摘要
早期海洋资料同化仅考虑温度的调整而忽略盐度的变化,这往往会带来虚假信息,可能导致密度场被严重恶化,同化后的结果甚至比没有同化任何观测资料时还要差。为了解决这个问题,海洋资料同化中的一些温、盐度多变量调整方案便被提出来了。本文对广泛应用于多变量分析的资料同化方法及不同温、盐度多变量调整方案进行了系统的回顾,对它们的优缺点进行了分析与讨论,并指出了不同调整方案的适用条件及应用现状,最后对Argo资料在海洋资料同化中的重要性及今后的研究重点进行了探讨。
Early ocean data assimilation only considered temperature adjustment and ignored the salinity chang- es, which often brings false information and lead to density field deteriorated seriously. The assimilation results were even worse than that without assimilating any observation data. In order to solve this problem, some multi- variable assimilation schemes for temperature and salinity were brought up. In this paper, we reviewed the data assimilation methods widely used in multivariate analysis and different temperature and salinity adjustment schemes, discussed the advantages and disadvantages of them, and pointed out their application situation respec- tively. Finally, the importance of Argo data and the key research of future data assimilation were discussed in this paper.
出处
《海洋预报》
北大核心
2013年第1期86-92,共7页
Marine Forecasts
基金
海洋公益性专项(201005033)
科技基础性工作专项(2012FY112300)
国家海洋局第二海洋研究所基本科研业务费专项(JT0904)
