A Statistical Framework for Conditional Extreme Event Attribution

Submitted to Advances in Statistical Climatology, Meteorology and Oceanography (ACSMO)International audienceThe goal of the attribution of individual events is to estimate whether and to what extent the risk of an extreme climate event evolves when external conditions (e.g. due to anthropogenic forcings) change. Many types of climate extremes are linked to the variability of the large-scale atmospheric circulation. It is hence essential to decipher the roles of atmospheric variability and increasing mean temperature in the change of probabilities of extremes. It is also crucial to define a background state (or counterfactual) to which recent observations are compared. In this paper we present a statistical framework to determine the 5 dynamical (linked to the atmospheric circulation) and thermodynamical (linked to slow forcings) contributions to the risk of extreme climate event. We discuss the creation of two states (or " worlds ") in which risk change is determined. We illustrate this methodology on a record precipitation event that hit southern UK in January 2014. The paper argues that it is possible to obtain qualitative results from reanalysis model simulation data for such an event