### 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.

Original language | English (US) |
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Pages (from-to) | 365-370 |

Number of pages | 6 |

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

Volume | 330 |

Issue number | 5 |

DOIs | |

State | Published - Sep 27 2004 |

### Keywords

- Chaos
- Kalman filter
- Spatio-temporal chaos
- Weather forecasting

### ASJC Scopus subject areas

- Physics and Astronomy(all)

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## Cite this

Ott, E., Hunt, B. R., Szunyogh, I., Zimin, A. V., Kostelich, E., Corazza, M., Kalnay, E., Patil, D. J., & Yorke, J. A. (2004). Estimating the state of large spatio-temporally chaotic systems.

*Physics Letters, Section A: General, Atomic and Solid State Physics*,*330*(5), 365-370. https://doi.org/10.1016/j.physleta.2004.08.004