Feasibility of Estimating Snow Emissivity Via Assimilation of Multifrequency Passive Microwave Data

Prior studies have shown that models and remote sensing data cannot accurately estimate snow emissivity due to limitations attributed to each of them. Hence, in this study, we merged Common Land Model (CLM) and snow emission (MEMLS) models with multi-frequency passive microwave data within an EnBS scheme to estimate snow emissivity. Its feasibility was tested via a test where passive microwave (at 1.4, 18.7, 36.5, and 87 GHz) measurements at the point scale were individually and simultaneously assimilated to estimate snow emissivity. The contribution of each channel in estimating the true snow emissivity is examined at the local-scale observation site of the National Aeronautics and Space Administration Cold Land Processes Experiment (NASA-CLPX) Field Campaign in Fall 2002-Winter 2003. All of the assimilated passive microwave measurements are found to contain complementary information for retrieving snow emissivity.