Meteorological events such as severe storms, floods or droughts are often referred to as extreme events. The impact of such events on society is immense and numerous efforts have been devoted to study them. Many proxy indicators in paleoclimate variability reconstructions are sensitive to such extremes, and a careful quantification of their link to environmental parameters is indispensable. In this paper we determine the relationship between typical states of the atmospheric circulation over and around the North Atlantic, on the one hand, and extreme events, on the other. We apply a novel statistical approach to associate extremes and weather regimes. This study enables us to infer the atmospheric conditions that prevailed in the North Atlantic region during key periods of the recent past.

Abstract. Extreme Value Theory (EVT) is a useful tool to describe the statistical properties of extreme events. Its underlying assumptions include some form of temporal stationarity in the data. Previous studies have been able to treat long-term trends in datasets, to obtain the time dependence of EVT parameters in a parametric form. Since there is also a dependence of surface temperature and precipitation to weather patterns obtained from pressure data, we determine the EVT parameters of those meteorological variables over France conditional to the occurrence of North Atlantic weather patterns in the summer. We use a clustering algorithm on geopotential height data over the North Atlantic to obtain those patterns. This approach refines the straightforward application of EVT on climate data by allowing us to assess the role of atmospheric variability on temperature and precipitation extreme parameters. This study also investigates the statistical robustness of this relation. Our results show how weather regimes can modulate the different behavior of mean climate variables and their extremes. Such a modulation can be very different for the mean and extreme precipitation.

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.

[1] Recent studies on extreme events have focused on the potential change of their intensity during the 20th century, but their frequency evolution has often been overlooked although its socio-economic impact is equally important. This paper focuses on extreme events of high and low temperatures and their amplitude and frequency changes over the last 60 years in the North Atlantic (NA) region. We analyze the temporal evolution of the amplitude and frequency of extreme events through the parameters of an extreme value distribution applied to NCEP reanalysis for the winter and summer seasons. We examine the relation of the statistics of extremes with greenhouse gas forcing and an atmospheric circulation index and obtain a spatial distribution of the trends of those extreme parameters. We find that the frequency of warm extremes increases over most of the NA while their magnitude does not vary as systematically. Apart from the Labrador Sea and parts of Scandinavia, the features of winter cold extremes exhibit decreasing or no trends.