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Enhancing Predictability by Increasing Nonlinearity in Enso and Lorenz Systems : Volume 15, Issue 5 (29/10/2008)

By Ye, Z.

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Book Id: WPLBN0003978366
Format Type: PDF Article :
File Size: Pages 9
Reproduction Date: 2015

Title: Enhancing Predictability by Increasing Nonlinearity in Enso and Lorenz Systems : Volume 15, Issue 5 (29/10/2008)  
Author: Ye, Z.
Volume: Vol. 15, Issue 5
Language: English
Subject: Science, Nonlinear, Processes
Collections: Periodicals: Journal and Magazine Collection, Copernicus GmbH
Publication Date:
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications


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Ye, Z., & Hsieh, W. W. (2008). Enhancing Predictability by Increasing Nonlinearity in Enso and Lorenz Systems : Volume 15, Issue 5 (29/10/2008). Retrieved from

Description: Department of Earth and Ocean Sciences, University of British Columbia Vancouver, BC V6T 1Z4, Canada. The presence of nonlinear terms in the governing equations of a dynamical system usually leads to the loss of predictability, e.g. in numerical weather prediction. However, for the El Niño-Southern Oscillation (ENSO) phenomenon, in an intermediate coupled equatorial Pacific model run under the 1961–1975 and the 1981–1995 climatologies, the latter climatology led to longer-period oscillations, thus greater predictability. In the Lorenz (1963) 3-component chaos system, by adjusting the model parameters to increase the nonlinearity of the system, a similar increase in predictability was found. Thus in the ENSO and Lorenz systems, enhanced nonlinearity from changes in the governing equations could produce longer period oscillations with increased predictability.

Enhancing predictability by increasing nonlinearity in ENSO and Lorenz systems

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