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
Chenzhi Li, Anne Dallmeyer, Jian Ni, Manuel Chevalier, Matteo Willeit, Andrei A. Andreev, Xianyong Cao, Laura Schild, Birgit Heim, and Ulrike Herzschuh
EGUsphere, https://doi.org/10.5194/egusphere-2024-1862, https://doi.org/10.5194/egusphere-2024-1862, 2024
This preprint is open for discussion and under review for Climate of the Past (CP).
Short summary
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We present a 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 areas and Tibetan Plateau during the Last Glacial Maximum and early deglaciation, as well as in North Africa and the Mediterranean regions during the Holocene.
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
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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 and Andrey Ganopolski
EGUsphere, https://doi.org/10.5194/egusphere-2024-1482, https://doi.org/10.5194/egusphere-2024-1482, 2024
Short summary
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Using a fast Earth system model we trace the stability landscape of the Atlantic Meridional Overturning Circulation (AMOC) in the combined freshwater forcing – atmospheric CO2 space. We find four different AMOC states that are stable under different conditions and a generally increasing equilibrium AMOC strength with increasing CO2 concentrations.
Matteo Willeit, Andrey Ganopolski, Neil R. Edwards, and Stefan Rahmstorf
EGUsphere, https://doi.org/10.5194/egusphere-2024-819, https://doi.org/10.5194/egusphere-2024-819, 2024
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Using an Earth system model that can simulate Dansgaard-Oeschger-like events, we show that the conditions under which millenial-scale climate variability occurs is related to the integrated surface buoyancy flux over the northern North-Atlantic. This newly defined buoyancy measure explains why millenial-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, 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
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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
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This paper maps out the state-of-the-art literature on interactions between tipping elements relevant for current global warming pathways. We find indications that many of the interactions between tipping elements are destabilizing. This means that tipping cascades cannot be ruled out on centennial to millennial timescales at global warming levels between 1.5 and 2.0 °C or on shorter timescales if global warming surpasses 2.0 °C.
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
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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
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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.
Johanna Beckmann, Mahé Perrette, Sebastian Beyer, Reinhard Calov, Matteo Willeit, and Andrey Ganopolski
The Cryosphere, 13, 2281–2301, https://doi.org/10.5194/tc-13-2281-2019, https://doi.org/10.5194/tc-13-2281-2019, 2019
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Submarine melting (SM) has been discussed as potentially triggering the recently observed retreat at outlet glaciers in Greenland. How much it may contribute in terms of future sea level rise (SLR) has not been quantified yet. When accounting for SM in our experiments, SLR contribution of 12 outlet glaciers increases by over 3-fold until the year 2100 under RCP8.5. Scaling up from 12 to all of Greenland's outlet glaciers increases future SLR contribution of Greenland by 50 %.
Reinhard Calov, Sebastian Beyer, Ralf Greve, Johanna Beckmann, Matteo Willeit, Thomas Kleiner, Martin Rückamp, Angelika Humbert, and Andrey Ganopolski
The Cryosphere, 12, 3097–3121, https://doi.org/10.5194/tc-12-3097-2018, https://doi.org/10.5194/tc-12-3097-2018, 2018
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We present RCP 4.5 and 8.5 projections for the Greenland glacial system with the new glacial system model IGLOO 1.0, which incorporates the ice sheet model SICOPOLIS 3.3, a model of basal hydrology and a parameterization of submarine melt of outlet glaciers. Surface temperature and mass balance anomalies from the MAR climate model serve as forcing delivering projections for the contribution of the Greenland ice sheet to sea level rise and submarine melt of Helheim and Store outlet glaciers.
Matteo Willeit and Andrey Ganopolski
Clim. Past, 14, 697–707, https://doi.org/10.5194/cp-14-697-2018, https://doi.org/10.5194/cp-14-697-2018, 2018
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The surface energy and mass balance of ice sheets strongly depends on surface albedo. Here, using an Earth system model of intermediate complexity, we explore the role played by surface albedo for the simulation of glacial cycles. We show that the evolution of the Northern Hemisphere ice sheets over the last glacial cycle is very sensitive to the parameterization of snow grain size and the effect of dust deposition on snow albedo.
Matteo Willeit and Andrey Ganopolski
Geosci. Model Dev., 9, 3817–3857, https://doi.org/10.5194/gmd-9-3817-2016, https://doi.org/10.5194/gmd-9-3817-2016, 2016
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PALADYN is presented; it is a new comprehensive and computationally efficient land surface–vegetation–carbon cycle model designed to be used in Earth system models of intermediate complexity for long-term simulations and paleoclimate studies.
M. Willeit and A. Ganopolski
Clim. Past, 11, 1165–1180, https://doi.org/10.5194/cp-11-1165-2015, https://doi.org/10.5194/cp-11-1165-2015, 2015
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In this paper we explore the permafrost–ice-sheet interaction using the fully coupled climate–ice-sheet model CLIMBER-2 with the addition of a newly developed permafrost module. We find that permafrost has a moderate but significant effect on ice sheet dynamics during the last glacial cycle. In particular at the Last Glacial Maximum the inclusion of permafrost leads to a 15m sea level equivalent increase in Northern Hemisphere ice volume when permafrost is included.
D. Dalmonech, A. M. Foley, A. Anav, P. Friedlingstein, A. D. Friend, M. Kidston, M. Willeit, and S. Zaehle
Biogeosciences Discuss., https://doi.org/10.5194/bgd-11-2083-2014, https://doi.org/10.5194/bgd-11-2083-2014, 2014
Revised manuscript has not been submitted
M. Willeit, A. Ganopolski, and G. Feulner
Biogeosciences, 11, 17–32, https://doi.org/10.5194/bg-11-17-2014, https://doi.org/10.5194/bg-11-17-2014, 2014
M. Willeit, A. Ganopolski, and G. Feulner
Clim. Past, 9, 1749–1759, https://doi.org/10.5194/cp-9-1749-2013, https://doi.org/10.5194/cp-9-1749-2013, 2013
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.
Chenzhi Li, Anne Dallmeyer, Jian Ni, Manuel Chevalier, Matteo Willeit, Andrei A. Andreev, Xianyong Cao, Laura Schild, Birgit Heim, and Ulrike Herzschuh
EGUsphere, https://doi.org/10.5194/egusphere-2024-1862, https://doi.org/10.5194/egusphere-2024-1862, 2024
This preprint is open for discussion and under review for Climate of the Past (CP).
Short summary
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We present a 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 areas and Tibetan Plateau during the Last Glacial Maximum and early deglaciation, as well as in North Africa and the Mediterranean regions during the Holocene.
Sergio Pérez-Montero, Jorge Alvarez-Solas, Jan Swierczek-Jereczek, Daniel Moreno-Parada, Marisa Montoya, and Alexander Robinson
EGUsphere, https://doi.org/10.5194/egusphere-2024-1842, https://doi.org/10.5194/egusphere-2024-1842, 2024
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The climate of the last 3 Myr varies 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 find that the main trigger is the displacement of the lithosphere due to the ice thickness evolution, but reproducing the climate records additionally requires the natural darkening of ice.
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 and Andrey Ganopolski
EGUsphere, https://doi.org/10.5194/egusphere-2024-1482, https://doi.org/10.5194/egusphere-2024-1482, 2024
Short summary
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Using a fast Earth system model we trace the stability landscape of the Atlantic Meridional Overturning Circulation (AMOC) in the combined freshwater forcing – atmospheric CO2 space. We find four different AMOC states that are stable under different conditions and a generally increasing equilibrium AMOC strength with increasing CO2 concentrations.
Matteo Willeit, Andrey Ganopolski, Neil R. Edwards, and Stefan Rahmstorf
EGUsphere, https://doi.org/10.5194/egusphere-2024-819, https://doi.org/10.5194/egusphere-2024-819, 2024
Short summary
Short summary
Using an Earth system model that can simulate Dansgaard-Oeschger-like events, we show that the conditions under which millenial-scale climate variability occurs is related to the integrated surface buoyancy flux over the northern North-Atlantic. This newly defined buoyancy measure explains why millenial-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, 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
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This paper maps out the state-of-the-art literature on interactions between tipping elements relevant for current global warming pathways. We find indications that many of the interactions between tipping elements are destabilizing. This means that tipping cascades cannot be ruled out on centennial to millennial timescales at global warming levels between 1.5 and 2.0 °C or on shorter timescales if global warming surpasses 2.0 °C.
Therese Rieckh, Andreas Born, Alexander Robinson, Robert Law, and Gerrit Gülle
EGUsphere, https://doi.org/10.5194/egusphere-2023-3127, https://doi.org/10.5194/egusphere-2023-3127, 2024
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We present the open-source model ELSA, which simulates the internal age structure of large ice sheets. ELSA is used coupled to a full ice sheet model and creates individual layers of accumulation with fixed time stamps during the simulation, modeling 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 parametrization.
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.
Antonio Juarez-Martinez, Javier Blasco, Alexander Robinson, Marisa Montoya, and Jorge Alvarez-Solas
EGUsphere, https://doi.org/10.5194/egusphere-2023-2863, https://doi.org/10.5194/egusphere-2023-2863, 2024
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We present sea-level projections for Antarctica in the context of ISMIP6-2300 with several forcings, but extending the simulations until 2500, and showing that more than 3 metres 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.
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.
Daniel Moreno-Parada, Alexander Robinson, Marisa Montoya, and Jorge Alvarez-Solas
EGUsphere, https://doi.org/10.5194/egusphere-2023-2690, https://doi.org/10.5194/egusphere-2023-2690, 2023
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We introduce Nix, an ice-sheet model designed for understanding how large masses of ice behave. Nix as a computer program that simulates the movement and temperature changes in ice sheets. Nix helps us study how ice sheets respond to changes in the atmosphere and ocean. We found that how fast ice melts under the shelves and how heat is exchanged, play a role in determining the future of ice sheets. Nix is a useful tool for learning more about how climate change affects polar ice sheets.
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
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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.
Javier Blasco, Ilaria Tabone, Daniel Moreno-Parada, Alexander Robinson, Jorge Alvarez-Solas, Frank Pattyn, and Marisa Montoya
Clim. Past Discuss., https://doi.org/10.5194/cp-2023-76, https://doi.org/10.5194/cp-2023-76, 2023
Revised manuscript accepted for CP
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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.
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.
Daniel Moreno, Alexander Robinson, Marisa Montoya, and Jorge Alvarez-Solas
The Cryosphere Discuss., https://doi.org/10.5194/tc-2022-97, https://doi.org/10.5194/tc-2022-97, 2022
Preprint under review for TC
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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.
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
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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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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.
Alexander Robinson, Jorge Alvarez-Solas, Marisa Montoya, Heiko Goelzer, Ralf Greve, and Catherine Ritz
Geosci. Model Dev., 13, 2805–2823, https://doi.org/10.5194/gmd-13-2805-2020, https://doi.org/10.5194/gmd-13-2805-2020, 2020
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Here we describe Yelmo v1.0, an intuitive and state-of-the-art hybrid ice sheet model. The model design and physics are described, and benchmark simulations are provided to validate its performance. Yelmo is a versatile ice sheet model that can be applied to a wide variety of problems.
Andreas Wernecke, Tamsin L. Edwards, Isabel J. Nias, Philip B. Holden, and Neil R. Edwards
The Cryosphere, 14, 1459–1474, https://doi.org/10.5194/tc-14-1459-2020, https://doi.org/10.5194/tc-14-1459-2020, 2020
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We investigate how the two-dimensional characteristics of ice thickness change from satellite measurements can be used to judge and refine a high-resolution ice sheet model of Antarctica. The uncertainty in 50-year model simulations for the currently most drastically changing part of Antarctica can be reduced by nearly 40 % compared to a simpler, non-spatial approach and nearly 90 % compared to the original spread in simulations.
Philip B. Holden, Neil R. Edwards, Thiago F. Rangel, Elisa B. Pereira, Giang T. Tran, and Richard D. Wilkinson
Geosci. Model Dev., 12, 5137–5155, https://doi.org/10.5194/gmd-12-5137-2019, https://doi.org/10.5194/gmd-12-5137-2019, 2019
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We describe the development of the Paleoclimate PLASIM-GENIE emulator and its application to derive a high-resolution spatio-temporal description of the climate of the last 5 x 106 years. Spatial fields of bioclimatic variables are emulated at 1000-year intervals, driven by time series of scalar boundary-condition forcing (CO2, orbit, and ice volume). Emulated anomalies are interpolated into modern climatology to produce a high-resolution climate reconstruction of the Pliocene–Pleistocene.
Jorge Alvarez-Solas, Marisa Montoya, and Alexander Robinson
Clim. Past Discuss., https://doi.org/10.5194/cp-2019-96, https://doi.org/10.5194/cp-2019-96, 2019
Publication in CP not foreseen
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Modelling the past abrupt climate changes often resorts to the use of freshwater flux (FWF) in the North Atlantic as an effective method to cause reorganizations of the Atlantic Meridional Overturning Circulation. This procedure has allowed to reproduce the timing of the events. However, the required FWF is inconsistent with reconstructions. Conversely, using a forcing derived from the sea-level record results in a poor fit with the data, highlighting the need of exploring other mechanisms.
Johanna Beckmann, Mahé Perrette, Sebastian Beyer, Reinhard Calov, Matteo Willeit, and Andrey Ganopolski
The Cryosphere, 13, 2281–2301, https://doi.org/10.5194/tc-13-2281-2019, https://doi.org/10.5194/tc-13-2281-2019, 2019
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Submarine melting (SM) has been discussed as potentially triggering the recently observed retreat at outlet glaciers in Greenland. How much it may contribute in terms of future sea level rise (SLR) has not been quantified yet. When accounting for SM in our experiments, SLR contribution of 12 outlet glaciers increases by over 3-fold until the year 2100 under RCP8.5. Scaling up from 12 to all of Greenland's outlet glaciers increases future SLR contribution of Greenland by 50 %.
Jamie D. Wilson, Stephen Barker, Neil R. Edwards, Philip B. Holden, and Andy Ridgwell
Biogeosciences, 16, 2923–2936, https://doi.org/10.5194/bg-16-2923-2019, https://doi.org/10.5194/bg-16-2923-2019, 2019
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The remains of plankton rain down from the surface ocean to the deep ocean, acting to store CO2 in the deep ocean. We used a model of biology and ocean circulation to explore the importance of this process in different regions of the ocean. The amount of CO2 stored in the deep ocean is most sensitive to changes in the Southern Ocean. As plankton in the Southern Ocean are likely those most impacted by future climate change, the amount of CO2 they store in the deep ocean could also be affected.
Ilaria Tabone, Alexander Robinson, Jorge Alvarez-Solas, and Marisa Montoya
The Cryosphere, 13, 1911–1923, https://doi.org/10.5194/tc-13-1911-2019, https://doi.org/10.5194/tc-13-1911-2019, 2019
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Recent reconstructions show that the North East Greenland Ice Stream (NEGIS) retreated away from its present-day position by 20–40 km during MIS-3. Atmospheric and external forcings were proposed as potential causes of this retreat, but the role of the ocean was not considered. Here, using a 3-D ice-sheet model, we suggest that oceanic warming is sufficient to induce a retreat of the NEGIS margin of many tens of kilometres during MIS-3, helping to explain this conundrum.
Krista M. S. Kemppinen, Philip B. Holden, Neil R. Edwards, Andy Ridgwell, and Andrew D. Friend
Clim. Past, 15, 1039–1062, https://doi.org/10.5194/cp-15-1039-2019, https://doi.org/10.5194/cp-15-1039-2019, 2019
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We simulate the Last Glacial Maximum atmospheric CO2 decrease with a large ensemble of parameter sets to investigate the range of possible physical and biogeochemical Earth system changes accompanying the CO2 decrease. Amongst the dominant ensemble changes is an increase in terrestrial carbon, which we attribute to a slower soil respiration rate, and the preservation of carbon by the LGM ice sheets. Further investigation into the role of terrestrial carbon is warranted.
Jorge Alvarez-Solas, Rubén Banderas, Alexander Robinson, and Marisa Montoya
Clim. Past, 15, 957–979, https://doi.org/10.5194/cp-15-957-2019, https://doi.org/10.5194/cp-15-957-2019, 2019
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The last glacial period was marked by the existence of of abrupt climatic changes; it is generally accepted that the presence of ice sheets played an important role in their occurrence. While an important effort has been made to investigate the dynamics and evolution of the Laurentide ice sheet during this period, the Eurasian ice sheet (EIS) has not received much attention. Here we investigate the response of the EIS to millennial-scale climate variability using a hybrid 3-D ice-sheet model.
Ilaria Tabone, Alexander Robinson, Jorge Alvarez-Solas, and Marisa Montoya
Clim. Past, 15, 593–609, https://doi.org/10.5194/cp-15-593-2019, https://doi.org/10.5194/cp-15-593-2019, 2019
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By using a 3-D hybrid ice-sheet–shelf model, we investigate the impact of millennial-scale oceanic variability on the Greenland Ice Sheet (GrIS) evolution during the last glacial period (LGP). We show that the GrIS may have strongly reacted to oceanic temperature fluctuations associated with Dansgaard–Oeschger cycles, contributing to sea-level variations of more than 1 m. Our results open the chance for a non-negligible role of the GrIS in millennial-scale oceanic reorganisations during the LGP.
Javier Blasco, Ilaria Tabone, Jorge Alvarez-Solas, Alexander Robinson, and Marisa Montoya
Clim. Past, 15, 121–133, https://doi.org/10.5194/cp-15-121-2019, https://doi.org/10.5194/cp-15-121-2019, 2019
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The LGP is a period punctuated by the presence of several abrupt climate events and sea-level variations of up to 20 m at millennial timescales. The origin of those fluctuations is attributed to NH paleo ice sheets, but a contribution from the AIS cannot be excluded. Here, for the first time, we investigate the response of the AIS to millennial climate variability using an ice sheet–shelf model. We shows that the AIS produces substantial sea-level rises and grounding line migrations.
Reinhard Calov, Sebastian Beyer, Ralf Greve, Johanna Beckmann, Matteo Willeit, Thomas Kleiner, Martin Rückamp, Angelika Humbert, and Andrey Ganopolski
The Cryosphere, 12, 3097–3121, https://doi.org/10.5194/tc-12-3097-2018, https://doi.org/10.5194/tc-12-3097-2018, 2018
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We present RCP 4.5 and 8.5 projections for the Greenland glacial system with the new glacial system model IGLOO 1.0, which incorporates the ice sheet model SICOPOLIS 3.3, a model of basal hydrology and a parameterization of submarine melt of outlet glaciers. Surface temperature and mass balance anomalies from the MAR climate model serve as forcing delivering projections for the contribution of the Greenland ice sheet to sea level rise and submarine melt of Helheim and Store outlet glaciers.
Rubén Banderas, Jorge Alvarez-Solas, Alexander Robinson, and Marisa Montoya
Geosci. Model Dev., 11, 2299–2314, https://doi.org/10.5194/gmd-11-2299-2018, https://doi.org/10.5194/gmd-11-2299-2018, 2018
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Here we present a new approach to force ice-sheet models offline, which accounts for a more realistic treatment of millennial-scale climate variability as compared to the existing methods. Our results reveal that an incorrect representation of the characteristic pattern of millennial-scale climate variability within the climate forcing not only affects NH ice-volume variations at millennial timescales but has consequences for glacial–interglacial ice-volume changes too.
Matteo Willeit and Andrey Ganopolski
Clim. Past, 14, 697–707, https://doi.org/10.5194/cp-14-697-2018, https://doi.org/10.5194/cp-14-697-2018, 2018
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The surface energy and mass balance of ice sheets strongly depends on surface albedo. Here, using an Earth system model of intermediate complexity, we explore the role played by surface albedo for the simulation of glacial cycles. We show that the evolution of the Northern Hemisphere ice sheets over the last glacial cycle is very sensitive to the parameterization of snow grain size and the effect of dust deposition on snow albedo.
Ilaria Tabone, Javier Blasco, Alexander Robinson, Jorge Alvarez-Solas, and Marisa Montoya
Clim. Past, 14, 455–472, https://doi.org/10.5194/cp-14-455-2018, https://doi.org/10.5194/cp-14-455-2018, 2018
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The response of the Greenland Ice Sheet (GrIS) to palaeo-oceanic changes on a glacial–interglacial timescale is studied from a modelling perspective. A 3-D hybrid ice-sheet–shelf model which includes a parameterization of the basal melting rate at the GrIS marine margins is used. The results show that the oceanic forcing plays a key role in the GrIS evolution, not only by controlling the ice retreat during the deglaciation but also by driving the ice expansion in glacial periods.
John S. Keery, Philip B. Holden, and Neil R. Edwards
Clim. Past, 14, 215–238, https://doi.org/10.5194/cp-14-215-2018, https://doi.org/10.5194/cp-14-215-2018, 2018
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In the Eocene (~ 55 million years ago), the Earth had high levels of atmospheric CO2, so studies of the Eocene can provide insights into the likely effects of present-day fossil fuel burning. We ran a low-resolution but very fast climate model with 50 combinations of CO2 and orbital parameters, and an Eocene layout of the oceans and continents. Climatic effects of CO2 are dominant but precession and obliquity strongly influence monsoon rainfall and ocean–land temperature contrasts, respectively.
Johanna Beckmann, Mahé Perrette, and Andrey Ganopolski
The Cryosphere, 12, 301–323, https://doi.org/10.5194/tc-12-301-2018, https://doi.org/10.5194/tc-12-301-2018, 2018
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Greenland's glaciers that are in contact with the ocean undergo a special ice–ocean melting. To project numerically Greenland's centennial contribution to sea level rise, it is crucial to incorporate this special melting. We demonstrate that a numerically cheap model shows the qualitative same behavior as numerical expensive 2–3-dimensional models and calculates the same melting as empirical data show. Our analytical solution gives some insight in the yet poorly understood melting behavior.
Andrey Ganopolski and Victor Brovkin
Clim. Past, 13, 1695–1716, https://doi.org/10.5194/cp-13-1695-2017, https://doi.org/10.5194/cp-13-1695-2017, 2017
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Ice cores reveal that atmospheric CO2 concentration varied synchronously with the global ice volume. Explaining the mechanism of glacial–interglacial variations of atmospheric CO2 concentrations and the link between CO2 and ice sheets evolution still remains a challenge. Here using the Earth system model of intermediate complexity we performed for the first time simulations of co-evolution of climate, ice sheets and carbon cycle using the astronomical forcing as the only external forcing.
Jorge Alvarez-Solas, Rubén Banderas, Alexander Robinson, and Marisa Montoya
Clim. Past Discuss., https://doi.org/10.5194/cp-2017-143, https://doi.org/10.5194/cp-2017-143, 2017
Revised manuscript not accepted
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The last glacial period was marked by the existence of of abrupt climatic changes. It is generally accepted that the presence of ice sheets played an
important role in their occurrence. While an important effort has been made to investigate the dynamics and evolution of the Laurentide Ice Sheet during this period, the Eurasian Ice Sheet (EIS) has not received much attention. Here we investigate the response of the EIS to millennial-scale climate variability. We use a hybrid 3D ice-sheet model.
Eva Bauer and Andrey Ganopolski
Clim. Past, 13, 819–832, https://doi.org/10.5194/cp-13-819-2017, https://doi.org/10.5194/cp-13-819-2017, 2017
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Transient glacial cycle simulations with an EMIC and the PDD method require smaller melt factors for inception than for termination and larger factors for American than European ice sheets. The PDD online method with standard values simulates a sea level drop of 250 m at the LGM. The PDD online run reproducing the LGM ice volume has deficient ablation for reversing from glacial to interglacial climate, so termination is delayed. The SEB method with dust impact on snow albedo is seen as superior.
Mario Krapp, Alexander Robinson, and Andrey Ganopolski
The Cryosphere, 11, 1519–1535, https://doi.org/10.5194/tc-11-1519-2017, https://doi.org/10.5194/tc-11-1519-2017, 2017
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We present the snowpack model SEMIC. It calculates snow height, surface temperature, surface albedo, and the surface mass balance of snow- and ice-covered surfaces while using meteorological data as input. In this paper we describe how SEMIC works and how well it compares with snowpack data of a more sophisticated regional climate model applied to the Greenland ice sheet. Because of its simplicity and efficiency, SEMIC can be used as a coupling interface between atmospheric and ice sheet models.
Matteo Willeit and Andrey Ganopolski
Geosci. Model Dev., 9, 3817–3857, https://doi.org/10.5194/gmd-9-3817-2016, https://doi.org/10.5194/gmd-9-3817-2016, 2016
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PALADYN is presented; it is a new comprehensive and computationally efficient land surface–vegetation–carbon cycle model designed to be used in Earth system models of intermediate complexity for long-term simulations and paleoclimate studies.
Philip B. Holden, Neil R. Edwards, Klaus Fraedrich, Edilbert Kirk, Frank Lunkeit, and Xiuhua Zhu
Geosci. Model Dev., 9, 3347–3361, https://doi.org/10.5194/gmd-9-3347-2016, https://doi.org/10.5194/gmd-9-3347-2016, 2016
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We describe the development, tuning and climate of PLASIM–GENIE, a new intermediate complexity Atmosphere–Ocean General Circulation Model (AOGCM), built by coupling the Planet Simulator to the GENIE Earth system model.
Giang T. Tran, Kevin I. C. Oliver, András Sóbester, David J. J. Toal, Philip B. Holden, Robert Marsh, Peter Challenor, and Neil R. Edwards
Adv. Stat. Clim. Meteorol. Oceanogr., 2, 17–37, https://doi.org/10.5194/ascmo-2-17-2016, https://doi.org/10.5194/ascmo-2-17-2016, 2016
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In this work, we combine the information from a complex and a simple atmospheric model to efficiently build a statistical representation (an emulator) of the complex model and to study the relationship between them. Thanks to the improved efficiency, this process is now feasible for complex models, which are slow and costly to run. The constructed emulator provide approximations of the model output, allowing various analyses to be made without the need to run the complex model again.
A. M. Foley, P. B. Holden, N. R. Edwards, J.-F. Mercure, P. Salas, H. Pollitt, and U. Chewpreecha
Earth Syst. Dynam., 7, 119–132, https://doi.org/10.5194/esd-7-119-2016, https://doi.org/10.5194/esd-7-119-2016, 2016
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We introduce GENIEem-PLASIM-ENTSem (GPem), a climate-carbon cycle emulator, showing how model emulation can be used in integrated assessment modelling to resolve regional climate impacts and systematically capture uncertainty. In a case study, we couple GPem to FTT:Power-E3MG, a non-equilibrium economic model with technology diffusion. We find that when the electricity sector is decarbonised by 90 %, further emissions reductions must be achieved in other sectors to avoid dangerous climate change.
M. Willeit and A. Ganopolski
Clim. Past, 11, 1165–1180, https://doi.org/10.5194/cp-11-1165-2015, https://doi.org/10.5194/cp-11-1165-2015, 2015
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In this paper we explore the permafrost–ice-sheet interaction using the fully coupled climate–ice-sheet model CLIMBER-2 with the addition of a newly developed permafrost module. We find that permafrost has a moderate but significant effect on ice sheet dynamics during the last glacial cycle. In particular at the Last Glacial Maximum the inclusion of permafrost leads to a 15m sea level equivalent increase in Northern Hemisphere ice volume when permafrost is included.
A. Robinson and M. Perrette
Geosci. Model Dev., 8, 1877–1883, https://doi.org/10.5194/gmd-8-1877-2015, https://doi.org/10.5194/gmd-8-1877-2015, 2015
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Here we present a concise interface to the NetCDF library designed to simplify reading and writing tasks of up to 6-D arrays in Fortran programs.
R. Calov, A. Robinson, M. Perrette, and A. Ganopolski
The Cryosphere, 9, 179–196, https://doi.org/10.5194/tc-9-179-2015, https://doi.org/10.5194/tc-9-179-2015, 2015
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Ice discharge into the ocean from outlet glaciers is an important
component of mass loss of the Greenland ice sheet. Here, we present a
simple parameterization of ice discharge for coarse resolution ice
sheet models, suitable for large ensembles or long-term palaeo
simulations. This parameterization reproduces in a good approximation
the present-day ice discharge compared with estimates, and the
simulation of the present-day ice sheet elevation is considerably
improved.
A. Robinson and H. Goelzer
The Cryosphere, 8, 1419–1428, https://doi.org/10.5194/tc-8-1419-2014, https://doi.org/10.5194/tc-8-1419-2014, 2014
E. Bauer and A. Ganopolski
Clim. Past, 10, 1333–1348, https://doi.org/10.5194/cp-10-1333-2014, https://doi.org/10.5194/cp-10-1333-2014, 2014
D. Dalmonech, A. M. Foley, A. Anav, P. Friedlingstein, A. D. Friend, M. Kidston, M. Willeit, and S. Zaehle
Biogeosciences Discuss., https://doi.org/10.5194/bgd-11-2083-2014, https://doi.org/10.5194/bgd-11-2083-2014, 2014
Revised manuscript has not been submitted
M. Willeit, A. Ganopolski, and G. Feulner
Biogeosciences, 11, 17–32, https://doi.org/10.5194/bg-11-17-2014, https://doi.org/10.5194/bg-11-17-2014, 2014
M. Willeit, A. Ganopolski, and G. Feulner
Clim. Past, 9, 1749–1759, https://doi.org/10.5194/cp-9-1749-2013, https://doi.org/10.5194/cp-9-1749-2013, 2013
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Hector V3.2.0: functionality and performance of a reduced-complexity climate model
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Minjin Lee, Charles A. Stock, John P. Dunne, and Elena Shevliakova
Geosci. Model Dev., 17, 5191–5224, https://doi.org/10.5194/gmd-17-5191-2024, https://doi.org/10.5194/gmd-17-5191-2024, 2024
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Modeling global freshwater solid and nutrient loads, in both magnitude and form, is imperative for understanding emerging eutrophication problems. Such efforts, however, have been challenged by the difficulty of balancing details of freshwater biogeochemical processes with limited knowledge, input, and validation datasets. Here we develop a global freshwater model that resolves intertwined algae, solid, and nutrient dynamics and provide performance assessment against measurement-based estimates.
Hunter York Brown, Benjamin Wagman, Diana Bull, Kara Peterson, Benjamin Hillman, Xiaohong Liu, Ziming Ke, and Lin Lin
Geosci. Model Dev., 17, 5087–5121, https://doi.org/10.5194/gmd-17-5087-2024, https://doi.org/10.5194/gmd-17-5087-2024, 2024
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Explosive volcanic eruptions lead to long-lived, microscopic particles in the upper atmosphere which act to cool the Earth's surface by reflecting the Sun's light back to space. We include and test this process in a global climate model, E3SM. E3SM is tested against satellite and balloon observations of the 1991 eruption of Mt. Pinatubo, showing that with these particles in the model we reasonably recreate Pinatubo and its global effects. We also explore how particle size leads to these effects.
Carl Svenhag, Moa K. Sporre, Tinja Olenius, Daniel Yazgi, Sara M. Blichner, Lars P. Nieradzik, and Pontus Roldin
Geosci. Model Dev., 17, 4923–4942, https://doi.org/10.5194/gmd-17-4923-2024, https://doi.org/10.5194/gmd-17-4923-2024, 2024
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Our research shows the importance of modeling new particle formation (NPF) and growth of particles in the atmosphere on a global scale, as they influence the outcomes of clouds and our climate. With the global model EC-Earth3 we show that using a new method for NPF modeling, which includes new detailed processes with NH3 and H2SO4, significantly impacts the number of particles in the air and clouds and changes the radiation balance of the same magnitude as anthropogenic greenhouse emissions.
Mengjie Han, Qing Zhao, Xili Wang, Ying-Ping Wang, Philippe Ciais, Haicheng Zhang, Daniel S. Goll, Lei Zhu, Zhe Zhao, Zhixuan Guo, Chen Wang, Wei Zhuang, Fengchang Wu, and Wei Li
Geosci. Model Dev., 17, 4871–4890, https://doi.org/10.5194/gmd-17-4871-2024, https://doi.org/10.5194/gmd-17-4871-2024, 2024
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The impact of biochar (BC) on soil organic carbon (SOC) dynamics is not represented in most land carbon models used for assessing land-based climate change mitigation. Our study develops a BC model that incorporates our current understanding of BC effects on SOC based on a soil carbon model (MIMICS). The BC model can reproduce the SOC changes after adding BC, providing a useful tool to couple dynamic land models to evaluate the effectiveness of BC application for CO2 removal from the atmosphere.
Kalyn Dorheim, Skylar Gering, Robert Gieseke, Corinne Hartin, Leeya Pressburger, Alexey N. Shiklomanov, Steven J. Smith, Claudia Tebaldi, Dawn L. Woodard, and Ben Bond-Lamberty
Geosci. Model Dev., 17, 4855–4869, https://doi.org/10.5194/gmd-17-4855-2024, https://doi.org/10.5194/gmd-17-4855-2024, 2024
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Hector is an easy-to-use, global climate–carbon cycle model. With its quick run time, Hector can provide climate information from a run in a fraction of a second. Hector models on a global and annual basis. Here, we present an updated version of the model, Hector V3. In this paper, we document Hector’s new features. Hector V3 is capable of reproducing historical observations, and its future temperature projections are consistent with those of more complex models.
Fangxuan Ren, Jintai Lin, Chenghao Xu, Jamiu A. Adeniran, Jingxu Wang, Randall V. Martin, Aaron van Donkelaar, Melanie S. Hammer, Larry W. Horowitz, Steven T. Turnock, Naga Oshima, Jie Zhang, Susanne Bauer, Kostas Tsigaridis, Øyvind Seland, Pierre Nabat, David Neubauer, Gary Strand, Twan van Noije, Philippe Le Sager, and Toshihiko Takemura
Geosci. Model Dev., 17, 4821–4836, https://doi.org/10.5194/gmd-17-4821-2024, https://doi.org/10.5194/gmd-17-4821-2024, 2024
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We evaluate the performance of 14 CMIP6 ESMs in simulating total PM2.5 and its 5 components over China during 2000–2014. PM2.5 and its components are underestimated in almost all models, except that black carbon (BC) and sulfate are overestimated in two models, respectively. The underestimation is the largest for organic carbon (OC) and the smallest for BC. Models reproduce the observed spatial pattern for OC, sulfate, nitrate and ammonium well, yet the agreement is poorer for BC.
Yi Xi, Chunjing Qiu, Yuan Zhang, Dan Zhu, Shushi Peng, Gustaf Hugelius, Jinfeng Chang, Elodie Salmon, and Philippe Ciais
Geosci. Model Dev., 17, 4727–4754, https://doi.org/10.5194/gmd-17-4727-2024, https://doi.org/10.5194/gmd-17-4727-2024, 2024
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The ORCHIDEE-MICT model can simulate the carbon cycle and hydrology at a sub-grid scale but energy budgets only at a grid scale. This paper assessed the implementation of a multi-tiling energy budget approach in ORCHIDEE-MICT and found warmer surface and soil temperatures, higher soil moisture, and more soil organic carbon across the Northern Hemisphere compared with the original version.
Georgia Lazoglou, Theo Economou, Christina Anagnostopoulou, George Zittis, Anna Tzyrkalli, Pantelis Georgiades, and Jos Lelieveld
Geosci. Model Dev., 17, 4689–4703, https://doi.org/10.5194/gmd-17-4689-2024, https://doi.org/10.5194/gmd-17-4689-2024, 2024
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This study focuses on the important issue of the drizzle bias effect in regional climate models, described by an over-prediction of the number of rainy days while underestimating associated precipitation amounts. For this purpose, two distinct methodologies are applied and rigorously evaluated. These results are encouraging for using the multivariate machine learning method random forest to increase the accuracy of climate models concerning the projection of the number of wet days.
Xu Yue, Hao Zhou, Chenguang Tian, Yimian Ma, Yihan Hu, Cheng Gong, Hui Zheng, and Hong Liao
Geosci. Model Dev., 17, 4621–4642, https://doi.org/10.5194/gmd-17-4621-2024, https://doi.org/10.5194/gmd-17-4621-2024, 2024
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We develop the interactive Model for Air Pollution and Land Ecosystems (iMAPLE). The model considers the full coupling between carbon and water cycles, dynamic fire emissions, wetland methane emissions, biogenic volatile organic compound emissions, and trait-based ozone vegetation damage. Evaluations show that iMAPLE is a useful tool for the study of the interactions among climate, chemistry, and ecosystems.
Malte Meinshausen, Carl-Friedrich Schleussner, Kathleen Beyer, Greg Bodeker, Olivier Boucher, Josep G. Canadell, John S. Daniel, Aïda Diongue-Niang, Fatima Driouech, Erich Fischer, Piers Forster, Michael Grose, Gerrit Hansen, Zeke Hausfather, Tatiana Ilyina, Jarmo S. Kikstra, Joyce Kimutai, Andrew D. King, June-Yi Lee, Chris Lennard, Tabea Lissner, Alexander Nauels, Glen P. Peters, Anna Pirani, Gian-Kasper Plattner, Hans Pörtner, Joeri Rogelj, Maisa Rojas, Joyashree Roy, Bjørn H. Samset, Benjamin M. Sanderson, Roland Séférian, Sonia Seneviratne, Christopher J. Smith, Sophie Szopa, Adelle Thomas, Diana Urge-Vorsatz, Guus J. M. Velders, Tokuta Yokohata, Tilo Ziehn, and Zebedee Nicholls
Geosci. Model Dev., 17, 4533–4559, https://doi.org/10.5194/gmd-17-4533-2024, https://doi.org/10.5194/gmd-17-4533-2024, 2024
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The scientific community is considering new scenarios to succeed RCPs and SSPs for the next generation of Earth system model runs to project future climate change. To contribute to that effort, we reflect on relevant policy and scientific research questions and suggest categories for representative emission pathways. These categories are tailored to the Paris Agreement long-term temperature goal, high-risk outcomes in the absence of further climate policy and worlds “that could have been”.
Ross Mower, Ethan D. Gutmann, Glen E. Liston, Jessica Lundquist, and Soren Rasmussen
Geosci. Model Dev., 17, 4135–4154, https://doi.org/10.5194/gmd-17-4135-2024, https://doi.org/10.5194/gmd-17-4135-2024, 2024
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Higher-resolution model simulations are better at capturing winter snowpack changes across space and time. However, increasing resolution also increases the computational requirements. This work provides an overview of changes made to a distributed snow-evolution modeling system (SnowModel) to allow it to leverage high-performance computing resources. Continental simulations that were previously estimated to take 120 d can now be performed in 5 h.
Jiaxu Guo, Juepeng Zheng, Yidan Xu, Haohuan Fu, Wei Xue, Lanning Wang, Lin Gan, Ping Gao, Wubing Wan, Xianwei Wu, Zhitao Zhang, Liang Hu, Gaochao Xu, and Xilong Che
Geosci. Model Dev., 17, 3975–3992, https://doi.org/10.5194/gmd-17-3975-2024, https://doi.org/10.5194/gmd-17-3975-2024, 2024
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To enhance the efficiency of experiments using SCAM, we train a learning-based surrogate model to facilitate large-scale sensitivity analysis and tuning of combinations of multiple parameters. Employing a hybrid method, we investigate the joint sensitivity of multi-parameter combinations across typical cases, identifying the most sensitive three-parameter combination out of 11. Subsequently, we conduct a tuning process aimed at reducing output errors in these cases.
Yung-Yao Lan, Huang-Hsiung Hsu, and Wan-Ling Tseng
Geosci. Model Dev., 17, 3897–3918, https://doi.org/10.5194/gmd-17-3897-2024, https://doi.org/10.5194/gmd-17-3897-2024, 2024
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This study uses the CAM5–SIT coupled model to investigate the effects of SST feedback frequency on the MJO simulations with intervals at 30 min, 1, 3, 6, 12, 18, 24, and 30 d. The simulations become increasingly unrealistic as the frequency of the SST feedback decreases. Our results suggest that more spontaneous air--sea interaction (e.g., ocean response within 3 d in this study) with high vertical resolution in the ocean model is key to the realistic simulation of the MJO.
Jiwoo Lee, Peter J. Gleckler, Min-Seop Ahn, Ana Ordonez, Paul A. Ullrich, Kenneth R. Sperber, Karl E. Taylor, Yann Y. Planton, Eric Guilyardi, Paul Durack, Celine Bonfils, Mark D. Zelinka, Li-Wei Chao, Bo Dong, Charles Doutriaux, Chengzhu Zhang, Tom Vo, Jason Boutte, Michael F. Wehner, Angeline G. Pendergrass, Daehyun Kim, Zeyu Xue, Andrew T. Wittenberg, and John Krasting
Geosci. Model Dev., 17, 3919–3948, https://doi.org/10.5194/gmd-17-3919-2024, https://doi.org/10.5194/gmd-17-3919-2024, 2024
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We introduce an open-source software, the PCMDI Metrics Package (PMP), developed for a comprehensive comparison of Earth system models (ESMs) with real-world observations. Using diverse metrics evaluating climatology, variability, and extremes simulated in thousands of simulations from the Coupled Model Intercomparison Project (CMIP), PMP aids in benchmarking model improvements across generations. PMP also enables efficient tracking of performance evolutions during ESM developments.
Haoyue Zuo, Yonggang Liu, Gaojun Li, Zhifang Xu, Liang Zhao, Zhengtang Guo, and Yongyun Hu
Geosci. Model Dev., 17, 3949–3974, https://doi.org/10.5194/gmd-17-3949-2024, https://doi.org/10.5194/gmd-17-3949-2024, 2024
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Compared to the silicate weathering fluxes measured at large river basins, the current models tend to systematically overestimate the fluxes over the tropical region, which leads to an overestimation of the global total weathering flux. The most possible cause of such bias is found to be the overestimation of tropical surface erosion, which indicates that the tropical vegetation likely slows down physical erosion significantly. We propose a way of taking this effect into account in models.
Quentin Pikeroen, Didier Paillard, and Karine Watrin
Geosci. Model Dev., 17, 3801–3814, https://doi.org/10.5194/gmd-17-3801-2024, https://doi.org/10.5194/gmd-17-3801-2024, 2024
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All accurate climate models use equations with poorly defined parameters, where knobs for the parameters are turned to fit the observations. This process is called tuning. In this article, we use another paradigm. We use a thermodynamic hypothesis, the maximum entropy production, to compute temperatures, energy fluxes, and precipitation, where tuning is impossible. For now, the 1D vertical model is used for a tropical atmosphere. The correct order of magnitude of precipitation is computed.
Jishi Zhang, Peter Bogenschutz, Qi Tang, Philip Cameron-smith, and Chengzhu Zhang
Geosci. Model Dev., 17, 3687–3731, https://doi.org/10.5194/gmd-17-3687-2024, https://doi.org/10.5194/gmd-17-3687-2024, 2024
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We developed a regionally refined climate model that allows resolved convection and performed a 20-year projection to the end of the century. The model has a resolution of 3.25 km in California, which allows us to predict climate with unprecedented accuracy, and a resolution of 100 km for the rest of the globe to achieve efficient, self-consistent simulations. The model produces superior results in reproducing climate patterns over California that typical modern climate models cannot resolve.
Xiaohui Zhong, Xing Yu, and Hao Li
Geosci. Model Dev., 17, 3667–3685, https://doi.org/10.5194/gmd-17-3667-2024, https://doi.org/10.5194/gmd-17-3667-2024, 2024
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In order to forecast localized warm-sector rainfall in the south China region, numerical weather prediction models are being run with finer grid spacing. The conventional convection parameterization (CP) performs poorly in the gray zone, necessitating the development of a scale-aware scheme. We propose a machine learning (ML) model to replace the scale-aware CP scheme. Evaluation against the original CP scheme has shown that the ML-based CP scheme can provide accurate and reliable predictions.
Taufiq Hassan, Kai Zhang, Jianfeng Li, Balwinder Singh, Shixuan Zhang, Hailong Wang, and Po-Lun Ma
Geosci. Model Dev., 17, 3507–3532, https://doi.org/10.5194/gmd-17-3507-2024, https://doi.org/10.5194/gmd-17-3507-2024, 2024
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Anthropogenic aerosol emissions are an essential part of global aerosol models. Significant errors can exist from the loss of emission heterogeneity. We introduced an emission treatment that significantly improved aerosol emission heterogeneity in high-resolution model simulations, with improvements in simulated aerosol surface concentrations. The emission treatment will provide a more accurate representation of aerosol emissions and their effects on climate.
Feng Zhu, Julien Emile-Geay, Gregory J. Hakim, Dominique Guillot, Deborah Khider, Robert Tardif, and Walter A. Perkins
Geosci. Model Dev., 17, 3409–3431, https://doi.org/10.5194/gmd-17-3409-2024, https://doi.org/10.5194/gmd-17-3409-2024, 2024
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Climate field reconstruction encompasses methods that estimate the evolution of climate in space and time based on natural archives. It is useful to investigate climate variations and validate climate models, but its implementation and use can be difficult for non-experts. This paper introduces a user-friendly Python package called cfr to make these methods more accessible, thanks to the computational and visualization tools that facilitate efficient and reproducible research on past climates.
Rose V. Palermo, J. Taylor Perron, Jason M. Soderblom, Samuel P. D. Birch, Alexander G. Hayes, and Andrew D. Ashton
Geosci. Model Dev., 17, 3433–3445, https://doi.org/10.5194/gmd-17-3433-2024, https://doi.org/10.5194/gmd-17-3433-2024, 2024
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Models of rocky coastal erosion help us understand the controls on coastal morphology and evolution. In this paper, we present a simplified model of coastline erosion driven by either uniform erosion where coastline erosion is constant or wave-driven erosion where coastline erosion is a function of the wave power. This model can be used to evaluate how coastline changes reflect climate, sea-level history, material properties, and the relative influence of different erosional processes.
Safae Oumami, Joaquim Arteta, Vincent Guidard, Pierre Tulet, and Paul David Hamer
Geosci. Model Dev., 17, 3385–3408, https://doi.org/10.5194/gmd-17-3385-2024, https://doi.org/10.5194/gmd-17-3385-2024, 2024
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In this paper, we coupled the SURFEX and MEGAN models. The aim of this coupling is to improve the estimation of biogenic fluxes by using the SURFEX canopy environment model. The coupled model results were validated and several sensitivity tests were performed. The coupled-model total annual isoprene flux is 442 Tg; this value is within the range of other isoprene estimates reported. The ultimate aim of this coupling is to predict the impact of climate change on biogenic emissions.
Lars Ackermann, Thomas Rackow, Kai Himstedt, Paul Gierz, Gregor Knorr, and Gerrit Lohmann
Geosci. Model Dev., 17, 3279–3301, https://doi.org/10.5194/gmd-17-3279-2024, https://doi.org/10.5194/gmd-17-3279-2024, 2024
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We present long-term simulations with interactive icebergs in the Southern Ocean. By melting, icebergs reduce the temperature and salinity of the surrounding ocean. In our simulations, we find that this cooling effect of iceberg melting is not limited to the surface ocean but also reaches the deep ocean and propagates northward into all ocean basins. Additionally, the formation of deep-water masses in the Southern Ocean is enhanced.
Nanhong Xie, Tijian Wang, Xiaodong Xie, Xu Yue, Filippo Giorgi, Qian Zhang, Danyang Ma, Rong Song, Beiyao Xu, Shu Li, Bingliang Zhuang, Mengmeng Li, Min Xie, Natalya Andreeva Kilifarska, Georgi Gadzhev, and Reneta Dimitrova
Geosci. Model Dev., 17, 3259–3277, https://doi.org/10.5194/gmd-17-3259-2024, https://doi.org/10.5194/gmd-17-3259-2024, 2024
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For the first time, we coupled a regional climate chemistry model, RegCM-Chem, with a dynamic vegetation model, YIBs, to create a regional climate–chemistry–ecology model, RegCM-Chem–YIBs. We applied it to simulate climatic, chemical, and ecological parameters in East Asia and fully validated it on a variety of observational data. Results show that RegCM-Chem–YIBs model is a valuable tool for studying the terrestrial carbon cycle, atmospheric chemistry, and climate change on a regional scale.
Bryce E. Harrop, Jian Lu, L. Ruby Leung, William K. M. Lau, Kyu-Myong Kim, Brian Medeiros, Brian J. Soden, Gabriel A. Vecchi, Bosong Zhang, and Balwinder Singh
Geosci. Model Dev., 17, 3111–3135, https://doi.org/10.5194/gmd-17-3111-2024, https://doi.org/10.5194/gmd-17-3111-2024, 2024
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Seven new experimental setups designed to interfere with cloud radiative heating have been added to the Energy Exascale Earth System Model (E3SM). These experiments include both those that test the mean impact of cloud radiative heating and those examining its covariance with circulations. This paper documents the code changes and steps needed to run these experiments. Results corroborate prior findings for how cloud radiative heating impacts circulations and rainfall patterns.
Mario C. Acosta, Sergi Palomas, Stella V. Paronuzzi Ticco, Gladys Utrera, Joachim Biercamp, Pierre-Antoine Bretonniere, Reinhard Budich, Miguel Castrillo, Arnaud Caubel, Francisco Doblas-Reyes, Italo Epicoco, Uwe Fladrich, Sylvie Joussaume, Alok Kumar Gupta, Bryan Lawrence, Philippe Le Sager, Grenville Lister, Marie-Pierre Moine, Jean-Christophe Rioual, Sophie Valcke, Niki Zadeh, and Venkatramani Balaji
Geosci. Model Dev., 17, 3081–3098, https://doi.org/10.5194/gmd-17-3081-2024, https://doi.org/10.5194/gmd-17-3081-2024, 2024
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We present a collection of performance metrics gathered during the Coupled Model Intercomparison Project Phase 6 (CMIP6), a worldwide initiative to study climate change. We analyse the metrics that resulted from collaboration efforts among many partners and models and describe our findings to demonstrate the utility of our study for the scientific community. The research contributes to understanding climate modelling performance on the current high-performance computing (HPC) architectures.
Sabine Doktorowski, Jan Kretzschmar, Johannes Quaas, Marc Salzmann, and Odran Sourdeval
Geosci. Model Dev., 17, 3099–3110, https://doi.org/10.5194/gmd-17-3099-2024, https://doi.org/10.5194/gmd-17-3099-2024, 2024
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Especially over the midlatitudes, precipitation is mainly formed via the ice phase. In this study we focus on the initial snow formation process in the ICON-AES, the aggregation process. We use a stochastical approach for the aggregation parameterization and investigate the influence in the ICON-AES. Therefore, a distribution function of cloud ice is created, which is evaluated with satellite data. The new approach leads to cloud ice loss and an improvement in the process rate bias.
Katie R. Blackford, Matthew Kasoar, Chantelle Burton, Eleanor Burke, Iain Colin Prentice, and Apostolos Voulgarakis
Geosci. Model Dev., 17, 3063–3079, https://doi.org/10.5194/gmd-17-3063-2024, https://doi.org/10.5194/gmd-17-3063-2024, 2024
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Peatlands are globally important stores of carbon which are being increasingly threatened by wildfires with knock-on effects on the climate system. Here we introduce a novel peat fire parameterization in the northern high latitudes to the INFERNO global fire model. Representing peat fires increases annual burnt area across the high latitudes, alongside improvements in how we capture year-to-year variation in burning and emissions.
Pengfei Shi, L. Ruby Leung, Bin Wang, Kai Zhang, Samson M. Hagos, and Shixuan Zhang
Geosci. Model Dev., 17, 3025–3040, https://doi.org/10.5194/gmd-17-3025-2024, https://doi.org/10.5194/gmd-17-3025-2024, 2024
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Improving climate predictions have profound socio-economic impacts. This study introduces a new weakly coupled land data assimilation (WCLDA) system for a coupled climate model. We demonstrate improved simulation of soil moisture and temperature in many global regions and throughout the soil layers. Furthermore, significant improvements are also found in reproducing the time evolution of the 2012 US Midwest drought. The WCLDA system provides the groundwork for future predictability studies.
Justin Peter, Elisabeth Vogel, Wendy Sharples, Ulrike Bende-Michl, Louise Wilson, Pandora Hope, Andrew Dowdy, Greg Kociuba, Sri Srikanthan, Vi Co Duong, Jake Roussis, Vjekoslav Matic, Zaved Khan, Alison Oke, Margot Turner, Stuart Baron-Hay, Fiona Johnson, Raj Mehrotra, Ashish Sharma, Marcus Thatcher, Ali Azarvinand, Steven Thomas, Ghyslaine Boschat, Chantal Donnelly, and Robert Argent
Geosci. Model Dev., 17, 2755–2781, https://doi.org/10.5194/gmd-17-2755-2024, https://doi.org/10.5194/gmd-17-2755-2024, 2024
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We detail the production of datasets and communication to end users of high-resolution projections of rainfall, runoff, and soil moisture for the entire Australian continent. This is important as previous projections for Australia were for small regions and used differing techniques for their projections, making comparisons difficult across Australia's varied climate zones. The data will be beneficial for research purposes and to aid adaptation to climate change.
Daniele Visioni, Alan Robock, Jim Haywood, Matthew Henry, Simone Tilmes, Douglas G. MacMartin, Ben Kravitz, Sarah J. Doherty, John Moore, Chris Lennard, Shingo Watanabe, Helene Muri, Ulrike Niemeier, Olivier Boucher, Abu Syed, Temitope S. Egbebiyi, Roland Séférian, and Ilaria Quaglia
Geosci. Model Dev., 17, 2583–2596, https://doi.org/10.5194/gmd-17-2583-2024, https://doi.org/10.5194/gmd-17-2583-2024, 2024
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This paper describes a new experimental protocol for the Geoengineering Model Intercomparison Project (GeoMIP). In it, we describe the details of a new simulation of sunlight reflection using the stratospheric aerosols that climate models are supposed to run, and we explain the reasons behind each choice we made when defining the protocol.
Jose Rafael Guarin, Jonas Jägermeyr, Elizabeth A. Ainsworth, Fabio A. A. Oliveira, Senthold Asseng, Kenneth Boote, Joshua Elliott, Lisa Emberson, Ian Foster, Gerrit Hoogenboom, David Kelly, Alex C. Ruane, and Katrina Sharps
Geosci. Model Dev., 17, 2547–2567, https://doi.org/10.5194/gmd-17-2547-2024, https://doi.org/10.5194/gmd-17-2547-2024, 2024
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The effects of ozone (O3) stress on crop photosynthesis and leaf senescence were added to maize, rice, soybean, and wheat crop models. The modified models reproduced growth and yields under different O3 levels measured in field experiments and reported in the literature. The combined interactions between O3 and additional stresses were reproduced with the new models. These updated crop models can be used to simulate impacts of O3 stress under future climate change and air pollution scenarios.
Jiachen Lu, Negin Nazarian, Melissa Anne Hart, E. Scott Krayenhoff, and Alberto Martilli
Geosci. Model Dev., 17, 2525–2545, https://doi.org/10.5194/gmd-17-2525-2024, https://doi.org/10.5194/gmd-17-2525-2024, 2024
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This study enhances urban canopy models by refining key assumptions. Simulations for various urban scenarios indicate discrepancies in turbulent transport efficiency for flow properties. We propose two modifications that involve characterizing diffusion coefficients for momentum and turbulent kinetic energy separately and introducing a physics-based
mass-fluxterm. These adjustments enhance the model's performance, offering more reliable temperature and surface flux estimates.
Justin L. Willson, Kevin A. Reed, Christiane Jablonowski, James Kent, Peter H. Lauritzen, Ramachandran Nair, Mark A. Taylor, Paul A. Ullrich, Colin M. Zarzycki, David M. Hall, Don Dazlich, Ross Heikes, Celal Konor, David Randall, Thomas Dubos, Yann Meurdesoif, Xi Chen, Lucas Harris, Christian Kühnlein, Vivian Lee, Abdessamad Qaddouri, Claude Girard, Marco Giorgetta, Daniel Reinert, Hiroaki Miura, Tomoki Ohno, and Ryuji Yoshida
Geosci. Model Dev., 17, 2493–2507, https://doi.org/10.5194/gmd-17-2493-2024, https://doi.org/10.5194/gmd-17-2493-2024, 2024
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Accurate simulation of tropical cyclones (TCs) is essential to understanding their behavior in a changing climate. One way this is accomplished is through model intercomparison projects, where results from multiple climate models are analyzed to provide benchmark solutions for the wider climate modeling community. This study describes and analyzes the previously developed TC test case for nine climate models in an intercomparison project, providing solutions that aid in model development.
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.
Yuwen Fan, Zhao Yang, Min-Hui Lo, Jina Hur, and Eun-Soon Im
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-38, https://doi.org/10.5194/gmd-2024-38, 2024
Revised manuscript accepted for GMD
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Irrigated agriculture in the North China Plain (NCP) has a significant impact on the local climate. To better understand this impact, we developed a specialized model specifically for the NCP region. This model allows us to simulate the double-cropping vegetation and the dynamic irrigation practices that are commonly employed in the NCP. This model shows improved performance in capturing the general crop growth, such as crop stages, biomass, crop yield, and vegetation greenness.
Sergey Danilov, Carolin Mehlmann, Dmitry Sidorenko, and Qiang Wang
Geosci. Model Dev., 17, 2287–2297, https://doi.org/10.5194/gmd-17-2287-2024, https://doi.org/10.5194/gmd-17-2287-2024, 2024
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Sea ice models are a necessary component of climate models. At very high resolution they are capable of simulating linear kinematic features, such as leads, which are important for better prediction of heat exchanges between the ocean and atmosphere. Two new discretizations are described which improve the sea ice component of the Finite volumE Sea ice–Ocean Model (FESOM version 2) by allowing simulations of finer scales.
Yangke Liu, Qing Bao, Bian He, Xiaofei Wu, Jing Yang, Yimin Liu, Guoxiong Wu, Tao Zhu, Siyuan Zhou, Yao Tang, Ankang Qu, Yalan Fan, Anling Liu, Dandan Chen, Zhaoming Luo, Xing Hu, and Tongwen Wu
EGUsphere, https://doi.org/10.5194/egusphere-2024-1, https://doi.org/10.5194/egusphere-2024-1, 2024
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This article gives an overview introduction of the IAP-CAS S2S (sub-seasonal to seasonal) ensemble forecasting system and MJO forecast evaluation of the system. Compared to other S2S models, the IAP-CAS model has its advantages but also exhibits some biases, including underdispersive ensemble, overestimated amplitude and faster propagation speed when forecasting MJO. We also provide the explanation towards these biases and prospects for further improvement of this system in the future.
Tian Gan, Gregory E. Tucker, Eric W. H. Hutton, Mark D. Piper, Irina Overeem, Albert J. Kettner, Benjamin Campforts, Julia M. Moriarty, Brianna Undzis, Ethan Pierce, and Lynn McCready
Geosci. Model Dev., 17, 2165–2185, https://doi.org/10.5194/gmd-17-2165-2024, https://doi.org/10.5194/gmd-17-2165-2024, 2024
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This study presents the design, implementation, and application of the CSDMS Data Components. The case studies demonstrate that the Data Components provide a consistent way to access heterogeneous datasets from multiple sources, and to seamlessly integrate them with various models for Earth surface process modeling. The Data Components support the creation of open data–model integration workflows to improve the research transparency and reproducibility.
Jérémy Bernard, Erwan Bocher, Matthieu Gousseff, François Leconte, and Elisabeth Le Saux Wiederhold
Geosci. Model Dev., 17, 2077–2116, https://doi.org/10.5194/gmd-17-2077-2024, https://doi.org/10.5194/gmd-17-2077-2024, 2024
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Geographical features may have a considerable effect on local climate. The local climate zone (LCZ) system proposed by Stewart and Oke (2012) is seen as a standard approach for classifying any zone according to a set of geographic indicators. While many methods already exist to map the LCZ, only a few tools are openly and freely available. We present the algorithm implemented in GeoClimate software to identify the LCZ of any place in the world using OpenStreetMap data.
Thomas Extier, Thibaut Caley, and Didier M. Roche
Geosci. Model Dev., 17, 2117–2139, https://doi.org/10.5194/gmd-17-2117-2024, https://doi.org/10.5194/gmd-17-2117-2024, 2024
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Stable water isotopes are used to infer changes in the hydrological cycle for different time periods in climatic archive and climate models. We present the implementation of the δ2H and δ17O water isotopes in the coupled climate model iLOVECLIM and calculate the d- and 17O-excess. Results of a simulation under preindustrial conditions show that the model correctly reproduces the water isotope distribution in the atmosphere and ocean in comparison to data and other global circulation models.
Joseph P. Hollowed, Christiane Jablonowski, Hunter Y. Brown, Benjamin R. Hillman, Diana L. Bull, and Joseph L. Hart
EGUsphere, https://doi.org/10.5194/egusphere-2024-335, https://doi.org/10.5194/egusphere-2024-335, 2024
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Large volcanic eruptions deposit material into the upper-atmosphere, which is capable of altering temperature and wind patterns of the Earth's atmosphere for years following. This research describes a new method of simulating these effects in an idealized, efficient atmospheric model. A volcanic eruption of sulfur dioxide is described with a simplified set of physical rules, which eventually cools the planetary surface. This model has been designed as a testbed for climate attribution studies.
Marit Sandstad, Borgar Aamaas, Ane Nordlie Johansen, Marianne Tronstad Lund, Glen Peters, Bjørn Hallvard Samset, Benjamin M. Sanderson, and Ragnhild Bieltvedt Skeie
EGUsphere, https://doi.org/10.5194/egusphere-2024-196, https://doi.org/10.5194/egusphere-2024-196, 2024
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The CICERO-SCM has existed as a FORTRAN model since 1999 and consists of a part that calculates radiative forcing and concentrations from emissions, and an upwelling diffusion energy balance model of the ocean that calculates temperature change. In this paper we describe an updated version ported to python and publicly available at https://github.com/ciceroOslo/ciceroscm (https://doi.org/10.5281/zenodo.10548720). This version contains functionality for parallel runs and automatic calibration.
Kirsten L. Findell, Zun Yin, Eunkyo Seo, Paul A. Dirmeyer, Nathan P. Arnold, Nathaniel Chaney, Megan D. Fowler, Meng Huang, David M. Lawrence, Po-Lun Ma, and Joseph A. Santanello Jr.
Geosci. Model Dev., 17, 1869–1883, https://doi.org/10.5194/gmd-17-1869-2024, https://doi.org/10.5194/gmd-17-1869-2024, 2024
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We outline a request for sub-daily data to accurately capture the process-level connections between land states, surface fluxes, and the boundary layer response. This high-frequency model output will allow for more direct comparison with observational field campaigns on process-relevant timescales, enable demonstration of inter-model spread in land–atmosphere coupling processes, and aid in targeted identification of sources of deficiencies and opportunities for improvement of the models.
Marlene Klockmann, Udo von Toussaint, and Eduardo Zorita
Geosci. Model Dev., 17, 1765–1787, https://doi.org/10.5194/gmd-17-1765-2024, https://doi.org/10.5194/gmd-17-1765-2024, 2024
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Reconstructions of climate variability before the observational period rely on climate proxies and sophisticated statistical models to link the proxy information and climate variability. Existing models tend to underestimate the true magnitude of variability, especially if the proxies contain non-climatic noise. We present and test a promising new framework for climate-index reconstructions, based on Gaussian processes, which reconstructs robust variability estimates from noisy and sparse data.
Aaron A. Naidoo-Bagwell, Fanny M. Monteiro, Katharine R. Hendry, Scott Burgan, Jamie D. Wilson, Ben A. Ward, Andy Ridgwell, and Daniel J. Conley
Geosci. Model Dev., 17, 1729–1748, https://doi.org/10.5194/gmd-17-1729-2024, https://doi.org/10.5194/gmd-17-1729-2024, 2024
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As an extension to the EcoGEnIE 1.0 Earth system model that features a diverse plankton community, EcoGEnIE 1.1 includes siliceous plankton diatoms and also considers their impact on biogeochemical cycles. With updates to existing nutrient cycles and the introduction of the silicon cycle, we see improved model performance relative to observational data. Through a more functionally diverse plankton community, the new model enables more comprehensive future study of ocean ecology.
Martin Butzin, Ying Ye, Christoph Völker, Özgür Gürses, Judith Hauck, and Peter Köhler
Geosci. Model Dev., 17, 1709–1727, https://doi.org/10.5194/gmd-17-1709-2024, https://doi.org/10.5194/gmd-17-1709-2024, 2024
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In this paper we describe the implementation of the carbon isotopes 13C and 14C into the marine biogeochemistry model FESOM2.1-REcoM3 and present results of long-term test simulations. Our model results are largely consistent with marine carbon isotope reconstructions for the pre-anthropogenic period, but also exhibit some discrepancies.
Sven Karsten, Hagen Radtke, Matthias Gröger, Ha T. M. Ho-Hagemann, Hossein Mashayekh, Thomas Neumann, and H. E. Markus Meier
Geosci. Model Dev., 17, 1689–1708, https://doi.org/10.5194/gmd-17-1689-2024, https://doi.org/10.5194/gmd-17-1689-2024, 2024
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This paper describes the development of a regional Earth System Model for the Baltic Sea region. In contrast to conventional coupling approaches, the presented model includes a flux calculator operating on a common exchange grid. This approach automatically ensures a locally consistent treatment of fluxes and simplifies the exchange of model components. The presented model can be used for various scientific questions, such as studies of natural variability and ocean–atmosphere interactions.
Skyler Graap and Colin M. Zarzycki
Geosci. Model Dev., 17, 1627–1650, https://doi.org/10.5194/gmd-17-1627-2024, https://doi.org/10.5194/gmd-17-1627-2024, 2024
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A key target for improving climate models is how low, bright clouds are predicted over tropical oceans, since they have important consequences for the Earth's energy budget. A climate model has been updated to improve the physical realism of the treatment of how momentum is moved up and down in the atmosphere. By comparing this updated model to real-world observations from balloon launches, it can be shown to more accurately depict atmospheric structure in trade-wind areas close to the Equator.
Marika M. Holland, Cecile Hannay, John Fasullo, Alexandra Jahn, Jennifer E. Kay, Michael Mills, Isla R. Simpson, William Wieder, Peter Lawrence, Erik Kluzek, and David Bailey
Geosci. Model Dev., 17, 1585–1602, https://doi.org/10.5194/gmd-17-1585-2024, https://doi.org/10.5194/gmd-17-1585-2024, 2024
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Climate evolves in response to changing forcings, as prescribed in simulations. Models and forcings are updated over time to reflect new understanding. This makes it difficult to attribute simulation differences to either model or forcing changes. Here we present new simulations which enable the separation of model structure and forcing influence between two widely used simulation sets. Results indicate a strong influence of aerosol emission uncertainty on historical climate.
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...