Estimating the state of large spatio-temporally chaotic systems Academic Article uri icon

abstract

  • 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.

published proceedings

  • Physics Letters A

author list (cited authors)

  • Ott, E., Hunt, B. R., Szunyogh, I., Zimin, A. V., Kostelich, E. J., Corazza, M., ... Yorke, J. A.

citation count

  • 8

complete list of authors

  • Ott, E||Hunt, BR||Szunyogh, I||Zimin, AV||Kostelich, EJ||Corazza, M||Kalnay, E||Patil, DJ||Yorke, JA

publication date

  • September 2004