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Entropy 2011, 13(3), 612-649; doi:10.3390/e13030612

Information Theory and Dynamical System Predictability

Received: 25 January 2011; in revised form: 14 February 2011 / Accepted: 20 February 2011 / Published: 7 March 2011
(This article belongs to the Special Issue Advances in Information Theory)
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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.
Keywords: predictability; information theory; statistical physics predictability; information theory; statistical physics
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Kleeman, R. Information Theory and Dynamical System Predictability. Entropy 2011, 13, 612-649.

AMA Style

Kleeman R. Information Theory and Dynamical System Predictability. Entropy. 2011; 13(3):612-649.

Chicago/Turabian Style

Kleeman, Richard. 2011. "Information Theory and Dynamical System Predictability." Entropy 13, no. 3: 612-649.

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