Development and Evaluation of the GCOM-W1 AMSR2 Snow Depth and Snow Water Equivalent Algorithm

Abstract:

An evaluation is presented of snow depth (SD) and snow water equivalent (SWE) estimates from recent developments to the standard snow product algorithm for the Advanced Microwave Scanning Radiometer – 2 (AMSR2) aboard the Global Change Observation Mission – Water. AMSR2 is designed as a follow-on from the successful Advanced Microwave Scanning Radiometer – EOS that ceased formal operations in 2011. The standard SD product for AMSR2 has been updated in two ways. First, the detection algorithm identifies various observable geophysical targets that can confound SD / SWE estimation (water bodies [including freeze/thaw state], rainfall, high altitude plateau regions [e.g. Tibetan plateau]) before detecting moderate and shallow snow. Second, the implementation of the Dense Media Radiative Transfer model (DMRT) originally developed by Tsang et al. (2000) and more recently adapted by Picard et al. (2011) is used to estimate SWE and SD. The implementation combines snow grain size and density parameterizations originally developed by Kelly et al. (2003). Snow grain size is estimated from the tracking of estimated air temperatures that are used to drive an empirical grain growth model. Snow density is estimated from the Sturm et al. (2010) scheme. Efforts have been made to keep the approach tractable while reducing uncertainty in these input variables. Results are presented from the recent winter seasons since 2012 to illustrate the performance of the new approach in comparison with the initial AMSR2 algorithm.