Abstract
Abstract A satellite data assimilation method is applied which incorporates satellite-observed heating infrared rates into a mesoscale atmospheric model to retrieve model soil moisture. In a 3D case study, the method is successful at retrieving realistic spatial representations of the heterogeneous surface soil moisture as compared to microwave surface emissivities, precipitation reports, and radar summaries; however, absolute magnitudes of the derived soil moisture fields are by nature model dependent. From noise sensitivity experiments, satellite instrument noise is not found to be a major factor in the data assimilation method’s performance. The case study presented here over the Great Plains region showed a significant soil moisture gradient where a weak dryline feature formed in the afternoon. The main effect of the soil moisture gradient was a tightening of the water vapor gradient in the boundary layer. However, it was found that this feature was much less important than latent heat release due to ...
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