Statistical and dynamical aspects of extreme heatwaves in the mid-latitudes

Heatwaves are increasing both in frequency and intensity as a result of anthropogenic global warming. This PhD studies statistical and dynamical aspects of extreme and very extreme heat events in the mid-latitudes with a particular focus on European heatwaves. It addresses the questions of the maximal nearsurface air temperatures that can be reached during a heatwave event, the difference between the physical mechanisms leading to extreme vs very extreme heatwaves, the possibility to simulate efficiently very extreme heatwaves in a climate model and the dynamical evolution of extreme heatwaves with global warming.The first part of the PhD investigates statistical aspects of extreme heatwaves. It addresses the question of the upper bound for near-surface air temperatures. The approach is based on Extreme Value Theory (EVT) and I compare the results of this method to the physical processes that fundamentally limit the increase of air surface temperatures. The shortcomings of the traditional EVT approach are demonstrated and I propose an approach to alleviate the latter by physically constraining the fit of the EVT-based probability distributions.The second part of the PhD addresses the question of the dynamical mechanisms by which the climate system organizes to produce intense heat events. I first show in a long control run of a climate model that extreme heatevents tend to be typical, i.e. to be more similar to each other than moderate heat events. Because the study of extremes is impaired by a strong under-sampling problem, I then detail the interest of using so-called rare events algorithms which allow to sample more extremes than regular simulations can provide. I apply such a rare events algorithm in the IPSL-CM6A-LR model to sample extreme and very extreme hot summers inWestern Europe underpre-industrial, present and future conditions of anthropogenic forcings. In particular I investigate changes in the dynamics leading to these extreme summers in the different periods. I show that, in the model, global warming is associated to a decrease of the variability of the atmospheric circulation but to an increase of the thermodynamic variability.The work presented in this thesis demonstrate the interest of bridging the gap between physical and statistical approaches for the study of extreme and very extreme climate events. I show in particular that using techniques like rare events algorithms allows to answer physical questions about the climate system that are out of reach for classical methods.

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