The Ensemble Kalman Filter: Theoretical formulation and practical implementation

被引:352
作者
Geir Evensen
机构
[1] Nansen Environmental and Remote Sensing Center, 5059 Solheimsviken
关键词
Data assimilation; Ensemble Kalman Filter;
D O I
10.1007/s10236-003-0036-9
中图分类号
学科分类号
摘要
The purpose of this paper is to provide a comprehensive presentation and interpretation of the Ensemble Kalman Filter (EnKF) and its numerical implementation. The EnKF has a large user group, and numerous publications have discussed applications and theoretical aspects of it. This paper reviews the important results from these studies and also presents new ideas and alternative interpretations which further explain the success of the EnKF. In addition to providing the theoretical framework needed for using the EnKF, there is also a focus on the algorithmic formulation and optimal numerical implementation. A program listing is given for some of the key subroutines. The paper also touches upon specific issues such as the use of nonlinear measurements, in situ profiles of temperature and salinity, and data which are available with high frequency in time. An ensemble based optimal interpolation (EnOI) scheme is presented as a cost-effective approach which may serve as an alternative to the EnKF in some applications. A fairly extensive discussion is devoted to the use of time correlated model errors and the estimation of model bias. © Springer-Verlag 2003.
引用
收藏
页码:343 / 367
页数:24
相关论文
共 73 条
[1]  
Allen J.I., Eknes M., Evensen G., An Ensemble Kalman Filter with a complex marine ecosystem model: Hindcasting phytoplankton in the Cretan Sea, Annal Geophys, 20, pp. 1-13, (2002)
[2]  
Anderson J.L., An ensemble adjustment Kalman filter for data assimilation, Mon Weather Rev, 129, pp. 2884-2903, (2001)
[3]  
Anderson J.L., A local least-squares framework for ensemble filtering, Mon Weather Rev, 131, pp. 634-642, (2003)
[4]  
Anderson J.L., Anderson S.L., A Monte Carlo implementation of the nonlinear filtering problem to produce ensemble assimilations and forecasts, Mon Weather Rev, 127, pp. 2741-2758, (1999)
[5]  
Bennett A.F., Inverse Methods in Physical Oceanography, (1992)
[6]  
Bennett A.F., Inverse Modeling of the Ocean and Atmosphere, (2002)
[7]  
Bennett A.F., Chua B.S., Open-ocean modeling as an inverse problem: The primitive equations, Mon Weather Rev, 122, pp. 1326-1336, (1994)
[8]  
Bennett A.F., Leslie L.M., Hagelberg C.R., Powers P.E., Tropical cyclone prediction using a barotropic model initialized by a generalized inverse method, Mon Weather Rev, 121, pp. 1714-1729, (1993)
[9]  
Bennett A.F., Chua B.S., Leslie L.M., Generalized inversion of a global numerical weather prediction model, Meteorol Atmos Phys, 60, pp. 165-178, (1996)
[10]  
Bertino L., Evensen G., Wackernagel H., Combining geostatistics and Kalman filtering for data assimilation in an estuarine system, Inverse Methods, 18, pp. 1-23, (2002)