Environmental phenomena are processes which are spatial by nature as a single extreme event (heat waves, floods, storms, etc.) often have repercussions at multiple locations. For risk management purposes it is important to have a good understanding of the dependence structure that links such events in order to make predictions on future phenomena, that can have a major impact on real life. Moreover available data at different sites can exhibit asymmetric distributions proving the necessity for max-stable processes that can handle skewness. The extremal-skew-$t$ process, constructed from a non-stationary skew-normal process is a solution that recently appeared in the literature. A generalisation of the discussion on the asymptotics of skewed families of extreme-value processes is provided, including skew-elliptical processes as well as the derivation of a skewed version of the well-known Gaussian extreme-value process. The challenge of simulating these processes is then tackled using the conditional simulation framework and simulated examples are provided to illustrate the method.
Invited talk in the session Multivariate Extremes, organised by Prof. M. Flak. Other presenters: C. Klueppelberg, A. Janssen, J. Segers.