Articles | Volume 18, issue 21
https://doi.org/10.5194/gmd-18-8269-2025
© 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/gmd-18-8269-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
METEORv1.0.1: a novel framework for emulating multi-timescale regional climate responses
Marit Sandstad
CORRESPONDING AUTHOR
CICERO Center for International Climate Research, Oslo 0349, Norway
Norman Julius Steinert
CICERO Center for International Climate Research, Oslo 0349, Norway
Susanne Baur
CECI, Université de Toulouse, CERFACS, CNRS, Toulouse, France
CNRM, Université de Toulouse, Météo-France/CNRS, Toulouse, France
Benjamin Mark Sanderson
CICERO Center for International Climate Research, Oslo 0349, Norway
Related authors
Srinath Krishnan, Ragnhild Bieltvedt Skeie, Øivind Hodnebrog, Gunnar Myhre, Maria Sand, Marit Sandstad, Hannah Bryant, Didier A. Hauglustaine, Fabien Paulot, Michael Prather, and David Stevenson
EGUsphere, https://doi.org/10.5194/egusphere-2025-4898, https://doi.org/10.5194/egusphere-2025-4898, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
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Hydrogen (H2) is an indirect greenhouse gas that can affect climate through chemical reactions in the atmosphere. To better understand this impact, it is important to constrain the sources and sinks of hydrogen. Using a suite of three-dimensional and one-dimensional models, we find that atmospheric production of hydrogen is 37–60 Tg/yr and that the geological source of H2 is much smaller than suggested. More field and isotopic measurements are needed to improve these estimates.
Gunnar Myhre, Øivind Hodnebrog, Srinath Krishnan, Maria Sand, Marit Sandstad, Ragnhild B. Skeie, Lieven Clarisse, Bruno Franco, Dylan B. Millet, Kelley C. Wells, Alexander Archibald, Hannah N. Bryant, Alex T. Chaudhri, David S. Stevenson, Didier Hauglustaine, Michael Prather, J. Christopher Kaiser, Dirk J. L. Olivie, Michael Schulz, Oliver Wild, Ye Wang, Thérèse Salameh, Jason E. Williams, Philippe Le Sager, Fabien Paulot, Kostas Tsigaridis, and Haley E. Plaas
EGUsphere, https://doi.org/10.5194/egusphere-2025-3057, https://doi.org/10.5194/egusphere-2025-3057, 2025
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Volatile organic compounds (VOCs) affect air quality and climate, but their behavior in the atmosphere is still uncertain. We launched a global research effort to compare how different models represent these compounds and to improve their accuracy. By analyzing model results alongside observations and satellite data, we aim to better understand the atmospheric composition of these compounds.
Benjamin M. Sanderson, Victor Brovkin, Rosie A. Fisher, David Hohn, Tatiana Ilyina, Chris D. Jones, Torben Koenigk, Charles Koven, Hongmei Li, David M. Lawrence, Peter Lawrence, Spencer Liddicoat, Andrew H. MacDougall, Nadine Mengis, Zebedee Nicholls, Eleanor O'Rourke, Anastasia Romanou, Marit Sandstad, Jörg Schwinger, Roland Séférian, Lori T. Sentman, Isla R. Simpson, Chris Smith, Norman J. Steinert, Abigail L. S. Swann, Jerry Tjiputra, and Tilo Ziehn
Geosci. Model Dev., 18, 5699–5724, https://doi.org/10.5194/gmd-18-5699-2025, https://doi.org/10.5194/gmd-18-5699-2025, 2025
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This study investigates how climate models warm in response to simplified carbon emissions trajectories, refining the understanding of climate reversibility and commitment. Metrics are defined for warming response to cumulative emissions and for the cessation of emissions or ramp-down to net-zero and net-negative levels. Results indicate that previous concentration-driven experiments may have overstated the Zero Emissions Commitment due to emissions rates exceeding historical levels.
Nina Schuhen, Carley E. Iles, Marit Sandstad, Viktor Ananiev, and Jana Sillmann
EGUsphere, https://doi.org/10.5194/egusphere-2025-3331, https://doi.org/10.5194/egusphere-2025-3331, 2025
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As climate changes, extremes are becoming increasingly frequent. We investigate the time of emergence for a large range of different extremes, meaning the earliest time when a significant change in these extremes can be detected beyond natural variability, whether in the past or in the future. The results based on 21 global climate models show considerable differences between regions, types of indices and emissions scenarios, as well as between temperature and precipitation extremes.
Ragnhild Bieltvedt Skeie, Marit Sandstad, Srinath Krishnan, Gunnar Myhre, and Maria Sand
Atmos. Chem. Phys., 25, 4929–4942, https://doi.org/10.5194/acp-25-4929-2025, https://doi.org/10.5194/acp-25-4929-2025, 2025
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Hydrogen leakages can alter the amount of climate gases in the atmosphere and hence have a climate impact. In this study we investigate, using an atmospheric chemistry model, how this indirect climate effect differs with different amounts of leakages and with where the hydrogen leaks and if this effect changes in the future. The effect is largest for emissions far from areas where hydrogen is removed from the atmosphere by the soil, but these are not relevant locations for a future hydrogen economy.
Marit Sandstad, Borgar Aamaas, Ane Nordlie Johansen, Marianne Tronstad Lund, Glen Philip Peters, Bjørn Hallvard Samset, Benjamin Mark Sanderson, and Ragnhild Bieltvedt Skeie
Geosci. Model Dev., 17, 6589–6625, https://doi.org/10.5194/gmd-17-6589-2024, https://doi.org/10.5194/gmd-17-6589-2024, 2024
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The CICERO-SCM has existed as a Fortran model since 1999 that calculates the radiative forcing and concentrations from emissions and is an upwelling diffusion energy balance model of the ocean that calculates temperature change. In this paper, we describe an updated version ported to Python and publicly available at https://github.com/ciceroOslo/ciceroscm (https://doi.org/10.5281/zenodo.10548720). This version contains functionality for parallel runs and automatic calibration.
David Gampe, Clemens Schwingshackl, Andrea Böhnisch, Magdalena Mittermeier, Marit Sandstad, and Raul R. Wood
Earth Syst. Dynam., 15, 589–605, https://doi.org/10.5194/esd-15-589-2024, https://doi.org/10.5194/esd-15-589-2024, 2024
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Using a special suite of climate simulations, we determine if and when climate change is detectable and translate this to the global warming prevalent in the corresponding year. Our results show that, at 1.5°C warming, >85 % of the global population (>95 % at 2.0° warming) is already exposed to nighttime temperatures altered by climate change beyond natural variability. Furthermore, even incremental changes in global warming levels result in increased human exposure to emerged climate signals.
Jarmo S. Kikstra, Zebedee R. J. Nicholls, Christopher J. Smith, Jared Lewis, Robin D. Lamboll, Edward Byers, Marit Sandstad, Malte Meinshausen, Matthew J. Gidden, Joeri Rogelj, Elmar Kriegler, Glen P. Peters, Jan S. Fuglestvedt, Ragnhild B. Skeie, Bjørn H. Samset, Laura Wienpahl, Detlef P. van Vuuren, Kaj-Ivar van der Wijst, Alaa Al Khourdajie, Piers M. Forster, Andy Reisinger, Roberto Schaeffer, and Keywan Riahi
Geosci. Model Dev., 15, 9075–9109, https://doi.org/10.5194/gmd-15-9075-2022, https://doi.org/10.5194/gmd-15-9075-2022, 2022
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Assessing hundreds or thousands of emission scenarios in terms of their global mean temperature implications requires standardised procedures of infilling, harmonisation, and probabilistic temperature assessments. We here present the open-source
climate-assessmentworkflow that was used in the IPCC AR6 Working Group III report. The paper provides key insight for anyone wishing to understand the assessment of climate outcomes of mitigation pathways in the context of the Paris Agreement.
Katja Weigel, Lisa Bock, Bettina K. Gier, Axel Lauer, Mattia Righi, Manuel Schlund, Kemisola Adeniyi, Bouwe Andela, Enrico Arnone, Peter Berg, Louis-Philippe Caron, Irene Cionni, Susanna Corti, Niels Drost, Alasdair Hunter, Llorenç Lledó, Christian Wilhelm Mohr, Aytaç Paçal, Núria Pérez-Zanón, Valeriu Predoi, Marit Sandstad, Jana Sillmann, Andreas Sterl, Javier Vegas-Regidor, Jost von Hardenberg, and Veronika Eyring
Geosci. Model Dev., 14, 3159–3184, https://doi.org/10.5194/gmd-14-3159-2021, https://doi.org/10.5194/gmd-14-3159-2021, 2021
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This work presents new diagnostics for the Earth System Model Evaluation Tool (ESMValTool) v2.0 on the hydrological cycle, extreme events, impact assessment, regional evaluations, and ensemble member selection. The ESMValTool v2.0 diagnostics are developed by a large community of scientists aiming to facilitate the evaluation and comparison of Earth system models (ESMs) with a focus on the ESMs participating in the Coupled Model Intercomparison Project (CMIP).
Srinath Krishnan, Ragnhild Bieltvedt Skeie, Øivind Hodnebrog, Gunnar Myhre, Maria Sand, Marit Sandstad, Hannah Bryant, Didier A. Hauglustaine, Fabien Paulot, Michael Prather, and David Stevenson
EGUsphere, https://doi.org/10.5194/egusphere-2025-4898, https://doi.org/10.5194/egusphere-2025-4898, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
Hydrogen (H2) is an indirect greenhouse gas that can affect climate through chemical reactions in the atmosphere. To better understand this impact, it is important to constrain the sources and sinks of hydrogen. Using a suite of three-dimensional and one-dimensional models, we find that atmospheric production of hydrogen is 37–60 Tg/yr and that the geological source of H2 is much smaller than suggested. More field and isotopic measurements are needed to improve these estimates.
Norman J. Steinert and Benjamin M. Sanderson
Earth Syst. Dynam., 16, 1711–1721, https://doi.org/10.5194/esd-16-1711-2025, https://doi.org/10.5194/esd-16-1711-2025, 2025
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In this study, we explore how carbon emissions from thawing permafrost, known as the permafrost carbon feedback, affect two important climate metrics: how much the Earth warms per amount of carbon we emit and how much warming continues after we stop emitting carbon. Our study tackles a major gap in how we estimate future climate change. Using simplified climate models, we find a generalizable relationship between the permafrost carbon feedback and its additional warming impact on climate.
John P. Dunne, Helene T. Hewitt, Julie M. Arblaster, Frédéric Bonou, Olivier Boucher, Tereza Cavazos, Beth Dingley, Paul J. Durack, Birgit Hassler, Martin Juckes, Tomoki Miyakawa, Matt Mizielinski, Vaishali Naik, Zebedee Nicholls, Eleanor O'Rourke, Robert Pincus, Benjamin M. Sanderson, Isla R. Simpson, and Karl E. Taylor
Geosci. Model Dev., 18, 6671–6700, https://doi.org/10.5194/gmd-18-6671-2025, https://doi.org/10.5194/gmd-18-6671-2025, 2025
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The seventh phase of the Coupled Model Intercomparison Project (CMIP7) coordinates efforts to answer key and timely climate science questions and facilitate delivery of relevant multi-model simulations for prediction and projection; characterization, attribution, and process understanding; and vulnerability, impact, and adaptation analysis. Key to the CMIP7 design are the mandatory Diagnostic, Evaluation and Characterization of Klima and optional Assessment Fast Track experiments.
Colin Jones, Isaline Bossert, Donovan P. Dennis, Hazel Jeffery, Chris D. Jones, Torben Koenigk, Sina Loriani, Benjamin Sanderson, Roland Séférian, Klaus Wyser, Shuting Yang, Manabu Abe, Sebastian Bathiany, Pascale Braconnot, Victor Brovkin, Friedrich A. Burger, Patrica Cadule, Frederic S. Castruccio, Gokhan Danabasoglu, Andrea Dittus, Jonathan F. Donges, Friederike Fröb, Thomas Frölicher, Goran Georgievski, Chuncheng Guo, Aixue Hu, Peter Lawrence, Paul Lerner, José Licón-Saláiz, Bette Otto-Bliesner, Anastasia Romanou, Elena Shevliakova, Yona Silvy, Didier Swingedouw, Jerry Tjiputra, Jeremy Walton, Andy Wiltshire, Ricarda Winkelmann, Richard Wood, Tokuta Yokohata, and Tilo Ziehn
EGUsphere, https://doi.org/10.5194/egusphere-2025-3604, https://doi.org/10.5194/egusphere-2025-3604, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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We introduce a new Earth system model experiment protocol to help researchers understand how Earth might respond to positive, zero, and negative carbon emissions. This protocol enables different models to be compared following similar warming and cooling rates. Researchers use the models to explore how the Earth reacts to different climate futures, including the risk of tipping points being exceeded and whether changes can be reversed. The results will support improved long-term climate policy.
Ken S. Carslaw, Leighton A. Regayre, Ulrike Proske, Andrew Gettelman, David M. H. Sexton, Yun Qian, Lauren Marshall, Oliver Wild, Marcus van Lier-Walqui, Annika Oertel, Saloua Peatier, Ben Yang, Jill S. Johnson, Sihan Li, Daniel T. McCoy, Benjamin M. Sanderson, Christina J. Williamson, Gregory S. Elsaesser, Kuniko Yamazaki, and Ben B. B. Booth
EGUsphere, https://doi.org/10.5194/egusphere-2025-4341, https://doi.org/10.5194/egusphere-2025-4341, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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A major challenge in climate science is reducing projection uncertainty despite advances in models and observational constraints. Perturbed parameter ensembles (PPEs) offer a powerful tool to explore and reduce uncertainty by revealing model weaknesses and guiding development. PPEs are now widely applied across climate systems and scales. We argue they should be prioritized alongside complexity and resolution in model resource planning.
Gunnar Myhre, Øivind Hodnebrog, Srinath Krishnan, Maria Sand, Marit Sandstad, Ragnhild B. Skeie, Lieven Clarisse, Bruno Franco, Dylan B. Millet, Kelley C. Wells, Alexander Archibald, Hannah N. Bryant, Alex T. Chaudhri, David S. Stevenson, Didier Hauglustaine, Michael Prather, J. Christopher Kaiser, Dirk J. L. Olivie, Michael Schulz, Oliver Wild, Ye Wang, Thérèse Salameh, Jason E. Williams, Philippe Le Sager, Fabien Paulot, Kostas Tsigaridis, and Haley E. Plaas
EGUsphere, https://doi.org/10.5194/egusphere-2025-3057, https://doi.org/10.5194/egusphere-2025-3057, 2025
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Volatile organic compounds (VOCs) affect air quality and climate, but their behavior in the atmosphere is still uncertain. We launched a global research effort to compare how different models represent these compounds and to improve their accuracy. By analyzing model results alongside observations and satellite data, we aim to better understand the atmospheric composition of these compounds.
Benjamin M. Sanderson, Victor Brovkin, Rosie A. Fisher, David Hohn, Tatiana Ilyina, Chris D. Jones, Torben Koenigk, Charles Koven, Hongmei Li, David M. Lawrence, Peter Lawrence, Spencer Liddicoat, Andrew H. MacDougall, Nadine Mengis, Zebedee Nicholls, Eleanor O'Rourke, Anastasia Romanou, Marit Sandstad, Jörg Schwinger, Roland Séférian, Lori T. Sentman, Isla R. Simpson, Chris Smith, Norman J. Steinert, Abigail L. S. Swann, Jerry Tjiputra, and Tilo Ziehn
Geosci. Model Dev., 18, 5699–5724, https://doi.org/10.5194/gmd-18-5699-2025, https://doi.org/10.5194/gmd-18-5699-2025, 2025
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This study investigates how climate models warm in response to simplified carbon emissions trajectories, refining the understanding of climate reversibility and commitment. Metrics are defined for warming response to cumulative emissions and for the cessation of emissions or ramp-down to net-zero and net-negative levels. Results indicate that previous concentration-driven experiments may have overstated the Zero Emissions Commitment due to emissions rates exceeding historical levels.
Nina Schuhen, Carley E. Iles, Marit Sandstad, Viktor Ananiev, and Jana Sillmann
EGUsphere, https://doi.org/10.5194/egusphere-2025-3331, https://doi.org/10.5194/egusphere-2025-3331, 2025
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As climate changes, extremes are becoming increasingly frequent. We investigate the time of emergence for a large range of different extremes, meaning the earliest time when a significant change in these extremes can be detected beyond natural variability, whether in the past or in the future. The results based on 21 global climate models show considerable differences between regions, types of indices and emissions scenarios, as well as between temperature and precipitation extremes.
Félix García-Pereira, Jesús Fidel González-Rouco, Nagore Meabe-Yanguas, Philipp de Vrese, Norman Julius Steinert, Johann Jungclaus, and Stephan Lorenz
EGUsphere, https://doi.org/10.5194/egusphere-2025-2126, https://doi.org/10.5194/egusphere-2025-2126, 2025
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This work shows that changing the hydrological state of permafrost produces differences of up to 3 °C in the annual ground temperature, 1–2 m in the active layer thickness, and 5 million km2 in the permafrost extent. Including a deeper vertical thermal scheme reduces the extent decline by more than 2 million km2 in the highest radiative emission scenario. This is shown for the first time in fully-coupled experiments with an Earth System Model.
Ricarda Winkelmann, Donovan P. Dennis, Jonathan F. Donges, Sina Loriani, Ann Kristin Klose, Jesse F. Abrams, Jorge Alvarez-Solas, Torsten Albrecht, David Armstrong McKay, Sebastian Bathiany, Javier Blasco Navarro, Victor Brovkin, Eleanor Burke, Gokhan Danabasoglu, Reik V. Donner, Markus Drüke, Goran Georgievski, Heiko Goelzer, Anna B. Harper, Gabriele Hegerl, Marina Hirota, Aixue Hu, Laura C. Jackson, Colin Jones, Hyungjun Kim, Torben Koenigk, Peter Lawrence, Timothy M. Lenton, Hannah Liddy, José Licón-Saláiz, Maxence Menthon, Marisa Montoya, Jan Nitzbon, Sophie Nowicki, Bette Otto-Bliesner, Francesco Pausata, Stefan Rahmstorf, Karoline Ramin, Alexander Robinson, Johan Rockström, Anastasia Romanou, Boris Sakschewski, Christina Schädel, Steven Sherwood, Robin S. Smith, Norman J. Steinert, Didier Swingedouw, Matteo Willeit, Wilbert Weijer, Richard Wood, Klaus Wyser, and Shuting Yang
EGUsphere, https://doi.org/10.5194/egusphere-2025-1899, https://doi.org/10.5194/egusphere-2025-1899, 2025
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The Tipping Points Modelling Intercomparison Project (TIPMIP) is an international collaborative effort to systematically assess tipping point risks in the Earth system using state-of-the-art coupled and stand-alone domain models. TIPMIP will provide a first global atlas of potential tipping dynamics, respective critical thresholds and key uncertainties, generating an important building block towards a comprehensive scientific basis for policy- and decision-making.
Ragnhild Bieltvedt Skeie, Marit Sandstad, Srinath Krishnan, Gunnar Myhre, and Maria Sand
Atmos. Chem. Phys., 25, 4929–4942, https://doi.org/10.5194/acp-25-4929-2025, https://doi.org/10.5194/acp-25-4929-2025, 2025
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Hydrogen leakages can alter the amount of climate gases in the atmosphere and hence have a climate impact. In this study we investigate, using an atmospheric chemistry model, how this indirect climate effect differs with different amounts of leakages and with where the hydrogen leaks and if this effect changes in the future. The effect is largest for emissions far from areas where hydrogen is removed from the atmosphere by the soil, but these are not relevant locations for a future hydrogen economy.
Susanne Baur, Benjamin M. Sanderson, Roland Séférian, and Laurent Terray
Earth Syst. Dynam., 16, 667–681, https://doi.org/10.5194/esd-16-667-2025, https://doi.org/10.5194/esd-16-667-2025, 2025
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Stratospheric aerosol injection (SAI) could be used alongside mitigation to reduce global warming. Previous studies suggest that more atmospheric CO2 is taken up when SAI is deployed. Here, we look at the entire SAI deployment from start to after termination. We show how the initial CO2 uptake benefit, and hence lower mitigation burden, is reduced in later stages of SAI, where the reduction in natural CO2 uptake turns into an additional mitigation burden.
Camilla Mathison, Eleanor J. Burke, Gregory Munday, Chris D. Jones, Chris J. Smith, Norman J. Steinert, Andy J. Wiltshire, Chris Huntingford, Eszter Kovacs, Laila K. Gohar, Rebecca M. Varney, and Douglas McNeall
Geosci. Model Dev., 18, 1785–1808, https://doi.org/10.5194/gmd-18-1785-2025, https://doi.org/10.5194/gmd-18-1785-2025, 2025
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We present PRIME (Probabilistic Regional Impacts from Model patterns and Emissions), which is designed to take new emissions scenarios and rapidly provide regional impact information. PRIME allows large ensembles to be run on multi-centennial timescales, including the analysis of many important variables for impact assessments. Our evaluation shows that PRIME reproduces the climate response for known scenarios, providing confidence in using PRIME for novel scenarios.
Detlef van Vuuren, Brian O'Neill, Claudia Tebaldi, Louise Chini, Pierre Friedlingstein, Tomoko Hasegawa, Keywan Riahi, Benjamin Sanderson, Bala Govindasamy, Nico Bauer, Veronika Eyring, Cheikh Fall, Katja Frieler, Matthew Gidden, Laila Gohar, Andrew Jones, Andrew King, Reto Knutti, Elmar Kriegler, Peter Lawrence, Chris Lennard, Jason Lowe, Camila Mathison, Shahbaz Mehmood, Luciana Prado, Qiang Zhang, Steven Rose, Alexander Ruane, Carl-Friederich Schleussner, Roland Seferian, Jana Sillmann, Chris Smith, Anna Sörensson, Swapna Panickal, Kaoru Tachiiri, Naomi Vaughan, Saritha Vishwanathan, Tokuta Yokohata, and Tilo Ziehn
EGUsphere, https://doi.org/10.5194/egusphere-2024-3765, https://doi.org/10.5194/egusphere-2024-3765, 2025
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We propose a set of six 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.
Benjamin M. Sanderson, Ben B. B. Booth, John Dunne, Veronika Eyring, Rosie A. Fisher, Pierre Friedlingstein, Matthew J. Gidden, Tomohiro Hajima, Chris D. Jones, Colin G. Jones, Andrew King, Charles D. Koven, David M. Lawrence, Jason Lowe, Nadine Mengis, Glen P. Peters, Joeri Rogelj, Chris Smith, Abigail C. Snyder, Isla R. Simpson, Abigail L. S. Swann, Claudia Tebaldi, Tatiana Ilyina, Carl-Friedrich Schleussner, Roland Séférian, Bjørn H. Samset, Detlef van Vuuren, and Sönke Zaehle
Geosci. Model Dev., 17, 8141–8172, https://doi.org/10.5194/gmd-17-8141-2024, https://doi.org/10.5194/gmd-17-8141-2024, 2024
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We discuss how, in order to provide more relevant guidance for climate policy, coordinated climate experiments should adopt a greater focus on simulations where Earth system models are provided with carbon emissions from fossil fuels together with land use change instructions, rather than past approaches that have largely focused on experiments with prescribed atmospheric carbon dioxide concentrations. We discuss how these goals might be achieved in coordinated climate modeling experiments.
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.
Marit Sandstad, Borgar Aamaas, Ane Nordlie Johansen, Marianne Tronstad Lund, Glen Philip Peters, Bjørn Hallvard Samset, Benjamin Mark Sanderson, and Ragnhild Bieltvedt Skeie
Geosci. Model Dev., 17, 6589–6625, https://doi.org/10.5194/gmd-17-6589-2024, https://doi.org/10.5194/gmd-17-6589-2024, 2024
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The CICERO-SCM has existed as a Fortran model since 1999 that calculates the radiative forcing and concentrations from emissions and is an upwelling diffusion energy balance model of the ocean that calculates temperature change. In this paper, we describe an updated version ported to Python and publicly available at https://github.com/ciceroOslo/ciceroscm (https://doi.org/10.5281/zenodo.10548720). This version contains functionality for parallel runs and automatic calibration.
Saloua Peatier, Benjamin M. Sanderson, and Laurent Terray
Earth Syst. Dynam., 15, 987–1014, https://doi.org/10.5194/esd-15-987-2024, https://doi.org/10.5194/esd-15-987-2024, 2024
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The calibration of Earth system model parameters is a high-dimensionality problem subject to data, time, and computational constraints. In this study, we propose a practical solution for finding diverse near-optimal solutions. We argue that the effective degrees of freedom in the model performance response to parameter input is relatively small. Comparably performing parameter configurations exist and showcase different trade-offs in model errors, providing insights for model development.
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
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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”.
David Gampe, Clemens Schwingshackl, Andrea Böhnisch, Magdalena Mittermeier, Marit Sandstad, and Raul R. Wood
Earth Syst. Dynam., 15, 589–605, https://doi.org/10.5194/esd-15-589-2024, https://doi.org/10.5194/esd-15-589-2024, 2024
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Using a special suite of climate simulations, we determine if and when climate change is detectable and translate this to the global warming prevalent in the corresponding year. Our results show that, at 1.5°C warming, >85 % of the global population (>95 % at 2.0° warming) is already exposed to nighttime temperatures altered by climate change beyond natural variability. Furthermore, even incremental changes in global warming levels result in increased human exposure to emerged climate signals.
Félix García-Pereira, Jesús Fidel González-Rouco, Camilo Melo-Aguilar, Norman Julius Steinert, Elena García-Bustamante, Philip de Vrese, Johann Jungclaus, Stephan Lorenz, Stefan Hagemann, Francisco José Cuesta-Valero, Almudena García-García, and Hugo Beltrami
Earth Syst. Dynam., 15, 547–564, https://doi.org/10.5194/esd-15-547-2024, https://doi.org/10.5194/esd-15-547-2024, 2024
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According to climate model estimates, the land stored 2 % of the system's heat excess in the last decades, while observational studies show it was around 6 %. This difference stems from these models using land components that are too shallow to constrain land heat uptake. Deepening the land component does not affect the surface temperature. This result can be used to derive land heat uptake estimates from different sources, which are much closer to previous observational reports.
Susanne Baur, Benjamin M. Sanderson, Roland Séférian, and Laurent Terray
Earth Syst. Dynam., 15, 307–322, https://doi.org/10.5194/esd-15-307-2024, https://doi.org/10.5194/esd-15-307-2024, 2024
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Most solar radiation modification (SRM) simulations assume no physical coupling between mitigation and SRM. We analyze the impact of SRM on photovoltaic (PV) and concentrated solar power (CSP) and find that almost all regions have reduced PV and CSP potential compared to a mitigated or unmitigated scenario, especially in the middle and high latitudes. This suggests that SRM could pose challenges for meeting energy demands with solar renewable resources.
Nico Wunderling, Anna S. von der Heydt, Yevgeny Aksenov, Stephen Barker, Robbin Bastiaansen, Victor Brovkin, Maura Brunetti, Victor Couplet, Thomas Kleinen, Caroline H. Lear, Johannes Lohmann, Rosa Maria Roman-Cuesta, Sacha Sinet, Didier Swingedouw, Ricarda Winkelmann, Pallavi Anand, Jonathan Barichivich, Sebastian Bathiany, Mara Baudena, John T. Bruun, Cristiano M. Chiessi, Helen K. Coxall, David Docquier, Jonathan F. Donges, Swinda K. J. Falkena, Ann Kristin Klose, David Obura, Juan Rocha, Stefanie Rynders, Norman Julius Steinert, and Matteo Willeit
Earth Syst. Dynam., 15, 41–74, https://doi.org/10.5194/esd-15-41-2024, https://doi.org/10.5194/esd-15-41-2024, 2024
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This paper maps out the state-of-the-art literature on interactions between tipping elements relevant for current global warming pathways. We find indications that many of the interactions between tipping elements are destabilizing. This means that tipping cascades cannot be ruled out on centennial to millennial timescales at global warming levels between 1.5 and 2.0 °C or on shorter timescales if global warming surpasses 2.0 °C.
Félix García-Pereira, Jesús Fidel González-Rouco, Thomas Schmid, Camilo Melo-Aguilar, Cristina Vegas-Cañas, Norman Julius Steinert, Pedro José Roldán-Gómez, Francisco José Cuesta-Valero, Almudena García-García, Hugo Beltrami, and Philipp de Vrese
SOIL, 10, 1–21, https://doi.org/10.5194/soil-10-1-2024, https://doi.org/10.5194/soil-10-1-2024, 2024
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This work addresses air–ground temperature coupling and propagation into the subsurface in a mountainous area in central Spain using surface and subsurface data from six meteorological stations. Heat transfer of temperature changes at the ground surface occurs mainly by conduction controlled by thermal diffusivity of the subsurface, which varies with depth and time. A new methodology shows that near-surface diffusivity and soil moisture content changes with time are closely related.
Philipp de Vrese, Goran Georgievski, Jesus Fidel Gonzalez Rouco, Dirk Notz, Tobias Stacke, Norman Julius Steinert, Stiig Wilkenskjeld, and Victor Brovkin
The Cryosphere, 17, 2095–2118, https://doi.org/10.5194/tc-17-2095-2023, https://doi.org/10.5194/tc-17-2095-2023, 2023
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The current generation of Earth system models exhibits large inter-model differences in the simulated climate of the Arctic and subarctic zone. We used an adapted version of the Max Planck Institute (MPI) Earth System Model to show that differences in the representation of the soil hydrology in permafrost-affected regions could help explain a large part of this inter-model spread and have pronounced impacts on important elements of Earth systems as far to the south as the tropics.
Susanne Baur, Alexander Nauels, Zebedee Nicholls, Benjamin M. Sanderson, and Carl-Friedrich Schleussner
Earth Syst. Dynam., 14, 367–381, https://doi.org/10.5194/esd-14-367-2023, https://doi.org/10.5194/esd-14-367-2023, 2023
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Solar radiation modification (SRM) artificially cools global temperature without acting on the cause of climate change. This study looks at how long SRM would have to be deployed to limit warming to 1.5 °C and how this timeframe is affected by different levels of mitigation, negative emissions and climate uncertainty. None of the three factors alone can guarantee short SRM deployment. Due to their uncertainty at the time of SRM initialization, any deployment risks may be several centuries long.
Jarmo S. Kikstra, Zebedee R. J. Nicholls, Christopher J. Smith, Jared Lewis, Robin D. Lamboll, Edward Byers, Marit Sandstad, Malte Meinshausen, Matthew J. Gidden, Joeri Rogelj, Elmar Kriegler, Glen P. Peters, Jan S. Fuglestvedt, Ragnhild B. Skeie, Bjørn H. Samset, Laura Wienpahl, Detlef P. van Vuuren, Kaj-Ivar van der Wijst, Alaa Al Khourdajie, Piers M. Forster, Andy Reisinger, Roberto Schaeffer, and Keywan Riahi
Geosci. Model Dev., 15, 9075–9109, https://doi.org/10.5194/gmd-15-9075-2022, https://doi.org/10.5194/gmd-15-9075-2022, 2022
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Assessing hundreds or thousands of emission scenarios in terms of their global mean temperature implications requires standardised procedures of infilling, harmonisation, and probabilistic temperature assessments. We here present the open-source
climate-assessmentworkflow that was used in the IPCC AR6 Working Group III report. The paper provides key insight for anyone wishing to understand the assessment of climate outcomes of mitigation pathways in the context of the Paris Agreement.
Benjamin M. Sanderson and Maria Rugenstein
Earth Syst. Dynam., 13, 1715–1736, https://doi.org/10.5194/esd-13-1715-2022, https://doi.org/10.5194/esd-13-1715-2022, 2022
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Equilibrium climate sensitivity (ECS) is a measure of how much long-term warming should be expected in response to a change in greenhouse gas concentrations. It is generally calculated in climate models by extrapolating global average temperatures to a point of where the planet is no longer a net absorber of energy. Here we show that some climate models experience energy leaks which change as the planet warms, undermining the standard approach and biasing some existing model estimates of ECS.
Jörg Schwinger, Ali Asaadi, Norman Julius Steinert, and Hanna Lee
Earth Syst. Dynam., 13, 1641–1665, https://doi.org/10.5194/esd-13-1641-2022, https://doi.org/10.5194/esd-13-1641-2022, 2022
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We test whether climate change can be partially reversed if CO2 is removed from the atmosphere to compensate for too large past and near-term emissions by using idealized model simulations of overshoot pathways. On a timescale of 100 years, we find a high degree of reversibility if the overshoot size remains small, and we do not find tipping points even for intense overshoots. We caution that current Earth system models are most likely not able to skilfully model tipping points in ecosystems.
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.
Camille Besombes, Olivier Pannekoucke, Corentin Lapeyre, Benjamin Sanderson, and Olivier Thual
Nonlin. Processes Geophys., 28, 347–370, https://doi.org/10.5194/npg-28-347-2021, https://doi.org/10.5194/npg-28-347-2021, 2021
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This paper investigates the potential of a type of deep generative neural network to produce realistic weather situations when trained from the climate of a general circulation model. The generator represents the climate in a compact latent space. It is able to reproduce many aspects of the targeted multivariate distribution. Some properties of our method open new perspectives such as the exploration of the extremes close to a given state or how to connect two realistic weather states.
Katja Weigel, Lisa Bock, Bettina K. Gier, Axel Lauer, Mattia Righi, Manuel Schlund, Kemisola Adeniyi, Bouwe Andela, Enrico Arnone, Peter Berg, Louis-Philippe Caron, Irene Cionni, Susanna Corti, Niels Drost, Alasdair Hunter, Llorenç Lledó, Christian Wilhelm Mohr, Aytaç Paçal, Núria Pérez-Zanón, Valeriu Predoi, Marit Sandstad, Jana Sillmann, Andreas Sterl, Javier Vegas-Regidor, Jost von Hardenberg, and Veronika Eyring
Geosci. Model Dev., 14, 3159–3184, https://doi.org/10.5194/gmd-14-3159-2021, https://doi.org/10.5194/gmd-14-3159-2021, 2021
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This work presents new diagnostics for the Earth System Model Evaluation Tool (ESMValTool) v2.0 on the hydrological cycle, extreme events, impact assessment, regional evaluations, and ensemble member selection. The ESMValTool v2.0 diagnostics are developed by a large community of scientists aiming to facilitate the evaluation and comparison of Earth system models (ESMs) with a focus on the ESMs participating in the Coupled Model Intercomparison Project (CMIP).
Claudia Tebaldi, Kevin Debeire, Veronika Eyring, Erich Fischer, John Fyfe, Pierre Friedlingstein, Reto Knutti, Jason Lowe, Brian O'Neill, Benjamin Sanderson, Detlef van Vuuren, Keywan Riahi, Malte Meinshausen, Zebedee Nicholls, Katarzyna B. Tokarska, George Hurtt, Elmar Kriegler, Jean-Francois Lamarque, Gerald Meehl, Richard Moss, Susanne E. Bauer, Olivier Boucher, Victor Brovkin, Young-Hwa Byun, Martin Dix, Silvio Gualdi, Huan Guo, Jasmin G. John, Slava Kharin, YoungHo Kim, Tsuyoshi Koshiro, Libin Ma, Dirk Olivié, Swapna Panickal, Fangli Qiao, Xinyao Rong, Nan Rosenbloom, Martin Schupfner, Roland Séférian, Alistair Sellar, Tido Semmler, Xiaoying Shi, Zhenya Song, Christian Steger, Ronald Stouffer, Neil Swart, Kaoru Tachiiri, Qi Tang, Hiroaki Tatebe, Aurore Voldoire, Evgeny Volodin, Klaus Wyser, Xiaoge Xin, Shuting Yang, Yongqiang Yu, and Tilo Ziehn
Earth Syst. Dynam., 12, 253–293, https://doi.org/10.5194/esd-12-253-2021, https://doi.org/10.5194/esd-12-253-2021, 2021
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We present an overview of CMIP6 ScenarioMIP outcomes from up to 38 participating ESMs according to the new SSP-based scenarios. Average temperature and precipitation projections according to a wide range of forcings, spanning a wider range than the CMIP5 projections, are documented as global averages and geographic patterns. Times of crossing various warming levels are computed, together with benefits of mitigation for selected pairs of scenarios. Comparisons with CMIP5 are also discussed.
Katherine Dagon, Benjamin M. Sanderson, Rosie A. Fisher, and David M. Lawrence
Adv. Stat. Clim. Meteorol. Oceanogr., 6, 223–244, https://doi.org/10.5194/ascmo-6-223-2020, https://doi.org/10.5194/ascmo-6-223-2020, 2020
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Uncertainties in land model projections are important to understand in order to build confidence in Earth system modeling. In this paper, we introduce a framework for estimating uncertain land model parameters with machine learning. This method increases the computational efficiency of this process relative to traditional hand tuning approaches and provides objective methods to assess the results. We further identify key processes and parameters that are important for accurate land modeling.
Cited articles
Aamaas, B., Berntsen, T. K., Fuglestvedt, J. S., Shine, K. P., and Bellouin, N.: Regional emission metrics for short-lived climate forcers from multiple models, Atmos. Chem. Phys., 16, 7451–7468, https://doi.org/10.5194/acp-16-7451-2016, 2016. a
Adams, P. J., Seinfeld, J. H., Koch, D., Mickley, L., and Jacob, D.: General circulation model assessment of direct radiative forcing by the sulfate-nitrate-ammonium-water inorganic aerosol system, J. Geophys. Res.-Atmos., 106, 1097–1111, https://doi.org/10.1029/2000JD900512, 2001. a, b
Barata, J. C. A. and Hussein, M. S.: The Moore–Penrose pseudoinverse: A tutorial review of the theory, Brazilian Journal of Physics, 42, 146–165, https://doi.org/10.1007/s13538-011-0052-z, 2012. a, b
Bauer, S. E., Koch, D., Unger, N., Metzger, S. M., Shindell, D. T., and Streets, D. G.: Nitrate aerosols today and in 2030: a global simulation including aerosols and tropospheric ozone, Atmos. Chem. Phys., 7, 5043–5059, https://doi.org/10.5194/acp-7-5043-2007, 2007. a, b
Bellouin, N., Rae, J., Jones, A., Johnson, C., Haywood, J., and Boucher, O.: Aerosol forcing in the Climate Model Intercomparison Project (CMIP5) simulations by HadGEM2-ES and the role of ammonium nitrate, J. Geophys. Res.-Atmos., 116, https://doi.org/10.1029/2011JD016074, 2011. a, b
Beusch, L., Gudmundsson, L., and Seneviratne, S. I.: Emulating Earth system model temperatures with MESMER: from global mean temperature trajectories to grid-point-level realizations on land, Earth Syst. Dynam., 11, 139–159, https://doi.org/10.5194/esd-11-139-2020, 2020. a, b, c
Beusch, L., Nicholls, Z., Gudmundsson, L., Hauser, M., Meinshausen, M., and Seneviratne, S. I.: From emission scenarios to spatially resolved projections with a chain of computationally efficient emulators: coupling of MAGICC (v7.5.1) and MESMER (v0.8.3), Geosci. Model Dev., 15, 2085–2103, https://doi.org/10.5194/gmd-15-2085-2022, 2022. a
Bouabid, S., Sejdinovic, D., and Watson-Parris, D.: FaIRGP: A Bayesian Energy Balance Model for Surface Temperatures Emulation, Journal of Advances in Modeling Earth Systems, 16, e2023MS003926, https://doi.org/10.1029/2023MS003926, 2024. a
Cinquini, L., Crichton, D., Mattmann, C., Harney, J., Shipman, G., Wang, F., Ananthakrishnan, R., Miller, N., Denvil, S., Morgan, M., Pobre, Z., Bell, G. M., Doutriaux, C., Drach, R., Williams, D., Kershaw, P., Pascoe, S., Gonzalez, E., Fiore, S., and Schweitzer, R.: The Earth System Grid Federation: An open infrastructure for access to distributed geospatial data, Future Gener. Comput. Syst., 36, 400–417, https://esgf-node.llnl.gov (last access: 31 October 2025), 2014. a
Collins, M., Knutti, R., Arblaster, J., Dufresne, J.-L., Fichefet, T., Friedlingstein, P., Gao, X., Gutowski, W., Johns, T., Krinner, G., Shongwe, M., Tebaldi, C., Weaver, A., and Wehner, M.: Long-term Climate Change: Projections, Commitments and Irreversibility, in: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by Stocker, T., Qin, D., Plattner, G.-K., Tignor, M., Allen, S., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P., sect. 12, Cambridge University Press, Cambridge, United Kingdom and New York, USA, 1029–1136, https://doi.org/10.1017/CBO9781107415324.024, 2013. a
Dietz, S., Rising, J., Stoerk, T., and Wagner, G.: Economic impacts of tipping points in the climate system, P. Natl. Acad. Sci. USA, 118, e2103081118, https://doi.org/10.1073/pnas.2103081118, 2021. a
Dunne, J. P., Hewitt, H. T., Arblaster, J. M., Bonou, F., Boucher, O., Cavazos, T., Dingley, B., Durack, P. J., Hassler, B., Juckes, M., Miyakawa, T., Mizielinski, M., Naik, V., Nicholls, Z., O'Rourke, E., Pincus, R., Sanderson, B. M., Simpson, I. R., and Taylor, K. E.: An evolving Coupled Model Intercomparison Project phase 7 (CMIP7) and Fast Track in support of future climate assessment, Geosci. Model Dev., 18, 6671–6700, https://doi.org/10.5194/gmd-18-6671-2025, 2025. a
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., and Taylor, K. E.: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization, Geosci. Model Dev., 9, 1937–1958, https://doi.org/10.5194/gmd-9-1937-2016, 2016. a, b, c
Ferrari, L., Carlino, A., Gazzotti, P., Tavoni, M., and Castelletti, A.: From optimal to robust climate strategies: expanding integrated assessment model ensembles to manage economic, social, and environmental objectives, Environ. Res. Lett., 17, 084029, https://doi.org/10.1088/1748-9326/ac843b, 2022. a
Forster, P., Storelvmo, T., Armour, K., Collins, W., Dufresne, J.-L., Frame, D., Lunt, D., Mauritsen, T., Palmer, M., Watanabe, M., Wild, M., and Zhang, H.: The Earth's Energy Budget, Climate Feedbacks, and Climate Sensitivity, 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., book section 7, 923–1054, Cambridge University Press, Cambridge, UK, New York, USA, https://doi.org/10.1017/9781009157896.009, 2021. a, b
Forster, P. M., Smith, C., Walsh, T., Lamb, W. F., Lamboll, R., Cassou, C., Hauser, M., Hausfather, Z., Lee, J.-Y., Palmer, M. D., von Schuckmann, K., Slangen, A. B. A., Szopa, S., Trewin, B., Yun, J., Gillett, N. P., Jenkins, S., Matthews, H. D., Raghavan, K., Ribes, A., Rogelj, J., Rosen, D., Zhang, X., Allen, M., Aleluia Reis, L., Andrew, R. M., Betts, R. A., Borger, A., Broersma, J. A., Burgess, S. N., Cheng, L., Friedlingstein, P., Domingues, C. M., Gambarini, M., Gasser, T., Gütschow, J., Ishii, M., Kadow, C., Kennedy, J., Killick, R. E., Krummel, P. B., Liné, A., Monselesan, D. P., Morice, C., Mühle, J., Naik, V., Peters, G. P., Pirani, A., Pongratz, J., Minx, J. C., Rigby, M., Rohde, R., Savita, A., Seneviratne, S. I., Thorne, P., Wells, C., Western, L. M., van der Werf, G. R., Wijffels, S. E., Masson-Delmotte, V., and Zhai, P.: Indicators of Global Climate Change 2024: annual update of key indicators of the state of the climate system and human influence, Earth Syst. Sci. Data, 17, 2641–2680, https://doi.org/10.5194/essd-17-2641-2025, 2025. a, b
Freese, L. M., Giani, P., Fiore, A. M., and Selin, N. E.: Spatially Resolved Temperature Response Functions to CO2 Emissions, Geophys. Res. Lett., 51, e2024GL108788, https://doi.org/10.1029/2024GL108788, 2024. a
Gillett, N. P., Shiogama, H., Funke, B., Hegerl, G., Knutti, R., Matthes, K., Santer, B. D., Stone, D., and Tebaldi, C.: The Detection and Attribution Model Intercomparison Project (DAMIP v1.0) contribution to CMIP6, Geosci. Model Dev., 9, 3685–3697, https://doi.org/10.5194/gmd-9-3685-2016, 2016. a, b
Good, P., Lowe, J. A., Andrews, T., Wiltshire, A., Chadwick, R., Ridley, J. K., Menary, M. B., Bouttes, N., Dufresne, J. L., Gregory, J. M., Schaller, N., and Shiogama, H.: Nonlinear regional warming with increasing CO2 concentrations, Nature Climate Change, 5, https://doi.org/10.1038/nclimate2498, 2015. a
Hauglustaine, D. A., Balkanski, Y., and Schulz, M.: A global model simulation of present and future nitrate aerosols and their direct radiative forcing of climate, Atmos. Chem. Phys., 14, 11031–11063, https://doi.org/10.5194/acp-14-11031-2014, 2014. a, b
Herger, N., Sanderson, B. M., and Knutti, R.: Improved pattern scaling approaches for the use in climate impact studies, Geophys. Res. Lett., 42, 3486–3494, https://doi.org/10.1002/2015GL063569, 2015. a
Hulme, M., Wigley, T. M. L., Barrow, E. andRaper, S., Centella, A., Smith, S., and Chipanshi, A.: Using a Climate Scenario Generator for Vulnerability and Adaptation Assessments, in: MAGICC and SCENGEN Version 2.4 Workbook and CD-ROM, edited by: Lim, B. and Smith, J., Reprint, University of East Anglia, Climatic Research Unit, East Anglia, 2000. a
Huntingford, C. and Cox, P.: An analogue model to derive additional climate change scenarios from existing GCM simulations, Clim. Dynam., 16, 575–586, https://doi.org/10.1007/s003820000067, 2000. a
IPCC: Climate Change 2021: The Physical Science Basis, Cambridge University Press, Cambridge, UK, New York, USA,https://doi.org/10.1017/9781009157896 2021. a
IPCC: Climate Change 2022: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, UK, New York, USA, https://doi.org/10.1017/9781009325844, 2022. a, b
Rising, J., Tedesco, M., Piontek, F., and Stainforth, D. A.: The missing risks of climate change, Nature, 610, 643–651, https://doi.org/10.1038/s41586-022-05243-6, 2022. a
Jonko, A. K., Shell, K. M., Sanderson, B. M., and Danabasoglu, G.: Climate feedbacks in CCSM3 under changing CO2 forcing, Part II: Variation of climate feedbacks and sensitivity with forcing, J. Climate, 26, 2784–2795, 2013. a
Kikstra, J. S., Waidelich, P., James Rising, D. Y., Hope, C., and Brierley, C. M.: The social cost of carbon dioxide under climate-economy feedbacks and temperature variability, Environ. Res. Lett., 16, https://doi.org/10.1088/1748-9326/ac1d0b, 2021. a
Liao, H. and Seinfeld, J. H.: Global impacts of gas-phase chemistry-aerosol interactions on direct radiative forcing by anthropogenic aerosols and ozone, J. Geophys. Res.-Atmos., 110, https://doi.org/10.1029/2005JD005907, 2005. a, b
Liao, H., Zhang, Y., Chen, W.-T., Raes, F., and Seinfeld, J. H.: Effect of chemistry-aerosol-climate coupling on predictions of future climate and future levels of tropospheric ozone and aerosols, J. Geophys. Res.-Atmos., 114, https://doi.org/10.1029/2008JD010984, 2009. a, b
Mansfield, L. A., Nowack, P. J., Kasoar, M., Everitt, R. G., Collins, W. J., and Voulgarakis, A.: Predicting global patterns of long-term climate change from short-term simulations using machine learning, npj Climate and Atmospheric Science, 3, https://doi.org/10.1038/s41612-020-00148-5, 2020. a
Mathison, C., Burke, E. J., Munday, G., Jones, C. D., Smith, C. J., Steinert, N. J., Wiltshire, A. J., Huntingford, C., Kovacs, E., Gohar, L. K., Varney, R. M., and McNeall, D.: A rapid-application emissions-to-impacts tool for scenario assessment: Probabilistic Regional Impacts from Model patterns and Emissions (PRIME), Geosci. Model Dev., 18, 1785–1808, https://doi.org/10.5194/gmd-18-1785-2025, 2025. a, b
Mitchell, T. D.: Pattern Scaling: An Examination of the Accuracy of the Technique for Describing Future Climates, Climatic Change, 60, 217–242, https://doi.org/10.1023/A:1026035305597, 2003. a
Monerie, P.-A., Wilcox, L. J., and Turner, A. G.: Effects of Anthropogenic Aerosol and Greenhouse Gas Emissions on Northern Hemisphere Monsoon Precipitation: Mechanisms and Uncertainty, J. Climate, 35, 2305–2326, https://doi.org/10.1175/JCLI-D-21-0412.1, 2022. a
Myhre, G., Forster, P. M., Samset, B. H., Hodnebrog, Ø., Sillmann, J., Aalbergsjø, S. G., Andrews, T., Boucher, O., Faluvegi, G., Fläschner, D., Iversen, T., Kasoar, M., Kharin, V., Kirkevåg, A., Lamarque, J.-F., Olivié, D., Richardson, T. B., Shindell, D., Shine, K. P., Stjern, C. W., Takemura, T., Voulgarakis, A., and Zwiers, F.: PDRMIP: A Precipitation Driver and Response Model Intercomparison Project – Protocol and Preliminary Results, B. Am. Meteorol. Soc., 98, 1185–1198, https://doi.org/10.1175/BAMS-D-16-0019.1, 2017. a, b, c, d, e, f, g
Myhre, G., Samset, B., Forster, P. M., Hodnebrog, Ø., Sandstad, M., Mohr, C. W., Sillmann, J., Stjern, C. W., Andrews, T., Boucher, O., Faluvegi, G., Iversen, T., Lamarque, J.-F., Kasoar, M., Kirkevåg, A., Kramer, R., Liu, L., Mülmenstädt, J., Olivié, D., Quaas, J., Richardson, T. B., Shawki, D., Shindell, D., Smith, C., Stier, P., Tang, T., Takemura, T., Voulgarakis, A., and Watson-Parris, D.: Scientific data from precipitation driver response model intercomparison project, Scientific Data, 9, 2052–4463, https://doi.org/10.1038/s41597-022-01194-9, 2022. a
Nath, S., Lejeune, Q., Beusch, L., Seneviratne, S. I., and Schleussner, C.-F.: MESMER-M: an Earth system model emulator for spatially resolved monthly temperature, Earth Syst. Dynam., 13, 851–877, https://doi.org/10.5194/esd-13-851-2022, 2022. a
Nath, S., Carreau, J., Kornhuber, K., Pfleiderer, P., Schleussner, C.-F., and Naveau, P.: MERCURY: A fast and versatile multi-resolution based global emulator of compound climate hazards, arXiv [preprint], https://doi.org/10.48550/arXiv.2501.04018, 2024. a
Nicholls, Z. and Gieseke, R.: RCMIP Phase 1 Data (v2.0.0), Zenodo [data set], https://doi.org/10.5281/zenodo.4016613, 2019. a
Nicholls, Z. R. J., Meinshausen, M., Lewis, J., Gieseke, R., Dommenget, D., Dorheim, K., Fan, C.-S., Fuglestvedt, J. S., Gasser, T., Golüke, U., Goodwin, P., Hartin, C., Hope, A. P., Kriegler, E., Leach, N. J., Marchegiani, D., McBride, L. A., Quilcaille, Y., Rogelj, J., Salawitch, R. J., Samset, B. H., Sandstad, M., Shiklomanov, A. N., Skeie, R. B., Smith, C. J., Smith, S., Tanaka, K., Tsutsui, J., and Xie, Z.: Reduced Complexity Model Intercomparison Project Phase 1: introduction and evaluation of global-mean temperature response, Geosci. Model Dev., 13, 5175–5190, https://doi.org/10.5194/gmd-13-5175-2020, 2020. a, b
Nicholls, Z., Meinshausen, M., Lewis, J., Corradi, M. R., Dorheim, K., Gasser, T., Gieseke, R., Hope, A. P., Leach, N. J., McBride, L. A., Quilcaille, Y., Rogelj, J., Salawitch, R. J., Samset, B. H., Sandstad, M., Shiklomanov, A., Skeie, R. B., Smith, C. J., Smith, S. J., Su, X., Tsutsui, J., Vega-Westhoff, B., and Woodard, D. L.: Reduced Complexity Model Intercomparison Project Phase 2: Synthesizing Earth System Knowledge for Probabilistic Climate Projections, Earth's Future, 9, e2020EF001900, https://doi.org/10.1029/2020EF001900, 2021. a
O'Neill, B. C., Tebaldi, C., van Vuuren, D. P., Eyring, V., Friedlingstein, P., Hurtt, G., Knutti, R., Kriegler, E., Lamarque, J.-F., Lowe, J., Meehl, G. A., Moss, R., Riahi, K., and Sanderson, B. M.: The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6, Geosci. Model Dev., 9, 3461–3482, https://doi.org/10.5194/gmd-9-3461-2016, 2016. a
Persad, G., Samset, B. H., Wilcox, L. J., Allen, R. J., Bollasina, M. A., Booth, B. B. B., Bonfils, C., Crocker, T., Joshi, M., Lund, M. T., Marvel, K., Merikanto, J., Nordling, K., Undorf, S., van Vuuren, D. P., Westervelt, D. M., and Zhao, A.: Rapidly evolving aerosol emissions are a dangerous omission from near-term climate risk assessments, Environ. Res.: Climate, 2, 032001, https://doi.org/10.1088/2752-5295/acd6af, 2023. a
Proistosescu, C. and Huybers, P. J.: Slow climate mode reconciles historical and model-based estimates of climate sensitivity, Science Advances, 3, e1602821, https://doi.org/10.1126/sciadv.1602821, 2017. a
Quilcaille, Y., Gudmundsson, L., Beusch, L., Hauser, M., and Seneviratne, S. I.: Showcasing MESMER-X: Spatially Resolved Emulation of Annual Maximum Temperatures of Earth System Models, Geophys. Res. Lett., 49, e2022GL099012, https://doi.org/10.1029/2022GL099012, 2022. a, b
Quilcaille, Y., Gudmundsson, L., and Seneviratne, S. I.: Extending MESMER-X: a spatially resolved Earth system model emulator for fire weather and soil moisture, Earth Syst. Dynam., 14, 1333–1362, https://doi.org/10.5194/esd-14-1333-2023, 2023. a, b
Rugenstein, M. A., Gregory, J. M., Schaller, N., Sedláček, J., and Knutti, R.: Multiannual ocean–atmosphere adjustments to radiative forcing, J. Climate, 29, 5643–5659, 2016. a
Samset, B. H., Sand, M., Smith, C. J., Bauer, S. E., Forster, P. M., Fuglestvedt, J. S., Osprey, S., and Schleussner, C.-F.: Climate Impacts From a Removal of Anthropogenic Aerosol Emissions, Geophys. Res. Lett., 45, 1020–1029, https://doi.org/10.1002/2017GL076079, 2018. a
Samset, B. H., Lund, M. T., Bollasina, M., Myhre, G., and Wilcox, L.: Emerging Asian aerosol patterns, Nat. Geosci., 12, 582–584, https://doi.org/10.1038/s41561-019-0424-5, 2019. a
Sanderson, B., Sandstad, M., and normansteinert: benmsanderson/METEOR: v1.0.1 (v1.0.1), Zenodo [code], https://doi.org/10.5281/zenodo.15732955, 2025. a
Sanderson, B. M., Brovkin, V., Fisher, R. A., Hohn, D., Ilyina, T., Jones, C. D., Koenigk, T., Koven, C., Li, H., Lawrence, D. M., Lawrence, P., Liddicoat, S., MacDougall, A. H., Mengis, N., Nicholls, Z., O'Rourke, E., Romanou, A., Sandstad, M., Schwinger, J., Séférian, R., Sentman, L. T., Simpson, I. R., Smith, C., Steinert, N. J., Swann, A. L. S., Tjiputra, J., and Ziehn, T.: flat10MIP: an emissions-driven experiment to diagnose the climate response to positive, zero and negative CO2 emissions, Geosci. Model Dev., 18, 5699–5724, https://doi.org/10.5194/gmd-18-5699-2025, 2025. a, b
Sandstad, M., Aamaas, B., Johansen, A. N., Lund, M. T., Peters, G. P., Samset, B. H., Sanderson, B. M., and Skeie, R. B.: CICERO Simple Climate Model (CICERO-SCM v1.1.1) – an improved simple climate model with a parameter calibration tool, Geosci. Model Dev., 17, 6589–6625, https://doi.org/10.5194/gmd-17-6589-2024, 2024. a, b, c
Santer, B. D., Wigley, T. M., Schlesinger, M. E., and Mitchell, J. F.: Developing Climate Scenarios from Equilibrium GCM Results, Max-Planck-Institut für Meteorologie report, Max-Planck-Institut für Meteorologie, https://api.semanticscholar.org/CorpusID:127017512 (last access: 31 October 2025), 1990. a
Schöngart, S., Gudmundsson, L., Hauser, M., Pfleiderer, P., Lejeune, Q., Nath, S., Seneviratne, S. I., and Schleussner, C.-F.: Introducing the MESMER-M-TPv0.1.0 module: spatially explicit Earth system model emulation for monthly precipitation and temperature, Geosci. Model Dev., 17, 8283–8320, https://doi.org/10.5194/gmd-17-8283-2024, 2024. a, b
Schwaab, J., Hauser, M., Lamboll, R. D., Beusch, L., Gudmundsson, L., Quilcaille, Y., Lejeune, Q., Schöngart, S., Schleussner, C.-F., Nath, S., Rogelj, J., Nicholls, Z., and Seneviratne, S. I.: Spatially resolved emulated annual temperature projections for overshoot pathways, Scientific Data, 11, https://doi.org/10.1038/s41597-024-04122-1, 2024. a
Shiogama, H., Emori, S., Takahashi, K., Nagashima, T., Ogura, T., Nozawa, T., and Takemura, T.: Emission Scenario Dependency of Precipitation on Global Warming in the MIROC3.2 Model, J. Climate, 23, 2404–2417, https://doi.org/10.1175/2009JCLI3428.1, 2010. a
Sillmann, J., Kharin, V. V., Zwiers, F. W., Zhang, X., and Bronaugh, D.: Climate extremes indices in the CMIP5 multimodel ensemble: Part 2. Future climate projections, J. Geophys. Res.-Atmos., 118, 2473–2493, 2013. a
Steinert, N. J. and Sanderson, B.: benmsanderson/METEOR: v1.0.2 (v1.0.2), Zenodo [data set], https://doi.org/10.5281/zenodo.15727973, 2025. a
Tebaldi, C. and Knutti, R.: The use of the multi-model ensemble in probabilistic climate projections, Philos. T. R. Soc. A, 365, 2053–2075, https://doi.org/10.1098/rsta.2007.2076, 2007. a
Tebaldi, C., Debeire, K., Eyring, V., Fischer, E., Fyfe, J., Friedlingstein, P., Knutti, R., Lowe, J., O'Neill, B., Sanderson, B., van Vuuren, D., Riahi, K., Meinshausen, M., Nicholls, Z., Tokarska, K. B., Hurtt, G., Kriegler, E., Lamarque, J.-F., Meehl, G., Moss, R., Bauer, S. E., Boucher, O., Brovkin, V., Byun, Y.-H., Dix, M., Gualdi, S., Guo, H., John, J. G., Kharin, S., Kim, Y., Koshiro, T., Ma, L., Olivié, D., Panickal, S., Qiao, F., Rong, X., Rosenbloom, N., Schupfner, M., Séférian, R., Sellar, A., Semmler, T., Shi, X., Song, Z., Steger, C., Stouffer, R., Swart, N., Tachiiri, K., Tang, Q., Tatebe, H., Voldoire, A., Volodin, E., Wyser, K., Xin, X., Yang, S., Yu, Y., and Ziehn, T.: Climate model projections from the Scenario Model Intercomparison Project (ScenarioMIP) of CMIP6, Earth Syst. Dynam., 12, 253–293, https://doi.org/10.5194/esd-12-253-2021, 2021. a, b
Tebaldi, C., Snyder, A., and Dorheim, K.: STITCHES: creating new scenarios of climate model output by stitching together pieces of existing simulations, Earth Syst. Dynam., 13, 1557–1609, https://doi.org/10.5194/esd-13-1557-2022, 2022. a, b
van Vuuren, D. P., Bayer, L. B., Chuwah, C., Ganzeveld, L., Hazeleger, W., van den Hurka, B., van Noije, T., O'Neill, B., and Strengers, B. J.: A comprehensive view on climate change: coupling of earth system and integrated assessment models, Environ. Res. Lett., 7, https://doi.org/10.1088/1748-9326/7/2/024012, 2012. a
Watson-Parris, D.: ClimateBench, Zenodo [data set], https://doi.org/10.5281/zenodo.7064308, 2021. a, b, c
Watson-Parris, D., Williams, A., Deaconu, L., and Stier, P.: Model calibration using ESEm v1.1.0 – an open, scalable Earth system emulator, Geosci. Model Dev., 14, 7659–7672, https://doi.org/10.5194/gmd-14-7659-2021, 2021. a
Watson-Parris, D., Rao, Y., Olivié, D., Seland, Ø., Nowack, P., Camps-Valls, G., Stier, P., Bouabid, S., Dewey, M., Fons, E., Gonzalez, J., Harder, P., Jeggle, K., Lenhardt, J., Manshausen, P., Novitasari, M., Ricard, L., and Roesch, C.: ClimateBench v1.0: A Benchmark for Data-Driven Climate Projections, Journal of Advances in Modeling Earth Systems, 14, e2021MS002954, https://doi.org/10.1029/2021MS002954, 2022. a, b, c, d, e
Wilcox, L. J., Allen, R. J., Samset, B. H., Bollasina, M. A., Griffiths, P. T., Keeble, J., Lund, M. T., Makkonen, R., Merikanto, J., O'Donnell, D., Paynter, D. J., Persad, G. G., Rumbold, S. T., Takemura, T., Tsigaridis, K., Undorf, S., and Westervelt, D. M.: The Regional Aerosol Model Intercomparison Project (RAMIP), Geosci. Model Dev., 16, 4451–4479, https://doi.org/10.5194/gmd-16-4451-2023, 2023. a, b, c
Womack, C. B., Giani, P., Eastham, S. D., and Selin, N. E.: Rapid Emulation of Spatially Resolved Temperature Response to Effective Radiative Forcing, Journal of Advances in Modeling Earth Systems, 17, e2024MS004523, https://doi.org/10.1029/2024MS004523, 2025. a
Zelazowski, P., Huntingford, C., Mercado, L. M., and Schaller, N.: Climate pattern-scaling set for an ensemble of 22 GCMs – adding uncertainty to the IMOGEN version 2.0 impact system, Geosci. Model Dev., 11, 541–560, https://doi.org/10.5194/gmd-11-541-2018, 2018. a
Zhao, A. D., Stevenson, D. S., and Bollasina, M. A.: The role of anthropogenic aerosols in future precipitation extremes over the Asian Monsoon Region, Clim. Dynam., 52, 6257–6278, https://doi.org/10.1007/s00382-018-4514-7, 2019. a
Zhao, B., Reichler, T., Strong, C., and Penland, C.: Simultaneous Evolution of Gyre and Atlantic Meridional Overturning Circulation Anomalies as an Eigenmode of the North Atlantic System, J. Climate, 30, 6737–6755, https://doi.org/10.1175/JCLI-D-16-0751.1, 2017. a, b
Short summary
We present METEORv1.0.1, a climate model emulator, that can be trained on full spatially resolved and widely available climate model data to reproduce climate variables and make predictions from unseen emission trajectories. The methodology identifies patterns with timescales of impact for one or more forcers using idealised experiments and anomaly calculations. Results for precipitation and temperature show good model performance and can reproduce hysteresis for overshoot scenarios.
We present METEORv1.0.1, a climate model emulator, that can be trained on full spatially...