The impact of background error on incomplete observations for 4D-Var data assimilation with the FSU GSM

被引：0

作者：

Navon, IM ^{[1
]}

Daescu, DN

Liu, Z

机构：

[1] Florida State Univ, Sch Computat Sci & Informat Technol, Tallahassee, FL 32306 USA

[2] Portland State Univ, Dept Math & Stat, Portland, OR 97207 USA

来源：

COMPUTATIONAL SCIENCE - ICCS 2005, PT 2 | 2005年 / 3515卷

关键词：

data assimilation; incomplete observations; background error;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

To assess the impact of incomplete observations on the 4D-Var data assimilation, twin experiments were carried out with the dynamical core of the new FSU GSM consisting of a T126L14 global spectral model in a MPI parallel environment. Results and qualitative aspects are presented for incomplete data in the spatial dimension and for incomplete data in time, with and without inclusion of the background term into the cost functional. The importance of the background estimate on the 4D-Var analysis in the presence of small Gaussian errors in incomplete data is also investigated.

引用

页码：837 / 844

页数：8

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