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
收藏
页码：25 / 39
页数：15
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