On the variational data assimilation problem solving and sensitivity analysis

被引：27

作者：

Arcucci, Rossella ^{[1
,2
,3
]}

D'Amore, Luisa ^{[1
,2
]}

Pistoia, Jenny ^{[4
]}

Toumi, Ralf ^{[3
]}

Murli, Almerico ^{[2
,5
]}

机构：

[1] Univ Naples Federico II, Naples, Italy

[2] Euromediterranean Ctr Climate Change, Lecce, Italy

[3] Imperial Coll London, London, England

[4] Natl Inst Geophys & Volcanol, Bologna, Italy

[5] Southern Partnership Adv Computat Infrastruct, Bologna, Italy

来源：

JOURNAL OF COMPUTATIONAL PHYSICS | 2017年 / 335卷

关键词：

Data Assimilation; Sensitivity analysis; Inverse Problem; LAPLACE TRANSFORM INVERSION; CONDITION NUMBER; REGULARIZATION; IMPLEMENTATION;

D O I：

10.1016/j.jcp.2017.01.034

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

We consider the Variational Data Assimilation (VarDA) problem in an operational framework, namely, as it results when it is employed for the analysis of temperature and salinity variations of data collected in closed and semi closed seas. We present a computing approach to solve the main computational kernel at the heart of the VarDA problem, which outperforms the technique nowadays employed by the oceanographic operative software. The new approach is obtained by means of Tikhonov regularization. We provide the sensitivity analysis of this approach and we also study its performance in terms of the accuracy gain on the computed solution. We provide validations on two realistic oceanographic data sets. (C) 2017 Elsevier Inc. All rights reserved.

引用

页码：311 / 326

页数：16

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