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To make use of satellite microwave observations for estimating soil moisture, a dual-pass land data assimilation system (DLDAS) is developed in this paper by incorporating a dual-pass assimilation framework into the Community Land Model version 3 (CLM3).In the DLDAS, the model state (volumetric soil moisture content) and model parameters are jointly optimized using the gridded Advanced Microwave Scanning Radiometer-EOS (AMSR-E) satellite brightness temperature (Tb) data through a radiative transfer model (RTM), which acts as an observation operator to provide a link between the model states and the observational variable (i.e., Tb).