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

Henk Dijkstra*, Alexis Tantet, Jan Viebahn, Erik Mulder, Mariët Hebbink, Daniele Castellana, Henri van den Pol, Jason Frank, Sven Baars, Friederik Wubs, Mikael Chekroun, Christian Kuehn

*Corresponding author for this work

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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
Number of pages9
JournalDynamics and Statistics of the Climate System: An Interdisciplinary Journal
Volume1
Issue number1
DOIs
Publication statusPublished - 30-Nov-2016

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