Abstract
AbstractFor the American northern Great Plains region, the 1996/97 snow season had snow accumulations much greater than normal, which combined with rapid warming to produce extensive flooding in the Red River of the North river basin. Passive-microwave observations from the Special Sensor Microwave/Imager (SSM/I) are used to follow the evolution of the snowpack during the snow season and to map the extent of standing water or very saturated soils during spring 1997. SSM/I-derived snow-depth algorithms that assume a fixed snow grain-size constantly underestimated the snow depth by a factor of 2 in the region where extensive flooding occurred. An estimate of the thermal gradient through the snowpack is used to model the growth of the snow grain-size and to compute more accurately the evolution of the snow depth over the region. As is commonly observed, when the melt season begins, liquid water in the snowpack causes the SSM/I spectral gradient to drop to zero. In this case, the spectral gradient fell to unusually negative values, which were indicative of large areas of open water, and not wet snow or soil.
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