Advances in Inversion of Microwave Snowpack Emission Models for Simultaneous Retrieval of Depth, Density and Grain Size

This research studies the role of high frequency microwave channels, above 60 GHz, in reducing uncertainty of inversion of snowpack emission models. A multi-frequency algorithm, which relies on a sparse dictionary matching and locally constrained least-squares, is presented and tested for multi-layer inversion of the Dense Media Radiative Transfer (DMRT) equations of snowpack emission. Using observations from the microwave imager onboard the Global Precipitation Measurement (GPM, 10-166 GHz) core satellite, the initial results demonstrate that under a clear-sky condition, the algorithm is capable of simultaneous retrieval of snow depth, density and grain size over flat lands with light vegetation density --- consistent with high-resolution analysis data from the SNOw Data Assimilation System (SNODAS) over the conterminous United States.