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On Stochastic Stability of Regional Ocean Models with Uncertainty in Wind Forcing : Volume 14, Issue 5 (25/10/2007)

By Ivanov, L. M.

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Book Id: WPLBN0003977959
Format Type: PDF Article :
File Size: Pages 16
Reproduction Date: 2015

Title: On Stochastic Stability of Regional Ocean Models with Uncertainty in Wind Forcing : Volume 14, Issue 5 (25/10/2007)  
Author: Ivanov, L. M.
Volume: Vol. 14, 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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Ivanov, L. M., & Chu, P. C. (2007). On Stochastic Stability of Regional Ocean Models with Uncertainty in Wind Forcing : Volume 14, Issue 5 (25/10/2007). Retrieved from

Description: Naval Postgraduate School, Monterey, CA, USA. A shallow-water model was used to understand model error induced by non-Gaussian wind uncertainty. Although the model was simple, it described a generic system with many degrees of freedom randomized by external noise. The study focused on the nontrivial collective behavior of finite-amplitude perturbations on different scales and their influence on model predictability. The error growth strongly depended on the intensity and degree of spatial inhomogeneity of wind perturbations. For moderate but highly inhomogeneous winds, the error grew as a power law. This behavior was a consequence of varying local characteristic exponents and nonlinear interactions between different scales. Coherent growth of perturbations was obtained for different scales at various stages of error evolution. For the nonlinear stage, statistics of prediction error could be approximated by a Weibull distribution. An approach based on the Kullback-Leibler distance (the relative entropy) and probability-weighted moments was developed for identification of Weibull statistics. Bifurcations of the variance, skewness and kurtosis of the irreversible predictability time (a measure of model prediction skill) were detected when the accepted prediction accuracy (tolerance) exceeded some threshold.

On stochastic stability of regional ocean models with uncertainty in wind forcing

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