Satellite Retrieval of Microwave Land Surface Emissivity under Clear and Cloudy Skies in China Using Observations from AMSR-E and MODIS

Microwave land surface emissivity (MLSE) is an important geophysical parameter to determine the microwave radiative transfer over and has broad applications in satellite remote sensing of atmospheric parameters (e.g., precipitation, cloud properties), soil moisture, vegetation interactions between atmosphere terrestrial ecosystem evapotranspiration rate, gross primary production rate). In this study, MLSE China under both clear cloudy sky conditions was retrieved using passive measurements from Aqua Advanced Scanning Radiometer-Earth Observing System (AMSR-E), combined with visible/infrared observations Moderate Resolution Imaging Spectroradiometer (MODIS), European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis dataset ERA-20C. Attenuations oxygen water vapor, as well emissions scatterings particles are taken into account a radiation model do corrections. All needed derived MODIS visible infrared instantaneous measurements. Ancillary skin temperature temperature-humidity profiles collected ECMWF data. Quality control sensitivity analyses were conducted input variables temperature, air humidity. The ground-based validations show acceptable biases (skin 2 m near relative humidity, rain flag) retrieving using. subsequent tests suggest that 10 K bias or observed brightness may result 4% (~0.04) 7% (0.07) error at 23.5 GHz. A nonlinear same magnitude found perturbation, while less than 1% 300 g/m2 path. Results our algorithm can successfully retrieve 90% detected area typical day (cloud fraction 64%), which considerably higher 29% by clear-sky only algorithms. spatial distribution highly dependent on types topography. assessed compared other existing AMSR-E products optical depth (VOD) product. Overall, high consistencies shown study across though noticeable discrepancies Tibetan Plateau Qinling-Taihang Mountains due different sources temperature. addition, exhibits strong positive correlations patterns reported literature.