Variational data assimilation for a sea dynamics model

被引：1

作者：

Agoshkov, Valery ^{[1
,2
]}

Zalesny, Vladimir ^{[1
]}

Shutyaev, Victor ^{[1
,3
]}

Parmuzin, Eugene ^{[1
,3
]}

Zakharova, Natalia ^{[1
]}

机构：

[1] Russian Acad Sci, Marchuk Inst Numer Math, Moscow 119333, Russia

[2] Lomonosov Moscow State Univ, Moscow 119991, Russia

[3] Moscow Inst Phys & Technol, Dolgoprudnyi 141701, Russia

来源：

RUSSIAN JOURNAL OF NUMERICAL ANALYSIS AND MATHEMATICAL MODELLING | 2022年 / 37卷 / 03期

基金：

俄罗斯科学基金会;

关键词：

Sea dynamics modelling; variational data assimilation; observations; sea surface temperature; OCEAN CIRCULATION; SIMULATION; ALGORITHM;

D O I：

10.1515/rnam-2022-0011

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

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.

引用

页码：131 / 142

页数：12

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