A Physical Method for Generating the Surface Temperature from Passive Microwave Observations by Addressing the Thermal Sampling Depth for Barren Land

Abstract:

The land surface temperature (LST) is an important parameter in studying the global and regional climate change. Passive microwave (PMW) remote sensing is less influenced by the atmosphere and has a unique advantage in cloudy regions compared to satellite thermal infrared (TIR) remote sensing. However, the accuracy of LST estimation of many PMW remote sensing models, especially in barren land, is unsatisfactory due to the neglected discrepancy of thermal sampling depth between PMW and TIR. Here, a physical method for PMW remote sensing is proposed to generate the surface temperature, which has the same physically meaning as the TIR surface temperature, by addressing the thermal sampling depth over barren land surface. The method was applied to the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) data. Validation with the synchronous Moderate Resolution Imaging Spectroradiometer (MODIS) LSTs demonstrates that the method has better performances in estimating LSTs than another two methods that neglect the thermal sampling depth. In Northwest China and a part of Mongolia, the root mean squared errors (RMSEs) the physical method were 3.9 K and 3.7K for daytime and nighttime cases, respectively. In the region of western Namibia, the corresponding RMSEs were 3.8 K and 4.5 K. Further comparison with the in-situ measured LST temperatures at a ground station confirmed the better performance of the proposed method, compared with another two methods. The proposed method will be beneficial for improving the accuracies of the LSTs estimated from PMW observations and integrating the LST products generated from both the TIR and PMW remote sensing.