基于Argo资料的三维盐度场网格化产品重构  

Reconstruction of three-dimensional gridded salinity product based on Argo data

作　　者：张韧[1] 黄志松[1] 王辉赞[1,2] 王桂华[2] 陈大可[2] 

机构地区：[1]解放军理工大学气象学院,江苏南京211101 [2]卫星海洋环境动力学国家重点实验室,浙江杭州310012

出　　处：《解放军理工大学学报（自然科学版）》2012年第3期342-348,共7页Journal of PLA University of Science and Technology(Natural Science Edition)

基　　金：国家973计划资助项目(2007CB816005);中-加国际科技合作资助项目(2008DFA22230)

摘　　要：针对标准化海洋盐度场产品较为匮乏的事实,利用Argo温盐观测剖面与卫星遥感海表温度资料,采用时空权重插值和多变量DINEOF方法,对太平洋区域2000年1月至2008年12月的三维逐周盐度场进行重构。提出的重构方法有2个明显特色,一是采用时空权重插值与多变量DINEOF相结合的方法,弥补了时空权重插值结果中包含缺失数据的不足;二是引入卫星遥感海表温度,弥补了Argo可靠海表数据的缺乏。重构再分析产品与其他观测和数据产品的对比结果表明,重构产品不但能够抓住盐度分布的主要模态特征,而且可表现盐度不同时间尺度的变化特征,为海洋和气候研究提供了一种有用的标准化数据新产品。Aiming at the shortage of standard salinity fields, based on Argo temperature/salinity profiles and salellite-derived sea surface temperature （SST）, a combined technique of spatial-temperal weighted in- terpolation and multivariate data interpolating empirical orthogonal function （MDINEOF） was applied to reconstructing weekly three-dimensional salinity fields in the Pacific Ocean for the period from January 2000 to December 2008. The methodology that was used has two Obvious features： one is the combination of spatial-temporal weighted interpolation and MDINEOF methods to make up for the missing value in the spatial-temporal weighted interpolation, and the other is the inclusion of satellite-derived SST to make up for the lack of reliable surface data from Argo. Comparison with other observations and data products indi- cates that this gridded product captures the main patterns of the salinity distribution as well as its variabili- ty on various time scales, thus providing a useful new dataset for ocean and climate studies.

关 键 词：ARGO资料 多变量DINEOF 盐度 数据重构 时空权重插值 

分 类 号：P717[天文地球—海洋科学] O241.3[理学—计算数学]