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7 results on '"extreme event attribution"'

1. A statistical method to model non-stationarity in precipitation records changes

Author

Gonzalez, Paula, Naveau, Philippe, Thao, Soulivanh, Worms, Julien, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Extrèmes : Statistiques, Impacts et Régionalisation (ESTIMR), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Mathématiques de Versailles (LMV), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), FRAISE-LEFE/INSU, 80 PRIME CNRS-INSU, ANR-20-CE40-0025,T-REX,nouveaux challenges pour la prédiction des extremes et sa validation(2020), ANR-19-CE46-0011,MeLODy,Bridging geohysics and MachinE Learning for the modeling, simulation and reconstruction of Ocean DYnamics(2019), and European Project: 101003469,XAIDA

Subjects
[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], Climate extreme events, Detection & attribution, [SDU.STU]Sciences of the Universe [physics]/Earth Sciences, Precipitation, Extreme event attribution
Abstract

International audience; In the context of climate change, assessing how likely a particular change or event has been caused by human influence is important for mitigation and adaptation policies. In this work we propose an extreme event attribution (EEA) methodology to analyze yearly maxima records, key indicators of climate change that spark media attention and research in the EEA community. Although they deserve a specific statistical treatment, algorithms tailored to record analysis are lacking. This is particularly true in a non-stationarity context. This work aims at filling this methodological gap by focusing on records in transient climate simulations. We apply our methodology to study records of yearly maxima of daily precipitation issued from numerical climate model IPSL-CM6A-LR. Illustrating our approach with decadal records, we detect in 2023 a clear human induced signal in half of the globe, with probability mostly increasing, but decreasing in the south and north Atlantic oceans

Published
2023

2. Heat extremes in Western Europe are increasing faster than simulated due to missed atmospheric circulation trends

Author

Vautard, R., Cattiaux, J., Happé, T., Singh, J., Bonnet, R., Cassou, C., Coumou, D., D'Andrea, F., Faranda, Davide, Fischer, E., Ribes, A., Sippel, S., Yiou, P., Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Vrije Universiteit Amsterdam [Amsterdam] (VU), Institute for Atmospheric and Climate Science [Zürich] (IAC), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Centre Européen de Recherche et de Formation Avancée en Calcul Scientifique (CERFACS), Royal Netherlands Meteorological Institute (KNMI), Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), ANR-20-CE01-0008,SAMPRACE,Simuler des Evenements Climatiques Rares(2020), European Project: 101003469,XAIDA, and Centre Européen de Recherche et de Formation Avancée en Calcul Scientifique - CERFACS (CERFACS)

Subjects
climate change, [SDE]Environmental Sciences, Extreme event attribution, Heat waves, climate extremes
Abstract

Over the last 70 years, extreme heat has been increasing at global scale [1,2], with a rapid rate in several regions including Western Europe [3]. Climate models broadly capture heat trends globally [1], but exhibit systematically weaker extreme heat trends than observations in Western Europe [4-6], together with a weaker summer warming [7,8]. The causes of this mismatch, confirmed here by the analysis of 273 latest generation coupled climate simulations, among which only a handful of them overpass observed trends, are not well understood. Here we use a circulation analogue approach [9,10] to identify the dynamical contribution to daily maximum temperature trends [11-12], and show that a substantial fraction (0.8°C [0.2°-1.4°C] of 3.4°C per global warming degree) of the trend is due to circulation changes, largely due to increases in southerly flows over Western Europe. Their rapid increase in frequency (+43% per global warming degree [10%-76%] since 1950) and persistence are largely underestimated in the 32 climate model flow simulations analyzed, as well as their overall dynamical contributions to temperature trends. The few simulations reaching the observed warming trends in extreme heat have weaker and non-significant dynamical changes, indicating compensating biases in dynamical and thermodynamical trends. These model biases in circulation trends can be due to a systematically underestimated or erroneous representation of the circulation response to external forcing, or to a systematic underestimation of interdecadal variability, or both. The former implies that future projections are too conservative, the latter that we are left with deep uncertainty regarding the pace of future summer heat in Europe: the current strong trend could weaken or increase in future decades. This calls for caution when interpreting climate projections of heat extremes over Western Europe, in particular in view of adaptation to heat waves.

Published
2023

3. A methodology for attributing extratropical cyclones to climate change: the case study of storm Alex 2020

Author

Ginesta, Mireia, Yiou, Pascal, Messori, Gabriele, Faranda, Davide, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Extrèmes : Statistiques, Impacts et Régionalisation (ESTIMR), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Department of Earth Sciences [Uppsala], Uppsala University, Center for Natural Hazards Research, Department of Earth Sciences, Simon Fraser University, Department of Meteorology [Stockholm] (MISU), Stockholm University, Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), London Mathematical Laboratory, European Project: 956396,EDIPI, Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), and Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)

Subjects
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Analogues, Climate Change, [SDE.MCG]Environmental Sciences/Global Changes, Extratropical cyclones, Extreme Event Attribution
Abstract

International audience Extreme event attribution aims at evaluating the impact of climate change on extreme events. In this work, we adapt an attribution methodology applicable to extratropical cyclones, and test it on storm Alex: an explosive extratropical cyclone that affected Southern France and Northern Italy at the beginning of October 2020. The methodology specifically combines atmospheric analogues, dynamical systems theory and extreme value theory. We first divide 6-hourly ERA5 data into two periods: a counterfactual period with a weak climate change signal (1950-1985) and a factual period with a strong climate change signal (1985-2021). We then identify the 30 cyclones in each period whose sea-level pressure maps were most similar to Alex's map. We term these analogues of Alex. We find that analogues in the factual period are more persistent than in the counterfactual period, which may favour severe impacts resulting from persistent strong winds and heavy precipitation, as was the case for Alex. This effect is compounded by the doubling in accumulated daily precipitation detected in Northern Italy between the counterfactual and factual analogues. In the factual period, the analogues also display deeper cyclones with poleward-shifted backward trajectories. Furthermore, we identify a seasonal shift of the analogues, from spring to autumn. Finally, the analogues in the factual world are closer to Alex than in the counterfactual. These changes collectively point to high-impact storms like Alex becoming more common in a changing climate.

Published
2022
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4. Pathways and pitfalls in extreme event attribution

Author

Roop Singh, Julie Arrighi, Karin van der Wiel, Andrew D. King, Sarah F. Kew, Robert Vautard, Fraser C. Lott, Friederike E. L. Otto, Sjoukje Philip, Geert Jan van Oldenborgh, Maarten van Aalst, Royal Netherlands Meteorological Institute (KNMI), University of Oxford, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Extrèmes : Statistiques, Impacts et Régionalisation (ESTIMR), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), School of Earth Sciences [Melbourne], Faculty of Science [Melbourne], University of Melbourne-University of Melbourne, Met Office Hadley Centre for Climate Change (MOHC), United Kingdom Met Office [Exeter], Red Cross Red Crescent Climate Centre, University of Twente, Australian Research Council, ARC: DE180100638 European Commission, EC, This paper builds on results from the Copernicus COP 039 and C3S 62 contracts lead by KNMI, which focused on the development of a prototype for extreme events and attribution service within the context of the Copernicus Climate Change Service (C3S) implemented by the European Centre for Medium-Range Weather Forecasts (ECMWF) and funded by the European Union. The Red Cross Red Crescent Climate Centre authors were partly supported by the Partners for Resilience program. AK was funded by the Australian Research Council (DE180100638)., University of Oxford [Oxford], Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), University of Twente [Netherlands], Department of Earth Systems Analysis, Faculty of Geo-Information Science and Earth Observation, and UT-I-ITC-4DEarth

Subjects
Atmospheric Science, Global and Planetary Change, Extreme weather, 010504 meteorology & atmospheric sciences, Computer science, Vulnerability, Climate change, 010501 environmental sciences, Extreme event attribution, 01 natural sciences, Hazard, Data science, Public interest, ITC-HYBRID, Detection and attribution, 13. Climate action, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, ITC-ISI-JOURNAL-ARTICLE, Meteorology & Atmospheric Sciences, Climate model, Attribution, 0105 earth and related environmental sciences, Event (probability theory)
Abstract

The last few years have seen an explosion of interest in extreme event attribution, the science of estimating the influence of human activities or other factors on the probability and other characteristics of an observed extreme weather or climate event. This is driven by public interest, but also has practical applications in decision-making after the event and for raising awareness of current and future climate change impacts. The World Weather Attribution (WWA) collaboration has over the last 5 years developed a methodology to answer these questions in a scientifically rigorous way in the immediate wake of the event when the information is most in demand. This methodology has been developed in the practice of investigating the role of climate change in two dozen extreme events world-wide. In this paper, we highlight the lessons learned through this experience. The methodology itself is documented in a more extensive companion paper. It covers all steps in the attribution process: the event choice and definition, collecting and assessing observations and estimating probability and trends from these, climate model evaluation, estimating modelled hazard trends and their significance, synthesis of the attribution of the hazard, assessment of trends in vulnerability and exposure, and communication. Here, we discuss how each of these steps entails choices that may affect the results, the common problems that can occur and how robust conclusions can (or cannot) be derived from the analysis. Some of these developments also apply to other attribution methodologies and indeed to other problems in climate science.

Published
2021
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5. Human contribution to the recordbreaking June and July 2019 heatwaves in Western Europe

Author

Vautard, Robert, van Aalst, Maarten, Boucher, Olivier, Drouin, Agathe, Haustein, Karsten, Kreienkamp, Frank, van Oldenborgh, Jan, Otto, Friederike, Ribes, Aurélien, Robin, Yoann, Schneider, Michel, Soubeyroux, Jean-Michel, Stott, Peter, Seneviratne, Sonia, Vogel, Martha, Wehner, Michael, Vautard, Robert, Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), and Météo-France

Subjects
[SDU] Sciences of the Universe [physics], Heat Wave, [SDU]Sciences of the Universe [physics], Climate Change, Extreme event attribution
Abstract

International audience; Two extreme heatwaves hit Western Europe in the summer of 2019, with historical records broken by more than a degree in many locations, and significant societal impacts, including excess mortality of several thousand people. The extent to which human influence has played a role in the occurrence of these events has been of large interest to scientists, media and decision makers. However, the outstanding nature of these events poses challenges for physical and statistical modeling. Using an unprecedented number of climate model ensembles and statistical extreme value modeling, we demonstrate that these short and intense events would have had extremely small odds in the absence of human-induced climate change, and equivalently frequent events would have been 1.5°C to 3°C colder. For instance, in France and in The Netherlands, the July 3-day heatwave has a 50-150-year return period in the current climate and a return period of more than 1000 years without human forcing. The increase in the intensities is larger than the global warming by a factor 2 to 3. Finally, we note that the observed trends are much larger than those in current climate models.

Published
2021
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6. Attribution of Extreme Wave Height Records along the North Atlantic Coasts using Hindcast Data: Feasibility and Limitations

Author

Philippe Naveau, Jeremy Rohmer, Xavier Bertin, Jessie Louisor, Gonéri Le Cozannet, Soulivanh Thao, Bureau de Recherches Géologiques et Minières (BRGM) (BRGM), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Extrèmes : Statistiques, Impacts et Régionalisation (ESTIMR), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), LIttoral ENvironnement et Sociétés - UMRi 7266 (LIENSs), Université de La Rochelle (ULR)-Centre National de la Recherche Scientifique (CNRS), We acknowledge financial support of Project EUPHEME, which is part of ERA4CS, an ERA-365 NET initiated by JPI Climate, and funded by FORMAS (SE), BMBF (DE), BMWFW (AT), 366 IFD (DK), MINECO (ES), ANR (FR) with co-funding by the European Union (Grant 690462). The R script for implementing the EEA of Naveau et al. (2018) is available at: https://thaos.github.io/farr_vignette/. The wave data are, European Project: 690462,H2020,H2020-SC5-2015-one-stage,ERA4CS(2016), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), LIttoral ENvironnement et Sociétés (LIENSs), and La Rochelle Université (ULR)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Counterfactual thinking, 010504 meteorology & atmospheric sciences, fraction of attributable risk, Climate change, wave, 01 natural sciences, Latitude, Hindcast, 14. Life underwater, extreme event attribution, 0105 earth and related environmental sciences, Earth-Surface Processes, Water Science and Technology, Event (probability theory), geography, geography.geographical_feature_category, Ecology, 010505 oceanography, uncertainties, 13. Climate action, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, Climatology, Oceanic basin, Maxima, Significant wave height
Abstract

Rohmer, J.; Louisor, J.; Le Cozannet, G.; Naveau, P.; Thao, S., and Bertin, X., 2020. Attribution of extreme wave height records along the North Atlantic coasts using hindcast data: Feasibility and limitations. In: Malvarez, G. and Navas, F. (eds.), Global Coastal Issues of 2020. Journal of Coastal Research, Special Issue No. 95, pp. 1268-1272. Coconut Creek (Florida), ISSN 0749-0208.Extreme Event Attribution (EEA) aims at answering questions about how much climate change influenced the probability or intensity of a specific type of extreme meteo-oceanic event. Here, we focus on wave record breaking i.e. the occurrence of an extreme significant wave height (hs) value that exceeds all past observations. The objective is to evaluate the probability changes related to climate change by estimating the fraction of attributable risk far=1–p0/p1, where p0 and p1 are probabilities of the wave record event in two different worlds: a counterfactual world without anthropogenic forcings i.e. a “world that might have been”, and the factual world, i.e. “world that is.” To define these different worlds, we rely on a wave hindcast database, which provides very long time series (1900-2008) of hs over the whole North Atlantic Ocean Basin (NAOB). We assume that the counterfactual world corresponds to the series of annual hs maxima over the period 1900-1930, and that the factual world corresponds to the annual hs maxima over the period 1978-2008. The extreme event attribution approach dedicated to record breakings was applied over NAOB, and we show large far values (>0.5) along the northern Canadian, Scottish and southwestern Norwegian coasts (over the latitudes 50°-65°N). These results are, however, carefully discussed with respect to different uncertainty sources, namely the validity of the assumptions underlying the EEA, the statistical uncertainties, the use of hindcast data instead of global climate model's results, and the limitations in the hindcast database setup.

Published
2020
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7. Trends of atmospheric circulation during singular hot days in Europe

Author

Jézéquel, Aglaé, Cattiaux, Julien, Naveau, Philippe, Radanovics, Sabine, Ribes, Aurélien, Vautard, Robert, Vrac, Mathieu, Yiou, Pascal, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), Meteo France, Toulouse, France, Extrèmes : Statistiques, Impacts et Régionalisation (ESTIMR), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Groupe d'étude de l'atmosphère météorologique (CNRM-GAME), and Météo France-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Europe, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, heatwaves, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, atmospheric circulation, [SDE]Environmental Sciences, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, extreme event attribution, [STAT.ME]Statistics [stat]/Methodology [stat.ME]
Abstract

International audience; The influence of climate change on mid-latitudes atmospheric circulation is still very uncertain. The large internal variability makes it difficult to extract any statistically significant signal regarding the evolution of the circulation. Here we propose a methodology to calculate dynamical trends tailored to the circulation of specific days by computing the evolution of the distances between the circulation of the day of interest and the other days of the time series. We compute these dynamical trends for two case studies of the hottest days recorded in two different European regions (corresponding to the heatwaves of summer 2003 and 2010). We use the NCEP reanalysis dataset, an ensemble of CMIP5 models, and a large ensemble of a single model (CESM), in order to account for different sources of uncertainty. While we find a positive trend for most models for 2003, we cannot conclude for 2010 since the models disagree on the trend estimates.

Published
2018
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