Ensemble Kalman filter

Author

Lakshmivarahan, S. ; Stensrud, David J.

Author_Institution

Univ. of Oklahoma, Norman, OK

Volume

29

Issue

3

fYear

2009

fDate

6/1/2009 12:00:00 AM

Firstpage

34

Lastpage

46

Abstract

Meteorological models are used to predict the weather, study atmospheric processes, and provide input to decision makers on the consequences of increased greenhouse gas emissions to the Earth´s climate. Predictions of future atmospheric states are accomplished as an initial value or marching problem, where the initial atmospheric state is specified and the variables are advanced in time using numerical techniques. The challenge of data assimilation in meteorology is to estimate, based on a set of limited observations of varying types, the complete three-dimensional atmospheric state at a given time to provide an initial value for a meteorological model.

Keywords

Kalman filters; data assimilation; decision making; geophysical signal processing; weather forecasting; Earth climate; atmospheric process; atmospheric state prediction; decision making; ensemble Kalman filter; greenhouse gas emission; marching problem; meteorological data assimilation model; numerical technique; weather prediction; Atmospheric modeling; Data assimilation; Meteorology; Ocean temperature; Predictive models; Radar remote sensing; Satellite broadcasting; Sea surface; Spaceborne radar; State estimation;

fLanguage

English

Journal_Title

Control Systems, IEEE

Publisher

ieee

ISSN

1066-033X

Type

jour

DOI

10.1109/MCS.2009.932225

Filename

4939310