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In his paper in Climate Monitor, TML Wigley uses basic probability arguments to illustrate how a slowly changing climate could potentially affect the frequency of extreme events. In the time since the paper appeared, there has been increased interest in assessing how weather extremes may be altered by climate change. Much of the work has been conducted using extreme value analysis, which is the branch of statistics developed specifically to characterize extreme events. This commentary discusses the advantages of an EVA approach and reviews some EVA techniques that have been used to describe climate change’s potential impact on extreme phenomena. Additionally, this commentary illustrates basic EVA techniques in an analysis of temperatures for central England. In parallel to Wigley’s analysis, a time-varying EVA analysis is compared to a stationary one, and furthermore, the trend from the EVA analysis is compared to the trend in means. [ABSTRACT FROM AUTHOR]

Abstract: Currently there is an increasing research activity in the area of climate extremes because they represent a key manifestation of non-linear systems and an enormous impact on economic and social human activities. Our understanding of the mean behavior of climate and its ‘normal’ variability has been improving significantly during the last decades. In comparison, climate extreme events have been hard to study and even harder to predict because they are, by definition, rare and obey different statistical laws than averages. In this context, the motivation for this paper is twofold. Firstly, we recall the basic principles of Extreme Value Theory that is used on a regular basis in finance and hydrology, but it still does not have the same success in climate studies. More precisely, the theoretical distributions of maxima and large peaks are recalled. The parameters of such distributions are estimated with the maximum likelihood estimation procedure that offers the flexibility to take into account explanatory variables in our analysis. Secondly, we detail three case-studies to show that this theory can provide a solid statistical foundation, specially when assessing the uncertainty associated with extreme events in a wide range of applications linked to the study of our climate. To cite this article: P. Naveau et al., C. R. Geoscience 337 (2005). [Copyright &y& Elsevier]