Articles | Volume 19, issue 3
https://doi.org/10.5194/gmd-19-1229-2026
© Author(s) 2026. 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-19-1229-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The representation of climate impacts in the FRIDAv2.1 Integrated Assessment Model
Christopher D. Wells
CORRESPONDING AUTHOR
School of Earth and Environment, University of Leeds, Leeds, LS2 9JT, United Kingdom
Benjamin Blanz
Research Unit Sustainability and Climate Risks, University of Hamburg, Grindelberg 5, 20144 Hamburg, Germany
Lennart Ramme
Max-Planck-Institute for Meteorology, Bundesstraße 53, 20146 Hamburg, Germany
Jannes Breier
Department of Earth System Analysis, Potsdam Institute for Climate Impact Research, Telegrafenberg A31, 14473 Potsdam, Germany
Beniamino Callegari
School of Economics, Innovation and Technology, Kristiania University of Applied Sciences, Oslo, Norway
Adakudlu Muralidhar
Department of Ocean and Ice, Norwegian Meteorological Institute, 0313 Blindern, Oslo, Norway
Jefferson K. Rajah
System Dynamics Group, University of Bergen, P.O. Box 7802, 5020 Bergen, Norway
Andreas Nicolaidis Lindqvist
RISE Research Institutes of Sweden, Ideon Beta5, Scheelevägen 17, 223 70 Lund, Sweden
Stockholm Resilience Centre, Stockholm University, Albanovägen 28, 106 91 Stockholm, Sweden
Axel E. Eriksson
Department of Earth System Analysis, Potsdam Institute for Climate Impact Research, Telegrafenberg A31, 14473 Potsdam, Germany
Stockholm Resilience Centre, Stockholm University, Albanovägen 28, 106 91 Stockholm, Sweden
Department of Environmental and Energy Systems Studies, Lund University, P.O. Box 118, 221 00 Lund, Sweden
William Alexander Schoenberg
System Dynamics Group, University of Bergen, P.O. Box 7802, 5020 Bergen, Norway
isee systems inc., 24 Hanover St, Ste 8A, Lebanon, NH 03766, USA
Alexandre C. Köberle
Instituto Dom Luiz, Faculty of Sciences, Universidade de Lisboa, Campo Grande, Edifício C1, Piso 1, 1749-016, Lisboa, Portugal
Lan Wang-Erlandsson
Stockholm Resilience Centre, Stockholm University, Albanovägen 28, 106 91 Stockholm, Sweden
Potsdam Institute for Climate Impact Research, Member of the Leibnitz Association, 14473 Potsdam, Germany
Anthropocene Laboratory, the Royal Swedish Academy of Sciences, 104 05 Stockholm, Sweden
Cecilie Mauritzen
Climate Department, Norwegian Meteorological Institute, 0313 Oslo, Norway
Martin B. Grimeland
School of Economics, Innovation and Technology, Kristiania University of Applied Sciences, Oslo, Norway
Chris Smith
Energy, Climate and Environment Program, International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria
Related authors
Christopher D. Wells, Lennart Ramme, Chris Smith, Jannes Breier, Adakudlu Muralidhar, Chao Li, Ada Gjermundsen, William Alexander Schoenberg, Benjamin Blanz, and Cecilie Mauritzen
Geosci. Model Dev., 19, 1429–1453, https://doi.org/10.5194/gmd-19-1429-2026, https://doi.org/10.5194/gmd-19-1429-2026, 2026
Short summary
Short summary
Understanding the change in climate that would occur under different future pathways of greenhouse gas emissions and changes in land use is crucial. Here, we develop a new simple climate model to help study this. We reduce the number of inputs so that our model can be connected to a model of the human causes of climate change. This way, we can study the interaction between climate change and society, including climate impacts. Our model broadly agrees with historical observations.
Lennart Ramme, Benjamin Blanz, Christopher Wells, Tony E. Wong, William Schoenberg, Chris Smith, and Chao Li
Geosci. Model Dev., 18, 10017–10052, https://doi.org/10.5194/gmd-18-10017-2025, https://doi.org/10.5194/gmd-18-10017-2025, 2025
Short summary
Short summary
We present FRISIA version 1.0, a model for emulating sea level rise (SLR) and representing SLR impacts and adaptation in integrated assessment models (IAMs). FRISIA includes previously uncaptured coastal socio-economic feedback and a diverse set of impact strains, thereby improving the represenation of SLR impacts in IAMs. Here we describe the baseline behaviour of FRISIA, explore the effects of the additional feedback and showcase the coupling of FRISIA to an IAM.
Chris Smith, Lennart Ramme, Christopher D. Wells, Ada Gjermundsen, Hongmei Li, Tatiana Ilyina, Adakudlu Muralidhar, Timothée Bourgeois, Jörg Schwinger, Alejandro Romero-Prieto, Chao Li, and Cecilie Mauritzen
EGUsphere, https://doi.org/10.5194/egusphere-2025-5292, https://doi.org/10.5194/egusphere-2025-5292, 2025
Short summary
Short summary
We run the MPI-ESM1.2-LR and NorESM2-LM climate models in CO2 emissions-driven mode to 2300 for three climate scenarios. For climate overshoot scenarios, there is a large residual warming in the 22nd century in NorESM2-LM, despite negative CO2 emissions, related to Southern Ocean heat release. In both models, while global mean surface temperature is largely reversible, other global and regional climate models exhibit hysteresis and irreversibility.
William Schoenberg, Benjamin Blanz, Jefferson K. Rajah, Beniamino Callegari, Christopher Wells, Jannes Breier, Martin B. Grimeland, Andreas Nicolaidis Lindqvist, Lennart Ramme, Chris Smith, Chao Li, Sarah Mashhadi, Adakudlu Muralidhar, and Cecilie Mauritzen
Geosci. Model Dev., 18, 8047–8069, https://doi.org/10.5194/gmd-18-8047-2025, https://doi.org/10.5194/gmd-18-8047-2025, 2025
Short summary
Short summary
The current crop of models assessed by the Intergovernmental Panel on Climate Change to produce their assessment reports lack endogenous process-based representations of climate-driven changes to human activities, limiting understanding of the feedback between climate and humans. FRIDA (Feedback-based knowledge Repository for IntegrateD Assessments) v2.1 integrates these systems and generate results that suggest standard scenarios the shared socioeconomic pathways baseline scenarios may overestimate economic growth, highlighting the importance of feedbacks for realistic projections and informed policymaking.
Piers M. Forster, Chris Smith, Tristram Walsh, William F. Lamb, Robin Lamboll, Christophe Cassou, Mathias Hauser, Zeke Hausfather, June-Yi Lee, Matthew D. Palmer, Karina von Schuckmann, Aimée B. A. Slangen, Sophie Szopa, Blair Trewin, Jeongeun Yun, Nathan P. Gillett, Stuart Jenkins, H. Damon Matthews, Krishnan Raghavan, Aurélien Ribes, Joeri Rogelj, Debbie Rosen, Xuebin Zhang, Myles Allen, Lara Aleluia Reis, Robbie M. Andrew, Richard A. Betts, Alex Borger, Jiddu A. Broersma, Samantha N. Burgess, Lijing Cheng, Pierre Friedlingstein, Catia M. Domingues, Marco Gambarini, Thomas Gasser, Johannes Gütschow, Masayoshi Ishii, Christopher Kadow, John Kennedy, Rachel E. Killick, Paul B. Krummel, Aurélien Liné, Didier P. Monselesan, Colin Morice, Jens Mühle, Vaishali Naik, Glen P. Peters, Anna Pirani, Julia Pongratz, Jan C. Minx, Matthew Rigby, Robert Rohde, Abhishek Savita, Sonia I. Seneviratne, Peter Thorne, Christopher Wells, Luke M. Western, Guido R. van der Werf, Susan E. Wijffels, Valérie Masson-Delmotte, and Panmao Zhai
Earth Syst. Sci. Data, 17, 2641–2680, https://doi.org/10.5194/essd-17-2641-2025, https://doi.org/10.5194/essd-17-2641-2025, 2025
Short summary
Short summary
In a rapidly changing climate, evidence-based decision-making benefits from up-to-date and timely information. Here we compile monitoring datasets to track real-world changes over time. To make our work relevant to policymakers, we follow methods from the Intergovernmental Panel on Climate Change (IPCC). Human activities are increasing the Earth's energy imbalance and driving faster sea-level rise compared to the IPCC assessment.
Christopher D. Wells, Matthew Kasoar, Majid Ezzati, and Apostolos Voulgarakis
Atmos. Chem. Phys., 24, 1025–1039, https://doi.org/10.5194/acp-24-1025-2024, https://doi.org/10.5194/acp-24-1025-2024, 2024
Short summary
Short summary
Human-driven emissions of air pollutants, mostly caused by burning fossil fuels, impact both the climate and human health. Millions of deaths each year are caused by air pollution globally, and the future trends are uncertain. Here, we use a global climate model to study the effect of African pollutant emissions on surface level air pollution, and resultant impacts on human health, in several future emission scenarios. We find much lower health impacts under cleaner, lower-emission futures.
Christopher D. Wells, Lawrence S. Jackson, Amanda C. Maycock, and Piers M. Forster
Earth Syst. Dynam., 14, 817–834, https://doi.org/10.5194/esd-14-817-2023, https://doi.org/10.5194/esd-14-817-2023, 2023
Short summary
Short summary
There are many possibilities for future emissions, with different impacts in different places. Complex models can study these impacts but take a long time to run, even on powerful computers. Simple methods can be used to reduce this time by estimating the complex model output, but these are not perfect. This study looks at the accuracy of one of these techniques, showing that there are limitations to its use, especially for low-emission future scenarios.
Christopher D. Wells, Matthew Kasoar, Nicolas Bellouin, and Apostolos Voulgarakis
Atmos. Chem. Phys., 23, 3575–3593, https://doi.org/10.5194/acp-23-3575-2023, https://doi.org/10.5194/acp-23-3575-2023, 2023
Short summary
Short summary
The climate is altered by greenhouse gases and air pollutant particles, and such emissions are likely to change drastically in the future over Africa. Air pollutants do not travel far, so their climate effect depends on where they are emitted. This study uses a climate model to find the climate impacts of future African pollutant emissions being either high or low. The particles absorb and scatter sunlight, causing the ground nearby to be cooler, but elsewhere the increased heat causes warming.
Yawei Qu, Apostolos Voulgarakis, Tijian Wang, Matthew Kasoar, Chris Wells, Cheng Yuan, Sunil Varma, and Laura Mansfield
Atmos. Chem. Phys., 21, 5705–5718, https://doi.org/10.5194/acp-21-5705-2021, https://doi.org/10.5194/acp-21-5705-2021, 2021
Short summary
Short summary
The meteorological effect of aerosols on tropospheric ozone is investigated using global atmospheric modelling. We found that aerosol-induced meteorological effects act to reduce modelled ozone concentrations over China, which brings the simulation closer to observed levels. Our work sheds light on understudied processes affecting the levels of tropospheric gaseous pollutants and provides a basis for evaluating such processes using a combination of observations and model sensitivity experiments.
Philip J. Ward, Sophie L. Buijs, Roxana Ciurean, Judith N. Claassen, James Daniell, Kelley De Polt, Melanie Duncan, Stefania Gottardo, Stefan Hochrainer-Stigler, Robert Šakić Trogrlić, Julius Schlumberger, Timothy Tiggeloven, Silvia Torresan, Nicole van Maanen, Andrew Warren, Carmen D. Álvarez-Albelo, Vanessa Banks, Benjamin Blanz, Veronica Casartelli, Jordan Correa, Julia Crummy, Anne Sophie Daloz, Marleen C. de Ruiter, Juan José Díaz-Hernández, Jaime Díaz-Pacheco, Pedro Dorta Antequera, Davide Ferrario, David Geurts, Sara García-González, Joel C. Gill, Raúl Hernández-Martín, Wiebke S. Jäger, Abel López-Díez, Lin Ma, Jaroslav Mysiak, Diep Ngoc Nguyen, Noemi Padrón Fumero, Eva-Cristina Petrescu, Karina Reiter, Jana Sillmann, Lara Smale, and Tristian Stolte
Nat. Hazards Earth Syst. Sci., 26, 1325–1345, https://doi.org/10.5194/nhess-26-1325-2026, https://doi.org/10.5194/nhess-26-1325-2026, 2026
Short summary
Short summary
Disasters often result from interactions between different hazards, like floods triggering landslides, or earthquakes followed by tropical cyclones, so-called multi-hazards. People and societies are increasingly exposed and vulnerable to these multi-hazards. Assessing these aspects is referred to as multi-risk assessment and management. In this paper we synthesise key learnings from the MYRIAD-EU (Multi-hazard and sYstemic framework for enhancing Risk-Informed mAnagement and Decision-making in the E.U.) project, reflecting on progress and challenges faced in addressing multi-hazards and multi-risk.
Christopher D. Wells, Lennart Ramme, Chris Smith, Jannes Breier, Adakudlu Muralidhar, Chao Li, Ada Gjermundsen, William Alexander Schoenberg, Benjamin Blanz, and Cecilie Mauritzen
Geosci. Model Dev., 19, 1429–1453, https://doi.org/10.5194/gmd-19-1429-2026, https://doi.org/10.5194/gmd-19-1429-2026, 2026
Short summary
Short summary
Understanding the change in climate that would occur under different future pathways of greenhouse gas emissions and changes in land use is crucial. Here, we develop a new simple climate model to help study this. We reduce the number of inputs so that our model can be connected to a model of the human causes of climate change. This way, we can study the interaction between climate change and society, including climate impacts. Our model broadly agrees with historical observations.
Martin Breda Grimeland, Benjamin Blanz, William Schoenberg, and Beniamino Callegari
EGUsphere, https://doi.org/10.5194/egusphere-2025-6342, https://doi.org/10.5194/egusphere-2025-6342, 2026
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
This study develops a novel global economic model to better capture how climate change interacts with finance, innovation, employment, and public budgets. Instead of treating climate damage as a simple output loss, the model traces how rising temperatures affect investment risk, productivity, unemployment, and government spending. Large simulation ensembles show that without stronger climate action, growth slows, financial fragility rises, and welfare and debt pressures increase.
Peter W. Thorne, John M. Nicklas, John J. Kennedy, Bruce Calvert, Baylor Fox-Kemper, Mark T. Richardson, Adrian Simmons, Ed Hawkins, Robert Rhode, Kathryn Cowtan, Nerilie J. Abram, Axel Andersson, Simon Noone, Phillipe Marbaix, Nathan Lenssen, Dirk Olonscheck, Tristram Walsh, Stephen Outten, Ingo Bethke, Bjorn H. Samset, Chris Smith, Anna Pirani, Jan Fuglestvedt, Lavanya Rajamani, Richard A. Betts, Elizabeth C. Kent, Blair Trewin, Colin Morice, Tim Osborn, Samantha N. Burgess, Oliver Geden, Andrew Parnell, Piers M. Forster, Chris Hewitt, Zeke Hausfather, Valerie Masson-Delmotte, Jochem Marotzke, Nathan Gillett, Sonia I. Seneviratne, Gavin A. Schmidt, Duo Chan, Stefan Brönnimann, Andy Reisinger, Matthew Menne, Maisa Rojas Corradi, Christopher Kadow, Peter Huybers, David B. Stephenson, Emily Wallis, Joeri Rogelj, Andrew Schurer, Karen McKinnon, Panmao Zhai, Fatima Driouech, Wilfran Moufouma Okia, Saeed Vazifehkhah, Sophie Szopa, Christopher J. Merchant, Shoji Hirahara, Masayoshi Ishii, Francois A. Engelbrecht, Qingxiang Li, June-Yi Lee, Alex J. Cannon, Christophe Cassou, Karina von Schuckmann, Amir H. Delju, and Ellie Murtagh
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-825, https://doi.org/10.5194/essd-2025-825, 2026
Preprint under review for ESSD
Short summary
Short summary
We reassess the basis for determining the present level of long-term global warming. Unbiased estimates of both realised warming and anthropogenic warming are possible that approximate a 20-year retrospective mean. Our resulting estimates of 1.40 [1.23–1.58] °C (realised) and 1.34 [1.18–1.50] °C (anthropogenic) as at end of 2024 highlight the urgency of immediate, far-reaching and sustained climate mitigation actions if we are to meet the long term temperature goal of the Paris Agreement.
Benjamin M. Sanderson, Susanne Baur, Carl-Freidrich Schleussner, Glen P. Peters, Shivika Mittal, Marit Sandstad, Steffen Kallbekken, Chris Smith, Sabine Fuss, Bas van Ruijven, Rosie A. Fisher, Joeri Rogelj, Roland Séférian, Bjørn Samset, Norman J. Steinert, Laurent Terray, and Jan Fuglestvedt
EGUsphere, https://doi.org/10.5194/egusphere-2026-28, https://doi.org/10.5194/egusphere-2026-28, 2026
Short summary
Short summary
Solar Radiation Modification by adding aerosols to the stratosphere could rapidly and temporarily cool the Earth, but this speed creates unprecedented risks. Fast climate responses coupled with political instability create risks of failure to decarbonise, super-rapid climate change, and conflict. Idealized scenarios or conventional modeling tools could lead to systematic ignorance of these risks. We thus introduce a framework outlining what must be represented in future modeling and assessment.
Alejandro Romero-Prieto, Camilla Mathison, and Chris Smith
Geosci. Model Dev., 19, 115–165, https://doi.org/10.5194/gmd-19-115-2026, https://doi.org/10.5194/gmd-19-115-2026, 2026
Short summary
Short summary
Simple Climate Models (SCMs) are widely used tools to explore how Earth's climate may change in the future. In recent decades, the number and types of SCMs have increased significantly, hindering efforts to understand cross-model differences. In this study, we provide an overview of the main principles guiding climate simulation by SCMs, as well as a description of most high-profile SCMs. This work offers a clear reference to support the informed use of these important tools.
Lennart Ramme, Benjamin Blanz, Christopher Wells, Tony E. Wong, William Schoenberg, Chris Smith, and Chao Li
Geosci. Model Dev., 18, 10017–10052, https://doi.org/10.5194/gmd-18-10017-2025, https://doi.org/10.5194/gmd-18-10017-2025, 2025
Short summary
Short summary
We present FRISIA version 1.0, a model for emulating sea level rise (SLR) and representing SLR impacts and adaptation in integrated assessment models (IAMs). FRISIA includes previously uncaptured coastal socio-economic feedback and a diverse set of impact strains, thereby improving the represenation of SLR impacts in IAMs. Here we describe the baseline behaviour of FRISIA, explore the effects of the additional feedback and showcase the coupling of FRISIA to an IAM.
Simon P. Heselschwerdt, Thorsten Wagener, Lan Wang-Erlandsson, Anna M. Ukkola, Yannis Markonis, Yuting Yang, and Peter Greve
EGUsphere, https://doi.org/10.5194/egusphere-2025-5896, https://doi.org/10.5194/egusphere-2025-5896, 2025
This preprint is open for discussion and under review for Earth System Dynamics (ESD).
Short summary
Short summary
Precipitation on land is split into different pathways, contributing to runoff (blue water) or to plant water use (green water). Climate change alters this balance and shapes how future precipitation is divided. We use global climate models to study these changes and their drivers. We find that more extreme five-day precipitation is the main driver and routes more future precipitation into blue water, even where average precipitation decreases, with consequences for water and land management.
Alejandro Romero-Prieto, Marit Sandstad, Benjamin M. Sanderson, Zebedee R. J. Nicholls, Norman J. Steinert, Thomas Gasser, Camilla Mathison, Jarmo Kikstra, Thomas J. Aubry, and Chris Smith
EGUsphere, https://doi.org/10.5194/egusphere-2025-5775, https://doi.org/10.5194/egusphere-2025-5775, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
Reduced-complexity models are an important tool in climate science, helping us understand and estimate future climate change. We present the experimental protocol for the next phase of the reduced-complexity model intercomparison project, which aims to compare results from many such models to better understand their behaviour. This knowledge will guide how these models are developed and used in the future, including in the upcoming IPCC assessment report (AR7).
Chris Smith, Lennart Ramme, Christopher D. Wells, Ada Gjermundsen, Hongmei Li, Tatiana Ilyina, Adakudlu Muralidhar, Timothée Bourgeois, Jörg Schwinger, Alejandro Romero-Prieto, Chao Li, and Cecilie Mauritzen
EGUsphere, https://doi.org/10.5194/egusphere-2025-5292, https://doi.org/10.5194/egusphere-2025-5292, 2025
Short summary
Short summary
We run the MPI-ESM1.2-LR and NorESM2-LM climate models in CO2 emissions-driven mode to 2300 for three climate scenarios. For climate overshoot scenarios, there is a large residual warming in the 22nd century in NorESM2-LM, despite negative CO2 emissions, related to Southern Ocean heat release. In both models, while global mean surface temperature is largely reversible, other global and regional climate models exhibit hysteresis and irreversibility.
William Schoenberg, Benjamin Blanz, Jefferson K. Rajah, Beniamino Callegari, Christopher Wells, Jannes Breier, Martin B. Grimeland, Andreas Nicolaidis Lindqvist, Lennart Ramme, Chris Smith, Chao Li, Sarah Mashhadi, Adakudlu Muralidhar, and Cecilie Mauritzen
Geosci. Model Dev., 18, 8047–8069, https://doi.org/10.5194/gmd-18-8047-2025, https://doi.org/10.5194/gmd-18-8047-2025, 2025
Short summary
Short summary
The current crop of models assessed by the Intergovernmental Panel on Climate Change to produce their assessment reports lack endogenous process-based representations of climate-driven changes to human activities, limiting understanding of the feedback between climate and humans. FRIDA (Feedback-based knowledge Repository for IntegrateD Assessments) v2.1 integrates these systems and generate results that suggest standard scenarios the shared socioeconomic pathways baseline scenarios may overestimate economic growth, highlighting the importance of feedbacks for realistic projections and informed policymaking.
Jannes Breier, Luana Schwarz, Hannah Prawitz, Werner von Bloh, Christoph Müller, Stephen Björn Wirth, Max Bechthold, Dieter Gerten, and Jonathan F. Donges
EGUsphere, https://doi.org/10.5194/egusphere-2025-4475, https://doi.org/10.5194/egusphere-2025-4475, 2025
Short summary
Short summary
We present a new modelling framework that links global vegetation and agricultural modelling with human decision-making processes in an integrated simulation approach. This makes it possible to explore how farming practices and environmental changes influence each other over time. By combining climate, land use, and social dynamics in one system, the framework opens new ways to study food security, climate adaptation strategies, and long-term impacts.
Magali Verkerk, Thomas J. Aubry, Chris Smith, Peter O. Hopcroft, Michael Sigl, Jessica E. Tierney, Kevin Anchukaitis, Matthew Osman, Anja Schmidt, and Matthew Toohey
Clim. Past, 21, 1755–1778, https://doi.org/10.5194/cp-21-1755-2025, https://doi.org/10.5194/cp-21-1755-2025, 2025
Short summary
Short summary
Large volcanic eruptions can trigger global cooling, affecting human societies. Using ice-core records and simple climate model to simulate volcanic effect over the last 8500 years, we show that volcanic eruptions cool the climate by 0.12 °C on average. By comparing model results with temperature recorded by tree rings over the last 1000 years, we demonstrate that our models can predict the large-scale cooling caused by volcanic eruptions and can be used in cases of large eruptions in the future.
Luana Schwarz, Jannes Breier, Hannah Prawitz, Max Bechthold, Werner von Bloh, Sara M. Constantino, Dieter Gerten, Jobst Heitzig, Ronja Hotz, Leander John, Christoph Müller, Johan Rockström, and Jonathan F. Donges
EGUsphere, https://doi.org/10.5194/egusphere-2025-4079, https://doi.org/10.5194/egusphere-2025-4079, 2025
Short summary
Short summary
We present a novel global model that links farmer decisions with ecological processes to explore how agricultural systems co-evolve. Unlike previous tools, it captures feedbacks between society and nature at up-to planetary scale. We find that conservation practices can restore soil health and support stable harvests. Adoption spreads through learning and norms, showing how regeneration at the farm scale can ripple outward, contributing to global sustainability and Earth system resilience.
Ryan Kramer, Chris Smith, and Timothy Andrews
EGUsphere, https://doi.org/10.5194/egusphere-2025-4378, https://doi.org/10.5194/egusphere-2025-4378, 2025
Short summary
Short summary
Natural or anthropogenic activities can cause a perturbation in Earth’s radiative energy budget known as a radiative forcing, which induces a climate response. Diagnosing radiative forcing and its uncertainty is foundational to understanding past and future climate change. Here we outline the protocol for the second iteration of the Radiative Forcing Model Intercomparison Project (RFMIP2.0), which provides a standardized method for diagnosing radiative forcing across Global Climate Models.
Jefferson K. Rajah, Benjamin Blanz, Birgit Kopainsky, and William Schoenberg
Geosci. Model Dev., 18, 5997–6022, https://doi.org/10.5194/gmd-18-5997-2025, https://doi.org/10.5194/gmd-18-5997-2025, 2025
Short summary
Short summary
Climate models often exclude human behaviour. We introduce a model that includes economic, social, and environmental factors that influence dietary choices. This helps us understand how behaviour shifts impact future emissions and climate conditions. By considering a range of plausible behaviours, we provide a more accurate picture of potential outcomes, improving representations in climate models.
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
Short summary
Short summary
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.
Max Bechthold, Wolfram Barfuss, André Butz, Jannes Breier, Sara M. Constantino, Jobst Heitzig, Luana Schwarz, Sanam N. Vardag, and Jonathan F. Donges
Earth Syst. Dynam., 16, 1365–1390, https://doi.org/10.5194/esd-16-1365-2025, https://doi.org/10.5194/esd-16-1365-2025, 2025
Short summary
Short summary
Social norms are a major influence on human behaviour. In natural resource use models, norms are often included in a simplistic way leading to “black or white” sustainability outcomes. We find that a dynamic representation of norms, including social groups, determines more nuanced states of the environment in a stylised model of resource use while also defining the success of attempts to manage the system, suggesting the importance of representing both aspects well in coupled models.
Paul T. Griffiths, Laura J. Wilcox, Robert J. Allen, Vaishali Naik, Fiona M. O'Connor, Michael Prather, Alex Archibald, Florence Brown, Makoto Deushi, William Collins, Stephanie Fiedler, Naga Oshima, Lee T. Murray, Bjørn H. Samset, Chris Smith, Steven Turnock, Duncan Watson-Parris, and Paul J. Young
Atmos. Chem. Phys., 25, 8289–8328, https://doi.org/10.5194/acp-25-8289-2025, https://doi.org/10.5194/acp-25-8289-2025, 2025
Short summary
Short summary
The Aerosol Chemistry Model Intercomparison Project (AerChemMIP) aimed to quantify the climate and air quality impacts of aerosols and chemically reactive gases. We review its contribution to AR6 (Sixth Assessment Report of the Intergovernmental Panel on Climate Change) and the wider understanding of the role of these species in climate and climate change. We identify challenges and provide recommendations to improve the utility and uptake of climate model data, detailed summary tables of CMIP6 models, experiments, and emergent diagnostics.
Piers M. Forster, Chris Smith, Tristram Walsh, William F. Lamb, Robin Lamboll, Christophe Cassou, Mathias Hauser, Zeke Hausfather, June-Yi Lee, Matthew D. Palmer, Karina von Schuckmann, Aimée B. A. Slangen, Sophie Szopa, Blair Trewin, Jeongeun Yun, Nathan P. Gillett, Stuart Jenkins, H. Damon Matthews, Krishnan Raghavan, Aurélien Ribes, Joeri Rogelj, Debbie Rosen, Xuebin Zhang, Myles Allen, Lara Aleluia Reis, Robbie M. Andrew, Richard A. Betts, Alex Borger, Jiddu A. Broersma, Samantha N. Burgess, Lijing Cheng, Pierre Friedlingstein, Catia M. Domingues, Marco Gambarini, Thomas Gasser, Johannes Gütschow, Masayoshi Ishii, Christopher Kadow, John Kennedy, Rachel E. Killick, Paul B. Krummel, Aurélien Liné, Didier P. Monselesan, Colin Morice, Jens Mühle, Vaishali Naik, Glen P. Peters, Anna Pirani, Julia Pongratz, Jan C. Minx, Matthew Rigby, Robert Rohde, Abhishek Savita, Sonia I. Seneviratne, Peter Thorne, Christopher Wells, Luke M. Western, Guido R. van der Werf, Susan E. Wijffels, Valérie Masson-Delmotte, and Panmao Zhai
Earth Syst. Sci. Data, 17, 2641–2680, https://doi.org/10.5194/essd-17-2641-2025, https://doi.org/10.5194/essd-17-2641-2025, 2025
Short summary
Short summary
In a rapidly changing climate, evidence-based decision-making benefits from up-to-date and timely information. Here we compile monitoring datasets to track real-world changes over time. To make our work relevant to policymakers, we follow methods from the Intergovernmental Panel on Climate Change (IPCC). Human activities are increasing the Earth's energy imbalance and driving faster sea-level rise compared to the IPCC assessment.
William Lamb, Robbie Andrew, Matthew Jones, Zebedee Nicholls, Glen Peters, Chris Smith, Marielle Saunois, Giacomo Grassi, Julia Pongratz, Steven Smith, Francesco Tubiello, Monica Crippa, Matthew Gidden, Pierre Friedlingstein, Jan Minx, and Piers Forster
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-188, https://doi.org/10.5194/essd-2025-188, 2025
Revised manuscript accepted for ESSD
Short summary
Short summary
This study explores why global greenhouse gas (GHG) emissions estimates vary. Key reasons include different coverage of gases and sectors, varying definitions of anthropogenic land use change emissions, and the Paris Agreement not covering all emission sources. The study highlights three main ways emissions data is reported, each with different objectives and resulting in varying global emission totals. It emphasizes the need for transparency in choosing datasets and setting assessment scopes.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Chandrakant Singh, Ruud van der Ent, Ingo Fetzer, and Lan Wang-Erlandsson
Earth Syst. Dynam., 15, 1543–1565, https://doi.org/10.5194/esd-15-1543-2024, https://doi.org/10.5194/esd-15-1543-2024, 2024
Short summary
Short summary
Tropical rainforests risk tipping to savanna under future climate change. By analysing ecosystem root zone dynamics using hydroclimate data from Earth system models, we project the tipping risks for these rainforests. Our findings suggest that although some transition risks may be inevitable, most can still be mitigated by adapting to less severe climate change scenarios. Limiting global surface temperatures to meet the Paris Agreement targets is critical to preserving these ecosystems.
Chris Smith, Donald P. Cummins, Hege-Beate Fredriksen, Zebedee Nicholls, Malte Meinshausen, Myles Allen, Stuart Jenkins, Nicholas Leach, Camilla Mathison, and Antti-Ilari Partanen
Geosci. Model Dev., 17, 8569–8592, https://doi.org/10.5194/gmd-17-8569-2024, https://doi.org/10.5194/gmd-17-8569-2024, 2024
Short summary
Short summary
Climate projections are only useful if the underlying models that produce them are well calibrated and can reproduce observed climate change. We formalise a software package that calibrates the open-source FaIR simple climate model to full-complexity Earth system models. Observations, including historical warming, and assessments of key climate variables such as that of climate sensitivity are used to constrain the model output.
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
Short summary
Short summary
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.
Hongkai Gao, Markus Hrachowitz, Lan Wang-Erlandsson, Fabrizio Fenicia, Qiaojuan Xi, Jianyang Xia, Wei Shao, Ge Sun, and Hubert H. G. Savenije
Hydrol. Earth Syst. Sci., 28, 4477–4499, https://doi.org/10.5194/hess-28-4477-2024, https://doi.org/10.5194/hess-28-4477-2024, 2024
Short summary
Short summary
The concept of the root zone is widely used but lacks a precise definition. Its importance in Earth system science is not well elaborated upon. Here, we clarified its definition with several similar terms to bridge the multi-disciplinary gap. We underscore the key role of the root zone in the Earth system, which links the biosphere, hydrosphere, lithosphere, atmosphere, and anthroposphere. To better represent the root zone, we advocate for a paradigm shift towards ecosystem-centred modelling.
Robert J. Allen, Xueying Zhao, Cynthia A. Randles, Ryan J. Kramer, Bjørn H. Samset, and Christopher J. Smith
Atmos. Chem. Phys., 24, 11207–11226, https://doi.org/10.5194/acp-24-11207-2024, https://doi.org/10.5194/acp-24-11207-2024, 2024
Short summary
Short summary
Present-day methane shortwave absorption mutes 28% (7–55%) of the surface warming associated with its longwave absorption. The precipitation increase associated with the longwave radiative effects of the present-day methane perturbation is also muted by shortwave absorption but not significantly so. Methane shortwave absorption also impacts the magnitude of its climate feedback parameter, largely through the cloud feedback.
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”.
Piers M. Forster, Chris Smith, Tristram Walsh, William F. Lamb, Robin Lamboll, Bradley Hall, Mathias Hauser, Aurélien Ribes, Debbie Rosen, Nathan P. Gillett, Matthew D. Palmer, Joeri Rogelj, Karina von Schuckmann, Blair Trewin, Myles Allen, Robbie Andrew, Richard A. Betts, Alex Borger, Tim Boyer, Jiddu A. Broersma, Carlo Buontempo, Samantha Burgess, Chiara Cagnazzo, Lijing Cheng, Pierre Friedlingstein, Andrew Gettelman, Johannes Gütschow, Masayoshi Ishii, Stuart Jenkins, Xin Lan, Colin Morice, Jens Mühle, Christopher Kadow, John Kennedy, Rachel E. Killick, Paul B. Krummel, Jan C. Minx, Gunnar Myhre, Vaishali Naik, Glen P. Peters, Anna Pirani, Julia Pongratz, Carl-Friedrich Schleussner, Sonia I. Seneviratne, Sophie Szopa, Peter Thorne, Mahesh V. M. Kovilakam, Elisa Majamäki, Jukka-Pekka Jalkanen, Margreet van Marle, Rachel M. Hoesly, Robert Rohde, Dominik Schumacher, Guido van der Werf, Russell Vose, Kirsten Zickfeld, Xuebin Zhang, Valérie Masson-Delmotte, and Panmao Zhai
Earth Syst. Sci. Data, 16, 2625–2658, https://doi.org/10.5194/essd-16-2625-2024, https://doi.org/10.5194/essd-16-2625-2024, 2024
Short summary
Short summary
This paper tracks some key indicators of global warming through time, from 1850 through to the end of 2023. It is designed to give an authoritative estimate of global warming to date and its causes. We find that in 2023, global warming reached 1.3 °C and is increasing at over 0.2 °C per decade. This is caused by all-time-high greenhouse gas emissions.
Stephanie Fiedler, Vaishali Naik, Fiona M. O'Connor, Christopher J. Smith, Paul Griffiths, Ryan J. Kramer, Toshihiko Takemura, Robert J. Allen, Ulas Im, Matthew Kasoar, Angshuman Modak, Steven Turnock, Apostolos Voulgarakis, Duncan Watson-Parris, Daniel M. Westervelt, Laura J. Wilcox, Alcide Zhao, William J. Collins, Michael Schulz, Gunnar Myhre, and Piers M. Forster
Geosci. Model Dev., 17, 2387–2417, https://doi.org/10.5194/gmd-17-2387-2024, https://doi.org/10.5194/gmd-17-2387-2024, 2024
Short summary
Short summary
Climate scientists want to better understand modern climate change. Thus, climate model experiments are performed and compared. The results of climate model experiments differ, as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. This article gives insights into the challenges and outlines opportunities for further improving the understanding of climate change. It is based on views of a group of experts in atmospheric composition–climate interactions.
Christopher D. Wells, Matthew Kasoar, Majid Ezzati, and Apostolos Voulgarakis
Atmos. Chem. Phys., 24, 1025–1039, https://doi.org/10.5194/acp-24-1025-2024, https://doi.org/10.5194/acp-24-1025-2024, 2024
Short summary
Short summary
Human-driven emissions of air pollutants, mostly caused by burning fossil fuels, impact both the climate and human health. Millions of deaths each year are caused by air pollution globally, and the future trends are uncertain. Here, we use a global climate model to study the effect of African pollutant emissions on surface level air pollution, and resultant impacts on human health, in several future emission scenarios. We find much lower health impacts under cleaner, lower-emission futures.
Robert E. Kopp, Gregory G. Garner, Tim H. J. Hermans, Shantenu Jha, Praveen Kumar, Alexander Reedy, Aimée B. A. Slangen, Matteo Turilli, Tamsin L. Edwards, Jonathan M. Gregory, George Koubbe, Anders Levermann, Andre Merzky, Sophie Nowicki, Matthew D. Palmer, and Chris Smith
Geosci. Model Dev., 16, 7461–7489, https://doi.org/10.5194/gmd-16-7461-2023, https://doi.org/10.5194/gmd-16-7461-2023, 2023
Short summary
Short summary
Future sea-level rise projections exhibit multiple forms of uncertainty, all of which must be considered by scientific assessments intended to inform decision-making. The Framework for Assessing Changes To Sea-level (FACTS) is a new software package intended to support assessments of global mean, regional, and extreme sea-level rise. An early version of FACTS supported the development of the IPCC Sixth Assessment Report sea-level projections.
En Ning Lai, Lan Wang-Erlandsson, Vili Virkki, Miina Porkka, and Ruud J. van der Ent
Hydrol. Earth Syst. Sci., 27, 3999–4018, https://doi.org/10.5194/hess-27-3999-2023, https://doi.org/10.5194/hess-27-3999-2023, 2023
Short summary
Short summary
This research scrutinized predicted changes in root zone soil moisture dynamics across different climate scenarios and different climate regions globally between 2021 and 2100. The Mediterranean and most of South America stood out as regions that will likely experience permanently drier conditions, with greater severity observed in the no-climate-policy scenarios. These findings underscore the impact that possible future climates can have on green water resources.
Olivia Linke, Johannes Quaas, Finja Baumer, Sebastian Becker, Jan Chylik, Sandro Dahlke, André Ehrlich, Dörthe Handorf, Christoph Jacobi, Heike Kalesse-Los, Luca Lelli, Sina Mehrdad, Roel A. J. Neggers, Johannes Riebold, Pablo Saavedra Garfias, Niklas Schnierstein, Matthew D. Shupe, Chris Smith, Gunnar Spreen, Baptiste Verneuil, Kameswara S. Vinjamuri, Marco Vountas, and Manfred Wendisch
Atmos. Chem. Phys., 23, 9963–9992, https://doi.org/10.5194/acp-23-9963-2023, https://doi.org/10.5194/acp-23-9963-2023, 2023
Short summary
Short summary
Lapse rate feedback (LRF) is a major driver of the Arctic amplification (AA) of climate change. It arises because the warming is stronger at the surface than aloft. Several processes can affect the LRF in the Arctic, such as the omnipresent temperature inversion. Here, we compare multimodel climate simulations to Arctic-based observations from a large research consortium to broaden our understanding of these processes, find synergy among them, and constrain the Arctic LRF and AA.
Christopher D. Wells, Lawrence S. Jackson, Amanda C. Maycock, and Piers M. Forster
Earth Syst. Dynam., 14, 817–834, https://doi.org/10.5194/esd-14-817-2023, https://doi.org/10.5194/esd-14-817-2023, 2023
Short summary
Short summary
There are many possibilities for future emissions, with different impacts in different places. Complex models can study these impacts but take a long time to run, even on powerful computers. Simple methods can be used to reduce this time by estimating the complex model output, but these are not perfect. This study looks at the accuracy of one of these techniques, showing that there are limitations to its use, especially for low-emission future scenarios.
Mark D. Zelinka, Christopher J. Smith, Yi Qin, and Karl E. Taylor
Atmos. Chem. Phys., 23, 8879–8898, https://doi.org/10.5194/acp-23-8879-2023, https://doi.org/10.5194/acp-23-8879-2023, 2023
Short summary
Short summary
The primary uncertainty in how strongly Earth's climate has been perturbed by human activities comes from the unknown radiative impact of aerosol changes. Accurately quantifying these forcings – and their sub-components – in climate models is crucial for understanding the past and future simulated climate. In this study we describe biases in previously published estimates of aerosol radiative forcing in climate models and provide corrected estimates along with code for users to compute them.
Piers M. Forster, Christopher J. Smith, Tristram Walsh, William F. Lamb, Robin Lamboll, Mathias Hauser, Aurélien Ribes, Debbie Rosen, Nathan Gillett, Matthew D. Palmer, Joeri Rogelj, Karina von Schuckmann, Sonia I. Seneviratne, Blair Trewin, Xuebin Zhang, Myles Allen, Robbie Andrew, Arlene Birt, Alex Borger, Tim Boyer, Jiddu A. Broersma, Lijing Cheng, Frank Dentener, Pierre Friedlingstein, José M. Gutiérrez, Johannes Gütschow, Bradley Hall, Masayoshi Ishii, Stuart Jenkins, Xin Lan, June-Yi Lee, Colin Morice, Christopher Kadow, John Kennedy, Rachel Killick, Jan C. Minx, Vaishali Naik, Glen P. Peters, Anna Pirani, Julia Pongratz, Carl-Friedrich Schleussner, Sophie Szopa, Peter Thorne, Robert Rohde, Maisa Rojas Corradi, Dominik Schumacher, Russell Vose, Kirsten Zickfeld, Valérie Masson-Delmotte, and Panmao Zhai
Earth Syst. Sci. Data, 15, 2295–2327, https://doi.org/10.5194/essd-15-2295-2023, https://doi.org/10.5194/essd-15-2295-2023, 2023
Short summary
Short summary
This is a critical decade for climate action, but there is no annual tracking of the level of human-induced warming. We build on the Intergovernmental Panel on Climate Change assessment reports that are authoritative but published infrequently to create a set of key global climate indicators that can be tracked through time. Our hope is that this becomes an important annual publication that policymakers, media, scientists and the public can refer to.
Christopher D. Wells, Matthew Kasoar, Nicolas Bellouin, and Apostolos Voulgarakis
Atmos. Chem. Phys., 23, 3575–3593, https://doi.org/10.5194/acp-23-3575-2023, https://doi.org/10.5194/acp-23-3575-2023, 2023
Short summary
Short summary
The climate is altered by greenhouse gases and air pollutant particles, and such emissions are likely to change drastically in the future over Africa. Air pollutants do not travel far, so their climate effect depends on where they are emitted. This study uses a climate model to find the climate impacts of future African pollutant emissions being either high or low. The particles absorb and scatter sunlight, causing the ground nearby to be cooler, but elsewhere the increased heat causes warming.
Leonidas Linardakis, Irene Stemmler, Moritz Hanke, Lennart Ramme, Fatemeh Chegini, Tatiana Ilyina, and Peter Korn
Geosci. Model Dev., 15, 9157–9176, https://doi.org/10.5194/gmd-15-9157-2022, https://doi.org/10.5194/gmd-15-9157-2022, 2022
Short summary
Short summary
In Earth system modelling, we are facing the challenge of making efficient use of very large machines, with millions of cores. To meet this challenge we will need to employ multi-level and multi-dimensional parallelism. Component concurrency, being a function parallel technique, offers an additional dimension to the traditional data-parallel approaches. In this paper we examine the behaviour of component concurrency and identify the conditions for its optimal application.
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
Short summary
Short summary
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.
Chinchu Mohan, Tom Gleeson, James S. Famiglietti, Vili Virkki, Matti Kummu, Miina Porkka, Lan Wang-Erlandsson, Xander Huggins, Dieter Gerten, and Sonja C. Jähnig
Hydrol. Earth Syst. Sci., 26, 6247–6262, https://doi.org/10.5194/hess-26-6247-2022, https://doi.org/10.5194/hess-26-6247-2022, 2022
Short summary
Short summary
The relationship between environmental flow violations and freshwater biodiversity at a large scale is not well explored. This study intended to carry out an exploratory evaluation of this relationship at a large scale. While our results suggest that streamflow and EF may not be the only determinants of freshwater biodiversity at large scales, they do not preclude the existence of relationships at smaller scales or with more holistic EF methods or with other biodiversity data or metrics.
Johannes Quaas, Hailing Jia, Chris Smith, Anna Lea Albright, Wenche Aas, Nicolas Bellouin, Olivier Boucher, Marie Doutriaux-Boucher, Piers M. Forster, Daniel Grosvenor, Stuart Jenkins, Zbigniew Klimont, Norman G. Loeb, Xiaoyan Ma, Vaishali Naik, Fabien Paulot, Philip Stier, Martin Wild, Gunnar Myhre, and Michael Schulz
Atmos. Chem. Phys., 22, 12221–12239, https://doi.org/10.5194/acp-22-12221-2022, https://doi.org/10.5194/acp-22-12221-2022, 2022
Short summary
Short summary
Pollution particles cool climate and offset part of the global warming. However, they are washed out by rain and thus their effect responds quickly to changes in emissions. We show multiple datasets to demonstrate that aerosol emissions and their concentrations declined in many regions influenced by human emissions, as did the effects on clouds. Consequently, the cooling impact on the Earth energy budget became smaller. This change in trend implies a relative warming.
Vili Virkki, Elina Alanärä, Miina Porkka, Lauri Ahopelto, Tom Gleeson, Chinchu Mohan, Lan Wang-Erlandsson, Martina Flörke, Dieter Gerten, Simon N. Gosling, Naota Hanasaki, Hannes Müller Schmied, Niko Wanders, and Matti Kummu
Hydrol. Earth Syst. Sci., 26, 3315–3336, https://doi.org/10.5194/hess-26-3315-2022, https://doi.org/10.5194/hess-26-3315-2022, 2022
Short summary
Short summary
Direct and indirect human actions have altered streamflow across the world since pre-industrial times. Here, we apply a method of environmental flow envelopes (EFEs) that develops the existing global environmental flow assessments by methodological advances and better consideration of uncertainty. By assessing the violations of the EFE, we comprehensively quantify the frequency, severity, and trends of flow alteration during the past decades, illustrating anthropogenic effects on streamflow.
Lennart Ramme and Jochem Marotzke
Clim. Past, 18, 759–774, https://doi.org/10.5194/cp-18-759-2022, https://doi.org/10.5194/cp-18-759-2022, 2022
Short summary
Short summary
After the Marinoan snowball Earth, the climate warmed rapidly due to enhanced greenhouse conditions, and the freshwater inflow of melting glaciers caused a strong stratification of the ocean. Our climate simulations reveal a potentially only moderate global temperature increase and a break-up of the stratification within just a few thousand years. The findings give insights into the environmental conditions relevant for the geological and biological evolution during that time.
Nicholas J. Leach, Stuart Jenkins, Zebedee Nicholls, Christopher J. Smith, John Lynch, Michelle Cain, Tristram Walsh, Bill Wu, Junichi Tsutsui, and Myles R. Allen
Geosci. Model Dev., 14, 3007–3036, https://doi.org/10.5194/gmd-14-3007-2021, https://doi.org/10.5194/gmd-14-3007-2021, 2021
Short summary
Short summary
This paper presents an update of the FaIR simple climate model, which can estimate the impact of anthropogenic greenhouse gas and aerosol emissions on the global climate. This update aims to significantly increase the structural simplicity of the model, making it more understandable and transparent. This simplicity allows it to be implemented in a wide range of environments, including Excel. We suggest that it could be used widely in academia, corporate research, and education.
Yawei Qu, Apostolos Voulgarakis, Tijian Wang, Matthew Kasoar, Chris Wells, Cheng Yuan, Sunil Varma, and Laura Mansfield
Atmos. Chem. Phys., 21, 5705–5718, https://doi.org/10.5194/acp-21-5705-2021, https://doi.org/10.5194/acp-21-5705-2021, 2021
Short summary
Short summary
The meteorological effect of aerosols on tropospheric ozone is investigated using global atmospheric modelling. We found that aerosol-induced meteorological effects act to reduce modelled ozone concentrations over China, which brings the simulation closer to observed levels. Our work sheds light on understudied processes affecting the levels of tropospheric gaseous pollutants and provides a basis for evaluating such processes using a combination of observations and model sensitivity experiments.
Cited articles
Akerlof, K., Maibach, E. W., Fitzgerald, D., Cedeno, A. Y., and Neuman, A.: Do people “personally experience” global warming, and if so how, and does it matter?, Global Environmental Change, 23, 81–91, https://doi.org/10.1016/j.gloenvcha.2012.07.006, 2013.
Akerlof, K., Covi, M., and Rohring, E.: Communicating Sea Level Rise, Oxford Research Encyclopaedia of Climate Science, https://doi.org/10.1093/acrefore/9780190228620.013.417, 2017.
Allen, R. G., Pereira, L. S., Raes, D., and Smith, M.: FAO Irrigation and drainage paper 56, Food and Agriculture Organization of the United Nations, Rome, 56, https://www.fao.org/4/x0490e/x0490e00.htm (last access: 30 January 2026), 1998.
Monteith, J. L.: Evaporation and environment, in: Symposia of the society for experimental biology, Vol. 19, Cambridge University Press (CUP), Cambridge, UK, 205–234, https://pubmed.ncbi.nlm.nih.gov/5321565/ (last access: 30 January 2026), 1965.
Andrijevic, M., Schleussner, C. F., Crespo Cuaresma, J., Lissner, T., Muttarak, R., Riahi, K., Theokritoff, E., Thomas, A., van Maanen, N., and Byers, E.: Towards scenario representation of adaptive capacity for global climate change assessments, Nat. Clim. Chang., 13, 778–787, https://doi.org/10.1038/s41558-023-01725-1, 2023.
Arnell, N. W., Brown, S., Gosling, S. N., Hinkel, J., Huntingford, C., Lloyd-Hughes, B., Lowe, J. A., Osborn, T., Nicholls, R. J., and Zelazowski, P.: Global-scale climate impact functions: the relationship between climate forcing and impact, Clim. Change, 134, 475–487, https://doi.org/10.1007/s10584-013-1034-7, 2016a.
Arnell, N. W., Brown, S., Gosling, S. N., Gottschalk, P., Hinkel, J., Huntingford, C., Lloyd-Hughes, B., Lowe, J. A., Nicholls, R. J., Osborn, T. J., Osborne, T. M., Rose, G. A., Smith, P., Wheeler, T. R., and Zelazowski, P.: The impacts of climate change across the globe: A multi-sectoral assessment, Clim. Change, 134, 457–474, https://doi.org/10.1007/s10584-014-1281-2, 2016b.
Arnell, N. W., Lowe, J. A., Challinor, A. J., and Osborn, T. J.: Global and regional impacts of climate change at different levels of global temperature increase, Clim. Change, 155, 377–391, https://doi.org/10.1007/s10584-019-02464-z, 2019.
Avtar, R., Blickle, K., Chakrabarti, R., Janakiraman, J., and Pinkovskiy, M.: Understanding the linkages between climate change and inequality in the United States, SSRN Electron. J., 29, 1–39, https://doi.org/10.2139/ssrn.4487633, 2023.
Baldos, U. L. C., Chepeliev, M., Cultice, B., Huber, M., Meng, S., Ruane, A. C., Suttles, S., and Van Der Mensbrugghe, D.: Global-to-local-to-global interactions and climate change, Environ. Res. Lett., 18, 053002, https://doi.org/10.1088/1748-9326/acc95c, 2023.
Barlas, Y.: Formal aspects of model validity and validation in system dynamics, Syst. Dyn. Rev., 12, 183–210, https://doi.org/10.1002/(sici)1099-1727(199623)12:3<183::aid-sdr103>3.0.co;2-4, 1996.
Bartsch, F., Busies, I., Emambakhsh, T., Grill, M., Simoens, M., Spaggiari, M., and Tamburrini, F.: Designing a macroprudential capital buffer for climate-related risks: an application to transition risk, Climate Policy, 1–14, https://doi.org/10.1080/14693062.2025.2450279, 2025.
Bastidas-Arteaga, E. and Stewart, M. G.: Damage risks and economic assessment of climate adaptation strategies for design of new concrete structures subject to chloride-induced corrosion, Structural Safety, 52, 40–53, https://doi.org/10.1016/j.strusafe.2014.10.005, 2015.
Bastien-Olvera, B. A., Granella, F., and Moore, F. C.: Persistent effect of temperature on GDP identified from lower frequency temperature variability, Environmental Research Letters, 17, https://doi.org/10.1088/1748-9326/ac82c2, 2022.
Beckage, B., Gross, L. J., Lacasse, K., Carr, E., Metcalf, S. S., Winter, J. M., Howe, P. D., Fefferman, N., Franck, T., Zia, A., Kinzig, A., and Hoffman, F. M.: Linking models of human behaviour and climate alters projected climate change, Nat. Clim. Chang., 8, 79–84, https://doi.org/10.1038/s41558-017-0031-7, 2018.
Beckage, B., Moore, F. C., and Lacasse, K.: Incorporating human behaviour into Earth system modelling, Nature Human Behaviour, 6, 1493–1502, https://doi.org/10.1038/s41562-022-01478-5, 2022.
Bressler, R. D., Moore, F. C., Rennert, K., and Anthoff, D.: Estimates of country level temperature-related mortality damage functions, Sci. Rep., 11, https://doi.org/10.1038/s41598-021-99156-5, 2021.
Burke, M., Hsiang, S. M., and Miguel, E.: Global non-linear effect of temperature on economic production, Nature, 527, 235–239, https://doi.org/10.1038/nature15725, 2015.
Burton, C., Lampe, S., Kelley, D. I., Thiery, W., Hantson, S., Christidis, N., Gudmundsson, L., Forrest, M., Burke, E., Chang, J., Huang, H., Ito, A., Kou-Giesbrecht, S., Lasslop, G., Li, W., Nieradzik, L., Li, F., Chen, Y., Randerson, J., Reyer, C. P. O., and Mengel, M.: Global burned area increasingly explained by climate change, Nat. Clim. Chang., 14, 1186–1192, https://doi.org/10.1038/s41558-024-02140-w, 2024.
Calel, R., Chapman, S. C., Stainforth, D. A., and Watkins, N. W.: Temperature variability implies greater economic damages from climate change, Nat. Commun., 11, 5028, https://doi.org/10.1038/s41467-020-18797-8, 2020.
Carattini, S., Heutel, G., and Melkadze, G.: Climate policy, financial frictions, and transition risk, Rev. Econ. Dyn., 51, 778–794, https://doi.org/10.1016/j.red.2023.08.003, 2023.
Cazenave, A. and Le Cozannet, G.: Sea level rise and its coastal impacts, Earths Future, 2, 15–34, https://doi.org/10.1002/2013EF000188, 2014.
Chen, K., de Schrijver, E., Sivaraj, S., Sera, F., Scovronick, N., Jiang, L., Roye, D., Lavigne, E., Kyselý, J., Urban, A., Schneider, A., Huber, V., Madureira, J., Mistry, M. N., Cvijanovic, I., Gasparrini, A., Vicedo-Cabrera, A. M., Armstrong, B., Schneider, R., Tobias, A., Astrom, C., Guo, Y., Honda, Y., Abrutzky, R., Tong, S., de Sousa Zanotti Stagliorio Coelho, M., Saldiva, P. H. N., Correa, P. M., Ortega, N. V., Kan, H., Osorio, S., Orru, H., Indermitte, E., Jaakkola, J. J. K., Ryti, N., Pascal, M., Katsouyanni, K., Analitis, A., Mayvaneh, F., Entezari, A., Goodman, P., Zeka, A., Michelozzi, P., de'Donato, F., Hashizume, M., Alahmad, B., Diaz, M. H., De la Cruz Valencia, C., Overcenco, A., Houthuijs, D., Ameling, C., Rao, S., Carrasco-Escobar, G., Seposo, X., da Silva, S. P., Holobaca, I. H., Acquaotta, F., Kim, H., Lee, W., Íñiguez, C., Forsberg, B., Ragettli, M. S., Guo, Y. L. L., Pan, S. C., Li, S., Colistro, V., Zanobetti, A., Schwartz, J., Dang, T. N., Van Dung, D., Carlsen, H. K., Cauchi, J. P., Achilleos, S., and Raz, R.: Impact of population aging on future temperature-related mortality at different global warming levels, Nat. Commun., 15, https://doi.org/10.1038/s41467-024-45901-z, 2024.
Clarke, B., Otto, F., Stuart-Smith, R., and Harrington, L.: Extreme weather impacts of climate change: an attribution perspective, Environmental Research: Climate, 1, 012001, https://doi.org/10.1088/2752-5295/ac6e7d, 2022.
Clarke, L., Eom, J., Marten, E. H., Horowitz, R., Kyle, P., Link, R., Mignone, B. K., Mundra, A., and Zhou, Y.: Effects of long-term climate change on global building energy expenditures, Energy Econ., 72, 667–677, https://doi.org/10.1016/j.eneco.2018.01.003, 2018.
Colelli, F. Pietro, Emmerling, J., Marangoni, G., Mistry, M. N., and De Cian, E.: Increased energy use for adaptation significantly impacts mitigation pathways, Nat. Commun., 13, https://doi.org/10.1038/s41467-022-32471-1, 2022.
Cromar, K. R., Anenberg, S. C., Balmes, J. R., Fawcett, A. A., Ghazipura, M., Gohlke, J. M., Hashizume, M., Howard, P., Lavigne, E., Levy, K., Madrigano, J., Martinich, J. A., Mordecai, E. A., Rice, M. B., Saha, S., Scovronick, N. C., Sekercioglu, F., Svendsen, E. R., Zaitchik, B. F., and Ewart, G.: Global Health Impacts for Economic Models of Climate Change A Systematic Review and Meta-Analysis, Annals of the American Thoracic Society, 19, 1203–1212, https://doi.org/10.1513/AnnalsATS.202110-1193OC, 2022.
Dasgupta, S., van Maanen, N., Gosling, S. N., Piontek, F., Otto, C., and Schleussner, C. F.: Effects of climate change on combined labour productivity and supply: an empirical, multi-model study, Lancet Planet Health, 5, e455–e465, https://doi.org/10.1016/S2542-5196(21)00170-4, 2021.
Deetman, S., Marinova, S., van der Voet, E., van Vuuren, D. P., Edelenbosch, O., and Heijungs, R.: Modelling global material stocks and flows for residential and service sector buildings towards 2050, J. Clean. Prod., 245, 118658, https://doi.org/10.1016/j.jclepro.2019.118658, 2020.
Dell'ariccia, G. and Marquez, R.: Lending Booms and Lending Standards, J. Finance, 61, 2511–2546, https://doi.org/10.1111/j.1540-6261.2006.01065.x, 2006.
Deroubaix, A., Labuhn, I., Camredon, M., Gaubert, B., Monerie, P. A., Popp, M., Ramarohetra, J., Ruprich-Robert, Y., Silvers, L. G., and Siour, G.: Large uncertainties in trends of energy demand for heating and cooling under climate change, Nat. Commun., 12, https://doi.org/10.1038/s41467-021-25504-8, 2021.
Diaz, D. and Moore, F.: Quantifying the economic risks of climate change, Nat. Clim. Chang., 7, 774–782, https://doi.org/10.1038/nclimate3411, 2017.
Elsawah, S., Filatova, T., Jakeman, A. J., Kettner, A. J., Zellner, M. L., Athanasiadis, I. N., Hamilton, S. H., Axtell, R. L., Brown, D. G., Gilligan, J. M., Janssen, M. A., Robinson, D. T., Rozenberg, J., Ullah, I. I. T., and Lade, S. J.: Eight grand challenges in socio-environmental systems modeling, Socio-Environmental Systems Modelling, 2, 16226, https://doi.org/10.18174/sesmo.2020a16226, 2020.
Ember: Electricity generation from other renewables, excluding bioenergy, Our World in Data [data set], https://ourworldindata.org/grapher/electricity-prod-source-stacked (last access: 3 February 2026), 2026.
Eriksson, A.: Assessing Planetary Boundary Transgressions and Their Causes – Using the FRIDA system dynamics model, MSc thesis, Lund University, ISRN: LUTFD2/TFEM—25/5223–SE +, 1–42, https://lup.lub.lu.se/student-papers/search/publication/9186505 (last access: 30 January 2026), 2025.
Feng, Y., Pan, Y., Sun, C., and Niu, J.: Assessing the effect of green credit on risk-taking of commercial banks in China: Further analysis on the two-way Granger causality, J. Clean. Prod., 437, 140698, https://doi.org/10.1016/j.jclepro.2024.140698, 2024.
Fishman, M. J., Parker, J. A., and Straub, L.: A Dynamic Theory of Lending Standards, Rev. Financ. Stud., 37, 2355–2402, https://doi.org/10.1093/rfs/hhae010, 2024.
Fox-Kemper, B., Hewitt, H. T., Xiao, C., Aðalgeirsdóttir, G., Drijfhout, S. S., Edwards, T. L., Golledge, N. R., Hemer, M., Kopp, R. E., Krinner, G., Mix, A., Notz, D., Nowicki, S., Nurhati, I. S., Ruiz, L., Sallée, J.-B., Slangen, A. B. A., and Yu, Y.: Ocean, Cryosphere and Sea Level Change, 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, United Kingdom and New York, NY, USA, 1211–1362, https://doi.org/10.1017/9781009157896.011, 2021.
Franke, J. A., Müller, C., Elliott, J., Ruane, A. C., Jägermeyr, J., Snyder, A., Dury, M., Falloon, P. D., Folberth, C., François, L., Hank, T., Izaurralde, R. C., Jacquemin, I., Jones, C., Li, M., Liu, W., Olin, S., Phillips, M., Pugh, T. A. M., Reddy, A., Williams, K., Wang, Z., Zabel, F., and Moyer, E. J.: The GGCMI Phase 2 emulators: global gridded crop model responses to changes in CO2, temperature, water, and nitrogen (version 1.0), Geosci. Model Dev., 13, 3995–4018, https://doi.org/10.5194/gmd-13-3995-2020, 2020a.
Franke, J. A., Müller, C., Elliott, J., Ruane, A. C., Jägermeyr, J., Balkovic, J., Ciais, P., Dury, M., Falloon, P. D., Folberth, C., François, L., Hank, T., Hoffmann, M., Izaurralde, R. C., Jacquemin, I., Jones, C., Khabarov, N., Koch, M., Li, M., Liu, W., Olin, S., Phillips, M., Pugh, T. A. M., Reddy, A., Wang, X., Williams, K., Zabel, F., and Moyer, E. J.: The GGCMI Phase 2 experiment: global gridded crop model simulations under uniform changes in CO2, temperature, water, and nitrogen levels (protocol version 1.0), Geosci. Model Dev., 13, 2315–2336, https://doi.org/10.5194/gmd-13-2315-2020, 2020b.
Frieler, K., Lange, S., Piontek, F., Reyer, C. P. O., Schewe, J., Warszawski, L., Zhao, F., Chini, L., Denvil, S., Emanuel, K., Geiger, T., Halladay, K., Hurtt, G., Mengel, M., Murakami, D., Ostberg, S., Popp, A., Riva, R., Stevanovic, M., Suzuki, T., Volkholz, J., Burke, E., Ciais, P., Ebi, K., Eddy, T. D., Elliott, J., Galbraith, E., Gosling, S. N., Hattermann, F., Hickler, T., Hinkel, J., Hof, C., Huber, V., Jägermeyr, J., Krysanova, V., Marcé, R., Müller Schmied, H., Mouratiadou, I., Pierson, D., Tittensor, D. P., Vautard, R., van Vliet, M., Biber, M. F., Betts, R. A., Bodirsky, B. L., Deryng, D., Frolking, S., Jones, C. D., Lotze, H. K., Lotze-Campen, H., Sahajpal, R., Thonicke, K., Tian, H., and Yamagata, Y.: Assessing the impacts of 1.5 °C global warming – simulation protocol of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2b), Geosci. Model Dev., 10, 4321–4345, https://doi.org/10.5194/gmd-10-4321-2017, 2017.
Frieler, K., Volkholz, J., Lange, S., Schewe, J., Mengel, M., del Rocío Rivas López, M., Otto, C., Reyer, C. P. O., Karger, D. N., Malle, J. T., Treu, S., Menz, C., Blanchard, J. L., Harrison, C. S., Petrik, C. M., Eddy, T. D., Ortega-Cisneros, K., Novaglio, C., Rousseau, Y., Watson, R. A., Stock, C., Liu, X., Heneghan, R., Tittensor, D., Maury, O., Büchner, M., Vogt, T., Wang, T., Sun, F., Sauer, I. J., Koch, J., Vanderkelen, I., Jägermeyr, J., Müller, C., Rabin, S., Klar, J., Vega del Valle, I. D., Lasslop, G., Chadburn, S., Burke, E., Gallego-Sala, A., Smith, N., Chang, J., Hantson, S., Burton, C., Gädeke, A., Li, F., Gosling, S. N., Müller Schmied, H., Hattermann, F., Wang, J., Yao, F., Hickler, T., Marcé, R., Pierson, D., Thiery, W., Mercado-Bettín, D., Ladwig, R., Ayala-Zamora, A. I., Forrest, M., and Bechtold, M.: Scenario setup and forcing data for impact model evaluation and impact attribution within the third round of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3a), Geosci. Model Dev., 17, 1–51, https://doi.org/10.5194/gmd-17-1-2024, 2024.
Füssel, H.-M.: Modeling impacts and adaptation in global IAMs, Wiley Interdiscip. Rev. Clim. Change, 1, 288–303, 2010.
Gernaat, D. E. H. J., de Boer, H. S., Daioglou, V., Yalew, S. G., Müller, C., and van Vuuren, D. P.: Climate change impacts on renewable energy supply, Nat. Clim. Chang., 11, 119–125, https://doi.org/10.1038/s41558-020-00949-9, 2021.
Ghimire, B., Williams, C. A., Masek, J., Gao, F., Wang, Z., Schaaf, C., and He, T.: Global albedo change and radiative cooling from anthropogenic land cover change, 1700 to 2005 based on MODIS, land use harmonization, radiative kernels, and reanalysis, Geophys. Res. Lett., 41, 9087–9096, https://doi.org/10.1002/2014GL061671, 2014.
Guo, D., Westra, S., and Maier, H. R.: Sensitivity of potential evapotranspiration to changes in climate variables for different Australian climatic zones, Hydrol. Earth Syst. Sci., 21, 2107–2126, https://doi.org/10.5194/hess-21-2107-2017, 2017.
Hargreaves, G. H. and Samani, Z. A.: Reference Crop Evapotranspiration from Temperature, Appl. Eng. Agric., 1, 96–99, https://doi.org/10.13031/2013.26773, 1985.
Hamon, W. R.: Estimating potential evapotranspiration, T. Am. Soc. Civ. Eng., 128, 324–338, 1963.
Hartin, C., Link, R., Patel, P., Mundra, A., Horowitz, R., Dorheim, K., and Clarke, L.: Integrated modeling of human-earth system interactions: An application of GCAM-fusion, Energy Econ., 103, https://doi.org/10.1016/j.eneco.2021.105566, 2021.
Heinicke, S., Frieler, K., Jägermeyr, J., and Mengel, M.: Global gridded crop models underestimate yield responses to droughts and heatwaves, Environmental Research Letters, 17, https://doi.org/10.1088/1748-9326/ac592e, 2022.
Holman, I. P., Brown, C., Carter, T. R., Harrison, P. A., and Rounsevell, M.: Improving the representation of adaptation in climate change impact models, Reg. Environ. Change, 19, 711–721, https://doi.org/10.1007/s10113-018-1328-4, 2019.
Horwath, M., Gutknecht, B. D., Cazenave, A., Palanisamy, H. K., Marti, F., Marzeion, B., Paul, F., Le Bris, R., Hogg, A. E., Otosaka, I., Shepherd, A., Döll, P., Cáceres, D., Müller Schmied, H., Johannessen, J. A., Nilsen, J. E. Ø., Raj, R. P., Forsberg, R., Sandberg Sørensen, L., Barletta, V. R., Simonsen, S., Knudsen Per and Andersen, O. B., Ranndal, H., Rose Stine K and Merchant, C. J., Macintosh, C. R., von Schuckmann, K., Novotny, K., Groh, A., Restano, M., and Benveniste, J.: ESA Sea Level Budget Closure Climate Change Initiative (SLBC_cci): Time series of global mean sea level budget and ocean mass budget elements (1993–2016, at monthly resolution), version 2.2, NERC EDS Centre for Environmental Data Analysis [data set], https://doi.org/10.5285/17c2ce31784048de93996275ee976fff, 2021.
Howard, P. H. and Sterner, T.: Few and Not So Far Between: A Meta-analysis of Climate Damage Estimates, Environ. Resour. Econ. (Dordr), 68, 197–225, https://doi.org/10.1007/s10640-017-0166-z, 2017.
Hu, T., Zhang, X., Khanal, S., Wilson, R., Leng, G., Toman, E. M., Wang, X., Li, Y., and Zhao, K.: Climate change impacts on crop yields: A review of empirical findings, statistical crop models, and machine learning methods, Environ. Modell. Softw., 179, 106119,https://doi.org/10.1016/j.envsoft.2024.106119, 2024.
IPCC: Sea Level Rise and Implications for Low-Lying Islands, Coasts and Communities, in: The Ocean and Cryosphere in a Changing Climate: Special Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, 321–446, https://doi.org/10.1017/9781009157964.006, 2022.
Jones, C., Bossert, I., Dennis, D. P., Jeffery, H., Jones, C. D., Koenigk, T., Loriani, S., Sanderson, B., Séférian, R., Wyser, K., Yang, S., Abe, M., Bathiany, S., Braconnot, P., Brovkin, V., Burger, F. A., Cadule, P., Castruccio, F. S., Danabasoglu, G., Dittus, A., Donges, J. F., Fröb, F., Frölicher, T., Georgievski, G., Guo, C., Hu, A., Lawrence, P., Lerner, P., Licón-Saláiz, J., Otto-Bliesner, B., Romanou, A., Shevliakova, E., Silvy, Y., Swingedouw, D., Tjiputra, J., Walton, J., Wiltshire, A., Winkelmann, R., Wood, R., Yokohata, T., and Ziehn, T.: The TIPMIP Earth system model experiment protocol: phase 1, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2025-3604, 2025.
Kantor, B.: Rational Expectations and Economic Thought, J. Econ. Lit., 17, 1422–1441, 1979.
Kennard, H., Oreszczyn, T., Mistry, M., and Hamilton, I.: Population-weighted degree-days: The global shift between heating and cooling, Energy Build., 271, https://doi.org/10.1016/j.enbuild.2022.112315, 2022.
Kompas, T., Che, T. N., and Grafton, R. Q.: Global impacts of heat and water stress on food production and severe food insecurity, Sci. Rep., 14, https://doi.org/10.1038/s41598-024-65274-z, 2024.
Kopp, R. E., Gilmore, E. A., Shwom, R. L., Adams, H., Adler, C., Oppenheimer, M., Patwardhan, A., Russill, C., Schmidt, D. N., and York, R.: “Tipping points” confuse and can distract from urgent climate action, Nat. Clim. Chang., 15, 29–36, https://doi.org/10.1038/s41558-024-02196-8, 2025.
Kotz, M., Levermann, A., and Wenz, L.: The effect of rainfall changes on economic production, Nature, 601, 223–227, https://doi.org/10.1038/s41586-021-04283-8, 2022.
Kotz, M., Levermann, A., and Wenz, L.: The economic commitment of climate change, Nature, 628, 551–557, https://doi.org/10.1038/s41586-024-07219-0, 2024.
Lamperti, F., Dosi, G., Napoletano, M., Roventini, A., and Sapio, A.: Faraway, So Close: Coupled Climate and Economic Dynamics in an Agent-based Integrated Assessment Model, Ecological Economics, 150, 315–339, https://doi.org/10.1016/j.ecolecon.2018.03.023, 2018.
Lange, S.: Trend-preserving bias adjustment and statistical downscaling with ISIMIP3BASD (v1.0), Geosci. Model Dev., 12, 3055–3070, https://doi.org/10.5194/gmd-12-3055-2019, 2019.
Lange, S., Volkholz, J., Geiger, T., Zhao, F., Vega, I., Veldkamp, T., Reyer, C. P. O., Warszawski, L., Huber, V., Jägermeyr, J., Schewe, J., Bresch, D. N., Büchner, M., Chang, J., Ciais, P., Dury, M., Emanuel, K., Folberth, C., Gerten, D., Gosling, S. N., Grillakis, M., Hanasaki, N., Henrot, A. J., Hickler, T., Honda, Y., Ito, A., Khabarov, N., Koutroulis, A., Liu, W., Müller, C., Nishina, K., Ostberg, S., Müller Schmied, H., Seneviratne, S. I., Stacke, T., Steinkamp, J., Thiery, W., Wada, Y., Willner, S., Yang, H., Yoshikawa, M., Yue, C., and Frieler, K.: Projecting Exposure to Extreme Climate Impact Events Across Six Event Categories and Three Spatial Scales, Earths Future, 8, https://doi.org/10.1029/2020EF001616, 2020.
Leimbach, M., Marcolino, M., and Koch, J.: Structural change scenarios within the SSP framework, Futures, 150, https://doi.org/10.1016/j.futures.2023.103156, 2023.
Lenton, T. M., Xu, C., Abrams, J. F., Ghadiali, A., Loriani, S., Sakschewski, B., Zimm, C., Ebi, K. L., Dunn, R. R., Svenning, J. C., and Scheffer, M.: Quantifying the human cost of global warming, Nat. Sustain., 6, 1237–1247, https://doi.org/10.1038/s41893-023-01132-6, 2023.
Levis, S., Badger, A., Drewniak, B., Nevison, C., and Ren, X.: CLMcrop yields and water requirements: avoided impacts by choosing RCP 4.5 over 8.5, Clim. Change, 146, 501–515, https://doi.org/10.1007/s10584-016-1654-9, 2018.
Li, B., Liu, K., Wang, M., Wang, Q., He, Q., and Li, C.: Future Global Population Exposure to Record-Breaking Climate Extremes, Earths Future, 11, https://doi.org/10.1029/2023EF003786, 2023.
Li, C., Held, H., Hokamp, S., and Marotzke, J.: Optimal temperature overshoot profile found by limiting global sea level rise as a lower-cost climate target, Science Advances, 6, eaaw9490, https://doi.org/10.1126/sciadv.aaw9490, 2020.
Liu, W., Ye, T., Müller, C., Jägermeyr, J., Franke, J. A., Stephens, H., and Chen, S.: The statistical emulators of GGCMI phase 2: responses of year-to-year variation of crop yield to CO2, temperature, water, and nitrogen perturbations, Geosci. Model Dev., 16, 7203–7221, https://doi.org/10.5194/gmd-16-7203-2023, 2023.
Lown, C. and Morgan, D. P.: The Credit Cycle and the Business Cycle: New Findings Using the Loan Officer Opinion Survey, J. Money Credit Bank, 38, 1575–1597, 2006.
Marinova, S., Deetman, S., van der Voet, E., and Daioglou, V.: Global construction materials database and stock analysis of residential buildings between 1970–2050, J. Clean. Prod., 247, 119146, https://doi.org/10.1016/j.jclepro.2019.119146, 2020.
Masuda, Y. J., Parsons, L. A., Spector, J. T., Battisti, D. S., Castro, B., Erbaugh, J. T., Game, E. T., Garg, T., Kalmus, P., Kroeger, T., Mishra, V., Shindell, D., Tigchelaar, M., Wolff, N. H., and Vargas Zeppetello, L. R.: Impacts of warming on outdoor worker well-being in the tropics and adaptation options, One Earth, 7, 382–400, https://doi.org/10.1016/j.oneear.2024.02.001, 2024.
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.
McKay, D. I. A., Staal, A., Abrams, J. F., Winkelmann, R., Sakschewski, B., Loriani, S., Fetzer, I., Cornell, S. E., Rockström, J., and Lenton, T. M.: Exceeding 1.5 °C global warming could trigger multiple climate tipping points, Science, 377, https://doi.org/10.1126/science.abn7950, 2022.
McVicar, T. R., Roderick, M. L., Donohue, R. J., Li, L. T., Van Niel, T. G., Thomas, A., Grieser, J., Jhajharia, D., Himri, Y., Mahowald, N. M., Mescherskaya, A. V, Kruger, A. C., Rehman, S., and Dinpashoh, Y.: Global review and synthesis of trends in observed terrestrial near-surface wind speeds: Implications for evaporation, J. Hydrol., 416–417, 182–205, https://doi.org/10.1016/j.jhydrol.2011.10.024, 2012.
Meinshausen, M., Schleussner, C.-F., Beyer, K., Bodeker, G., Boucher, O., Canadell, J. G., Daniel, J. S., Diongue-Niang, A., Driouech, F., Fischer, E., Forster, P., Grose, M., Hansen, G., Hausfather, Z., Ilyina, T., Kikstra, J. S., Kimutai, J., King, A. D., Lee, J.-Y., Lennard, C., Lissner, T., Nauels, A., Peters, G. P., Pirani, A., Plattner, G.-K., Pörtner, H., Rogelj, J., Rojas, M., Roy, J., Samset, B. H., Sanderson, B. M., Séférian, R., Seneviratne, S., Smith, C. J., Szopa, S., Thomas, A., Urge-Vorsatz, D., Velders, G. J. M., Yokohata, T., Ziehn, T., and Nicholls, Z.: A perspective on the next generation of Earth system model scenarios: towards representative emission pathways (REPs), Geosci. Model Dev., 17, 4533–4559, https://doi.org/10.5194/gmd-17-4533-2024, 2024.
Méjean, A., Collins-Sowah, P., Guivarch, C., Piontek, F., Soergel, B., and Taconet, N.: Climate change impacts increase economic inequality: evidence from a systematic literature review, Environ. Res. Lett. 19, 043003, https://doi.org/10.1088/1748-9326/ad376e, 2024.
Miranda, N. D., Lizana, J., Sparrow, S. N., Zachau-Walker, M., Watson, P. A. G., Wallom, D. C. H., Khosla, R., and McCulloch, M.: Change in cooling degree days with global mean temperature rise increasing from 1.5 °C to 2.0 °C, Nat. Sustain., 6, 1326–1330, https://doi.org/10.1038/s41893-023-01155-z, 2023.
Molina Bacca, E. J., Stevanović, M., Bodirsky, B. L., Karstens, K., Chen, D. M.-C., Leip, D., Müller, C., Minoli, S., Heinke, J., Jägermeyr, J., Folberth, C., Iizumi, T., Jain, A. K., Liu, W., Okada, M., Smerald, A., Zabel, F., Lotze-Campen, H., and Popp, A.: Uncertainty in land-use adaptation persists despite crop model projections showing lower impacts under high warming, Commun. Earth Environ., 4, 284, https://doi.org/10.1038/s43247-023-00941-z, 2023.
Monteiro, P. J. M., Miller, S. A., and Horvath, A.: Towards sustainable concrete, Nat. Mater., 16, 698–699, https://doi.org/10.1038/nmat4930, 2017.
Moore, F. C., Baldos, U., Hertel, T., and Diaz, D.: New science of climate change impacts on agriculture implies higher social cost of carbon, Nat. Commun., 8, https://doi.org/10.1038/s41467-017-01792-x, 2017.
Moore, F. C., Lacasse, K., Mach, K. J., Shin, Y. A., Gross, L. J., and Beckage, B.: Determinants of emissions pathways in the coupled climate–social system, Nature, 603, 103–111, https://doi.org/10.1038/s41586-022-04423-8, 2022.
Müller, C., Elliott, J., Kelly, D., Arneth, A., Balkovic, J., Ciais, P., Deryng, D., Folberth, C., Hoek, S., Izaurralde, R. C., Jones, C. D., Khabarov, N., Lawrence, P., Liu, W., Olin, S., Pugh, T. A. M., Reddy, A., Rosenzweig, C., Ruane, A. C., Sakurai, G., Schmid, E., Skalsky, R., Wang, X., de Wit, A., and Yang, H.: The Global Gridded Crop Model Intercomparison phase 1 simulation dataset, Sci. Data, 6, https://doi.org/10.1038/s41597-019-0023-8, 2019.
Müller, C., Franke, J., Jägermeyr, J., Ruane, A. C., Elliott, J., Moyer, E., Heinke, J., Falloon, P. D., Folberth, C., Francois, L., Hank, T., Izaurralde, R. C., Jacquemin, I., Liu, W., Olin, S., Pugh, T. A. M., Williams, K., and Zabel, F.: Exploring uncertainties in global crop yield projections in a large ensemble of crop models and CMIP5 and CMIP6 climate scenarios, Environmental Research Letters, 16, https://doi.org/10.1088/1748-9326/abd8fc, 2021.
Müller, C., Jägermeyr, J., Franke, J. A., Ruane, A. C., Balkovic, J., Ciais, P., Dury, M., Falloon, P., Folberth, C., Hank, T., Hoffmann, M., Izaurralde, R. C., Jacquemin, I., Khabarov, N., Liu, W., Olin, S., Pugh, T. A. M., Wang, X., Williams, K., Zabel, F., and Elliott, J. W.: Substantial Differences in Crop Yield Sensitivities Between Models Call for Functionality-Based Model Evaluation, Earths Future, 12, https://doi.org/10.1029/2023EF003773, 2024.
Neumann, J. E., Willwerth, J., Martinich, J., McFarland, J., Sarofim, M. C., and Yohe, G.: Climate Damage Functions for Estimating the Economic Impacts of Climate Change in the United States, Rev. Environ. Econ. Policy, 14, 25–43, https://doi.org/10.1093/reep/rez021, 2020.
Newman, R. and Noy, I.: The global costs of extreme weather that are attributable to climate change, Nat. Commun., 14, https://doi.org/10.1038/s41467-023-41888-1, 2023.
Nordhaus, W.: Estimates of the Social Cost of Carbon: Concepts and Results from the DICE-2013R Model and Alternative Approaches, J. Assoc. Environ. Resour. Econ., 1, 273–312, https://doi.org/10.1086/676035, 2014.
O'Neill, B. C., Kriegler, E., Riahi, K., Ebi, K. L., Hallegatte, S., Carter, T. R., Mathur, R., and van Vuuren, D. P.: A new scenario framework for climate change research: The concept of shared socioeconomic pathways, Clim. Change, 122, 387–400, https://doi.org/10.1007/s10584-013-0905-2, 2014.
Orlov, A., Sillmann, J., Aunan, K., Kjellstrom, T., and Aaheim, A.: Economic costs of heat-induced reductions in worker productivity due to global warming, Global Environmental Change, 63, https://doi.org/10.1016/j.gloenvcha.2020.102087, 2020.
Orlov, A., Daloz, A. S., Sillmann, J., Thiery, W., Douzal, C., Lejeune, Q., and Schleussner, C.: Global Economic Responses to Heat Stress Impacts on Worker Productivity in Crop Production, Econ. Disaster Clim. Chang., 5, 367–390, https://doi.org/10.1007/s41885-021-00091-6, 2021.
Osborn, T. J., Jones, P. D., Lister, D. H., Morice, C. P., Simpson, I. R., Winn, J. P., Hogan, E., and Harris, I. C.: Land Surface Air Temperature Variations Across the Globe Updated to 2019: The CRUTEM5 Data Set, Journal of Geophysical Research: Atmospheres, 126, e2019JD032352, https://doi.org/10.1029/2019JD032352, 2021.
Ostberg, S., Schewe, J., Childers, K., and Frieler, K.: Changes in crop yields and their variability at different levels of global warming, Earth Syst. Dynam., 9, 479–496, https://doi.org/10.5194/esd-9-479-2018, 2018.
Palagi, E., Coronese, M., Lamperti, F., and Roventini, A.: Climate change and the nonlinear impact of precipitation anomalies on income inequality, P. Natl. Acad. Sci. USA, 119, e2203595119, https://doi.org/10.1073/pnas.2203595119, 2022.
Park, C. Y., Takahashi, K., Fujimori, S., Phung, V. L. H., Li, F., Takakura, J., Hasegawa, T., and Jansakoo, T.: Future fire-PM2.5 mortality varies depending on climate and socioeconomic changes, Environmental Research Letters, 19, https://doi.org/10.1088/1748-9326/ad1b7d, 2024.
Piontek, F., Drouet, L., Emmerling, J., Kompas, T., Méjean, A., Otto, C., Rising, J., Soergel, B., Taconet, N., and Tavoni, M.: Integrated perspective on translating biophysical to economic impacts of climate change, Nat. Clim. Change, 11, 563–572, https://doi.org/10.1038/s41558-021-01065-y, 2021.
Pirani, A., Fuglestvedt, J. S., Byers, E., O'Neill, B., Riahi, K., Lee, J.-Y., Marotzke, J., Rose, S. K., Schaeffer, R., and Tebaldi, C.: Scenarios in IPCC assessments: lessons from AR6 and opportunities for AR7, npj Climate Action, 3, https://doi.org/10.1038/s44168-023-00082-1, 2024.
Pörtner, H.-O., Roberts, D. C., Adams, H., Adelekan, I., Adler, C., Adrian, R., Aldunce, P., Ali, E., Ara Begum, R., Bednar-Friedl, B., Bezner Kerr, R., Biesbroek, R., Birkmann, J., Bowen, K., Caretta, M. A., Carnicer, J., Castellanos, E., Cheong, T. S., Chow, W., Cissé, G., Clayton, S., Constable, A., Cooley, S. R., Costello, M. J., Craig, M., Cramer, W., Dawson, R., Dodman, D., Efitre, J., Garschagen, M., Gilmore, E. A., Glavovic, B. C., Gutzler, D., Haasnoot, M., Harper, S., Hasegawa, T., Hayward, B., Hicke, J. A., Hirabayashi, Y., Huang, C., Kalaba, K., Kiessling, W., Kitoh, A., Lasco, R., Lawrence, J., Lemos, M. F., Lempert, R., Lennard, C., Ley, D., Lissner, T., Liu, Q., Liwenga, E., Lluch-Cota, S., Löschke, S., Lucatello, S., Luo, Y., Mackey, B., Mintenbeck, K., Mirzabaev, A., Möller, V., Moncassim Vale, M., Morecroft, M. D., Mortsch, L., Mukherji, A., Mustonen, T., Mycoo, M., Nalau, J., New, M., Okem, A., Ometto, J. P., O’Neill, B., Pandey, R., Parmesan, C., Pelling, M., Pinho, P. F., Pinnegar, J., Poloczanska, E. S., Prakash, A., Preston, B., Racault, M.-F., Reckien, D., Revi, A., Rose, S. K., Schipper, E. L. F., Schmidt, D. N., Schoeman, D., Shaw, R., Simpson, N. P., Singh, C., Solecki, W., Stringer, L., Totin, E., Trisos, C. H., Trisurat, Y., van Aalst, M., Viner, D., Wairiu, M., Warren, R., Wester, P., Wrathall, D., and Zaiton Ibrahim, Z. (Eds.): Technical Summary, in: Climate Change 2022: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Pörtner, H.-O., Roberts, D. C., Poloczanska, E. S., Mintenbeck, K., Tignor, M., Alegría, A., Craig, M., Langsdorf, S., Löschke, S., Möller, V., and Okem A., Cambridge University Press, Cambridge, UK and New York, NY, USA, 37–118, https://doi.org/10.1017/9781009325844.002, 2022.
Rajah, J. K., Blanz, B., Kopainsky, B., and Schoenberg, W.: An endogenous modelling framework of dietary behavioural change in the fully coupled human-climate FRIDA v2.1 model, Geosci. Model Dev., 18, 5997–6022, https://doi.org/10.5194/gmd-18-5997-2025, 2025.
Ramme, L., Blanz, B., Wells, C., Wong, T. E., Schoenberg, W., Smith, C., and Li, C.: Feedback-based sea level rise impact modelling for integrated assessment models with FRISIAv1.0, Geosci. Model Dev., 18, 10017–10052, https://doi.org/10.5194/gmd-18-10017-2025, 2025.
Ren, X., Weitzel, M., O'Neill, B. C., Lawrence, P., Meiyappan, P., Levis, S., Balistreri, E. J., and Dalton, M.: Avoided economic impacts of climate change on agriculture: integrating a land surface model (CLM) with a global economic model (iPETS), Clim. Change, 146, 517–531, https://doi.org/10.1007/s10584-016-1791-1, 2018.
Rennert, K., Errickson, F., Prest, B. C., Rennels, L., Newell, R. G., Pizer, W., Kingdon, C., Wingenroth, J., Cooke, R., Parthum, B., Smith, D., Cromar, K., Diaz, D., Moore, F. C., Müller, U. K., Plevin, R. J., Raftery, A. E., Ševčíková, H., Sheets, H., Stock, J. H., Tan, T., Watson, M., Wong, T. E., and Anthoff, D.: Comprehensive evidence implies a higher social cost of CO2, Nature, 610, 687–692, https://doi.org/10.1038/s41586-022-05224-9, 2022.
Rezaei, E. E., Webber, H., Asseng, S., Boote, K., Durand, J. L., Ewert, F., Martre, P., and MacCarthy, D. S.: Climate change impacts on crop yields, Nature Reviews Earth & Environment, 4, 831–846, https://doi.org/10.1038/s43017-023-00491-0, 2023.
Richardson, K., Steffen, W., Lucht, W., Bendtsen, J., Cornell, S. E., Donges, J. F., Drüke, M., Fetzer, I., Bala, G., von Bloh, W., Feulner, G., Fiedler, S., Gerten, D., Gleeson, T., Hofmann, M., Huiskamp, W., Kummu, M., Mohan, C., Nogués-Bravo, D., Petri, S., Porkka, M., Rahmstorf, S., Schaphoff, S., Thonicke, K., Tobian, A., Virkki, V., Wang-Erlandsson, L., Weber, L., and Rockström, J.: Earth beyond six of nine planetary boundaries, Sci. Adv., 9, eadh2458, https://doi.org/10.1126/sciadv.adh2458, 2023.
Ripple, W. J., Wolf, C., Lenton, T. M., Gregg, J. W., Natali, S. M., Duffy, P. B., Rockström, J., and Schellnhuber, H. J.: Many risky feedback loops amplify the need for climate action, One Earth, 6, 86–91, https://doi.org/10.1016/j.oneear.2023.01.004, 17 2023.
Robinson, D. T., Di Vittorio, A., Alexander, P., Arneth, A., Barton, C. M., Brown, D. G., Kettner, A., Lemmen, C., O'Neill, B. C., Janssen, M., Pugh, T. A. M., Rabin, S. S., Rounsevell, M., Syvitski, J. P., Ullah, I., and Verburg, P. H.: Modelling feedbacks between human and natural processes in the land system, Earth Syst. Dynam., 9, 895–914, https://doi.org/10.5194/esd-9-895-2018, 2018.
Rodano, G., Serrano-Velarde, N., and Tarantino, E.: Lending Standards over the Credit Cycle, Rev. Financ. Stud., 31, 2943–2982, https://doi.org/10.1093/rfs/hhy023, 2018.
Rode, A., Carleton, T., Delgado, M., Greenstone, M., Houser, T., Hsiang, S., Hultgren, A., Jina, A., Kopp, R. E., McCusker, K. E., Nath, I., Rising, J., and Yuan, J.: Estimating a social cost of carbon for global energy consumption, Nature, 598, 308–314, https://doi.org/10.1038/s41586-021-03883-8, 2021.
Rounsevell, M. D. A., Robinson, D. T., and Murray-Rust, D.: From actors to agents in socio-ecological systems models, Philos. T. Roy. Soc. B, 367, 259–269, https://doi.org/10.1098/rstb.2011.0187, 2012.
Ruane, A. C., Phillips, M., Jägermeyr, J., and Müller, C.: Non-Linear Climate Change Impacts on Crop Yields May Mislead Stakeholders, Earths Future, 12, https://doi.org/10.1029/2023EF003842, 2024.
Schoenberg, W. and Callegari, B.: The role of persistent climate-driven financial effects in estimating climate damages through integrated assessment models, SSRN [preprint], https://doi.org/10.2139/ssrn.5677205, 2025.
Schoenberg, W., Blanz, B., Rajah, J. K., Callegari, B., Wells, C., Breier, J., Grimeland, M. B., Lindqvist, A. N., Ramme, L., Smith, C., Li, C., Mashhadi, S., Muralidhar, A., and Mauritzen, C.: An overview of FRIDA v2.1: a feedback-based, fully coupled, global integrated assessment model of climate and humans, Geosci. Model Dev., 18, 8047–8069, https://doi.org/10.5194/gmd-18-8047-2025, 2025a.
Schoenberg, W., Blanz, B., Ramme, L., Wells, C., Grimeland, M., Callegari, B., Breier, J., Rajah, J., Nicolaidis Lindqvist, A., Mashhadi, S., Muralidhar, A., and Eriksson, A.: FRIDA: Feedback-based knowledge Repository for IntegrateD Assessments (v2.1), Zenodo [code], https://doi.org/10.5281/zenodo.15310860, 2025b.
Schwarzwald, K., Lenssen, N., and Palmer, E. T.: The importance of internal climate variability in climate impact projections, P. Natl. Acad. Sci. USA, 119, e2208095119, https://doi.org/10.1073/pnas.2208095119, 2022.
Schwingshackl, C., Sillmann, J., Vicedo-Cabrera, A. M., Sandstad, M., and Aunan, K.: Heat Stress Indicators in CMIP6: Estimating Future Trends and Exceedances of Impact-Relevant Thresholds, Earths Future, 9, https://doi.org/10.1029/2020EF001885, 2021.
Sherwood, S. C., Dixit, V., and Salomez, C.: The global warming potential of near-surface emitted water vapour, Environmental Research Letters, 13, https://doi.org/10.1088/1748-9326/aae018, 2018.
Shi, L., Feng, P., Wang, B., Li Liu, D., Cleverly, J., Fang, Q., and Yu, Q.: Projecting potential evapotranspiration change and quantifying its uncertainty under future climate scenarios: A case study in southeastern Australia, J. Hydrol., 584, 124756, https://doi.org/10.1016/j.jhydrol.2020.124756, 2020.
Shiogama, H., Takakura, J., and Takahashi, K.: Uncertainty constraints on economic impact assessments of climate change simulated by an impact emulator, Environmental Research Letters, 17, https://doi.org/10.1088/1748-9326/aca68d, 2022.
Smith, C., Cummins, D. P., Fredriksen, H.-B., Nicholls, Z., Meinshausen, M., Allen, M., Jenkins, S., Leach, N., Mathison, C., and Partanen, A.-I.: fair-calibrate v1.4.1: calibration, constraining, and validation of the FaIR simple climate model for reliable future climate projections, Geosci. Model Dev., 17, 8569–8592, https://doi.org/10.5194/gmd-17-8569-2024, 2024.
Spinoni, J., Barbosa, P., Füssel, H. M., McCormick, N., Vogt, J. V., and Dosio, A.: Global population-weighted degree-day projections for a combination of climate and socio-economic scenarios, International Journal of Climatology, 41, 5447–5464, https://doi.org/10.1002/joc.7328, 2021.
Stewart, M. G., Wang, X., and Nguyen, M. N.: Climate change impact and risks of concrete infrastructure deterioration, Eng. Struct., 33, 1326–1337, https://doi.org/10.1016/j.engstruct.2011.01.010, 2011.
Stroebel, J. and Wurgler, J.: What do you think about climate finance?, J. Financ. Econ., 142, 487–498, https://doi.org/10.1016/j.jfineco.2021.08.004, 2021.
Takakura, J., Fujimori, S., Hanasaki, N., Hasegawa, T., Hirabayashi, Y., Honda, Y., Iizumi, T., Kumano, N., Park, C., Shen, Z., Takahashi, K., Tamura, M., Tanoue, M., Tsuchida, K., Yokoki, H., Zhou, Q., Oki, T., and Hijioka, Y.: Dependence of economic impacts of climate change on anthropogenically directed pathways, Nat. Clim. Chang., 9, 737–741, https://doi.org/10.1038/s41558-019-0578-6, 2019.
Tebaldi, C. and Lobell, D.: Estimated impacts of emission reductions on wheat and maize crops, Clim. Change, 146, 533–545, https://doi.org/10.1007/s10584-015-1537-5, 2018.
Tiggeloven, T., de Moel, H., Winsemius, H. C., Eilander, D., Erkens, G., Gebremedhin, E., Diaz Loaiza, A., Kuzma, S., Luo, T., Iceland, C., Bouwman, A., van Huijstee, J., Ligtvoet, W., and Ward, P. J.: Global-scale benefit–cost analysis of coastal flood adaptation to different flood risk drivers using structural measures, Nat. Hazards Earth Syst. Sci., 20, 1025–1044, https://doi.org/10.5194/nhess-20-1025-2020, 2020.
Tol, R. S. J.: The double trade-off between adaptation and mitigation for sea level rise: an application of FUND, Mitig. Adapt. Strateg. Glob. Chang., 12, 741–753, 2007.
van der Linden, S.: The social-psychological determinants of climate change risk perceptions: Towards a comprehensive model, J. Environ. Psychol., 41, 112–124, https://doi.org/10.1016/j.jenvp.2014.11.012, 2015.
van Maanen, N., Lissner, T., Harmsen, M., Piontek, F., Andrijevic, M., and van Vuuren, D. P.: Representation of adaptation in quantitative climate assessments, Nat. Clim. Change, 13, 309–311, https://doi.org/10.1038/s41558-023-01644-1, 2023.
van Ruijven, B. J., De Cian, E., and Sue Wing, I.: Amplification of future energy demand growth due to climate change, Nat. Commun., 10, https://doi.org/10.1038/s41467-019-10399-3, 2019.
Van Vliet, M. T. H., Wiberg, D., Leduc, S., and Riahi, K.: Power-generation system vulnerability and adaptation to changes in climate and water resources, Nat. Clim. Chang., 6, 375–380, https://doi.org/10.1038/nclimate2903, 2016.
van Vuuren, D., O'Neill, B., Tebaldi, C., Chini, L., Friedlingstein, P., Hasegawa, T., Riahi, K., Sanderson, B., Govindasamy, B., Bauer, N., Eyring, V., Fall, C., Frieler, K., Gidden, M., Gohar, L., Jones, A., King, A., Knutti, R., Kriegler, E., Lawrence, P., Lennard, C., Lowe, J., Mathison, C., Mehmood, S., Prado, L., Zhang, Q., Rose, S., Ruane, A., Schleussner, C.-F., Seferian, R., Sillmann, J., Smith, C., Sörensson, A., Panickal, S., Tachiiri, K., Vaughan, N., Vishwanathan, S., Yokohata, T., and Ziehn, T.: The Scenario Model Intercomparison Project for CMIP7 (ScenarioMIP-CMIP7) , EGUsphere [preprint], https://doi.org/10.5194/egusphere-2024-3765, 2025.
Waidelich, P., Batibeniz, F., Rising, J., Kikstra, J. S., and Seneviratne, S. I.: Climate damage projections beyond annual temperature, Nat. Clim. Chang., 14, 592–599, https://doi.org/10.1038/s41558-024-01990-8, 2024.
Waldhoff, S., Anthoff, D., Rose, S., and Tol, R. S. J.: The Marginal Damage Costs of Different Greenhouse Gases: An Application of FUND, Economics, 8, https://doi.org/10.5018/economics-ejournal.ja.2014-31, 2014.
Wang, X., Stewart, M. G., and Nguyen, M.: Impact of climate change on corrosion and damage to concrete infrastructure in Australia, Clim. Change, 110, 941–957, https://doi.org/10.1007/s10584-011-0124-7, 2012.
Wells, C. D.: FRIDAv2.1 climate damage functions and figures (Version v1), Zenodo [code], https://doi.org/10.5281/zenodo.18154029, 2026.
Wells, C. D., Ramme, L., Smith, C., Breier, J., Muralidhar, A., Li, C., Gjermundsen, A., Schoenberg, W. A., Blanz, B., and Mauritzen, C.: FRIDA-Clim v1.0.0: a Simple Climate Model with Process-Based Carbon Cycle used in the FRIDAv2.1 IAM, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2025-4766, 2025.
Werning, M., Frank, S., Hooke, D., Nguyen, B., Rafaj, P., Satoh, Y., Wögerer, M., Krey, V., Riahi, K., van Ruivjen, B., and Byers, E.: Climate Solutions Explorer – hazard, impacts and exposure data, Zenodo [data set], https://doi.org/10.5281/zenodo.13753537, 2024a.
Werning, M., Hooke, D., Krey, V., Riahi, K., van Ruijven, B., and Byers, E. A.: Global warming level indicators of climate change and hotspots of exposure, Environmental Research: Climate, 3, 045015, https://doi.org/10.1088/2752-5295/ad8300, 2024b.
Wong, T. E., Ledna, C., Rennels, L., Sheets, H., Errickson, F. C., Diaz, D., and Anthoff, D.: Sea Level and Socioeconomic Uncertainty Drives High-End Coastal Adaptation Costs, Earths Future, 10, e2022EF003061, https://doi.org/10.1029/2022EF003061, 2022.
World Bank: World Development Indicators, https://databank.worldbank.org/source/world-development-indicators (last access: 5 August 2024), 2012.
Wunderling, N., Winkelmann, R., Rockström, J., Loriani, S., Armstrong McKay, D. I., Ritchie, P. D. L., Sakschewski, B., and Donges, J. F.: Global warming overshoots increase risks of climate tipping cascades in a network model, Nat. Clim. Chang., 13, 75–82, https://doi.org/10.1038/s41558-022-01545-9, 2023.
Xie, B., Brewer, M. B., Hayes, B. K., McDonald, R. I., and Newell, B. R.: Predicting climate change risk perception and willingness to act, J. Environ. Psychol., 65, 101331, https://doi.org/10.1016/j.jenvp.2019.101331, 2019.
Yalew, S. G., van Vliet, M. T. H., Gernaat, D. E. H. J., Ludwig, F., Miara, A., Park, C., Byers, E., De Cian, E., Piontek, F., Iyer, G., Mouratiadou, I., Glynn, J., Hejazi, M., Dessens, O., Rochedo, P., Pietzcker, R., Schaeffer, R., Fujimori, S., Dasgupta, S., Mima, S., da Silva, S. R. S., Chaturvedi, V., Vautard, R., and van Vuuren, D. P.: Impacts of climate change on energy systems in global and regional scenarios, Nat. Energy, 5, 794–802, https://doi.org/10.1038/s41560-020-0664-z, 2020.
Zhao, C., Liu, B., Piao, S., Wang, X., Lobell, D. B., Huang, Y., Huang, M., Yao, Y., Bassu, S., Ciais, P., Durand, J. L., Elliott, J., Ewert, F., Janssens, I. A., Li, T., Lin, E., Liu, Q., Martre, P., Müller, C., Peng, S., Peñuelas, J., Ruane, A. C., Wallach, D., Wang, T., Wu, D., Liu, Z., Zhu, Y., Zhu, Z., and Asseng, S.: Temperature increase reduces global yields of major crops in four independent estimates, Proc. Natl. Acad. Sci. USA, 114, 9326–9331, https://doi.org/10.1073/pnas.1701762114, 2017.
Short summary
Computer models built to study future developments of human activity and climate change often exclude the impacts of climate change. Here, we include these effects in a new model. We create functions connecting changes in global temperature, carbon dioxide, and sea level to energy supply and demand, food systems, mortality, economic damages, and other important quantities. Including these effects will allow us to explore their impact on future changes in the human and climate realms.
Computer models built to study future developments of human activity and climate change often...