A dual-weighted trust-region adaptive POD 4D-VAR applied to a finite-element shallow-water equations model

被引:21
作者
Chen, X. [2 ]
Navon, I. M. [1 ]
Fang, F. [3 ]
机构
[1] Florida State Univ, Dept Comp Sci, Tallahassee, FL 32306 USA
[2] Florida State Univ, Dept Math, Tallahassee, FL 32306 USA
[3] Univ London Imperial Coll Sci Technol & Med, Dept Earth Sci & Engn, Appl Modelling & Computat Grp, London SW7 2AZ, England
基金
美国国家科学基金会; 英国自然环境研究理事会;
关键词
proper orthogonal decomposition; 4-D VAR; shallow water equations; dual weighting; trust-region method; inverse problem; PROPER ORTHOGONAL DECOMPOSITION; VARIATIONAL DATA ASSIMILATION; STATISTICAL VARIABLES; PRIMITIVE EQUATIONS; REDUCTION; COMPLEX;
D O I
10.1002/fld.2198
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
We consider a limited-area finite-element discretization of the shallow-water equations model. Our purpose in this paper is to solve an inverse problem for the above model controlling its initial conditions in presence of observations being assimilated in a time interval (window of assimilation). We then attempt to obtain a reduced-order model of the above inverse problem, based on proper orthogonal decomposition (POD), referred to as POD 4-D VAR. Different approaches of POD implementation of the reduced inverse problem are compared, including a dual-weighed method for snapshot selection coupled with a trust-region POD approach. Numerical results obtained point to an improved accuracy in all metrics tested when dual-weighing choice of snapshots is combined with POD adaptivity of the trust-region type. Results of ad-hoc adaptivity of the POD 4-D VAR turn out to yield less accurate results than trust-region POD when compared with high-fidelity model. Directions of future research are finally outlined. (C) Copyright 2009 John Wiley & Sons, Ltd.
引用
收藏
页码:520 / 541
页数:22
相关论文
共 65 条
[11]   THE PROPER ORTHOGONAL DECOMPOSITION IN THE ANALYSIS OF TURBULENT FLOWS [J].
BERKOOZ, G ;
HOLMES, P ;
LUMLEY, JL .
ANNUAL REVIEW OF FLUID MECHANICS, 1993, 25 :539-575
[12]   Goal-oriented, model-constrained optimization for reduction of large-scale systems [J].
Bui-Thanh, T. ;
Willcox, K. ;
Ghattas, O. ;
Waanders, B. van Bloemen .
JOURNAL OF COMPUTATIONAL PHYSICS, 2007, 224 (02) :880-896
[13]   A reduced-order approach to four-dimensional variational data assimilation using proper orthogonal decomposition [J].
Cao, Yanhua ;
Zhu, Jiang ;
Navon, I. M. ;
Luo, Zhendong .
INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN FLUIDS, 2007, 53 (10) :1571-1583
[14]   Reduced-order modeling of the upper tropical Pacific Ocean model using proper orthogonal decomposition [J].
Cao, Yanhua ;
Zhu, Jiang ;
Luo, Zhendong ;
Navon, I. M. .
COMPUTERS & MATHEMATICS WITH APPLICATIONS, 2006, 52 (8-9) :1373-1386
[15]  
Celis M.R., 1985, NUMERICAL OPTIMIZATI, P71
[16]  
Chen X, 2009, STUD INFORM CONTROL, V18, P41
[17]   A dual-weighted approach to order reduction in 4DVAR data assimilation [J].
Daescu, D. N. ;
Navon, I. M. .
MONTHLY WEATHER REVIEW, 2008, 136 (03) :1026-1041
[18]   Efficiency of a POD-based reduced second-order adjoint model in 4D-Var data assimilation [J].
Daescu, D. N. ;
Navon, I. M. .
INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN FLUIDS, 2007, 53 (06) :985-1004
[19]  
DENNIS JE, 1978, P S APPL MATH, V22, P19
[20]  
FAHL M, 2000, THESIS TRIER U