Presentation
Extreme weather events such as heatwaves, floods, drought periods, and cyclones have significant consequences on our environment and societies. Understanding and modeling these extreme climatic events require expertise at various spatial scales, ranging from large-scale structures related to atmospheric dynamics to very local phenomena. Similarly, a perspective at different temporal scales is crucial, covering the study of current processes and past climates, as well as the evolution of the characteristics of extreme events during global climate changes, whether past, present, or future. The summarized work below, carried out by the ESTIMR and CLIM teams, has contributed to a better understanding, modeling, and attribution of extreme climatic phenomena.
Tropical and Mediterranean cyclones represent disasters with high costs and potentially devastating consequences. Stella Bourdin, during her thesis, studied the representation of these phenomena by LMDZ (regular grid) and ico-LMDZ (icosahedral grid) general atmospheric circulation models, for a set of six simulations covering spatial resolutions ranging from 200 to 25km. Bourdin et al. (2022) first compared different methods of detecting tropical cyclones, applied to ERA5 reanalysis, and showed that all these methods detect about 80% of observed cyclones. The differences are restricted to weak and/or short-lived cyclones. The cyclonic activity simulated by both models LMDZ and ico-LMDZ increases strongly with spatial resolution until achieving realistic results for the finest resolution studied. This resolution allows for a better representation of the geographical distribution and structure of cyclones, especially in the North Atlantic where the IPSL model demonstrated remarkable performance. Extending the study to Mediterranean cyclones (“medicanes”) showed for the first time the model’s ability to faithfully reproduce their climatology.
These research efforts enable the study of phenomena that have been little studied so far, as climate simulations generally rely on models with lower resolution. They pave the way for studies attributing these phenomena to climate change. The LSCE has played a significant role in the development and application of methodologies for attributing extreme events to ongoing climate change. This approach aims to analyze various extreme weather events by determining to what extent human-induced climate change has contributed to the intensity or frequency of these phenomena. Using the conditional attribution methodology, which is based on searching for conditions similar to those observed during a specific extreme event, the LSCE has examined several cases, including the winter storm Filomena in Spain, the cold wave of April 2021 in France, the Mediterranean heatwave in August associated with wildfires in Greece and Italy, the tornado swarm in the Po Valley in September, and Medicane Apollo causing floods in Sicily in October. This approach has also been used in the more detailed attribution of the extratropical cyclone Alex affecting southern France in 2020.
Beyond the analysis of specific events, the LSCE has extended the use of attribution methodology to detect trends in the frequency of extreme events and attribute phenomena such as the Euro-Mediterranean drought of 2022. This approach has been applied to assess the impact of anthropogenic climate change on Mediterranean cyclones affecting the city of Venice, allowing for the evaluation of flood adaptation strategies in the city. This conditional attribution method defined by Faranda et al (2022) is the basis of the ClimaMeter initiative, a rapid experimental framework led by the LSCE’s ESTIMR team, involving more than 20 internationally renowned scientists. ClimaMeter allows for the understanding of extreme weather events in an evolving climate by examining similar past meteorological situations. The ClimaMeter framework offers a dynamic approach to contextualize and analyze extreme weather events in the current climate context. This initiative provides immediate and accessible understanding for the public, as well as in-depth technical analysis. In a few months, ClimaMeter has analyzed more than 25 extreme events globally and generated more than 150 press articles in 30 countries worldwide.
Our work on extremes is not limited to explicit modeling and attribution; it also allows for simplified projections. An innovative approach relies on the use of rare event algorithms from statistical physics. These algorithms have been used to “push” climate models toward physically plausible extreme scenarios. The results of the study suggest that the record temperature of 2003 could be exceeded by several degrees Celsius well before 2050 (Yiou et al. 2023). This innovative simulation approach is also applied to the IPSL climate model, through an ingenious development by the Calculs team to launch simulation ensembles (see TH3-FM1 sheet). The initial results show a form of uniqueness in the physical mechanisms leading to the most intense heatwaves in France (thesis of Robin Noyelle).
- Bourdin, S., Fromang, S., Dulac, W., Cattiaux, J., and Chauvin, F.: Intercomparison of four algorithms for detecting tropical cyclones using ERA5, Geosci. Model Dev., 15, 6759–6786, https://doi.org/10.5194/gmd-15-6759-2022, 2022
- Faranda, D., Bourdin, S., Ginesta, M., Krouma, M., Noyelle, R., Pons, F., … & Messori, G. (2022). A climate-change attribution retrospective of some impactful weather extremes of 2021. Weather and Climate Dynamics, 3(4), 1311-1340.
- Yiou, P., Cadiou, C., Faranda, D., Jézéquel, A., Malhomme, N., Miloshevich, G., … & Vrac, M. (2023). Ensembles of climate simulations to anticipate worst case heatwaves during the Paris 2024 Olympics. npj climate and atmospheric science, 6(1), 188