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热带海洋学报

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基于近海浮标与ERA5的海洋一号C/D卫星海表温度一致性检验及算法升级评估

吴彬锋1, 2, 林志佳1, 2, 孙澍亭3*, 叶小敏4, 王峥1, 2

  

  1. 1. 卫星海洋环境监测预警全国重点实验室(国家海洋环境预报中心), 北京 100081;

    2. 自然资源部海洋灾害预报重点实验室, 北京 100081;

    3. 交通运输部水运科学研究院, 北京 100088;

    4. 国家卫星海洋应用中心, 北京 100081


  • 收稿日期:2026-07-10 修回日期:2026-08-25 接受日期:2026-09-04
  • 通讯作者: 孙澍亭
  • 基金资助:

    国家重点研发计划(2023YFC3107900)

Consistency validation and algorithm-upgrade assessment of HY-1C/1D sea surface temperature using coastal buoys and ERA5

WU Binfeng1,2, LIN Zhijia1,2, SUN Shuting3*, YE Xiaomin4, WANG Zheng1,2    

  1. 1. State Key Laboratory of Satellite Ocean Environment Dynamics, National Marine Environmental Forecasting Center, Beijing 100081, China;

    2. Key Laboratory of Marine Hazards Forecasting, Ministry of Natural Resources, Beijing 100081, China;

    3. China Waterborne Transport Research Institute, Beijing 100088, China;

    4. National Satellite Ocean Application Service, Beijing 100081, China


  • Received:2026-07-10 Revised:2026-08-25 Accepted:2026-09-04
  • Supported by:

     National Key Research and Development Program of China (2023YFC3107900)

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摘要： 近海海表温度(SST)广泛应用于赤潮监测、渔业资源评估、海洋灾害预报及数值同化等业务, 产品精度与时间序列稳定性直接决定其业务可信度。海洋一号C/D星(HY-1C/D)搭载同型海洋水色水温扫描仪(COCTS), 是我国自主SST遥感的重要数据源; 受在轨仪器漂移与云/质量阈值判识异常影响, HY-1C的SST反演长期存在随海温、纬度和季节变化的系统性冷偏差, 其业务反演算法已于2025年10月升级。为独立量化本次升级的效果, 本文以2025年中国近海32个浮标的匹配观测为基准, 以欧洲中期天气预报中心第五代大气再分析数据集(ERA5)海温为独立参照, 提出同温对照方法, 在固定海温条件下比较升级前后的误差, 以剥离季节循环的干扰。结果表明, 升级后HY-1C与HY-1D的均方根误差分别为1.35℃与1.22℃, 双星精度已无明显差距, 晴空核区的稳健标准差进入亚度级, 可满足近海业务应用的一般需求; 受限于COCTS仅有的两个热红外通道, 其精度与配备中红外通道的国际主流红外传感器相比仍有差距。同温对照显示各海温区间的稳健标准差成倍下降, ERA5交叉验证与浮标检验结论一致, 证实精度增益源自算法优化而非季节循环。统计后处理订正仅能削减部分系统偏差, 效能远逊于源头算法升级。受观测时段所限, 高海温条件下的精度仍有待夏季观测的进一步检验。

关键词: 海表温度, 海洋一号卫星, 近海遥感, 同温对照, 辐射漂移, 分裂窗反演

Abstract: Coastal sea surface temperature (SST) supports operational applications such as red-tide monitoring, fishery-resource assessment, marine-disaster forecasting and data assimilation, for which product accuracy and time-series stability are decisive. HY-1C and HY-1D carry the same Chinese Ocean Colour and Temperature Scanner (COCTS) and are a crucial source of China's independent SST remote sensing. However, owing to on-orbit instrument drift and anomalies in the cloud/quality threshold tests, HY-1C SST had long exhibited a systematic cold bias varying with SST, latitude and season, and the operational retrieval algorithm underwent an upgrade in October 2025. To quantify the improvement independently, we use 2025 matchups with 32 buoys over the Chinese coastal seas, adopt European Centre for Medium-Range Weather Forecasts Reanalysis V5 (ERA5) SST as an independent reference, and apply a matched-temperature method that compares pre-upgrade (January–September) and post-upgrade (October–December) errors based on the matched-temperature method, thereby removing the seasonal cycle from the assessment. After the upgrade of the operational retrieval algorithm, the root mean square error (RMSE) reached 1.35 °C and 1.22 °C for HY-1C and HY-1D, respectively, leaving no substantial gap between the two satellites, and the robust standard deviation of the clear-sky core fell below 1 °C; the accuracy nevertheless still trails that of infrared sensors equipped with mid-infrared channels. At equal SST values the robust standard deviation decreased in every interval and the ERA5 cross-validation reproduced the buoy results, confirming that the improvement originated from the algorithm, not from seasonal variations. A statistical post-processing correction removed only part of the systematic bias and proved far less effective than the source-level upgrade. Since the post-upgrade data cover only autumn and winter, the retrieval accuracy under high-SST conditions still requires further validation with summer observations.

Key words: sea surface temperature, HY-1 satellite, coastal remote sensing, matched-temperature method, radiometric drift, split-window retrieval