Articles | Volume 14, issue 5
https://doi.org/10.5194/gmd-14-3007-2021
© Author(s) 2021. 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-14-3007-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| Highlight paper
| 
27 May 2021
Model description paper | Highlight paper |
| 27 May 2021
| 27 May 2021
FaIRv2.0.0: a generalized impulse response model for climate uncertainty and future scenario exploration
Nicholas J. Leach
CORRESPONDING AUTHOR
Atmospheric, Oceanic, and Planetary Physics, Department of Physics, University of Oxford, Oxford, UK
Stuart Jenkins
Atmospheric, Oceanic, and Planetary Physics, Department of Physics, University of Oxford, Oxford, UK
Zebedee Nicholls
Australian–German Climate and Energy College, University of Melbourne, Melbourne, Australia
School of Geography, Earth and Atmospheric Sciences, University of Melbourne, Melbourne, Australia
Christopher J. Smith
CORRESPONDING AUTHOR
School of Earth and Environment, University of Leeds, Leeds, UK
International Institute for Applied Systems Analysis, Laxenburg, Austria
John Lynch
Atmospheric, Oceanic, and Planetary Physics, Department of Physics, University of Oxford, Oxford, UK
Michelle Cain
Atmospheric, Oceanic, and Planetary Physics, Department of Physics, University of Oxford, Oxford, UK
Tristram Walsh
Atmospheric, Oceanic, and Planetary Physics, Department of Physics, University of Oxford, Oxford, UK
Bill Wu
Atmospheric, Oceanic, and Planetary Physics, Department of Physics, University of Oxford, Oxford, UK
Junichi Tsutsui
Environmental Science Research Laboratory, Central Research Institute of Electric Power Industry, Abiko, Japan
Myles R. Allen
Atmospheric, Oceanic, and Planetary Physics, Department of Physics, University of Oxford, Oxford, UK
Environmental Change Institute, University of Oxford, Oxford, UK
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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
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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
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Benjamin Mark Sanderson, Victor Brovkin, Rosie Fisher, David Hohn, Tatiana Ilyina, Chris Jones, Torben Koenigk, Charles Koven, Hongmei Li, David Lawrence, Peter Lawrence, Spencer Liddicoat, Andrew Macdougall, Nadine Mengis, Zebedee Nicholls, Eleanor O'Rourke, Anastasia Romanou, Marit Sandstad, Jörg Schwinger, Roland Seferian, Lori Sentman, Isla Simpson, Chris Smith, Norman Steinert, Abigail Swann, Jerry Tjiputra, and Tilo Ziehn
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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
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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
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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
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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
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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.
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.
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.
Susanne Baur, Alexander Nauels, Zebedee Nicholls, Benjamin M. Sanderson, and Carl-Friedrich Schleussner
Earth Syst. Dynam., 14, 367–381, https://doi.org/10.5194/esd-14-367-2023, https://doi.org/10.5194/esd-14-367-2023, 2023
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Solar radiation modification (SRM) artificially cools global temperature without acting on the cause of climate change. This study looks at how long SRM would have to be deployed to limit warming to 1.5 °C and how this timeframe is affected by different levels of mitigation, negative emissions and climate uncertainty. None of the three factors alone can guarantee short SRM deployment. Due to their uncertainty at the time of SRM initialization, any deployment risks may be several centuries long.
Jarmo S. Kikstra, Zebedee R. J. Nicholls, Christopher J. Smith, Jared Lewis, Robin D. Lamboll, Edward Byers, Marit Sandstad, Malte Meinshausen, Matthew J. Gidden, Joeri Rogelj, Elmar Kriegler, Glen P. Peters, Jan S. Fuglestvedt, Ragnhild B. Skeie, Bjørn H. Samset, Laura Wienpahl, Detlef P. van Vuuren, Kaj-Ivar van der Wijst, Alaa Al Khourdajie, Piers M. Forster, Andy Reisinger, Roberto Schaeffer, and Keywan Riahi
Geosci. Model Dev., 15, 9075–9109, https://doi.org/10.5194/gmd-15-9075-2022, https://doi.org/10.5194/gmd-15-9075-2022, 2022
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Assessing hundreds or thousands of emission scenarios in terms of their global mean temperature implications requires standardised procedures of infilling, harmonisation, and probabilistic temperature assessments. We here present the open-source
climate-assessmentworkflow that was used in the IPCC AR6 Working Group III report. The paper provides key insight for anyone wishing to understand the assessment of climate outcomes of mitigation pathways in the context of the Paris Agreement.
Ruksana H. Rimi, Karsten Haustein, Emily J. Barbour, Sarah N. Sparrow, Sihan Li, David C. H. Wallom, and Myles R. Allen
Hydrol. Earth Syst. Sci., 26, 5737–5756, https://doi.org/10.5194/hess-26-5737-2022, https://doi.org/10.5194/hess-26-5737-2022, 2022
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Extreme rainfall events are major concerns in Bangladesh. Heavy downpours can cause flash floods and damage nearly harvestable crops in pre-monsoon season. While in monsoon season, the impacts can range from widespread agricultural loss, huge property damage, to loss of lives and livelihoods. This paper assesses the role of anthropogenic climate change drivers in changing risks of extreme rainfall events during pre-monsoon and monsoon seasons at local sub-regional-scale within Bangladesh.
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.
Charles D. Koven, Vivek K. Arora, Patricia Cadule, Rosie A. Fisher, Chris D. Jones, David M. Lawrence, Jared Lewis, Keith Lindsay, Sabine Mathesius, Malte Meinshausen, Michael Mills, Zebedee Nicholls, Benjamin M. Sanderson, Roland Séférian, Neil C. Swart, William R. Wieder, and Kirsten Zickfeld
Earth Syst. Dynam., 13, 885–909, https://doi.org/10.5194/esd-13-885-2022, https://doi.org/10.5194/esd-13-885-2022, 2022
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We explore the long-term dynamics of Earth's climate and carbon cycles under a pair of contrasting scenarios to the year 2300 using six models that include both climate and carbon cycle dynamics. One scenario assumes very high emissions, while the second assumes a peak in emissions, followed by rapid declines to net negative emissions. We show that the models generally agree that warming is roughly proportional to carbon emissions but that many other aspects of the model projections differ.
Lea Beusch, Zebedee Nicholls, Lukas Gudmundsson, Mathias Hauser, Malte Meinshausen, and Sonia I. Seneviratne
Geosci. Model Dev., 15, 2085–2103, https://doi.org/10.5194/gmd-15-2085-2022, https://doi.org/10.5194/gmd-15-2085-2022, 2022
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We introduce the first chain of computationally efficient Earth system model (ESM) emulators to translate user-defined greenhouse gas emission pathways into regional temperature change time series accounting for all major sources of climate change projection uncertainty. By combining the global mean emulator MAGICC with the spatially resolved emulator MESMER, we can derive ESM-specific and constrained probabilistic emulations to rapidly provide targeted climate information at the local scale.
Junichi Tsutsui
Geosci. Model Dev., 15, 951–970, https://doi.org/10.5194/gmd-15-951-2022, https://doi.org/10.5194/gmd-15-951-2022, 2022
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A new simple climate model, MCE, was developed. It can emulate the basic behavior of comprehensive climate models in a minimal way with sufficient accuracy, providing a reasonable way to assess climate change mitigation scenarios in terms of consistency with long-term temperature goals. The model's simple structure is suitable for building probability distributions of key model parameters such that they reflect uncertainty ranges of multiple climate projections and observed warming trends.
Geert Jan van Oldenborgh, Folmer Krikken, Sophie Lewis, Nicholas J. Leach, Flavio Lehner, Kate R. Saunders, Michiel van Weele, Karsten Haustein, Sihan Li, David Wallom, Sarah Sparrow, Julie Arrighi, Roop K. Singh, Maarten K. van Aalst, Sjoukje Y. Philip, Robert Vautard, and Friederike E. L. Otto
Nat. Hazards Earth Syst. Sci., 21, 941–960, https://doi.org/10.5194/nhess-21-941-2021, https://doi.org/10.5194/nhess-21-941-2021, 2021
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Southeastern Australia suffered from disastrous bushfires during the 2019/20 fire season, raising the question whether these have become more likely due to climate change. We found no attributable trend in extreme annual or monthly low precipitation but a clear shift towards more extreme heat. However, this shift is underestimated by the models. Analysing fire weather directly, we found that the chance has increased by at least 30 %, but due to the underestimation it could well be higher.
Claudia Tebaldi, Kevin Debeire, Veronika Eyring, Erich Fischer, John Fyfe, Pierre Friedlingstein, Reto Knutti, Jason Lowe, Brian O'Neill, Benjamin Sanderson, Detlef van Vuuren, Keywan Riahi, Malte Meinshausen, Zebedee Nicholls, Katarzyna B. Tokarska, George Hurtt, Elmar Kriegler, Jean-Francois Lamarque, Gerald Meehl, Richard Moss, Susanne E. Bauer, Olivier Boucher, Victor Brovkin, Young-Hwa Byun, Martin Dix, Silvio Gualdi, Huan Guo, Jasmin G. John, Slava Kharin, YoungHo Kim, Tsuyoshi Koshiro, Libin Ma, Dirk Olivié, Swapna Panickal, Fangli Qiao, Xinyao Rong, Nan Rosenbloom, Martin Schupfner, Roland Séférian, Alistair Sellar, Tido Semmler, Xiaoying Shi, Zhenya Song, Christian Steger, Ronald Stouffer, Neil Swart, Kaoru Tachiiri, Qi Tang, Hiroaki Tatebe, Aurore Voldoire, Evgeny Volodin, Klaus Wyser, Xiaoge Xin, Shuting Yang, Yongqiang Yu, and Tilo Ziehn
Earth Syst. Dynam., 12, 253–293, https://doi.org/10.5194/esd-12-253-2021, https://doi.org/10.5194/esd-12-253-2021, 2021
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We present an overview of CMIP6 ScenarioMIP outcomes from up to 38 participating ESMs according to the new SSP-based scenarios. Average temperature and precipitation projections according to a wide range of forcings, spanning a wider range than the CMIP5 projections, are documented as global averages and geographic patterns. Times of crossing various warming levels are computed, together with benefits of mitigation for selected pairs of scenarios. Comparisons with CMIP5 are also discussed.
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.
Robin D. Lamboll, Zebedee R. J. Nicholls, Jarmo S. Kikstra, Malte Meinshausen, and Joeri Rogelj
Geosci. Model Dev., 13, 5259–5275, https://doi.org/10.5194/gmd-13-5259-2020, https://doi.org/10.5194/gmd-13-5259-2020, 2020
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Many models project how human activity can lead to more or less climate change, but most of these models do not project all climate-relevant emissions, potentially biasing climate projections. This paper outlines a Python package called Silicone, which can add missing emissions in a flexible yet high-throughput manner. It does this
infillingbased on more complete literature projections. It facilitates a more complete understanding of the climate impact of alternative emission pathways.
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.
Christopher J. Smith, Ryan J. Kramer, and Adriana Sima
Earth Syst. Sci. Data, 12, 2157–2168, https://doi.org/10.5194/essd-12-2157-2020, https://doi.org/10.5194/essd-12-2157-2020, 2020
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Radiative kernels allow efficient diagnosis of climate feedbacks and radiative adjustments to an external forcing using standard climate model output. We present a radiative kernel derived from the UK Met Office's HadGEM3-GA7.1 climate model. We show that a highly resolved stratosphere is important for correctly diagnosing the stratospheric temperature adjustment to greenhouse gas forcings and, by extension, the instantaneous radiative forcing.
Cited articles
Alexander, K. and Easterbrook, S. M.: The software architecture of climate models: a graphical comparison of CMIP5 and EMICAR5 configurations, Geosci. Model Dev., 8, 1221–1232, https://doi.org/10.5194/gmd-8-1221-2015, 2015. a
Allen, M. R., Frame, D. J., Huntingford, C., Jones, C. D., Lowe, J. A., Meinshausen, M., and Meinshausen, N.: Warming caused by cumulative carbon emissions towards the trillionth tonne, Nature, 458, 1163–1166, https://doi.org/10.1038/nature08019, 2009. a, b
Allen, M. R., Shine, K. P., Fuglestvedt, J. S., Millar, R. J., Cain, M., Frame, D. J., and Macey, A. H.: A solution to the misrepresentations of CO2-equivalent emissions of short-lived climate pollutants under ambitious mitigation, npj Climate and Atmospheric Science, 1, 16, https://doi.org/10.1038/s41612-018-0026-8, 2018. a
Arora, V. K., Katavouta, A., Williams, R. G., Jones, C. D., Brovkin, V., Friedlingstein, P., Schwinger, J., Bopp, L., Boucher, O., Cadule, P., Chamberlain, M. A., Christian, J. R., Delire, C., Fisher, R. A., Hajima, T., Ilyina, T., Joetzjer, E., Kawamiya, M., Koven, C. D., Krasting, J. P., Law, R. M., Lawrence, D. M., Lenton, A., Lindsay, K., Pongratz, J., Raddatz, T., Séférian, R., Tachiiri, K., Tjiputra, J. F., Wiltshire, A., Wu, T., and Ziehn, T.: Carbon–concentration and carbon–climate feedbacks in CMIP6 models and their comparison to CMIP5 models, Biogeosciences, 17, 4173–4222, https://doi.org/10.5194/bg-17-4173-2020, 2020. a, b, c
Bellouin, N., Quaas, J., Gryspeerdt, E., Kinne, S., Stier, P., Watson-Parris, D., Boucher, O., Carslaw, K. S., Christensen, M., Daniau, A. L., Dufresne, J. L., Feingold, G., Fiedler, S., Forster, P., Gettelman, A., Haywood, J. M., Lohmann, U., Malavelle, F., Mauritsen, T., McCoy, D. T., Myhre, G., Mülmenstädt, J., Neubauer, D., Possner, A., Rugenstein, M., Sato, Y., Schulz, M., Schwartz, S. E., Sourdeval, O., Storelvmo, T., Toll, V., Winker, D., and Stevens, B.: Bounding Global Aerosol Radiative Forcing of Climate Change, Tech. Rep., 1, https://doi.org/10.1029/2019RG000660, 2020. a, b
Bodman, R. W. and Jones, R. N.: Bayesian estimation of climate sensitivity using observationally constrained simple climate models, WIRes. Clim. Change, 7, 461–473, https://doi.org/10.1002/wcc.397, 2016. a
Bond, T. C., Doherty, S. J., Fahey, D. W., Forster, P. M., Berntsen, T., Deangelo, B. J., Flanner, M. G., Ghan, S., Kärcher, B., Koch, D., Kinne, S., Kondo, Y., Quinn, P. K., Sarofim, M. C., Schultz, M. G., Schulz, M., Venkataraman, C., Zhang, H., Zhang, S., Bellouin, N., Guttikunda, S. K., Hopke, P. K., Jacobson, M. Z., Kaiser, J. W., Klimont, Z., Lohmann, U., Schwarz, J. P., Shindell, D., Storelvmo, T., Warren, S. G., and Zender, C. S.: Bounding the role of black carbon in the climate system: A scientific assessment, J. Geophys. Res.-Atmos., 118, 5380–5552, https://doi.org/10.1002/jgrd.50171, 2013. a
Brunner, L., Pendergrass, A. G., Lehner, F., Merrifield, A. L., Lorenz, R., and Knutti, R.: Reduced global warming from CMIP6 projections when weighting models by performance and independence, Earth Syst. Dynam., 11, 995–1012, https://doi.org/10.5194/esd-11-995-2020, 2020. a, b, c
Burkholder, J. B., Hodnebrog, Ø., and Orkin, V. L.: Appendix A: Summary of Abundances, Lifetimes, ODPs, REs, GWPs, and GTPs, Scientific Assessment of Ozone Depletion: 2018, Global Ozone Research and Monitoring Project – Report no. 58, World Meteorological Organization, Geneva, Switzerland, 2018. a, b, c
Butchart, N. and Scaife, A. A.: Removal of chlorofluorocarbons by increased mass exchange between the stratosphere and troposphere in a changing climate, Nature, 410, 799–802, https://doi.org/10.1038/35071047, 2001. a
Cain, M., Lynch, J., Allen, M. R., Fuglestvedt, J. S., Frame, D. J., and Macey, A. H.: Improved calculation of warming-equivalent emissions for short-lived climate pollutants, npj Climate and Atmospheric Science, 2, 29, https://doi.org/10.1038/s41612-019-0086-4, 2019. a
Cinquini, L., Crichton, D., Mattmann, C., Harney, J., Shipman, G., Wang, F., Ananthakrishnan, R., Miller, N., Denvil, S., Morgan, M., Pobre, Z., Bell, G. M., Doutriaux, C., Drach, R., Williams, D., Kershaw, P., Pascoe, S., Gonzalez, E., Fiore, S., and Schweitzer, R.: The Earth System Grid Federation: An open infrastructure for access to distributed geospatial data, Future Gener. Comp. Sy., 36, 400–417, https://doi.org/10.1016/j.future.2013.07.002, 2014. a
Collins, M., Knutti, R., Arblaster, J., Dufresne, J.-L., Fichefet, T., Friedlingstein, P., Gao, X., Gutowski, W. J., Johns, T., Krinner, G., Shongwe, M., Tebaldi, C., Weaver, A. J., and Wehner, M.: Long-term Climate Change: Projections, Commitments and Irreversibility, in: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., chap. 12, 1029–1136, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, https://doi.org/10.1017/CBO9781107415324.024, 2013. a, b
Cowtan, K. and Way, R. G.: Coverage bias in the HadCRUT4 temperature series and its impact on recent temperature trends, Q. J. Roy. Meteor. Soc., 140, 1935–1944, https://doi.org/10.1002/qj.2297, 2014. a, b, c, d
Cummins, D. P., Stephenson, D. B., and Stott, P. A.: Optimal estimation of stochastic energy balance model parameters, J. Climate, 33, 7909–7926, https://doi.org/10.1175/JCLI-D-19-0589.1, 2020. a, b, c, d
Engel, A., Rigby, M., Burkholder, J., Fernandez, R., Froidevaux, L., Hall, B., Hossaini, R., Saito, T., Vollmer, M., and Yao, B.: Update on Ozone-Depleting Substances (ODSs) and Other Gases of Interest to the Montreal Protocol, Chapter 1 in Scientific Assessment of Ozone Depletion: 2018, Global Ozone Research and Monitoring Project – Report no. 58, World Meteorological Organization, Geneva, Switzerland, 2018. a
Etminan, M., Myhre, G., Highwood, E. J., and Shine, K. P.: Radiative forcing of carbon dioxide, methane, and nitrous oxide: A significant revision of the methane radiative forcing, Geophys. Res. Lett., 43, 12614–12623, https://doi.org/10.1002/2016GL071930, 2016. a, b, c
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., and Taylor, K. E.: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization, Geosci. Model Dev., 9, 1937–1958, https://doi.org/10.5194/gmd-9-1937-2016, 2016. a, b, c, d
Forest, C. E., Stone, P. H., Sokolov, A. P., Allen, M. R., and Webster, M. D.: Quantifying uncertainties in climate system properties with the use of recent climate observations, Science, 295, 113–117, https://doi.org/10.1126/science.1064419, 2002. a
Friedlingstein, P., Jones, M. W., O'Sullivan, M., Andrew, R. M., Hauck, J., Peters, G. P., Peters, W., Pongratz, J., Sitch, S., Le Quéré, C., Bakker, D. C. E., Canadell, J. G., Ciais, P., Jackson, R. B., Anthoni, P., Barbero, L., Bastos, A., Bastrikov, V., Becker, M., Bopp, L., Buitenhuis, E., Chandra, N., Chevallier, F., Chini, L. P., Currie, K. I., Feely, R. A., Gehlen, M., Gilfillan, D., Gkritzalis, T., Goll, D. S., Gruber, N., Gutekunst, S., Harris, I., Haverd, V., Houghton, R. A., Hurtt, G., Ilyina, T., Jain, A. K., Joetzjer, E., Kaplan, J. O., Kato, E., Klein Goldewijk, K., Korsbakken, J. I., Landschützer, P., Lauvset, S. K., Lefèvre, N., Lenton, A., Lienert, S., Lombardozzi, D., Marland, G., McGuire, P. C., Melton, J. R., Metzl, N., Munro, D. R., Nabel, J. E. M. S., Nakaoka, S.-I., Neill, C., Omar, A. M., Ono, T., Peregon, A., Pierrot, D., Poulter, B., Rehder, G., Resplandy, L., Robertson, E., Rödenbeck, C., Séférian, R., Schwinger, J., Smith, N., Tans, P. P., Tian, H., Tilbrook, B., Tubiello, F. N., van der Werf, G. R., Wiltshire, A. J., and Zaehle, S.: Global Carbon Budget 2019, Earth Syst. Sci. Data, 11, 1783–1838, https://doi.org/10.5194/essd-11-1783-2019, 2019. a
Friedlingstein, P., O'Sullivan, M., Jones, M. W., Andrew, R. M., Hauck, J., Olsen, A., Peters, G. P., Peters, W., Pongratz, J., Sitch, S., Le Quéré, C., Canadell, J. G., Ciais, P., Jackson, R. B., Alin, S., Aragão, L. E. O. C., Arneth, A., Arora, V., Bates, N. R., Becker, M., Benoit-Cattin, A., Bittig, H. C., Bopp, L., Bultan, S., Chandra, N., Chevallier, F., Chini, L. P., Evans, W., Florentie, L., Forster, P. M., Gasser, T., Gehlen, M., Gilfillan, D., Gkritzalis, T., Gregor, L., Gruber, N., Harris, I., Hartung, K., Haverd, V., Houghton, R. A., Ilyina, T., Jain, A. K., Joetzjer, E., Kadono, K., Kato, E., Kitidis, V., Korsbakken, J. I., Landschützer, P., Lefèvre, N., Lenton, A., Lienert, S., Liu, Z., Lombardozzi, D., Marland, G., Metzl, N., Munro, D. R., Nabel, J. E. M. S., Nakaoka, S.-I., Niwa, Y., O'Brien, K., Ono, T., Palmer, P. I., Pierrot, D., Poulter, B., Resplandy, L., Robertson, E., Rödenbeck, C., Schwinger, J., Séférian, R., Skjelvan, I., Smith, A. J. P., Sutton, A. J., Tanhua, T., Tans, P. P., Tian, H., Tilbrook, B., van der Werf, G., Vuichard, N., Walker, A. P., Wanninkhof, R., Watson, A. J., Willis, D., Wiltshire, A. J., Yuan, W., Yue, X., and Zaehle, S.: Global Carbon Budget 2020, Earth Syst. Sci. Data, 12, 3269–3340, https://doi.org/10.5194/essd-12-3269-2020, 2020. a, b
Geoffroy, O., Saint-Martin, D., Olivié, D. J. L., Voldoire, A., Bellon, G., Tytéca, S., Geoffroy, O., Saint-Martin, D., Olivié, D. J. L., Voldoire, A., Bellon, G., and Tytéca, S.: Transient Climate Response in a Two-Layer Energy-Balance Model. Part I: Analytical Solution and Parameter Calibration Using CMIP5 AOGCM Experiments, J. Climate, 26, 1841–1857, https://doi.org/10.1175/JCLI-D-12-00195.1, 2013. a, b
Gillett, N. P., Arora, V. K., Matthews, D., Allen, M. R., Gillett, N. P., Arora, V. K., Matthews, D., and Allen, M. R.: Constraining the Ratio of Global Warming to Cumulative CO2 Emissions Using CMIP5 Simulations*, J. Climate, 26, 6844–6858, https://doi.org/10.1175/JCLI-D-12-00476.1, https://doi.org/10.1175/JCLI-D-12-00476.1, 2013. a
Gillett, N. P., Kirchmeier-Young, M., Ribes, A., Shiogama, H., Hegerl, G. C., Knutti, R., Gastineau, G., John, J. G., Li, L., Nazarenko, L., Rosenbloom, N., Seland, Ø., Wu, T., Yukimoto, S., and Ziehn, T.: Constraining human contributions to observed warming since the pre-industrial period, Nat. Clim. Change, 11, 207–212, https://doi.org/10.1038/s41558-020-00965-9, 2021. a
Goodwin, P., Williams, R. G., Roussenov, V. M., and Katavouta, A.: Climate Sensitivity From Both Physical and Carbon Cycle Feedbacks, Geophys. Res. Lett., 46, 7554–7564, https://doi.org/10.1029/2019GL082887, 2019. a
Gregory, J. M., Ingram, W. J., Palmer, M. A., Jones, G. S., Stott, P. A., Thorpe, R. B., Lowe, J. A., Johns, T. C., and Williams, K. D.: A new method for diagnosing radiative forcing and climate sensitivity, Geophys. Res. Lett., 31, 3, https://doi.org/10.1029/2003GL018747, 2004. a
Haustein, K., Allen, M. R., Forster, P. M., Otto, F. E. L., Mitchell, D. M., Matthews, H. D., and Frame, D. J.: A real-time Global Warming Index, Sci. Rep., 7, 15417, https://doi.org/10.1038/s41598-017-14828-5, 2017. a
Held, I. M., Winton, M., Takahashi, K., Delworth, T., Zeng, F., Vallis, G. K., Held, I. M., Winton, M., Takahashi, K., Delworth, T., Zeng, F., and Vallis, G. K.: Probing the Fast and Slow Components of Global Warming by Returning Abruptly to Preindustrial Forcing, J. Climate, 23, 2418–2427, https://doi.org/10.1175/2009JCLI3466.1, 2010. a
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J. N.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020. a
Hooss, G., Voss, R., Hasselmann, K., Maier-Reimer, E., and Joos, F.: A nonlinear impulse response model of the coupled carbon cycle-climate system (NICCS), Clim. Dynam., 18, 189–202, https://doi.org/10.1007/s003820100170, 2001. a
Huppmann, D., Kriegler, E., Krey, V., Riahi, K., Rogelj, J., Rose, S. K., Weyant, J., Bauer, N., Bertram, C., Bosetti, V., Calvin, K., Doelman, J., Drouet, L., Emmerling, J., Frank, S., Fujimori, S., Gernaat, D., Grubler, A., Guivarch, C., Haigh, M., Holz, C., Iyer, G., Kato, E., Keramidas, K., Kitous, A., Leblanc, F., Liu, J.-Y., Löffler, K., Luderer, G., Marcucci, A., McCollum, D., Mima, S., Popp, A., Sands, R. D., Sano, F., Strefler, J., Tsutsui, J., Van Vuuren, D., Vrontisi, Z., Wise, M., and Zhang, R.: IAMC 1.5 ∘C Scenario Explorer and Data hosted by IIASA, Integrated Assessment Modeling Consortium & International Institute for Applied Systems Analysis, https://doi.org/10.22022/SR15/08-2018.15429, 2018. a
IPCC: Global Warming of 1.5 ∘C. An IPCC Special Report on the impacts of global warming of 1.5 ∘C above pre-industrial levels
and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate
change, sustainable development, and efforts to eradicate poverty, edited by: Masson-Delmotte, V., Zhai, P., Pörtner, H.-O., Roberts, D., Skea, J., Shukla,
P. R., Pirani, A., Moufouma-Okia, W., Péan, C., Pidcock, R., Connors, S., Matthews, J. B. R., Chen, Y., Zhou, X., Gomis, M. I., Lonnoy, E., Maycock,
T., Tignor, M., and Waterfield, T., in press, 2018. a, b, c
IPCC, Prather, M., Flato, G., Friedlingstein, P., Jones, C., Lamarque, J.-F., Liao, H., and Rasch, P.: Annex II: Climate System Scenario Tables , in: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., chap. AII, 1395–1446, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, https://doi.org/10.1017/CBO9781107415324.030, 2013. a
Jenkins, S., Millar, R. J., Leach, N., and Allen, M. R.: Framing Climate Goals in Terms of Cumulative CO2-Forcing-Equivalent Emissions, Geophys. Res. Lett., 45, 2795– 2804, https://doi.org/10.1002/2017GL076173, 2018. a, b
Jiménez-de-la Cuesta, D. and Mauritsen, T.: Emergent constraints on Earth's transient and equilibrium response to doubled CO2 from post-1970s global warming, Nat. Geosci., 12, 902–905, https://doi.org/10.1038/s41561-019-0463-y, 2019. a, b, c
Jones, C. D., Arora, V., Friedlingstein, P., Bopp, L., Brovkin, V., Dunne, J., Graven, H., Hoffman, F., Ilyina, T., John, J. G., Jung, M., Kawamiya, M., Koven, C., Pongratz, J., Raddatz, T., Randerson, J. T., and Zaehle, S.: C4MIP – The Coupled Climate–Carbon Cycle Model Intercomparison Project: experimental protocol for CMIP6, Geosci. Model Dev., 9, 2853–2880, https://doi.org/10.5194/gmd-9-2853-2016, 2016. a
Joos, F., Bruno, M., Fink, R., Siegenthaler, U., Stocker, T. F., Le Quéré, C., and Sarmiento, J. L.: An efficient and accurate representation of complex oceanic and biospheric models of anthropogenic carbon uptake, Tellus B, 48, 397–417, https://doi.org/10.1034/j.1600-0889.1996.t01-2-00006.x, 1996. a
Joos, F., Roth, R., Fuglestvedt, J. S., Peters, G. P., Enting, I. G., von Bloh, W., Brovkin, V., Burke, E. J., Eby, M., Edwards, N. R., Friedrich, T., Frölicher, T. L., Halloran, P. R., Holden, P. B., Jones, C., Kleinen, T., Mackenzie, F. T., Matsumoto, K., Meinshausen, M., Plattner, G.-K., Reisinger, A., Segschneider, J., Shaffer, G., Steinacher, M., Strassmann, K., Tanaka, K., Timmermann, A., and Weaver, A. J.: Carbon dioxide and climate impulse response functions for the computation of greenhouse gas metrics: a multi-model analysis, Atmos. Chem. Phys., 13, 2793–2825, https://doi.org/10.5194/acp-13-2793-2013, 2013. a, b, c, d, e, f, g, h
Kristiansen, N. I., Stohl, A., Olivié, D. J. L., Croft, B., Søvde, O. A., Klein, H., Christoudias, T., Kunkel, D., Leadbetter, S. J., Lee, Y. H., Zhang, K., Tsigaridis, K., Bergman, T., Evangeliou, N., Wang, H., Ma, P.-L., Easter, R. C., Rasch, P. J., Liu, X., Pitari, G., Di Genova, G., Zhao, S. Y., Balkanski, Y., Bauer, S. E., Faluvegi, G. S., Kokkola, H., Martin, R. V., Pierce, J. R., Schulz, M., Shindell, D., Tost, H., and Zhang, H.: Evaluation of observed and modelled aerosol lifetimes using radioactive tracers of opportunity and an ensemble of 19 global models, Atmos. Chem. Phys., 16, 3525–3561, https://doi.org/10.5194/acp-16-3525-2016, 2016. a
Lashof, D. A. and Ahuja, D. R.: Relative contributions of greenhouse gas emissions to global warming, Nature, 344, 529–531, https://doi.org/10.1038/344529a0, 1990. a
Leach, N., and Smith, C.: FaIRv2.0.0 notebooks (Version 1.0.0), Zenodo, https://doi.org/10.5281/zenodo.4683388, 2021. a
Leach, N. J., Millar, R. J., Haustein, K., Jenkins, S., Graham, E., and Allen, M. R.: Current level and rate of warming determine emissions budgets under ambitious mitigation, Nat. Geosci., 11, 574–579, https://doi.org/10.1038/s41561-018-0156-y, 2018. a, b
Leach, N., Smith, C., Nicholls, Z., Jenkins, S., Millar, R., and Allen, M.: FaIRv2.0.0-alpha (Version 2.0.0-alpha), Zenodo [Data set], https://doi.org/10.5281/zenodo.4683173, 2021a. a
Leach, N., Smith, C., Nicholls, Z., Jenkins, S., Millar, R., and Allen, M.: FaIRv2.0.0-alpha (Version 2.0.0-alpha1), https://doi.org/10.5281/zenodo.4774994, 2021b. a
Lee, D., Fahey, D., Skowron, A., Allen, M., Burkhardt, U., Chen, Q., Doherty, S., Freeman, S., Forster, P., Fuglestvedt, J., Gettelman, A., De León, R., Lim, L., Lund, M., Millar, R., Owen, B., Penner, J., Pitari, G., Prather, M., Sausen, R., and Wilcox, L.: The contribution of global aviation to anthropogenic climate forcing for 2000 to 2018, Atmos. Environ., 244, 117 834, https://doi.org/10.1016/j.atmosenv.2020.117834, 2021. a
Lenssen, N. J. L., Schmidt, G. A., Hansen, J. E., Menne, M. J., Persin, A., Ruedy, R., and Zyss, D.: Improvements in the uncertainty model in the Goddard Institute for Space Studies Surface Temperature (GISTEMP) analysis, J. Geophys. Res.-Atmos., 124, 6307–6326, https://doi.org/10.1029/2018JD029522, 2019. a, b
MacDougall, A. H.: The Transient Response to Cumulative CO2 Emissions: a Review, J. Geophys. Res.-Atmos., 124, 6307–6326, https://doi.org/10.1007/s40641-015-0030-6, 2016. a
Marvel, K., Schmidt, G. A., Miller, R. L., and Nazarenko, L. S.: Implications for climate sensitivity from the response to individual forcings, Nat. Clim. Change, 6, 386–389, https://doi.org/10.1038/nclimate2888, 2016. a
Matthews, H. D., Gillett, N. P., Stott, P. A., and Zickfeld, K.: The proportionality of global warming to cumulative carbon emissions, Nature, 459, 829–832, https://doi.org/10.1038/nature08047, 2009. a
Meinshausen, M., Meinshausen, N., Hare, W., Raper, S. C. B., Frieler, K., Knutti, R., Frame, D. J., and Allen, M. R.: Greenhouse-gas emission targets for limiting global warming to 2 ∘C, Nature, 458, 1158–1162, https://doi.org/10.1038/nature08017, 2009. a
Meinshausen, M., Raper, S. C. B., and Wigley, T. M. L.: Emulating coupled atmosphere-ocean and carbon cycle models with a simpler model, MAGICC6 – Part 1: Model description and calibration, Atmos. Chem. Phys., 11, 1417–1456, https://doi.org/10.5194/acp-11-1417-2011, 2011a. a, b, c, d, e, f, g, h, i, j, k, l
Meinshausen, M., Vogel, E., Nauels, A., Lorbacher, K., Meinshausen, N., Etheridge, D. M., Fraser, P. J., Montzka, S. A., Rayner, P. J., Trudinger, C. M., Krummel, P. B., Beyerle, U., Canadell, J. G., Daniel, J. S., Enting, I. G., Law, R. M., Lunder, C. R., O'Doherty, S., Prinn, R. G., Reimann, S., Rubino, M., Velders, G. J. M., Vollmer, M. K., Wang, R. H. J., and Weiss, R.: Historical greenhouse gas concentrations for climate modelling (CMIP6), Geosci. Model Dev., 10, 2057–2116, https://doi.org/10.5194/gmd-10-2057-2017, 2017. a, b, c, d, e
Meinshausen, M., Nicholls, Z. R. J., Lewis, J., Gidden, M. J., Vogel, E., Freund, M., Beyerle, U., Gessner, C., Nauels, A., Bauer, N., Canadell, J. G., Daniel, J. S., John, A., Krummel, P. B., Luderer, G., Meinshausen, N., Montzka, S. A., Rayner, P. J., Reimann, S., Smith, S. J., van den Berg, M., Velders, G. J. M., Vollmer, M. K., and Wang, R. H. J.: The shared socio-economic pathway (SSP) greenhouse gas concentrations and their extensions to 2500, Geosci. Model Dev., 13, 3571–3605, https://doi.org/10.5194/gmd-13-3571-2020, 2020. a, b, c, d
Millar, R. J. and Friedlingstein, P.: The utility of the historical record for assessing the transient climate response to cumulative emissions, Philos. T. R. Soc. S-A, 376, 20160449, https://doi.org/10.1098/rsta.2016.0449, 2018. a
Millar, R. J., Otto, A., Forster, P. M., Lowe, J. A., Ingram, W. J., and Allen, M. R.: Model structure in observational constraints on transient climate response, Clim. Change, 131, 199–211, https://doi.org/10.1007/s10584-015-1384-4, 2015. a, b
Millar, R. J., Nicholls, Z. R., Friedlingstein, P., and Allen, M. R.: A modified impulse-response representation of the global near-surface air temperature and atmospheric concentration response to carbon dioxide emissions, Atmos. Chem. Phys., 17, 7213–7228, https://doi.org/10.5194/acp-17-7213-2017, 2017. a, b, c, d, e, f, g, h, i, j, k, l, m
Morice, C. P., Kennedy, J. J., Rayner, N. A., and Jones, P. D.: Quantifying uncertainties in global and regional temperature change using an ensemble of observational estimates: The HadCRUT4 data set, J. Geophys. Res., 117, D08101, https://doi.org/10.1029/2011JD017187, 2012. a, b
Morice, C. P., Kennedy, J. J., Rayner, N. A., Winn, J. P., Hogan, E., Killick, R. E., Dunn, R. J. H., Osborn, T. J., Jones, P. D., and Simpson, I. R.: An updated assessment of near-surface temperature change from 1850: the HadCRUT5 dataset, J. Geophys. Res.-Atmos., 126, 3, https://doi.org/10.1029/2019JD032361, 2020. a, b
Myhre, G., Shindell, D., Bréon, F.-M., Collins, W., Fuglestvedt, J., Huang, J., Koch, D., Lamarque, J.-F., Lee, D., Mendoza, B., Nakajima, T., Robock, A., Stephens, G., Takemura, T., and Zhang, H.: Anthropogenic and Natural Radiative Forcing, in: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., chap. 8, 659–740, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, https://doi.org/10.1017/CBO9781107415324.018, 2013. a, b, c, d, e, f
Nelder, J. A. and Mead, R.: A Simplex Method for Function Minimization, Comput. J., 7, 308–313, https://doi.org/10.1093/comjnl/7.4.308, 1965. a
Newman, P. A., Daniel, J. S., Waugh, D. W., and Nash, E. R.: A new formulation of equivalent effective stratospheric chlorine (EESC), Atmos. Chem. Phys., 7, 4537–4552, https://doi.org/10.5194/acp-7-4537-2007, 2007. a
Nicholls, Z. R. J., Meinshausen, M., Lewis, J., Gieseke, R., Dommenget, D., Dorheim, K., Fan, C.-S., Fuglestvedt, J. S., Gasser, T., Golüke, U., Goodwin, P., Hartin, C., Hope, A. P., Kriegler, E., Leach, N. J., Marchegiani, D., McBride, L. A., Quilcaille, Y., Rogelj, J., Salawitch, R. J., Samset, B. H., Sandstad, M., Shiklomanov, A. N., Skeie, R. B., Smith, C. J., Smith, S., Tanaka, K., Tsutsui, J., and Xie, Z.: Reduced Complexity Model Intercomparison Project Phase 1: introduction and evaluation of global-mean temperature response, Geosci. Model Dev., 13, 5175–5190, https://doi.org/10.5194/gmd-13-5175-2020, 2020a. a, b, c, d, e, f, g, h, i, j, k
Nicholls, Z. R. J., Meinshausen, M. A., Lewis, J., Rojas Corradi, M., Dorheim, K., Gasser, T., Gieseke, R., Hope, A. P., Leach, N., McBride, L. A., Quilcaille, Y., Rogelj, J., Salawitch, R. J., Samset, B. H., Sandstad, M., Shiklomanov, A., Skeie, R. B., Smith, C. J., Smith, S. J., Su, X., Tsutsui, J., Vega-Westhoff, B., and Woodard, D. L.: Reduced Complexity Model Intercomparison Project Phase 2: Synthesising Earth system knowledge for probabilistic climate projections, Earth and Space Science Open Archive, 29, e2020EF001900, https://doi.org/10.1002/ESSOAR.10504793.1, 2020b. a, b
Nicholls, Z., Lewis, J., Makin, M., Nattala, U., Zhang, G. Z., Mutch, S. J., Tescari, E., and Meinshausen, M.: Regionally aggregated, stitched and de-drifted CMIP-climate data, processed with netCDF-SCM v2.0.0, Geosci. Data J., gdj3.113, https://doi.org/10.1002/gdj3.113, 2021. a, b
Nijsse, F. J. M. M., Cox, P. M., and Williamson, M. S.: Emergent constraints on transient climate response (TCR) and equilibrium climate sensitivity (ECS) from historical warming in CMIP5 and CMIP6 models, Earth Syst. Dynam., 11, 737–750, https://doi.org/10.5194/esd-11-737-2020, 2020. a, b
Prather, M. J., Holmes, C. D., and Hsu, J.: Reactive greenhouse gas scenarios: Systematic exploration of uncertainties and the role of atmospheric chemistry, Geophys. Res. Lett., 39, 9, https://doi.org/10.1029/2012GL051440, 2012. a
Prather, M. J., Hsu, J., DeLuca, N. M., Jackman, C. H., Oman, L. D., Douglass, A. R., Fleming, E. L., Strahan, S. E., Steenrod, S. D., Søvde, O. A., Isaksen, I. S. A., Froidevaux, L., and Funke, B.: Measuring and modeling the lifetime of nitrous oxide including its variability, J. Geophys. Res.-Atmos., 120, 5693–5705, https://doi.org/10.1002/2015JD023267, 2015. a, b
Ramaswamy, V., Boucher, O., Haigh, J., Hauglustaine, D., Haywood, J., Myhre, G., Nakajima, T., Shi, G., and Solomon, S.: Radiative Forcing of Climate Change, in: Climate Change 2001: The Scientific Basis. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Houghton, J. T., Ding, Y., Griggs, D., Noguer, M., van der Linden, P., Dai, X., Maskell, K., and Johnson, C., chap. 6, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 881 pp., 2001. a
Riahi, K., Rao, S., Krey, V., Cho, C., Chirkov, V., Fischer, G., Kindermann, G., Nakicenovic, N., and Rafaj, P.: RCP 8.5–A scenario of comparatively high greenhouse gas emissions, Clim. Change, 109, 33–57, https://doi.org/10.1007/s10584-011-0149-y, 2011. a
Riahi, K., van Vuuren, D. P., Kriegler, E., Edmonds, J., O'Neill, B. C., Fujimori, S., Bauer, N., Calvin, K., Dellink, R., Fricko, O., Lutz, W., Popp, A., Cuaresma, J. C., KC, S., Leimbach, M., Jiang, L., Kram, T., Rao, S., Emmerling, J., Ebi, K., Hasegawa, T., Havlik, P., Humpenöder, F., Da Silva, L. A., Smith, S., Stehfest, E., Bosetti, V., Eom, J., Gernaat, D., Masui, T., Rogelj, J., Strefler, J., Drouet, L., Krey, V., Luderer, G., Harmsen, M., Takahashi, K., Baumstark, L., Doelman, J. C., Kainuma, M., Klimont, Z., Marangoni, G., Lotze-Campen, H., Obersteiner, M., Tabeau, A., and Tavoni, M.: The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: An overview, Sci. Tech., 42, 153–168, https://doi.org/10.1016/J.GLOENVCHA.2016.05.009, 2017. a, b, c
Richardson, M., Cowtan, K., Hawkins, E., and Stolpe, M. B.: Reconciled climate response estimates from climate models and the energy budget of Earth, Nat. Clim. Change, 6, 931–935, https://doi.org/10.1038/nclimate3066, 2016. a
Richardson, M., Cowtan, K., and Millar, R. J.: Global temperature definition affects achievement of long-term climate goals, Environ. Res. Lett., 13, 54 004, https://doi.org/10.1088/1748-9326/aab305, 2018. a, b
Rohde, R., Muller, R. A., Jacobsen, R., Muller, E., Perlmutter, S., Rosenfeld, A., Wurtele, J., Groom, D., and Wickham, C.: A New Estimate of the Average Earth Surface Land Temperature Spanning 1753 to 2011, Geoinformatics & Geostatistics: An Overview, 1, 1, https://doi.org/10.4172/2327-4581.1000101, 2013. a, b
Sanderson, B.: Relating climate sensitivity indices to projection uncertainty, Earth Syst. Dynam., 11, 721–735, https://doi.org/10.5194/esd-11-721-2020, 2020. a, b
Sherwood, S., Webb, M. J., Annan, J. D., Armour, K. C., Forster, P. M., Hargreaves, J. C., Hegerl, G., Klein, S. A., Marvel, K. D., Rohling, E. J., Watanabe, M., Andrews, T., Braconnot, P., Bretherton, C. S., Foster, G. L., Hausfather, Z., von der Heydt, A. S., Knutti, R., Mauritsen, T., Norris, J. R., Proistosescu, C., Rugenstein, M., Schmidt, G. A., Tokarska, K. B., and Zelinka, M. D.: An assessment of Earth's climate sensitivity using multiple lines of evidence, Rev. Geophys., 58, e2019RG000678, https://doi.org/10.1029/2019rg000678, 2020. a, b, c
Skeie, R. B., Myhre, G., Hodnebrog, Ø., Cameron-Smith, P. J., Deushi, M., Hegglin, M. I., Horowitz, L. W., Kramer, R. J., Michou, M., Mills, M. J., Olivié, D. J., Connor, F. M., Paynter, D., Samset, B. H., Sellar, A., Shindell, D., Takemura, T., Tilmes, S., and Wu, T.: Historical total ozone radiative forcing derived from CMIP6 simulations, npj Climate and Atmospheric Science, 3, 1–10, https://doi.org/10.1038/s41612-020-00131-0, 2020. a
Smith, C.: Effective Radiative Forcing Time Series from the Shared Socioeconomic Pathways, https://doi.org/10.5281/ZENODO.3973015, 2020. a, b
Smith, C. J., Forster, P. M., Allen, M., Leach, N., Millar, R. J., Passerello, G. A., and Regayre, L. A.: FAIR v1.3: a simple emissions-based impulse response and carbon cycle model, Geosci. Model Dev., 11, 2273–2297, https://doi.org/10.5194/gmd-11-2273-2018, 2018. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q, r, s, t, u
Smith, C. J., Harris, G., Palmer, M. D., Bellouin, N., Myhre, G., Schulz, M., Golaz, J.-C., Ringer, M., Storelvmo, T., and Forster, P. M.: Energy Budget Constraints on the Time History of Aerosol Forcing and Climate Sensitivity, J. Geophys. Res.-Atmos., https://doi.org/10.1002/essoar.10503977.2, 2020. a, b, c, d, e, f, g
Taylor, K. E., Stouffer, R. J., and Meehl, G. A.: An Overview of CMIP5 and the Experiment Design, B. Am. Meteorol. Soc., 93, 485–498, https://doi.org/10.1175/BAMS-D-11-00094.1, 2012. a
Thornhill, G. D., Collins, W. J., Kramer, R. J., Olivié, D., Skeie, R. B., O'Connor, F. M., Abraham, N. L., Checa-Garcia, R., Bauer, S. E., Deushi, M., Emmons, L. K., Forster, P. M., Horowitz, L. W., Johnson, B., Keeble, J., Lamarque, J.-F., Michou, M., Mills, M. J., Mulcahy, J. P., Myhre, G., Nabat, P., Naik, V., Oshima, N., Schulz, M., Smith, C. J., Takemura, T., Tilmes, S., Wu, T., Zeng, G., and Zhang, J.: Effective radiative forcing from emissions of reactive gases and aerosols – a multi-model comparison, Atmos. Chem. Phys., 21, 853–874, https://doi.org/10.5194/acp-21-853-2021, 2021. a
Tokarska, K. B., Schleussner, C.-F., Rogelj, J., Stolpe, M. B., Matthews, H. D., Pfleiderer, P., and Gillett, N. P.: Recommended temperature metrics for carbon budget estimates, model evaluation and climate policy, Nat. Geosci., 12, 964–971, https://doi.org/10.1038/s41561-019-0493-5, 2019. a
Trenberth, K. E. and Fasullo, J. T.: An apparent hiatus in global warming?, Earth's Future, 1, 19–32, https://doi.org/10.1002/2013ef000165, 2013. a
Tsutsui, J.: Diagnosing Transient Response to CO2 Forcing in Coupled Atmosphere-Ocean Model Experiments Using a Climate Model Emulator, Geophys. Res. Lett., 47, e2019GL085844, https://doi.org/10.1029/2019GL085844, 2020. a, b, c
Velders, G. J. M. and Daniel, J. S.: Uncertainty analysis of projections of ozone-depleting substances: mixing ratios, EESC, ODPs, and GWPs, Atmos. Chem. Phys., 14, 2757–2776, https://doi.org/10.5194/acp-14-2757-2014, 2014. a
Vose, R. S., Arndt, D., Banzon, V. F., Easterling, D. R., Gleason, B., Huang, B., Kearns, E., Lawrimore, J. H., Menne, M. J., Peterson, T. C., Reynolds, R. W., Smith, T. M., Williams, C. N., Wuertz, D. B., Vose, R. S., Arndt, D., Banzon, V. F., Easterling, D. R., Gleason, B., Huang, B., Kearns, E., Lawrimore, J. H., Menne, M. J., Peterson, T. C., Reynolds, R. W., Smith, T. M., Williams Jr., C. N., and Wuertz, D. B.: NOAA's Merged Land–Ocean Surface Temperature Analysis, B. Am. Meteorol. Soc., 93, 1677–1685, https://doi.org/10.1175/BAMS-D-11-00241.1, 2012.
a, b
Wilks, D. S.: Resampling hypothesis tests for autocorrelated fields, J. Climate, 10, 65–82, https://doi.org/10.1175/1520-0442(1997)010<0065:RHTFAF>2.0.CO;2, 1997. a
Zelinka, M. D., Andrews, T., Forster, P. M., and Taylor, K. E.: Quantifying components of aerosol-cloud-radiation interactions in climate models, J. Geophys. Res.-Atmos., 119, 7599–7615, https://doi.org/10.1002/2014JD021710, 2014. a, b
Zickfeld, K., MacDougall, A. H., and Matthews, H. D.: On the proportionality between global temperature change and cumulative CO2 emissions during periods of net negative CO2 emissions, Environ. Res. Lett., 11, 055 006, https://doi.org/10.1088/1748-9326/11/5/055006, 2016. a
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.
This paper presents an update of the FaIR simple climate model, which can estimate the impact of...
