A Three-Dimensional Variational Analysis Using Sequential Filter

Author

Wu, Xinrong ; Han, Guijun ; Li, Dong ; Li, Wei

Author_Institution

South China Sea Inst. of Oceanol., Chinese Acad. of Sci., Guangzhou, China

fYear

2011

fDate

15-19 April 2011

Firstpage

1016

Lastpage

1020

Abstract

A three-dimensional variational (3D-Var) data assimilation (DA) scheme which introduces sequential filter is designed to improve state estimation from observations. The sequential filter employed in this new hybrid scheme, operating on the background field instead of on the observation field as usual, is under the framework of ensemble adjustment Kalman filter (EAKF). Under perfect global barotropic spectral model, numerical experiments show that the new 3D-Var can retrieve structures of true field appropriately and outperforms traditional 3D-Var.

Keywords

Kalman filters; data assimilation; variational techniques; data assimilation scheme; ensemble adjustment Kalman filter; global barotropic spectral model; sequential filter; state estimation; three-dimensional variational analysis; Covariance matrix; Data assimilation; Filtering theory; Information filters; Kalman filters; Numerical models; Time series analysis; 3D-Var; data assimilation; sequential filter;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Sciences and Optimization (CSO), 2011 Fourth International Joint Conference on

Conference_Location

Yunnan

Print_ISBN

978-1-4244-9712-6

Electronic_ISBN

978-0-7695-4335-2

Type

conf

DOI

10.1109/CSO.2011.60

Filename

5957829