海洋水温垂直分布数据同化方法研究

韩桂军; 何柏荣; 马继瑞; 李冬

海洋水温垂直分布数据同化方法研究

1.
国家海洋信息中心, 天津300171;中国科学院海洋研究所, 青岛266071
2.
南开大学数学科学学院, 天津300071
3.
国家海洋信息中心, 天津300171

基金项目: 国家“九五”攀登项目“现代地壳运动和地球动力学研究”C95-04-05;国家自然科学基金49876001

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出版历程
- 收稿日期: 1999-03-23
- 修回日期: 1999-08-25

A study on data assimilation for the vertical distribution of sea temperature

1.
National Marine Data and Information Service, State Oceanic Administration, Tianjin 300171;Institute of Ocenology, Chinese Academy of Sciences, Qingdao 266071
2.
College of Mathematical Science, Nankai University, Tianjin 300071
3.
National Marine Data and Information Service, State Oceanic Administration, Tianjin 300171

摘要

摘要: 以一维海洋水温模型为例,利用伴随法进行海洋观测数据同化试验,以便为水温的数值预报提供较准确的初始场.文中利用泛函的Gâteaux微分和Hilbert空间上伴随算子的概念讨论了连续的伴随模型的建立,并通过选择适当的差分格式离散伴随模型,使其保持连续时的伴随关系,同时给出了水温初始场最优化过程及相应的同化试验数值结果.
- 海洋水温 /
- 数据同化 /
- 伴随法
Abstract: In order to provide more accurate initial field for numerical predict of the sea temperature the adjoins method is used to assimilate the sea temperature observations into one-dimensional sea temperature model in this paper.How to establish the adjoint model is discussed by using the Gâteaux differential of function and the concepts of the adjoint operators in Hibert space.At the same time it is verified that selecting proper finite difference scheme can ensure discrete form remaining the same adjoint relationship to continuous form of the model.The numerical resuits describing the varying sea temperature field are illustr ated.
- Sea temperature /
- data assimilation /
- adjoint method

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参考文献(7)

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Le Dimet F X. Determination of the adjoint of a numerical weather prediction model. Manuscript

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