Estimating Cloudy-Sky Land Surface Temperature From FY-3D/MERSI-II Using the Surface Energy Balance Theory

This letter reports the first cloudy-sky land surface temperature (LST) retrieval from the MEdium Resolution Spectral Imager-II (MERSI-II) onboard Fengyun-3D (FY-3D). In this study, a new cloudy-sky LST retrieval algorithm was adapted for FY-3D/MERSI-II. The method consists of two key components: (1) estimating the hypothetical clear-sky LST using geographically weighted regression (GWR) downscaling and linear model correction, and (2) quantifying the temperature difference (ΔT) caused by cloud radiative effect (CRE) based on surface energy balance (SEB) theory. Validation against in situ LST measurements from the SURFRAD and HiWATER networks indicates that the retrieved cloud-sky LST exhibits a bias of 0.02 K and a root mean square error (RMSE) of 3.77 K. The results confirm that the algorithm achieves reliable retrieval of FY-3D/MERSI-II cloudy-sky LST, with the ΔT correction term making a notable contribution. This method is expected to be used to generate the operational FY-3D cloudy-sky LST product.