A numerical framework to understand transitions in high-dimensional stochastic dynamical systems

H.A. Dijkstra, A.J.J. Tantet, J.P. Viebahn, T.E. Mulder, M. Hebbink, D. Castellana, Henri van den Pol, J.E. Frank, Sven Baars, F.W. Wubs, Mickael Chekroun, C. Kuehn

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Dynamical systems methodology is a mature complementary approach to forward simulation which can be used to investigate many aspects of climate dynamics. With this paper, a review is given on the methods to analyse deterministic and stochastic climate models and show that these are not restricted to low-dimensional toy models, but that they can be applied to models formulated by stochastic partial differential equations. We sketch the numerical implementation of these methods and illustrate these by showing results for two canonical problems in climate dynamics.
Original languageEnglish
Article numberdzw003
JournalDynamics and Statistics of the Climate System
Volume1
Issue number1
DOIs
Publication statusPublished - 2016

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