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Impact of Surface Roughness on AMSR-E Sea Ice ProductsThis paper examines the sensitivity of Advanced Microwave Scanning Radiometer (AMSR-E) brightness temperatures (Tbs) to surface roughness by a using radiative transfer model to simulate AMSR-E Tbs as a function of incidence angle at which the surface is viewed. The simulated Tbs are then used to examine the influence that surface roughness has on two operational sea ice algorithms, namely: 1) the National Aeronautics and Space Administration Team (NT) algorithm and 2) the enhanced NT algorithm, as well as the impact of roughness on the AMSR-E snow depth algorithm. Surface snow and ice data collected during the AMSR-Ice03 field campaign held in March 2003 near Barrow, AK, were used to force the radiative transfer model, and resultant modeled Tbs are compared with airborne passive microwave observations from the Polarimetric Scanning Radiometer. Results indicate that passive microwave Tbs are very sensitive even to small variations in incidence angle, which can cause either an over or underestimation of the true amount of sea ice in the pixel area viewed. For example, this paper showed that if the sea ice areas modeled in this paper mere assumed to be completely smooth, sea ice concentrations were underestimated by nearly 14% using the NT sea ice algorithm and by 7% using the enhanced NT algorithm. A comparison of polarization ratios (PRs) at 10.7,18.7, and 37 GHz indicates that each channel responds to different degrees of surface roughness and suggests that the PR at 10.7 GHz can be useful for identifying locations of heavily ridged or rubbled ice. Using the PR at 10.7 GHz to derive an "effective" viewing angle, which is used as a proxy for surface roughness, resulted in more accurate retrievals of sea ice concentration for both algorithms. The AMSR-E snow depth algorithm was found to be extremely sensitive to instrument calibration and sensor viewing angle, and it is concluded that more work is needed to investigate the sensitivity of the gradient ratio at 37 and 18.7 GHz to these factors to improve snow depth retrievals from spaceborne passive microwave sensors.
Document ID
20070021414
Acquisition Source
Goddard Space Flight Center
Document Type
Reprint (Version printed in journal)
Authors
Stroeve, Julienne C.
(Colorado Univ. Boulder, CO, United States)
Markus, Thorsten
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Maslanik, James A.
(Colorado Univ. Boulder, CO, United States)
Cavalieri, Donald J.
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Gasiewski, Albin J.
(Colorado Univ. Boulder, CO, United States)
Heinrichs, John F.
(Fort Hayes State University Hays, KS, United States)
Holmgren, Jon
(Army Cold Regions Research and Engineering Lab. Fort Wainright, AK, United States)
Perovich, Donald K.
(Army Cold Regions Research and Engineering Lab. Hanover, NH, United States)
Sturm, Matthew
(Army Cold Regions Research and Engineering Lab. Fort Wainright, AK, United States)
Date Acquired
August 23, 2013
Publication Date
November 1, 2006
Publication Information
Publication: IEEE Transactions on Geoscience and Remote Sensing
Volume: 44
Issue: 11
Subject Category
Earth Resources And Remote Sensing
Funding Number(s)
CONTRACT_GRANT: NAG5-11369
CONTRACT_GRANT: NNG04GH68G
Distribution Limits
Public
Copyright
Other

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