Argo数据同化方法及其网格化产品研究进展  

Research progress of Argo data assimilation methods and grid products

作　　者：王丹阳 苏涵 张春玲 WANG Danyang;SU Han;ZHANG Chunling(College of marine sciences,Shanghai Ocean University,Shanghai 201306,China;Center for Polar Research,Shanghai Ocean University,Shanghai 201306,China)

机构地区：[1]上海海洋大学海洋科学学院,上海201306 [2]上海海洋大学极地研究中心,上海201306

出　　处：《海洋湖沼通报》2022年第3期158-165,共8页Transactions of Oceanology and Limnology

基　　金：农业部远洋与极地渔业创新重点实验室开放基金项目(A1-0203-00-2017-1)。

摘　　要：正如卫星的出现使海洋表面的观测方式产生了革命性的变革一样,Argo计划的诞生改变了人们对海洋内部的监测手段和方式。目前,由Argo剖面浮标获得的中上层观测剖面已逾200万条,并正以每天数百条的速度在增长,这些资料对于研究全球海洋的温度、盐度、环流及其它们的变化情况(不管时间尺度是几天还是几十年),都将是一个不可或缺的资源。同时,由于Argo浮标具有随波逐流的特性,其观测剖面数据具有空间不均匀性,这对充分有效利用这些海量的观测数据带来一定的局限性。为此,国内外学者借助于一些常用的数据同化方法,研制了包含多个海洋要素、多种分辨率的网格化产品。本文对目前适用于Argo剖面资料的常用数据同化方法、国内外基于Argo观测资料构建的网格化数据产品进行了比较系统地回顾和总结,对比分析了各种同化方法的适用条件和计算效率,以及各种Argo网格化产品的特点,并针对目前Argo资料的观测现状,给出了未来Argo数据同化的研究展望。The birth of Argo project has changed the means and methods of monitoring the interior of the ocean just as the appearance of satellite for the observing ocean surface.Currently,there are more than 2 million observation profiles in the upper and middle layers of oceans obtained by Argo profile buoy.They are growing at the rate of hundreds per day.And these data will be an indispensable resource for studying the temperature,salinity,circular current and their changes of the global oceans(whether on a time scale of several days or decades).At the same time,the Argo buoy has spatial unevenness,which brings some limitations to make full and effective use of these massive observation data.With the help of some common data assimilation methods,scholars have developed grid products with multiple ocean elements and multiple resolutions.This paper systematically reviewed and summarized the common data assimilation methods applicable to Argo profile data and grid data products.The applicable conditions and computational efficiency of various assimilation methods as well as the characteristics of various Argo grid products are compared and analyzed.The future of Argo data assimilation research prospect is given in view of the current observation status of Argo data.

关 键 词：Argo剖面资料 同化方法 网格化产品 

分 类 号：P731[天文地球—海洋科学]