Four-dimensional variational data assimilation for high resolution nested models

被引：8
|
作者：
Baxter, G. M. [1 ]
Dance, S. L. [1 ]
Lawless, A. S. [1 ]
Nichols, N. K. [1 ]
机构：
[1] Univ Reading, Dept Math, Reading RG6 6AX, Berks, England
来源：
COMPUTERS & FLUIDS | 2011年 / 46卷 / 01期
关键词：
Advection-diffusion equation; Sine transform; 4D-Var; FORMULATION;
D O I：
10.1016/j.compfluid.2011.01.023
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
Four-dimensional variational data assimilation (4D-Var) is used in environmental prediction to estimate the state of a system from measurements. When 4D-Var is applied in the context of high resolution nested models, problems may arise in the representation of spatial scales longer than the domain of the model. In this paper we study how well 4D-Var is able to estimate the whole range of spatial scales present in one-way nested models. Using a model of the one-dimensional advection-diffusion equation we show that small spatial scales that are observed can be captured by a 4D-Var assimilation, but that information in the larger scales may be degraded. We propose a modification to 4D-Var which allows a better representation of these larger scales. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码：137 / 141
页数：5
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