Downscaling microwave brightness temperatures from FY3B/MWRI with a linear unmixing method

The coarse spatial resolution of microwave radiometer measurements hinders its application on land and sea surface parameters estimation. Measurements therefore require better spatial resolution to improve parameters estimation with enhanced resolution and accuracy. In this paper, a linear unmixing method is presented to downscale brightness temperatures (TB) for accurate land surface parameters retrieval. Contributions to brightness temperatures originating from different land surfaces can be identified with high-resolution land-cover images, land surface temperature products, and an antenna gain function. This produces an underdetermined equation set, which can be solved by a constrained linear least-square method with an assumption that the emissivity of each land-cover type over a small localized region is uniform. Finally, downscaled (unmixed) brightness temperatures of each land-cover type are derived from mixed pixels. Simulation results of three numerical experiments validated that the unmixing algorithm is capable of separating the signals of land-cover types from mixed pixels. The unmixing method is then applied to FY3B-MWRI measurements. The resulting downscaled brightness temperature presented enhanced details while keeping the original overall distribution of brightness temperatures. In conclusion, the linear unmixing method is capable of downscaling brightness temperatures.