Cloudy land surface temperature retrieval from three-channel microwave data

Land surface temperature (LST) plays an important role in land surface processes, and it is a key input for estimating important hydrological states and fluxes, such as soil moisture and evapotranspiration. In this study, a three-channel method is proposed to retrieve cloudy LST values from passive microwave data based on the relationship among surface emissivities at 18.70, 36.50, and 89.00 GHz over a bare soil surface. The performance of the method was evaluated using simulated data, resulting in a root mean square error (RMSE) of approximately 1.4K over the bare soil surface. This method was further extended to retrieve cloudy LST values over a natural surface. Due to the lack of in situ LST measurements, ground-based air temperatures were used as proxy data to validate the cloudy LST values retrieved from AMSR-E data. The RMSE values of the differences between the retrieved cloudy LST values and the ground-based air temperatures are approximately 3.4K and 4.3K for the descending and ascending overpasses, respectively. The results demonstrate that the three-channel method can be used to retrieve cloudy LST values from passive microwave data with reasonable accuracy.