Simulating record-shattering cold winters of the beginning of the 21st century in France.

Extreme winter cold temperatures in Europe have huge societal impacts on society. Being able to simulate worst-case scenarios of such events for present and future climates is hence crucial for short and long-term adaptation. In this paper, we are interested in low-probability cold events, whose probability is deemed to decrease with climate change. Large ensembles of simulations allow to better analyse the mechanisms and characteristics of such events, but can require a lot of computational resources. Rather than simulating very large ensembles of normal climate trajectories, rare event algorithms allow sampling the tail of distributions more efficiently. Such algorithms have been applied to simulate extreme heat waves. They have emphasized the role of atmospheric circulation in such extremes. The goal of this study is to evaluate the dynamics of extreme cold spells simulated by a rare event algorithm. We focus first on winter cold temperatures that have occurred in France from 1950 to 2021. We investigate winter mean temperatures in France (December, January, and February) and identify a record-shattering event in 1963. We find that, although the frequency of extreme cold spells decreases with time, their intensity is stationary. We applied a stochastic weather generator approach with importance sampling, to simulate the coldest winters that could occur in a factual and counterfactual climate. We hence simulated ensembles of worst winter cold spells that are consistent with reanalyses. We find that a few simulations reach colder temperatures than the record-shattering event of 1963. The atmospheric circulation that prevails during those events is analyzed and compared to the observed circulation during the record-breaking events. [ABSTRACT FROM AUTHOR]