Intensity and dynamics of extreme cold spells of the 21st century in France from CMIP6 data

Abstract. Cold extremes significantly impact society, causing excess mortality, strain on healthcare systems, and increased demand on the energy system. With global warming, these extremes are expected to decrease, as observed in various indicators. This study simulates extreme cold spells of 15 d using a stochastic weather generator (SWG) based on circulation analogues and importance sampling, adapted for CMIP6 data. Our results show that the most extreme cold spells decrease in intensity with global warming, making 20th-century-like events (e.g., 1985 in France) nearly impossible by the end of the 21st century. However, some events of similar intensity may still occur in the near future. Such events are associated with patterns of atmospheric dynamics that convey cold air from high latitudes into Europe. Those atmospheric circulation patterns show a consistent high-pressure system over Iceland and a strong low-pressure system over southwestern Europe in ERA5 and CMIP6 models. We show that nudging the SWG towards this type of pattern triggers extreme cold spells, even in a warmer world. We also show that most CMIP6 models accurately represent this atmospheric pattern. This study highlights the importance of understanding cold spell dynamics and the relevance of rare events algorithms and large ensemble models to simulate low-probability, high-impact events, offering insights into the future evolution of cold extremes.

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Publication Details

Journal
Earth System Dynamics
Published
2025-10-16
DOI
https://doi.org/10.5194/esd-16-1759-2025
Citations
1
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
1.11

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article

Intensity and dynamics of extreme cold spells of the 21st century in France from CMIP6 data

Pascal Yiou, Camille Cadiou
1 citations
Earth System Dynamics
Climate variability and models
1.11
article

Intensity and dynamics of extreme cold spells of the 21st century in France from CMIP6 data

Pascal Yiou, Camille Cadiou
article en
1 citations

Abstract

Abstract. Cold extremes significantly impact society, causing excess mortality, strain on healthcare systems, and increased demand on the energy system. With global warming, these extremes are expected to decrease, as observed in various indicators. This study simulates extreme cold spells of 15 d using a stochastic weather generator (SWG) based on circulation analogues and importance sampling, adapted for CMIP6 data. Our results show that the most extreme cold spells decrease in intensity with global warming, making 20th-century-like events (e.g., 1985 in France) nearly impossible by the end of the 21st century. However, some events of similar intensity may still occur in the near future. Such events are associated with patterns of atmospheric dynamics that convey cold air from high latitudes into Europe. Those atmospheric circulation patterns show a consistent high-pressure system over Iceland and a strong low-pressure system over southwestern Europe in ERA5 and CMIP6 models. We show that nudging the SWG towards this type of pattern triggers extreme cold spells, even in a warmer world. We also show that most CMIP6 models accurately represent this atmospheric pattern. This study highlights the importance of understanding cold spell dynamics and the relevance of rare events algorithms and large ensemble models to simulate low-probability, high-impact events, offering insights into the future evolution of cold extremes.

Earth System DynamicsVol. 16(5)
Centre National de la Recherche Scientifique (FR), Université de Versailles Saint-Quentin-en-Yvelines (FR), Commissariat à l'Énergie Atomique et aux Énergies Alternatives (FR), Université Paris-Saclay (FR), Sorbonne Université (FR), Institut Pierre-Simon Laplace (FR), Laboratoire des Sciences du Climat et de l'Environnement (FR), CEA Paris-Saclay (FR)
Agence Nationale de la Recherche, Horizon 2020 Framework Programme, H2020 European Research Council
Openalex Percentile: Top 19%
Climate variability and models
1.11
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