Convergence of extreme value statistics in a two-layer quasi-geostrophic atmospheric model

Galfi, V. M., Bodai, T. and Lucarini, V. ORCID: https://orcid.org/0000-0001-9392-1471 (2017) Convergence of extreme value statistics in a two-layer quasi-geostrophic atmospheric model. Complexity, 2017. 5340858. ISSN 1076-2787 doi: 10.1155/2017/5340858

Abstract/Summary

We search for the signature of universal properties of extreme events, theoretically predicted for Axiom A flows, in a chaotic and high dimensional dynamical system by studying the convergence of GEV (Generalized Extreme Value) and GP (Generalized Pareto) shape parameter estimates to a theoretical value, expressed in terms of partial dimensions of the attractor, which are global properties. We consider a two layer quasi-geostrophic (QG) atmospheric model using two forcing levels, and analyse extremes of different types of physical observables (local, zonally-averaged energy, and the average value of energy over the mid-latitudes). Regarding the predicted universality, we find closer agreement in the shape parameter estimates only in the case of strong forcing, producing a highly chaotic behaviour, for some observables (the local energy at every latitude). Due to the limited (though very large) data size and the presence of serial correlations, it is difficult to obtain robust statistics of extremes in case of the other observables. In the case of weak forcing, inducing a less pronounced chaotic flow with regime behaviour, we find worse agreement with the theory developed for Axiom A flows, which is unsurprising considering the properties of the system.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/71594
Item Type	Article
Refereed	Yes
Divisions	Interdisciplinary Research Centres (IDRCs) > Walker Institute Science > School of Mathematical, Physical and Computational Sciences > Department of Mathematics and Statistics Interdisciplinary Research Centres (IDRCs) > Centre for the Mathematics of Planet Earth (CMPE)
Publisher	Hindawi
Download/View statistics	View download statistics for this item