Study on the Fusionand Validation of Sea Surface Height Anomaly Field based on the Radar Altimeters Onboard HY-2C/D Satellites
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摘要: 星载雷达高度计能够定期提供高精度的全球海面高观测,但单星的星下点观测稀疏,为提升中尺度海洋现象的研究能力,对多颗卫星的观测进行融合是最有效的技术手段。本文对HY-2C/D卫星的海面高异常进行了计算,开展基于Jason-3卫星的交叉定标,校正系统偏差,并利用最优插值法,以当前国际上最先进的MIOST海面高异常场作为背景场,生成了南海区域(10°×10°)的海面高异常融合场。在最优插值法最关键的方差-协方差矩阵的构造中,基于HY-2C/D卫星自交叉定标的标准差构造对角线,利用海面高异常功率谱确定相关尺度,进而构造协方差阵元。最后,本文利用我国自主的万山定标场验潮站数据,对融合前后的海面高异常场进行了检验,证明了HY-2C/D数据在提升多源数据融合精度方面的贡献。Abstract: Spaceborne radar altimeters can provide high-precision global sea surface height (SSH) observations regularly. However, the along-track observations from a single satellite are sparse. To enhance research capabilities for mesoscale ocean phenomena, fusing observations from multiple satellites is the most effective technical approach. The HY-2C/D satellites are China's first inclined-orbit altimetry satellites. Their orbital configuration is similar to that of the internationally advanced Jason series satellites, making them particularly suitable as data sources for sea surface height anomaly (SSHA) fusion. Building upon the internationally advanced operational MIOST SSHA fusion product, this study integrates HY-2C/D satellite data to generate a fused SSHA product that incorporates observations from all currently operating satellite radar altimeters, thereby expanding the application scope of the HY-2C/D satellites. The study first calculated the SSHA for the HY-2C/D satellites and performed cross-calibration, including self-cross-calibration and mutual cross-calibration using the Jason-3 satellite as the reference standard, to correct their systematic biases. Subsequently, the Optimal Interpolation (OI) method was employed, using the MIOST SSHA field as the background field, to generate a fused SSHA field for a region (10°×10°) in the South China Sea. In constructing the most critical variance-covariance matrix for the OI method, its diagonal elements were derived from the standard deviations obtained from the HY-2C/D self-cross-calibration, while the correlation scales were determined based on the SSHA power spectrum to construct the covariance matrix elements. Finally, this paper conducted both qualitative and quantitative validation of the fusion results. The qualitative analysis was primarily based on geographical distribution maps of SSHA before and after fusion; a comparison reveals that additional eddies were identified in the fused product. Quantitative analysis utilized tidal gauge data from China's independent Wanshan Calibration Site as validation data. The assessment of the SSHA fields before and after fusion demonstrated the contribution of HY-2C/D data in improving the accuracy of multi-source data fusion.
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