Articles | Volume 18, issue 21
https://doi.org/10.5194/gmd-18-8047-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-18-8047-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
30 Oct 2025
Model description paper |
| 30 Oct 2025
| 30 Oct 2025
An overview of FRIDA v2.1: a feedback-based, fully coupled, global integrated assessment model of climate and humans
William Schoenberg
CORRESPONDING AUTHOR
System Dynamics Group, University of Bergen, P.O. Box 7802, 5020 Bergen, Norway
isee systems inc., 24 Hanover St. Suite 8A, Lebanon, New Hampshire 03766, USA
Benjamin Blanz
Research Unit Sustainability and Climate Risks, University of Hamburg, Grindelberg 5, 20144 Hamburg, Germany
Jefferson K. Rajah
System Dynamics Group, University of Bergen, P.O. Box 7802, 5020 Bergen, Norway
Beniamino Callegari
School of Economics, Innovation and Technology, Kristiania University of Applied Sciences, Oslo, Norway
Christopher Wells
School of Earth and Environment, University of Leeds, Leeds, LS2 9JT, United Kingdom
Jannes Breier
Potsdam Institute for Climate Impact Research, Telegrafenberg A31, 14473 Potsdam, Germany
Martin B. Grimeland
School of Economics, Innovation and Technology, Kristiania University of Applied Sciences, Oslo, Norway
Andreas Nicolaidis Lindqvist
Stockholm Resilience Centre, Stockholm University, Albanovägen 28, 106 91 Stockholm, Sweden
RISE Research Institutes of Sweden, Ideon Beta5, Scheelevägen 17, 22370, Lund, Sweden
Lennart Ramme
Max-Planck-Institute for Meteorology, Bundesstraße 53, 20146 Hamburg, Germany
Chris Smith
Department of Water and Climate, Vrije Universiteit Brussel, 1050 Brussels, Belgium
Energy, Climate and Environment Program, International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria
Max-Planck-Institute for Meteorology, Bundesstraße 53, 20146 Hamburg, Germany
Sarah Mashhadi
Department of Ocean and Ice, Norwegian Meteorological Institute, 0313 Blindern, Oslo
Adakudlu Muralidhar
Department of Ocean and Ice, Norwegian Meteorological Institute, 0313 Blindern, Oslo
Cecilie Mauritzen
Department of Ocean and Ice, Norwegian Meteorological Institute, 0313 Blindern, Oslo
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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
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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.
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
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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
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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
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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
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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
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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
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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
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Assessing hundreds or thousands of emission scenarios in terms of their global mean temperature implications requires standardised procedures of infilling, harmonisation, and probabilistic temperature assessments. We here present the open-source
climate-assessmentworkflow that was used in the IPCC AR6 Working Group III report. The paper provides key insight for anyone wishing to understand the assessment of climate outcomes of mitigation pathways in the context of the Paris Agreement.
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
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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.
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
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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
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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
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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.
Gillian Thornhill, William Collins, Dirk Olivié, Ragnhild B. Skeie, Alex Archibald, Susanne Bauer, Ramiro Checa-Garcia, Stephanie Fiedler, Gerd Folberth, Ada Gjermundsen, Larry Horowitz, Jean-Francois Lamarque, Martine Michou, Jane Mulcahy, Pierre Nabat, Vaishali Naik, Fiona M. O'Connor, Fabien Paulot, Michael Schulz, Catherine E. Scott, Roland Séférian, Chris Smith, Toshihiko Takemura, Simone Tilmes, Kostas Tsigaridis, and James Weber
Atmos. Chem. Phys., 21, 1105–1126, https://doi.org/10.5194/acp-21-1105-2021, https://doi.org/10.5194/acp-21-1105-2021, 2021
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We find that increased temperatures affect aerosols and reactive gases by changing natural emissions and their rates of removal from the atmosphere. Changing the composition of these species in the atmosphere affects the radiative budget of the climate system and therefore amplifies or dampens the climate response of climate models of the Earth system. This study found that the largest effect is a dampening of climate change as warmer temperatures increase the emissions of cooling aerosols.
Gillian D. Thornhill, William J. Collins, Ryan J. Kramer, Dirk Olivié, Ragnhild B. Skeie, Fiona M. O'Connor, Nathan Luke Abraham, Ramiro Checa-Garcia, Susanne E. Bauer, Makoto Deushi, Louisa K. Emmons, Piers M. Forster, Larry W. Horowitz, Ben Johnson, James Keeble, Jean-Francois Lamarque, Martine Michou, Michael J. Mills, Jane P. Mulcahy, Gunnar Myhre, Pierre Nabat, Vaishali Naik, Naga Oshima, Michael Schulz, Christopher J. Smith, Toshihiko Takemura, Simone Tilmes, Tongwen Wu, Guang Zeng, and Jie Zhang
Atmos. Chem. Phys., 21, 853–874, https://doi.org/10.5194/acp-21-853-2021, https://doi.org/10.5194/acp-21-853-2021, 2021
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This paper is a study of how different constituents in the atmosphere, such as aerosols and gases like methane and ozone, affect the energy balance in the atmosphere. Different climate models were run using the same inputs to allow an easy comparison of the results and to understand where the models differ. We found the effect of aerosols is to reduce warming in the atmosphere, but this effect varies between models. Reactions between gases are also important in affecting climate.
Zebedee R. J. Nicholls, Malte Meinshausen, Jared Lewis, Robert Gieseke, Dietmar Dommenget, Kalyn Dorheim, Chen-Shuo Fan, Jan S. Fuglestvedt, Thomas Gasser, Ulrich Golüke, Philip Goodwin, Corinne Hartin, Austin P. Hope, Elmar Kriegler, Nicholas J. Leach, Davide Marchegiani, Laura A. McBride, Yann Quilcaille, Joeri Rogelj, Ross J. Salawitch, Bjørn H. Samset, Marit Sandstad, Alexey N. Shiklomanov, Ragnhild B. Skeie, Christopher J. Smith, Steve Smith, Katsumasa Tanaka, Junichi Tsutsui, and Zhiang Xie
Geosci. Model Dev., 13, 5175–5190, https://doi.org/10.5194/gmd-13-5175-2020, https://doi.org/10.5194/gmd-13-5175-2020, 2020
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Computational limits mean that we cannot run our most comprehensive climate models for all applications of interest. In such cases, reduced complexity models (RCMs) are used. Here, researchers working on 15 different models present the first systematic community effort to evaluate and compare RCMs: the Reduced Complexity Model Intercomparison Project (RCMIP). Our research ensures that users of RCMs can more easily evaluate the strengths, weaknesses and limitations of their tools.
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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.
The current crop of models assessed by the Intergovernmental Panel on Climate Change to produce...
