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

Information Theory and Dynamical System Predictability

Courant Institute of Mathematical Sciences, New York University, 251 Mercer Street, New York, NY 10012, USA
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)
PDF Full-text Download PDF Full-Text [1206 KB, uploaded 7 March 2011 15:07 CET]
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

Article Statistics

Load and display the download statistics.

Citations to this Article

Cite This Article

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.

Entropy EISSN 1099-4300 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert