Precipitation downscaling improves the coarse resolution and poor representation of
precipitation in global climate models and helps end users to assess the likely hydrological …

The last decade has seen development of a plethora of approaches for threshold estimation
in extreme value applications. From a statistical perspective, the threshold is loosely defined …

Statistical issues arising in modelling univariate extremes of a random sample have been
successfully used in the most diverse fields, such as biometrics, finance, insurance and risk …

Conditional independence, graphical models and sparsity are key notions for parsimonious
statistical models and for understanding the structural relationships in the data. The theory of …

In statistics, extreme events are often defined as excesses above a given large threshold.
This definition allows hydrologists and flood planners to apply Extreme‐Value Theory (EVT) …

We review work on extreme events, their causes and consequences, by a group of
European and American researchers involved in a three-year project on these topics. The …

The aim of this paper is to analyse extremal events using generalized Pareto distributions
(GPD), considering explicitly the uncertainty about the threshold. Current practice empirically …

This work is motivated by the challenge organized for the 10th International Conference on
Extreme-Value Analysis (EVA2017) to predict daily precipitation quantiles at the 99.8 …

Recent wildfires in Australia have led to considerable economic loss and property
destruction, and there is increasing concern that climate change may exacerbate their …

Downscaling precipitation is a difficult challenge for the climate community. We propose and
study a new stochastic weather typing approach to perform such a task. In addition to …