Land surface temperature retrieval from AMSR-E passive microwave data

Abstract

The land surface temperature (LST) is a key parameter for energy balance, evapotranspiration and climate change. In this study, two new methods of LST retrieval from passive microwave data are developed: one is deriving LST only using single-channel dual-polarized data based on the relationship between the emissivity and microwave polarization difference index (MPDI) (denoted as Method 1); the other one is deriving LST using the traditional multi-channel method with prior knowledge of the normalized difference vegetation index (NDVI) (denoted as Method 3). Taking Moderate Resolution Imaging Spectroradiometer (MODIS) LST products as the actual LSTs, the coefficients for these algorithms are determined. From the results for the year 2008, it is demonstrated that the root mean square errors (RMSEs) for the LST retrieval using Method 3 are the smallest and range from 2.92 K to 3.44 K, the RMSEs for the LST retrieval using traditional multi-channel method (denoted as Method 2) range from 3.07 K to 4.05 K, and the worst results come from Method 1, whose RMSEs range from 3.11 K to 4.13 K at a frequency of 89 GHz. This could be caused by the fact that the NDVI provides substantial emissivity knowledge in Method 3, and much richer vegetation could result in a more accurate emissivity estimation.