Information theory and dynamical system predictability

Research output: Contribution to journalArticle

Abstract

Predicting the future state of a turbulent dynamical system such as the atmosphere has been recognized for several decades to be an essentially statistical undertaking. Uncertainties from a variety of sources are magnified by dynamical mechanisms and given sufficient time, compromise any prediction. In the last decade or so this process of uncertainty evolution has been studied using a variety of tools from information theory. These provide both a conceptually general view of the problem as well as a way of probing its non-linearity. Here we review these advances from both a theoretical and practical perspective. Connections with other theoretical areas such as statistical mechanics are emphasized. The importance of obtaining practical results for prediction also guides the development presented.

Original languageEnglish (US)
Pages (from-to)612-649
Number of pages38
JournalEntropy
Volume13
Issue number3
DOIs
StatePublished - Mar 2011

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information theory
dynamical systems
predictions
statistical mechanics
nonlinearity
atmospheres

Keywords

  • Information theory
  • Predictability
  • Statistical physics

ASJC Scopus subject areas

  • Physics and Astronomy(all)

Cite this

Information theory and dynamical system predictability. / Kleeman, Richard.

In: Entropy, Vol. 13, No. 3, 03.2011, p. 612-649.

Research output: Contribution to journalArticle

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