Séance Séminaire

Colloquium de Mathématiques

Emergence time and records analysis in a changing climate

Numerical climate models are complex and combine a large number of physical processes. They are key tools in quantifying the relative contribution of potential anthropogenic causes (e.g., the current increase in greenhouse gases) on high-impact atmospheric variables like heavy rainfall or temperatures. These so-called climate extreme event attribution problems are particularly challenging in a non-stationary context. In addition, global climate models like any in sillico numerical experiments are affected by different types of bias. In this talk, I will discuss about how to combine two different statistical concepts of univariate and multivariate extreme value theory to assess records changes in the context of extreme event attribution. In addition, the question of uncertainties quantification that remains a challenge in any climate attribution analysis will be explored from various directions. In particular, a simple model bias correction step for records will described in details. To illustrate our approach, we infer emergence times in precipitation from the CMIP5 and CMIP6 archives. This is joint work with Paula Gonzalez Soulivanh Thao and Julien Worms.