Statistical Distribution of Characteristics of the Model Solution after Data Assimilation

IF 0.8 Q2 MATHEMATICS
A. Kuleshov, K. Belyaev, I. Smirnov, N. Tuchkova
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引用次数: 0

Abstract

The probability distribution of several characteristics, in particular, sea surface and subsurface temperature and sea salinity simulated by the ocean circulation model of Nucleus for European Modeling of the Ocean in conjunction with data assimilation are determined. The data assimilation method, called as the Generalized Kalman filter method developed by the authors earlier and published in a number of studies is used. For assimilation the Agro drifter data have been applied for different model levels from sea surface until 2000 m. In order to define the probability distribution of sought model characteristics the Karhunen–Loeve decomposition of the covariance function has been utilized. The results of numerical experiments have been presented and analyzed.

Abstract Image

数据同化后模型解决方案特征的统计分布
摘要 确定了欧洲海洋建模核心的海洋环流模型与数据同化相结合模拟的若干特征的概率分布,特别是海表和海下温度以及海水盐度的概率分布。使用的数据同化方法称为广义卡尔曼滤波法,由作者早先开发并在多项研究中发表。为了确定所寻求模型特征的概率分布,使用了协方差函数的卡尔胡宁-洛夫分解法。对数值实验结果进行了介绍和分析。
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来源期刊
CiteScore
1.50
自引率
42.90%
发文量
127
期刊介绍: Lobachevskii Journal of Mathematics is an international peer reviewed journal published in collaboration with the Russian Academy of Sciences and Kazan Federal University. The journal covers mathematical topics associated with the name of famous Russian mathematician Nikolai Lobachevsky (Lobachevskii). The journal publishes research articles on geometry and topology, algebra, complex analysis, functional analysis, differential equations and mathematical physics, probability theory and stochastic processes, computational mathematics, mathematical modeling, numerical methods and program complexes, computer science, optimal control, and theory of algorithms as well as applied mathematics. The journal welcomes manuscripts from all countries in the English language.
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