Atmospheric and forest decoupling from AMSR-E passive microwave brightness temperature observations in snow-covered regions over North America

Tuesday, 16 December 2014
Yuan Xue and Barton A Forman, University of Maryland, College Park, MD, United States
Remotely-sensed measurements from space-borne instrumentation have been extensively utilized in order to quantify snow water equivalent (SWE) across the globe, primarily in the form of SWE retrievals derived from passive microwave (PMW) brightness temperature (Tb) measurements. However, the application of these SWE retrieval products is largely limited by wet snow, deep snow, overlying vegetation, depth hoar, ice crusts, sub-grid scale lake ice, snow stratigraphy, and snow morphology. Alternatively, PMW Tb can be integrated directly (i.e., without the need of a SWE retrieval algorithm) into a land surface model as part of a Tb data assimilation (DA) framework. However, it is worthwhile to first decouple non-SWE related signals from the Tb observations prior to assimilation of the SWE-related Tb information. This study addresses two significant sources of SWE-related uncertainties using the Advanced Microwave Scanning Radiometer (AMSR-E) PMW Tb observations. Namely, atmospheric and overlying forest effects are decoupled using relatively simple radiative transfer models. Comparisons against independent Tb measurements collected during airborne PMW Tb surveys highlight the effectiveness of AMSR-E Tb measurements decoupling with the eventual goal of enhancing estimated SWE as part of a PMW Tb data assimilation framework into an advanced land surface model.