H13H-1650
­­Calibration to improve forward model simulation of microwave emissivity at GPM frequencies over the U.S. Southern Great Plains

Monday, 14 December 2015
Poster Hall (Moscone South)
Kenneth W Harrison1, Christa D Peters-Lidard2, Yudong Tian3, Sarah Ringerud2 and Sujay Kumar2, (1)University of Maryland College Park, College Park, MD, United States, (2)NASA Goddard Space Flight Center, Greenbelt, MD, United States, (3)University of California Los Angeles, Los Angeles, CA, United States
Abstract:
Improved land surface microwave emissivity estimation promises to improve over-land precipitation retrievals in the GPM era. Forward models are available but have suffered from poor parameter specification. Here, forward models are calibrated and the accompanying change in predictive power is discussed. With inputs (e.g., soil moisture) from the Noah land surface model and applying MODIS LAI data, two microwave emissivity models are tested, the Community Radiative Transfer Model (CRTM) and Community Microwave Emission Model (CMEM). The calibration is conducted with the NASA Land Information System (LIS) parameter estimation subsystem using AMSR-E based emissivity retrievals for the calibration dataset. The extent of agreement between the modeled and retrieved estimates is evaluated using the AMSR-E retrievals for a separate 7-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. It remains as future work to assess the extent to which the improvements in emissivity estimation translate into improvements in precipitation retrieval accuracy.