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热带海洋学报

• • 上一篇    

基于逐步订正的国产卫星遥感海表温度数据融合

牛浩然1, 2, 王喜冬1, 2, 高振博1, 2, 陈志强3   

  1. 1. 河海大学, 自然资源部海洋灾害预报技术重点实验室, 江苏 南京 210024;

    2. 河海大学, 海洋学院, 江苏 南京 210024;

    3. 中国科学院南海海洋研究所, 广东 广州 510301

  • 收稿日期:2025-01-25 修回日期:2025-03-18 接受日期:2025-04-07
  • 通讯作者: 王喜冬
  • 基金资助:

    国家自然科学基金（41776004）

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 Accepted:2025-04-07
  • Supported by:

    National Natural Science Foundation of China (41776004)

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摘要： 海表温度（sea surface temperature，SST）作为大气海洋圈层的重要环境变量之一，对于海洋学的研究具有重要意义。本文基于国产海洋和风云卫星遥感SST数据，利用逐步订正数据融合方法，研制了“海上丝绸之路”沿线海域自主化、高时空分辨率卫星SST融合产品。首先利用iQuam实测数据开展了海洋卫星和风云卫星的SST观测数据精度评估，发现风云卫星数据SST观测精度整体优于海洋卫星，同时对HY-1系列卫星进行了偏差校正；接着，利用HY-1C COCTS、HY-1D COCTS、HY-2B SMR、FY-3D MWRI、FY-3E MERSI和FY-4B AGRI的SST数据以及多尺度逐步订正融合算法，制作了2024年4月-6月“海上丝绸之路”沿线海域逐日0.1°×0.1°分辨率SST融合产品；最后，利用iQuam实测数据评估了融合产品精度。结果发现，融合产品平均偏差为0.0776℃，均方根误差为0.6712℃，产品精度较好。不同SST融合产品的功率谱分析结果表明，本文生成的SST融合产品较OISST产品在刻画100千米以小尺度特征上更有优势，与OSTIA产品在50至100千米尺度上性能相当，体现了融合产品良好的应用潜力。

关键词: 海表温度, 国产卫星, 逐步订正, 数据融合

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