Calibration to Improve Forward Model Simulation of Microwave Emissivity at GPM Frequencies Over the U.S. Southern Great Plains

Better estimation of land surface microwave emissivity (MWE) promises to improve overland precipitation retrievals in the Global Precipitation Measurement era. Forward models of land MWE are available but have suffered from poor parameter specification and limited testing. Here, forward models are calibrated, and the accompanying change in predictive power is evaluated. With inputs (e.g., soil moisture) from the Noah land surface model and applying Moderate Resolution Imaging Spectroradiometer leaf area index data, two microwave emissivity models (MEMs) are tested, namely, the Community Radiative Transfer Model and the Community Microwave Emission Model. The calibration is conducted with the National Aeronautics and Space Administration Land Information System parameter estimation subsystem using Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E)-based emissivity retrievals for the calibration data set. The extent of agreement between the modeled and retrieved estimates is evaluated using the AMSR-E retrievals for a separate seven-year validation period. Results indicate that calibration can significantly improve the agreement, simulating emissivity with an across-channel average root-mean-square difference (RMSD) of about 0.013 or about 20% lower than if relying on daily estimates based on climatology. The results also indicate that calibration of the MEM alone, as was done in prior studies, results in as much as 12% higher across-channel average RMSD, as compared with the joint calibration of the land surface and microwave emissivity models. It remains as future work to assess the extent to which the improvements in emissivity estimation translate into improvements in precipitation retrieval accuracy.