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Application of altimetry data assimilation on mesoscale eddies simulation

查看全文 作  者:GAO [1]Shan;WANG [1]Fan;LI [1]MingKui;CHEN [1]YongLi;YAN [2]ChangXiang;ZHU [2]Jiang 高影响力作者 机构地区:[1]Institute of Oceanology,Chinese Academy of Sciences,Qingdao 266071,China;[2]Institute of Atmospheric Physics,Chinese Academy of Sciences,Beijing 100029,China高影响力机构 出  处:《Science China Earth Sciences》索引2008年第51卷第1期,共10页高影响力期刊 基  金:the National Natural Science Foundation of China (Grant Nos. 40506010 and 40576016);the National Basic Research Program (Grant No. 2006CB403601);the Knowledge Innovation Program of the Chinese Academy of Sciences (Grant Nos. KZCX3-SW-222 and KZCX2-YW-208) 摘  要:Mesoscale eddy plays an important role in the ocean circulation. In order to improve the simulation accuracy of the mesoscale eddies, a three-dimensional variation (3DVAR) data assimilation system called Ocean Variational Analysis System (OVALS) is coupled with a POM model to simulate the mesoscale eddies in the Northwest Pacific Ocean. In this system, the sea surface height anomaly (SSHA) data by satellite altimeters are assimilated and translated into pseudo temperature and salinity (T-S) profile data. Then, these profile data are taken as observation data to be assimilated again and produce the three-dimensional analysis T-S field. According to the characteristics of mesoscale eddy, the most appropriate assimilation parameters are set up and testified in this system. A ten years mesoscale eddies simulation and comparison experiment is made, which includes two schemes: assimilation and non-assimilation. The results of comparison between two schemes and the observation show that the simulation accuracy of the assimilation scheme is much better than that of non-assimilation, which verified that the altimetry data assimilation method can improve the simulation accuracy of the mesoscale dramatically and indicates that it is possible to use this system on the forecast of mesoscale eddies in the future. 关 键 词:MESOSCALE EDDIES ALTIMETRY DATA ASSIMILATION OVALS
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