海洋学研究 ›› 2022, Vol. 40 ›› Issue (2): 10-18.DOI: 10.3969-j.issn.1001-909X.2022.02.002

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基于DINEOF的风云极轨气象卫星海表温度重构方法研究

  

  1. 1.中国气象局中国遥感卫星辐射测量和定标重点开放实验室,国家卫星气象中心(国家空间天气监测预警中心),北京 100081；
    2.卫星海洋环境动力学国家重点实验室,浙江 杭州 310012； 3.自然资源部第二海洋研究所,浙江 杭州 310012；
    4.许健民气象卫星创新中心,北京 100081
  • 出版日期:2022-06-15 发布日期:2022-06-15

Reconstruction of sea surface temperature from DINEOF-based FY polar-orbiting meteorological satellite

  1. 1.Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, National Satellite Meteorological Center (National Center for Space Weather), China Meteorological Administration, Beijing 100081, China;
    2.State Key Laboratory of Satellite Ocean Environment Dynamics, Hangzhou 310012, China;
    3.Second Institute of Oceanography, MNR, Hangzhou 310012, China;
    4.Innovation Center for FengYun Meteorological Satellite (FYSIC), China Meteorological Administration, Beijing 100081, China
  • Online:2022-06-15 Published:2022-06-15

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摘要：

海表温度是表征海洋表层热力状况的重要海洋参数，日均全天候覆盖的海温观测数据可为服务台风监测及其他海洋灾害时空演变的精细化预报提供数据支撑。可见光红外扫描辐射计和中分辨率光谱成像仪反演的海温产品具有较高的空间分辨率，但是红外遥感反演的海温产品受到云、雾和霾的影响，在云下存在大面积、无规律的缺值；微波辐射计反演的海温产品空间分辨率低，但可穿透云层，实现全天候海温观测。本文基于风云三号B、C、D三颗极轨气象卫星红外和微波遥感仪器反演的海温资料，利用经验正交函数插值法(DINEOF)重构得到全球海表温度产品。与全球分析场日平均海温OISST数据进行比较可知：原始海温资料的均方根误差为0.59~0.70℃，DINEOF重构后海温资料均方根误差降至0.10~0.34℃；相关系数从0.33~0.48提升到0.78~0.98。多传感器重构海温数据空间分布上连续可信，能够监测不同季节的海温变化特征及暖池空间模态。风云三号气象卫星微波遥感的加入显著提升了重构海温的空间连续覆盖率和时间分辨率。


关键词: 海面温度重构, DINEOF方法, 风云三号卫星

Abstract: Sea surface temperature (SST) is the critical factor for depicting the marine thermal distribution. Daily global SST data sets support the typhoon elaborated monitoring and other marine disasters forecast. SST products retrieved by the visible infrared radiometers and mediumresolution imagers have high spatial resolution, while the SST products retrieved by infrared remote sensing are affected by clouds, fog and haze, and therefore a large areas under the clouds are lack of value. SST products retrieved by the microwave radiometer have low spatial resolution, while the microwave could penetrate the cloud layer to achieve all-weather sea surface observation. The data interpolation empirical orthogonal function method (DINEOF) was used to reconstructed the global SST products, and FY-3 (Fengyun 3) SST data sets were applied in this study, which included the SST data sets from the FY-3B/FY-3C Visible and Infra-Red Radiometer, FY-3D Medium Resolution Spectral Imager and FY-3D Micro-Wave Radiation Imager. Accuracy of the reconstructed data sets was verified using OISST measurements to demonstrate the validity and reliability of the DINEOF method. The results show that DINEOF reconstructed sea surface temperature (DSST) data are validated reliable. Root mean square error of the original data is ranging from 0.59 ℃ to 0.70 ℃, while the reconstructed data is relatively stable, ranging from 0.10 ℃ to 0.34 ℃. Correlation coefficient obvious raises from 0.33-0.48 to 0.78-0.98. Multi-sensors reconstructed SST products is continuous and credible in spatial distribution and monitor the variation of warm pool from spring to winter. Addition of FY-3D microwave SST products has significantly improved the spatial continuous distribution and temporal resolution of reconstructed SST.

Key words: SST reconstruction, DINEOF, FY-3 satellites

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