Variational data assimilation for a sea dynamics model

Pub Date : 2022-06-01 DOI:10.1515/rnam-2022-0011
V. Agoshkov, V. Zalesny, V. Shutyaev, E. Parmuzin, N. Zakharova
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Abstract

Abstract The 4D variational data assimilation technique is presented for modelling the sea dynamics problems, developed at the Marchuk Institute of Numerical Mathematics of the Russian Academy of Sciences (INM RAS). The approach is based on the splitting method for the mathematical model of sea dynamics and the minimization of cost functionals related to the observation data by solving an optimality system that involves the adjoint equations and observation and background error covariances. Efficient algorithms for solving the variational data assimilation problems are presented based on iterative processes with a special choice of iterative parameters. The technique is illustrated for the Black Sea dynamics model with variational data assimilation to restore the sea surface heat fluxes.
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海洋动力模式的变分资料同化
摘要:4D变分数据同化技术是由俄罗斯科学院马尔丘克数值数学研究所(INM RAS)开发的,用于模拟海洋动力学问题。该方法基于海洋动力学数学模型的分裂方法,并通过求解涉及伴随方程、观测和背景误差协方差的最优性系统,最小化与观测数据相关的成本泛函。基于迭代过程和迭代参数的特殊选择,提出了求解变分数据同化问题的有效算法。利用变分数据同化技术对黑海动力学模型进行了数值模拟,以恢复海面热通量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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