Variational Data Assimilation Technique in Mathematical Modeling of Ocean Dynamics

被引：8

作者：

Agoshkov, V. I. ^{[1
]}

Zalesny, V. B. ^{[1
]}

机构：

[1] RAS, Inst Numer Math, Moscow 199333, Russia

来源：

PURE AND APPLIED GEOPHYSICS | 2012年 / 169卷 / 03期

基金：

俄罗斯基础研究基金会;

关键词：

Variational data assimilation; ocean dynamics; mathematical models; numerical algorithms; adjoint equations; multicomponent splitting; World ocean circulation; ENSEMBLE KALMAN FILTER; HYDROTHERMODYNAMICS PROBLEM; NUMERICAL ALGORITHM; OBSERVATIONAL DATA; CIRCULATION; SENSITIVITY; SIMULATION;

D O I：

10.1007/s00024-011-0372-5

中图分类号：

P3 [地球物理学]; P59 [地球化学];

学科分类号：

0708 ; 070902 ;

摘要：

Problems of the variational data assimilation for the primitive equation ocean model constructed at the Institute of Numerical Mathematics, Russian Academy of Sciences are considered. The model has a flexible computational structure and consists of two parts: a forward prognostic model, and its adjoint analog. The numerical algorithm for the forward and adjoint models is constructed based on the method of multicomponent splitting. The method includes splitting with respect to physical processes and space coordinates. Numerical experiments are performed with the use of the Indian Ocean and the World Ocean as examples. These numerical examples support the theoretical conclusions and demonstrate the rationality of the approach using an ocean dynamics model with an observed data assimilation procedure.

引用

页码：555 / 578

页数：24

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