake <span class="hlt">ice</span> ranged...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19950008483','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19950008483"><span><span class="hlt">Icing</span>: Accretion, Detection, Protection</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Reinmann, John J.</p> <p>1994-01-01</p> <p>The global aircraft industry and its regulatory agencies are currently involved in three major <span class="hlt">icing</span> efforts: ground <span class="hlt">icing</span>; advanced technologies for in-flight <span class="hlt">icing</span>; and tailplane <span class="hlt">icing</span>. These three major <span class="hlt">icing</span> topics correspondingly support the three major segments of any aircraft flight profile: takeoff; cruise and hold; and approach and land. This lecture addressess these three topics in the same sequence as they appear in flight, starting with ground deicing, followed by advanced technologies for in-flight <span class="hlt">ice</span> protection, and ending with tailplane <span class="hlt">icing</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.osti.gov/scitech/servlets/purl/106795','SCIGOV-STC'); return false;" href="http://www.osti.gov/scitech/servlets/purl/106795"><span>Self-releasing submerged <span class="hlt">ice</span> maker</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Stewart, W.E. Jr.; Greer, M.E.; Stickler, L.A.</p> <p>1989-03-01</p> <p>This study reports the results of a series of experiments which investigated a thermal storage technology whereby slush <span class="hlt">ice</span> is grown on a submerged cold surface and the resultant growth of slush <span class="hlt">ice</span> released without auxiliary thermal or mechanical means. The process investigated consists of growing slush <span class="hlt">ice</span> from an electrolyte solution of low molarity. The cold surface (substrate) upon which the slush <span class="hlt">ice</span> forms is submerged in the bulk solution. As the buoyancy force on the <span class="hlt">ice</span> crystals exceeds the adhesion to the cold surface, the slush <span class="hlt">ice</span> is forced from the substrate and floats away, to the top of the solution. The results of this study reveal the relative insensitivity of the growth rate of <span class="hlt">ice</span> crystals to solution initial bulk <span class="hlt">concentration</span> over the range of values tested and to <span class="hlt">concentration</span> of electrolyte during accumulation of <span class="hlt">ice</span> crystals. The critical parameter appears to be substrate temperature, which generally cannot be less than approximately 2{degrees}C below the freezing point temperature of the solution, as apparent adhesion increases rapidly with decreasing substrate temperature.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=PIA04406&hterms=Cloud+technology&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3DCloud%2Btechnology','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=PIA04406&hterms=Cloud+technology&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3DCloud%2Btechnology"><span><span class="hlt">Ice</span> Clouds</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p></p> <p>2003-01-01</p> <p><p/> [figure removed for brevity, see original site] <p/>Heavy water <span class="hlt">ice</span> clouds almost completely obscure the surface in Vastitas Borealis.<p/>Note: this THEMIS visual image has not been radiometrically nor geometrically calibrated for this preliminary release. An empirical correction has been performed to remove instrumental effects. A linear shift has been applied in the cross-track and down-track direction to approximate spacecraft and planetary motion. Fully calibrated and geometrically projected images will be released through the Planetary Data System in accordance with Project policies at a later time.<p/>NASA's Jet Propulsion Laboratory manages the 2001 Mars Odyssey mission for NASA's Office of Space Science, Washington, D.C. The Thermal Emission Imaging System (THEMIS) was developed by Arizona State University, Tempe, in collaboration with Raytheon Santa Barbara Remote Sensing. The THEMIS investigation is led by Dr. Philip Christensen at Arizona State University. Lockheed Martin Astronautics, Denver, is the prime contractor for the Odyssey project, and developed and built the orbiter. Mission operations are conducted jointly from Lockheed Martin and from JPL, a division of the California Institute of Technology in Pasadena.<p/>Image information: VIS instrument. Latitude 69.5, Longitude 283.6 East (76.4 West). 19 meter/pixel resolution.<p/></p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014E%26ES...17a2115H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014E%26ES...17a2115H"><span>Sea <span class="hlt">ice</span> classification using dual polarization SAR data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Huiying, Liu; Huadong, Guo; Lu, Zhang</p> <p>2014-03-01</p> <p>Sea <span class="hlt">ice</span> is an indicator of climate change and also a threat to the navigation security of ships. Polarimetric SAR images are useful in the sea <span class="hlt">ice</span> detection and classification. In this paper, backscattering coefficients and texture features derived from dual polarization SAR images are used for sea <span class="hlt">ice</span> classification. Firstly, the HH image is recalculated based on the angular dependences of sea <span class="hlt">ice</span> types. Then the effective gray level co-occurrence matrix (GLCM) texture features are selected for the support vector machine (SVM) classification. In the end, because sea <span class="hlt">ice</span> <span class="hlt">concentration</span> can provide a better separation of pancake <span class="hlt">ice</span> from old <span class="hlt">ice</span>, it is used to improve the SVM result. This method provides a good classification result, compared with the sea <span class="hlt">ice</span> chart from CIS.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.osti.gov/scitech/servlets/purl/6091444','SCIGOV-STC'); return false;" href="http://www.osti.gov/scitech/servlets/purl/6091444"><span>Arctic <span class="hlt">ice</span> islands</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Sackinger, W.M.; Jeffries, M.O.; Lu, M.C.; Li, F.C.</p> <p>1988-01-01</p> <p>The development of offshore oil and gas resources in the Arctic waters of Alaska requires offshore structures which successfully resist the lateral forces due to moving, drifting <span class="hlt">ice</span>. <span class="hlt">Ice</span> islands are floating, a tabular icebergs, up to 60 meters thick, of solid <span class="hlt">ice</span> throughout their thickness. The <span class="hlt">ice</span> islands are thus regarded as the strongest <span class="hlt">ice</span> features in the Arctic; fixed offshore structures which can directly withstand the impact of <span class="hlt">ice</span> islands are possible but in some locations may be so expensive as to make oilfield development uneconomic. The resolution of the <span class="hlt">ice</span> island problem requires two research steps: (1) calculation of the probability of interaction between an <span class="hlt">ice</span> island and an offshore structure in a given region; and (2) if the probability if sufficiently large, then the study of possible interactions between <span class="hlt">ice</span> island and structure, to discover mitigative measures to deal with the moving <span class="hlt">ice</span> island. The <span class="hlt">ice</span> island research conducted during the 1983-1988 interval, which is summarized in this report, was concerned with the first step. Monte Carlo simulations of <span class="hlt">ice</span> island generation and movement suggest that <span class="hlt">ice</span> island lifetimes range from 0 to 70 years, and that 85% of the lifetimes are less then 35 years. The simulation shows a mean value of 18 <span class="hlt">ice</span> islands present at any time in the Arctic Ocean, with a 90% probability of less than 30 <span class="hlt">ice</span> islands. At this time, approximately 34 <span class="hlt">ice</span> islands are known, from observations, to exist in the Arctic Ocean, not including the 10-meter thick class of <span class="hlt">ice</span> islands. Return interval plots from the simulation show that coastal zones of the Beaufort and Chukchi Seas, already leased for oil development, have <span class="hlt">ice</span> island recurrences of 10 to 100 years. This implies that the <span class="hlt">ice</span> island hazard must be considered thoroughly, and appropriate safety measures adopted, when offshore oil production plans are formulated for the Alaskan Arctic offshore. 132 refs., 161 figs., 17 tabs.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/19727513','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/19727513"><span>Homogeneous <span class="hlt">ice</span> freezing temperatures and <span class="hlt">ice</span> nucleation rates of aqueous ammonium sulfate and aqueous levoglucosan particles for relevant atmospheric conditions.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Knopf, Daniel Alexander; Lopez, Miguel David</p> <p>2009-09-28</p> <p>Homogeneous <span class="hlt">ice</span> nucleation from micrometre-sized aqueous (NH4)2SO4 and aqueous levoglucosan particles is studied employing the optical microscope technique. A new experimental method is introduced that allows us to control the initial water activity of the aqueous droplets. Homogeneous <span class="hlt">ice</span> freezing temperatures and <span class="hlt">ice</span> melting temperatures of these aqueous solution droplets, 10 to 80 microm in diameter, are determined. Homogeneous <span class="hlt">ice</span> nucleation from aqueous (NH4)2SO4 particles 5-39 wt% in <span class="hlt">concentration</span> and aqueous levoglucosan particles with initial water activities of 0.85-0.99 yield upper limits of the homogeneous <span class="hlt">ice</span> nucleation rate coefficients of up to 1x10(10) cm(-3) s(-1). The experimentally derived homogeneous <span class="hlt">ice</span> freezing temperatures and upper limits of the homogeneous <span class="hlt">ice</span> nucleation rate coefficients are compared with corresponding predictions of the water-activity-based <span class="hlt">ice</span> nucleation theory [T. Koop, B. P. Luo, A. Tsias and T. Peter, Nature, 2000, 406, 611]. It is found that the water-activity-based <span class="hlt">ice</span> nucleation theory can capture the experimentally derived <span class="hlt">ice</span> freezing temperatures and homogeneous <span class="hlt">ice</span> nucleation rate coefficients of the aqueous (NH4)2SO4 and aqueous levoglucosan particles. However, the level of agreement between experimentally derived and predicted values, in particular for homogeneous <span class="hlt">ice</span> nucleation rate coefficients, crucially depends on the extrapolation method to obtain water activities at corresponding freezing temperatures. It is suggested that the combination of experimentally derived <span class="hlt">ice</span> freezing temperatures and homogeneous <span class="hlt">ice</span> nucleation rate coefficients can serve as a better validation of the water-activity-based <span class="hlt">ice</span> nucleation theory than when compared to the observation of homogeneous <span class="hlt">ice</span> freezing temperatures alone. The atmospheric implications with regard to the application of the water-activity-based <span class="hlt">ice</span> nucleation theory and derivation of maximum <span class="hlt">ice</span> particle production rates are briefly discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20000038177&hterms=arctic+temperature&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Darctic%2Btemperature','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20000038177&hterms=arctic+temperature&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Darctic%2Btemperature"><span>A Microwave Technique for Mapping <span class="hlt">Ice</span> Temperature in the Arctic Seasonal Sea <span class="hlt">Ice</span> Zone</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>St.Germain, Karen M.; Cavalieri, Donald J.</p> <p>1997-01-01</p> <p>A technique for deriving <span class="hlt">ice</span> temperature in the Arctic seasonal sea <span class="hlt">ice</span> zone from passive microwave radiances has been developed. The algorithm operates on brightness temperatures derived from the Special Sensor Microwave/Imager (SSM/I) and uses <span class="hlt">ice</span> <span class="hlt">concentration</span> and type from a previously developed thin <span class="hlt">ice</span> algorithm to estimate the surface emissivity. Comparisons of the microwave derived temperatures with estimates derived from infrared imagery of the Bering Strait yield a correlation coefficient of 0.93 and an RMS difference of 2.1 K when coastal and cloud contaminated pixels are removed. SSM/I temperatures were also compared with a time series of air temperature observations from Gambell on St. Lawrence Island and from Point Barrow, AK weather stations. These comparisons indicate that the relationship between the air temperature and the <span class="hlt">ice</span> temperature depends on <span class="hlt">ice</span> type.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20020039858&hterms=Cloud+chamber&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3DCloud%2Bchamber','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20020039858&hterms=Cloud+chamber&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3DCloud%2Bchamber"><span>SUCCESS Evidence for Cirrus Cloud <span class="hlt">Ice</span> Nucleation Mechanisms</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Jensen, Eric; Gore, Warren J. Y. (Technical Monitor)</p> <p>1997-01-01</p> <p>During the SUCCESS mission, several measurements were made which should improve our understanding of <span class="hlt">ice</span> nucleation processes in cirrus clouds. Temperature and water vapor <span class="hlt">concentration</span> were made with a variety of instruments on the NASA DC-8. These observations should provide accurate upper tropospheric humidities. In particular, we will evaluate what humidities are required for <span class="hlt">ice</span> nucleation. Preliminary results suggest that substantial supersaturations frequently exist in the upper troposphere. The leading-edge region of wave-clouds (where <span class="hlt">ice</span> nucleation occurs) was sampled extensively at temperatures near -40 and -60C. These observations should give precise information about conditions required for <span class="hlt">ice</span> nucleation. In addition, we will relate the observed aerosol composition and size distributions to the <span class="hlt">ice</span> formation observed to evaluate the role of soot or mineral particles on <span class="hlt">ice</span> nucleation. As an alternative technique for determining what particles act as <span class="hlt">ice</span> nuclei, numerous samples of aerosols inside <span class="hlt">ice</span> crystals were taken. In some cases, large numbers of aerosols were detected in each crystal, indicating that efficient scavenging occurred. Analysis of aerosols in <span class="hlt">ice</span> crystals when only one particle per crystal was detected should help with the <span class="hlt">ice</span> nucleation issue. Direct measurements of the <span class="hlt">ice</span> nucleating activity of ambient aerosols drawn into airborne cloud chambers were also made. Finally, measurements of aerosols and <span class="hlt">ice</span> crystals in contrails should indicate whether aircraft exhaust soot particles are effective <span class="hlt">ice</span> nuclei.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24015900','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24015900"><span>Sea <span class="hlt">ice</span> ecosystems.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Arrigo, Kevin R</p> <p>2014-01-01</p> <p>Polar sea <span class="hlt">ice</span> is one of the largest ecosystems on Earth. The liquid brine fraction of the <span class="hlt">ice</span> 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 <span class="hlt">ice</span> algal communities, generally dominated by diatoms, live at the <span class="hlt">ice</span>/water interface and in recently flooded surface and interior layers, especially during spring, when temperatures begin to rise. Although protists dominate the sea <span class="hlt">ice</span> biomass, heterotrophic bacteria are also abundant. The sea <span class="hlt">ice</span> ecosystem provides food for a host of animals, with crustaceans being the most conspicuous. Uneaten organic matter from the <span class="hlt">ice</span> sinks through the water column and feeds benthic ecosystems. As sea <span class="hlt">ice</span> extent declines, <span class="hlt">ice</span> algae likely contribute a shrinking fraction of the total amount of organic matter produced in polar waters.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2005PrAeS..41..323B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2005PrAeS..41..323B"><span><span class="hlt">Iced</span>-airfoil aerodynamics</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bragg, M. B.; Broeren, A. P.; Blumenthal, L. A.</p> <p>2005-07-01</p> <p>Past research on airfoil aerodynamics in <span class="hlt">icing</span> are reviewed. This review emphasizes the time period after the 1978 NASA Lewis workshop that initiated the modern <span class="hlt">icing</span> research program at NASA and the current period after the 1994 ATR accident where aerodynamics research has been more aircraft safety focused. Research pre-1978 is also briefly reviewed. Following this review, our current knowledge of <span class="hlt">iced</span> airfoil aerodynamics is presented from a flowfield-physics perspective. This article identifies four classes of <span class="hlt">ice</span> accretions: roughness, horn <span class="hlt">ice</span>, streamwise <span class="hlt">ice</span>, and spanwise-ridge <span class="hlt">ice</span>. For each class, the key flowfield features such as flowfield separation and reattachment are discussed and how these contribute to the known aerodynamic effects of these <span class="hlt">ice</span> shapes. Finally Reynolds number and Mach number effects on <span class="hlt">iced</span>-airfoil aerodynamics are summarized.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016PNAS..113E4594M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016PNAS..113E4594M"><span>Stochastic <span class="hlt">ice</span> stream dynamics</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mantelli, Elisa; Bertagni, Matteo Bernard; Ridolfi, Luca</p> <p>2016-08-01</p> <p><span class="hlt">Ice</span> streams are narrow corridors of fast-flowing <span class="hlt">ice</span> that constitute the arterial drainage network of <span class="hlt">ice</span> sheets. Therefore, changes in <span class="hlt">ice</span> stream flow are key to understanding paleoclimate, sea level changes, and rapid disintegration of <span class="hlt">ice</span> sheets during deglaciation. The dynamics of <span class="hlt">ice</span> flow are tightly coupled to the climate system through atmospheric temperature and snow recharge, which are known exhibit stochastic variability. Here we focus on the interplay between stochastic climate forcing and <span class="hlt">ice</span> stream temporal dynamics. Our work demonstrates that realistic climate fluctuations are able to (i) induce the coexistence of dynamic behaviors that would be incompatible in a purely deterministic system and (ii) drive <span class="hlt">ice</span> stream flow away from the regime expected in a steady climate. We conclude that environmental noise appears to be crucial to interpreting the past behavior of <span class="hlt">ice</span> sheets, as well as to predicting their future evolution.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014ARMS....6..439A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014ARMS....6..439A"><span>Sea <span class="hlt">Ice</span> Ecosystems</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Arrigo, Kevin R.</p> <p>2014-01-01</p> <p>Polar sea <span class="hlt">ice</span> is one of the largest ecosystems on Earth. The liquid brine fraction of the <span class="hlt">ice</span> 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 <span class="hlt">ice</span> algal communities, generally dominated by diatoms, live at the <span class="hlt">ice</span>/water interface and in recently flooded surface and interior layers, especially during spring, when temperatures begin to rise. Although protists dominate the sea <span class="hlt">ice</span> biomass, heterotrophic bacteria are also abundant. The sea <span class="hlt">ice</span> ecosystem provides food for a host of animals, with crustaceans being the most conspicuous. Uneaten organic matter from the <span class="hlt">ice</span> sinks through the water column and feeds benthic ecosystems. As sea <span class="hlt">ice</span> extent declines, <span class="hlt">ice</span> algae likely contribute a shrinking fraction of the total amount of organic matter produced in polar waters.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4987822','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4987822"><span>Stochastic <span class="hlt">ice</span> stream dynamics</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Bertagni, Matteo Bernard; Ridolfi, Luca</p> <p>2016-01-01</p> <p><span class="hlt">Ice</span> streams are narrow corridors of fast-flowing <span class="hlt">ice</span> that constitute the arterial drainage network of <span class="hlt">ice</span> sheets. Therefore, changes in <span class="hlt">ice</span> stream flow are key to understanding paleoclimate, sea level changes, and rapid disintegration of <span class="hlt">ice</span> sheets during deglaciation. The dynamics of <span class="hlt">ice</span> flow are tightly coupled to the climate system through atmospheric temperature and snow recharge, which are known exhibit stochastic variability. Here we focus on the interplay between stochastic climate forcing and <span class="hlt">ice</span> stream temporal dynamics. Our work demonstrates that realistic climate fluctuations are able to (i) induce the coexistence of dynamic behaviors that would be incompatible in a purely deterministic system and (ii) drive <span class="hlt">ice</span> stream flow away from the regime expected in a steady climate. We conclude that environmental noise appears to be crucial to interpreting the past behavior of <span class="hlt">ice</span> sheets, as well as to predicting their future evolution. PMID:27457960</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li class="active"><span>20</span></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_20 --> <div id="page_21" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li class="active"><span>21</span></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="401"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.C31D0348P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.C31D0348P"><span>Top Sounder <span class="hlt">Ice</span> Penetration</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Porter, D. L.; Goemmer, S. A.; Sweeney, J. H.</p> <p>2014-12-01</p> <p><span class="hlt">Ice</span> draft measurements are made as part of normal operations for all US Navy submarines operating in the Arctic Ocean. The submarine <span class="hlt">ice</span> draft data are unique in providing high resolution measurements over long transects of the <span class="hlt">ice</span> covered ocean. The data has been used to document a multidecadal drop in <span class="hlt">ice</span> thickness, and for validating and improving numerical sea-<span class="hlt">ice</span> models. A submarine upward-looking sonar draft measurement is made by a sonar transducer mounted in the sail or deck of the submarine. An acoustic beam is transmitted upward through the water column, reflecting off the bottom of the sea <span class="hlt">ice</span> and returning to the transducer. <span class="hlt">Ice</span> thickness is estimated as the difference between the ship's depth (measured by pressure) and the acoustic range to the bottom of the <span class="hlt">ice</span> estimated from the travel time of the sonar pulse. Digital recording systems can provide the return off the water-<span class="hlt">ice</span> interface as well as returns that have penetrated the <span class="hlt">ice</span>. Typically, only the first return from the <span class="hlt">ice</span> hull is analyzed. Information regarding <span class="hlt">ice</span> flow interstitial layers provides <span class="hlt">ice</span> age information and may possibly be derived with the entire return signal. The approach being investigated is similar to that used in measuring bottom sediment layers and will involve measuring the echo level from the first interface, solving the reflection loss from that transmission, and employing reflection loss versus impedance mismatch to ascertain <span class="hlt">ice</span> structure information.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19860049995&hterms=uranium&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Duranium','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19860049995&hterms=uranium&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Duranium"><span>Uranium series dating of Allan Hills <span class="hlt">ice</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Fireman, E. L.</p> <p>1986-01-01</p> <p>Uranium-238 decay series nuclides dissolved in Antarctic <span class="hlt">ice</span> samples were measured in areas of both high and low <span class="hlt">concentrations</span> of volcanic glass shards. <span class="hlt">Ice</span> from the Allan Hills site (high shard content) had high Ra-226, Th-230 and U-234 activities but similarly low U-238 activities in comparison with Antarctic <span class="hlt">ice</span> samples without shards. The Ra-226, Th-230 and U-234 excesses were found to be proportional to the shard content, while the U-238 decay series results were consistent with the assumption that alpha decay products recoiled into the <span class="hlt">ice</span> from the shards. Through this method of uranium series dating, it was learned that the Allen Hills Cul de Sac <span class="hlt">ice</span> is approximately 325,000 years old.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=STS048-151-164&hterms=Ross&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3DRoss','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=STS048-151-164&hterms=Ross&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3DRoss"><span>Ross <span class="hlt">Ice</span> Shelf, Antarctic <span class="hlt">Ice</span> and Clouds</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p></p> <p>1991-01-01</p> <p>In this view of Antarctic <span class="hlt">ice</span> and clouds, (56.5S, 152.0W), the Ross <span class="hlt">Ice</span> Shelf of Antarctica is almost totally clear, showing stress cracks in the <span class="hlt">ice</span> surface caused by wind and tidal drift. Clouds on the eastern edge of the picture are associated with an Antarctic cyclone. Winds stirred up these storms have been known to reach hurricane force.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C31A..03A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C31A..03A"><span>Interactions Between <span class="hlt">Ice</span> Thickness, Bottom <span class="hlt">Ice</span> Algae, and Transmitted Spectral Irradiance in the Chukchi Sea</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Arntsen, A. E.; Perovich, D. K.; Polashenski, C.; Stwertka, C.</p> <p>2015-12-01</p> <p>The amount of light that penetrates the Arctic sea <span class="hlt">ice</span> cover impacts sea-<span class="hlt">ice</span> mass balance as well as ecological processes in the upper ocean. The seasonally evolving macro and micro spatial variability of transmitted spectral irradiance observed in the Chukchi Sea from May 18 to June 17, 2014 can be primarily attributed to variations in snow depth, <span class="hlt">ice</span> thickness, and bottom <span class="hlt">ice</span> algae <span class="hlt">concentrations</span>. This study characterizes the interactions among these dominant variables using observed optical properties at each sampling site. We employ a normalized difference index to compute estimates of Chlorophyll a <span class="hlt">concentrations</span> and analyze the increased attenuation of incident irradiance due to absorption by biomass. On a kilometer spatial scale, the presence of bottom <span class="hlt">ice</span> algae reduced the maximum transmitted irradiance by about 1.5 orders of magnitude when comparing floes of similar snow and <span class="hlt">ice</span> thicknesses. On a meter spatial scale, the combined effects of disparities in the depth and distribution of the overlying snow cover along with algae <span class="hlt">concentrations</span> caused maximum transmittances to vary between 0.0577 and 0.282 at a single site. Temporal variability was also observed as the average integrated transmitted photosynthetically active radiation increased by one order of magnitude to 3.4% for the last eight measurement days compared to the first nine. Results provide insight on how interrelated physical and ecological parameters of sea <span class="hlt">ice</span> in varying time and space may impact new trends in Arctic sea <span class="hlt">ice</span> extent and the progression of melt.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1817819A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1817819A"><span>Recent Improvements in the U.S. Navy's <span class="hlt">Ice</span> Modeling Using Merged CryoSat-2/SMOS <span class="hlt">Ice</span> Thickness</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Allard, Richard; Hebert, David; Posey, Pamela; Wallcraft, Alan; Li, Li; Johnston, William; Phelps, Michael; Ridout, Andy; Shepherd, Andrew; Tilling, Rachel</p> <p>2016-04-01</p> <p>The U.S. Navy's Arctic Cap Nowcast/Forecast System (ACNFS) is composed of the Community <span class="hlt">Ice</span> CodE (CICE) coupled to the HYbrid Community Ocean Model (HYCOM). The system assimilates ocean and <span class="hlt">ice</span> observations including <span class="hlt">ice</span> <span class="hlt">concentration</span> from the Advanced Microwave Scanning Radiometer 2 (AMSR2), Special Sensor Microwave Imager Sounder (SSMIS) and <span class="hlt">ice</span> edge data from the National <span class="hlt">Ice</span> Center's Interactive Multisensor Snow and <span class="hlt">Ice</span> Mapping System (IMS). In this study, we perform a series of experiments in which the ACNFS is initialized with a blended <span class="hlt">ice</span> thickness field from CryoSat-2 and the Soil Moisture and Ocean Salinity (SMOS) Missions. CryoSat-2 produces a sea <span class="hlt">ice</span> thickness product which is more accurate for thicknesses greater than 0.46 m while SMOS <span class="hlt">ice</span> thickness is best for thicknesses less than 0.46 m. The experiments begin in March 2012 and continue through April 2015. ACNFS <span class="hlt">ice</span> thickness is compared against NASA <span class="hlt">Ice</span>Bridge, WHOI Upward Looking Sonar, and Cold Regions Research and Engineering Laboratory (CRREL) <span class="hlt">ice</span> mass balance buoy data. Preliminary results show reduced <span class="hlt">ice</span> thickness errors using this blended technique.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.C31A0612G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.C31A0612G"><span>Examining Dual Frequency X- and Ku-band Backscatter of Snow on Lake <span class="hlt">Ice</span> and First-Year Sea <span class="hlt">Ice</span> in the Sub-Arctic Hudson Bay Lowlands</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gunn, G. E.; Duguay, C. R.; Howell, S.; Kelly, R. E.; Silis, A.</p> <p>2011-12-01</p> <p>Fully polarimetric dual frequency ground-based scatterometer observations were collected at X- and Ku-band (9.6 and 17.2 GHz, respectively) near Churchill, Manitoba, Canada in the winter of 2010-11 as part of the Canadian Snow and <span class="hlt">Ice</span> Experiment (CASIX). Backscatter measurements were collected for five landcover types: lake <span class="hlt">ice</span>, sea <span class="hlt">ice</span>, dry tundra, open forest and wetland tundra (sedge fen); the combination of which comprises a unique dataset of dual-frequency backscatter signatures. Correlative data collected, including snow and <span class="hlt">ice</span> properties, are utilized to characterize active microwave interactions and contribute to the development of snow/<span class="hlt">ice</span> retrieval algorithms. This study presents backscatter signatures for lake and sea <span class="hlt">ice</span> obtained during winter 2010-11. The seasonal backscatter evolution is compared to changes in snow and <span class="hlt">ice</span> properties, including depth, density, snow water equivalent (SWE), <span class="hlt">ice</span> thickness, <span class="hlt">ice</span> type, and bubble <span class="hlt">concentration</span> within the <span class="hlt">ice</span>. Results over lake <span class="hlt">ice</span> suggest that increases in backscatter at both X- and Ku-band frequencies correspond to increases in SWE, but are confounded by changes in the sub-nivian <span class="hlt">ice</span> composition. Surface <span class="hlt">ice</span> types (snow <span class="hlt">ice</span>, rafted <span class="hlt">ice</span>), high bubble <span class="hlt">concentrations</span> at the <span class="hlt">ice</span>/water interface and pressure/deformation cracks in the <span class="hlt">ice</span> serve to confound backscatter at several monitoring sites. Over sea <span class="hlt">ice</span>, preliminary results indicate that increased salinity levels near the <span class="hlt">ice</span>/snow interface is the predominate factor influencing backscatter signatures. Physical phenomena encountered at sea <span class="hlt">ice</span> sites are further explored to assess potential influences on scattering signatures. Preliminary findings presented here document the first ground-based dual frequency X- and Ku-band backscatter signatures collected over first year sea <span class="hlt">ice</span>, and contribute to the scientific objectives of the proposed Cold Regions Hydrology High-resolution Observatory (CoReH2O), a candidate Earth Explorer mission of the European Space</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016GeCoA.182...40B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016GeCoA.182...40B"><span>Mirabilite solubility in equilibrium sea <span class="hlt">ice</span> brines</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Butler, Benjamin Miles; Papadimitriou, Stathys; Santoro, Anna; Kennedy, Hilary</p> <p>2016-06-01</p> <p>The sea <span class="hlt">ice</span> microstructure is permeated by brine channels and pockets that contain <span class="hlt">concentrated</span> seawater-derived brine. Cooling the sea <span class="hlt">ice</span> results in further formation of pure <span class="hlt">ice</span> within these pockets as thermal equilibrium is attained, resulting in a smaller volume of increasingly <span class="hlt">concentrated</span> 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 <span class="hlt">ice</span> microstructure. Here, mirabilite solubility in natural and synthetic seawater derived brines, representative of sea <span class="hlt">ice</span> 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 <span class="hlt">ice</span> 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- <span class="hlt">concentrations</span> respectively, compared to that of conservative seawater <span class="hlt">concentration</span>. Such large non-conservative changes in brine composition could potentially impact upon the measurement of sea <span class="hlt">ice</span> brine salinity and pH, whilst the altered osmotic conditions may create additional challenges for the sympagic organisms that inhabit the sea <span class="hlt">ice</span> 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 <span class="hlt">ice</span>. 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 <span class="hlt">ice</span>. Model results ultimately suggest that mirabilite has a near ubiquitous presence in much of the sea <span class="hlt">ice</span> on Earth, and illustrate the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23110707','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23110707"><span>Periodic <span class="hlt">ice</span> banding in freezing colloidal dispersions.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Anderson, Anthony M; Worster, M Grae</p> <p>2012-12-04</p> <p><span class="hlt">Concentrated</span> colloidal alumina dispersions were frozen in a directional solidification apparatus that provides independent control of the freezing rate and temperature gradient. Two distinct steady-state modes of periodic <span class="hlt">ice</span> banding were observed in the range of freezing rates examined. For each mode, the wavelength between successive bands of segregated <span class="hlt">ice</span> decreases with increasing freezing rate. At low freezing rates (0.25-3 μm s(-1)), the <span class="hlt">ice</span> segregates from the suspension into <span class="hlt">ice</span> lenses, which are cracklike in appearance, and there is visible structure in the layer of rejected particles in the unfrozen region ahead of the <span class="hlt">ice</span> lenses. In this regime, we argue that compressive cryosuction forces lead to the irreversible aggregation of the rejected particles into a close-packed cohesive layer. The temperature in the aggregated layer is depressed below the bulk freezing point by more than 2 °C before the <span class="hlt">ice</span> lenses are encountered; moreover, this undercooled region appears as a light-colored layer. The magnitude of the undercooling and the color change in this region both suggest the presence of pore <span class="hlt">ice</span> and the formation of a frozen fringe. The possibility of a frozen fringe is supported by a quantitative model of the freezing behavior. At intermediate freezing rates, around 4 μm s(-1), the pattern of <span class="hlt">ice</span> segregation is disordered, coinciding with the disappearance of the dark- and light-colored layers. Finally, at high freezing rates (5-10 μm s(-1)), there is a new mode of periodic <span class="hlt">ice</span> banding that is no longer cracklike and is absent of any visible structure in the suspension ahead of the <span class="hlt">ice</span> bands. We discuss the implications of our experimental findings for theories of <span class="hlt">ice</span> lensing.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://pubs.er.usgs.gov/publication/70011316','USGSPUBS'); return false;" href="http://pubs.er.usgs.gov/publication/70011316"><span>Norwegian remote sensing experiment in a marginal <span class="hlt">ice</span> zone</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Farrelly, B.; Johannessen, J.A.; Svendsen, E.; Kloster, K.; Horjen, I.; Matzler, C.; Crawford, J.; Harrington, R.; Jones, L.; Swift, C.; Delnore, V.E.; Cavalieri, D.; Gloersen, P.; Hsiao, S.V.; Shemdin, O.H.; Thompson, T.W.; Ramseier, R.O.; Johannessen, O.M.; Campbell, W.J.</p> <p>1983-01-01</p> <p>The Norwegian Remote Sensing Experiment in the marginal <span class="hlt">ice</span> zone north of Svalbard took place in fall 1979. Coordinated passive and active microwave measurements were obtained from shipborne, airborne, and satellite instruments together with in situ observations. The obtained spectra of emissivity (frequency range, 5 to 100 gigahertz) should improve identification of <span class="hlt">ice</span> types and estimates of <span class="hlt">ice</span> <span class="hlt">concentration</span>. Mesoscale features along the <span class="hlt">ice</span> edge were revealed by a 1.215-gigahertz synthetic aperture radar. <span class="hlt">Ice</span> edge location by the Nimbus 7 scanning multichannel microwave radiometer was shown to be accurate to within 10 kilometers.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.osti.gov/scitech/servlets/purl/972218','SCIGOV-STC'); return false;" href="http://www.osti.gov/scitech/servlets/purl/972218"><span>Parameterizing Size Distribution in <span class="hlt">Ice</span> Clouds</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>DeSlover, Daniel; Mitchell, David L.</p> <p>2009-09-25</p> <p>PARAMETERIZING SIZE DISTRIBUTIONS IN <span class="hlt">ICE</span> CLOUDS David L. Mitchell and Daniel H. DeSlover ABSTRACT An outstanding problem that contributes considerable uncertainty to Global Climate Model (GCM) predictions of future climate is the characterization of <span class="hlt">ice</span> particle sizes in cirrus clouds. Recent parameterizations of <span class="hlt">ice</span> cloud effective diameter differ by a factor of three, which, for overcast conditions, often translate to changes in outgoing longwave radiation (OLR) of 55 W m-2 or more. Much of this uncertainty in cirrus particle sizes is related to the problem of <span class="hlt">ice</span> particle shattering during in situ sampling of the <span class="hlt">ice</span> particle size distribution (PSD). <span class="hlt">Ice</span> particles often shatter into many smaller <span class="hlt">ice</span> fragments upon collision with the rim of the probe inlet tube. These small <span class="hlt">ice</span> artifacts are counted as real <span class="hlt">ice</span> crystals, resulting in anomalously high <span class="hlt">concentrations</span> of small <span class="hlt">ice</span> crystals (D < 100 µm) and underestimates of the mean and effective size of the PSD. Half of the cirrus cloud optical depth calculated from these in situ measurements can be due to this shattering phenomenon. Another challenge is the determination of <span class="hlt">ice</span> and liquid water amounts in mixed phase clouds. Mixed phase clouds in the Arctic contain mostly liquid water, and the presence of <span class="hlt">ice</span> is important for determining their lifecycle. Colder high clouds between -20 and -36 oC may also be mixed phase but in this case their condensate is mostly <span class="hlt">ice</span> with low levels of liquid water. Rather than affecting their lifecycle, the presence of liquid dramatically affects the cloud optical properties, which affects cloud-climate feedback processes in GCMs. This project has made advancements in solving both of these problems. Regarding the first problem, PSD in <span class="hlt">ice</span> clouds are uncertain due to the inability to reliably measure the <span class="hlt">concentrations</span> of the smallest crystals (D < 100 µm), known as the “small mode”. Rather than using in situ probe measurements aboard aircraft, we employed a treatment of <span class="hlt">ice</span></p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2000JGR...10511299K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2000JGR...10511299K"><span>Results of the Sea <span class="hlt">Ice</span> Model Intercomparison Project: Evaluation of sea <span class="hlt">ice</span> rheology schemes for use in climate simulations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kreyscher, Martin; Harder, Markus; Lemke, Peter; Flato, Gregory M.</p> <p>2000-05-01</p> <p>A hierarchy of sea <span class="hlt">ice</span> rheologies is evaluated on the basis of a comprehensive set of observational data. The investigations are part of the Sea <span class="hlt">Ice</span> Model Intercomparison Project (SIMIP). Four different sea <span class="hlt">ice</span> rheology schemes are compared: a viscous-plastic rheology, a cavitating-fluid model, a compressible Newtonian fluid, and a simple free drift approach with velocity correction. The same grid, land boundaries, and forcing fields are applied to all models. As verification data, there are (1) <span class="hlt">ice</span> thickness data from upward looking sonars (ULS), (2) <span class="hlt">ice</span> <span class="hlt">concentration</span> data from the passive microwave radiometers SMMR and SSM/I, (3) daily buoy drift data obtained by the International Arctic Buoy Program (IABP), and (4) satellite-derived <span class="hlt">ice</span> drift fields based on the 85 GHz channel of SSM/I. All models are optimized individually with respect to mean drift speed and daily drift speed statistics. The impact of <span class="hlt">ice</span> strength on the <span class="hlt">ice</span> cover is best revealed by the spatial pattern of <span class="hlt">ice</span> thickness, <span class="hlt">ice</span> drift on different timescales, daily drift speed statistics, and the drift velocities in Fram Strait. Overall, the viscous-plastic rheology yields the most realistic simulation. In contrast, the results of the very simple free-drift model with velocity correction clearly show large errors in simulated <span class="hlt">ice</span> drift as well as in <span class="hlt">ice</span> thicknesses and <span class="hlt">ice</span> export through Fram Strait compared to observation. The compressible Newtonian fluid cannot prevent excessive <span class="hlt">ice</span> thickness buildup in the central Arctic and overestimates the internal forces in Fram Strait. Because of the lack of shear strength, the cavitating-fluid model shows marked differences to the statistics of observed <span class="hlt">ice</span> drift and the observed spatial pattern of <span class="hlt">ice</span> thickness. Comparison of required computer resources demonstrates that the additional cost for the viscous-plastic sea <span class="hlt">ice</span> rheology is minor compared with the atmospheric and oceanic model components in global climate simulations.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011JGRD..11623214H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011JGRD..11623214H"><span>Modeled methanesulfonic acid (MSA) deposition in Antarctica and its relationship to sea <span class="hlt">ice</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hezel, P. J.; Alexander, B.; Bitz, C. M.; Steig, E. J.; Holmes, C. D.; Yang, X.; Sciare, J.</p> <p>2011-12-01</p> <p>Methanesulfonic acid (MSA) has previously been measured in <span class="hlt">ice</span> cores in Antarctica as a proxy for sea <span class="hlt">ice</span> extent and Southern Hemisphere circulation. In a series of chemical transport model (GEOS-Chem) sensitivity experiments, we identify mechanisms that control the MSA <span class="hlt">concentrations</span> recorded in <span class="hlt">ice</span> cores. Sea <span class="hlt">ice</span> is linked to MSA via dimethylsulfide (DMS), which is produced biologically in the surface ocean and known to be particularly <span class="hlt">concentrated</span> in the sea <span class="hlt">ice</span> zone. Given existing ocean surface DMS <span class="hlt">concentration</span> data sets, the model does not demonstrate a strong relationship between sea <span class="hlt">ice</span> and MSA deposition in Antarctica. The variability of DMS emissions associated with sea <span class="hlt">ice</span> extent is small (11-30%) due to the small interannual variability of sea <span class="hlt">ice</span> extent. Wind plays a role in the variability in DMS emissions, but its contribution relative to that of sea <span class="hlt">ice</span> is strongly dependent on the assumed DMS <span class="hlt">concentrations</span> in the sea <span class="hlt">ice</span> zone. Atmospheric sulfur emitted as DMS from the sea <span class="hlt">ice</span> undergoes net transport northward. Our model runs suggest that DMS emissions from the sea <span class="hlt">ice</span> zone may account for 26-62% of MSA deposition at the Antarctic coast and 36-95% in inland Antarctica. Though our results are sensitive to model assumptions, it is clear that an improved understanding of both DMS <span class="hlt">concentrations</span> and emissions from the sea <span class="hlt">ice</span> zone are required to better assess the impact of sea <span class="hlt">ice</span> variability on MSA deposition to Antarctica.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012EGUGA..1410049V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012EGUGA..1410049V"><span>Greenland <span class="hlt">Ice</span> Sheet retreat during the Eemian</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>van de Berg, W. J.; Helsen, M. M.; van de Wal, R. S. W.; van den Broeke, M. R.; Oerlemans, J.</p> <p>2012-04-01</p> <p>We present a new estimate of the evolution of the Greenland <span class="hlt">Ice</span> Sheet through the Eemian (130 till 115 ky BP). This estimate is determined using the 3D 'shallow' <span class="hlt">ice</span> sheet model ANICE and the regional climate model RACMO2/GR. The two models are time-slice coupled with an interval of 1500 years. 3D interpolated surface mass balance fields from RACMO2/GR force ANICE. Eemian and post-Eemian climate from the GCM ECHO-G drives RACMO2/GR on its lateral boundaries. These boundaries are gradually adjusted from maximum Eemian conditions to post-Eemian inception conditions, following the orbital parameters and Greenhouse gas <span class="hlt">concentrations</span> derived from <span class="hlt">ice</span> cores. The simulation shows a steady mass loss till the insolation conditions decline and the summer climate cools, with a typical rate of mass loss equivalent to 5 cm sea level rise per century for most of the time. Once summer start to cool the Greenland <span class="hlt">ice</span> sheet recovers fast. The maximum <span class="hlt">ice</span> loss is about 2 m eustatic sea level compared to present day volume and originates predominantly from southwest Greenland. Our results align with paleo-observations of Eemian <span class="hlt">ice</span> sheet existence in South Greenland. Strong summer radiation also induces <span class="hlt">ice</span> retreat in northern Greenland. Moreover, it agrees with preceding studies that the Greenland <span class="hlt">ice</span> sheet had only a limited contribution to the Eemian sea level high stand. A finding of this novel approach is the impact of topographic pinpoints on the <span class="hlt">ice</span> sheet evolution. Subglacial topography, like at 52° W 72° N (near Uummannaq), cause promontories in the <span class="hlt">ice</span> sheet that enhances snowfall. Locations with high snowfall react less on warming than dry locations, because more melt is needed before all snow is removed, and the more efficient <span class="hlt">ice</span> melt starts. The reduced <span class="hlt">ice</span> depth also buttresses inland <span class="hlt">ice</span>, limiting the <span class="hlt">ice</span> sheet response to enhanced ablation. As a result, this topographical feature becomes the northern limit of significant <span class="hlt">ice</span> sheet retreat, and shields the north</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016OSJ....51..387S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016OSJ....51..387S"><span>In-situ measured primary productivity of <span class="hlt">ice</span> algae in Arctic sea <span class="hlt">ice</span> floes using a new incubation method</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Song, Ho Jung; Lee, Jae Hyung; Kim, Gawn Woo; Ahn, So Hyun; Joo, Houng-Min; Jeong, Jin Young; Yang, Eun Jin; Kang, Sung-Ho; Lee, Sang Heon</p> <p>2016-09-01</p> <p>Recent changes in climate and environmental conditions have had great negative effects such as decreasing sea <span class="hlt">ice</span> thickness and the extent of Arctic sea <span class="hlt">ice</span> floes that support <span class="hlt">ice</span>-related organisms. However, limited field observations hinder the understanding of the impacts of the current changes in the previously <span class="hlt">ice</span>-covered regions on sea <span class="hlt">ice</span> algae and other <span class="hlt">ice</span>-related ecosystems. Our main objective in this study was to measure recent primary production of <span class="hlt">ice</span> algae and their relative contribution to total primary production (<span class="hlt">ice</span> plus pelagic primary production). In-situ primary productivity experiments with a new incubation system for <span class="hlt">ice</span> algae were conducted in 3 sea <span class="hlt">ice</span> cores at 2 different <span class="hlt">ice</span> camps in the northern Chukchi Sea, 2014, using a 13C and 15N isotope tracer technique. A new incubation system was tested for conducting primary productivity experiments on <span class="hlt">ice</span> algae that has several advantages over previous incubation methods, enabling stable carbon and nitrogen uptake experiments on <span class="hlt">ice</span> algae under more natural environmental conditions. The vertical C-shaped distributions of the <span class="hlt">ice</span> algal chl- a, with elevated <span class="hlt">concentrations</span> at the top and bottom of the sea <span class="hlt">ice</span> were observed in all cores, which is unusual for Arctic sea <span class="hlt">ice</span>. The mean chl- a <span class="hlt">concentration</span> (0.05 ± 0.03 mg chl- a m-3) and the daily carbon uptake rates (ranging from 0.55 to 2.23 mg C m-2 d-1) for the <span class="hlt">ice</span> algae were much lower in this study than in previous studies in the Arctic Ocean. This is likely because of the late sampling periods and thus the substantial melting occurring. <span class="hlt">Ice</span> algae contributed 1.5-5.7% of the total particulate organic carbon (POC) con