Articles | Volume 14, issue 1
https://doi.org/10.5194/esd-14-81-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esd-14-81-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| Highlight paper
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26 Jan 2023
Research article | Highlight paper |
| 26 Jan 2023
| 26 Jan 2023
Robust global detection of forced changes in mean and extreme precipitation despite observational disagreement on the magnitude of change
Iris Elisabeth de Vries
CORRESPONDING AUTHOR
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
Sebastian Sippel
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
Angeline Greene Pendergrass
Earth and Atmospheric Sciences, Cornell University, Ithaca, NY, USA
National Center for Atmospheric Research, Boulder, CO, USA
Reto Knutti
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
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Florian E. Roemer, Erich M. Fischer, Robin Noyelle, and Reto Knutti
EGUsphere, https://doi.org/10.5194/egusphere-2026-2005, https://doi.org/10.5194/egusphere-2026-2005, 2026
This preprint is open for discussion and under review for Weather and Climate Dynamics (WCD).
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Climate model based storylines of future extreme events are a useful tool to inform disaster preparations, but it is often unclear whether such events are plausible to occur in the real world. We present an approach that evaluates the plausibility of climate storylines based on process understanding and historical precedents. We demonstrate our approach for long-lasting heatwaves in Western Europe; it can also be applied other types of extreme events.
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
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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.
Na Li, Sebastian Sippel, Nora Linscheid, Miguel D. Mahecha, Markus Reichstein, and Ana Bastos
Biogeosciences, 23, 767–792, https://doi.org/10.5194/bg-23-767-2026, https://doi.org/10.5194/bg-23-767-2026, 2026
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We study when anthropogenic signal becomes detectable in the global land carbon sink, which has risen since the 1950s due to CO₂ fertilization and mid- to high-latitude warming. The signal emerges earlier at the global than at regional scales. Future scenarios (2016–2100) take longer to detect than the historical period (1851–2014) because the signal is weaker relative to larger natural variability. Removing circulation-induced variability with dynamical adjustment shortens the detection time.
Peter Pfleiderer, Anna Merrifield, István Dunkl, Homer Durand, Enora Cariou, Julien Cattiaux, Gustau Camps-Valls, and Sebastian Sippel
Weather Clim. Dynam., 7, 89–108, https://doi.org/10.5194/wcd-7-89-2026, https://doi.org/10.5194/wcd-7-89-2026, 2026
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Due to changes in atmospheric circulation some regions are warming quicker than others. Statistical methods are used to estimate how much of the local summer temperature changes are due to circulation changes. We evaluate these methods by comparing their estimates to special simulations representing only temperature changes related to circulation changes. By applying the methods to observations of 1979–2023 we find that half of the warming over parts of Europe is related to circulation changes.
Luna Bloin-Wibe, Robin Noyelle, Vincent Humphrey, Urs Beyerle, Reto Knutti, and Erich Fischer
Weather Clim. Dynam., 6, 1147–1177, https://doi.org/10.5194/wcd-6-1147-2025, https://doi.org/10.5194/wcd-6-1147-2025, 2025
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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.
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
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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
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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.
Angeline G. Pendergrass, Michael P. Byrne, Oliver Watt-Meyer, Penelope Maher, and Mark J. Webb
Geosci. Model Dev., 17, 6365–6378, https://doi.org/10.5194/gmd-17-6365-2024, https://doi.org/10.5194/gmd-17-6365-2024, 2024
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The width of the tropical rain belt affects many aspects of our climate, yet we do not understand what controls it. To better understand it, we present a method to change it in numerical model experiments. We show that the method works well in four different models. The behavior of the width is unexpectedly simple in some ways, such as how strong the winds are as it changes, but in other ways, it is more complicated, especially how temperature increases with carbon dioxide.
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
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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.
Jiwoo Lee, Peter J. Gleckler, Min-Seop Ahn, Ana Ordonez, Paul A. Ullrich, Kenneth R. Sperber, Karl E. Taylor, Yann Y. Planton, Eric Guilyardi, Paul Durack, Celine Bonfils, Mark D. Zelinka, Li-Wei Chao, Bo Dong, Charles Doutriaux, Chengzhu Zhang, Tom Vo, Jason Boutte, Michael F. Wehner, Angeline G. Pendergrass, Daehyun Kim, Zeyu Xue, Andrew T. Wittenberg, and John Krasting
Geosci. Model Dev., 17, 3919–3948, https://doi.org/10.5194/gmd-17-3919-2024, https://doi.org/10.5194/gmd-17-3919-2024, 2024
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We introduce an open-source software, the PCMDI Metrics Package (PMP), developed for a comprehensive comparison of Earth system models (ESMs) with real-world observations. Using diverse metrics evaluating climatology, variability, and extremes simulated in thousands of simulations from the Coupled Model Intercomparison Project (CMIP), PMP aids in benchmarking model improvements across generations. PMP also enables efficient tracking of performance evolutions during ESM developments.
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
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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.
Min-Seop Ahn, Paul A. Ullrich, Peter J. Gleckler, Jiwoo Lee, Ana C. Ordonez, and Angeline G. Pendergrass
Geosci. Model Dev., 16, 3927–3951, https://doi.org/10.5194/gmd-16-3927-2023, https://doi.org/10.5194/gmd-16-3927-2023, 2023
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We introduce a framework for regional-scale evaluation of simulated precipitation distributions with 62 climate reference regions and 10 metrics and apply it to evaluate CMIP5 and CMIP6 models against multiple satellite-based precipitation products. The common model biases identified in this study are mainly associated with the overestimated light precipitation and underestimated heavy precipitation. These biases persist from earlier-generation models and have been slightly improved in CMIP6.
Na Li, Sebastian Sippel, Alexander J. Winkler, Miguel D. Mahecha, Markus Reichstein, and Ana Bastos
Earth Syst. Dynam., 13, 1505–1533, https://doi.org/10.5194/esd-13-1505-2022, https://doi.org/10.5194/esd-13-1505-2022, 2022
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Quantifying the imprint of large-scale atmospheric circulation dynamics and associated carbon cycle responses is key to improving our understanding of carbon cycle dynamics. Using a statistical model that relies on spatiotemporal sea level pressure as a proxy for large-scale atmospheric circulation, we quantify the fraction of interannual variability in atmospheric CO2 growth rate and the land CO2 sink that are driven by atmospheric circulation variability.
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
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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.
Christina Heinze-Deml, Sebastian Sippel, Angeline G. Pendergrass, Flavio Lehner, and Nicolai Meinshausen
Geosci. Model Dev., 14, 4977–4999, https://doi.org/10.5194/gmd-14-4977-2021, https://doi.org/10.5194/gmd-14-4977-2021, 2021
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Quantifying dynamical and thermodynamical components of regional precipitation change is a key challenge in climate science. We introduce a novel statistical model (Latent Linear Adjustment Autoencoder) that combines the flexibility of deep neural networks with the robustness advantages of linear regression. The method enables estimation of the contribution of a coarse-scale atmospheric circulation proxy to daily precipitation at high resolution and in a spatially coherent manner.
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Editorial statement
Detecting and attributing forced precipitation changes is a long-standing challenge in climate science. This study proposes an approach to efficiently extract information on forced precipitation changes from climate data and models, which can be valuable both from a scientific and policy-making perspective.
Detecting and attributing forced precipitation changes is a long-standing challenge in climate...
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.
Precipitation change is an important consequence of climate change, but it is hard to detect and...
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