海洋数据同化技术在南海区域的应用研究

Performance of Ocean Data Assimilation Methods in the South China Sea

海洋资料同化是运用所有可获得的信息,尽可能地确定海洋的状态。因而海洋资料同化能有效的将现有的海洋观测融入海洋模式中,提供时空分布更加完善的分析资料。近年来,南海的卫星观测资料以及航次实测资料不断增多,计算机资源不断丰富。利用海洋数据同化方法,这些资料能极大地改善南海海洋数值模拟,为南海区域海洋学研究提供高质量的分析数据。在有关国家科技计划的资助下,中国科学院南海海洋研究所开展了一系列的南海海洋数据同化方面的基础性研究。通过这些研究,在南海海域建立了基于最优插值、集合卡曼滤波、集合卡曼平滑等同化方法的海洋数据同化系统。

Ocean data assimilation is capable of mostly confirming the ocean state through utilization of acquired information.Thus it could effectively apply observations to ocean model to produce analysis product with more complete time-space distribution.With the increasing of satellite remote observation and cruise observation over South China Sea,and the improvement of computational condition,ocean numerical simulations are largely improved by data assimilation,and subsequently provide high qualitative analysis data for SCS regional oceanology research.Under the support of related national technology fund,a series of fundamental research of ocean numerical reanalysis in SCS have been carried out in South China Sea Institute of Oceanology(SCSIO),Chinese Academy of Sciences(CAS),where ocean data reanalysis system based on assimilation methods as optimal interpolation,ENKF and ENKS has been set up.