Abstract

The NASA Soil Moisture Active Passive (SMAP) mission was launched in January 2015 and has been providing near global coverage of soil moisture every 3 days. At Environment and Climate Change Canada (ECCC) considerable effort has been focused upon the assimilation of SMAP brightness temperatures for a better analysis of the soil moisture state and resulting Numerical Weather Prediction (NWP) forecasts. A new land-surface parameterization, Soil, Vegetation, and Snow (SVS) was recently developed at ECCC which includes more sophisticated hydrology incorporating multiple soil layers where soil moisture evolves according to Darcian flow, and includes separate energy budgets for different land-surface components. The objectives of this study are to perform a set of assimilation experiments to quantify improvements in soil moisture and added NWP skill from the inclusion of SMAP data within SVS.

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