Assessment of the NASA AMSR-E SWE Product

被引:137
作者
Tedesco, Marco [1 ]
Narvekar, Parag S. [1 ]
机构
[1] CUNY City Coll, Dept Earth & Atmospher Sci, New York, NY 10031 USA
关键词
Snow; Grain size; Heuristic algorithms; Microwave measurements; Microwave FET integrated circuits; Microwave integrated circuits; Remote sensing; SNOW WATER EQUIVALENT; DEPTH ALGORITHM; RETRIEVAL; METAMORPHISM; MODEL;
D O I
10.1109/JSTARS.2010.2040462
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Since the launch of the Scanning Multichannel Microwave Radiometer (SMMR) in 1978, several studies have demonstrated the capability of spaceborne passive microwave sensors for mapping global snow water equivalent (SWE). Currently, SWE values are estimated operationally from microwave brightness temperatures measured by the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) and distributed through the National Snow and Ice Data Center (NSIDC). In this study, we report results regarding the comparison between AMSR-E SWE and SWE/snow depth values distributed by the Snow Data Assimilation System (SNODAS) product of the NOAA's National Operational Hydrologic Remote Sensing Center and snow depth measured by automatic weather stations of the World Meteorological Organization. Generally, we found poor correlation between the AMSR-E and SNODAS SWE/snow depth values. The algorithm performance improves when considering WMO data, though the number of samples used for the analysis might play a role in this sense. We discuss algorithm-related sources of error and uncertainties, such as vegetation and grain size. Moreover, we report results aimed at evaluating whether replacing the linear approach with a nonlinear one and not using the brightness temperatures and ancillary data sets combined as in the current approach but taken separately as inputs to the algorithm might improve the performance of the algorithm.
引用
收藏
页码:141 / 159
页数:19
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