Journal of Tropical Oceanography ›› 2025, Vol. 44 ›› Issue (6): 1-11.doi: 10.11978/2025015CSTR: 32234.14.2025015

Special Issue: 海洋大数据及应用

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Domestic satellite sea surface temperature data fusion based on successive corrections*

NIU Haoran1,2(), WANG Xidong1,2(), GAO Zhenbo1,2, CHEN Zhiqiang3   

  1. 1 Key Laboratory of Marine Hazards Forecasting, Ministry of Natural Resources, Hohai University, Nanjing 210024, China
    2 College of Oceanography, Hohai University, Nanjing 210024, China
    3 South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China
  • Received:2025-01-25 Revised:2025-03-18 Online:2025-11-10 Published:2025-12-03
  • Contact: WANG Xidong. email:
  • Supported by:
    National Natural Science Foundation of China(41776004)

Abstract:

As one of the important environmental variables in the atmosphere-ocean system, sea surface temperature (SST) is of significant importance for oceanographic research. This paper utilizes domestic HaiYang (HY) and FengYun (FY) satellites remote sensing SST data to develop an autonomous, high spatiotemporal resolution satellite SST fusion product for the “Maritime Silk Road” region using the successive corrections method. First, the accuracy of SST observation data from HY and FY satellites was evaluated using iQuam in-situ data, with bias correction performed on HY-1C and HY-1D. Next, SST data from HY-1C, HY-1D, HY-2B, FY-3D, FY-3E, and FY-4B, 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 fusion product had an average bias of 0.08°C and a root mean square error (RMSE) of 0.67°C, indicating good accuracy. Power spectral analysis of different SST fusion products demonstrated that the SST fusion product generated in this study outperforms the Optimum Interpolation Sea Surface Temperature (OISST) in capturing small-scale features at the 100 km scale and shows comparable performance to the Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) at the 50-100 km scale, reflecting its good application potential.

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

CLC Number: 

  • P714.1