Articles | Volume 6, issue 4
https://doi.org/10.5194/wcd-6-1147-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wcd-6-1147-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| Highlight paper
| 
21 Oct 2025
Research article | Highlight paper |
| 21 Oct 2025
| 21 Oct 2025
Estimating return periods for extreme events in climate models through Ensemble Boosting
Luna Bloin-Wibe
CORRESPONDING AUTHOR
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
Robin Noyelle
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
Vincent Humphrey
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
Federal Office of Meteorology and Climatology MeteoSwiss, Zurich, Switzerland
Urs Beyerle
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
Reto Knutti
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
Erich Fischer
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
Related authors
No articles found.
Detlef P. Van Vuuren, Brian C. O'Neill, Claudia Tebaldi, Benjamin M. Sanderson, Louise P. Chini, Pierre Friedlingstein, Tomoko Hasegawa, Keywan Riahi, Bala Govindasamy, Nico Bauer, Veronika Eyring, Cheikh M. N. Fall, Katja Frieler, Matthew J. Gidden, Laila K. Gohar, Annika Högner, Andrew D. Jones, Jarmo Kikstra, Andrew King, Reto Knutti, Elmar Kriegler, Peter Lawrence, Chris Lennard, Jason Lowe, Camilla Mathison, Shahbaz Mehmood, Zebedee Nicholls, Luciana F. Prado, Qiang Zhang, Steven K. Rose, Alex C. Ruane, Marit Sandstad, Carl-Friedrich Schleussner, Roland Seferian, Jana Sillmann, Chris Smith, Anna A. Sörensson, Swapna Panickal, Kaoru Tachiiri, Naomi Vaughan, Saritha S. Vishwanathan, Tokuta Yokohata, Marco Zecchetto, and Tilo Ziehn
Geosci. Model Dev., 19, 2627–2656, https://doi.org/10.5194/gmd-19-2627-2026, https://doi.org/10.5194/gmd-19-2627-2026, 2026
Short summary
Short summary
We propose a set of seven plausible 21st century emission scenarios, and their multi-century extensions, that will be used by the international community of climate modeling centers to produce the next generation of climate projections. These projections will support climate, impact and mitigation researchers, provide information to practitioners to address future risks from climate change, and contribute to policymakers’ considerations of the trade-offs among various levels of mitigation.
Belinda Hotz, Heini Wernli, Matthias Röthlisberger, and Robin Noyelle
EGUsphere, https://doi.org/10.5194/egusphere-2026-1522, https://doi.org/10.5194/egusphere-2026-1522, 2026
This preprint is open for discussion and under review for Weather and Climate Dynamics (WCD).
Short summary
Short summary
We systematically investigate vertical temperature anomaly profiles during heat extremes on a global scale. Three distinct clusters emerge, aligning closely with the polar, mid-latitude, and tropical climate zones and capturing the key characteristics of the vertical profiles. While mid-latitude and polar profiles feature anomalies throughout the troposphere, with the highest temperature anomalies in the boundary layer, tropical temperature anomalies are confined to the boundary layer.
Roland Hohensinn, Junyang Gou, Ulrich Meyer, Vincent Humphrey, Wouter Dorigo, Eva Boergens, Benedikt Soja, Alexander Gruber, Laura Jensen, Annette Eicker, Michael Rast, and Andreas Güntner
EGUsphere, https://doi.org/10.5194/egusphere-2026-975, https://doi.org/10.5194/egusphere-2026-975, 2026
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
Short summary
Short summary
This study provides a statistically traceable, uncertainty-aware assessment of global terrestrial and groundwater storage trends based on 21.5 years of GRACE/-FO observations using the Global Gravity-based Groundwater Product (G3P). By accounting for long-range memory and interannual variability, we isolate robust trends from climate variability and noise. The analysis refines continental budgets and identifies emerging groundwater gains alongside widespread persistent decline.
Donghe Zhu, Patrick Pieper, Stephan Pfahl, and Erich Fischer
EGUsphere, https://doi.org/10.5194/egusphere-2026-1258, https://doi.org/10.5194/egusphere-2026-1258, 2026
This preprint is open for discussion and under review for Weather and Climate Dynamics (WCD).
Short summary
Short summary
Climate models consistently project stronger heavy rainfall in a warming climate, but they disagree on how large these changes will be across regions. In this study, we identify the key causes of this uncertainty. Shifts in when events occur during the year alter the warming on those days and explain part of the thermodynamic increase in heavy rainfall. Differences in mid-tropospheric atmospheric motion are the dominant source of model disagreement in the dynamic increase in heavy rainfall.
Seppe Lampe, Lukas Gudmundsson, Basil Kraft, Stijn Hantson, Douglas Kelley, Vincent Humphrey, Bertrand Le Saux, Emilio Chuvieco, and Wim Thiery
Geosci. Model Dev., 19, 955–988, https://doi.org/10.5194/gmd-19-955-2026, https://doi.org/10.5194/gmd-19-955-2026, 2026
Short summary
Short summary
We introduce BuRNN (BUrned area modelling by Recurrent Neural Networks), a model which estimates monthly burned area based on satellite observations and climate, vegetation, and socio-economic data using machine learning. BuRNN outperforms existing process-based fire models, which improves our capabilities of modelling past and future burned areas.
Jacopo Riboldi, Robin Noyelle, Ellina Agayar, Hanin Binder, Marc Federer, Katharina Hartmuth, Michael Sprenger, Iris Thurnherr, and Selvakumar Vishnupriya
Weather Clim. Dynam., 7, 65–87, https://doi.org/10.5194/wcd-7-65-2026, https://doi.org/10.5194/wcd-7-65-2026, 2026
Short summary
Short summary
Storm Boris led to record-breaking precipitation over central Europe in September 2024. By incorporating event-specific meteorological information, this work introduces a methodology to strengthen our comprehension of how global warming affects similar hazards. Furthermore, it contextualizes how the answer to the question "How will Boris-like storms change in a warmer climate?" depends on explicit and implicit methodological choices, with the aim to inform future attribution research.
Matthias Röthlisberger, Michael Sprenger, Urs Beyerle, Erich M. Fischer, and Heini Wernli
EGUsphere, https://doi.org/10.5194/egusphere-2025-5146, https://doi.org/10.5194/egusphere-2025-5146, 2025
Short summary
Short summary
This study investigates yearly heat extremes simulated with the global climate model CESM2. A trajectory-based method is used, which allows quantifying the contributions to temperature anomalies from advection, subsidence, and diabatic heating. The results show that the magnitude of CESM2 heat extremes agrees fairly well with ERA5 reanalyses, but it is often “right for the partly wrong physical reasons”.
Hans Segura, Xabier Pedruzo-Bagazgoitia, Philipp Weiss, Sebastian K. Müller, Thomas Rackow, Junhong Lee, Edgar Dolores-Tesillos, Imme Benedict, Matthias Aengenheyster, Razvan Aguridan, Gabriele Arduini, Alexander J. Baker, Jiawei Bao, Swantje Bastin, Eulàlia Baulenas, Tobias Becker, Sebastian Beyer, Hendryk Bockelmann, Nils Brüggemann, Lukas Brunner, Suvarchal K. Cheedela, Sushant Das, Jasper Denissen, Ian Dragaud, Piotr Dziekan, Madeleine Ekblom, Jan Frederik Engels, Monika Esch, Richard Forbes, Claudia Frauen, Lilli Freischem, Diego García-Maroto, Philipp Geier, Paul Gierz, Álvaro González-Cervera, Katherine Grayson, Matthew Griffith, Oliver Gutjahr, Helmuth Haak, Ioan Hadade, Kerstin Haslehner, Shabeh ul Hasson, Jan Hegewald, Lukas Kluft, Aleksei Koldunov, Nikolay Koldunov, Tobias Kölling, Shunya Koseki, Sergey Kosukhin, Josh Kousal, Peter Kuma, Arjun U. Kumar, Rumeng Li, Nicolas Maury, Maximilian Meindl, Sebastian Milinski, Kristian Mogensen, Bimochan Niraula, Jakub Nowak, Divya Sri Praturi, Ulrike Proske, Dian Putrasahan, René Redler, David Santuy, Domokos Sármány, Reiner Schnur, Patrick Scholz, Dmitry Sidorenko, Dorian Spät, Birgit Sützl, Daisuke Takasuka, Adrian Tompkins, Alejandro Uribe, Mirco Valentini, Menno Veerman, Aiko Voigt, Sarah Warnau, Fabian Wachsmann, Marta Wacławczyk, Nils Wedi, Karl-Hermann Wieners, Jonathan Wille, Marius Winkler, Yuting Wu, Florian Ziemen, Janos Zimmermann, Frida A.-M. Bender, Dragana Bojovic, Sandrine Bony, Simona Bordoni, Patrice Brehmer, Marcus Dengler, Emanuel Dutra, Saliou Faye, Erich Fischer, Chiel van Heerwaarden, Cathy Hohenegger, Heikki Järvinen, Markus Jochum, Thomas Jung, Johann H. Jungclaus, Noel S. Keenlyside, Daniel Klocke, Heike Konow, Martina Klose, Szymon Malinowski, Olivia Martius, Thorsten Mauritsen, Juan Pedro Mellado, Theresa Mieslinger, Elsa Mohino, Hanna Pawłowska, Karsten Peters-von Gehlen, Abdoulaye Sarré, Pajam Sobhani, Philip Stier, Lauri Tuppi, Pier Luigi Vidale, Irina Sandu, and Bjorn Stevens
Geosci. Model Dev., 18, 7735–7761, https://doi.org/10.5194/gmd-18-7735-2025, https://doi.org/10.5194/gmd-18-7735-2025, 2025
Short summary
Short summary
The Next Generation of Earth Modeling Systems project (nextGEMS) developed two Earth system models that use horizontal grid spacing of 10 km and finer, giving more fidelity to the representation of local phenomena, globally. In its fourth cycle, nextGEMS simulated the Earth System climate over the 2020–2049 period under the SSP3-7.0 scenario. Here, we provide an overview of nextGEMS, insights into the model development, and the realism of multi-decadal, kilometer-scale simulations.
Sean P. Burns, Vincent Humphrey, Ethan D. Gutmann, Mark S. Raleigh, David R. Bowling, and Peter D. Blanken
Biogeosciences, 22, 5741–5769, https://doi.org/10.5194/bg-22-5741-2025, https://doi.org/10.5194/bg-22-5741-2025, 2025
Short summary
Short summary
We compared two techniques that are affected by the amount of liquid water in a forest canopy. One technique relies on remote sensing (a pair of GPSs) and the other uses tree motion generated by the wind. Though completely different, these two techniques show strikingly similar changes when rain falls on an evergreen forest. We combine these measurements with eddy covariance fluxes of water vapor to provide insight into the evaporation of canopy-intercepted precipitation.
Luise J. Fischer, David N. Bresch, Dominik Büeler, Christian M. Grams, Robin Noyelle, Matthias Röthlisberger, and Heini Wernli
Weather Clim. Dynam., 6, 1027–1043, https://doi.org/10.5194/wcd-6-1027-2025, https://doi.org/10.5194/wcd-6-1027-2025, 2025
Short summary
Short summary
Atmospheric flows over the North Atlantic can be meaningfully classified into weather regimes, and climate simulations suggest that the regime frequencies might change in the future. We provide a quantitative framework that helps assess whether these regime frequency changes are relevant to understanding climate change signals in precipitation. At least in our example application, in most regions, regime frequency changes explain little of the projected precipitation changes.
Nicola Maher, Adam S. Phillips, Clara Deser, Robert C. Jnglin Wills, Flavio Lehner, John Fasullo, Julie M. Caron, Lukas Brunner, Urs Beyerle, and Jemma Jeffree
Geosci. Model Dev., 18, 6341–6365, https://doi.org/10.5194/gmd-18-6341-2025, https://doi.org/10.5194/gmd-18-6341-2025, 2025
Short summary
Short summary
We present the new Multi-Model Large Ensemble Archive (MMLEAv2) and introduce the newly updated Climate Variability Diagnostics Package version 6 (CVDPv6), which is designed specifically for use with large ensembles. For highly variable quantities, we demonstrate that a model might perform evaluation poorly or favourably compared to the single realisation of the world that the observations represent, highlighting the need for large ensembles for model evaluation.
Robin Noyelle, Davide Faranda, Yoann Robin, Mathieu Vrac, and Pascal Yiou
Weather Clim. Dynam., 6, 817–839, https://doi.org/10.5194/wcd-6-817-2025, https://doi.org/10.5194/wcd-6-817-2025, 2025
Short summary
Short summary
Properties of extreme meteorological and climatological events are changing under human-caused climate change. Extreme event attribution methods seek to estimate the contribution of global warming in the probability and intensity changes of extreme events. Here we propose a procedure to estimate these quantities for the flow analogue method, which compares the observed event to similar events in the past.
Nathan P. Gillett, Isla R. Simpson, Gabi Hegerl, Reto Knutti, Dann Mitchell, Aurélien Ribes, Hideo Shiogama, Dáithí Stone, Claudia Tebaldi, Piotr Wolski, Wenxia Zhang, and Vivek K. Arora
Geosci. Model Dev., 18, 4399–4416, https://doi.org/10.5194/gmd-18-4399-2025, https://doi.org/10.5194/gmd-18-4399-2025, 2025
Short summary
Short summary
Climate model simulations of the response to human and natural influences together, natural climate influences alone and greenhouse gases alone are key to quantifying human influence on the climate. The last set of such coordinated simulations underpinned key findings in the last Intergovernmental Panel on Climate Change (IPCC) report. Here we propose a new set of such simulations to be used in the next generation of attribution studies and to underpin the next IPCC report.
Colin G. Jones, Fanny Adloff, Ben B. B. Booth, Peter M. Cox, Veronika Eyring, Pierre Friedlingstein, Katja Frieler, Helene T. Hewitt, Hazel A. Jeffery, Sylvie Joussaume, Torben Koenigk, Bryan N. Lawrence, Eleanor O'Rourke, Malcolm J. Roberts, Benjamin M. Sanderson, Roland Séférian, Samuel Somot, Pier Luigi Vidale, Detlef van Vuuren, Mario Acosta, Mats Bentsen, Raffaele Bernardello, Richard Betts, Ed Blockley, Julien Boé, Tom Bracegirdle, Pascale Braconnot, Victor Brovkin, Carlo Buontempo, Francisco Doblas-Reyes, Markus Donat, Italo Epicoco, Pete Falloon, Sandro Fiore, Thomas Frölicher, Neven S. Fučkar, Matthew J. Gidden, Helge F. Goessling, Rune Grand Graversen, Silvio Gualdi, José M. Gutiérrez, Tatiana Ilyina, Daniela Jacob, Chris D. Jones, Martin Juckes, Elizabeth Kendon, Erik Kjellström, Reto Knutti, Jason Lowe, Matthew Mizielinski, Paola Nassisi, Michael Obersteiner, Pierre Regnier, Romain Roehrig, David Salas y Mélia, Carl-Friedrich Schleussner, Michael Schulz, Enrico Scoccimarro, Laurent Terray, Hannes Thiemann, Richard A. Wood, Shuting Yang, and Sönke Zaehle
Earth Syst. Dynam., 15, 1319–1351, https://doi.org/10.5194/esd-15-1319-2024, https://doi.org/10.5194/esd-15-1319-2024, 2024
Short summary
Short summary
We propose a number of priority areas for the international climate research community to address over the coming decade. Advances in these areas will both increase our understanding of past and future Earth system change, including the societal and environmental impacts of this change, and deliver significantly improved scientific support to international climate policy, such as future IPCC assessments and the UNFCCC Global Stocktake.
Sebastian Sippel, Clair Barnes, Camille Cadiou, Erich Fischer, Sarah Kew, Marlene Kretschmer, Sjoukje Philip, Theodore G. Shepherd, Jitendra Singh, Robert Vautard, and Pascal Yiou
Weather Clim. Dynam., 5, 943–957, https://doi.org/10.5194/wcd-5-943-2024, https://doi.org/10.5194/wcd-5-943-2024, 2024
Short summary
Short summary
Winter temperatures in central Europe have increased. But cold winters can still cause problems for energy systems, infrastructure, or human health. Here we tested whether a record-cold winter, such as the one observed in 1963 over central Europe, could still occur despite climate change. The answer is yes: it is possible, but it is very unlikely. Our results rely on climate model simulations and statistical rare event analysis. In conclusion, society must be prepared for such cold winters.
Malte Meinshausen, Carl-Friedrich Schleussner, Kathleen Beyer, Greg Bodeker, Olivier Boucher, Josep G. Canadell, John S. Daniel, Aïda Diongue-Niang, Fatima Driouech, Erich Fischer, Piers Forster, Michael Grose, Gerrit Hansen, Zeke Hausfather, Tatiana Ilyina, Jarmo S. Kikstra, Joyce Kimutai, Andrew D. King, June-Yi Lee, Chris Lennard, Tabea Lissner, Alexander Nauels, Glen P. Peters, Anna Pirani, Gian-Kasper Plattner, Hans Pörtner, Joeri Rogelj, Maisa Rojas, Joyashree Roy, Bjørn H. Samset, Benjamin M. Sanderson, Roland Séférian, Sonia Seneviratne, Christopher J. Smith, Sophie Szopa, Adelle Thomas, Diana Urge-Vorsatz, Guus J. M. Velders, Tokuta Yokohata, Tilo Ziehn, and Zebedee Nicholls
Geosci. Model Dev., 17, 4533–4559, https://doi.org/10.5194/gmd-17-4533-2024, https://doi.org/10.5194/gmd-17-4533-2024, 2024
Short summary
Short summary
The scientific community is considering new scenarios to succeed RCPs and SSPs for the next generation of Earth system model runs to project future climate change. To contribute to that effort, we reflect on relevant policy and scientific research questions and suggest categories for representative emission pathways. These categories are tailored to the Paris Agreement long-term temperature goal, high-risk outcomes in the absence of further climate policy and worlds “that could have been”.
Anna L. Merrifield, Lukas Brunner, Ruth Lorenz, Vincent Humphrey, and Reto Knutti
Geosci. Model Dev., 16, 4715–4747, https://doi.org/10.5194/gmd-16-4715-2023, https://doi.org/10.5194/gmd-16-4715-2023, 2023
Short summary
Short summary
Using all Coupled Model Intercomparison Project (CMIP) models is unfeasible for many applications. We provide a subselection protocol that balances user needs for model independence, performance, and spread capturing CMIP’s projection uncertainty simultaneously. We show how sets of three to five models selected for European applications map to user priorities. An audit of model independence and its influence on equilibrium climate sensitivity uncertainty in CMIP is also presented.
Joel Zeder and Erich M. Fischer
Adv. Stat. Clim. Meteorol. Oceanogr., 9, 83–102, https://doi.org/10.5194/ascmo-9-83-2023, https://doi.org/10.5194/ascmo-9-83-2023, 2023
Short summary
Short summary
The intensities of recent heatwave events, such as the record-breaking heatwave in early June 2021 in the Pacific Northwest area, are substantially altered by climate change. We further quantify the contribution of the local weather situation and the land surface conditions with a statistical model suited for extreme data. Based on this method, we can answer
what ifquestions, such as estimating the change in the 2021 heatwave temperature if it happened in a world without climate change.
Vincent Humphrey and Christian Frankenberg
Biogeosciences, 20, 1789–1811, https://doi.org/10.5194/bg-20-1789-2023, https://doi.org/10.5194/bg-20-1789-2023, 2023
Short summary
Short summary
Microwave satellites can be used to monitor how vegetation biomass changes over time or how droughts affect the world's forests. However, such satellite data are still difficult to validate and interpret because of a lack of comparable field observations. Here, we present a remote sensing technique that uses the Global Navigation Satellite System (GNSS) as a makeshift radar, making it possible to observe canopy transmissivity at any existing environmental research site in a cost-efficient way.
Iris Elisabeth de Vries, Sebastian Sippel, Angeline Greene Pendergrass, and Reto Knutti
Earth Syst. Dynam., 14, 81–100, https://doi.org/10.5194/esd-14-81-2023, https://doi.org/10.5194/esd-14-81-2023, 2023
Short summary
Short summary
Precipitation change is an important consequence of climate change, but it is hard to detect and quantify. Our intuitive method yields robust and interpretable detection of forced precipitation change in three observational datasets for global mean and extreme precipitation, but the different observational datasets show different magnitudes of forced change. Assessment and reduction of uncertainties surrounding forced precipitation change are important for future projections and adaptation.
Hanna Joos, Michael Sprenger, Hanin Binder, Urs Beyerle, and Heini Wernli
Weather Clim. Dynam., 4, 133–155, https://doi.org/10.5194/wcd-4-133-2023, https://doi.org/10.5194/wcd-4-133-2023, 2023
Short summary
Short summary
Warm conveyor belts (WCBs) are strongly ascending, cloud- and precipitation-forming airstreams in extratropical cyclones. In this study we assess their representation in a climate simulation and their changes under global warming. They become moister, become more intense, and reach higher altitudes in a future climate, implying that they potentially have an increased impact on the mid-latitude flow.
Ryan S. Padrón, Lukas Gudmundsson, Laibao Liu, Vincent Humphrey, and Sonia I. Seneviratne
Biogeosciences, 19, 5435–5448, https://doi.org/10.5194/bg-19-5435-2022, https://doi.org/10.5194/bg-19-5435-2022, 2022
Short summary
Short summary
The answer to how much carbon land ecosystems are projected to remove from the atmosphere until 2100 is different for each Earth system model. We find that differences across models are primarily explained by the annual land carbon sink dependence on temperature and soil moisture, followed by the dependence on CO2 air concentration, and by average climate conditions. Our insights on why each model projects a relatively high or low land carbon sink can help to reduce the underlying uncertainty.
Davide Faranda, Stella Bourdin, Mireia Ginesta, Meriem Krouma, Robin Noyelle, Flavio Pons, Pascal Yiou, and Gabriele Messori
Weather Clim. Dynam., 3, 1311–1340, https://doi.org/10.5194/wcd-3-1311-2022, https://doi.org/10.5194/wcd-3-1311-2022, 2022
Short summary
Short summary
We analyze the atmospheric circulation leading to impactful extreme events for the calendar year 2021 such as the Storm Filomena, Westphalia floods, Hurricane Ida and Medicane Apollo. For some of the events, we find that climate change has contributed to their occurrence or enhanced their intensity; for other events, we find that they are unprecedented. Our approach underscores the importance of considering changes in the atmospheric circulation when performing attribution studies.
Benjamin M. Sanderson, Angeline G. Pendergrass, Charles D. Koven, Florent Brient, Ben B. B. Booth, Rosie A. Fisher, and Reto Knutti
Earth Syst. Dynam., 12, 899–918, https://doi.org/10.5194/esd-12-899-2021, https://doi.org/10.5194/esd-12-899-2021, 2021
Short summary
Short summary
Emergent constraints promise a pathway to the reduction in climate projection uncertainties by exploiting ensemble relationships between observable quantities and unknown climate response parameters. This study considers the robustness of these relationships in light of biases and common simplifications that may be present in the original ensemble of climate simulations. We propose a classification scheme for constraints and a number of practical case studies.
Cited articles
Au, S.-K. and Beck, J. L.: Estimation of small failure probabilities in high dimensions by subset simulation, Probabilistic Engineering Mechanics, 16, 263–277, https://doi.org/10.1016/S0266-8920(01)00019-4, 2001. a, b, c
Barriopedro, D., García-Herrera, R., Ordóñez, C., Miralles, D. G., and Salcedo-Sanz, S.: Heat Waves: Physical Understanding and Scientific Challenges, Reviews of Geophysics, 61, e2022RG000780, https://doi.org/10.1029/2022RG000780, 2023. a
Bartusek, S., Kornhuber, K., and Ting, M.: 2021 North American heatwave amplified by climate change-driven nonlinear interactions, Nature Climate Change, 12, 1143–1150, https://doi.org/10.1038/s41558-022-01520-4, 2022. a, b
Bloin-Wibe, L., Noyelle, R., Humphrey, V., Beyerle, U., Knutti,R., and Fischer, E.: Estimating return periods for extreme events in climate models through Ensemble Boosting, ETH Bibliography [data set], https://doi.org/10.3929/ethz-b-000720049, 2025a. a
Bloin-Wibe, L., Noyelle, R., and Humphrey, V.: Boosting_estimator, GitHub [code], https://github.com/luna-bloin/Boosting_estimator, 2025b. a
Coles, S., Bawa, J., Trenner, L., and Dorazio, P.: An introduction to statistical modeling of extreme values, 208, Springer, https://doi.org/10.1007/978-1-4471-3675-0, 2001. a
Cooley, D.: Return Periods and Return Levels Under Climate Change, in: Extremes in a Changing Climate: Detection, Analysis and Uncertainty, edited by: AghaKouchak, A., Easterling, D., Hsu, K., Schubert, S., and Sorooshian, S., Springer Netherlands, Dordrecht, 97–114, ISBN 978-94-007-4479-0, https://doi.org/10.1007/978-94-007-4479-0_4, 2013. a
Danabasoglu, G., Lamarque, J., Bacmeister, J., Bailey, D. A., DuVivier, A. K., Edwards, J., Emmons, L. K., Fasullo, J., Garcia, R., Gettelman, A., Hannay, C., Holland, M. M., Large, W. G., Lauritzen, P. H., Lawrence, D. M., Lenaerts, J. T. M., Lindsay, K., Lipscomb, W. H., Mills, M. J., Neale, R., Oleson, K. W., Otto‐Bliesner, B., Phillips, A. S., Sacks, W., Tilmes, S., Van Kampenhout, L., Vertenstein, M., Bertini, A., Dennis, J., Deser, C., Fischer, C., Fox‐Kemper, B., Kay, J. E., Kinnison, D., Kushner, P. J., Larson, V. E., Long, M. C., Mickelson, S., Moore, J. K., Nienhouse, E., Polvani, L., Rasch, P. J., and Strand, W. G.: The Community Earth System Model Version 2 (CESM2), Journal of Advances in Modeling Earth Systems, 12, e2019MS001916, https://doi.org/10.1029/2019MS001916, 2020. a, b
Dunne, J. P., Stouffer, R. J., and John, J. G.: Reductions in labour capacity from heat stress under climate warming, Nature Climate Change, 3, 563–566, https://doi.org/10.1038/nclimate1827, 2013. a
Fischer, E. M., Sippel, S., and Knutti, R.: Increasing probability of record-shattering climate extremes, Nature Climate Change, 11, 689–695, https://doi.org/10.1038/s41558-021-01092-9, 2021. a
Fischer, E. M., Beyerle, U., Bloin-Wibe, L., Gessner, C., Humphrey, V., Lehner, F., Pendergrass, A. G., Sippel, S., Zeder, J., and Knutti, R.: Storylines for unprecedented heatwaves based on ensemble boosting, Nature Communications, 14, 4643, https://doi.org/10.1038/s41467-023-40112-4, 2023. a, b, c, d, e
Galfi, V. M. and Lucarini, V.: Fingerprinting Heatwaves and Cold Spells and Assessing Their Response to Climate Change Using Large Deviation Theory, Physical Review Letters, 127, 058701, https://doi.org/10.1103/PhysRevLett.127.058701, 2021. a
Gessner, C., Fischer, E. M., Beyerle, U., and Knutti, R.: Very rare heat extremes: quantifying and understanding using ensemble re-initialization, Journal of Climate, 1–46, https://doi.org/10.1175/JCLI-D-20-0916.1, 2021. a, b, c
Gessner, C., Fischer, E. M., Beyerle, U., and Knutti, R.: Multi-year drought storylines for Europe and North America from an iteratively perturbed global climate model, Weather and Climate Extremes, 38, 100512, https://doi.org/10.1016/j.wace.2022.100512, 2022. a
Gessner, C., Fischer, E. M., Beyerle, U., and Knutti, R.: Developing Low‐Likelihood Climate Storylines for Extreme Precipitation Over Central Europe, Earth's Future, 11, e2023EF003628, https://doi.org/10.1029/2023EF003628, 2023. a
Giardina, C., Kurchan, J., Lecomte, V., and Tailleur, J.: Simulating Rare Events in Dynamical Processes, Journal of Statistical Physics, 145, 787–811, https://doi.org/10.1007/s10955-011-0350-4, 2011. a
Giardinà, C., Kurchan, J., and Peliti, L.: Direct Evaluation of Large-Deviation Functions, Physical Review Letters, 96, 120603, https://doi.org/10.1103/PhysRevLett.96.120603, 2006. a
Gourdji, S. M., Sibley, A. M., and Lobell, D. B.: Global crop exposure to critical high temperatures in the reproductive period: historical trends and future projections, Environmental Research Letters, 8, 024041, https://doi.org/10.1088/1748-9326/8/2/024041, 2013. a
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5 global reanalysis, Quarterly Journal of the Royal Meteorological Society, 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020. a
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 hourly data on single levels from 1940 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.adbb2d47, 2023. a
Horton, R. M., Mankin, J. S., Lesk, C., Coffel, E., and Raymond, C.: A Review of Recent Advances in Research on Extreme Heat Events, Current Climate Change Reports, 2, 242–259, https://doi.org/10.1007/s40641-016-0042-x, 2016. a
Kendall, M. G. and others: The advanced theory of statistics. Vols. 1., The advanced theory of statistics. Vols. 1., 1, publisher: Charles Griffin and Co., Ltd., 42 Drury Lane, London, 1948. a
Krishnamurthy, V.: Predictability of Weather and Climate, Earth and Space Science, 6, 1043–1056, https://doi.org/10.1029/2019EA000586, 2019. a
Lorenz, E. N.: Predictability – a problem partly solved, in: Predictability of Weather and Climate, edited by: Palmer, T. and Hagedorn, R., Cambridge University Press, 1 edn., 40–58, ISBN 978-0-521-84882-4 978-0-511-61765-2 978-1-107-41485-3, https://doi.org/10.1017/CBO9780511617652.004, 2006. a
Lucarini, V., Galfi, V. M., Riboldi, J., and Messori, G.: Typicality of the 2021 Western North America summer heatwave, Environmental Research Letters, 18, 015004, https://doi.org/10.1088/1748-9326/acab77, 2023. a
Lüthi, S., Huber, V., Pascal, M., Beyerle, U., Pyrina, M., Domeisen, D., Vicedo-Cabrera, A. M., and Fischer, E.: Storylines for month-long heatwaves and associated heat-related mortality impacts over Western Europe, https://doi.org/10.21203/rs.3.rs-5356341/v1, 2024. a
Malinina, E. and Gillett, N. P.: The 2021 heatwave was less rare in Western Canada than previously thought, Weather and Climate Extremes, 43, 100642, https://doi.org/10.1016/j.wace.2024.100642, 2024. a, b
McKinnon, K. A. and Simpson, I. R.: How Unexpected Was the 2021 Pacific Northwest Heatwave?, Geophysical Research Letters, 49, e2022GL100380, https://doi.org/10.1029/2022GL100380, 2022. a, b
Meehl, G. A. and Tebaldi, C.: More Intense, More Frequent, and Longer Lasting Heat Waves in the 21st Century, Science, 305, 994–997, https://doi.org/10.1126/science.1098704, 2004. a
Miloshevich, G., Cozian, B., Abry, P., Borgnat, P., and Bouchet, F.: Probabilistic forecasts of extreme heatwaves using convolutional neural networks in a regime of lack of data, Physical Review Fluids, 8, 040501, https://doi.org/10.1103/PhysRevFluids.8.040501, 2023. a
Miralles, D. G., Teuling, A. J., Van Heerwaarden, C. C., and Vilà-Guerau De Arellano, J.: Mega-heatwave temperatures due to combined soil desiccation and atmospheric heat accumulation, Nature Geoscience, 7, 345–349, https://doi.org/10.1038/ngeo2141, 2014. a
Neal, E., Huang, C. S. Y., and Nakamura, N.: The 2021 Pacific Northwest Heat Wave and Associated Blocking: Meteorology and the Role of an Upstream Cyclone as a Diabatic Source of Wave Activity, Geophysical Research Letters, 49, e2021GL097699, https://doi.org/10.1029/2021GL097699, 2022. a
Noyelle, R.: Statistical and dynamical aspects of extreme heatwaves in the mid-latitudes, Ocean, Atmosphere, Université Paris-Saclay, https://theses.hal.science/tel-04632646v2 (last access: 17 October 2025), 2024. a
Noyelle, R., Robin, Y., Naveau, P., Yiou, P., and Faranda, D.: Integration of physical bound constraints to alleviate shortcomings of statistical models for extreme temperatures, https://hal.science/hal-04479249, 2024a. a
Noyelle, R., Yiou, P., and Faranda, D.: Investigating the typicality of the dynamics leading to extreme temperatures in the IPSL-CM6A-LR model, Climate Dynamics, 62, 1329–1357, https://doi.org/10.1007/s00382-023-06967-5, 2024b. a, b
Otto, F. E. L., Massey, N., van Oldenborgh, G. J., Jones, R. G., and Allen, M. R.: Reconciling two approaches to attribution of the 2010 Russian heat wave, Geophysical Research Letters, 39, https://doi.org/10.1029/2011GL050422, 2012. a
Overland, J. E.: Causes of the Record-Breaking Pacific Northwest Heatwave, Late June 2021, Atmosphere, 12, 1434, https://doi.org/10.3390/atmos12111434, 2021. a
Perkins, S. E.: A review on the scientific understanding of heatwaves–Their measurement, driving mechanisms, and changes at the global scale, Atmospheric Research, 164–165, 242–267, https://doi.org/10.1016/j.atmosres.2015.05.014, 2015. a
Pfahl, S. and Wernli, H.: Quantifying the relevance of atmospheric blocking for co-located temperature extremes in the Northern Hemisphere on (sub-)daily time scales: blocking and temperature extremes, Geophysical Research Letters, 39, https://doi.org/10.1029/2012GL052261, 2012. a
Philip, S., Kew, S., van Oldenborgh, G. J., Otto, F., Vautard, R., van der Wiel, K., King, A., Lott, F., Arrighi, J., Singh, R., and van Aalst, M.: A protocol for probabilistic extreme event attribution analyses, Adv. Stat. Clim. Meteorol. Oceanogr., 6, 177–203, https://doi.org/10.5194/ascmo-6-177-2020, 2020. a
Philip, S. Y., Kew, S. F., van Oldenborgh, G. J., Anslow, F. S., Seneviratne, S. I., Vautard, R., Coumou, D., Ebi, K. L., Arrighi, J., Singh, R., van Aalst, M., Pereira Marghidan, C., Wehner, M., Yang, W., Li, S., Schumacher, D. L., Hauser, M., Bonnet, R., Luu, L. N., Lehner, F., Gillett, N., Tradowsky, J. S., Vecchi, G. A., Rodell, C., Stull, R. B., Howard, R., and Otto, F. E. L.: Rapid attribution analysis of the extraordinary heat wave on the Pacific coast of the US and Canada in June 2021, Earth Syst. Dynam., 13, 1689–1713, https://doi.org/10.5194/esd-13-1689-2022, 2022. a
Plotkin, D. A., Webber, R. J., O'Neill, M. E., Weare, J., and Abbot, D. S.: Maximizing Simulated Tropical Cyclone Intensity With Action Minimization, Journal of Advances in Modeling Earth Systems, 11, 863–891, https://doi.org/10.1029/2018MS001419, 2019. a
Ragone, F., Wouters, J., and Bouchet, F.: Computation of extreme heat waves in climate models using a large deviation algorithm, Proceedings of the National Academy of Sciences, 115, 24–29, https://doi.org/10.1073/pnas.1712645115, 2018. a
Rahmstorf, S. and Coumou, D.: Increase of extreme events in a warming world, Proceedings of the National Academy of Sciences, 108, 17905–17909, https://doi.org/10.1073/pnas.1101766108, 2011. a
Ranasinghe, R., Ruane, A., Vautard, R., Arnell, N., Coppola, E., Cruz, F., Dessai, S., Islam, A., Rahimi, M., Ruiz Carrascal, D., Sillmann, J., Sylla, M., Tebaldi, C., Wang, W., and Zaaboul, R.: Climate Change Information for Regional Impact and for Risk Assessment, in: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekçi, O., Yu, R., and Zhou, B., Cambridge University Press, Cambridge, UK and New York, NY, USA, 1767–1925, https://doi.org/10.1017/9781009157896.014, 2021. a
Risken, H.: The Fokker-Planck Equation: Methods of Solution and Applications, vol. 18 of Springer Series in Synergetics, Springer Berlin Heidelberg, Berlin, Heidelberg, ISBN 978-3-540-61530-9 978-3-642-61544-3, https://doi.org/10.1007/978-3-642-61544-3, 1996. a
Robine, J.-M., Cheung, S. L. K., Le Roy, S., Van Oyen, H., Griffiths, C., Michel, J.-P., and Herrmann, F. R.: Death toll exceeded 70,000 in Europe during the summer of 2003, Comptes Rendus Biologies, 331, 171–178, https://doi.org/10.1016/j.crvi.2007.12.001, 2008. a, b
Rodgers, K. B., Lee, S.-S., Rosenbloom, N., Timmermann, A., Danabasoglu, G., Deser, C., Edwards, J., Kim, J.-E., Simpson, I. R., Stein, K., Stuecker, M. F., Yamaguchi, R., Bódai, T., Chung, E.-S., Huang, L., Kim, W. M., Lamarque, J.-F., Lombardozzi, D. L., Wieder, W. R., and Yeager, S. G.: Ubiquity of human-induced changes in climate variability, Earth Syst. Dynam., 12, 1393–1411, https://doi.org/10.5194/esd-12-1393-2021, 2021 (data available at: https://www.cesm.ucar.edu/community-projects/lens2/data-sets, last access: 7 October 2025). a, b
Röthlisberger, M. and Papritz, L.: Quantifying the physical processes leading to atmospheric hot extremes at a global scale, Nature Geoscience, 16, 210–216, https://doi.org/10.1038/s41561-023-01126-1, 2023. a
Schaller, N., Sillmann, J., Anstey, J., Fischer, E. M., Grams, C. M., and Russo, S.: Influence of blocking on Northern European and Western Russian heatwaves in large climate model ensembles, Environmental Research Letters, 13, 054015, https://doi.org/10.1088/1748-9326/aaba55, 2018. a
Schumacher, D. L., Hauser, M., and Seneviratne, S. I.: Drivers and Mechanisms of the 2021 Pacific Northwest Heatwave, Earth's Future, 10, e2022EF002967, https://doi.org/10.1029/2022EF002967, 2022. a
Seneviratne, S., Zhang, X., Adnan, M., Badi, W., Dereczynski, C., Di Luca, A., Ghosh, S., Iskandar, I., Kossin, J., Lewis, S., Otto, F., Pinto, I., Satoh, M., Vicente-Serrano, S., Wehner, M., and Zhou, B.: Weather and Climate Extreme Events in a Changing Climate, in: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, edited by Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekçi, O., Yu, R., and Zhou, B., Cambridge University Press, Cambridge, UK and New York, NY, USA, 1513–1765, https://doi.org/10.1017/9781009157896.013, 2021. a, b
Shepherd, T. G., Boyd, E., Calel, R. A., Chapman, S. C., Dessai, S., Dima-West, I. M., Fowler, H. J., James, R., Maraun, D., Martius, O., Senior, C. A., Sobel, A. H., Stainforth, D. A., Tett, S. F. B., Trenberth, K. E., Van Den Hurk, B. J. J. M., Watkins, N. W., Wilby, R. L., and Zenghelis, D. A.: Storylines: an alternative approach to representing uncertainty in physical aspects of climate change, Climatic Change, 151, 555–571, https://doi.org/10.1007/s10584-018-2317-9, 2018. a
Suarez-Gutierrez, L., Li, C., Müller, W. A., and Marotzke, J.: Internal variability in European summer temperatures at 1.5 °C and 2 °C of global warming, Environmental Research Letters, 13, 064026, https://doi.org/10.1088/1748-9326/aaba58, 2018. a
Thiery, W., Lange, S., Rogelj, J., Schleussner, C.-F., Gudmundsson, L., Seneviratne, S. I., Andrijevic, M., Frieler, K., Emanuel, K., Geiger, T., Bresch, D. N., Zhao, F., Willner, S. N., Büchner, M., Volkholz, J., Bauer, N., Chang, J., Ciais, P., Dury, M., François, L., Grillakis, M., Gosling, S. N., Hanasaki, N., Hickler, T., Huber, V., Ito, A., Jägermeyr, J., Khabarov, N., Koutroulis, A., Liu, W., Lutz, W., Mengel, M., Müller, C., Ostberg, S., Reyer, C. P. O., Stacke, T., and Wada, Y.: Intergenerational inequities in exposure to climate extremes, Science, 374, 158–160, https://doi.org/10.1126/science.abi7339, 2021. a
Trevisan, A. and Palatella, L.: Chaos and weather forecasting: the role of the unstable subspace in predictability and state estimation problems, International Journal of Bifurcation and Chaos, 21, 3389–3415, https://doi.org/10.1142/S0218127411030635, 2011. a
Vannitsem, S.: Predictability of large-scale atmospheric motions: Lyapunov exponents and error dynamics, Chaos: An Interdisciplinary Journal of Nonlinear Science, 27, 032101, https://doi.org/10.1063/1.4979042, 2017. a
Vicedo-Cabrera, A. M., Scovronick, N., Sera, F., Royé, D., Schneider, R., Tobias, A., Astrom, C., Guo, Y., Honda, Y., Hondula, D. M., Abrutzky, R., Tong, S., Coelho, M. d. S. Z. S., Saldiva, P. H. N., Lavigne, E., Correa, P. M., Ortega, N. V., Kan, H., Osorio, S., Kyselý, J., Urban, A., Orru, H., Indermitte, E., Jaakkola, J. J. K., Ryti, N., Pascal, M., Schneider, A., Katsouyanni, K., Samoli, E., Mayvaneh, F., Entezari, A., Goodman, P., Zeka, A., Michelozzi, P., de’Donato, F., Hashizume, M., Alahmad, B., Diaz, M. H., Valencia, C. D. L. C., Overcenco, A., Houthuijs, D., Ameling, C., Rao, S., Di Ruscio, F., Carrasco-Escobar, G., Seposo, X., Silva, S., Madureira, J., Holobaca, I. H., Fratianni, S., Acquaotta, F., Kim, H., Lee, W., Iniguez, C., Forsberg, B., Ragettli, M. S., Guo, Y. L. L., Chen, B. Y., Li, S., Armstrong, B., Aleman, A., Zanobetti, A., Schwartz, J., Dang, T. N., Dung, D. V., Gillett, N., Haines, A., Mengel, M., Huber, V., and Gasparrini, A.: The burden of heat-related mortality attributable to recent human-induced climate change, Nature Climate Change, 11, 492–500, https://doi.org/10.1038/s41558-021-01058-x, 2021. a
Webber, R. J., Plotkin, D. A., O’Neill, M. E., Abbot, D. S., and Weare, J.: Practical rare event sampling for extreme mesoscale weather, Chaos: An Interdisciplinary Journal of Nonlinear Science, 29, 053109, https://doi.org/10.1063/1.5081461, 2019. a
White, R. H., Anderson, S., Booth, J. F., Braich, G., Draeger, C., Fei, C., Harley, C. D. G., Henderson, S. B., Jakob, M., Lau, C.-A., Mareshet Admasu, L., Narinesingh, V., Rodell, C., Roocroft, E., Weinberger, K. R., and West, G.: The unprecedented Pacific Northwest heatwave of June 2021, Nature Communications, 14, 727, https://doi.org/10.1038/s41467-023-36289-3, 2023. a, b
Wouters, J. and Bouchet, F.: Rare event computation in deterministic chaotic systems using genealogical particle analysis, Journal of Physics A: Mathematical and Theoretical, 49, 374002, https://doi.org/10.1088/1751-8113/49/37/374002, 2016. a
Yiou, P. and Jézéquel, A.: Simulation of extreme heat waves with empirical importance sampling, Geosci. Model Dev., 13, 763–781, https://doi.org/10.5194/gmd-13-763-2020, 2020. a
Zeder, J. and Fischer, E. M.: Quantifying the statistical dependence of mid-latitude heatwave intensity and likelihood on prevalent physical drivers and climate change, Adv. Stat. Clim. Meteorol. Oceanogr., 9, 83–102, https://doi.org/10.5194/ascmo-9-83-2023, 2023. a
Zeder, J., Sippel, S., Pasche, O. C., Engelke, S., and Fischer, E. M.: The Effect of a Short Observational Record on the Statistics of Temperature Extremes, Geophysical Research Letters, 50, e2023GL104090, https://doi.org/10.1029/2023GL104090, 2023. a, b
Editorial statement
This study introduces an original methodology combining ensemble boosting and conditional probability theory to estimate return periods of rare climate extremes without relying on long climate simulations. The method is rigorously developed, validated on a red-noise process, and applied to CESM2 simulations, including an analysis of the 2021 Pacific Northwest heatwave. Importantly, this framework enables linking probability estimates to specific climate storylines, allowing an assessment of the odds that an extreme event like the one examined will occur in the future.
This study introduces an original methodology combining ensemble boosting and conditional...
Short summary
Weather extremes have become more frequent due to climate change. It is therefore crucial to understand them, but since they are rarer than average weather, they are challenging to study. Ensemble Boosting (EB) is a tool that generates extreme climate model events efficiently, but without directly estimating their probability. Here, we present a method to recover these probabilities for a global climate model. EB can thus now be used to find extremes with meaningful statistical information.
Weather extremes have become more frequent due to climate change. It is therefore crucial to...
