Estimating the state of large spatio-temporally chaotic systems
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We consider the estimation of the state of a large spatio-temporally chaotic system from noisy observations and knowledge of a system model. Standard state estimation techniques using the Kalman filter approach are not computationally feasible for systems with very many effective degrees of freedom. We present and test a new technique (called a Local Ensemble Kalman Filter), generally applicable to large spatio-temporally chaotic systems for which correlations between system variables evaluated at different points become small at large separation between the points. 2004 Elsevier B.V. All rights reserved.
author list (cited authors)
Ott, E., Hunt, B. R., Szunyogh, I., Zimin, A. V., Kostelich, E. J., Corazza, M., ... Yorke, J. A.
complete list of authors
Ott, E||Hunt, BR||Szunyogh, I||Zimin, AV||Kostelich, EJ||Corazza, M||Kalnay, E||Patil, DJ||Yorke, JA
Physics Letters A: General Physics, Nonlinear Science, Statistical Physics, Atomic, Molecular and Cluster Physics, Plasma and Fluid Physics, Condensed Matter, Cross-disciplinary Physics, Biological Physics, Nanosciences, Quantum Physics Journal