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.
Model description paper
| 
28 Jul 2022
Model description paper |
| 28 Jul 2022
| 28 Jul 2022
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
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Using a fast Earth system model we trace the stability landscape of the Atlantic meridional overturning circulation in the combined freshwater forcing–atmospheric CO2 space. We find four different Atlantic meridional overturning circulation states that are stable under different conditions and a generally increasing equilibrium Atlantic meridional overturning circulation strength with increasing CO2 concentrations.
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This study simulates long-term future climate scenarios to examine how long CO2 emissions will persist in the atmosphere. It shows that the effectiveness of carbon removal processes varies with the amount emitted. The removal of CO2 through silicate weathering is faster than previously thought, leading to a quicker reduction over time. The combined behaviour of different carbon cycle processes emphasizes the need to include all of them in models, as to better predict long-term atmospheric CO2.
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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.
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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, 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.
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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
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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
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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.
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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
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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 %.
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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
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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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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
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Clim. Past, 9, 1749–1759, https://doi.org/10.5194/cp-9-1749-2013, https://doi.org/10.5194/cp-9-1749-2013, 2013
Matteo Willeit and Andrey Ganopolski
Earth Syst. Dynam., 15, 1417–1434, https://doi.org/10.5194/esd-15-1417-2024, https://doi.org/10.5194/esd-15-1417-2024, 2024
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Using a fast Earth system model we trace the stability landscape of the Atlantic meridional overturning circulation in the combined freshwater forcing–atmospheric CO2 space. We find four different Atlantic meridional overturning circulation states that are stable under different conditions and a generally increasing equilibrium Atlantic meridional overturning circulation strength with increasing CO2 concentrations.
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EGUsphere, https://doi.org/10.5194/egusphere-2024-2976, https://doi.org/10.5194/egusphere-2024-2976, 2024
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The Cryosphere, 18, 4257–4283, https://doi.org/10.5194/tc-18-4257-2024, https://doi.org/10.5194/tc-18-4257-2024, 2024
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We present sea level projections for Antarctica in the context of ISMIP6-2300 with several forcings but extend the simulations to 2500, showing that more than 3 m of sea level contribution could be reached. We also test the sensitivity on a basal melting parameter and determine the timing of the loss of ice in the west region. All the simulations were carried out with the ice sheet model Yelmo.
Therese Rieckh, Andreas Born, Alexander Robinson, Robert Law, and Gerrit Gülle
Geosci. Model Dev., 17, 6987–7000, https://doi.org/10.5194/gmd-17-6987-2024, https://doi.org/10.5194/gmd-17-6987-2024, 2024
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We present the open-source model ELSA, which simulates the internal age structure of large ice sheets. It creates layers of snow accumulation at fixed times during the simulation, which are used to model the internal stratification of the ice sheet. Together with reconstructed isochrones from radiostratigraphy data, ELSA can be used to assess ice sheet models and to improve their parameterization. ELSA can be used coupled to an ice sheet model or forced with its output.
Daniel Moreno-Parada, Alexander Robinson, Marisa Montoya, and Jorge Alvarez-Solas
The Cryosphere, 18, 4215–4232, https://doi.org/10.5194/tc-18-4215-2024, https://doi.org/10.5194/tc-18-4215-2024, 2024
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Our study tries to understand how the ice temperature evolves in a large mass as in the case of Antarctica. We found a relation that tells us the ice temperature at any point. These results are important because they also determine how the ice moves. In general, ice moves due to slow deformation (as if pouring honey from a jar). Nevertheless, in some regions the ice base warms enough and melts. The liquid water then serves as lubricant and the ice slides and its velocity increases rapidly.
Javier Blasco, Ilaria Tabone, Daniel Moreno-Parada, Alexander Robinson, Jorge Alvarez-Solas, Frank Pattyn, and Marisa Montoya
Clim. Past, 20, 1919–1938, https://doi.org/10.5194/cp-20-1919-2024, https://doi.org/10.5194/cp-20-1919-2024, 2024
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In this study, we assess Antarctic tipping points which may had been crossed during the mid-Pliocene Warm Period. For this, we use data from the PlioMIP2 ensemble. Additionally, we investigate various sources of uncertainty, like ice dynamics and bedrock configuration. Our research significantly enhances our comprehension of Antarctica's response to a warming climate, shedding light on potential future tipping points that may be surpassed.
Jan Swierczek-Jereczek, Marisa Montoya, Konstantin Latychev, Alexander Robinson, Jorge Alvarez-Solas, and Jerry Mitrovica
Geosci. Model Dev., 17, 5263–5290, https://doi.org/10.5194/gmd-17-5263-2024, https://doi.org/10.5194/gmd-17-5263-2024, 2024
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Ice sheets present a thickness of a few kilometres, leading to a vertical deformation of the crust of up to a kilometre. This process depends on properties of the solid Earth, which can be regionally very different. We propose a model that accounts for this often-ignored heterogeneity and run 100 000 simulation years in minutes. Thus, the evolution of ice sheets is modeled with better accuracy, which is critical for a good mitigation of climate change and, in particular, sea-level rise.
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
Short summary
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
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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, 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
Short summary
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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.
Andrey Ganopolski
Clim. Past, 20, 151–185, https://doi.org/10.5194/cp-20-151-2024, https://doi.org/10.5194/cp-20-151-2024, 2024
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Despite significant progress in modelling Quaternary climate dynamics, a comprehensive theory of glacial cycles is still lacking. Here, using the results of model simulations and data analysis, I present a framework of the generalized Milankovitch theory (GMT), which further advances the concept proposed by Milutin Milankovitch over a century ago. The theory explains a number of facts which were not known during Milankovitch time's, such as the 100 kyr periodicity of the late Quaternary.
Takahito Mitsui, Matteo Willeit, and Niklas Boers
Earth Syst. Dynam., 14, 1277–1294, https://doi.org/10.5194/esd-14-1277-2023, https://doi.org/10.5194/esd-14-1277-2023, 2023
Short summary
Short summary
The glacial–interglacial cycles of the Quaternary exhibit 41 kyr periodicity before the Mid-Pleistocene Transition (MPT) around 1.2–0.8 Myr ago and ~100 kyr periodicity after that. The mechanism generating these periodicities remains elusive. Through an analysis of an Earth system model of intermediate complexity, CLIMBER-2, we show that the dominant periodicities of glacial cycles can be explained from the viewpoint of synchronization theory.
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
Short summary
To quantify the sensitivity of the earth system to orbital-scale forcings, we conducted an unprecedented quasi-continuous coupled general climate model simulation with the Community Earth System Model, which covers the climatic history of the past 3 million years. This study could stimulate future transient paleo-climate model simulations and perspectives to further highlight and document the effect of anthropogenic CO2 emissions in the broader paleo-climatic context.
Christine Kaufhold and Andrey Ganopolski
Saf. Nucl. Waste Disposal, 2, 89–90, https://doi.org/10.5194/sand-2-89-2023, https://doi.org/10.5194/sand-2-89-2023, 2023
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A repository in Germany must be secure for a period of at least 1 million years. We argue that the deep-future climate should be considered in the site selection process. A suite of possible future climates will be provided, using different emission scenarios. In low-emission scenarios, glacial cycles will quickly resume, changing subterranean stress and permafrost. In high-emission scenarios, the sea level will rise. Both regimes should be of interest to those working on nuclear waste disposal.
Matteo Willeit, Tatiana Ilyina, Bo Liu, Christoph Heinze, Mahé Perrette, Malte Heinemann, Daniela Dalmonech, Victor Brovkin, Guy Munhoven, Janine Börker, Jens Hartmann, Gibran Romero-Mujalli, and Andrey Ganopolski
Geosci. Model Dev., 16, 3501–3534, https://doi.org/10.5194/gmd-16-3501-2023, https://doi.org/10.5194/gmd-16-3501-2023, 2023
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In this paper we present the carbon cycle component of the newly developed fast Earth system model CLIMBER-X. The model can be run with interactive atmospheric CO2 to investigate the feedbacks between climate and the carbon cycle on temporal scales ranging from decades to > 100 000 years. CLIMBER-X is expected to be a useful tool for studying past climate–carbon cycle changes and for the investigation of the long-term future evolution of the Earth system.
Daniel Moreno-Parada, Jorge Alvarez-Solas, Javier Blasco, Marisa Montoya, and Alexander Robinson
The Cryosphere, 17, 2139–2156, https://doi.org/10.5194/tc-17-2139-2023, https://doi.org/10.5194/tc-17-2139-2023, 2023
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We have reconstructed the Laurentide Ice Sheet, located in North America during the Last Glacial Maximum (21 000 years ago). The absence of direct measurements raises a number of uncertainties. Here we study the impact of different physical laws that describe the friction as the ice slides over its base. We found that the Laurentide Ice Sheet is closest to prior reconstructions when the basal friction takes into account whether the base is frozen or thawed during its motion.
Negar Vakilifard, Richard G. Williams, Philip B. Holden, Katherine Turner, Neil R. Edwards, and David J. Beerling
Biogeosciences, 19, 4249–4265, https://doi.org/10.5194/bg-19-4249-2022, https://doi.org/10.5194/bg-19-4249-2022, 2022
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To remain within the Paris climate agreement, there is an increasing need to develop and implement carbon capture and sequestration techniques. The global climate benefits of implementing negative emission technologies over the next century are assessed using an Earth system model covering a wide range of plausible climate states. In some model realisations, there is continued warming after emissions cease. This continued warming is avoided if negative emissions are incorporated.
Alexander Robinson, Daniel Goldberg, and William H. Lipscomb
The Cryosphere, 16, 689–709, https://doi.org/10.5194/tc-16-689-2022, https://doi.org/10.5194/tc-16-689-2022, 2022
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Here we investigate the numerical stability of several commonly used methods in order to determine which of them are capable of resolving the complex physics of the ice flow and are also computationally efficient. We find that the so-called DIVA solver outperforms the others. Its representation of the physics is consistent with more complex methods, while it remains computationally efficient at high resolution.
Stefanie Talento and Andrey Ganopolski
Earth Syst. Dynam., 12, 1275–1293, https://doi.org/10.5194/esd-12-1275-2021, https://doi.org/10.5194/esd-12-1275-2021, 2021
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We propose a model for glacial cycles and produce an assessment of possible trajectories for the next 1 million years. Under natural conditions, the next glacial inception would most likely occur ∼50 kyr after present. We show that fossil-fuel CO2 releases can have an extremely long-term effect. Potentially achievable CO2 anthropogenic emissions during the next centuries will most likely provoke ice-free conditions in the Northern Hemisphere landmasses throughout the next half a million years.
Andreas Born and Alexander Robinson
The Cryosphere, 15, 4539–4556, https://doi.org/10.5194/tc-15-4539-2021, https://doi.org/10.5194/tc-15-4539-2021, 2021
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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
Short summary
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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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Geosci. Model Dev., 17, 7835–7853, https://doi.org/10.5194/gmd-17-7835-2024, https://doi.org/10.5194/gmd-17-7835-2024, 2024
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We describe a dataset where 45 parameters related to cloud processes in the Community Earth System Model version 2 (CESM2) Community Atmosphere Model version 6 (CAM6) are perturbed. Three sets of perturbed parameter ensembles (263 members) were created: current climate, preindustrial aerosol loading and future climate with sea surface temperature increased by 4 K.
Ha Thi Minh Ho-Hagemann, Vera Maurer, Stefan Poll, and Irina Fast
Geosci. Model Dev., 17, 7815–7834, https://doi.org/10.5194/gmd-17-7815-2024, https://doi.org/10.5194/gmd-17-7815-2024, 2024
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The regional Earth system model GCOAST-AHOI v2.0 that includes the regional climate model ICON-CLM coupled to the ocean model NEMO and the hydrological discharge model HD via the OASIS3-MCT coupler can be a useful tool for conducting long-term regional climate simulations over the EURO-CORDEX domain. The new OASIS3-MCT coupling interface implemented in ICON-CLM makes it more flexible for coupling to an external ocean model and an external hydrological discharge model.
Sandro Vattioni, Rahel Weber, Aryeh Feinberg, Andrea Stenke, John A. Dykema, Beiping Luo, Georgios A. Kelesidis, Christian A. Bruun, Timofei Sukhodolov, Frank N. Keutsch, Thomas Peter, and Gabriel Chiodo
Geosci. Model Dev., 17, 7767–7793, https://doi.org/10.5194/gmd-17-7767-2024, https://doi.org/10.5194/gmd-17-7767-2024, 2024
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We quantified impacts and efficiency of stratospheric solar climate intervention via solid particle injection. Microphysical interactions of solid particles with the sulfur cycle were interactively coupled to the heterogeneous chemistry scheme and the radiative transfer code of an aerosol–chemistry–climate model. Compared to injection of SO2 we only find a stronger cooling efficiency for solid particles when normalizing to the aerosol load but not when normalizing to the injection rate.
Samuel Rémy, Swen Metzger, Vincent Huijnen, Jason E. Williams, and Johannes Flemming
Geosci. Model Dev., 17, 7539–7567, https://doi.org/10.5194/gmd-17-7539-2024, https://doi.org/10.5194/gmd-17-7539-2024, 2024
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In this paper we describe the development of the future operational cycle 49R1 of the IFS-COMPO system, used for operational forecasts of atmospheric composition in the CAMS project, and focus on the implementation of the thermodynamical model EQSAM4Clim version 12. The implementation of EQSAM4Clim significantly improves the simulated secondary inorganic aerosol surface concentration. The new aerosol and precipitation acidity diagnostics showed good agreement against observational datasets.
Maximillian Van Wyk de Vries, Tom Matthews, L. Baker Perry, Nirakar Thapa, and Rob Wilby
Geosci. Model Dev., 17, 7629–7643, https://doi.org/10.5194/gmd-17-7629-2024, https://doi.org/10.5194/gmd-17-7629-2024, 2024
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This paper introduces the AtsMOS workflow, a new tool for improving weather forecasts in mountainous areas. By combining advanced statistical techniques with local weather data, AtsMOS can provide more accurate predictions of weather conditions. Using data from Mount Everest as an example, AtsMOS has shown promise in better forecasting hazardous weather conditions, making it a valuable tool for communities in mountainous regions and beyond.
Sofia Allende, Anne Marie Treguier, Camille Lique, Clément de Boyer Montégut, François Massonnet, Thierry Fichefet, and Antoine Barthélemy
Geosci. Model Dev., 17, 7445–7466, https://doi.org/10.5194/gmd-17-7445-2024, https://doi.org/10.5194/gmd-17-7445-2024, 2024
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We study the parameters of the turbulent-kinetic-energy mixed-layer-penetration scheme in the NEMO model with regard to sea-ice-covered regions of the Arctic Ocean. This evaluation reveals the impact of these parameters on mixed-layer depth, sea surface temperature and salinity, and ocean stratification. Our findings demonstrate significant impacts on sea ice thickness and sea ice concentration, emphasizing the need for accurately representing ocean mixing to understand Arctic climate dynamics.
Sabin I. Taranu, David M. Lawrence, Yoshihide Wada, Ting Tang, Erik Kluzek, Sam Rabin, Yi Yao, Steven J. De Hertog, Inne Vanderkelen, and Wim Thiery
Geosci. Model Dev., 17, 7365–7399, https://doi.org/10.5194/gmd-17-7365-2024, https://doi.org/10.5194/gmd-17-7365-2024, 2024
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In this study, we improved a climate model by adding the representation of water use sectors such as domestic, industry, and agriculture. This new feature helps us understand how water is used and supplied in various areas. We tested our model from 1971 to 2010 and found that it accurately identifies areas with water scarcity. By modelling the competition between sectors when water availability is limited, the model helps estimate the intensity and extent of individual sectors' water shortages.
Cynthia Whaley, Montana Etten-Bohm, Courtney Schumacher, Ayodeji Akingunola, Vivek Arora, Jason Cole, Michael Lazare, David Plummer, Knut von Salzen, and Barbara Winter
Geosci. Model Dev., 17, 7141–7155, https://doi.org/10.5194/gmd-17-7141-2024, https://doi.org/10.5194/gmd-17-7141-2024, 2024
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This paper describes how lightning was added as a process in the Canadian Earth System Model in order to interactively respond to climate changes. As lightning is an important cause of global wildfires, this new model development allows for more realistic projections of how wildfires may change in the future, responding to a changing climate.
Erik Gustafsson, Bo G. Gustafsson, Martijn Hermans, Christoph Humborg, and Christian Stranne
Geosci. Model Dev., 17, 7157–7179, https://doi.org/10.5194/gmd-17-7157-2024, https://doi.org/10.5194/gmd-17-7157-2024, 2024
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Methane (CH4) cycling in the Baltic Proper is studied through model simulations, enabling a first estimate of key CH4 fluxes. A preliminary budget identifies benthic CH4 release as the dominant source and two main sinks: CH4 oxidation in the water (92 % of sinks) and outgassing to the atmosphere (8 % of sinks). This study addresses CH4 emissions from coastal seas and is a first step toward understanding the relative importance of open-water outgassing compared with local coastal hotspots.
Tridib Banerjee, Patrick Scholz, Sergey Danilov, Knut Klingbeil, and Dmitry Sidorenko
Geosci. Model Dev., 17, 7051–7065, https://doi.org/10.5194/gmd-17-7051-2024, https://doi.org/10.5194/gmd-17-7051-2024, 2024
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In this paper we propose a new alternative to one of the functionalities of the sea ice model FESOM2. The alternative we propose allows the model to capture and simulate fast changes in quantities like sea surface elevation more accurately. We also demonstrate that the new alternative is faster and more adept at taking advantages of highly parallelized computing infrastructure. We therefore show that this new alternative is a great addition to the sea ice model FESOM2.
Yuwen Fan, Zhao Yang, Min-Hui Lo, Jina Hur, and Eun-Soon Im
Geosci. Model Dev., 17, 6929–6947, https://doi.org/10.5194/gmd-17-6929-2024, https://doi.org/10.5194/gmd-17-6929-2024, 2024
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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.
Ed Blockley, Emma Fiedler, Jeff Ridley, Luke Roberts, Alex West, Dan Copsey, Daniel Feltham, Tim Graham, David Livings, Clement Rousset, David Schroeder, and Martin Vancoppenolle
Geosci. Model Dev., 17, 6799–6817, https://doi.org/10.5194/gmd-17-6799-2024, https://doi.org/10.5194/gmd-17-6799-2024, 2024
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This paper documents the sea ice model component of the latest Met Office coupled model configuration, which will be used as the physical basis for UK contributions to CMIP7. Documentation of science options used in the configuration are given along with a brief model evaluation. This is the first UK configuration to use NEMO’s new SI3 sea ice model. We provide details on how SI3 was adapted to work with Met Office coupling methodology and documentation of coupling processes in the model.
Jean-François Lemieux, William H. Lipscomb, Anthony Craig, David A. Bailey, Elizabeth C. Hunke, Philippe Blain, Till A. S. Rasmussen, Mats Bentsen, Frédéric Dupont, David Hebert, and Richard Allard
Geosci. Model Dev., 17, 6703–6724, https://doi.org/10.5194/gmd-17-6703-2024, https://doi.org/10.5194/gmd-17-6703-2024, 2024
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We present the latest version of the CICE model. It solves equations that describe the dynamics and the growth and melt of sea ice. To do so, the domain is divided into grid cells and variables are positioned at specific locations in the cells. A new implementation (C-grid) is presented, with the velocity located on cell edges. Compared to the previous B-grid, the C-grid allows for a natural coupling with some oceanic and atmospheric models. It also allows for ice transport in narrow channels.
Rachid El Montassir, Olivier Pannekoucke, and Corentin Lapeyre
Geosci. Model Dev., 17, 6657–6681, https://doi.org/10.5194/gmd-17-6657-2024, https://doi.org/10.5194/gmd-17-6657-2024, 2024
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This study introduces a novel approach that combines physics and artificial intelligence (AI) for improved cloud cover forecasting. This approach outperforms traditional deep learning (DL) methods in producing realistic and physically consistent results while requiring less training data. This architecture provides a promising solution to overcome the limitations of classical AI methods and contributes to open up new possibilities for combining physical knowledge with deep learning models.
Marit Sandstad, Borgar Aamaas, Ane Nordlie Johansen, Marianne Tronstad Lund, Glen Philip Peters, Bjørn Hallvard Samset, Benjamin Mark Sanderson, and Ragnhild Bieltvedt Skeie
Geosci. Model Dev., 17, 6589–6625, https://doi.org/10.5194/gmd-17-6589-2024, https://doi.org/10.5194/gmd-17-6589-2024, 2024
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The CICERO-SCM has existed as a Fortran model since 1999 that calculates the radiative forcing and concentrations from emissions and is 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.
Zheng Xiang, Yongkang Xue, Weidong Guo, Melannie D. Hartman, Ye Liu, and William J. Parton
Geosci. Model Dev., 17, 6437–6464, https://doi.org/10.5194/gmd-17-6437-2024, https://doi.org/10.5194/gmd-17-6437-2024, 2024
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A process-based plant carbon (C)–nitrogen (N) interface coupling framework has been developed which mainly focuses on plant resistance and N-limitation effects on photosynthesis, plant respiration, and plant phenology. A dynamic C / N ratio is introduced to represent plant resistance and self-adjustment. The framework has been implemented in a coupled biophysical-ecosystem–biogeochemical model, and testing results show a general improvement in simulating plant properties with this framework.
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
Geosci. Model Dev., 17, 6249–6275, https://doi.org/10.5194/gmd-17-6249-2024, https://doi.org/10.5194/gmd-17-6249-2024, 2024
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We give an overview of the Institute of Atmospheric Physics–Chinese Academy of Sciences subseasonal-to-seasonal ensemble forecasting system and Madden–Julian Oscillation forecast evaluation of the system. Compared to other S2S models, the IAP-CAS model has its benefits but also biases, i.e., underdispersive ensemble, overestimated amplitude, and faster propagation speed when forecasting MJO. We provide a reason for these biases and prospects for further improvement of this system in the future.
Laurent Brodeau, Pierre Rampal, Einar Ólason, and Véronique Dansereau
Geosci. Model Dev., 17, 6051–6082, https://doi.org/10.5194/gmd-17-6051-2024, https://doi.org/10.5194/gmd-17-6051-2024, 2024
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A new brittle sea ice rheology, BBM, has been implemented into the sea ice component of NEMO. We describe how a new spatial discretization framework was introduced to achieve this. A set of idealized and realistic ocean and sea ice simulations of the Arctic have been performed using BBM and the standard viscous–plastic rheology of NEMO. When compared to satellite data, our simulations show that our implementation of BBM leads to a fairly good representation of sea ice deformations.
Joseph P. Hollowed, Christiane Jablonowski, Hunter Y. Brown, Benjamin R. Hillman, Diana L. Bull, and Joseph L. Hart
Geosci. Model Dev., 17, 5913–5938, https://doi.org/10.5194/gmd-17-5913-2024, https://doi.org/10.5194/gmd-17-5913-2024, 2024
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Large volcanic eruptions deposit material in the upper atmosphere, which is capable of altering temperature and wind patterns of Earth's atmosphere for subsequent years. 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 test bed for climate attribution studies.
Hong Li, Yi Yang, Jian Sun, Yuan Jiang, Ruhui Gan, and Qian Xie
Geosci. Model Dev., 17, 5883–5896, https://doi.org/10.5194/gmd-17-5883-2024, https://doi.org/10.5194/gmd-17-5883-2024, 2024
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Vertical atmospheric motions play a vital role in convective-scale precipitation forecasts by connecting atmospheric dynamics with cloud development. A three-dimensional variational vertical velocity assimilation scheme is developed within the high-resolution CMA-MESO model, utilizing the adiabatic Richardson equation as the observation operator. A 10 d continuous run and an individual case study demonstrate improved forecasts, confirming the scheme's effectiveness.
Matthias Nützel, Laura Stecher, Patrick Jöckel, Franziska Winterstein, Martin Dameris, Michael Ponater, Phoebe Graf, and Markus Kunze
Geosci. Model Dev., 17, 5821–5849, https://doi.org/10.5194/gmd-17-5821-2024, https://doi.org/10.5194/gmd-17-5821-2024, 2024
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We extended the infrastructure of our modelling system to enable the use of an additional radiation scheme. After calibrating the model setups to the old and the new radiation scheme, we find that the simulation with the new scheme shows considerable improvements, e.g. concerning the cold-point temperature and stratospheric water vapour. Furthermore, perturbations of radiative fluxes associated with greenhouse gas changes, e.g. of methane, tend to be improved when the new scheme is employed.
Yibing Wang, Xianhong Xie, Bowen Zhu, Arken Tursun, Fuxiao Jiang, Yao Liu, Dawei Peng, and Buyun Zheng
Geosci. Model Dev., 17, 5803–5819, https://doi.org/10.5194/gmd-17-5803-2024, https://doi.org/10.5194/gmd-17-5803-2024, 2024
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Urban expansion intensifies challenges like urban heat and urban dry islands. To address this, we developed an urban module, VIC-urban, in the Variable Infiltration Capacity (VIC) model. Tested in Beijing, VIC-urban accurately simulated turbulent heat fluxes, runoff, and land surface temperature. We provide a reliable tool for large-scale simulations considering urban environment and a systematic urban modelling framework within VIC, offering crucial insights for urban planners and designers.
Jeremy Carter, Erick A. Chacón-Montalván, and Amber Leeson
Geosci. Model Dev., 17, 5733–5757, https://doi.org/10.5194/gmd-17-5733-2024, https://doi.org/10.5194/gmd-17-5733-2024, 2024
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Climate models are essential tools in the study of climate change and its wide-ranging impacts on life on Earth. However, the output is often afflicted with some bias. In this paper, a novel model is developed to predict and correct bias in the output of climate models. The model captures uncertainty in the correction and explicitly models underlying spatial correlation between points. These features are of key importance for climate change impact assessments and resulting decision-making.
Anna Martin, Veronika Gayler, Benedikt Steil, Klaus Klingmüller, Patrick Jöckel, Holger Tost, Jos Lelieveld, and Andrea Pozzer
Geosci. Model Dev., 17, 5705–5732, https://doi.org/10.5194/gmd-17-5705-2024, https://doi.org/10.5194/gmd-17-5705-2024, 2024
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The study evaluates the land surface and vegetation model JSBACHv4 as a replacement for the simplified submodel SURFACE in EMAC. JSBACH mitigates earlier problems of soil dryness, which are critical for vegetation modelling. When analysed using different datasets, the coupled model shows strong correlations of key variables, such as land surface temperature, surface albedo and radiation flux. The versatility of the model increases significantly, while the overall performance does not degrade.
Hugo Banderier, Christian Zeman, David Leutwyler, Stefan Rüdisühli, and Christoph Schär
Geosci. Model Dev., 17, 5573–5586, https://doi.org/10.5194/gmd-17-5573-2024, https://doi.org/10.5194/gmd-17-5573-2024, 2024
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We investigate the effects of reduced-precision arithmetic in a state-of-the-art regional climate model by studying the results of 10-year-long simulations. After this time, the results of the reduced precision and the standard implementation are hardly different. This should encourage the use of reduced precision in climate models to exploit the speedup and memory savings it brings. The methodology used in this work can help researchers verify reduced-precision implementations of their model.
David Fuchs, Steven C. Sherwood, Abhnil Prasad, Kirill Trapeznikov, and Jim Gimlett
Geosci. Model Dev., 17, 5459–5475, https://doi.org/10.5194/gmd-17-5459-2024, https://doi.org/10.5194/gmd-17-5459-2024, 2024
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Machine learning (ML) of unresolved processes offers many new possibilities for improving weather and climate models, but integrating ML into the models has been an engineering challenge, and there are performance issues. We present a new software plugin for this integration, TorchClim, that is scalable and flexible and thereby allows a new level of experimentation with the ML approach. We also provide guidance on ML training and demonstrate a skillful hybrid ML atmosphere model.
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.
Deifilia Aurora To, Julian Quinting, Gholam Ali Hoshyaripour, Markus Götz, Achim Streit, and Charlotte Debus
EGUsphere, https://doi.org/10.5194/egusphere-2024-1714, https://doi.org/10.5194/egusphere-2024-1714, 2024
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Pangu-Weather is a breakthrough machine learning model in medium-range weather forecasting that considers three-dimensional atmospheric information. We show that using a simpler 2D framework improves robustness, speeds up training, and reduces computational needs by 20–30%. We introduce a training procedure that varies the importance of atmospheric variables over time to speed up training convergence. Decreasing computational demand increases accessibility of training and working with the model.
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.
Peter Berg, Thomas Bosshard, Denica Bozhinova, Lars Bärring, Joakim Löw, Carolina Nilsson, Gustav Strandberg, Johan Södling, Johan Thuresson, Renate Wilcke, and Wei Yang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-98, https://doi.org/10.5194/gmd-2024-98, 2024
Revised manuscript accepted for GMD
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When bias adjusting climate model data using quantile mapping, one needs to prescribe what to do at the tails of the distribution, where a larger range of data is likely encountered outside the calibration period. The end result is highly dependent on the method used, and we show that one needs to exclude data in the calibration range to activate the extrapolation functionality also in that time period, else there will be discontinuities in the timeseries.
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.
Maria Rosa Russo, Sadie L. Bartholomew, David Hassell, Alex M. Mason, Erica Neininger, A. James Perman, David A. J. Sproson, Duncan Watson-Parris, and Nathan Luke Abraham
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-73, https://doi.org/10.5194/gmd-2024-73, 2024
Revised manuscript accepted for GMD
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Observational data and modelling capabilities are expanding in recent years, but there are still barriers preventing these two data sources to be used in synergy. Proper comparison requires generating, storing and handling a large amount of data. This manuscript describes the first step in the development of a new set of software tools, the ‘VISION toolkit’, which can enable the easy and efficient integration of observational and model data required for model evaluation.
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”.
Seung H. Baek, Paul A. Ullrich, Bo Dong, and Jiwoo Lee
EGUsphere, https://doi.org/10.5194/egusphere-2024-1456, https://doi.org/10.5194/egusphere-2024-1456, 2024
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We evaluate downscaled products by examining locally relevant covariances during convective and frontal precipitation events. Common statistical downscaling techniques preserve expected covariances during convective precipitation. However, they dampen future intensification of frontal precipitation captured in global climate models and dynamical downscaling. This suggests statistical downscaling may not fully resolve non-stationary hydrologic processes as compared to dynamical downscaling.
Emmanuel Nyenah, Petra Döll, Daniel S. Katz, and Robert Reinecke
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-97, https://doi.org/10.5194/gmd-2024-97, 2024
Revised manuscript accepted for GMD
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Research software is crucial for scientific progress but is often developed by scientists with limited training, time, and funding, leading to software that is hard to understand, (re)use, modify, and maintain. Our study across 10 research sectors highlights strengths in version control, open-source licensing, and documentation while emphasizing the need for containerization and code quality. Recommendations include workshops, code quality metrics, funding, and adherence to FAIR standards.
Yilin Fang, Hoang Viet Tran, and L. Ruby Leung
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-70, https://doi.org/10.5194/gmd-2024-70, 2024
Revised manuscript accepted for GMD
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Hurricanes may worsen the water quality in the lower Mississippi River Basin (LMRB) by increasing nutrient runoff. We found that runoff parameterizations greatly affect nitrate-nitrogen runoff simulated using an Earth system land model. Our simulations predicted increased nitrogen runoff in LMRB during Hurricane Ida in 2021, but less pronounced than the observations, indicating areas for model improvement to better understand and manage nutrient runoff loss during hurricanes in the region.
Giovanni G. Seijo-Ellis, Donata Giglio, Gustavo M. Marques, and Frank O. Bryan
EGUsphere, https://doi.org/10.5194/egusphere-2024-1378, https://doi.org/10.5194/egusphere-2024-1378, 2024
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A CESM/MOM6 regional configuration of the Caribbean Sea was developed as a response to the rising need of high-resolution models for climate impact studies. The configuration is validated for the period of 2000–2020 and improves significant errors in a low resolution model. Oceanic properties are well represented. Patterns of freshwater associated with the Amazon river are well captured and the mean flows across the multiple passages in the Caribbean Sea agree with observations.
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.
Catherine Guiavarc'h, Dave Storkey, Adam T. Blaker, Ed Blockley, Alex Megann, Helene T. Hewitt, Michael J. Bell, Daley Calvert, Dan Copsey, Bablu Sinha, Sophia Moreton, Pierre Mathiot, and Bo An
EGUsphere, https://doi.org/10.5194/egusphere-2024-805, https://doi.org/10.5194/egusphere-2024-805, 2024
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GOSI9 is the new UK’s hierarchy of global ocean and sea ice models. Developed as part of a collaboration between several UK research institutes it will be used for various applications such as weather forecast and climate prediction. The models, based on NEMO, are available at three resolutions 1°, ¼° and 1/12°. GOSI9 improves upon previous version by reducing global temperature and salinity biases and enhancing the representation of the Arctic sea ice and of the Antarctic Circumpolar Current.
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.
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...
