Hessian-based covariance approximations in variational data assimilation

被引：6

作者：

Gejadze, Igor Yu. ^{[1
]}

Shutyaev, Victor P. ^{[2
,3
]}

Le Dimet, Francois-Xavier ^{[4
]}

机构：

[1] IRSTEA Montpellier, UMR G EAU, 361 Rue JF Breton,BP 5095, F-34196 Montpellier, France

[2] Russian Acad Sci, Inst Numer Math, Gubkina 8, Moscow 119333, Russia

[3] RAS, Inst Marine Hydrophys, Fed State Budget Sci Inst, Kapitanskaya 2, Sevastopol 299011, Russia

[4] Univ Grenoble Alpes, BP 51, F-38051 Grenoble 9, France

来源：

RUSSIAN JOURNAL OF NUMERICAL ANALYSIS AND MATHEMATICAL MODELLING | 2018年 / 33卷 / 01期

基金：

俄罗斯科学基金会;

关键词：

Variational data assimilation; optimality system; Hessian; estimation error covariance; ERROR COVARIANCES; METEOROLOGICAL OBSERVATIONS; OPERATIONAL IMPLEMENTATION;

D O I：

10.1515/rnam-2018-0003

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

The problem of variational data assimilation (estimation) for a nonlinear model is considered in general operator formulation. Hessian-based methods are presented to compute the estimation error covariances. The importance of dynamic formulation and the role of the Hessian and its inverse are discussed.

引用

页码：25 / 39

页数：15

共 38 条

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