Variational assimilation with covariance matrices of observation data errors for the model of the Baltic Sea dynamics

被引：5

作者：

Agoshkov, Valery I. ^{[1
]}

Parmuzin, Eugene I. ^{[1
,2
]}

Zakharova, Natalia B. ^{[1
,2
]}

Shutyaev, Victor P. ^{[1
,2
]}

机构：

[1] RAS, Inst Numer Math, Moscow 119333, Russia

[2] Moscow Inst Phys & Technol, Dolgoprudnyi 141701, Moscow Region, Russia

来源：

RUSSIAN JOURNAL OF NUMERICAL ANALYSIS AND MATHEMATICAL MODELLING | 2018年 / 33卷 / 03期

基金：

俄罗斯科学基金会; 俄罗斯基础研究基金会;

关键词：

Variational assimilation; covariance matrices; numerical algorithm; determination of heat fluxes; sea surface temperature; OCEAN CIRCULATION; SIMULATION;

D O I：

10.1515/rnam-2018-0013

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

The mathematical model of the Baltic Sea dynamics developed at the Institute of Numerical Mathematics of RAS is considered. The problem of variational assimilation of average daily data for the sea surface temperature (SST) is formulated and studied with the use of covariance matrices of observation data errors. Based on variational assimilation of satellite observation data, we propose an algorithm for solving the inverse problem of the heat flux reconstruction on the sea surface. The results of numerical experiments on reconstruction of the heat flux function are presented for the problem of variational assimilation of observation SST data.

引用

页码：149 / 160

页数：12

共 19 条

[1] Numerical Algorithm for Variational Assimilation of Sea Surface Temperature Data [J].