Inversion of Sea Surface Flow Field in Southern South China Sea Based on Satellite Remote Sensing Data
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摘要: 海表流场可直接影响海表的气候变化，且对于研究海气相互作用、热通量输送等具有重要意义.通过利用Jason-2号与HY-2号卫星高度计数据以及Metop卫星的ASCAT与HY-2号卫星散射计数据反演海表流场.利用距离加权平均法生成分辨率为0.25°×0.25°的网格，通过数据融合分别得到海表高度场与海面风场，在此基础上构建地转流和Ekman流反演数学模型.利用Jason-2与HY-2号卫星高程计数据反演地转流，利用ASCAT与HY-2号卫星散射计数据得出风应力驱动的Ekman流，合并两者得到海表流场.通过对研究海域海表流速的反演结果与OSCAR海流产品的对比分析，发现越靠近赤道的位置，其流速误差较大，最大相对误差达到了0.6 m/s.实验结果表明利用卫星遥感数据反演海洋表层流场能较为准确地表现实际海表流场的基本特征.Abstract: The sea surface flow field can directly affect the climate change of the sea surface,and is of great significance to the study of air-sea interaction and heat flux transfer. This paper uses altimeter data from Jason-2 and HY-2 satellite,scatterometer data from ASCAT of Metop and HY-2 satellite to estimate the sea surface flow field. The grid with resolution of 0.25°×0.25° is generated by the method of weighted average distance,the sea surface elevation field and wind field are obtained by data fusing. On this basis,the inversion mathematical models of the geostrophic flow and the Ekman flow are constructed. The geostrophic flow is retrieved from Jason-2 and Hy-2 altimeter data,and the wind-driven Ekman flow is obtained from the ASCAT and Hy-2 scatterometer data,the combination of both date results in the sea surface flow field. By comparing the inversion results of the sea surface flow in the study area with OSCAR current products,it is found that the closer to the equator,the greater the error of the velocity of the sea surface flow. The maximum relative error reached 0.6 m/s. The experimental results show that the sea surface flow field estimated by satellite remote sensing data can exactly describe the basic characters of actual sea surface flow field.
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图 1 研究海域地理位置
地图取自自然资源部网站《中国地图 1:4 200万32开》，审图号：GS（2016）1545号
Fig. 1. Geographical location of the study area
图 13 经验模型与OSCAR海流u相对误差
Fig. 13. u relative error of sea flow between empirical model and OSCAR
图 14 经验模型与OSCAR海流v相对误差
Fig. 14. v relative error of sea flow between empirical model and OSCAR
表 1 高程计数据融合
Table 1. Altimeter data fusion
Jason⁃2 Value1 Value1 Nan Nan HY⁃2 Value2 Nan Value2 Nan 融合处理 加权平均 Value1 Value2 Nan 
下载: 导出CSV
表 2 散射计数据融合
Table 2. Scatterometer data fusion
ASCAT Value1 Value1 Nan Nan HY⁃2 Value2 Nan Value2 Nan 融合处理 加权平均 Value1 Value2 Nan
下载: 导出CSV
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