Convergence of Extreme Value Statistics in a Two-Layer Quasi-Geostrophic Atmospheric Model

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. We study the convergence of GEV (Generalized Extreme Value) and GP (Generalized Pareto) shape parameter estimates to the theoretical value, which is expressed in terms of the partial information dimensions of the attractor. We consider a two-layer quasi-geostrophic atmospheric model of the mid-latitudes, adopt two levels of forcing, and analyse the extremes of different types of physical observables (local energy, zonally averaged energy, and globally averaged energy). We find good agreement in the shape parameter estimates with the theory only in the case of more intense forcing, corresponding to a strong chaotic behaviour, for some observables (the local energy at every latitude). Due to the limited (though very large) data size and to the presence of serial correlations, it is difficult to obtain robust statistics of extremes in the case of the other observables. In the case of weak forcing, which leads to weaker chaotic conditions with regime behaviour, we find, unsurprisingly, worse agreement with the theory developed for Axiom A flows.

Rainfall-triggered slope instabilities under a changing climate: comparative study using historical and projected precipitation extremes

This study aims to quantitatively assess the impact of extreme precipitation events under current and future climate scenarios on landslides. Rainfall-triggered landslides are analyzed primarily using extreme precipitation estimates, derived using the so-called stationary assumption (i.e., statistics of extreme events will not vary significantly over a long period of time). However, extreme precipitation patterns have shown to vary substantially due to climate change, leading to unprecedented changes in the statistics of extremes. In this study, a nonstationary approach, applied to climate model simulations, is adopted to project the upper bound of future precipitation extremes. Future precipitation estimates are obtained from the coupled model intercomparison project phase 5 (CMIP5) simulations. Baseline (historical) and projected (future) precipitation extremes are obtained for a study area near Seattle, Washington. The precipitation patterns are integrated into a series of fully coupled two-dimensional stress – unsaturated flow finite element simulations. The responses of the baseline and projected models at a 7 day rainfall duration obtained for a 50 year recurrence interval are compared in terms of the local strength reduction factor, displacements, matric suctions, and suction stresses. The results indicate that the usage of historical rainfall data can lead to underestimations in the hydromechanical behavior of natural slopes where locally increased transient seepage rates occur from the upper bound of future extreme precipitation estimates.