Abstract: Sea surface temperature (SST), as one of the important environmental variables in the atmosphere-ocean system, is of significant importance for oceanographic research. This paper is based on domestic Haiyang and Fengyun satellites remote sensing SST data. It develops an autonomous, high spatiotemporal resolution satellite SST fusion product for the "Maritime Silk Road" region using the successive corrections method. First, SST observation data from Haiyang and Fengyun satellites were evaluated for accuracy using iQuam in-situ data. The results showed that the SST observation accuracy of Fengyun satellites was generally superior to that of the Haiyang satellites. Bias correction was also performed on the HY-1 series satellites. Next, SST data from HY-1C COCTS, HY-1D COCTS, HY-2B SMR, FY-3D MWRI, FY-3E MERSI and FY-4B AGRI, along with a multi-scale successive corrections fusion algorithm, were used to create a daily 0.1° × 0.1° resolution SST fusion product for the "Maritime Silk Road" region from April to June 2024. Finally, the accuracy of the fusion product was assessed using iQuam in-situ data. The results showed that the average bias of the fusion product was 0.0776°C, and the root mean square error (RMSE) was 0.6712°C, indicating good product accuracy. Power spectral analysis of different SST fusion products demonstrated that the SST fusion product generated in this study outperforms OISST in capturing small-scale features at the 100 km scale and shows comparable performance to OSTIA at the 50 to 100 km scale, reflecting the good application potential of the fusion product.

Key words: sea surface temperature, domestic satellite, successive corrections, data fusion