Data Assimilation of Satellite-Derived Heating Rates as Proxy Surface Wetness Data into a Regional Atmospheric Mesoscale Model. Part II: A Case Study

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 convection along the dryline.