Estimating the state of large spatio-temporally chaotic systems

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.

authors

• Szunyogh, Istvan

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

publisher

• Elsevier  Publisher

published in

• Physics Letters, Section A: General, Atomic and Solid State Physics  Journal

keywords

• Chaos
• Kalman Filter
• Spatio-temporal Chaos
• Weather Forecasting

Digital Object Identifier (DOI)

• 10.1016/j.physleta.2004.08.004

start page

• 365

end page

• 370

volume

• 330

issue

• 5

URL

• http%3A%2F%2Fdx.doi.org%2F10.1016%2Fj.physleta.2004.08.004