A Physical Method for Retrieving Microwave Land Surface Emissivity under all-Weather Conditions

Microwave land surface emissivity (LSE) is an important parameter for retrievals of land surface and atmospheric characteristics, and it is also crucial as an input parameter for numerical weather prediction model data assimilation. This study develops a method for retrieving all-weather LSE over China based on radiative transfer model through reconstructing spatial-temporal continuous land surface temperature (LST) data using China Land Data Assimilation System (CLDAS). Atmospheric effect is also removed with the relationships among atmospheric transmittances, atmospheric effective radiating temperature, precipitable water vapor (PWV), and cloud liquid water (CLW). The retrieved LSE are preliminarily validated by the simulations of Community Radiative Transfer Model (CRTM) and two LSEs show a determined parameter (R2) of 0.81 at 18.7 GHz.