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

Autor: Dijkstra, H.A., Tantet, A.J.J., Viebahn, J.P., Mulder, T.E., Hebbink, M., Castellana, D., van den Pol, Henri, Frank, J.E., Baars, Sven, Wubs, F.W., Chekroun, Mickael, Kuehn, C.
Přispěvatelé: Mathematical Modeling, Sub Physical Oceanography, Sub Dynamics Meteorology, Dep Wiskunde, Sub Mathematical Modeling
Jazyk: angličtina
Rok vydání: 2016
Popis: 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.
Databáze: OpenAIRE