Journal
REMOTE SENSING OF ENVIRONMENT
Volume 74, Issue 2, Pages 275-286Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/S0034-4257(00)00121-8
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Existing algorithms for retrieving snow water equivalent (SWE) from the Special Sensor Microwave/Imager (SSM/I) passive microwave brightness temperature data were assessed and new algorithms that include physiographic and atmospheric data were developed for the Red River basin of North Dakota and Minnesota. The frequencies of SSM/I data used are 19 GHz and 37 GHz in both horizontal and vertical polarization. Encouraging calibration results are obtained for the algorithms using multivariate regression technique and dry snow cases of the 1989 and 1988 SSM/I data (from DMSP-F8). Similarly, validation results for data not used in calibration [e.g., 1988 (1989 as calibration data), 1989 (1988 as calibration data), and 1997 (from DMSP-F10 and F13)] are also encouraging. The nonparametric, Projection Pursuit Regression (PPR) technique also gave good results in both stages. However, for the validation stage, adding a shift parameter to all retrieval algorithms was always necessary, possibly because of different scatter-induced darkening (caused by scattering albedo), which could arise even for snowpacks of the same thickness because snowpacks undergo different metamorphism in different winter years. Screening criteria are also proposed to eliminate SSM/I footprints affected by large water bodies and depth-hoar-another key step toward reliable SWE estimation from passive microwave data. (C) 2000 Elsevier Science Inc.
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