Title: Data assimilation for magnetohydrodynamics systems
Authors: Barrero, OB ×
De Moor, Bart
Bernstein, DS #
Issue Date: May-2006
Publisher: Elsevier
Series Title: Journal of Computational and Applied Mathematics vol:189 issue:1-2 pages:242-259
Abstract: Prediction of solar storms has become a very important issue due to the fact that they can affect dramatically the telecommunication and electrical power systems at the earth. As a result, a lot of research is being done in this direction, space weather forecast. Magnetohydrodynamics systems are being studied in order to analyse the space plasma dynamics, and techniques which have been broadly used in the prediction of earth environmental variables like the Kalman filter (KF), the ensemble Kalman filter (EnKF), the extended Kalman filter (EKF), etc., are being studied and adapted to this new framework. The assimilation of a wide range of space environment data into first-principles-based global numerical models will improve our understanding of the physics of the geospace environment and the forecasting of its behaviour. Therefore, the aim of this paper is to study the performance of nonlinear observers in magnetohydrodynamics systems, namely, the EnKF.
ISSN: 0377-0427
Publication status: published
KU Leuven publication type: IT
Appears in Collections:ESAT - STADIUS, Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics
× corresponding author
# (joint) last author

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