Title :
Ensemble Kalman filter
Author :
Lakshmivarahan, S. ; Stensrud, David J.
Author_Institution :
Univ. of Oklahoma, Norman, OK
fDate :
6/1/2009 12:00:00 AM
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;
Journal_Title :
Control Systems, IEEE
DOI :
10.1109/MCS.2009.932225
