High-Resolution Sea Surface Temperature Retrieval from GF5-02 VIMI Data Using A Nonlinear Split-Window Algorithm

Sea Surface Temperature (SST) is a pivotal parameter in studying the energy balance and material exchange between the ocean and the atmosphere. Obtaining high-precision SST is of significant importance for a deep understanding of the dynamic changes in the ocean and atmospheric systems. This study utilized a nonlinear split-window algorithm for deriving 40m SST from Chinese Gaofen5-02 (GF5-02) Visible and Infrared Multispectral Imager (VIMI). The coefficients of the algorithm were simulated utilizing the MODTRAN 5.2 atmospheric radiative transfer model and the global atmospheric profile library of SeeBor V5.0. The retrieved VIMI SST was validated using iQuam SST measurements (in-situ measurements) and the MODIS SST products. The results of the cross-validation demonstrate a reasonable accuracy of the produced VIMI SST products, exhibiting a bias of 1.34 K and an RMSE of 2.68 K.