Articles | Volume 15, issue 14
https://doi.org/10.5194/gmd-15-5905-2022
© Author(s) 2022. 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-15-5905-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The Earth system model CLIMBER-X v1.0 – Part 1: Climate model description and validation
Earth System Analysis, Potsdam Institute for Climate Impact Research, Potsdam, Germany
Andrey Ganopolski
Earth System Analysis, Potsdam Institute for Climate Impact Research, Potsdam, Germany
Alexander Robinson
Dept. of Earth Science and Astrophysics
Faculty of Physics, Complutense University of Madrid, Madrid, Spain
Instituto de Geosciencias CSIC-UCM, Madrid, Spain
Earth System Analysis, Potsdam Institute for Climate Impact Research, Potsdam, Germany
Climate and Global Dynamics Laboratory, National Center for Atmospheric Research, Boulder, CO 80305, USA
Neil R. Edwards
Environment, Earth and Ecosystems, The Open University, Walton Hall, Milton Keynes, MK7 6AA, UK
Related authors
Christine Kaufhold, Matteo Willeit, Bo Liu, and Andrey Ganopolski
Biogeosciences, 22, 2767–2801, https://doi.org/10.5194/bg-22-2767-2025, https://doi.org/10.5194/bg-22-2767-2025, 2025
Short summary
Short summary
This study simulates long-term future climate scenarios to assess the persistence of CO2 emissions in the atmosphere. Results show that the land stores 4 %–13 % of emissions after 100 kyr and that the removal timescale of CO2 for silicate weathering is shorter than previously expected. Our study highlights the importance of adding model complexity to the global carbon cycle in Earth system models for improved predictions of long-term atmospheric CO2 concentration.
Ricarda Winkelmann, Donovan P. Dennis, Jonathan F. Donges, Sina Loriani, Ann Kristin Klose, Jesse F. Abrams, Jorge Alvarez-Solas, Torsten Albrecht, David Armstrong McKay, Sebastian Bathiany, Javier Blasco Navarro, Victor Brovkin, Eleanor Burke, Gokhan Danabasoglu, Reik V. Donner, Markus Drüke, Goran Georgievski, Heiko Goelzer, Anna B. Harper, Gabriele Hegerl, Marina Hirota, Aixue Hu, Laura C. Jackson, Colin Jones, Hyungjun Kim, Torben Koenigk, Peter Lawrence, Timothy M. Lenton, Hannah Liddy, José Licón-Saláiz, Maxence Menthon, Marisa Montoya, Jan Nitzbon, Sophie Nowicki, Bette Otto-Bliesner, Francesco Pausata, Stefan Rahmstorf, Karoline Ramin, Alexander Robinson, Johan Rockström, Anastasia Romanou, Boris Sakschewski, Christina Schädel, Steven Sherwood, Robin S. Smith, Norman J. Steinert, Didier Swingedouw, Matteo Willeit, Wilbert Weijer, Richard Wood, Klaus Wyser, and Shuting Yang
EGUsphere, https://doi.org/10.5194/egusphere-2025-1899, https://doi.org/10.5194/egusphere-2025-1899, 2025
This preprint is open for discussion and under review for Earth System Dynamics (ESD).
Short summary
Short summary
The Tipping Points Modelling Intercomparison Project (TIPMIP) is an international collaborative effort to systematically assess tipping point risks in the Earth system using state-of-the-art coupled and stand-alone domain models. TIPMIP will provide a first global atlas of potential tipping dynamics, respective critical thresholds and key uncertainties, generating an important building block towards a comprehensive scientific basis for policy- and decision-making.
Chenzhi Li, Anne Dallmeyer, Jian Ni, Manuel Chevalier, Matteo Willeit, Andrei A. Andreev, Xianyong Cao, Laura Schild, Birgit Heim, Mareike Wieczorek, and Ulrike Herzschuh
Clim. Past, 21, 1001–1024, https://doi.org/10.5194/cp-21-1001-2025, https://doi.org/10.5194/cp-21-1001-2025, 2025
Short summary
Short summary
We present global megabiome dynamics and distributions derived from pollen-based reconstructions over the last 21 000 years, which are suitable for the evaluation of Earth-system-model-based paleo-megabiome simulations. We identified strong deviations between pollen- and model-derived megabiome distributions in the circum-Arctic and Tibetan Plateau areas during the Last Glacial Maximum and early deglaciation and in northern Africa and the Mediterranean region during the Holocene.
Matteo Willeit, Andrey Ganopolski, Neil R. Edwards, and Stefan Rahmstorf
Clim. Past, 20, 2719–2739, https://doi.org/10.5194/cp-20-2719-2024, https://doi.org/10.5194/cp-20-2719-2024, 2024
Short summary
Short summary
Using an Earth system model that can simulate Dansgaard–Oeschger-like events, we show that conditions under which millennial-scale climate variability occurs are related to the integrated surface buoyancy flux over the northern North Atlantic. This newly defined buoyancy measure explains why millennial-scale climate variability arising from abrupt changes in the Atlantic meridional overturning circulation occurred for mid-glacial conditions but not for interglacial or full glacial conditions.
Matteo Willeit and Andrey Ganopolski
Earth Syst. Dynam., 15, 1417–1434, https://doi.org/10.5194/esd-15-1417-2024, https://doi.org/10.5194/esd-15-1417-2024, 2024
Short summary
Short summary
Using a fast Earth system model we trace the stability landscape of the Atlantic meridional overturning circulation in the combined freshwater forcing–atmospheric CO2 space. We find four different Atlantic meridional overturning circulation states that are stable under different conditions and a generally increasing equilibrium Atlantic meridional overturning circulation strength with increasing CO2 concentrations.
Stefanie Talento, Matteo Willeit, and Andrey Ganopolski
Clim. Past, 20, 1349–1364, https://doi.org/10.5194/cp-20-1349-2024, https://doi.org/10.5194/cp-20-1349-2024, 2024
Short summary
Short summary
To trigger glacial inception, the summer maximum insolation at high latitudes in the Northern Hemisphere must be lower than a critical value. This value is not constant but depends on the atmospheric CO2 concentration. Paleoclimatic data do not give enough information to derive the relationship between the critical threshold and CO2. However, knowledge of such a relation is important for predicting future glaciations and the impact anthropogenic CO2 emissions might have on them.
Matteo Willeit, Reinhard Calov, Stefanie Talento, Ralf Greve, Jorjo Bernales, Volker Klemann, Meike Bagge, and Andrey Ganopolski
Clim. Past, 20, 597–623, https://doi.org/10.5194/cp-20-597-2024, https://doi.org/10.5194/cp-20-597-2024, 2024
Short summary
Short summary
We present transient simulations of the last glacial inception with the coupled climate–ice sheet model CLIMBER-X showing a rapid increase in Northern Hemisphere ice sheet area and a sea level drop by ~ 35 m, with the vegetation feedback playing a key role. Overall, our simulations confirm and refine previous results showing that climate-vegetation–cryosphere–carbon cycle feedbacks play a fundamental role in the transition from interglacial to glacial states.
Nico Wunderling, Anna S. von der Heydt, Yevgeny Aksenov, Stephen Barker, Robbin Bastiaansen, Victor Brovkin, Maura Brunetti, Victor Couplet, Thomas Kleinen, Caroline H. Lear, Johannes Lohmann, Rosa Maria Roman-Cuesta, Sacha Sinet, Didier Swingedouw, Ricarda Winkelmann, Pallavi Anand, Jonathan Barichivich, Sebastian Bathiany, Mara Baudena, John T. Bruun, Cristiano M. Chiessi, Helen K. Coxall, David Docquier, Jonathan F. Donges, Swinda K. J. Falkena, Ann Kristin Klose, David Obura, Juan Rocha, Stefanie Rynders, Norman Julius Steinert, and Matteo Willeit
Earth Syst. Dynam., 15, 41–74, https://doi.org/10.5194/esd-15-41-2024, https://doi.org/10.5194/esd-15-41-2024, 2024
Short summary
Short summary
This paper maps out the state-of-the-art literature on interactions between tipping elements relevant for current global warming pathways. We find indications that many of the interactions between tipping elements are destabilizing. This means that tipping cascades cannot be ruled out on centennial to millennial timescales at global warming levels between 1.5 and 2.0 °C or on shorter timescales if global warming surpasses 2.0 °C.
Takahito Mitsui, Matteo Willeit, and Niklas Boers
Earth Syst. Dynam., 14, 1277–1294, https://doi.org/10.5194/esd-14-1277-2023, https://doi.org/10.5194/esd-14-1277-2023, 2023
Short summary
Short summary
The glacial–interglacial cycles of the Quaternary exhibit 41 kyr periodicity before the Mid-Pleistocene Transition (MPT) around 1.2–0.8 Myr ago and ~100 kyr periodicity after that. The mechanism generating these periodicities remains elusive. Through an analysis of an Earth system model of intermediate complexity, CLIMBER-2, we show that the dominant periodicities of glacial cycles can be explained from the viewpoint of synchronization theory.
Kyung-Sook Yun, Axel Timmermann, Sun-Seon Lee, Matteo Willeit, Andrey Ganopolski, and Jyoti Jadhav
Clim. Past, 19, 1951–1974, https://doi.org/10.5194/cp-19-1951-2023, https://doi.org/10.5194/cp-19-1951-2023, 2023
Short summary
Short summary
To quantify the sensitivity of the earth system to orbital-scale forcings, we conducted an unprecedented quasi-continuous coupled general climate model simulation with the Community Earth System Model, which covers the climatic history of the past 3 million years. This study could stimulate future transient paleo-climate model simulations and perspectives to further highlight and document the effect of anthropogenic CO2 emissions in the broader paleo-climatic context.
Matteo Willeit, Tatiana Ilyina, Bo Liu, Christoph Heinze, Mahé Perrette, Malte Heinemann, Daniela Dalmonech, Victor Brovkin, Guy Munhoven, Janine Börker, Jens Hartmann, Gibran Romero-Mujalli, and Andrey Ganopolski
Geosci. Model Dev., 16, 3501–3534, https://doi.org/10.5194/gmd-16-3501-2023, https://doi.org/10.5194/gmd-16-3501-2023, 2023
Short summary
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In this paper we present the carbon cycle component of the newly developed fast Earth system model CLIMBER-X. The model can be run with interactive atmospheric CO2 to investigate the feedbacks between climate and the carbon cycle on temporal scales ranging from decades to > 100 000 years. CLIMBER-X is expected to be a useful tool for studying past climate–carbon cycle changes and for the investigation of the long-term future evolution of the Earth system.
Nils Bochow, Philipp Hess, and Alexander Robinson
EGUsphere, https://doi.org/https://doi.org/10.48550/arXiv.2507.22485, https://doi.org/https://doi.org/10.48550/arXiv.2507.22485, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
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This study presents a fast, physics-guided machine-learning method that downscales coarse climate fields to fine resolution while enforcing conservation of large-scale totals. Trained on regional climate simulations and driven by Earth system model output, it handles extremes and outperforms linear interpolation, providing realistic, high-resolution forcing for ice-sheet models and improving projections of Greenland’s sea-level contribution.
Lucía Gutiérrez-González, Alexander Robinson, Jorge Alvarez-Solas, Ilaria Tabone, Jan Swierczek-Jereczek, Daniel Moreno-Parada, and Marisa Montoya
EGUsphere, https://doi.org/10.5194/egusphere-2025-2616, https://doi.org/10.5194/egusphere-2025-2616, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
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The Greenland ice sheet is considered a tipping element: if temperatures exceed its threshold, it would transition to a virtually ice-free state. We analyze its stability across the full range of glacial-interglacial temperatures, as well as those expected in the coming centuries. We find a future critical threshold between +1.5 and +2 K of global warming, another under colder climates, and persistent hysteresis across the full range of study.
Daniel Moreno-Parada, Alexander Robinson, Marisa Montoya, and Jorge Alvarez-Solas
Geosci. Model Dev., 18, 3895–3919, https://doi.org/10.5194/gmd-18-3895-2025, https://doi.org/10.5194/gmd-18-3895-2025, 2025
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We introduce Nix, an ice-sheet model designed for understanding how large masses of ice behave. Nix is a computer programme that simulates the movement and temperature evolution in ice sheets. It helps us study how ice sheets respond to changes in the atmosphere and ocean. We found that ice temperatures play an essential role in determining the motion and stability of ice sheets. Nix is a useful tool for learning how climate change affects polar ice sheets.
Sergio Pérez-Montero, Jorge Alvarez-Solas, Jan Swierczek-Jereczek, Daniel Moreno-Parada, Alexander Robinson, and Marisa Montoya
Earth Syst. Dynam., 16, 915–937, https://doi.org/10.5194/esd-16-915-2025, https://doi.org/10.5194/esd-16-915-2025, 2025
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The climate of the last 3 Myr has varied between cold and warm periods. Numerous independent mechanisms have been proposed to explain this; however, no effort has been made to study their competing effects. Here we present a simple but physically motivated model that includes these mechanisms in a modular way. We identify ice-sheet dynamics and lithosphere displacement as main triggers, but reproducing the climate records additionally requires the natural darkening of ice.
Christine Kaufhold, Matteo Willeit, Bo Liu, and Andrey Ganopolski
Biogeosciences, 22, 2767–2801, https://doi.org/10.5194/bg-22-2767-2025, https://doi.org/10.5194/bg-22-2767-2025, 2025
Short summary
Short summary
This study simulates long-term future climate scenarios to assess the persistence of CO2 emissions in the atmosphere. Results show that the land stores 4 %–13 % of emissions after 100 kyr and that the removal timescale of CO2 for silicate weathering is shorter than previously expected. Our study highlights the importance of adding model complexity to the global carbon cycle in Earth system models for improved predictions of long-term atmospheric CO2 concentration.
Ricarda Winkelmann, Donovan P. Dennis, Jonathan F. Donges, Sina Loriani, Ann Kristin Klose, Jesse F. Abrams, Jorge Alvarez-Solas, Torsten Albrecht, David Armstrong McKay, Sebastian Bathiany, Javier Blasco Navarro, Victor Brovkin, Eleanor Burke, Gokhan Danabasoglu, Reik V. Donner, Markus Drüke, Goran Georgievski, Heiko Goelzer, Anna B. Harper, Gabriele Hegerl, Marina Hirota, Aixue Hu, Laura C. Jackson, Colin Jones, Hyungjun Kim, Torben Koenigk, Peter Lawrence, Timothy M. Lenton, Hannah Liddy, José Licón-Saláiz, Maxence Menthon, Marisa Montoya, Jan Nitzbon, Sophie Nowicki, Bette Otto-Bliesner, Francesco Pausata, Stefan Rahmstorf, Karoline Ramin, Alexander Robinson, Johan Rockström, Anastasia Romanou, Boris Sakschewski, Christina Schädel, Steven Sherwood, Robin S. Smith, Norman J. Steinert, Didier Swingedouw, Matteo Willeit, Wilbert Weijer, Richard Wood, Klaus Wyser, and Shuting Yang
EGUsphere, https://doi.org/10.5194/egusphere-2025-1899, https://doi.org/10.5194/egusphere-2025-1899, 2025
This preprint is open for discussion and under review for Earth System Dynamics (ESD).
Short summary
Short summary
The Tipping Points Modelling Intercomparison Project (TIPMIP) is an international collaborative effort to systematically assess tipping point risks in the Earth system using state-of-the-art coupled and stand-alone domain models. TIPMIP will provide a first global atlas of potential tipping dynamics, respective critical thresholds and key uncertainties, generating an important building block towards a comprehensive scientific basis for policy- and decision-making.
Sergio Pérez-Montero, Jorge Alvarez-Solas, Jan Swierczek-Jereczek, Daniel Moreno-Parada, Alexander Robinson, and Marisa Montoya
EGUsphere, https://doi.org/10.5194/egusphere-2025-2467, https://doi.org/10.5194/egusphere-2025-2467, 2025
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Almost 3 million years ago, the planet began to experience a succession of cold and warm periods every 40,000 years. However, about 1 million years ago, they began to occur every 100,000 years. In this paper we explore how the change in the basal velocity of the ice sheets could have produced this change in behavior. On the other hand, we also see that in our model, decreasing in time the sensitivity of snowfall to temperature is also an effective mechanism with which to reproduce the records.
Chenzhi Li, Anne Dallmeyer, Jian Ni, Manuel Chevalier, Matteo Willeit, Andrei A. Andreev, Xianyong Cao, Laura Schild, Birgit Heim, Mareike Wieczorek, and Ulrike Herzschuh
Clim. Past, 21, 1001–1024, https://doi.org/10.5194/cp-21-1001-2025, https://doi.org/10.5194/cp-21-1001-2025, 2025
Short summary
Short summary
We present global megabiome dynamics and distributions derived from pollen-based reconstructions over the last 21 000 years, which are suitable for the evaluation of Earth-system-model-based paleo-megabiome simulations. We identified strong deviations between pollen- and model-derived megabiome distributions in the circum-Arctic and Tibetan Plateau areas during the Last Glacial Maximum and early deglaciation and in northern Africa and the Mediterranean region during the Holocene.
Matteo Willeit, Andrey Ganopolski, Neil R. Edwards, and Stefan Rahmstorf
Clim. Past, 20, 2719–2739, https://doi.org/10.5194/cp-20-2719-2024, https://doi.org/10.5194/cp-20-2719-2024, 2024
Short summary
Short summary
Using an Earth system model that can simulate Dansgaard–Oeschger-like events, we show that conditions under which millennial-scale climate variability occurs are related to the integrated surface buoyancy flux over the northern North Atlantic. This newly defined buoyancy measure explains why millennial-scale climate variability arising from abrupt changes in the Atlantic meridional overturning circulation occurred for mid-glacial conditions but not for interglacial or full glacial conditions.
Matteo Willeit and Andrey Ganopolski
Earth Syst. Dynam., 15, 1417–1434, https://doi.org/10.5194/esd-15-1417-2024, https://doi.org/10.5194/esd-15-1417-2024, 2024
Short summary
Short summary
Using a fast Earth system model we trace the stability landscape of the Atlantic meridional overturning circulation in the combined freshwater forcing–atmospheric CO2 space. We find four different Atlantic meridional overturning circulation states that are stable under different conditions and a generally increasing equilibrium Atlantic meridional overturning circulation strength with increasing CO2 concentrations.
Antonio Juarez-Martinez, Javier Blasco, Alexander Robinson, Marisa Montoya, and Jorge Alvarez-Solas
The Cryosphere, 18, 4257–4283, https://doi.org/10.5194/tc-18-4257-2024, https://doi.org/10.5194/tc-18-4257-2024, 2024
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We present sea level projections for Antarctica in the context of ISMIP6-2300 with several forcings but extend the simulations to 2500, showing that more than 3 m of sea level contribution could be reached. We also test the sensitivity on a basal melting parameter and determine the timing of the loss of ice in the west region. All the simulations were carried out with the ice sheet model Yelmo.
Therese Rieckh, Andreas Born, Alexander Robinson, Robert Law, and Gerrit Gülle
Geosci. Model Dev., 17, 6987–7000, https://doi.org/10.5194/gmd-17-6987-2024, https://doi.org/10.5194/gmd-17-6987-2024, 2024
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We present the open-source model ELSA, which simulates the internal age structure of large ice sheets. It creates layers of snow accumulation at fixed times during the simulation, which are used to model the internal stratification of the ice sheet. Together with reconstructed isochrones from radiostratigraphy data, ELSA can be used to assess ice sheet models and to improve their parameterization. ELSA can be used coupled to an ice sheet model or forced with its output.
Daniel Moreno-Parada, Alexander Robinson, Marisa Montoya, and Jorge Alvarez-Solas
The Cryosphere, 18, 4215–4232, https://doi.org/10.5194/tc-18-4215-2024, https://doi.org/10.5194/tc-18-4215-2024, 2024
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Our study tries to understand how the ice temperature evolves in a large mass as in the case of Antarctica. We found a relation that tells us the ice temperature at any point. These results are important because they also determine how the ice moves. In general, ice moves due to slow deformation (as if pouring honey from a jar). Nevertheless, in some regions the ice base warms enough and melts. The liquid water then serves as lubricant and the ice slides and its velocity increases rapidly.
Javier Blasco, Ilaria Tabone, Daniel Moreno-Parada, Alexander Robinson, Jorge Alvarez-Solas, Frank Pattyn, and Marisa Montoya
Clim. Past, 20, 1919–1938, https://doi.org/10.5194/cp-20-1919-2024, https://doi.org/10.5194/cp-20-1919-2024, 2024
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In this study, we assess Antarctic tipping points which may had been crossed during the mid-Pliocene Warm Period. For this, we use data from the PlioMIP2 ensemble. Additionally, we investigate various sources of uncertainty, like ice dynamics and bedrock configuration. Our research significantly enhances our comprehension of Antarctica's response to a warming climate, shedding light on potential future tipping points that may be surpassed.
Jan Swierczek-Jereczek, Marisa Montoya, Konstantin Latychev, Alexander Robinson, Jorge Alvarez-Solas, and Jerry Mitrovica
Geosci. Model Dev., 17, 5263–5290, https://doi.org/10.5194/gmd-17-5263-2024, https://doi.org/10.5194/gmd-17-5263-2024, 2024
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Ice sheets present a thickness of a few kilometres, leading to a vertical deformation of the crust of up to a kilometre. This process depends on properties of the solid Earth, which can be regionally very different. We propose a model that accounts for this often-ignored heterogeneity and run 100 000 simulation years in minutes. Thus, the evolution of ice sheets is modeled with better accuracy, which is critical for a good mitigation of climate change and, in particular, sea-level rise.
Stefanie Talento, Matteo Willeit, and Andrey Ganopolski
Clim. Past, 20, 1349–1364, https://doi.org/10.5194/cp-20-1349-2024, https://doi.org/10.5194/cp-20-1349-2024, 2024
Short summary
Short summary
To trigger glacial inception, the summer maximum insolation at high latitudes in the Northern Hemisphere must be lower than a critical value. This value is not constant but depends on the atmospheric CO2 concentration. Paleoclimatic data do not give enough information to derive the relationship between the critical threshold and CO2. However, knowledge of such a relation is important for predicting future glaciations and the impact anthropogenic CO2 emissions might have on them.
Matteo Willeit, Reinhard Calov, Stefanie Talento, Ralf Greve, Jorjo Bernales, Volker Klemann, Meike Bagge, and Andrey Ganopolski
Clim. Past, 20, 597–623, https://doi.org/10.5194/cp-20-597-2024, https://doi.org/10.5194/cp-20-597-2024, 2024
Short summary
Short summary
We present transient simulations of the last glacial inception with the coupled climate–ice sheet model CLIMBER-X showing a rapid increase in Northern Hemisphere ice sheet area and a sea level drop by ~ 35 m, with the vegetation feedback playing a key role. Overall, our simulations confirm and refine previous results showing that climate-vegetation–cryosphere–carbon cycle feedbacks play a fundamental role in the transition from interglacial to glacial states.
Nico Wunderling, Anna S. von der Heydt, Yevgeny Aksenov, Stephen Barker, Robbin Bastiaansen, Victor Brovkin, Maura Brunetti, Victor Couplet, Thomas Kleinen, Caroline H. Lear, Johannes Lohmann, Rosa Maria Roman-Cuesta, Sacha Sinet, Didier Swingedouw, Ricarda Winkelmann, Pallavi Anand, Jonathan Barichivich, Sebastian Bathiany, Mara Baudena, John T. Bruun, Cristiano M. Chiessi, Helen K. Coxall, David Docquier, Jonathan F. Donges, Swinda K. J. Falkena, Ann Kristin Klose, David Obura, Juan Rocha, Stefanie Rynders, Norman Julius Steinert, and Matteo Willeit
Earth Syst. Dynam., 15, 41–74, https://doi.org/10.5194/esd-15-41-2024, https://doi.org/10.5194/esd-15-41-2024, 2024
Short summary
Short summary
This paper maps out the state-of-the-art literature on interactions between tipping elements relevant for current global warming pathways. We find indications that many of the interactions between tipping elements are destabilizing. This means that tipping cascades cannot be ruled out on centennial to millennial timescales at global warming levels between 1.5 and 2.0 °C or on shorter timescales if global warming surpasses 2.0 °C.
Andrey Ganopolski
Clim. Past, 20, 151–185, https://doi.org/10.5194/cp-20-151-2024, https://doi.org/10.5194/cp-20-151-2024, 2024
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Despite significant progress in modelling Quaternary climate dynamics, a comprehensive theory of glacial cycles is still lacking. Here, using the results of model simulations and data analysis, I present a framework of the generalized Milankovitch theory (GMT), which further advances the concept proposed by Milutin Milankovitch over a century ago. The theory explains a number of facts which were not known during Milankovitch time's, such as the 100 kyr periodicity of the late Quaternary.
Takahito Mitsui, Matteo Willeit, and Niklas Boers
Earth Syst. Dynam., 14, 1277–1294, https://doi.org/10.5194/esd-14-1277-2023, https://doi.org/10.5194/esd-14-1277-2023, 2023
Short summary
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The glacial–interglacial cycles of the Quaternary exhibit 41 kyr periodicity before the Mid-Pleistocene Transition (MPT) around 1.2–0.8 Myr ago and ~100 kyr periodicity after that. The mechanism generating these periodicities remains elusive. Through an analysis of an Earth system model of intermediate complexity, CLIMBER-2, we show that the dominant periodicities of glacial cycles can be explained from the viewpoint of synchronization theory.
Kyung-Sook Yun, Axel Timmermann, Sun-Seon Lee, Matteo Willeit, Andrey Ganopolski, and Jyoti Jadhav
Clim. Past, 19, 1951–1974, https://doi.org/10.5194/cp-19-1951-2023, https://doi.org/10.5194/cp-19-1951-2023, 2023
Short summary
Short summary
To quantify the sensitivity of the earth system to orbital-scale forcings, we conducted an unprecedented quasi-continuous coupled general climate model simulation with the Community Earth System Model, which covers the climatic history of the past 3 million years. This study could stimulate future transient paleo-climate model simulations and perspectives to further highlight and document the effect of anthropogenic CO2 emissions in the broader paleo-climatic context.
Christine Kaufhold and Andrey Ganopolski
Saf. Nucl. Waste Disposal, 2, 89–90, https://doi.org/10.5194/sand-2-89-2023, https://doi.org/10.5194/sand-2-89-2023, 2023
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A repository in Germany must be secure for a period of at least 1 million years. We argue that the deep-future climate should be considered in the site selection process. A suite of possible future climates will be provided, using different emission scenarios. In low-emission scenarios, glacial cycles will quickly resume, changing subterranean stress and permafrost. In high-emission scenarios, the sea level will rise. Both regimes should be of interest to those working on nuclear waste disposal.
Matteo Willeit, Tatiana Ilyina, Bo Liu, Christoph Heinze, Mahé Perrette, Malte Heinemann, Daniela Dalmonech, Victor Brovkin, Guy Munhoven, Janine Börker, Jens Hartmann, Gibran Romero-Mujalli, and Andrey Ganopolski
Geosci. Model Dev., 16, 3501–3534, https://doi.org/10.5194/gmd-16-3501-2023, https://doi.org/10.5194/gmd-16-3501-2023, 2023
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In this paper we present the carbon cycle component of the newly developed fast Earth system model CLIMBER-X. The model can be run with interactive atmospheric CO2 to investigate the feedbacks between climate and the carbon cycle on temporal scales ranging from decades to > 100 000 years. CLIMBER-X is expected to be a useful tool for studying past climate–carbon cycle changes and for the investigation of the long-term future evolution of the Earth system.
Daniel Moreno-Parada, Jorge Alvarez-Solas, Javier Blasco, Marisa Montoya, and Alexander Robinson
The Cryosphere, 17, 2139–2156, https://doi.org/10.5194/tc-17-2139-2023, https://doi.org/10.5194/tc-17-2139-2023, 2023
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We have reconstructed the Laurentide Ice Sheet, located in North America during the Last Glacial Maximum (21 000 years ago). The absence of direct measurements raises a number of uncertainties. Here we study the impact of different physical laws that describe the friction as the ice slides over its base. We found that the Laurentide Ice Sheet is closest to prior reconstructions when the basal friction takes into account whether the base is frozen or thawed during its motion.
Negar Vakilifard, Richard G. Williams, Philip B. Holden, Katherine Turner, Neil R. Edwards, and David J. Beerling
Biogeosciences, 19, 4249–4265, https://doi.org/10.5194/bg-19-4249-2022, https://doi.org/10.5194/bg-19-4249-2022, 2022
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To remain within the Paris climate agreement, there is an increasing need to develop and implement carbon capture and sequestration techniques. The global climate benefits of implementing negative emission technologies over the next century are assessed using an Earth system model covering a wide range of plausible climate states. In some model realisations, there is continued warming after emissions cease. This continued warming is avoided if negative emissions are incorporated.
Alexander Robinson, Daniel Goldberg, and William H. Lipscomb
The Cryosphere, 16, 689–709, https://doi.org/10.5194/tc-16-689-2022, https://doi.org/10.5194/tc-16-689-2022, 2022
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Here we investigate the numerical stability of several commonly used methods in order to determine which of them are capable of resolving the complex physics of the ice flow and are also computationally efficient. We find that the so-called DIVA solver outperforms the others. Its representation of the physics is consistent with more complex methods, while it remains computationally efficient at high resolution.
Stefanie Talento and Andrey Ganopolski
Earth Syst. Dynam., 12, 1275–1293, https://doi.org/10.5194/esd-12-1275-2021, https://doi.org/10.5194/esd-12-1275-2021, 2021
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We propose a model for glacial cycles and produce an assessment of possible trajectories for the next 1 million years. Under natural conditions, the next glacial inception would most likely occur ∼50 kyr after present. We show that fossil-fuel CO2 releases can have an extremely long-term effect. Potentially achievable CO2 anthropogenic emissions during the next centuries will most likely provoke ice-free conditions in the Northern Hemisphere landmasses throughout the next half a million years.
Andreas Born and Alexander Robinson
The Cryosphere, 15, 4539–4556, https://doi.org/10.5194/tc-15-4539-2021, https://doi.org/10.5194/tc-15-4539-2021, 2021
Short summary
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Ice penetrating radar reflections from the Greenland ice sheet are the best available record of past accumulation and how these layers have been deformed over time by the flow of ice. Direct simulations of this archive hold great promise for improving our models and for uncovering details of ice sheet dynamics that neither models nor data could achieve alone. We present the first three-dimensional ice sheet model that explicitly simulates individual layers of accumulation and how they deform.
Javier Blasco, Jorge Alvarez-Solas, Alexander Robinson, and Marisa Montoya
The Cryosphere, 15, 215–231, https://doi.org/10.5194/tc-15-215-2021, https://doi.org/10.5194/tc-15-215-2021, 2021
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Short summary
During the Last Glacial Maximum the Antarctic Ice Sheet was larger and more extended than at present. However, neither its exact position nor the total ice volume are well constrained. Here we investigate how the different climatic boundary conditions, as well as basal friction configurations, affect the size and extent of the Antarctic Ice Sheet and discuss its potential implications.
Cited articles
Adcroft, A., Anderson, W., Balaji, V., Blanton, C., Bushuk, M., Dufour, C. O.,
Dunne, J. P., Griffies, S. M., Hallberg, R., Harrison, M. J., Held, I. M.,
Jansen, M. F., John, J. G., Krasting, J. P., Langenhorst, A. R., Legg, S.,
Liang, Z., McHugh, C., Radhakrishnan, A., Reichl, B. G., Rosati, T., Samuels,
B. L., Shao, A., Stouffer, R., Winton, M., Wittenberg, A. T., Xiang, B.,
Zadeh, N., and Zhang, R.: The GFDL Global Ocean and Sea Ice Model OM4.0:
Model Description and Simulation Features, J. Adv. Model.
Earth Sy., 11, 3167–3211, https://doi.org/10.1029/2019MS001726, 2019. a, b
Adkins, J. F., McIntyre, K., and Schrag, D. P.: The salinity, temperature, and
δ18O of the glacial deep ocean, Science, 298, 1769–1773,
https://doi.org/10.1126/science.1076252, 2002. a
Bala, G., Caldeira, K., Mirin, A., Wickett, M., Delire, C., and Phillips,
T. J.: Biogeophysical effects of CO2 fertilization on global climate,
Tellus B, 58, 620–627,
https://doi.org/10.1111/j.1600-0889.2006.00210.x, 2006. a
Bauer, E. and Ganopolski, A.: Aeolian dust modeling over the past four glacial
cycles with CLIMBER-2, Global Planet. Change, 74, 49–60,
https://doi.org/10.1016/j.gloplacha.2010.07.009, 2010. a, b
Bauer, E., Petoukhov, V., Ganopolski, A., and Eliseev, A. V.: Climatic
response to anthropogenic sulphate aerosols versus well-mixed greenhouse
gases from 1850 to 2000 AD in CLIMBER-2, Tellus B, 60B, 82–97, https://doi.org/10.1111/j.1600-0889.2007.00318.x,
2008. a, b
Bereiter, B., Shackleton, S., Baggenstos, D., Kawamura, K., and Severinghaus,
J.: Mean global ocean temperatures during the last glacial transition,
Nature, 553, 39–44, https://doi.org/10.1038/nature25152, 2018. a
Bock, L., Lauer, A., Schlund, M., Barreiro, M., Bellouin, N., Jones, C., Meehl,
G. A., Predoi, V., Roberts, M. J., and Eyring, V.: Quantifying Progress
Across Different CMIP Phases With the ESMValTool, J. Geophys.
Res.-Atmos., 125, e2019JD032321, https://doi.org/10.1029/2019JD032321, 2020. a
Bohm, E., Lippold, J., Gutjahr, M., Frank, M., Blaser, P., Antz, B.,
Fohlmeister, J., Frank, N., Andersen, M. B., and Deininger, M.: Strong and
deep Atlantic meridional overturning circulation during the last glacial
cycle, Nature, 517, 73–76, https://doi.org/10.1038/nature14059, 2015. a
Bonan, G. B.: Forests and climate change: forcings, feedbacks, and the climate
benefits of forests, Science, 320, 1444–1449,
https://doi.org/10.1126/science.1155121, 2008. a
Bony, S., Colman, R., Kattsov, V. M., Allan, R. P., Bretherton, C. S.,
Dufresne, J.-L. L., Hall, A., Hallegatte, S., Holland, M. M., Ingram, W.,
Randall, D. a., Soden, B. J., Tselioudis, G., and Webb, M. J.: How Well Do
We Understand and Evaluate Climate Change Feedback Processes?, J.
Climate, 19, 3445–3482, https://doi.org/10.1175/JCLI3819.1, 2006. a, b
Bouillon, S., Morales Maqueda, M. Á., Legat, V., and Fichefet, T.: An
elastic–viscous–plastic sea ice model formulated on Arakawa B and C
grids, Ocean Model., 27, 174–184, https://doi.org/10.1016/j.ocemod.2009.01.004,
2009. a, b
Brown, J., Ferrians, O., Heginbottom, J. A., and Melnikov, E.: Circum-Arctic Map of Permafrost and Ground-Ice Conditions, Version 2, Boulder, Colorado USA, NSIDC: National Snow and Ice Data Center [data set], https://doi.org/https://doi.org/10.7265/skbg-kf16, 1998. a
Bryan, K. and Lewis, L. J.: A water mass model of the World Ocean, J.
Geophys. Res., 84, 2503–2517, https://doi.org/10.1029/JC084iC05p02503, 1979. a
Burton, C., Betts, R., Cardoso, M., Feldpausch, T. R., Harper, A., Jones, C. D., Kelley, D. I., Robertson, E., and Wiltshire, A.: Representation of fire, land-use change and vegetation dynamics in the Joint UK Land Environment Simulator vn4.9 (JULES), Geosci. Model Dev., 12, 179–193, https://doi.org/10.5194/gmd-12-179-2019, 2019. a
Caballero, R. and Hanley, J.: Midlatitude eddies, storm-track diffusivity, and
poleward moisture transport in warm climates, J. Atmos.
Sci., 69, 3237–3250, https://doi.org/10.1175/JAS-D-12-035.1, 2012. a
Calov, R., Ganopolski, A., Claussen, M., Petoukhov, V., and Greve, R.:
Transient simulation of the last glacial inception. Part I: glacial
inception as a bifurcation in the climate system, Clim. Dynam., 24,
545–561, https://doi.org/10.1007/s00382-005-0007-6, 2005. a
Charney, J., Arakawa, A., Baker, D., Bolin, B., Dickinson, R., Goody, R.,
Leith, C., Stommel, H., and Wunsch, C.: Carbon Dioxide and Climate: A
Scientific Assessment, Tech. Rep., National Academy of Sciences, Washington,
D.C., https://doi.org/10.17226/12181, 1979. a
Charney, J. G. and Eliassen, A.: A Numerical Method for Predicting the
Perturbations of the Middle Latitude Westerlies, Tellus, 1, 38–54,
https://doi.org/10.3402/tellusa.v1i2.8500, 1949. a, b
Claussen, M., Mysak, L., Weaver, A., Crucifix, M., Fichefet, T., Loutre, M. F.,
Weber, S., Alcamo, J., Alexeev, V., Berger, A., Calov, R., Ganopolski, A.,
Goosse, H., Lohmann, G., Lunkeit, F., Mokhov, I., Petoukhov, V., Stone, P.,
and Wang, Z.: Earth system models of intermediate complexity: Closing the
gap in the spectrum of climate system models, Clim. Dynam., 18,
579–586, https://doi.org/10.1007/s00382-001-0200-1, 2002. a
Colman, R. and McAvaney, B.: Climate feedbacks under a very broad range of
forcing, Geophys. Res. Lett., 36, 1–5, https://doi.org/10.1029/2008GL036268,
2009. a, b
Colman, R., Fraser, J., and Rotstayn, L.: Climate feedbacks in a general
circulation model incorporating prognostic clouds, Clim. Dynam., 18,
103–122, https://doi.org/10.1007/s003820100162, 2001. a
Crook, J. A., Forster, P. M., and Stuber, N.: Spatial patterns of modeled
climate feedback and contributions to temperature response and polar
amplification, J. Climate, 24, 3575–3592,
https://doi.org/10.1175/2011JCLI3863.1, 2011. a
Dang, C., Brandt, R. E., and Warren, S. G.: Parameterizations for narrowband
and broadband albedo of pure snow and snow containing mineral dust and black
carbon, J. Geophys. Res.-Atmos., 120, 5446–5468,
https://doi.org/10.1002/2014JD022646, 2015. a, b, c, d
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi,
S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P.,
Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C.,
Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B.,
Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler,
M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J.,
Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N.,
and Vitart, F.: The ERA-Interim reanalysis: configuration and performance of
the data assimilation system, Q. J. Roy. Meteor.
Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011. a, b, c, d, e, f, g, h, i, j, k, l, m, n
Delworth, T. L., Broccoli, A. J., Rosati, A., Stouffer, R. J., Balaji, V.,
Beesley, J. A., Cooke, W. F., Dixon, K. W., Dunne, J., Dunne, K. A.,
Durachta, J. W., Findell, K. L., Ginoux, P., Gnanadesikan, A., Gordon, C. T.,
Griffies, S. M., Gudgel, R., Harrison, M. J., Held, I. M., Hemler, R. S.,
Horowitz, L. W., Klein, S. A., Knutson, T. R., Kushner, P. J., Langenhorst,
A. R., Lee, H.-C., Lin, S.-J., Lu, J., Malyshev, S. L., Milly, P. C. D.,
Ramaswamy, V., Russell, J., Schwarzkopf, M. D., Shevliakova, E., Sirutis,
J. J., Spelman, M. J., Stern, W. F., Winton, M., Wittenberg, A. T., Wyman,
B., Zeng, F., and Zhang, R.: GFDL's CM2 Global Coupled Climate Models. Part
I: Formulation and Simulation Characteristics, J. Climate, 19,
643–674, https://doi.org/10.1175/JCLI3629.1, 2006. a, b
Durack, P. J., Wijffels, S. E., and Matear, R. J.: Ocean Salinities Reveal
Strong Global Water Cycle Intensification During 1950 to 2000, Science, 336,
455–458, https://doi.org/10.1126/science.1212222, 2012. a, b
Eby, M., Weaver, A. J., Alexander, K., Zickfeld, K., Abe-Ouchi, A., Cimatoribus, A. A., Crespin, E., Drijfhout, S. S., Edwards, N. R., Eliseev, A. V., Feulner, G., Fichefet, T., Forest, C. E., Goosse, H., Holden, P. B., Joos, F., Kawamiya, M., Kicklighter, D., Kienert, H., Matsumoto, K., Mokhov, I. I., Monier, E., Olsen, S. M., Pedersen, J. O. P., Perrette, M., Philippon-Berthier, G., Ridgwell, A., Schlosser, A., Schneider von Deimling, T., Shaffer, G., Smith, R. S., Spahni, R., Sokolov, A. P., Steinacher, M., Tachiiri, K., Tokos, K., Yoshimori, M., Zeng, N., and Zhao, F.: Historical and idealized climate model experiments: an intercomparison of Earth system models of intermediate complexity, Clim. Past, 9, 1111–1140, https://doi.org/10.5194/cp-9-1111-2013, 2013. a
ECCO Consortium, Fukumori, I., Wang, O., Fenty, I., Forget, G., Heimbach, P., and
Ponte, R. M.: ECCO Ocean Mixed Layer Depth – Monthly Mean 0.5 Degree
(Version 4 Release 4), Ver. V4r4, NASA [data set], https://doi.org/10.5067/ECG5M-OML44, 2021. a
Edwards, N. and Shepherd, J.: Bifurcations of the thermohaline circulation in
a simplified three-dimensional model of the world ocean and the effects of
inter-basin connectivity, Clim. Dynam., 19, 31–42,
https://doi.org/10.1007/s00382-001-0207-7, 2002. a, b
Edwards, N. R. and Marsh, R.: Uncertainties due to transport-parameter
sensitivity in an efficient 3-D ocean-climate model, Clim. Dynam., 24,
415–433, https://doi.org/10.1007/s00382-004-0508-8, 2005. a, b
Edwards, N. R., Willmott, A. J., and Killworth, P. D.: On the Role of
Topography and Wind Stress on the Stability of the Thermohaline Circulation,
J. Phys. Oceanogr., 28, 756–778,
https://doi.org/10.1175/1520-0485(1998)028<0756:OTROTA>2.0.CO;2, 1998. a, b
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
Falloon, P. D., Dankers, R., Betts, R. A., Jones, C. D., Booth, B. B. B., and Lambert, F. H.: Role of vegetation change in future climate under the A1B scenario and a climate stabilisation scenario, using the HadCM3C Earth system model, Biogeosciences, 9, 4739–4756, https://doi.org/10.5194/bg-9-4739-2012, 2012. a
Farneti, R. and Vallis, G. K.: An Intermediate Complexity Climate Model (ICCMp1) based on the GFDL flexible modelling system, Geosci. Model Dev., 2, 73–88, https://doi.org/10.5194/gmd-2-73-2009, 2009. a
Fasullo, J. T. and Trenberth, K. E.: The annual cycle of the energy budget.
Part II: Meridional structures and poleward transports, J. Climate,
21, 2313–2325, https://doi.org/10.1175/2007JCLI1936.1, 2008. a, b, c
Fedorovich, E. and Shapiro, A.: Structure of numerically simulated katabatic
and anabatic flows along steep slopes, Acta Geophys., 57, 981–1010,
https://doi.org/10.2478/s11600-009-0027-4, 2009. a
Feigelson, E., Ginzburg, A., Krasnokutskaya, L., and Petoukhov, V.: Effects of
clouds on the radiative heat exchange in the atmosphere, Geofís.
Int., 15, 293–326, https://doi.org/10.22201/igeof.00167169p.1975.15.4.1010,
1975. a, b
Fettweis, X., Box, J. E., Agosta, C., Amory, C., Kittel, C., Lang, C., van As, D., Machguth, H., and Gallée, H.: Reconstructions of the 1900–2015 Greenland ice sheet surface mass balance using the regional climate MAR model, The Cryosphere, 11, 1015–1033, https://doi.org/10.5194/tc-11-1015-2017, 2017. a, b
Fichefet, T. and Maqueda, M. A. M.: Sensitivity of a global sea ice model to
the treatment of ice thermodynamics and dynamics, J. Geophys.
Res.-Oceans, 102, 12609–12646, https://doi.org/10.1029/97JC00480, 1997. a, b, c
Fraedrich, K., Kirk, E., Luksch, U., and Lunkeit, F.: The portable university
model of the atmosphere (PUMA): Storm track dynamics and low-frequency
variability, Meteorol. Z., 14, 735–745,
https://doi.org/10.1127/0941-2948/2005/0074, 2005. a
Frajka-Williams, E., Moat, B., Smeed, D., Rayner, D., Johns, W., Baringer, M.,
Volkov, D., and Collins, J.: Atlantic meridional overturning circulation
observed by the RAPID-MOCHA-WBTS (RAPID-Meridional Overturning Circulation
and Heatflux Array-Western Boundary Time Series) array at 26N from 2004 to
2020 (v2020.1), National Oceanography Centre [data set], https://doi.org/10.5285/cc1e34b3-3385-662b-e053-6c86abc03444, 2021. a, b
Frierson, D. M., Lu, J., and Chen, G.: Width of the Hadley cell in simple and
comprehensive general circulation models, Geophys. Res. Lett., 34,
1–5, https://doi.org/10.1029/2007GL031115, 2007. a
Ganopolski, A. and Brovkin, V.: Simulation of climate, ice sheets and CO2 evolution during the last four glacial cycles with an Earth system model of intermediate complexity, Clim. Past, 13, 1695–1716, https://doi.org/10.5194/cp-13-1695-2017, 2017. a
Ganopolski, A., Rahmstorf, S., Petoukhov, V., and Claussen, M.: Simulation of
modern and glacial climates with a coupled global model of intermediate
complexity, Nature, 391, 351–356, https://doi.org/10.1038/34839, 1998. a
Ganopolski, A., Petoukhov, V., Rahmstorf, S., Brovkin, V., Claussen, M.,
Eliseev, A., and Kubatzki, C.: CLIMBER-2: a climate system model of
intermediate complexity. Part II: model sensitivity, Clim. Dynam., 17,
735–751, https://doi.org/10.1007/s003820000144, 2001. a
Ganopolski, A., Winkelmann, R., and Schellnhuber, H. J.: Critical
insolation–CO2 relation for diagnosing past and future glacial inception,
Nature, 529, 200–203, https://doi.org/10.1038/nature16494, 2016. a
Gent, P. R. and Mcwilliams, J. C.: Isopycnal Mixing in Ocean Circulation
Models, J. Phys. Oceanogr., 20, 150–155, https://doi.org/10.1175/1520-0485(1990)020<0150:IMIOCM>2.0.CO;2, 1990. a
Gerdes, R., Köberle, C., and Willebrand, J.: The influence of numerical
advection schemes on the results of ocean general circulation models,
Clim. Dynam., 5, 211–226, https://doi.org/10.1007/BF00210006, 1991. a
Goosse, H., Brovkin, V., Fichefet, T., Haarsma, R., Huybrechts, P., Jongma, J., Mouchet, A., Selten, F., Barriat, P.-Y., Campin, J.-M., Deleersnijder, E., Driesschaert, E., Goelzer, H., Janssens, I., Loutre, M.-F., Morales Maqueda, M. A., Opsteegh, T., Mathieu, P.-P., Munhoven, G., Pettersson, E. J., Renssen, H., Roche, D. M., Schaeffer, M., Tartinville, B., Timmermann, A., and Weber, S. L.: Description of the Earth system model of intermediate complexity LOVECLIM version 1.2, Geosci. Model Dev., 3, 603–633, https://doi.org/10.5194/gmd-3-603-2010, 2010. a
Greve, R.: Application of a Polythermal Three-Dimensional Ice Sheet Model to
the Greenland Ice Sheet: Response to Steady-State and Transient Climate
Scenarios, J. Climate, 10, 901–918,
https://doi.org/10.1175/1520-0442(1997)010<0901:AOAPTD>2.0.CO;2, 1997. a
Griffies, S. M.: The Gent–McWilliams Skew Flux, J. Phys.
Oceanogr., 28, 831–841,
https://doi.org/10.1175/1520-0485(1998)028<0831:TGMSF>2.0.CO;2, 1998. a
Hansen, J.: Efficacy of climate forcings, J. Geophys. Res.,
110, D18104, https://doi.org/10.1029/2005JD005776, 2005. a
Hansen, J., Russell, G., Rind, D., Stone, P., Lacis, A., Lebedeff, S., Ruedy,
R., and Travis, L.: Efficient Three-Dimensional Global Models for Climate
Studies: Models I and II, Mon. Weather Rev., 111, 609–662,
https://doi.org/10.1175/1520-0493(1983)111<0609:ETDGMF>2.0.CO;2, 1983. a, b
Hawkins, E., Smith, R. S., Allison, L. C., Gregory, J. M., Woollings, T. J.,
Pohlmann, H., and De Cuevas, B.: Bistability of the Atlantic overturning
circulation in a global climate model and links to ocean freshwater
transport, Geophys. Res. Lett., 38, 1–6,
https://doi.org/10.1029/2011GL047208, 2011. a
Held, I. M.: Stationary and quasi-stationary eddies in the extratropical
troposphere: Theory, in: Large-Scale Dynamical Processes in the Atmosphere,
edited by: Hoskins, B. and Pearce, R. P., Academic Press, 127–168, ISBN-10 0123566800, ISBN-13 978-0123566805, 1983. a
Held, I. M. and Soden, B. J.: Robust Responses of the Hydrological Cycle to
Global Warming, J. Climate, 19, 5686–5699,
https://doi.org/10.1175/JCLI3990.1, 2006. a
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 monthly averaged data on single levels from 1959 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.f17050d7, 2019. 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.
Meteorol. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020. a
Hibler, W. D.: A Dynamic Thermodynamic Sea Ice Model, J. Phys.
Oceanogr., 9, 815–846,
https://doi.org/10.1175/1520-0485(1979)009<0815:ADTSIM>2.0.CO;2, 1979. a, b
Holden, P. B., Edwards, N. R., Fraedrich, K., Kirk, E., Lunkeit, F., and Zhu, X.: PLASIM–GENIE v1.0: a new intermediate complexity AOGCM, Geosci. Model Dev., 9, 3347–3361, https://doi.org/10.5194/gmd-9-3347-2016, 2016. a, b
Holton, J. R.: Chapter 7 Atmospheric oscillations: Linear perturbation
theory, in: An Introduction to Dynamic Meteorology, edited by: Holton, J. R., vol. 88, Academic Press, 182–227,
https://doi.org/10.1016/S0074-6142(04)80041-X, 2004. a
Hoskins, B. J. and Valdes, P. J.: On the Existence of Storm-Tracks, J. Atmos. Sci., 47, 1854–1864,
https://doi.org/10.1175/1520-0469(1990)047<1854:OTEOST>2.0.CO;2, 1990. a, b
Hu, Y., Huang, H., and Zhou, C.: Widening and weakening of the Hadley
circulation under global warming, Sci. Bull., 63, 640–644,
https://doi.org/10.1016/j.scib.2018.04.020, 2018. a
Hunke, E. C. and Dukowicz, J. K.: An elastic-viscous-plastic model for sea ice
dynamics, J. Phys. Oceanogr., 27, 1849–1867,
https://doi.org/10.1175/1520-0485(1997)027<1849:AEVPMF>2.0.CO;2, 1997. a, b
Ilyina, T., Six, K. D., Segschneider, J., Maier-Reimer, E., Li, H., and
Núñez-Riboni, I.: Global ocean biogeochemistry model HAMOCC:
Model architecture and performance as component of the MPI-Earth system model
in different CMIP5 experimental realizations, J. Adv.
Model. Earth Sy., 5, 287–315, https://doi.org/10.1029/2012MS000178, 2013. a
IPCC: Annex II: Climate System Scenario Tables, edited by: Prather, M., Flato, G., Friedlingstein, P., Jones, C., Lamarque, J.-F., Liao, H., and Rasch, P., 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., Cambridge
University Press, Cambridge, United Kingdom and New York, NY, USA, 1395–1446, https://doi.org/10.1017/CBO9781107415324.030, 2013. a
IPCC: 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, in press, https://doi.org/10.1017/9781009157896, 2021. a
Jackett, D. R. and McDougall, T. J.: Minimal Adjustment of Hydrographic
Profiles to Achieve Static Stability, J. Atmos. Ocean. Tech., 12, 381–389,
https://doi.org/10.1175/1520-0426(1995)012<0381:maohpt>2.0.co;2, 1995. a, b
Jackson, L. C., Kahana, R., Graham, T., Ringer, M. A., Woollings, T., Mecking,
J. V., and Wood, R. A.: Global and European climate impacts of a slowdown of
the AMOC in a high resolution GCM, Clim. Dynam., 45, 3299–3316,
https://doi.org/10.1007/s00382-015-2540-2, 2015. a
Johns, W. E., Baringer, M. O., Beal, L. M., Cunningham, S. A., Kanzow, T.,
Bryden, H. L., Hirschi, J. J., Marotzke, J., Meinen, C. S., Shaw, B., and
Curry, R.: Continuous, array-based estimates of atlantic ocean heat
transport at 26.5∘ N, J. Climate, 24, 2429–2449,
https://doi.org/10.1175/2010JCLI3997.1, 2011. a
Kageyama, M., Albani, S., Braconnot, P., Harrison, S. P., Hopcroft, P. O., Ivanovic, R. F., Lambert, F., Marti, O., Peltier, W. R., Peterschmitt, J.-Y., Roche, D. M., Tarasov, L., Zhang, X., Brady, E. C., Haywood, A. M., LeGrande, A. N., Lunt, D. J., Mahowald, N. M., Mikolajewicz, U., Nisancioglu, K. H., Otto-Bliesner, B. L., Renssen, H., Tomas, R. A., Zhang, Q., Abe-Ouchi, A., Bartlein, P. J., Cao, J., Li, Q., Lohmann, G., Ohgaito, R., Shi, X., Volodin, E., Yoshida, K., Zhang, X., and Zheng, W.: The PMIP4 contribution to CMIP6 – Part 4: Scientific objectives and experimental design of the PMIP4-CMIP6 Last Glacial Maximum experiments and PMIP4 sensitivity experiments, Geosci. Model Dev., 10, 4035–4055, https://doi.org/10.5194/gmd-10-4035-2017, 2017. a
Kageyama, M., Harrison, S. P., Kapsch, M.-L., Lofverstrom, M., Lora, J. M., Mikolajewicz, U., Sherriff-Tadano, S., Vadsaria, T., Abe-Ouchi, A., Bouttes, N., Chandan, D., Gregoire, L. J., Ivanovic, R. F., Izumi, K., LeGrande, A. N., Lhardy, F., Lohmann, G., Morozova, P. A., Ohgaito, R., Paul, A., Peltier, W. R., Poulsen, C. J., Quiquet, A., Roche, D. M., Shi, X., Tierney, J. E., Valdes, P. J., Volodin, E., and Zhu, J.: The PMIP4 Last Glacial Maximum experiments: preliminary results and comparison with the PMIP3 simulations, Clim. Past, 17, 1065–1089, https://doi.org/10.5194/cp-17-1065-2021, 2021. a, b, c
Klemann, V., Martinec, Z., and Ivins, E. R.: Glacial isostasy and plate
motion, J. Geodyn., 46, 95–103,
https://doi.org/10.1016/j.jog.2008.04.005, 2008. a
Köhler, P., Nehrbass-Ahles, C., Schmitt, J., Stocker, T. F., and Fischer, H.: A 156 kyr smoothed history of the atmospheric greenhouse gases CO2, CH4, and N2O and their radiative forcing, Earth Syst. Sci. Data, 9, 363–387, https://doi.org/10.5194/essd-9-363-2017, 2017. a
Krapp, M., Robinson, A., and Ganopolski, A.: SEMIC: an efficient surface energy and mass balance model applied to the Greenland ice sheet, The Cryosphere, 11, 1519–1535, https://doi.org/10.5194/tc-11-1519-2017, 2017. a, b
Kraus, E. B. and Turner, J. S.: A one-dimensional model of the seasonal
thermocline II. The general theory and its consequences, Tellus, 19,
98–106, https://doi.org/10.3402/tellusa.v19i1.9753, 1967. a, b
Lacis, A. A. and Hansen, J.: A Parameterization for the Absorption of Solar
Radiation in the Earth's Atmosphere, J. Atmos. Sci.,
31, 118–133, https://doi.org/10.1175/1520-0469(1974)031<0118:APFTAO>2.0.CO;2, 1974. a
Lenton, T. M., Marsh, R., Price, A. R., Lunt, D. J., Aksenov, Y., Annan, J. D.,
Cooper-Chadwick, T., Cox, S. J., Edwards, N. R., Goswami, S., Hargreaves,
J. C., Harris, P. P., Jiao, Z., Livina, V. N., Payne, A. J., Rutt, I. C.,
Shepherd, J. G., Valdes, P. J., Williams, G., Williamson, M. S., and Yool,
A.: Effects of atmospheric dynamics and ocean resolution on bi-stability of
the thermohaline circulation examined using the Grid ENabled Integrated Earth
system modelling (GENIE) framework, Clim. Dynam., 29, 591–613,
https://doi.org/10.1007/s00382-007-0254-9, 2007. a
Levis, S., Foley, J. A., and Pollard, D.: Potential high-latitude vegetation
feedbacks on CO2-induced climate change, Geophys. Res. Lett., 26,
747–750, https://doi.org/10.1029/1999GL900107, 1999. a
Levitus, S., Antonov, J. I., Boyer, T. P., Baranova, O. K., Garcia, H. E.,
Locarnini, R. A., Mishonov, A. V., Reagan, J. R., Seidov, D., Yarosh, E. S.,
and Zweng, M. M.: World ocean heat content and thermosteric sea level change
(0–2000 m), 1955–2010, Geophys. Res. Lett., 39, 1–5,
https://doi.org/10.1029/2012GL051106, 2012. a, b
Levitus, S., Boyer, T. P., and Garcia, Hernan E. Locarnini, Ricardo A. Zweng,
Melissa M. Mishonov, Alexey V. Reagan, James R. Antonov, John I. Baranova,
Olga K. Biddle, Mathew Hamilton, Melanie Johnson, Daphne R. Paver,
Christopher R. Seidov, D.: World Ocean Atlas 2013 (NCEI Accession
0114815), NCEI [data set], https://doi.org/10.7289/v5f769gt, 2015. a, b
Lhardy, F., Bouttes, N., Roche, D. M., Crosta, X., Waelbroeck, C., and Paillard, D.: Impact of Southern Ocean surface conditions on deep ocean circulation during the LGM: a model analysis, Clim. Past, 17, 1139–1159, https://doi.org/10.5194/cp-17-1139-2021, 2021. a, b
Loeb, N. G., Doelling, D. R., Wang, H., Su, W., Nguyen, C., Corbett, J. G.,
Liang, L., Mitrescu, C., Rose, F. G., and Kato, S.: Clouds and the Earth'S
Radiant Energy System (CERES) Energy Balanced and Filled (EBAF)
top-of-atmosphere (TOA) edition-4.0 data product, J. Climate, 31,
895–918, https://doi.org/10.1175/JCLI-D-17-0208.1, 2018. a, b, c, d, e
Lucazeau, F.: Analysis and Mapping of an Updated Terrestrial Heat Flow Data
Set, Geochem. Geophy. Geosy., 20, 4001–4024,
https://doi.org/10.1029/2019GC008389, 2019. a
Ma, L., Hurtt, G. C., Chini, L. P., Sahajpal, R., Pongratz, J., Frolking, S., Stehfest, E., Klein Goldewijk, K., O'Leary, D., and Doelman, J. C.: Global rules for translating land-use change (LUH2) to land-cover change for CMIP6 using GLM2, Geosci. Model Dev., 13, 3203–3220, https://doi.org/10.5194/gmd-13-3203-2020, 2020. a
Maier-Reimer, E. and Hasselmann, K.: Transport and storage of CO2 in the ocean
– an inorganic ocean-circulation carbon cycle model, Clim. Dynam.,
2, 63–90, https://doi.org/10.1007/BF01054491, 1987. a
Manabe, S. and Stouffer, R. J.: Two Stable Equilibria of a Coupled
Ocean-Atmosphere Model, J. Climate, 841–866,
https://doi.org/10.1175/1520-0442(1988)001<0841:TSEOAC>2.0.CO;2, 1988. a
Marsh, R., Müller, S. A., Yool, A., and Edwards, N. R.: Incorporation of the C-GOLDSTEIN efficient climate model into the GENIE framework: “eb_go_gs” configurations of GENIE, Geosci. Model Dev., 4, 957–992, https://doi.org/10.5194/gmd-4-957-2011, 2011. a, b
Marsland, S., Haak, H., Jungclaus, J., Latif, M., and Röske, F.: The
Max-Planck-Institute global ocean/sea ice model with orthogonal curvilinear
coordinates, Ocean Model., 5, 91–127,
https://doi.org/10.1016/S1463-5003(02)00015-X, 2003. a
Martinec, Z., Klemann, V., van der Wal, W., Riva, R. E., Spada, G., Sun, Y.,
Melini, D., Kachuck, S. B., Barletta, V., Simon, K., A, G., and James, T. S.:
A benchmark study of numerical implementations of the sea level equation in
GIA modelling, Geophys. J. Int., 215, 389–414,
https://doi.org/10.1093/gji/ggy280, 2018. a
Matthes, K., Funke, B., Andersson, M. E., Barnard, L., Beer, J., Charbonneau, P., Clilverd, M. A., Dudok de Wit, T., Haberreiter, M., Hendry, A., Jackman, C. H., Kretzschmar, M., Kruschke, T., Kunze, M., Langematz, U., Marsh, D. R., Maycock, A. C., Misios, S., Rodger, C. J., Scaife, A. A., Seppälä, A., Shangguan, M., Sinnhuber, M., Tourpali, K., Usoskin, I., van de Kamp, M., Verronen, P. T., and Versick, S.: Solar forcing for CMIP6 (v3.2), Geosci. Model Dev., 10, 2247–2302, https://doi.org/10.5194/gmd-10-2247-2017, 2017. a
Mauritsen, T., Stevens, B., Roeckner, E., Crueger, T., Esch, M., Giorgetta, M.,
Haak, H., Jungclaus, J., Klocke, D., Matei, D., Mikolajewicz, U., Notz, D.,
Pincus, R., Schmidt, H., and Tomassini, L.: Tuning the climate of a global
model, J. Adv. Model. Earth Sy., 4, 1–18,
https://doi.org/10.1029/2012MS000154, 2012. a
McManus, J. F., Francois, R., Gherardi, J.-M., Keigwin, L. D., and Brown-Leger,
S.: Collapse and rapid resumption of Atlantic meridional circulation linked
to deglacial climate changes., Nature, 428, 834–837,
https://doi.org/10.1038/nature02494, 2004. a
McPhee, M. G.: Turbulent heat flux in the upper ocean under sea ice, J. Geophys. Res., 97, 5365–5379, https://doi.org/10.1029/92JC00239, 1992. a, b
Meier, W. N., Fetterer, F., Windnagel, A., and Stewart, J.: NOAA/NSIDC Climate
Data Record of Passive Microwave Sea Ice Concentration, Version 4, National Snow & Ice Data Center [data set],
https://doi.org/10.7265/efmz-2t65, 2021. a, b
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
Millero, F. J. and Poisson, A.: International one-atmosphere equation of state
of seawater, Deep-Sea Res. Pt. I, 28,
625–629, https://doi.org/10.1016/0198-0149(81)90122-9, 1981. a, b, c
Montoya, M., Griesel, A., Levermann, A., Mignot, J., Hofmann, M., Ganopolski,
A., and Rahmstorf, S.: The earth system model of intermediate complexity
CLIMBER-3α. Part I: Description and performance for present-day conditions,
Clim. Dynam., 25, 237–263, https://doi.org/10.1007/s00382-005-0044-1, 2005. a
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.-Atmos., 117, 1–22, https://doi.org/10.1029/2011JD017187, 2012. a, b
Müller, S. A., Joos, F., Edwards, N. R., and Stocker, T. F.: Water Mass
Distribution and Ventilation Time Scales in a Cost-Efficient,
Three-Dimensional Ocean Model, J. Climate, 19, 5479–5499,
https://doi.org/10.1175/JCLI3911.1, 2006. a, b, c, d
Myhre, G., Highwood, E. J., Shine, K. P., and Stordal, F.: New estimates of
radiative forcing due to well mixed greenhouse gases, Geophys. Res.
Lett., 25, 2715–2718, https://doi.org/10.1029/98GL01908, 1998. a
Nadeau, L. P., Ferrari, R., and Jansen, M. F.: Antarctic sea ice control on
the depth of North Atlantic deep water, J. Climate, 32, 2537–2551,
https://doi.org/10.1175/JCLI-D-18-0519.1, 2019. a
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
Niu, G. Y. and Yang, Z. L.: An observation-based formulation of snow cover
fraction and its evaluation over large North American river basins, J. Geophys. Res.-Atmos., 112, 1–14, https://doi.org/10.1029/2007JD008674,
2007. a
Oleson, K. W., Lawrence, D. M., Bonan, G. B., Drewniak, B., Huang, M., Charles,
D., Levis, S., Li, F., Riley, W. J., Zachary, M., Swenson, S. C., Thornton,
P. E., Bozbiyik, A., Fisher, R., Heald, C. L., Kluzek, E., Lamarque, F.,
Lawrence, P. J., Leung, L. R., Muszala, S., Ricciuto, D. M., Sacks, W., Sun,
Y., Tang, J., and Yang, Z.-L.: Technical Description of version 4.5 of the
Community Land Model (CLM) Coordinating, Tech. Rep., No. NCAR/TN-503+STR, https://doi.org/10.5065/D6RR1W7M, 2013. a
Orr, J. C., Najjar, R. G., Aumont, O., Bopp, L., Bullister, J. L., Danabasoglu, G., Doney, S. C., Dunne, J. P., Dutay, J.-C., Graven, H., Griffies, S. M., John, J. G., Joos, F., Levin, I., Lindsay, K., Matear, R. J., McKinley, G. A., Mouchet, A., Oschlies, A., Romanou, A., Schlitzer, R., Tagliabue, A., Tanhua, T., and Yool, A.: Biogeochemical protocols and diagnostics for the CMIP6 Ocean Model Intercomparison Project (OMIP), Geosci. Model Dev., 10, 2169–2199, https://doi.org/10.5194/gmd-10-2169-2017, 2017. a
Paul, A., Mulitza, S., Stein, R., and Werner, M.: A global climatology of the ocean surface during the Last Glacial Maximum mapped on a regular grid (GLOMAP), Clim. Past, 17, 805–824, https://doi.org/10.5194/cp-17-805-2021, 2021. a, b
Pedro, J. B., Jochum, M., Buizert, C., He, F., Barker, S., and Rasmussen,
S. O.: Beyond the bipolar seesaw: Toward a process understanding of
interhemispheric coupling, Quaternary Sci. Rev., 192, 27–46,
https://doi.org/10.1016/j.quascirev.2018.05.005, 2018. a
Petoukhov, V., Ganopolski, A., Brovkin, V., Claussen, M., Eliseev, A.,
Kubatzki, C., and Rahmstorf, S.: CLIMBER-2: a climate system model of
intermediate complexity. Part I: model description and performance for
present climate, Clim. Dynam., 16, 1–17, https://doi.org/10.1007/PL00007919,
2000. a, b, c, d, e, f, g, h, i, j, k
Pinardi, N., Rosati, A., and Pacanowski, R. C.: The sea surface pressure
formulation of rigid lid models. Implications for altimetric data
assimilation studies, J. Marine Syst., 6, 109–119,
https://doi.org/10.1016/0924-7963(94)00011-Y, 1995. a
Planchon, O. and Darboux, F.: A fast, simple and versatile algorithm to fill
the depressions of digital elevation models, Catena, 46, 159–176,
https://doi.org/10.1016/S0341-8162(01)00164-3, 2002. a
Rahmstorf, S.: Bifurcations of the Atlantic thermohaline circulation in
response to changes in the hydrological cycle, Nature, 378, 145–149,
https://doi.org/10.1038/378145a0, 1995. a
Rahmstorf, S., Crucifix, M., Ganopolski, A., Goosse, H., Kamenkovich, I.,
Knutti, R., Lohmann, G., Marsh, R., Mysak, L. A., Wang, Z., and Weaver,
A. J.: Thermohaline circulation hysteresis: A model intercomparison,
Geophys. Res. Lett., 32, L23605, https://doi.org/10.1029/2005GL023655, 2005. a, b
Redi, M. H.: Oceanic isopycnal mixing by coordinate rotation, J.
Phys. Oceanogr., 12, 1154–1158,
https://doi.org/10.1175/1520-0485(1982)012<1154:OIMBCR>2.0.CO;2, 1982. a
Ritz, S. P., Stocker, T. F., and Joos, F.: A coupled dynamical ocean-energy
balance atmosphere model for paleoclimate studies, J. Climate, 24,
349–375, https://doi.org/10.1175/2010JCLI3351.1, 2011. a
Robinson, A. and Perrette, M.: NCIO 1.0: a simple Fortran NetCDF interface, Geosci. Model Dev., 8, 1877–1883, https://doi.org/10.5194/gmd-8-1877-2015, 2015. a
Robinson, A., Alvarez-Solas, J., Montoya, M., Goelzer, H., Greve, R., and Ritz, C.: Description and validation of the ice-sheet model Yelmo (version 1.0), Geosci. Model Dev., 13, 2805–2823, https://doi.org/10.5194/gmd-13-2805-2020, 2020. a
Roesch, A., Wild, M., Gilgen, H., and Ohmura, A.: A new snow cover fraction
parameterization for the ECHAM4 GCM, Clim. Dynam., 17, 933–946,
https://doi.org/10.1007/s003820100153, 2001. a, b
Rossow, W. B. and Schiffer, R. A.: Advances in Understanding Clouds from
ISCCP, B. Am. Meteorol. Soc., 80, 2261–2287,
https://doi.org/10.1175/1520-0477(1999)080<2261:AIUCFI>2.0.CO;2, 1999. a, b
Schaffer, J., Timmermann, R., Arndt, J. E., Kristensen, S. S., Mayer, C., Morlighem, M., and Steinhage, D.: A global, high-resolution data set of ice sheet topography, cavity geometry, and ocean bathymetry, Earth Syst. Sci. Data, 8, 543–557, https://doi.org/10.5194/essd-8-543-2016, 2016. a
Semtner, A. J.: A Model for the Thermodynamic Growth of Sea Ice in Numerical
Investigations of Climate, J. Phys. Oceanogr., 6, 379–389,
https://doi.org/10.1175/1520-0485(1976)006<0379:AMFTTG>2.0.CO;2, 1976. a, b, c
Shin, S. I., Liu, Z., Otto-Bliesner, B. L., Kutzbach, J. E., and Vavrus, S. J.:
Southern Ocean sea-ice control of the glacial North Atlantic thermohaline
circulation, Geophys. Res. Lett., 30, 68–71,
https://doi.org/10.1029/2002GL015513, 2003. a
Smith, C. J., Kramer, R. J., Myhre, G., Forster, P. M., Soden, B. J., Andrews,
T., Boucher, O., Faluvegi, G., Fläschner, D., Hodnebrog, Kasoar, M.,
Kharin, V., Kirkevåg, A., Lamarque, J. F., Mülmenstädt, J.,
Olivié, D., Richardson, T., Samset, B. H., Shindell, D., Stier, P.,
Takemura, T., Voulgarakis, A., and Watson-Parris, D.: Understanding Rapid
Adjustments to Diverse Forcing Agents, Geophys. Res. Lett., 45,
12023–12031, https://doi.org/10.1029/2018GL079826, 2018. a, b, c, d
Smith, R. S., Gregory, J. M., and Osprey, A.: A description of the FAMOUS (version XDBUA) climate model and control run, Geosci. Model Dev., 1, 53–68, https://doi.org/10.5194/gmd-1-53-2008, 2008. a
Stommel, H.: Thermohaline Convection with Two Stable Regimes of Flow, Tellus,
13, 224–230, https://doi.org/10.1111/j.2153-3490.1961.tb00079.x, 1961. a
Stouffer, R. J. and Manabe, S.: Equilibrium response of thermohaline
circulation to large changes in atmospheric CO2 concentration, Clim.
Dynam., 20, 759–773, https://doi.org/10.1007/s00382-002-0302-4, 2003. a
Subin, Z. M., Riley, W. J., and Mironov, D.: An improved lake model for
climate simulations: Model structure, evaluation, and sensitivity analyses in
CESM1, J. Adv. Model. Earth Sy., 4, 1–27,
https://doi.org/10.1029/2011MS000072, 2012. a
Tarasov, L., Dyke, A. S., Neal, R. M., and Peltier, W. R.: A data-calibrated
distribution of deglacial chronologies for the North American ice complex
from glaciological modeling, Earth Planet. Sc. Lett., 315–316,
30–40, https://doi.org/10.1016/j.epsl.2011.09.010, 2012. a
Tarnocai, C., Canadell, J. G., Schuur, E. a. G., Kuhry, P., Mazhitova, G., and
Zimov, S.: Soil organic carbon pools in the northern circumpolar permafrost
region, Global Biogeochem. Cy., 23, 2,
https://doi.org/10.1029/2008GB003327, 2009. a
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
Tierney, J. E., Zhu, J., King, J., Malevich, S. B., Hakim, G. J., and Poulsen,
C. J.: Glacial cooling and climate sensitivity revisited, Nature, 584,
569–573, https://doi.org/10.1038/s41586-020-2617-x, 2020. a, b, c
Trenberth, K. E. and Caron, J. M.: Estimates of Meridional Atmosphere and
Ocean Heat Transports, J. Climate, 14, 3433–3443,
https://doi.org/10.1175/1520-0442(2001)014<3433:EOMAAO>2.0.CO;2, 2001. a
Trenberth, K. E., Smith, L., Qian, T., Dai, A., and Fasullo, J.: Estimates of
the Global Water Budget and Its Annual Cycle Using Observational and Model
Data, J. Hydrometeorol., 8, 758–769, https://doi.org/10.1175/JHM600.1,
2007. a
Vavrus, S. and Waliser, D.: An improved parameterization for simulating Arctic
cloud amount in the CCSM3 climate model, J. Climate, 21, 5673–5687,
https://doi.org/10.1175/2008JCLI2299.1, 2008. a
Vellinga, M. and Wood, R. A.: Global climatic impacts of a collapse of the
atlantic thermohaline circulation, Climatic Change, 54, 251–267,
https://doi.org/10.1023/A:1016168827653, 2002. a
Weaver, A. J., Eby, M., Wiebe, E. C., Ewen, T. L., Fanning, A. F., MacFadyen,
A., Matthews, H. D., Meissner, K. J., Saenko, O., Schmittner, A., Yoshimori,
M., Bitz, C. M., Holland, M. M., Duffy, P. B., and Wang, H.: The UVic earth
system climate model: Model description, climatology, and applications to
past, present and future climates, Atmos. Ocean, 39, 361–428,
https://doi.org/10.1080/07055900.2001.9649686, 2001. a, b, c
Weber, S. L., Drijfhout, S. S., Abe-Ouchi, A., Crucifix, M., Eby, M., Ganopolski, A., Murakami, S., Otto-Bliesner, B., and Peltier, W. R.: The modern and glacial overturning circulation in the Atlantic ocean in PMIP coupled model simulations, Clim. Past, 3, 51–64, https://doi.org/10.5194/cp-3-51-2007, 2007. a
Weijer, W., Cheng, W., Drijfhout, S. S., Fedorov, A. V., Hu, A., Jackson,
L. C., Liu, W., McDonagh, E. L., Mecking, J. V., and Zhang, J.: Stability of
the Atlantic Meridional Overturning Circulation: A Review and Synthesis,
J. Geophys. Res.-Oceans, 124, 5336–5375,
https://doi.org/10.1029/2019JC015083, 2019. a
Wetherald, R. T. and Manabe, S.: Cloud Feedback Processes in a General
Circulation Model, J. Atmos. Sci., 45, 1397–1416,
https://doi.org/10.1175/1520-0469(1988)045<1397:CFPIAG>2.0.CO;2, 1988. a
Wild, M., Folini, D., Schär, C., Loeb, N., Dutton, E. G., and
König-Langlo, G.: The global energy balance from a surface
perspective, Clim. Dynam., 40, 3107–3134,
https://doi.org/10.1007/s00382-012-1569-8, 2013. a
Willeit, M.: CLIMBER-X v1.0, Zenodo [code], https://doi.org/10.5281/zenodo.6877358, 2022. a
Willeit, M., Ganopolski, A., and Feulner, G.: Asymmetry and uncertainties in biogeophysical climate–vegetation feedback over a range of CO2 forcings, Biogeosciences, 11, 17–32, https://doi.org/10.5194/bg-11-17-2014, 2014. a
Willeit, M., Ganopolski, A., Calov, R., and Brovkin, V.: Mid-Pleistocene
transition in glacial cycles explained by declining CO2 and regolith
removal, Science Advances, 5, eaav7337, https://doi.org/10.1126/sciadv.aav7337, 2019. a
Yamamoto, G. and Tanaka, M.: Increase of Global Albedo Due to Air Pollution,
J. Atmos. Sci., 29, 1405–1412,
https://doi.org/10.1175/1520-0469(1972)029<1405:IOGADT>2.0.CO;2, 1972. a
Yang, H., Li, Q., Wang, K., Sun, Y., and Sun, D.: Decomposing the meridional
heat transport in the climate system, Clim. Dynam., 44, 2751–2768,
https://doi.org/10.1007/s00382-014-2380-5, 2015. a
Yin, J., Stouffer, R. J., Spelman, M. J., and Griffies, S. M.: Evaluating the
uncertainty induced by the virtual salt flux assumption in climate
simulations and future projections, J. Climate, 23, 80–96,
https://doi.org/10.1175/2009JCLI3084.1, 2010. a
Zalesak, S. T.: Fully multidimensional flux-corrected transport algorithms for
fluids, J. Comput. Phys., 31, 335–362,
https://doi.org/10.1016/0021-9991(79)90051-2, 1979. a, b, c
Zelinka, M. D., Klein, S. A., and Hartmann, D. L.: Computing and partitioning
cloud feedbacks using cloud property histograms. Part II: Attribution to
changes in cloud amount, altitude, and optical depth, J. Climate,
25, 3736–3754, https://doi.org/10.1175/JCLI-D-11-00249.1, 2012.
a
Zelinka, M. D., Myers, T. A., McCoy, D. T., Po-Chedley, S., Caldwell, P. M.,
Ceppi, P., Klein, S. A., and Taylor, K. E.: Causes of Higher Climate
Sensitivity in CMIP6 Models, Geophys. Res. Lett., 47, e2019GL085782,
https://doi.org/10.1029/2019GL085782, 2020. a
Zika, J. D., Skliris, N., Blaker, A. T., Marsh, R., Nurser, A. J., and Josey,
S. A.: Improved estimates of water cycle change from ocean salinity: The key
role of ocean warming, Environ. Res. Lett., 13, 074036,
https://doi.org/10.1088/1748-9326/aace42, 2018. a, b
Short summary
In this paper we present the climate component of the newly developed fast Earth system model CLIMBER-X. It has a horizontal resolution of 5°x5° and is designed to simulate the evolution of the Earth system on temporal scales ranging from decades to >100 000 years. CLIMBER-X is available as open-source code and is expected to be a useful tool for studying past climate changes and for the investigation of the long-term future evolution of the climate.
In this paper we present the climate component of the newly developed fast Earth system model...