Interpreting the remotely sensed microwave radiance FROm snow covered mountains via a high-resolution modeling framework

Applying passive microwave (PM) remote sensing to estimate mountain snow water equivalent (SWE) is challenging due to the complex interaction between the microwave radiance and the mountain environment; a better knowledge of the interaction is requisite to improve the characterization of mountain SWE via PM. In this study, we modeled the 36.5GHz V-Pol microwave radiance at 90m spatial resolution over the Upper Kern Basin. We replicated the AMSR-E observations with the modeling results, and used the modeled radiance to interpret the satellite observations, as well as to explore the impacts of the mountain environment on microwave radiance. We found snow grain size, model stratigraphic representation, liquid water content and intense snowfall event close related with the modeling accuracy; the calibration to these parameters reduced the error in the modeled radiance by 81%. We aggregated the modeled radiance to AMSR-E footprint scale using the antenna sampling pattern to facilitate the comparison between the modeled radiance and the AMSR-E observations. The RMSE of the basin-scale modeling was 3.1K during the dry snow season. Using the modeling results, we classified the environmental variables in terms of their influence on microwave radiance in the study area; from high to low: SWE (significant only when snowpack is deep), vegetation, elevation, aspect, slope.