Articles | Volume 7, issue 4
https://doi.org/10.5194/gmd-7-1377-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/gmd-7-1377-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model description paper
| 
10 Jul 2014
Model description paper |
| 10 Jul 2014
Adding a dynamical cryosphere to iLOVECLIM (version 1.0): coupling with the GRISLI ice-sheet model
D. M. Roche
Laboratoire des Sciences du Climat et de l'Environnement (LSCE), UMR8212, CEA/CNRS-INSU/UVSQ, Gif-sur-Yvette Cedex, France
Earth and Climate Cluster, Faculty of Earth and Life Sciences, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
C. Dumas
Laboratoire des Sciences du Climat et de l'Environnement (LSCE), UMR8212, CEA/CNRS-INSU/UVSQ, Gif-sur-Yvette Cedex, France
M. Bügelmayer
Earth and Climate Cluster, Faculty of Earth and Life Sciences, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
S. Charbit
Laboratoire des Sciences du Climat et de l'Environnement (LSCE), UMR8212, CEA/CNRS-INSU/UVSQ, Gif-sur-Yvette Cedex, France
Laboratoire de Glaciologie et Géophysique de l'Environnement (LGGE), UMR5183 CNRS/UJF-Grenoble I, Saint Martin d'Hères, France
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This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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The ice-ocean interaction is a large source of uncertainty in future projections of the Antarctic ice sheet. Here we implement a basal ice shelf melt module (PICO) in a ice sheet model (GRISLI) and test six simple statistical methods to calibrate this module. We show that calculating the mean absolute error of bins best fits the observational datasets under multiple conditions. We also assess the impact of the module implementation and calibration choice on future projections until 2300.
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To improve the simulation of surface mass balance (SMB) that influences the advance–retreat of ice sheets, we run a snow model, the BErgen Snow SImulator (BESSI), with transient climate forcing obtained from an Earth system model, iLOVECLIM, over Greenland and Antarctica during the Last Interglacial (LIG; 130–116 ka). Compared to the simple existing SMB scheme of iLOVECLIM, BESSI gives more details about SMB processes with higher physics constraints while maintaining a low computational cost.
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In this work, we use the same experimental protocol to simulate the last two glacial terminations with a coupled ice sheet–climate model. Major differences among the two terminations are that the ice sheets retreat earlier and the Atlantic oceanic circulation is more prone to collapse during the penultimate termination. However, for both terminations the pattern of ice retreat is similar, and this retreat is primarily explained by orbital forcing changes and greenhouse gas concentration changes.
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Stable water isotopes are used to infer changes in the hydrological cycle for different time periods in climatic archive and climate models. We present the implementation of the δ2H and δ17O water isotopes in the coupled climate model iLOVECLIM and calculate the d- and 17O-excess. Results of a simulation under preindustrial conditions show that the model correctly reproduces the water isotope distribution in the atmosphere and ocean in comparison to data and other global circulation models.
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This study analyses transient simulations of the last deglaciation performed by six climate models to understand the processes driving southern high latitude temperature changes. We find that atmospheric CO2 changes and AMOC changes are the primary drivers of the major warming and cooling during the middle stage of the deglaciation. The multi-model analysis highlights the model’s sensitivity of CO2, AMOC to meltwater, and the meltwater history on temperature changes in southern high latitudes.
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Natural climate variability plays an important role in the discussion of past and future climate change. Here we study centennial temperature variability and the role of large-scale ocean circulation variability using different climate models, geological reconstructions and temperature observations. Unfortunately, uncertainties in models and geological reconstructions are such that more research is needed before we can describe the characteristics of natural centennial temperature variability.
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Masa Kageyama, Pascale Braconnot, Sandy P. Harrison, Alan M. Haywood, Johann H. Jungclaus, Bette L. Otto-Bliesner, Jean-Yves Peterschmitt, Ayako Abe-Ouchi, Samuel Albani, Patrick J. Bartlein, Chris Brierley, Michel Crucifix, Aisling Dolan, Laura Fernandez-Donado, Hubertus Fischer, Peter O. Hopcroft, Ruza F. Ivanovic, Fabrice Lambert, Daniel J. Lunt, Natalie M. Mahowald, W. Richard Peltier, Steven J. Phipps, Didier M. Roche, Gavin A. Schmidt, Lev Tarasov, Paul J. Valdes, Qiong Zhang, and Tianjun Zhou
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Earth system models of intermediate complexity generally have a simplified model physics and a coarse model resolution. In this work we present the inclusion of an online dynamical downscaling of temperature and precipitation in such a model. This downscaling explicitly takes into account sub-grid topography. With this new model functionality we are able to simulate temperature and precipitation on a 40 km grid for the whole Northern Hemisphere from the native model resolution.
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The Last Glacial Maximum (LGM, 21000 years ago) is an interval when global ice volume was at a maximum, eustatic sea level close to a minimum, greenhouse gas concentrations were lower, atmospheric aerosol loadings were higher than today, and vegetation and land-surface characteristics were different from today. This paper describes the implementation of the LGM numerical experiment for the PMIP4-CMIP6 modelling intercomparison projects and the associated sensitivity experiments.
Pierre Burckel, Claire Waelbroeck, Yiming Luo, Didier M. Roche, Sylvain Pichat, Samuel L. Jaccard, Jeanne Gherardi, Aline Govin, Jörg Lippold, and François Thil
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In this paper, we compare new and published Atlantic sedimentary Pa/Th data with Pa/Th simulated using stream functions generated under various climatic conditions. We show that during Greenland interstadials of the 20–50 ka period, the Atlantic meridional overturning circulation was very different from that of the Holocene. Moreover, southern-sourced waters dominated the Atlantic during Heinrich stadial 2, a slow northern-sourced water mass flowing above 2500 m in the North Atlantic.
Timothé Bolliet, Patrick Brockmann, Valérie Masson-Delmotte, Franck Bassinot, Valérie Daux, Dominique Genty, Amaelle Landais, Marlène Lavrieux, Elisabeth Michel, Pablo Ortega, Camille Risi, Didier M. Roche, Françoise Vimeux, and Claire Waelbroeck
Clim. Past, 12, 1693–1719, https://doi.org/10.5194/cp-12-1693-2016, https://doi.org/10.5194/cp-12-1693-2016, 2016
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This paper presents a new database of past climate proxies which aims to facilitate the distribution of data by using a user-friendly interface. Available data from the last 40 years are often fragmented, with lots of different formats, and online libraries are sometimes nonintuitive. We thus built a new dynamic web portal for data browsing, visualizing, and batch downloading of hundreds of datasets presenting a homogeneous format.
Ruza F. Ivanovic, Lauren J. Gregoire, Masa Kageyama, Didier M. Roche, Paul J. Valdes, Andrea Burke, Rosemarie Drummond, W. Richard Peltier, and Lev Tarasov
Geosci. Model Dev., 9, 2563–2587, https://doi.org/10.5194/gmd-9-2563-2016, https://doi.org/10.5194/gmd-9-2563-2016, 2016
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This manuscript presents the experiment design for the PMIP4 Last Deglaciation Core experiment: a transient simulation of the last deglaciation, 21–9 ka. Specified model boundary conditions include time-varying orbital parameters, greenhouse gases, ice sheets, ice meltwater fluxes and other geographical changes (provided for 26–0 ka). The context of the experiment and the choices for the boundary conditions are explained, along with the future direction of the working group.
Marianne Bügelmayer-Blaschek, Didier M. Roche, Hans Renssen, and Claire Waelbroeck
Clim. Past Discuss., https://doi.org/10.5194/cp-2016-31, https://doi.org/10.5194/cp-2016-31, 2016
Revised manuscript has not been submitted
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Using the global isotope-enabled climate – iceberg model iLOVECLIM we performed three experiments to investigate the mechanisms behind the simulated δ18Ocalcite pattern applying a Heinrich event like iceberg forcing. Our model results display two main patterns in the δ18Ocalcite signal. First, we find regions that display almost no response in δ18Ocalcite and second, regions where the δ18Ocalcite pattern closely follows the δ18Oseawater signal.
M. Bügelmayer, D. M. Roche, and H. Renssen
Geosci. Model Dev., 8, 2139–2151, https://doi.org/10.5194/gmd-8-2139-2015, https://doi.org/10.5194/gmd-8-2139-2015, 2015
N. Bouttes, D. M. Roche, V. Mariotti, and L. Bopp
Geosci. Model Dev., 8, 1563–1576, https://doi.org/10.5194/gmd-8-1563-2015, https://doi.org/10.5194/gmd-8-1563-2015, 2015
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We describe the development of a relatively simple climate model to include a model of the carbon cycle in the ocean. The carbon cycle consists of the exchange of carbon between the atmosphere, land vegetation and ocean. In the ocean, carbon exists in organic form, such as plankton which grows and dies, and inorganic forms, such as dissolved CO2. With this we will be able to explore long-standing questions such as why the atmospheric CO2 has changed over time during the last million years.
D. C. Kitover, R. van Balen, D. M. Roche, J. Vandenberghe, and H. Renssen
Geosci. Model Dev., 8, 1445–1460, https://doi.org/10.5194/gmd-8-1445-2015, https://doi.org/10.5194/gmd-8-1445-2015, 2015
M. Bügelmayer, D. M. Roche, and H. Renssen
The Cryosphere, 9, 821–835, https://doi.org/10.5194/tc-9-821-2015, https://doi.org/10.5194/tc-9-821-2015, 2015
K. A. Crichton, D. M. Roche, G. Krinner, and J. Chappellaz
Geosci. Model Dev., 7, 3111–3134, https://doi.org/10.5194/gmd-7-3111-2014, https://doi.org/10.5194/gmd-7-3111-2014, 2014
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Permafrost is ground that remains frozen for two or more consecutive years. An estimated 50% of the global below-ground organic carbon is stored in soils of the permafrost zone. This study presents the development and validation of a simplified permafrost-carbon mechanism for the CLIMBER-2 model. Our model development allows, for the first time, the study of the role of permafrost soils in the global carbon cycle for long timescales and for coupled palaeoclimate Earth system modelling studies.
T. Caley, D. M. Roche, C. Waelbroeck, and E. Michel
Clim. Past, 10, 1939–1955, https://doi.org/10.5194/cp-10-1939-2014, https://doi.org/10.5194/cp-10-1939-2014, 2014
P. Beghin, S. Charbit, C. Dumas, M. Kageyama, D. M. Roche, and C. Ritz
Clim. Past, 10, 345–358, https://doi.org/10.5194/cp-10-345-2014, https://doi.org/10.5194/cp-10-345-2014, 2014
D. M. Roche
Geosci. Model Dev., 6, 1481–1491, https://doi.org/10.5194/gmd-6-1481-2013, https://doi.org/10.5194/gmd-6-1481-2013, 2013
D. M. Roche and T. Caley
Geosci. Model Dev., 6, 1493–1504, https://doi.org/10.5194/gmd-6-1493-2013, https://doi.org/10.5194/gmd-6-1493-2013, 2013
T. Caley and D. M. Roche
Geosci. Model Dev., 6, 1505–1516, https://doi.org/10.5194/gmd-6-1505-2013, https://doi.org/10.5194/gmd-6-1505-2013, 2013
S. Charbit, C. Dumas, M. Kageyama, D. M. Roche, and C. Ritz
The Cryosphere, 7, 681–698, https://doi.org/10.5194/tc-7-681-2013, https://doi.org/10.5194/tc-7-681-2013, 2013
M. Kageyama, U. Merkel, B. Otto-Bliesner, M. Prange, A. Abe-Ouchi, G. Lohmann, R. Ohgaito, D. M. Roche, J. Singarayer, D. Swingedouw, and X Zhang
Clim. Past, 9, 935–953, https://doi.org/10.5194/cp-9-935-2013, https://doi.org/10.5194/cp-9-935-2013, 2013
J. Zumaque, F. Eynaud, S. Zaragosi, F. Marret, K. M. Matsuzaki, C. Kissel, D. M. Roche, B. Malaizé, E. Michel, I. Billy, T. Richter, and E. Palis
Clim. Past, 8, 1997–2017, https://doi.org/10.5194/cp-8-1997-2012, https://doi.org/10.5194/cp-8-1997-2012, 2012
Maxence Menthon, Pepijn Bakker, Aurélien Quiquet, Didier M. Roche, and Ronja Reese
EGUsphere, https://doi.org/10.5194/egusphere-2025-777, https://doi.org/10.5194/egusphere-2025-777, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
The ice-ocean interaction is a large source of uncertainty in future projections of the Antarctic ice sheet. Here we implement a basal ice shelf melt module (PICO) in a ice sheet model (GRISLI) and test six simple statistical methods to calibrate this module. We show that calculating the mean absolute error of bins best fits the observational datasets under multiple conditions. We also assess the impact of the module implementation and calibration choice on future projections until 2300.
Thi-Khanh-Dieu Hoang, Aurélien Quiquet, Christophe Dumas, Andreas Born, and Didier M. Roche
Clim. Past, 21, 27–51, https://doi.org/10.5194/cp-21-27-2025, https://doi.org/10.5194/cp-21-27-2025, 2025
Short summary
Short summary
To improve the simulation of surface mass balance (SMB) that influences the advance–retreat of ice sheets, we run a snow model, the BErgen Snow SImulator (BESSI), with transient climate forcing obtained from an Earth system model, iLOVECLIM, over Greenland and Antarctica during the Last Interglacial (LIG; 130–116 ka). Compared to the simple existing SMB scheme of iLOVECLIM, BESSI gives more details about SMB processes with higher physics constraints while maintaining a low computational cost.
Sylvie Charbit, Christophe Dumas, Fabienne Maignan, Catherine Ottlé, Nina Raoult, Xavier Fettweis, and Philippe Conesa
The Cryosphere, 18, 5067–5099, https://doi.org/10.5194/tc-18-5067-2024, https://doi.org/10.5194/tc-18-5067-2024, 2024
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The evolution of the Greenland ice sheet is highly dependent on surface melting and therefore on the processes operating at the snow–atmosphere interface and within the snow cover. Here we present new developments to apply a snow model to the Greenland ice sheet. The performance of this model is analysed in terms of its ability to simulate ablation processes. Our analysis shows that the model performs well when compared with the MAR regional polar atmospheric model.
Aurélien Quiquet and Didier M. Roche
Clim. Past, 20, 1365–1385, https://doi.org/10.5194/cp-20-1365-2024, https://doi.org/10.5194/cp-20-1365-2024, 2024
Short summary
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In this work, we use the same experimental protocol to simulate the last two glacial terminations with a coupled ice sheet–climate model. Major differences among the two terminations are that the ice sheets retreat earlier and the Atlantic oceanic circulation is more prone to collapse during the penultimate termination. However, for both terminations the pattern of ice retreat is similar, and this retreat is primarily explained by orbital forcing changes and greenhouse gas concentration changes.
Thomas Extier, Thibaut Caley, and Didier M. Roche
Geosci. Model Dev., 17, 2117–2139, https://doi.org/10.5194/gmd-17-2117-2024, https://doi.org/10.5194/gmd-17-2117-2024, 2024
Short summary
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Stable water isotopes are used to infer changes in the hydrological cycle for different time periods in climatic archive and climate models. We present the implementation of the δ2H and δ17O water isotopes in the coupled climate model iLOVECLIM and calculate the d- and 17O-excess. Results of a simulation under preindustrial conditions show that the model correctly reproduces the water isotope distribution in the atmosphere and ocean in comparison to data and other global circulation models.
Victor van Aalderen, Sylvie Charbit, Christophe Dumas, and Aurélien Quiquet
Clim. Past, 20, 187–209, https://doi.org/10.5194/cp-20-187-2024, https://doi.org/10.5194/cp-20-187-2024, 2024
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We present idealized numerical experiments to test the main mechanisms that triggered the deglaciation of the past Eurasian ice sheet. Simulations were performed with the GRISLI2.0 ice sheet model. The results indicate that the Eurasian ice sheet was primarily driven by surface melting, due to increased atmospheric temperatures. Basal melting below the ice shelves is only a significant driver if ocean temperatures increase by nearly 10 °C, in contrast with the findings of previous studies.
Hélène Seroussi, Vincent Verjans, Sophie Nowicki, Antony J. Payne, Heiko Goelzer, William H. Lipscomb, Ayako Abe-Ouchi, Cécile Agosta, Torsten Albrecht, Xylar Asay-Davis, Alice Barthel, Reinhard Calov, Richard Cullather, Christophe Dumas, Benjamin K. Galton-Fenzi, Rupert Gladstone, Nicholas R. Golledge, Jonathan M. Gregory, Ralf Greve, Tore Hattermann, Matthew J. Hoffman, Angelika Humbert, Philippe Huybrechts, Nicolas C. Jourdain, Thomas Kleiner, Eric Larour, Gunter R. Leguy, Daniel P. Lowry, Chistopher M. Little, Mathieu Morlighem, Frank Pattyn, Tyler Pelle, Stephen F. Price, Aurélien Quiquet, Ronja Reese, Nicole-Jeanne Schlegel, Andrew Shepherd, Erika Simon, Robin S. Smith, Fiammetta Straneo, Sainan Sun, Luke D. Trusel, Jonas Van Breedam, Peter Van Katwyk, Roderik S. W. van de Wal, Ricarda Winkelmann, Chen Zhao, Tong Zhang, and Thomas Zwinger
The Cryosphere, 17, 5197–5217, https://doi.org/10.5194/tc-17-5197-2023, https://doi.org/10.5194/tc-17-5197-2023, 2023
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Mass loss from Antarctica is a key contributor to sea level rise over the 21st century, and the associated uncertainty dominates sea level projections. We highlight here the Antarctic glaciers showing the largest changes and quantify the main sources of uncertainty in their future evolution using an ensemble of ice flow models. We show that on top of Pine Island and Thwaites glaciers, Totten and Moscow University glaciers show rapid changes and a strong sensitivity to warmer ocean conditions.
Takashi Obase, Laurie Menviel, Ayako Abe-Ouchi, Tristan Vadsaria, Ruza Ivanovic, Brooke Snoll, Sam Sherriff-Tadano, Paul Valdes, Lauren Gregoire, Marie-Luise Kapsch, Uwe Mikolajewicz, Nathaelle Bouttes, Didier Roche, Fanny Lhardy, Chengfei He, Bette Otto-Bliesner, Zhengyu Liu, and Wing-Le Chan
Clim. Past Discuss., https://doi.org/10.5194/cp-2023-86, https://doi.org/10.5194/cp-2023-86, 2023
Preprint under review for CP
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This study analyses transient simulations of the last deglaciation performed by six climate models to understand the processes driving southern high latitude temperature changes. We find that atmospheric CO2 changes and AMOC changes are the primary drivers of the major warming and cooling during the middle stage of the deglaciation. The multi-model analysis highlights the model’s sensitivity of CO2, AMOC to meltwater, and the meltwater history on temperature changes in southern high latitudes.
Ailsa Chung, Frédéric Parrenin, Daniel Steinhage, Robert Mulvaney, Carlos Martín, Marie G. P. Cavitte, David A. Lilien, Veit Helm, Drew Taylor, Prasad Gogineni, Catherine Ritz, Massimo Frezzotti, Charles O'Neill, Heinrich Miller, Dorthe Dahl-Jensen, and Olaf Eisen
The Cryosphere, 17, 3461–3483, https://doi.org/10.5194/tc-17-3461-2023, https://doi.org/10.5194/tc-17-3461-2023, 2023
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We combined a numerical model with radar measurements in order to determine the age of ice in the Dome C region of Antarctica. Our results show that at the current ice core drilling sites on Little Dome C, the maximum age of the ice is almost 1.5 Ma. We also highlight a new potential drill site called North Patch with ice up to 2 Ma. Finally, we explore the nature of a stagnant ice layer at the base of the ice sheet which has been independently observed and modelled but is not well understood.
Benoit S. Lecavalier, Lev Tarasov, Greg Balco, Perry Spector, Claus-Dieter Hillenbrand, Christo Buizert, Catherine Ritz, Marion Leduc-Leballeur, Robert Mulvaney, Pippa L. Whitehouse, Michael J. Bentley, and Jonathan Bamber
Earth Syst. Sci. Data, 15, 3573–3596, https://doi.org/10.5194/essd-15-3573-2023, https://doi.org/10.5194/essd-15-3573-2023, 2023
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The Antarctic Ice Sheet Evolution constraint database version 2 (AntICE2) consists of a large variety of observations that constrain the evolution of the Antarctic Ice Sheet over the last glacial cycle. This includes observations of past ice sheet extent, past ice thickness, past relative sea level, borehole temperature profiles, and present-day bedrock displacement rates. The database is intended to improve our understanding of past Antarctic changes and for ice sheet model calibrations.
Nina Raoult, Sylvie Charbit, Christophe Dumas, Fabienne Maignan, Catherine Ottlé, and Vladislav Bastrikov
The Cryosphere, 17, 2705–2724, https://doi.org/10.5194/tc-17-2705-2023, https://doi.org/10.5194/tc-17-2705-2023, 2023
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Greenland ice sheet melting due to global warming could significantly impact global sea-level rise. The ice sheet's albedo, i.e. how reflective the surface is, affects the melting speed. The ORCHIDEE computer model is used to simulate albedo and snowmelt to make predictions. However, the albedo in ORCHIDEE is lower than that observed using satellites. To correct this, we change model parameters (e.g. the rate of snow decay) to reduce the difference between simulated and observed values.
Nathaelle Bouttes, Fanny Lhardy, Aurélien Quiquet, Didier Paillard, Hugues Goosse, and Didier M. Roche
Clim. Past, 19, 1027–1042, https://doi.org/10.5194/cp-19-1027-2023, https://doi.org/10.5194/cp-19-1027-2023, 2023
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The last deglaciation is a period of large warming from 21 000 to 9000 years ago, concomitant with ice sheet melting. Here, we evaluate the impact of different ice sheet reconstructions and different processes linked to their changes. Changes in bathymetry and coastlines, although not often accounted for, cannot be neglected. Ice sheet melt results in freshwater into the ocean with large effects on ocean circulation, but the timing cannot explain the observed abrupt climate changes.
Frank Arthur, Didier M. Roche, Ralph Fyfe, Aurélien Quiquet, and Hans Renssen
Clim. Past, 19, 87–106, https://doi.org/10.5194/cp-19-87-2023, https://doi.org/10.5194/cp-19-87-2023, 2023
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This paper simulates transcient Holocene climate in Europe by applying an interactive downscaling to the standard version of the iLOVECLIM model. The results show that downscaling presents a higher spatial variability in better agreement with proxy-based reconstructions as compared to the standard model, particularly in the Alps, the Scandes, and the Mediterranean. Our downscaling scheme is numerically cheap, which can perform kilometric multi-millennial simulations suitable for future studies.
Pepijn Bakker, Hugues Goosse, and Didier M. Roche
Clim. Past, 18, 2523–2544, https://doi.org/10.5194/cp-18-2523-2022, https://doi.org/10.5194/cp-18-2523-2022, 2022
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Natural climate variability plays an important role in the discussion of past and future climate change. Here we study centennial temperature variability and the role of large-scale ocean circulation variability using different climate models, geological reconstructions and temperature observations. Unfortunately, uncertainties in models and geological reconstructions are such that more research is needed before we can describe the characteristics of natural centennial temperature variability.
Huan Li, Hans Renssen, and Didier M. Roche
Clim. Past, 18, 2303–2319, https://doi.org/10.5194/cp-18-2303-2022, https://doi.org/10.5194/cp-18-2303-2022, 2022
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In past warm periods, the Sahara region was covered by vegetation. In this paper we study transitions from this
greenstate to the desert state we find today. For this purpose, we have used a global climate model coupled to a vegetation model to perform transient simulations. We analyzed the model results to assess the effect of vegetation shifts on the abruptness of the transition. We find that the vegetation feedback was more efficient during the last interglacial than during the Holocene.
M. Reza Ershadi, Reinhard Drews, Carlos Martín, Olaf Eisen, Catherine Ritz, Hugh Corr, Julia Christmann, Ole Zeising, Angelika Humbert, and Robert Mulvaney
The Cryosphere, 16, 1719–1739, https://doi.org/10.5194/tc-16-1719-2022, https://doi.org/10.5194/tc-16-1719-2022, 2022
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Radio waves transmitted through ice split up and inform us about the ice sheet interior and orientation of single ice crystals. This can be used to infer how ice flows and improve projections on how it will evolve in the future. Here we used an inverse approach and developed a new algorithm to infer ice properties from observed radar data. We applied this technique to the radar data obtained at two EPICA drilling sites, where ice cores were used to validate our results.
Marie Sicard, Masa Kageyama, Sylvie Charbit, Pascale Braconnot, and Jean-Baptiste Madeleine
Clim. Past, 18, 607–629, https://doi.org/10.5194/cp-18-607-2022, https://doi.org/10.5194/cp-18-607-2022, 2022
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The Last Interglacial (129–116 ka) is characterised by an increased summer insolation over the Arctic region, which leads to a strong temperature rise. The aim of this study is to identify and quantify the main processes and feedback causing this Arctic warming. Using the IPSL-CM6A-LR model, we investigate changes in the energy budget relative to the pre-industrial period. We highlight the crucial role of Arctic sea ice cover, ocean and clouds on the Last Interglacial Arctic warming.
Marie G. P. Cavitte, Duncan A. Young, Robert Mulvaney, Catherine Ritz, Jamin S. Greenbaum, Gregory Ng, Scott D. Kempf, Enrica Quartini, Gail R. Muldoon, John Paden, Massimo Frezzotti, Jason L. Roberts, Carly R. Tozer, Dustin M. Schroeder, and Donald D. Blankenship
Earth Syst. Sci. Data, 13, 4759–4777, https://doi.org/10.5194/essd-13-4759-2021, https://doi.org/10.5194/essd-13-4759-2021, 2021
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We present a data set consisting of ice-penetrating-radar internal stratigraphy: 26 internal reflecting horizons that cover the greater Dome C area, East Antarctica, the most extensive IRH data set to date in the region. This data set uses radar surveys collected over the span of 10 years, starting with an airborne international collaboration in 2008 to explore the region, up to the detailed ground-based surveys in support of the European Beyond EPICA – Oldest Ice (BE-OI) project.
Aurélien Quiquet, Didier M. Roche, Christophe Dumas, Nathaëlle Bouttes, and Fanny Lhardy
Clim. Past, 17, 2179–2199, https://doi.org/10.5194/cp-17-2179-2021, https://doi.org/10.5194/cp-17-2179-2021, 2021
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In this paper we discuss results obtained with a set of coupled ice-sheet–climate model experiments for the last 26 kyrs. The model displays a large sensitivity of the oceanic circulation to the amount of the freshwater flux resulting from ice sheet melting. Ice sheet geometry changes alone are not enough to lead to abrupt climate events, and rapid warming at high latitudes is here only reported during abrupt oceanic circulation recoveries that occurred when accounting for freshwater flux.
Fanny Lhardy, Nathaëlle Bouttes, Didier M. Roche, Xavier Crosta, Claire Waelbroeck, and Didier Paillard
Clim. Past, 17, 1139–1159, https://doi.org/10.5194/cp-17-1139-2021, https://doi.org/10.5194/cp-17-1139-2021, 2021
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Climate models struggle to simulate a LGM ocean circulation in agreement with paleotracer data. Using a set of simulations, we test the impact of boundary conditions and other modelling choices. Model–data comparisons of sea-surface temperatures and sea-ice cover support an overall cold Southern Ocean, with implications on the AMOC strength. Changes in implemented boundary conditions are not sufficient to simulate a shallower AMOC; other mechanisms to better represent convection are required.
Masa Kageyama, Sandy P. Harrison, Marie-L. Kapsch, Marcus Lofverstrom, Juan M. Lora, Uwe Mikolajewicz, Sam Sherriff-Tadano, Tristan Vadsaria, Ayako Abe-Ouchi, Nathaelle Bouttes, Deepak Chandan, Lauren J. Gregoire, Ruza F. Ivanovic, Kenji Izumi, Allegra N. LeGrande, Fanny Lhardy, Gerrit Lohmann, Polina A. Morozova, Rumi Ohgaito, André Paul, W. Richard Peltier, Christopher J. Poulsen, Aurélien Quiquet, Didier M. Roche, Xiaoxu Shi, Jessica E. Tierney, Paul J. Valdes, Evgeny Volodin, and Jiang Zhu
Clim. Past, 17, 1065–1089, https://doi.org/10.5194/cp-17-1065-2021, https://doi.org/10.5194/cp-17-1065-2021, 2021
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The Last Glacial Maximum (LGM; ~21 000 years ago) is a major focus for evaluating how well climate models simulate climate changes as large as those expected in the future. Here, we compare the latest climate model (CMIP6-PMIP4) to the previous one (CMIP5-PMIP3) and to reconstructions. Large-scale climate features (e.g. land–sea contrast, polar amplification) are well captured by all models, while regional changes (e.g. winter extratropical cooling, precipitations) are still poorly represented.
David A. Lilien, Daniel Steinhage, Drew Taylor, Frédéric Parrenin, Catherine Ritz, Robert Mulvaney, Carlos Martín, Jie-Bang Yan, Charles O'Neill, Massimo Frezzotti, Heinrich Miller, Prasad Gogineni, Dorthe Dahl-Jensen, and Olaf Eisen
The Cryosphere, 15, 1881–1888, https://doi.org/10.5194/tc-15-1881-2021, https://doi.org/10.5194/tc-15-1881-2021, 2021
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We collected radar data between EDC, an ice core spanning ~800 000 years, and BELDC, the site chosen for a new
oldest icecore at nearby Little Dome C. These data allow us to identify 50 % older internal horizons than previously traced in the area. We fit a model to the ages of those horizons at BELDC to determine the age of deep ice there. We find that there is likely to be 1.5 Myr old ice ~265 m above the bed, with sufficient resolution to preserve desired climatic information.
Aurélien Quiquet and Christophe Dumas
The Cryosphere, 15, 1015–1030, https://doi.org/10.5194/tc-15-1015-2021, https://doi.org/10.5194/tc-15-1015-2021, 2021
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We present here the GRISLI-LSCE contribution to the Ice Sheet Model Intercomparison Project for CMIP6 for Greenland. The project aims to quantify the ice sheet contribution to global sea level rise for the next century. We show an important spread in the simulated Greenland ice loss in the future depending on the climate forcing used. Mass loss is primarily driven by atmospheric warming, while oceanic forcing contributes to a relatively smaller uncertainty in our simulations.
Aurélien Quiquet and Christophe Dumas
The Cryosphere, 15, 1031–1052, https://doi.org/10.5194/tc-15-1031-2021, https://doi.org/10.5194/tc-15-1031-2021, 2021
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We present here the GRISLI-LSCE contribution to the Ice Sheet Model Intercomparison Project for CMIP6 for Antarctica. The project aims to quantify the ice sheet contribution to global sea level rise for the next century. We show that increased precipitation in the future in some cases mitigates this contribution, with positive to negative values in 2100 depending of the climate forcing used. Sub-shelf-basal-melt uncertainties induce large differences in simulated grounding-line retreats.
Heiko Goelzer, Sophie Nowicki, Anthony Payne, Eric Larour, Helene Seroussi, William H. Lipscomb, Jonathan Gregory, Ayako Abe-Ouchi, Andrew Shepherd, Erika Simon, Cécile Agosta, Patrick Alexander, Andy Aschwanden, Alice Barthel, Reinhard Calov, Christopher Chambers, Youngmin Choi, Joshua Cuzzone, Christophe Dumas, Tamsin Edwards, Denis Felikson, Xavier Fettweis, Nicholas R. Golledge, Ralf Greve, Angelika Humbert, Philippe Huybrechts, Sebastien Le clec'h, Victoria Lee, Gunter Leguy, Chris Little, Daniel P. Lowry, Mathieu Morlighem, Isabel Nias, Aurelien Quiquet, Martin Rückamp, Nicole-Jeanne Schlegel, Donald A. Slater, Robin S. Smith, Fiamma Straneo, Lev Tarasov, Roderik van de Wal, and Michiel van den Broeke
The Cryosphere, 14, 3071–3096, https://doi.org/10.5194/tc-14-3071-2020, https://doi.org/10.5194/tc-14-3071-2020, 2020
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In this paper we use a large ensemble of Greenland ice sheet models forced by six different global climate models to project ice sheet changes and sea-level rise contributions over the 21st century.
The results for two different greenhouse gas concentration scenarios indicate that the Greenland ice sheet will continue to lose mass until 2100, with contributions to sea-level rise of 90 ± 50 mm and 32 ± 17 mm for the high (RCP8.5) and low (RCP2.6) scenario, respectively.
Hélène Seroussi, Sophie Nowicki, Antony J. Payne, Heiko Goelzer, William H. Lipscomb, Ayako Abe-Ouchi, Cécile Agosta, Torsten Albrecht, Xylar Asay-Davis, Alice Barthel, Reinhard Calov, Richard Cullather, Christophe Dumas, Benjamin K. Galton-Fenzi, Rupert Gladstone, Nicholas R. Golledge, Jonathan M. Gregory, Ralf Greve, Tore Hattermann, Matthew J. Hoffman, Angelika Humbert, Philippe Huybrechts, Nicolas C. Jourdain, Thomas Kleiner, Eric Larour, Gunter R. Leguy, Daniel P. Lowry, Chistopher M. Little, Mathieu Morlighem, Frank Pattyn, Tyler Pelle, Stephen F. Price, Aurélien Quiquet, Ronja Reese, Nicole-Jeanne Schlegel, Andrew Shepherd, Erika Simon, Robin S. Smith, Fiammetta Straneo, Sainan Sun, Luke D. Trusel, Jonas Van Breedam, Roderik S. W. van de Wal, Ricarda Winkelmann, Chen Zhao, Tong Zhang, and Thomas Zwinger
The Cryosphere, 14, 3033–3070, https://doi.org/10.5194/tc-14-3033-2020, https://doi.org/10.5194/tc-14-3033-2020, 2020
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The Antarctic ice sheet has been losing mass over at least the past 3 decades in response to changes in atmospheric and oceanic conditions. This study presents an ensemble of model simulations of the Antarctic evolution over the 2015–2100 period based on various ice sheet models, climate forcings and emission scenarios. Results suggest that the West Antarctic ice sheet will continue losing a large amount of ice, while the East Antarctic ice sheet could experience increased snow accumulation.
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.
Brett Metcalfe, Bryan C. Lougheed, Claire Waelbroeck, and Didier M. Roche
Clim. Past, 16, 885–910, https://doi.org/10.5194/cp-16-885-2020, https://doi.org/10.5194/cp-16-885-2020, 2020
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Planktonic foraminifera construct a shell that, post mortem, settles to the seafloor, prior to collection by Palaeoclimatologists for use as proxies. Such organisms in life are sensitive to the ambient conditions (e.g. temperature, salinity), which therefore means our proxies maybe skewed toward the ecology of organisms. Using a proxy system model, Foraminifera as Modelled Entities (FAME), we assess the potential of extracting ENSO signal from tropical Pacific planktonic foraminifera.
Lise Missiaen, Nathaelle Bouttes, Didier M. Roche, Jean-Claude Dutay, Aurélien Quiquet, Claire Waelbroeck, Sylvain Pichat, and Jean-Yves Peterschmitt
Clim. Past, 16, 867–883, https://doi.org/10.5194/cp-16-867-2020, https://doi.org/10.5194/cp-16-867-2020, 2020
Anders Levermann, Ricarda Winkelmann, Torsten Albrecht, Heiko Goelzer, Nicholas R. Golledge, Ralf Greve, Philippe Huybrechts, Jim Jordan, Gunter Leguy, Daniel Martin, Mathieu Morlighem, Frank Pattyn, David Pollard, Aurelien Quiquet, Christian Rodehacke, Helene Seroussi, Johannes Sutter, Tong Zhang, Jonas Van Breedam, Reinhard Calov, Robert DeConto, Christophe Dumas, Julius Garbe, G. Hilmar Gudmundsson, Matthew J. Hoffman, Angelika Humbert, Thomas Kleiner, William H. Lipscomb, Malte Meinshausen, Esmond Ng, Sophie M. J. Nowicki, Mauro Perego, Stephen F. Price, Fuyuki Saito, Nicole-Jeanne Schlegel, Sainan Sun, and Roderik S. W. van de Wal
Earth Syst. Dynam., 11, 35–76, https://doi.org/10.5194/esd-11-35-2020, https://doi.org/10.5194/esd-11-35-2020, 2020
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We provide an estimate of the future sea level contribution of Antarctica from basal ice shelf melting up to the year 2100. The full uncertainty range in the warming-related forcing of basal melt is estimated and applied to 16 state-of-the-art ice sheet models using a linear response theory approach. The sea level contribution we obtain is very likely below 61 cm under unmitigated climate change until 2100 (RCP8.5) and very likely below 40 cm if the Paris Climate Agreement is kept.
Ning Tan, Camille Contoux, Gilles Ramstein, Yong Sun, Christophe Dumas, Pierre Sepulchre, and Zhengtang Guo
Clim. Past, 16, 1–16, https://doi.org/10.5194/cp-16-1-2020, https://doi.org/10.5194/cp-16-1-2020, 2020
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To understand the warm climate during the late Pliocene (~3.205 Ma), modeling experiments with the new boundary conditions are launched and analyzed based on the Institut Pierre Simon Laplace (IPSL) atmosphere–ocean coupled general circulation model (AOGCM). Our results show that the warming in mid- to high latitudes enhanced due to the modifications of the land–sea mask and land–ice configuration. The pCO2 uncertainties within the records can produce asymmetrical warming patterns.
Sébastien Le clec'h, Aurélien Quiquet, Sylvie Charbit, Christophe Dumas, Masa Kageyama, and Catherine Ritz
Geosci. Model Dev., 12, 2481–2499, https://doi.org/10.5194/gmd-12-2481-2019, https://doi.org/10.5194/gmd-12-2481-2019, 2019
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To provide reliable projections of the ice-sheet contribution to future sea-level rise, ice sheet models must be able to simulate the observed ice sheet present-day state. Using a low computational iterative minimisation procedure, based on the adjustment of the basal drag coefficient, we rapidly minimise the errors between the simulated and the observed Greenland ice thickness and ice velocity, and we succeed in stabilising the simulated Greenland ice sheet state under present-day conditions.
Hélène Seroussi, Sophie Nowicki, Erika Simon, Ayako Abe-Ouchi, Torsten Albrecht, Julien Brondex, Stephen Cornford, Christophe Dumas, Fabien Gillet-Chaulet, Heiko Goelzer, Nicholas R. Golledge, Jonathan M. Gregory, Ralf Greve, Matthew J. Hoffman, Angelika Humbert, Philippe Huybrechts, Thomas Kleiner, Eric Larour, Gunter Leguy, William H. Lipscomb, Daniel Lowry, Matthias Mengel, Mathieu Morlighem, Frank Pattyn, Anthony J. Payne, David Pollard, Stephen F. Price, Aurélien Quiquet, Thomas J. Reerink, Ronja Reese, Christian B. Rodehacke, Nicole-Jeanne Schlegel, Andrew Shepherd, Sainan Sun, Johannes Sutter, Jonas Van Breedam, Roderik S. W. van de Wal, Ricarda Winkelmann, and Tong Zhang
The Cryosphere, 13, 1441–1471, https://doi.org/10.5194/tc-13-1441-2019, https://doi.org/10.5194/tc-13-1441-2019, 2019
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We compare a wide range of Antarctic ice sheet simulations with varying initialization techniques and model parameters to understand the role they play on the projected evolution of this ice sheet under simple scenarios. Results are improved compared to previous assessments and show that continued improvements in the representation of the floating ice around Antarctica are critical to reduce the uncertainty in the future ice sheet contribution to sea level rise.
Sébastien Le clec'h, Sylvie Charbit, Aurélien Quiquet, Xavier Fettweis, Christophe Dumas, Masa Kageyama, Coraline Wyard, and Catherine Ritz
The Cryosphere, 13, 373–395, https://doi.org/10.5194/tc-13-373-2019, https://doi.org/10.5194/tc-13-373-2019, 2019
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Quantifying the future contribution of the Greenland ice sheet (GrIS) to sea-level rise in response to atmospheric changes is important but remains challenging. For the first time a full representation of the feedbacks between a GrIS model and a regional atmospheric model was implemented. The authors highlight the fundamental need for representing the GrIS topography change feedbacks with respect to the atmospheric component face to the strong impact on the projected sea-level rise.
Aurélien Quiquet, Christophe Dumas, Catherine Ritz, Vincent Peyaud, and Didier M. Roche
Geosci. Model Dev., 11, 5003–5025, https://doi.org/10.5194/gmd-11-5003-2018, https://doi.org/10.5194/gmd-11-5003-2018, 2018
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This paper presents the GRISLI (Grenoble ice sheet and land ice) model in its newest revision. We present the recent model improvements from its original version (Ritz et al., 2001), together with a discussion of the model performance in reproducing the present-day Antarctic ice sheet geometry and the grounding line advances and retreats during the last 400 000 years. We show that GRISLI is a computationally cheap model, able to reproduce the large-scale behaviour of ice sheets.
Didier M. Roche, Claire Waelbroeck, Brett Metcalfe, and Thibaut Caley
Geosci. Model Dev., 11, 3587–3603, https://doi.org/10.5194/gmd-11-3587-2018, https://doi.org/10.5194/gmd-11-3587-2018, 2018
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The oxygen-18 signal recorded in fossil planktonic foraminifers has been used for over 50 years in many geoscience applications. However, different planktonic foraminifer species from the same sediment core generally yield distinct oxygen-18 signals, as a consequence of their specific living habitat in the water column and along the year. To explicitly take into account this variability for five common planktonic species, we developed the portable module FAME (Foraminifers As Modeled Entities).
Zhongshi Zhang, Qing Yan, Elizabeth J. Farmer, Camille Li, Gilles Ramstein, Terence Hughes, Martin Jakobsson, Matt O'Regan, Ran Zhang, Ning Tan, Camille Contoux, Christophe Dumas, and Chuncheng Guo
Clim. Past Discuss., https://doi.org/10.5194/cp-2018-79, https://doi.org/10.5194/cp-2018-79, 2018
Revised manuscript not accepted
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Our study challenges the widely accepted idea that the Laurentide-Eurasian ice sheets gradually extended across North America and Northwest Eurasia, and suggests the growth of the NH ice sheets is much more complicated. We find climate feedbacks regulate the distribution of the NH ice sheets, producing swings between two distinct ice sheet configurations: the Laurentide-Eurasian and a circum-Arctic configuration, where large ice sheets existed over Northeast Siberia and the Canadian Rockies.
Guillaume Latombe, Ariane Burke, Mathieu Vrac, Guillaume Levavasseur, Christophe Dumas, Masa Kageyama, and Gilles Ramstein
Geosci. Model Dev., 11, 2563–2579, https://doi.org/10.5194/gmd-11-2563-2018, https://doi.org/10.5194/gmd-11-2563-2018, 2018
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It is still unclear how climate conditions, and especially climate variability, influenced the spatial distribution of past human populations. Global climate models (GCMs) cannot simulate climate at sufficiently fine scale for this purpose. We propose a statistical method to obtain fine-scale climate projections for 15 000 years ago from coarse-scale GCM outputs. Our method agrees with local reconstructions from fossil and pollen data, and generates sensible climate variability maps over Europe.
Olivier Passalacqua, Marie Cavitte, Olivier Gagliardini, Fabien Gillet-Chaulet, Frédéric Parrenin, Catherine Ritz, and Duncan Young
The Cryosphere, 12, 2167–2174, https://doi.org/10.5194/tc-12-2167-2018, https://doi.org/10.5194/tc-12-2167-2018, 2018
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Locating a suitable drill site is a key step in the Antarctic oldest-ice challenge. Here we have conducted a 3-D ice flow simulation in the region of Dome C using a refined bedrock description. Five selection criteria are computed that together provide an objective overview on the local ice flow conditions. We delineate kilometer-scale favorable areas that overlap with the ones recently proposed by another group. We propose a few drill sites that should be surveyed during the next field seasons.
Marie G. P. Cavitte, Frédéric Parrenin, Catherine Ritz, Duncan A. Young, Brice Van Liefferinge, Donald D. Blankenship, Massimo Frezzotti, and Jason L. Roberts
The Cryosphere, 12, 1401–1414, https://doi.org/10.5194/tc-12-1401-2018, https://doi.org/10.5194/tc-12-1401-2018, 2018
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We reconstruct the pattern of surface accumulation in the region around Dome C, East Antarctica, over the last 73 kyr. We use internal isochrones interpreted from ice-penetrating radar surveys and a 1-D ice flow model to invert for time-averaged and paleo-accumulation rates. We observe that surface accumulation patterns are stable through the last 73 kyr, consistent with current observed regional precipitation gradients and consistent interactions between prevailing winds and surface slope.
Masa Kageyama, Pascale Braconnot, Sandy P. Harrison, Alan M. Haywood, Johann H. Jungclaus, Bette L. Otto-Bliesner, Jean-Yves Peterschmitt, Ayako Abe-Ouchi, Samuel Albani, Patrick J. Bartlein, Chris Brierley, Michel Crucifix, Aisling Dolan, Laura Fernandez-Donado, Hubertus Fischer, Peter O. Hopcroft, Ruza F. Ivanovic, Fabrice Lambert, Daniel J. Lunt, Natalie M. Mahowald, W. Richard Peltier, Steven J. Phipps, Didier M. Roche, Gavin A. Schmidt, Lev Tarasov, Paul J. Valdes, Qiong Zhang, and Tianjun Zhou
Geosci. Model Dev., 11, 1033–1057, https://doi.org/10.5194/gmd-11-1033-2018, https://doi.org/10.5194/gmd-11-1033-2018, 2018
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The Paleoclimate Modelling Intercomparison Project (PMIP) takes advantage of the existence of past climate states radically different from the recent past to test climate models used for climate projections and to better understand these climates. This paper describes the PMIP contribution to CMIP6 (Coupled Model Intercomparison Project, 6th phase) and possible analyses based on PMIP results, as well as on other CMIP6 projects.
Nathaelle Bouttes, Didier Swingedouw, Didier M. Roche, Maria F. Sanchez-Goni, and Xavier Crosta
Clim. Past, 14, 239–253, https://doi.org/10.5194/cp-14-239-2018, https://doi.org/10.5194/cp-14-239-2018, 2018
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Atmospheric CO2 is key for climate change. CO2 is lower during the oldest warm period of the last million years, the interglacials, than during the most recent ones (since 430 000 years ago). This difference has not been explained yet, but could be due to changes of ocean circulation. We test this hypothesis and the role of vegetation and ice sheets using an intermediate complexity model. We show that only small changes of CO2 can be obtained, underlying missing feedbacks or mechanisms.
Aurélien Quiquet, Didier M. Roche, Christophe Dumas, and Didier Paillard
Geosci. Model Dev., 11, 453–466, https://doi.org/10.5194/gmd-11-453-2018, https://doi.org/10.5194/gmd-11-453-2018, 2018
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Earth system models of intermediate complexity generally have a simplified model physics and a coarse model resolution. In this work we present the inclusion of an online dynamical downscaling of temperature and precipitation in such a model. This downscaling explicitly takes into account sub-grid topography. With this new model functionality we are able to simulate temperature and precipitation on a 40 km grid for the whole Northern Hemisphere from the native model resolution.
Masa Kageyama, Samuel Albani, Pascale Braconnot, Sandy P. Harrison, Peter O. Hopcroft, Ruza F. Ivanovic, Fabrice Lambert, Olivier Marti, W. Richard Peltier, Jean-Yves Peterschmitt, Didier M. Roche, Lev Tarasov, Xu Zhang, Esther C. Brady, Alan M. Haywood, Allegra N. LeGrande, Daniel J. Lunt, Natalie M. Mahowald, Uwe Mikolajewicz, Kerim H. Nisancioglu, Bette L. Otto-Bliesner, Hans Renssen, Robert A. Tomas, Qiong Zhang, Ayako Abe-Ouchi, Patrick J. Bartlein, Jian Cao, Qiang Li, Gerrit Lohmann, Rumi Ohgaito, Xiaoxu Shi, Evgeny Volodin, Kohei Yoshida, Xiao Zhang, and Weipeng Zheng
Geosci. Model Dev., 10, 4035–4055, https://doi.org/10.5194/gmd-10-4035-2017, https://doi.org/10.5194/gmd-10-4035-2017, 2017
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The Last Glacial Maximum (LGM, 21000 years ago) is an interval when global ice volume was at a maximum, eustatic sea level close to a minimum, greenhouse gas concentrations were lower, atmospheric aerosol loadings were higher than today, and vegetation and land-surface characteristics were different from today. This paper describes the implementation of the LGM numerical experiment for the PMIP4-CMIP6 modelling intercomparison projects and the associated sensitivity experiments.
Frédéric Parrenin, Marie G. P. Cavitte, Donald D. Blankenship, Jérôme Chappellaz, Hubertus Fischer, Olivier Gagliardini, Valérie Masson-Delmotte, Olivier Passalacqua, Catherine Ritz, Jason Roberts, Martin J. Siegert, and Duncan A. Young
The Cryosphere, 11, 2427–2437, https://doi.org/10.5194/tc-11-2427-2017, https://doi.org/10.5194/tc-11-2427-2017, 2017
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The oldest dated deep ice core drilled in Antarctica has been retrieved at EPICA Dome C (EDC), reaching ~ 800 000 years. Obtaining an older palaeoclimatic record from Antarctica is one of the greatest challenges of the ice core community. Here, we estimate the age of basal ice in the Dome C area. We find that old ice (> 1.5 Myr) likely exists in two regions a few tens of kilometres away from EDC:
Little Dome C Patchand
North Patch.
Olivier Passalacqua, Catherine Ritz, Frédéric Parrenin, Stefano Urbini, and Massimo Frezzotti
The Cryosphere, 11, 2231–2246, https://doi.org/10.5194/tc-11-2231-2017, https://doi.org/10.5194/tc-11-2231-2017, 2017
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As the Dome C region is a key area for oldest-ice research, we need to better constrain the geothermal flux (GF) so that past basal melt rates are well constrained. Our inverse heat model significantly reduces the confidence intervals of the GF regional field around Dome C, which ranges from 48 to 60 mW m−2. Radar echoes need to be interpreted knowing the time lag of the climate signal to reach the bed. Several old-ice targets are confirmed and a new one is suggested, in which the GF is very low.
Duncan A. Young, Jason L. Roberts, Catherine Ritz, Massimo Frezzotti, Enrica Quartini, Marie G. P. Cavitte, Carly R. Tozer, Daniel Steinhage, Stefano Urbini, Hugh F. J. Corr, Tas van Ommen, and Donald D. Blankenship
The Cryosphere, 11, 1897–1911, https://doi.org/10.5194/tc-11-1897-2017, https://doi.org/10.5194/tc-11-1897-2017, 2017
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To find records of the greenhouse gases found in key periods of climate transition, we need to find sites of unmelted old ice at the base of the Antarctic ice sheet for ice core retrieval. A joint US–Australian–EU team performed a high-resolution survey of such a site (1 km line spacing) near Concordia Station in East Antarctica, using airborne ice-penetrating radar. We found promising targets in rough subglacial terrain, surrounded by subglacial lakes restricted below a minimum hydraulic head.
Pierre Burckel, Claire Waelbroeck, Yiming Luo, Didier M. Roche, Sylvain Pichat, Samuel L. Jaccard, Jeanne Gherardi, Aline Govin, Jörg Lippold, and François Thil
Clim. Past, 12, 2061–2075, https://doi.org/10.5194/cp-12-2061-2016, https://doi.org/10.5194/cp-12-2061-2016, 2016
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In this paper, we compare new and published Atlantic sedimentary Pa/Th data with Pa/Th simulated using stream functions generated under various climatic conditions. We show that during Greenland interstadials of the 20–50 ka period, the Atlantic meridional overturning circulation was very different from that of the Holocene. Moreover, southern-sourced waters dominated the Atlantic during Heinrich stadial 2, a slow northern-sourced water mass flowing above 2500 m in the North Atlantic.
Timothé Bolliet, Patrick Brockmann, Valérie Masson-Delmotte, Franck Bassinot, Valérie Daux, Dominique Genty, Amaelle Landais, Marlène Lavrieux, Elisabeth Michel, Pablo Ortega, Camille Risi, Didier M. Roche, Françoise Vimeux, and Claire Waelbroeck
Clim. Past, 12, 1693–1719, https://doi.org/10.5194/cp-12-1693-2016, https://doi.org/10.5194/cp-12-1693-2016, 2016
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This paper presents a new database of past climate proxies which aims to facilitate the distribution of data by using a user-friendly interface. Available data from the last 40 years are often fragmented, with lots of different formats, and online libraries are sometimes nonintuitive. We thus built a new dynamic web portal for data browsing, visualizing, and batch downloading of hundreds of datasets presenting a homogeneous format.
Ruza F. Ivanovic, Lauren J. Gregoire, Masa Kageyama, Didier M. Roche, Paul J. Valdes, Andrea Burke, Rosemarie Drummond, W. Richard Peltier, and Lev Tarasov
Geosci. Model Dev., 9, 2563–2587, https://doi.org/10.5194/gmd-9-2563-2016, https://doi.org/10.5194/gmd-9-2563-2016, 2016
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This manuscript presents the experiment design for the PMIP4 Last Deglaciation Core experiment: a transient simulation of the last deglaciation, 21–9 ka. Specified model boundary conditions include time-varying orbital parameters, greenhouse gases, ice sheets, ice meltwater fluxes and other geographical changes (provided for 26–0 ka). The context of the experiment and the choices for the boundary conditions are explained, along with the future direction of the working group.
Olivier Passalacqua, Olivier Gagliardini, Frédéric Parrenin, Joe Todd, Fabien Gillet-Chaulet, and Catherine Ritz
Geosci. Model Dev., 9, 2301–2313, https://doi.org/10.5194/gmd-9-2301-2016, https://doi.org/10.5194/gmd-9-2301-2016, 2016
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In ice-flow modelling, computing in 3-D requires a lot of resources, but 2-D models lack physical likelihood when the flow is diverging. That is why 2-D models accounting for the divergence, so-called 2.5-D models, are an interesting trade-off. However, the applicability of these 2.5-D models has never been systematically examined. We show that these models are ineffective in the case of highly diverging flows, but also for varying temperature, which was not suspected.
Lucie Bazin, Amaelle Landais, Emilie Capron, Valérie Masson-Delmotte, Catherine Ritz, Ghislain Picard, Jean Jouzel, Marie Dumont, Markus Leuenberger, and Frédéric Prié
Clim. Past, 12, 729–748, https://doi.org/10.5194/cp-12-729-2016, https://doi.org/10.5194/cp-12-729-2016, 2016
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We present new measurements of δO2⁄N2 and δ18Oatm performed on well-conserved ice from EDC covering MIS5 and between 380 and 800 ka. The combination of the observation of a 100 ka periodicity in the new δO2⁄N2 record with a MIS5 multi-site multi-proxy study has revealed a potential influence of local climatic parameters on δO2⁄N2. Moreover, we propose that the varying delay between d18Oatm and precession for the last 800 ka is affected by the occurrence of ice sheet discharge events.
Marianne Bügelmayer-Blaschek, Didier M. Roche, Hans Renssen, and Claire Waelbroeck
Clim. Past Discuss., https://doi.org/10.5194/cp-2016-31, https://doi.org/10.5194/cp-2016-31, 2016
Revised manuscript has not been submitted
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Using the global isotope-enabled climate – iceberg model iLOVECLIM we performed three experiments to investigate the mechanisms behind the simulated δ18Ocalcite pattern applying a Heinrich event like iceberg forcing. Our model results display two main patterns in the δ18Ocalcite signal. First, we find regions that display almost no response in δ18Ocalcite and second, regions where the δ18Ocalcite pattern closely follows the δ18Oseawater signal.
P. Beghin, S. Charbit, C. Dumas, M. Kageyama, and C. Ritz
Clim. Past, 11, 1467–1490, https://doi.org/10.5194/cp-11-1467-2015, https://doi.org/10.5194/cp-11-1467-2015, 2015
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The present study investigates the potential impact of the North American ice sheet on the surface mass balance of the Eurasian ice sheet through changes in the past glacial atmospheric circulation. Using an atmospheric circulation model and an ice-sheet model, we show that the albedo of the American ice sheet favors the growth of the Eurasian ice sheet, whereas the topography of the American ice sheet leads to more ablation over North Eurasia, and therefore to a smaller Eurasian ice sheet.
M. Bügelmayer, D. M. Roche, and H. Renssen
Geosci. Model Dev., 8, 2139–2151, https://doi.org/10.5194/gmd-8-2139-2015, https://doi.org/10.5194/gmd-8-2139-2015, 2015
N. Bouttes, D. M. Roche, V. Mariotti, and L. Bopp
Geosci. Model Dev., 8, 1563–1576, https://doi.org/10.5194/gmd-8-1563-2015, https://doi.org/10.5194/gmd-8-1563-2015, 2015
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We describe the development of a relatively simple climate model to include a model of the carbon cycle in the ocean. The carbon cycle consists of the exchange of carbon between the atmosphere, land vegetation and ocean. In the ocean, carbon exists in organic form, such as plankton which grows and dies, and inorganic forms, such as dissolved CO2. With this we will be able to explore long-standing questions such as why the atmospheric CO2 has changed over time during the last million years.
D. C. Kitover, R. van Balen, D. M. Roche, J. Vandenberghe, and H. Renssen
Geosci. Model Dev., 8, 1445–1460, https://doi.org/10.5194/gmd-8-1445-2015, https://doi.org/10.5194/gmd-8-1445-2015, 2015
M. Bügelmayer, D. M. Roche, and H. Renssen
The Cryosphere, 9, 821–835, https://doi.org/10.5194/tc-9-821-2015, https://doi.org/10.5194/tc-9-821-2015, 2015
K. A. Crichton, D. M. Roche, G. Krinner, and J. Chappellaz
Geosci. Model Dev., 7, 3111–3134, https://doi.org/10.5194/gmd-7-3111-2014, https://doi.org/10.5194/gmd-7-3111-2014, 2014
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Permafrost is ground that remains frozen for two or more consecutive years. An estimated 50% of the global below-ground organic carbon is stored in soils of the permafrost zone. This study presents the development and validation of a simplified permafrost-carbon mechanism for the CLIMBER-2 model. Our model development allows, for the first time, the study of the role of permafrost soils in the global carbon cycle for long timescales and for coupled palaeoclimate Earth system modelling studies.
J.-B. Ladant, Y. Donnadieu, and C. Dumas
Clim. Past, 10, 1957–1966, https://doi.org/10.5194/cp-10-1957-2014, https://doi.org/10.5194/cp-10-1957-2014, 2014
T. Caley, D. M. Roche, C. Waelbroeck, and E. Michel
Clim. Past, 10, 1939–1955, https://doi.org/10.5194/cp-10-1939-2014, https://doi.org/10.5194/cp-10-1939-2014, 2014
B. Bonan, M. Nodet, C. Ritz, and V. Peyaud
Nonlin. Processes Geophys., 21, 569–582, https://doi.org/10.5194/npg-21-569-2014, https://doi.org/10.5194/npg-21-569-2014, 2014
P. Beghin, S. Charbit, C. Dumas, M. Kageyama, D. M. Roche, and C. Ritz
Clim. Past, 10, 345–358, https://doi.org/10.5194/cp-10-345-2014, https://doi.org/10.5194/cp-10-345-2014, 2014
F. Colleoni, S. Masina, A. Cherchi, A. Navarra, C. Ritz, V. Peyaud, and B. Otto-Bliesner
Clim. Past, 10, 269–291, https://doi.org/10.5194/cp-10-269-2014, https://doi.org/10.5194/cp-10-269-2014, 2014
T. L. Edwards, X. Fettweis, O. Gagliardini, F. Gillet-Chaulet, H. Goelzer, J. M. Gregory, M. Hoffman, P. Huybrechts, A. J. Payne, M. Perego, S. Price, A. Quiquet, and C. Ritz
The Cryosphere, 8, 181–194, https://doi.org/10.5194/tc-8-181-2014, https://doi.org/10.5194/tc-8-181-2014, 2014
T. L. Edwards, X. Fettweis, O. Gagliardini, F. Gillet-Chaulet, H. Goelzer, J. M. Gregory, M. Hoffman, P. Huybrechts, A. J. Payne, M. Perego, S. Price, A. Quiquet, and C. Ritz
The Cryosphere, 8, 195–208, https://doi.org/10.5194/tc-8-195-2014, https://doi.org/10.5194/tc-8-195-2014, 2014
H. Fischer, J. Severinghaus, E. Brook, E. Wolff, M. Albert, O. Alemany, R. Arthern, C. Bentley, D. Blankenship, J. Chappellaz, T. Creyts, D. Dahl-Jensen, M. Dinn, M. Frezzotti, S. Fujita, H. Gallee, R. Hindmarsh, D. Hudspeth, G. Jugie, K. Kawamura, V. Lipenkov, H. Miller, R. Mulvaney, F. Parrenin, F. Pattyn, C. Ritz, J. Schwander, D. Steinhage, T. van Ommen, and F. Wilhelms
Clim. Past, 9, 2489–2505, https://doi.org/10.5194/cp-9-2489-2013, https://doi.org/10.5194/cp-9-2489-2013, 2013
D. M. Roche
Geosci. Model Dev., 6, 1481–1491, https://doi.org/10.5194/gmd-6-1481-2013, https://doi.org/10.5194/gmd-6-1481-2013, 2013
D. M. Roche and T. Caley
Geosci. Model Dev., 6, 1493–1504, https://doi.org/10.5194/gmd-6-1493-2013, https://doi.org/10.5194/gmd-6-1493-2013, 2013
T. Caley and D. M. Roche
Geosci. Model Dev., 6, 1505–1516, https://doi.org/10.5194/gmd-6-1505-2013, https://doi.org/10.5194/gmd-6-1505-2013, 2013
L. Bazin, A. Landais, B. Lemieux-Dudon, H. Toyé Mahamadou Kele, D. Veres, F. Parrenin, P. Martinerie, C. Ritz, E. Capron, V. Lipenkov, M.-F. Loutre, D. Raynaud, B. Vinther, A. Svensson, S. O. Rasmussen, M. Severi, T. Blunier, M. Leuenberger, H. Fischer, V. Masson-Delmotte, J. Chappellaz, and E. Wolff
Clim. Past, 9, 1715–1731, https://doi.org/10.5194/cp-9-1715-2013, https://doi.org/10.5194/cp-9-1715-2013, 2013
S. Charbit, C. Dumas, M. Kageyama, D. M. Roche, and C. Ritz
The Cryosphere, 7, 681–698, https://doi.org/10.5194/tc-7-681-2013, https://doi.org/10.5194/tc-7-681-2013, 2013
M. Kageyama, U. Merkel, B. Otto-Bliesner, M. Prange, A. Abe-Ouchi, G. Lohmann, R. Ohgaito, D. M. Roche, J. Singarayer, D. Swingedouw, and X Zhang
Clim. Past, 9, 935–953, https://doi.org/10.5194/cp-9-935-2013, https://doi.org/10.5194/cp-9-935-2013, 2013
P. Bakker, E. J. Stone, S. Charbit, M. Gröger, U. Krebs-Kanzow, S. P. Ritz, V. Varma, V. Khon, D. J. Lunt, U. Mikolajewicz, M. Prange, H. Renssen, B. Schneider, and M. Schulz
Clim. Past, 9, 605–619, https://doi.org/10.5194/cp-9-605-2013, https://doi.org/10.5194/cp-9-605-2013, 2013
A. Quiquet, C. Ritz, H. J. Punge, and D. Salas y Mélia
Clim. Past, 9, 353–366, https://doi.org/10.5194/cp-9-353-2013, https://doi.org/10.5194/cp-9-353-2013, 2013
F. Gillet-Chaulet, O. Gagliardini, H. Seddik, M. Nodet, G. Durand, C. Ritz, T. Zwinger, R. Greve, and D. G. Vaughan
The Cryosphere, 6, 1561–1576, https://doi.org/10.5194/tc-6-1561-2012, https://doi.org/10.5194/tc-6-1561-2012, 2012
J. Zumaque, F. Eynaud, S. Zaragosi, F. Marret, K. M. Matsuzaki, C. Kissel, D. M. Roche, B. Malaizé, E. Michel, I. Billy, T. Richter, and E. Palis
Clim. Past, 8, 1997–2017, https://doi.org/10.5194/cp-8-1997-2012, https://doi.org/10.5194/cp-8-1997-2012, 2012
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Daniel F. J. Gunning, Kerim H. Nisancioglu, Emilie Capron, and Roderik S. W. van de Wal
Geosci. Model Dev., 18, 2479–2508, https://doi.org/10.5194/gmd-18-2479-2025, https://doi.org/10.5194/gmd-18-2479-2025, 2025
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This work documents the first results from ZEMBA: an energy balance model of the climate system. The model is a computationally efficient tool designed to study the response of climate to changes in the Earth's orbit. We demonstrate that ZEMBA reproduces many features of the Earth's climate for both the pre-industrial period and the Earth's most recent cold extreme – the Last Glacial Maximum. We intend to develop ZEMBA further and investigate the glacial cycles of the last 2.5 million years.
Pengfei Shi, L. Ruby Leung, and Bin Wang
Geosci. Model Dev., 18, 2443–2460, https://doi.org/10.5194/gmd-18-2443-2025, https://doi.org/10.5194/gmd-18-2443-2025, 2025
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Improving climate predictions has significant socio-economic impacts. In this study, we develop and apply a new weakly coupled ocean data assimilation (WCODA) system to a coupled climate model. The WCODA system improves simulations of ocean temperature and salinity across many global regions. This system is meant to advance our understanding of the ocean's role in climate predictability.
Liwen Wang, Qian Li, Qi Lv, Xuan Peng, and Wei You
Geosci. Model Dev., 18, 2427–2442, https://doi.org/10.5194/gmd-18-2427-2025, https://doi.org/10.5194/gmd-18-2427-2025, 2025
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Our research presents a novel deep learning approach called "TemDeep" for downscaling atmospheric variables at arbitrary time resolutions based on temporal coherence. Results show that our method can accurately recover evolution details superior to other methods, reaching 53.7 % in the restoration rate. Our findings are important for advancing weather forecasting models and enabling more precise and reliable predictions to support disaster preparedness, agriculture, and sustainable development.
Teo Price-Broncucia, Allison Baker, Dorit Hammerling, Michael Duda, and Rebecca Morrison
Geosci. Model Dev., 18, 2349–2372, https://doi.org/10.5194/gmd-18-2349-2025, https://doi.org/10.5194/gmd-18-2349-2025, 2025
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The ensemble consistency test (ECT) and its ultrafast variant (UF-ECT) have become powerful tools in the development community for the identification of unwanted changes in the Community Earth System Model (CESM). We develop a generalized setup framework to enable easy adoption of the ECT approach for other model developers and communities. This framework specifies test parameters to accurately characterize model variability and balance test sensitivity and computational cost.
Esteban Fernández Villanueva and Gary Shaffer
Geosci. Model Dev., 18, 2161–2192, https://doi.org/10.5194/gmd-18-2161-2025, https://doi.org/10.5194/gmd-18-2161-2025, 2025
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We describe, calibrate and test the Danish Center for Earth System Science (DCESS) II model, a new, broad, adaptable and fast Earth system model. DCESS II is designed for global simulations over timescales of years to millions of years using limited computer resources like a personal computer. With its flexibility and comprehensive treatment of the global carbon cycle, DCESS II is a useful, computationally friendly tool for simulations of past climates as well as for future Earth system projections.
Gang Tang, Zebedee Nicholls, Alexander Norton, Sönke Zaehle, and Malte Meinshausen
Geosci. Model Dev., 18, 2193–2230, https://doi.org/10.5194/gmd-18-2193-2025, https://doi.org/10.5194/gmd-18-2193-2025, 2025
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We studied carbon–nitrogen coupling in Earth system models by developing a global carbon–nitrogen cycle model (CNit v1.0) within the widely used emulator MAGICC. CNit effectively reproduced the global carbon–nitrogen cycle dynamics observed in complex models. Our results show persistent nitrogen limitations on plant growth (net primary production) from 1850 to 2100, suggesting that nitrogen deficiency may constrain future land carbon sequestration.
Ngoc Thi Nhu Do, Kengo Sudo, Akihiko Ito, Louisa K. Emmons, Vaishali Naik, Kostas Tsigaridis, Øyvind Seland, Gerd A. Folberth, and Douglas I. Kelley
Geosci. Model Dev., 18, 2079–2109, https://doi.org/10.5194/gmd-18-2079-2025, https://doi.org/10.5194/gmd-18-2079-2025, 2025
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Understanding historical isoprene emission changes is important for predicting future climate, but trends and their controlling factors remain uncertain. This study shows that long-term isoprene trends vary among Earth system models mainly due to partially incorporating CO2 effects and land cover changes rather than to climate. Future models that refine these factors’ effects on isoprene emissions, along with long-term observations, are essential for better understanding plant–climate interactions.
Gang Tang, Zebedee Nicholls, Chris Jones, Thomas Gasser, Alexander Norton, Tilo Ziehn, Alejandro Romero-Prieto, and Malte Meinshausen
Geosci. Model Dev., 18, 2111–2136, https://doi.org/10.5194/gmd-18-2111-2025, https://doi.org/10.5194/gmd-18-2111-2025, 2025
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We analyzed carbon and nitrogen mass conservation in data from various Earth system models. Our findings reveal significant discrepancies between flux and pool size data, where cumulative imbalances can reach hundreds of gigatons of carbon or nitrogen. These imbalances appear primarily due to missing or inconsistently reported fluxes – especially for land-use and fire emissions. To enhance data quality, we recommend that future climate data protocols address this issue at the reporting stage.
Florian Börgel, Sven Karsten, Karoline Rummel, and Ulf Gräwe
Geosci. Model Dev., 18, 2005–2019, https://doi.org/10.5194/gmd-18-2005-2025, https://doi.org/10.5194/gmd-18-2005-2025, 2025
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Forecasting river runoff, which is crucial for managing water resources and understanding climate impacts, can be challenging. This study introduces a new method using convolutional long short-term memory (ConvLSTM) networks, a machine learning model that processes spatial and temporal data. Focusing on the Baltic Sea region, our model uses weather data as input to predict daily river runoff for 97 rivers.
Tao Zhang, Cyril Morcrette, Meng Zhang, Wuyin Lin, Shaocheng Xie, Ye Liu, Kwinten Van Weverberg, and Joana Rodrigues
Geosci. Model Dev., 18, 1917–1928, https://doi.org/10.5194/gmd-18-1917-2025, https://doi.org/10.5194/gmd-18-1917-2025, 2025
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Earth system models (ESMs) struggle with the uncertainties associated with parameterizing subgrid physics. Machine learning (ML) algorithms offer a solution by learning the important relationships and features from high-resolution models. To incorporate ML parameterizations into ESMs, we develop a Fortran–Python interface that allows for calling Python functions within Fortran-based ESMs. Through two case studies, this interface demonstrates its feasibility, modularity, and effectiveness.
Camilla Mathison, Eleanor J. Burke, Gregory Munday, Chris D. Jones, Chris J. Smith, Norman J. Steinert, Andy J. Wiltshire, Chris Huntingford, Eszter Kovacs, Laila K. Gohar, Rebecca M. Varney, and Douglas McNeall
Geosci. Model Dev., 18, 1785–1808, https://doi.org/10.5194/gmd-18-1785-2025, https://doi.org/10.5194/gmd-18-1785-2025, 2025
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We present PRIME (Probabilistic Regional Impacts from Model patterns and Emissions), which is designed to take new emissions scenarios and rapidly provide regional impact information. PRIME allows large ensembles to be run on multi-centennial timescales, including the analysis of many important variables for impact assessments. Our evaluation shows that PRIME reproduces the climate response for known scenarios, providing confidence in using PRIME for novel scenarios.
Katherine M. Smith, Alice M. Barthel, LeAnn M. Conlon, Luke P. Van Roekel, Anthony Bartoletti, Jean-Christophe Golaz, Chengzhu Zhang, Carolyn Branecky Begeman, James J. Benedict, Gautam Bisht, Yan Feng, Walter Hannah, Bryce E. Harrop, Nicole Jeffery, Wuyin Lin, Po-Lun Ma, Mathew E. Maltrud, Mark R. Petersen, Balwinder Singh, Qi Tang, Teklu Tesfa, Jonathan D. Wolfe, Shaocheng Xie, Xue Zheng, Karthik Balaguru, Oluwayemi Garuba, Peter Gleckler, Aixue Hu, Jiwoo Lee, Ben Moore-Maley, and Ana C. Ordoñez
Geosci. Model Dev., 18, 1613–1633, https://doi.org/10.5194/gmd-18-1613-2025, https://doi.org/10.5194/gmd-18-1613-2025, 2025
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Version 2.1 of the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) adds the Fox-Kemper et al. (2011) mixed-layer eddy parameterization, which restratifies the ocean surface layer through an overturning streamfunction. Results include surface layer bias reduction in temperature, salinity, and sea ice extent in the North Atlantic; a small strengthening of the Atlantic meridional overturning circulation; and improvements to many atmospheric climatological variables.
Huilin Huang, Yun Qian, Gautam Bisht, Jiali Wang, Tirthankar Chakraborty, Dalei Hao, Jianfeng Li, Travis Thurber, Balwinder Singh, Zhao Yang, Ye Liu, Pengfei Xue, William J. Sacks, Ethan Coon, and Robert Hetland
Geosci. Model Dev., 18, 1427–1443, https://doi.org/10.5194/gmd-18-1427-2025, https://doi.org/10.5194/gmd-18-1427-2025, 2025
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We integrate the E3SM Land Model (ELM) with the WRF model through the Lightweight Infrastructure for Land Atmosphere Coupling (LILAC) Earth System Modeling Framework (ESMF). This framework includes a top-level driver, LILAC, for variable communication between WRF and ELM and ESMF caps for ELM initialization, execution, and finalization. The LILAC–ESMF framework maintains the integrity of the ELM's source code structure and facilitates the transfer of future ELM model developments to WRF-ELM.
Michael Nole, Jonah Bartrand, Fawz Naim, and Glenn Hammond
Geosci. Model Dev., 18, 1413–1425, https://doi.org/10.5194/gmd-18-1413-2025, https://doi.org/10.5194/gmd-18-1413-2025, 2025
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Safe carbon dioxide (CO2) storage is likely to be critical for mitigating some of the most severe effects of climate change. We present a simulation framework for modeling CO2 storage beneath the seafloor, where CO2 can form a solid. This can aid in permanent CO2 storage for long periods of time. Our models show what a commercial-scale CO2 injection would look like in a marine environment. We discuss what would need to be considered when designing a subsea CO2 injection.
Reyk Börner, Jan O. Haerter, and Romain Fiévet
Geosci. Model Dev., 18, 1333–1356, https://doi.org/10.5194/gmd-18-1333-2025, https://doi.org/10.5194/gmd-18-1333-2025, 2025
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The daily cycle of sea surface temperature (SST) impacts clouds above the ocean and could influence the clustering of thunderstorms linked to extreme rainfall and hurricanes. However, daily SST variability is often poorly represented in modeling studies of how clouds cluster. We present a simple, wind-responsive model of upper-ocean temperature for use in atmospheric simulations. Evaluating the model against observations, we show that it performs significantly better than common slab models.
Malcolm J. Roberts, Kevin A. Reed, Qing Bao, Joseph J. Barsugli, Suzana J. Camargo, Louis-Philippe Caron, Ping Chang, Cheng-Ta Chen, Hannah M. Christensen, Gokhan Danabasoglu, Ivy Frenger, Neven S. Fučkar, Shabeh ul Hasson, Helene T. Hewitt, Huanping Huang, Daehyun Kim, Chihiro Kodama, Michael Lai, Lai-Yung Ruby Leung, Ryo Mizuta, Paulo Nobre, Pablo Ortega, Dominique Paquin, Christopher D. Roberts, Enrico Scoccimarro, Jon Seddon, Anne Marie Treguier, Chia-Ying Tu, Paul A. Ullrich, Pier Luigi Vidale, Michael F. Wehner, Colin M. Zarzycki, Bosong Zhang, Wei Zhang, and Ming Zhao
Geosci. Model Dev., 18, 1307–1332, https://doi.org/10.5194/gmd-18-1307-2025, https://doi.org/10.5194/gmd-18-1307-2025, 2025
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HighResMIP2 is a model intercomparison project focusing on high-resolution global climate models, that is, those with grid spacings of 25 km or less in the atmosphere and ocean, using simulations of decades to a century in length. We are proposing an update of our simulation protocol to make the models more applicable to key questions for climate variability and hazard in present-day and future projections and to build links with other communities to provide more robust climate information.
Jordi Buckley Paules, Simone Fatichi, Bonnie Warring, and Athanasios Paschalis
Geosci. Model Dev., 18, 1287–1305, https://doi.org/10.5194/gmd-18-1287-2025, https://doi.org/10.5194/gmd-18-1287-2025, 2025
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We present and validate enhancements to the process-based T&C model aimed at improving its representation of crop growth and management practices. The updated model, T&C-CROP, enables applications such as analysing the hydrological and carbon storage impacts of land use transitions (e.g. conversions between crops, forests, and pastures) and optimizing irrigation and fertilization strategies in response to climate change.
Sébastien Masson, Swen Jullien, Eric Maisonnave, David Gill, Guillaume Samson, Mathieu Le Corre, and Lionel Renault
Geosci. Model Dev., 18, 1241–1263, https://doi.org/10.5194/gmd-18-1241-2025, https://doi.org/10.5194/gmd-18-1241-2025, 2025
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This article details a new feature we implemented in the popular regional atmospheric model WRF. This feature allows for data exchange between WRF and any other model (e.g. an ocean model) using the coupling library Ocean–Atmosphere–Sea–Ice–Soil Model Coupling Toolkit (OASIS3-MCT). This coupling interface is designed to be non-intrusive, flexible and modular. It also offers the possibility of taking into account the nested zooms used in WRF or in the models with which it is coupled.
Axel Lauer, Lisa Bock, Birgit Hassler, Patrick Jöckel, Lukas Ruhe, and Manuel Schlund
Geosci. Model Dev., 18, 1169–1188, https://doi.org/10.5194/gmd-18-1169-2025, https://doi.org/10.5194/gmd-18-1169-2025, 2025
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Earth system models are important tools to improve our understanding of current climate and to project climate change. Thus, it is crucial to understand possible shortcomings in the models. New features of the ESMValTool software package allow one to compare and visualize a model's performance with respect to reproducing observations in the context of other climate models in an easy and user-friendly way. We aim to help model developers assess and monitor climate simulations more efficiently.
Ulrich G. Wortmann, Tina Tsan, Mahrukh Niazi, Irene A. Ma, Ruben Navasardyan, Magnus-Roland Marun, Bernardo S. Chede, Jingwen Zhong, and Morgan Wolfe
Geosci. Model Dev., 18, 1155–1167, https://doi.org/10.5194/gmd-18-1155-2025, https://doi.org/10.5194/gmd-18-1155-2025, 2025
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The Earth Science Box Modeling Toolkit (ESBMTK) is a user-friendly Python library that simplifies the creation of models to study earth system processes, such as the carbon cycle and ocean chemistry. It enhances learning by emphasizing concepts over programming and is accessible to students and researchers alike. By automating complex calculations and promoting code clarity, ESBMTK accelerates model development while improving reproducibility and the usability of scientific research.
Florian Zabel, Matthias Knüttel, and Benjamin Poschlod
Geosci. Model Dev., 18, 1067–1087, https://doi.org/10.5194/gmd-18-1067-2025, https://doi.org/10.5194/gmd-18-1067-2025, 2025
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CropSuite is a new open-source crop suitability model. It provides a GUI and a wide range of options, including a spatial downscaling of climate data. We apply CropSuite to 48 staple and opportunity crops at a 1 km spatial resolution in Africa. We find that climate variability significantly impacts suitable areas but also affects optimal sowing dates and multiple cropping potential. The results provide valuable information for climate impact assessments, adaptation, and land-use planning.
Kerstin Hartung, Bastian Kern, Nils-Arne Dreier, Jörn Geisbüsch, Mahnoosh Haghighatnasab, Patrick Jöckel, Astrid Kerkweg, Wilton Jaciel Loch, Florian Prill, and Daniel Rieger
Geosci. Model Dev., 18, 1001–1015, https://doi.org/10.5194/gmd-18-1001-2025, https://doi.org/10.5194/gmd-18-1001-2025, 2025
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The ICOsahedral Non-hydrostatic (ICON) model system Community Interface (ComIn) library supports connecting third-party modules to the ICON model. Third-party modules can range from simple diagnostic Python scripts to full chemistry models. ComIn offers a low barrier for code extensions to ICON, provides multi-language support (Fortran, C/C++, and Python), and reduces the migration effort in response to new ICON releases. This paper presents the ComIn design principles and a range of use cases.
Daniel Ries, Katherine Goode, Kellie McClernon, and Benjamin Hillman
Geosci. Model Dev., 18, 1041–1065, https://doi.org/10.5194/gmd-18-1041-2025, https://doi.org/10.5194/gmd-18-1041-2025, 2025
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Machine learning has advanced research in the climate science domain, but its models are difficult to understand. In order to understand the impacts and consequences of climate interventions such as stratospheric aerosol injection, complex models are often necessary. We use a case study to illustrate how we can understand the inner workings of a complex model. We present this technique as an exploratory tool that can be used to quickly discover and assess relationships in complex climate data.
Bo Dong, Paul Ullrich, Jiwoo Lee, Peter Gleckler, Kristin Chang, and Travis A. O'Brien
Geosci. Model Dev., 18, 961–976, https://doi.org/10.5194/gmd-18-961-2025, https://doi.org/10.5194/gmd-18-961-2025, 2025
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A metrics package designed for easy analysis of atmospheric river (AR) characteristics and statistics is presented. The tool is efficient for diagnosing systematic AR bias in climate models and useful for evaluating new AR characteristics in model simulations. In climate models, landfalling AR precipitation shows dry biases globally, and AR tracks are farther poleward (equatorward) in the North and South Atlantic (South Pacific and Indian Ocean).
Panagiotis Adamidis, Erik Pfister, Hendryk Bockelmann, Dominik Zobel, Jens-Olaf Beismann, and Marek Jacob
Geosci. Model Dev., 18, 905–919, https://doi.org/10.5194/gmd-18-905-2025, https://doi.org/10.5194/gmd-18-905-2025, 2025
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In this paper, we investigated performance indicators of the climate model ICON (ICOsahedral Nonhydrostatic) on different compute architectures to answer the question of how to generate high-resolution climate simulations. Evidently, it is not enough to use more computing units of the conventionally used architectures; higher memory throughput is the most promising approach. More potential can be gained from single-node optimization rather than simply increasing the number of compute nodes.
Kangari Narender Reddy, Somnath Baidya Roy, Sam S. Rabin, Danica L. Lombardozzi, Gudimetla Venkateswara Varma, Ruchira Biswas, and Devavat Chiru Naik
Geosci. Model Dev., 18, 763–785, https://doi.org/10.5194/gmd-18-763-2025, https://doi.org/10.5194/gmd-18-763-2025, 2025
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The study aimed to improve the representation of wheat and rice in a land model for the Indian region. The modified model performed significantly better than the default model in simulating crop phenology, yield, and carbon, water, and energy fluxes compared to observations. The study highlights the need for global land models to use region-specific crop parameters for accurately simulating vegetation processes and land surface processes.
Giovanni Di Virgilio, Fei Ji, Eugene Tam, Jason P. Evans, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Yue Li, and Matthew L. Riley
Geosci. Model Dev., 18, 703–724, https://doi.org/10.5194/gmd-18-703-2025, https://doi.org/10.5194/gmd-18-703-2025, 2025
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We evaluate the skill in simulating the Australian climate of some of the latest generation of regional climate models. We show when and where the models simulate this climate with high skill versus model limitations. We show how new models perform relative to the previous-generation models, assessing how model design features may underlie key performance improvements. This work is of national and international relevance as it can help guide the use and interpretation of climate projections.
Giovanni Di Virgilio, Jason P. Evans, Fei Ji, Eugene Tam, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Stephen White, Yue Li, Moutassem El Rafei, Rishav Goyal, Matthew L. Riley, and Jyothi Lingala
Geosci. Model Dev., 18, 671–702, https://doi.org/10.5194/gmd-18-671-2025, https://doi.org/10.5194/gmd-18-671-2025, 2025
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We introduce new climate models that simulate Australia’s future climate at regional scales, including at an unprecedented resolution of 4 km for 1950–2100. We describe the model design process used to create these new climate models. We show how the new models perform relative to previous-generation models and compare their climate projections. This work is of national and international relevance as it can help guide climate model design and the use and interpretation of climate projections.
Nathan P. Gillett, Isla R. Simpson, Gabi Hegerl, Reto Knutti, Dann Mitchell, Aurélien Ribes, Hideo Shiogama, Dáithí Stone, Claudia Tebaldi, Piotr Wolski, Wenxia Zhang, and Vivek K. Arora
EGUsphere, https://doi.org/10.5194/egusphere-2024-4086, https://doi.org/10.5194/egusphere-2024-4086, 2025
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Climate model simulations of the response to human and natural influences together, natural climate influences alone, and greenhouse gases alone, among others, are key to quantifying human influence on the climate. The last set of such coordinated simulations underpinned key findings in the last Intergovernmental Panel on Climate Change (IPCC) report. Here we propose a new set of such simulations to be used in the next generation of attribution studies, and to underpin the next IPCC report.
Jiawang Feng, Chun Zhao, Qiuyan Du, Zining Yang, and Chen Jin
Geosci. Model Dev., 18, 585–603, https://doi.org/10.5194/gmd-18-585-2025, https://doi.org/10.5194/gmd-18-585-2025, 2025
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In this study, we improved the calculation of how aerosols in the air interact with radiation in WRF-Chem. The original model used a simplified method, but we developed a more accurate approach. We found that this method significantly changes the properties of the estimated aerosols and their effects on radiation, especially for dust aerosols. It also impacts the simulated weather conditions. Our work highlights the importance of correctly representing aerosol–radiation interactions in models.
Eduardo Moreno-Chamarro, Thomas Arsouze, Mario Acosta, Pierre-Antoine Bretonnière, Miguel Castrillo, Eric Ferrer, Amanda Frigola, Daria Kuznetsova, Eneko Martin-Martinez, Pablo Ortega, and Sergi Palomas
Geosci. Model Dev., 18, 461–482, https://doi.org/10.5194/gmd-18-461-2025, https://doi.org/10.5194/gmd-18-461-2025, 2025
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We present the high-resolution model version of the EC-Earth global climate model to contribute to HighResMIP. The combined model resolution is about 10–15 km in both the ocean and atmosphere, which makes it one of the finest ever used to complete historical and scenario simulations. This model is compared with two lower-resolution versions, with a 100 km and a 25 km grid. The three models are compared with observations to study the improvements thanks to the increased resolution.
Catherine Guiavarc'h, David Storkey, Adam T. Blaker, Ed Blockley, Alex Megann, Helene Hewitt, Michael J. Bell, Daley Calvert, Dan Copsey, Bablu Sinha, Sophia Moreton, Pierre Mathiot, and Bo An
Geosci. Model Dev., 18, 377–403, https://doi.org/10.5194/gmd-18-377-2025, https://doi.org/10.5194/gmd-18-377-2025, 2025
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The Global Ocean and Sea Ice configuration version 9 (GOSI9) is the new UK hierarchy of model configurations based on the Nucleus for European Modelling of the Ocean (NEMO) and available at three resolutions. It will be used for various applications, e.g. weather forecasting and climate prediction. It improves upon the previous version by reducing global temperature and salinity biases and enhancing the representation of Arctic sea ice and the Antarctic Circumpolar Current.
Andy Richling, Jens Grieger, and Henning W. Rust
Geosci. Model Dev., 18, 361–375, https://doi.org/10.5194/gmd-18-361-2025, https://doi.org/10.5194/gmd-18-361-2025, 2025
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The performance of weather and climate prediction systems is variable in time and space. It is of interest how this performance varies in different situations. We provide a decomposition of a skill score (a measure of forecast performance) as a tool for detailed assessment of performance variability to support model development or forecast improvement. The framework is exemplified with decadal forecasts to assess the impact of different ocean states in the North Atlantic on temperature forecast.
Maria R. 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., 18, 181–191, https://doi.org/10.5194/gmd-18-181-2025, https://doi.org/10.5194/gmd-18-181-2025, 2025
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Observational data and modelling capabilities have expanded in recent years, but there are still barriers preventing these two data sources from being used in synergy. Proper comparison requires generating, storing, and handling a large amount of data. This work 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.
Bijan Fallah, Masoud Rostami, Emmanuele Russo, Paula Harder, Christoph Menz, Peter Hoffmann, Iulii Didovets, and Fred F. Hattermann
Geosci. Model Dev., 18, 161–180, https://doi.org/10.5194/gmd-18-161-2025, https://doi.org/10.5194/gmd-18-161-2025, 2025
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We tried to contribute to a local climate change impact study in central Asia, a region that is water-scarce and vulnerable to global climate change. We use regional models and machine learning to produce reliable local data from global climate models. We find that regional models show more realistic and detailed changes in heavy precipitation than global climate models. Our work can help assess the future risks of extreme events and plan adaptation strategies in central Asia.
Manuel Schlund, Bouwe Andela, Jörg Benke, Ruth Comer, Birgit Hassler, Emma Hogan, Peter Kalverla, Axel Lauer, Bill Little, Saskia Loosveldt Tomas, Francesco Nattino, Patrick Peglar, Valeriu Predoi, Stef Smeets, Stephen Worsley, Martin Yeo, and Klaus Zimmermann
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-236, https://doi.org/10.5194/gmd-2024-236, 2025
Revised manuscript accepted for GMD
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The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool for the evaluation of Earth system models. Here, we describe recent significant improvements of ESMValTool’s computational efficiency including parallel, out-of-core, and distributed computing. Evaluations with the enhanced version of ESMValTool are faster, use less computational resources, and can handle input data larger than the available memory.
Thomas Rackow, Xabier Pedruzo-Bagazgoitia, Tobias Becker, Sebastian Milinski, Irina Sandu, Razvan Aguridan, Peter Bechtold, Sebastian Beyer, Jean Bidlot, Souhail Boussetta, Willem Deconinck, Michail Diamantakis, Peter Dueben, Emanuel Dutra, Richard Forbes, Rohit Ghosh, Helge F. Goessling, Ioan Hadade, Jan Hegewald, Thomas Jung, Sarah Keeley, Lukas Kluft, Nikolay Koldunov, Aleksei Koldunov, Tobias Kölling, Josh Kousal, Christian Kühnlein, Pedro Maciel, Kristian Mogensen, Tiago Quintino, Inna Polichtchouk, Balthasar Reuter, Domokos Sármány, Patrick Scholz, Dmitry Sidorenko, Jan Streffing, Birgit Sützl, Daisuke Takasuka, Steffen Tietsche, Mirco Valentini, Benoît Vannière, Nils Wedi, Lorenzo Zampieri, and Florian Ziemen
Geosci. Model Dev., 18, 33–69, https://doi.org/10.5194/gmd-18-33-2025, https://doi.org/10.5194/gmd-18-33-2025, 2025
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Detailed global climate model simulations have been created based on a numerical weather prediction model, offering more accurate spatial detail down to the scale of individual cities ("kilometre-scale") and a better understanding of climate phenomena such as atmospheric storms, whirls in the ocean, and cracks in sea ice. The new model aims to provide globally consistent information on local climate change with greater precision, benefiting environmental planning and local impact modelling.
Yilin Fang, Hoang Viet Tran, and L. Ruby Leung
Geosci. Model Dev., 18, 19–32, https://doi.org/10.5194/gmd-18-19-2025, https://doi.org/10.5194/gmd-18-19-2025, 2025
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Hurricanes may worsen 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 the LMRB during Hurricane Ida in 2021, albeit less pronounced than the observations, indicating areas for model improvement to better understand and manage nutrient runoff loss during hurricanes in the region.
Giovanni Seijo-Ellis, Donata Giglio, Gustavo Marques, and Frank Bryan
Geosci. Model Dev., 17, 8989–9021, https://doi.org/10.5194/gmd-17-8989-2024, https://doi.org/10.5194/gmd-17-8989-2024, 2024
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A CESM–MOM6 regional configuration of the Caribbean Sea was developed in response to the rising need for high-resolution models for climate impact studies. The configuration is validated for the period 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 of ocean waters across multiple passages in the Caribbean Sea agree with observations.
Yan Bo, Hao Liang, Tao Li, and Feng Zhou
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-212, https://doi.org/10.5194/gmd-2024-212, 2024
Revised manuscript accepted for GMD
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This study proposed an advancing framework for modeling regional rice production, water use, and greenhouse gas emissions. The framework integrated a process-based soil-crop model with key physiological effects, a novel model upscaling method, and the NSGA-II multi-objective optimization algorithm at a parallel computing platform. The framework provides a valuable tool for irrigation optimization to deliver co-benefits of ensuring food production, reducing water use and greenhouse gas emissions.
Deifilia To, Julian Quinting, Gholam Ali Hoshyaripour, Markus Götz, Achim Streit, and Charlotte Debus
Geosci. Model Dev., 17, 8873–8884, https://doi.org/10.5194/gmd-17-8873-2024, https://doi.org/10.5194/gmd-17-8873-2024, 2024
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Pangu-Weather is a breakthrough machine learning model in medium-range weather forecasting that considers 3D 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 the accessibility of training and working with the model.
Fang Li, Xiang Song, Sandy P. Harrison, Jennifer R. Marlon, Zhongda Lin, L. Ruby Leung, Jörg Schwinger, Virginie Marécal, Shiyu Wang, Daniel S. Ward, Xiao Dong, Hanna Lee, Lars Nieradzik, Sam S. Rabin, and Roland Séférian
Geosci. Model Dev., 17, 8751–8771, https://doi.org/10.5194/gmd-17-8751-2024, https://doi.org/10.5194/gmd-17-8751-2024, 2024
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This study provides the first comprehensive assessment of historical fire simulations from 19 Earth system models in phase 6 of the Coupled Model Intercomparison Project (CMIP6). Most models reproduce global totals, spatial patterns, seasonality, and regional historical changes well but fail to simulate the recent decline in global burned area and underestimate the fire response to climate variability. CMIP6 simulations address three critical issues of phase-5 models.
Seung H. Baek, Paul A. Ullrich, Bo Dong, and Jiwoo Lee
Geosci. Model Dev., 17, 8665–8681, https://doi.org/10.5194/gmd-17-8665-2024, https://doi.org/10.5194/gmd-17-8665-2024, 2024
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We evaluate downscaled products by examining locally relevant co-variances during precipitation events. Common statistical downscaling techniques preserve expected co-variances during convective precipitation (a stationary phenomenon). However, they dampen future intensification of frontal precipitation (a non-stationary phenomenon) captured in global climate models and dynamical downscaling. Our study quantifies a ramification of the stationarity assumption underlying statistical downscaling.
Emmanuel Nyenah, Petra Döll, Daniel S. Katz, and Robert Reinecke
Geosci. Model Dev., 17, 8593–8611, https://doi.org/10.5194/gmd-17-8593-2024, https://doi.org/10.5194/gmd-17-8593-2024, 2024
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Research software is vital for scientific progress but is often developed by scientists with limited skills, time, and funding, leading to challenges in usability and maintenance. Our study across 10 sectors shows strengths in version control, open-source licensing, and documentation while emphasizing the need for containerization and code quality. We recommend workshops; code quality metrics; funding; and following the findable, accessible, interoperable, and reusable (FAIR) standards.
Chris Smith, Donald P. Cummins, Hege-Beate Fredriksen, Zebedee Nicholls, Malte Meinshausen, Myles Allen, Stuart Jenkins, Nicholas Leach, Camilla Mathison, and Antti-Ilari Partanen
Geosci. Model Dev., 17, 8569–8592, https://doi.org/10.5194/gmd-17-8569-2024, https://doi.org/10.5194/gmd-17-8569-2024, 2024
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Climate projections are only useful if the underlying models that produce them are well calibrated and can reproduce observed climate change. We formalise a software package that calibrates the open-source FaIR simple climate model to full-complexity Earth system models. Observations, including historical warming, and assessments of key climate variables such as that of climate sensitivity are used to constrain the model output.
Jingwei Xie, Xi Wang, Hailong Liu, Pengfei Lin, Jiangfeng Yu, Zipeng Yu, Junlin Wei, and Xiang Han
Geosci. Model Dev., 17, 8469–8493, https://doi.org/10.5194/gmd-17-8469-2024, https://doi.org/10.5194/gmd-17-8469-2024, 2024
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We propose the concept of mesoscale ocean direct numerical simulation (MODNS), which should resolve the first baroclinic deformation radius and ensure the numerical dissipative effects do not directly contaminate the mesoscale motions. It can be a benchmark for testing mesoscale ocean large eddy simulation (MOLES) methods in ocean models. We build an idealized Southern Ocean model using MITgcm to generate a type of MODNS. We also illustrate the diversity of multiscale eddy interactions.
Emily Black, John Ellis, and Ross I. Maidment
Geosci. Model Dev., 17, 8353–8372, https://doi.org/10.5194/gmd-17-8353-2024, https://doi.org/10.5194/gmd-17-8353-2024, 2024
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We present General TAMSAT-ALERT, a computationally lightweight and versatile tool for generating ensemble forecasts from time series data. General TAMSAT-ALERT is capable of combining multiple streams of monitoring and meteorological forecasting data into probabilistic hazard assessments. In this way, it complements existing systems and enhances their utility for actionable hazard assessment.
Sarah Schöngart, Lukas Gudmundsson, Mathias Hauser, Peter Pfleiderer, Quentin Lejeune, Shruti Nath, Sonia Isabelle Seneviratne, and Carl-Friedrich Schleussner
Geosci. Model Dev., 17, 8283–8320, https://doi.org/10.5194/gmd-17-8283-2024, https://doi.org/10.5194/gmd-17-8283-2024, 2024
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Precipitation and temperature are two of the most impact-relevant climatic variables. Yet, projecting future precipitation and temperature data under different emission scenarios relies on complex models that are computationally expensive. In this study, we propose a method that allows us to generate monthly means of local precipitation and temperature at low computational costs. Our modelling framework is particularly useful for all downstream applications of climate model data.
Benjamin M. Sanderson, Ben B. B. Booth, John Dunne, Veronika Eyring, Rosie A. Fisher, Pierre Friedlingstein, Matthew J. Gidden, Tomohiro Hajima, Chris D. Jones, Colin G. Jones, Andrew King, Charles D. Koven, David M. Lawrence, Jason Lowe, Nadine Mengis, Glen P. Peters, Joeri Rogelj, Chris Smith, Abigail C. Snyder, Isla R. Simpson, Abigail L. S. Swann, Claudia Tebaldi, Tatiana Ilyina, Carl-Friedrich Schleussner, Roland Séférian, Bjørn H. Samset, Detlef van Vuuren, and Sönke Zaehle
Geosci. Model Dev., 17, 8141–8172, https://doi.org/10.5194/gmd-17-8141-2024, https://doi.org/10.5194/gmd-17-8141-2024, 2024
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We discuss how, in order to provide more relevant guidance for climate policy, coordinated climate experiments should adopt a greater focus on simulations where Earth system models are provided with carbon emissions from fossil fuels together with land use change instructions, rather than past approaches that have largely focused on experiments with prescribed atmospheric carbon dioxide concentrations. We discuss how these goals might be achieved in coordinated climate modeling experiments.
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., 17, 8173–8179, https://doi.org/10.5194/gmd-17-8173-2024, https://doi.org/10.5194/gmd-17-8173-2024, 2024
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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 data range is likely encountered outside of the calibration period. The end result is highly dependent on the method used. We show that, to avoid discontinuities in the time series, one needs to exclude data in the calibration range to also activate the extrapolation functionality in that time period.
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