Articles | Volume 17, issue 18
https://doi.org/10.5194/gmd-17-6987-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-17-6987-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
19 Sep 2024
Model description paper |
| 19 Sep 2024
| 19 Sep 2024
Design and performance of ELSA v2.0: an isochronal model for ice-sheet layer tracing
Department of Earth Science, University of Bergen, Bergen, Norway
Bjerknes Centre for Climate Research, Bergen, Norway
Andreas Born
Department of Earth Science, University of Bergen, Bergen, Norway
Bjerknes Centre for Climate Research, Bergen, Norway
Alexander Robinson
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Potsdam, Germany
Robert Law
Department of Earth Science, University of Bergen, Bergen, Norway
Bjerknes Centre for Climate Research, Bergen, Norway
Gerrit Gülle
Department of Physics, University of Hamburg, Hamburg, Germany
Related authors
Robert G. Bingham, Julien A. Bodart, Marie G. P. Cavitte, Ailsa Chung, Rebecca J. Sanderson, Johannes C. R. Sutter, Olaf Eisen, Nanna B. Karlsson, Joseph A. MacGregor, Neil Ross, Duncan A. Young, David W. Ashmore, Andreas Born, Winnie Chu, Xiangbin Cui, Reinhard Drews, Steven Franke, Vikram Goel, John W. Goodge, A. Clara J. Henry, Antoine Hermant, Benjamin H. Hills, Nicholas Holschuh, Michelle R. Koutnik, Gwendolyn J.-M. C. Leysinger Vieli, Emma J. Mackie, Elisa Mantelli, Carlos Martín, Felix S. L. Ng, Falk M. Oraschewski, Felipe Napoleoni, Frédéric Parrenin, Sergey V. Popov, Therese Rieckh, Rebecca Schlegel, Dustin M. Schroeder, Martin J. Siegert, Xueyuan Tang, Thomas O. Teisberg, Kate Winter, Shuai Yan, Harry Davis, Christine F. Dow, Tyler J. Fudge, Tom A. Jordan, Bernd Kulessa, Kenichi Matsuoka, Clara J. Nyqvist, Maryam Rahnemoonfar, Matthew R. Siegfried, Shivangini Singh, Verjan Višnjević, Rodrigo Zamora, and Alexandra Zuhr
EGUsphere, https://doi.org/10.5194/egusphere-2024-2593, https://doi.org/10.5194/egusphere-2024-2593, 2024
Short summary
Short summary
The ice sheets covering Antarctica have built up over millenia through successive snowfall events which become buried and preserved as internal surfaces of equal age detectable with ice-penetrating radar. This paper describes an international initiative to work together on this archival data to build a comprehensive 3-D picture of how old the ice is everywhere across Antarctica, and how this will be used to reconstruct past and predict future ice and climate behaviour.
Nils Bochow, Philipp Hess, and Alexander Robinson
EGUsphere, https://doi.org/https://doi.org/10.48550/arXiv.2507.22485, https://doi.org/https://doi.org/10.48550/arXiv.2507.22485, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
Short summary
This study presents a fast, physics-guided machine-learning method that downscales coarse climate fields to fine resolution while enforcing conservation of large-scale totals. Trained on regional climate simulations and driven by Earth system model output, it handles extremes and outperforms linear interpolation, providing realistic, high-resolution forcing for ice-sheet models and improving projections of Greenland’s sea-level contribution.
Lucía Gutiérrez-González, Alexander Robinson, Jorge Alvarez-Solas, Ilaria Tabone, Jan Swierczek-Jereczek, Daniel Moreno-Parada, and Marisa Montoya
EGUsphere, https://doi.org/10.5194/egusphere-2025-2616, https://doi.org/10.5194/egusphere-2025-2616, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
Short summary
The Greenland ice sheet is considered a tipping element: if temperatures exceed its threshold, it would transition to a virtually ice-free state. We analyze its stability across the full range of glacial-interglacial temperatures, as well as those expected in the coming centuries. We find a future critical threshold between +1.5 and +2 K of global warming, another under colder climates, and persistent hysteresis across the full range of study.
Daniel Moreno-Parada, Alexander Robinson, Marisa Montoya, and Jorge Alvarez-Solas
Geosci. Model Dev., 18, 3895–3919, https://doi.org/10.5194/gmd-18-3895-2025, https://doi.org/10.5194/gmd-18-3895-2025, 2025
Short summary
Short summary
We introduce Nix, an ice-sheet model designed for understanding how large masses of ice behave. Nix is a computer programme that simulates the movement and temperature evolution in ice sheets. It helps us study how ice sheets respond to changes in the atmosphere and ocean. We found that ice temperatures play an essential role in determining the motion and stability of ice sheets. Nix is a useful tool for learning how climate change affects polar ice sheets.
Sergio Pérez-Montero, Jorge Alvarez-Solas, Jan Swierczek-Jereczek, Daniel Moreno-Parada, Alexander Robinson, and Marisa Montoya
Earth Syst. Dynam., 16, 915–937, https://doi.org/10.5194/esd-16-915-2025, https://doi.org/10.5194/esd-16-915-2025, 2025
Short summary
Short summary
The climate of the last 3 Myr has varied between cold and warm periods. Numerous independent mechanisms have been proposed to explain this; however, no effort has been made to study their competing effects. Here we present a simple but physically motivated model that includes these mechanisms in a modular way. We identify ice-sheet dynamics and lithosphere displacement as main triggers, but reproducing the climate records additionally requires the natural darkening of ice.
Ricarda Winkelmann, Donovan P. Dennis, Jonathan F. Donges, Sina Loriani, Ann Kristin Klose, Jesse F. Abrams, Jorge Alvarez-Solas, Torsten Albrecht, David Armstrong McKay, Sebastian Bathiany, Javier Blasco Navarro, Victor Brovkin, Eleanor Burke, Gokhan Danabasoglu, Reik V. Donner, Markus Drüke, Goran Georgievski, Heiko Goelzer, Anna B. Harper, Gabriele Hegerl, Marina Hirota, Aixue Hu, Laura C. Jackson, Colin Jones, Hyungjun Kim, Torben Koenigk, Peter Lawrence, Timothy M. Lenton, Hannah Liddy, José Licón-Saláiz, Maxence Menthon, Marisa Montoya, Jan Nitzbon, Sophie Nowicki, Bette Otto-Bliesner, Francesco Pausata, Stefan Rahmstorf, Karoline Ramin, Alexander Robinson, Johan Rockström, Anastasia Romanou, Boris Sakschewski, Christina Schädel, Steven Sherwood, Robin S. Smith, Norman J. Steinert, Didier Swingedouw, Matteo Willeit, Wilbert Weijer, Richard Wood, Klaus Wyser, and Shuting Yang
EGUsphere, https://doi.org/10.5194/egusphere-2025-1899, https://doi.org/10.5194/egusphere-2025-1899, 2025
This preprint is open for discussion and under review for Earth System Dynamics (ESD).
Short summary
Short summary
The Tipping Points Modelling Intercomparison Project (TIPMIP) is an international collaborative effort to systematically assess tipping point risks in the Earth system using state-of-the-art coupled and stand-alone domain models. TIPMIP will provide a first global atlas of potential tipping dynamics, respective critical thresholds and key uncertainties, generating an important building block towards a comprehensive scientific basis for policy- and decision-making.
Sergio Pérez-Montero, Jorge Alvarez-Solas, Jan Swierczek-Jereczek, Daniel Moreno-Parada, Alexander Robinson, and Marisa Montoya
EGUsphere, https://doi.org/10.5194/egusphere-2025-2467, https://doi.org/10.5194/egusphere-2025-2467, 2025
Short summary
Short summary
Almost 3 million years ago, the planet began to experience a succession of cold and warm periods every 40,000 years. However, about 1 million years ago, they began to occur every 100,000 years. In this paper we explore how the change in the basal velocity of the ice sheets could have produced this change in behavior. On the other hand, we also see that in our model, decreasing in time the sensitivity of snowfall to temperature is also an effective mechanism with which to reproduce the records.
Charlotte Rahlves, Heiko Goelzer, Andreas Born, and Petra M. Langebroek
EGUsphere, https://doi.org/10.5194/egusphere-2025-2192, https://doi.org/10.5194/egusphere-2025-2192, 2025
Short summary
Short summary
We present a method to better simulate how Greenland’s ice sheet may change over thousands of years in response to climate change. Using a stand-alone ice sheet model, we adjust snowfall and melting patterns based on changes in the ice sheet’s shape. This approach avoids complex coupled models and enables faster testing of many future scenarios to understand the long-term stability of Greenland’s ice.
Sjur Barndon, Robert Law, Andreas Born, Thomas Chudley, and Stefanie Brechtelsbauer
EGUsphere, https://doi.org/10.5194/egusphere-2025-1304, https://doi.org/10.5194/egusphere-2025-1304, 2025
Short summary
Short summary
By simulating a section of the Scandinavian Ice Sheet over a deep fjord, we aim to understand the behaviour of ice sheets over rough landscapes. For perpendicular flow, we find reduced speed within the fjord and reverse flow at its base. Comparing real and smoothed topography shows that low-resolution models fail to capture these effects. Our findings have implications for Greenland ice sheet models, as commonly used bedrock resolutions likely overlook the influence of similar rough landscapes.
Robert Law, Andreas Born, Philipp Voigt, Joseph A. MacGregor, and Claire Marie Guimond
EGUsphere, https://doi.org/10.48550/arXiv.2411.18779, https://doi.org/10.48550/arXiv.2411.18779, 2025
Short summary
Short summary
Convection has been previously, yet contentiously, suggested for ice sheets, but never before comprehensively explored using numerical models. We use mantle dynamics code to test the hypothesis that convection gives rise to enigmatic plume-like features observed in radio-stratigraphy observations of the Greenland Ice Sheet. Our results provide very good agreement with field observations, but could imply that ice in northern Greenland is significantly softer than commonly thought.
Charlotte Rahlves, Heiko Goelzer, Andreas Born, and Petra M. Langebroek
The Cryosphere, 19, 1205–1220, https://doi.org/10.5194/tc-19-1205-2025, https://doi.org/10.5194/tc-19-1205-2025, 2025
Short summary
Short summary
Mass loss from the Greenland ice sheet significantly contributes to rising sea levels, threatening coastal communities globally. To improve future sea-level projections, we simulated ice sheet behavior until 2100, initializing the model with observed geometry and using various climate models. Predictions indicate a sea-level rise of 32 to 228 mm by 2100, with climate model uncertainty being the main source of variability in projections.
Lise Seland Graff, Jerry Tjiputra, Ada Gjermundsen, Andreas Born, Jens Boldingh Debernard, Heiko Goelzer, Yan-Chun He, Petra Margaretha Langebroek, Aleksi Nummelin, Dirk Olivié, Øyvind Seland, Trude Storelvmo, Mats Bentsen, Chuncheng Guo, Andrea Rosendahl, Dandan Tao, Thomas Toniazzo, Camille Li, Stephen Outten, and Michael Schulz
EGUsphere, https://doi.org/10.5194/egusphere-2025-472, https://doi.org/10.5194/egusphere-2025-472, 2025
Short summary
Short summary
The magnitude of future Arctic amplification is highly uncertain. Using the Norwegian Earth system model, we explore the effect of improving the representation of clouds, ocean eddies, the Greenland ice sheet, sea ice, and ozone on the projected Arctic winter warming in a coordinated experiment set. These improvements all lead to enhanced projected Arctic warming, with the largest changes found in the sea-ice retreat regions and the largest uncertainty on the Atlantic side.
Konstanze Haubner, Heiko Goelzer, and Andreas Born
EGUsphere, https://doi.org/10.5194/egusphere-2024-3785, https://doi.org/10.5194/egusphere-2024-3785, 2025
Short summary
Short summary
We add a new dynamic component – an ice sheet model simulating the Greenland ice sheet – to an Earth system model that already captures the global climate evolution including ocean, atmosphere, land and sea ice. Under a strong warming scenario, the global warming of 10 °C over 250 yrs is dominating the climate evolution. Changes from the ice-climate interaction are mainly local yet impacting the evolution of the Greenland ice sheet. Hence, ice-climate feedbacks should be considered beyond 2100.
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.
Heiko Goelzer, Petra M. Langebroek, Andreas Born, Stefan Hofer, Konstanze Haubner, Michele Petrini, Gunter Leguy, William H. Lipscomb, and Katherine Thayer-Calder
EGUsphere, https://doi.org/10.5194/egusphere-2024-3045, https://doi.org/10.5194/egusphere-2024-3045, 2025
Short summary
Short summary
On the backdrop of observed accelerating ice sheet mass loss over the last few decades, there is growing interest in the role of ice sheet changes in global climate projections. In this regard, we have coupled an Earth system model with an ice sheet model and have produced an initial set of climate projections including an interactive coupling with a dynamic Greenland ice sheet.
Tobias Zolles and Andreas Born
The Cryosphere, 18, 4831–4844, https://doi.org/10.5194/tc-18-4831-2024, https://doi.org/10.5194/tc-18-4831-2024, 2024
Short summary
Short summary
The Greenland ice sheet largely depends on the climate state. The uncertainties associated with the year-to-year variability have only a marginal impact on our simulated surface mass budget; this increases our confidence in projections and reconstructions. Basing the simulations on proxies, e.g., temperature, results in overestimates of the surface mass balance, as climatologies lead to small amounts of snowfall every day. This can be reduced by including sub-monthly precipitation variability.
Robert G. Bingham, Julien A. Bodart, Marie G. P. Cavitte, Ailsa Chung, Rebecca J. Sanderson, Johannes C. R. Sutter, Olaf Eisen, Nanna B. Karlsson, Joseph A. MacGregor, Neil Ross, Duncan A. Young, David W. Ashmore, Andreas Born, Winnie Chu, Xiangbin Cui, Reinhard Drews, Steven Franke, Vikram Goel, John W. Goodge, A. Clara J. Henry, Antoine Hermant, Benjamin H. Hills, Nicholas Holschuh, Michelle R. Koutnik, Gwendolyn J.-M. C. Leysinger Vieli, Emma J. Mackie, Elisa Mantelli, Carlos Martín, Felix S. L. Ng, Falk M. Oraschewski, Felipe Napoleoni, Frédéric Parrenin, Sergey V. Popov, Therese Rieckh, Rebecca Schlegel, Dustin M. Schroeder, Martin J. Siegert, Xueyuan Tang, Thomas O. Teisberg, Kate Winter, Shuai Yan, Harry Davis, Christine F. Dow, Tyler J. Fudge, Tom A. Jordan, Bernd Kulessa, Kenichi Matsuoka, Clara J. Nyqvist, Maryam Rahnemoonfar, Matthew R. Siegfried, Shivangini Singh, Verjan Višnjević, Rodrigo Zamora, and Alexandra Zuhr
EGUsphere, https://doi.org/10.5194/egusphere-2024-2593, https://doi.org/10.5194/egusphere-2024-2593, 2024
Short summary
Short summary
The ice sheets covering Antarctica have built up over millenia through successive snowfall events which become buried and preserved as internal surfaces of equal age detectable with ice-penetrating radar. This paper describes an international initiative to work together on this archival data to build a comprehensive 3-D picture of how old the ice is everywhere across Antarctica, and how this will be used to reconstruct past and predict future ice and climate behaviour.
Antonio Juarez-Martinez, Javier Blasco, Alexander Robinson, Marisa Montoya, and Jorge Alvarez-Solas
The Cryosphere, 18, 4257–4283, https://doi.org/10.5194/tc-18-4257-2024, https://doi.org/10.5194/tc-18-4257-2024, 2024
Short summary
Short summary
We present sea level projections for Antarctica in the context of ISMIP6-2300 with several forcings but extend the simulations to 2500, showing that more than 3 m of sea level contribution could be reached. We also test the sensitivity on a basal melting parameter and determine the timing of the loss of ice in the west region. All the simulations were carried out with the ice sheet model Yelmo.
Daniel Moreno-Parada, Alexander Robinson, Marisa Montoya, and Jorge Alvarez-Solas
The Cryosphere, 18, 4215–4232, https://doi.org/10.5194/tc-18-4215-2024, https://doi.org/10.5194/tc-18-4215-2024, 2024
Short summary
Short summary
Our study tries to understand how the ice temperature evolves in a large mass as in the case of Antarctica. We found a relation that tells us the ice temperature at any point. These results are important because they also determine how the ice moves. In general, ice moves due to slow deformation (as if pouring honey from a jar). Nevertheless, in some regions the ice base warms enough and melts. The liquid water then serves as lubricant and the ice slides and its velocity increases rapidly.
Javier Blasco, Ilaria Tabone, Daniel Moreno-Parada, Alexander Robinson, Jorge Alvarez-Solas, Frank Pattyn, and Marisa Montoya
Clim. Past, 20, 1919–1938, https://doi.org/10.5194/cp-20-1919-2024, https://doi.org/10.5194/cp-20-1919-2024, 2024
Short summary
Short summary
In this study, we assess Antarctic tipping points which may had been crossed during the mid-Pliocene Warm Period. For this, we use data from the PlioMIP2 ensemble. Additionally, we investigate various sources of uncertainty, like ice dynamics and bedrock configuration. Our research significantly enhances our comprehension of Antarctica's response to a warming climate, shedding light on potential future tipping points that may be surpassed.
Jan Swierczek-Jereczek, Marisa Montoya, Konstantin Latychev, Alexander Robinson, Jorge Alvarez-Solas, and Jerry Mitrovica
Geosci. Model Dev., 17, 5263–5290, https://doi.org/10.5194/gmd-17-5263-2024, https://doi.org/10.5194/gmd-17-5263-2024, 2024
Short summary
Short summary
Ice sheets present a thickness of a few kilometres, leading to a vertical deformation of the crust of up to a kilometre. This process depends on properties of the solid Earth, which can be regionally very different. We propose a model that accounts for this often-ignored heterogeneity and run 100 000 simulation years in minutes. Thus, the evolution of ice sheets is modeled with better accuracy, which is critical for a good mitigation of climate change and, in particular, sea-level rise.
Gustav Jungdal-Olesen, Jane Lund Andersen, Andreas Born, and Vivi Kathrine Pedersen
The Cryosphere, 18, 1517–1532, https://doi.org/10.5194/tc-18-1517-2024, https://doi.org/10.5194/tc-18-1517-2024, 2024
Short summary
Short summary
We explore how the shape of the land and underwater features in Scandinavia affected the former Scandinavian ice sheet over time. Using a computer model, we simulate how the ice sheet evolved during different stages of landscape development. We discovered that early glaciations were limited in size by underwater landforms, but as these changed, the ice sheet expanded more rapidly. Our findings highlight the importance of considering landscape changes when studying ice-sheet history.
Sina Loriani, Yevgeny Aksenov, David Armstrong McKay, Govindasamy Bala, Andreas Born, Cristiano M. Chiessi, Henk Dijkstra, Jonathan F. Donges, Sybren Drijfhout, Matthew H. England, Alexey V. Fedorov, Laura Jackson, Kai Kornhuber, Gabriele Messori, Francesco Pausata, Stefanie Rynders, Jean-Baptiste Salée, Bablu Sinha, Steven Sherwood, Didier Swingedouw, and Thejna Tharammal
EGUsphere, https://doi.org/10.5194/egusphere-2023-2589, https://doi.org/10.5194/egusphere-2023-2589, 2023
Short summary
Short summary
In this work, we draw on paleoreords, observations and modelling studies to review tipping points in the ocean overturning circulations, monsoon systems and global atmospheric circulations. We find indications for tipping in the ocean overturning circulations and the West African monsoon, with potentially severe impacts on the Earth system and humans. Tipping in the other considered systems is considered conceivable but currently not sufficiently supported by evidence.
Bjørg Risebrobakken, Mari F. Jensen, Helene R. Langehaug, Tor Eldevik, Anne Britt Sandø, Camille Li, Andreas Born, Erin Louise McClymont, Ulrich Salzmann, and Stijn De Schepper
Clim. Past, 19, 1101–1123, https://doi.org/10.5194/cp-19-1101-2023, https://doi.org/10.5194/cp-19-1101-2023, 2023
Short summary
Short summary
In the observational period, spatially coherent sea surface temperatures characterize the northern North Atlantic at multidecadal timescales. We show that spatially non-coherent temperature patterns are seen both in further projections and a past warm climate period with a CO2 level comparable to the future low-emission scenario. Buoyancy forcing is shown to be important for northern North Atlantic temperature patterns.
Daniel Moreno-Parada, Jorge Alvarez-Solas, Javier Blasco, Marisa Montoya, and Alexander Robinson
The Cryosphere, 17, 2139–2156, https://doi.org/10.5194/tc-17-2139-2023, https://doi.org/10.5194/tc-17-2139-2023, 2023
Short summary
Short summary
We have reconstructed the Laurentide Ice Sheet, located in North America during the Last Glacial Maximum (21 000 years ago). The absence of direct measurements raises a number of uncertainties. Here we study the impact of different physical laws that describe the friction as the ice slides over its base. We found that the Laurentide Ice Sheet is closest to prior reconstructions when the basal friction takes into account whether the base is frozen or thawed during its motion.
Matteo Willeit, Andrey Ganopolski, Alexander Robinson, and Neil R. Edwards
Geosci. Model Dev., 15, 5905–5948, https://doi.org/10.5194/gmd-15-5905-2022, https://doi.org/10.5194/gmd-15-5905-2022, 2022
Short summary
Short summary
In this paper we present the climate component of the newly developed fast Earth system model CLIMBER-X. It has a horizontal resolution of 5°x5° and is designed to simulate the evolution of the Earth system on temporal scales ranging from decades to >100 000 years. CLIMBER-X is available as open-source code and is expected to be a useful tool for studying past climate changes and for the investigation of the long-term future evolution of the climate.
Alexander Robinson, Daniel Goldberg, and William H. Lipscomb
The Cryosphere, 16, 689–709, https://doi.org/10.5194/tc-16-689-2022, https://doi.org/10.5194/tc-16-689-2022, 2022
Short summary
Short summary
Here we investigate the numerical stability of several commonly used methods in order to determine which of them are capable of resolving the complex physics of the ice flow and are also computationally efficient. We find that the so-called DIVA solver outperforms the others. Its representation of the physics is consistent with more complex methods, while it remains computationally efficient at high resolution.
Katharina M. Holube, Tobias Zolles, and Andreas Born
The Cryosphere, 16, 315–331, https://doi.org/10.5194/tc-16-315-2022, https://doi.org/10.5194/tc-16-315-2022, 2022
Short summary
Short summary
We simulated the surface mass balance of the Greenland Ice Sheet in the 21st century by forcing a snow model with the output of many Earth system models and four greenhouse gas emission scenarios. We quantify the contribution to uncertainty in surface mass balance of these two factors and the choice of parameters of the snow model. The results show that the differences between Earth system models are the main source of uncertainty. This effect is localised mostly near the equilibrium line.
Andreas Born and Alexander Robinson
The Cryosphere, 15, 4539–4556, https://doi.org/10.5194/tc-15-4539-2021, https://doi.org/10.5194/tc-15-4539-2021, 2021
Short summary
Short summary
Ice penetrating radar reflections from the Greenland ice sheet are the best available record of past accumulation and how these layers have been deformed over time by the flow of ice. Direct simulations of this archive hold great promise for improving our models and for uncovering details of ice sheet dynamics that neither models nor data could achieve alone. We present the first three-dimensional ice sheet model that explicitly simulates individual layers of accumulation and how they deform.
Tobias Zolles and Andreas Born
The Cryosphere, 15, 2917–2938, https://doi.org/10.5194/tc-15-2917-2021, https://doi.org/10.5194/tc-15-2917-2021, 2021
Short summary
Short summary
We investigate the sensitivity of a glacier surface mass and the energy balance model of the Greenland ice sheet for the cold period of the Last Glacial Maximum (LGM) and the present-day climate. The results show that the model sensitivity changes with climate. While for present-day simulations inclusions of sublimation and hoar formation are of minor importance, they cannot be neglected during the LGM. To simulate the surface mass balance over long timescales, a water vapor scheme is necessary.
Javier Blasco, Jorge Alvarez-Solas, Alexander Robinson, and Marisa Montoya
The Cryosphere, 15, 215–231, https://doi.org/10.5194/tc-15-215-2021, https://doi.org/10.5194/tc-15-215-2021, 2021
Short summary
Short summary
During the Last Glacial Maximum the Antarctic Ice Sheet was larger and more extended than at present. However, neither its exact position nor the total ice volume are well constrained. Here we investigate how the different climatic boundary conditions, as well as basal friction configurations, affect the size and extent of the Antarctic Ice Sheet and discuss its potential implications.
Xavier Fettweis, Stefan Hofer, Uta Krebs-Kanzow, Charles Amory, Teruo Aoki, Constantijn J. Berends, Andreas Born, Jason E. Box, Alison Delhasse, Koji Fujita, Paul Gierz, Heiko Goelzer, Edward Hanna, Akihiro Hashimoto, Philippe Huybrechts, Marie-Luise Kapsch, Michalea D. King, Christoph Kittel, Charlotte Lang, Peter L. Langen, Jan T. M. Lenaerts, Glen E. Liston, Gerrit Lohmann, Sebastian H. Mernild, Uwe Mikolajewicz, Kameswarrao Modali, Ruth H. Mottram, Masashi Niwano, Brice Noël, Jonathan C. Ryan, Amy Smith, Jan Streffing, Marco Tedesco, Willem Jan van de Berg, Michiel van den Broeke, Roderik S. W. van de Wal, Leo van Kampenhout, David Wilton, Bert Wouters, Florian Ziemen, and Tobias Zolles
The Cryosphere, 14, 3935–3958, https://doi.org/10.5194/tc-14-3935-2020, https://doi.org/10.5194/tc-14-3935-2020, 2020
Short summary
Short summary
We evaluated simulated Greenland Ice Sheet surface mass balance from 5 kinds of models. While the most complex (but expensive to compute) models remain the best, the faster/simpler models also compare reliably with observations and have biases of the same order as the regional models. Discrepancies in the trend over 2000–2012, however, suggest that large uncertainties remain in the modelled future SMB changes as they are highly impacted by the meltwater runoff biases over the current climate.
Cited articles
AntArchitecture: Archiving and interrogating Antarctica's internal structure from radar sounding, in: Workshop to establish scientific goals, working practices, and funding routes, Tech. rep., School of GeoSciences, 2017. a
Born, A.: Tracer transport in an isochronal ice sheet model, J. Glaciol., 63, 22–38, https://doi.org/10.1017/jog.2016.111, 2017. a, b, c, d
Born, A. and Robinson, A.: Modeling the Greenland englacial stratigraphy, The Cryosphere, 15, 4539–4556, https://doi.org/10.5194/tc-15-4539-2021, 2021. a, b, c
Brondex, J., Gillet-Chaulet, F., and Gagliardini, O.: Sensitivity of centennial mass loss projections of the Amundsen basin to the friction law, The Cryosphere, 13, 177–195, https://doi.org/10.5194/tc-13-177-2019, 2019. a
Cavitte, M. G. P., Young, D. A., Mulvaney, R., Ritz, C., Greenbaum, J. S., Ng, G., Kempf, S. D., Quartini, E., Muldoon, G. R., Paden, J., Frezzotti, M., Roberts, J. L., Tozer, C. R., Schroeder, D. M., and Blankenship, D. D.: A detailed radiostratigraphic data set for the central East Antarctic Plateau spanning from the Holocene to the mid-Pleistocene, Earth Syst. Sci. Data, 13, 4759–4777, https://doi.org/10.5194/essd-13-4759-2021, 2021. a
Choi, Y., Seroussi, H., Gardner, A., and Schlegel, N.-J.: Uncovering basal friction in Northwest Greenland using an ice flow model and observations of the past decade, J. Geophy. Res.-Earth Surf., 127, e2022JF006710, https://doi.org/10.1029/2022JF006710, 2022. a
Clarke, G. K. and Marshall, S. J.: Isotopic balance of the Greenland Ice Sheet : modelled concentrations of water isotopes from 30,000 BP to present, Quaternary Sci. Rev., 21, 419–430, https://doi.org/10.1016/S0277-3791(01)00111-1, 2002. a
Clarke, G. K., Lhomme, N., and Marshall, S. J.: Tracer transport in the Greenland ice sheet: three-dimensional isotopic stratigraphy, Quaternary Sci. Rev., 24, 155–171, https://doi.org/10.1016/j.quascirev.2004.08.021, 2005. a
Dahl-Jensen, D., Albert, M. R., Aldahan, A., Azuma, N., Balslev-Clausen, D., Baumgartner, M., Berggren, A. M., Bigler, M., Binder, T., Blunier, T., Bourgeois, J. C., Brook, E. J., Buchardt, S. L., Buizert, C., Capron, E., Chappellaz, J., Chung, J., Clausen, H. B., Cvijanovic, I., Davies, S. M., Ditlevsen, P., Eicher, O., Fischer, H., Fisher, D. A., Fleet, L. G., Gfeller, G., Gkinis, V., Gogineni, S., Goto-Azuma, K., Grinsted, A., Gudlaugsdottir, H., Guillevic, M., Hansen, S. B., Hansson, M., Hirabayashi, M., Hong, S., Hur, S. D., Huybrechts, P., Hvidberg, C. S., Iizuka, Y., Jenk, T., Johnsen, S. J., Jones, T. R., Jouzel, J., Karlsson, N. B., Kawamura, K., Keegan, K., Kettner, E., Kipfstuhl, S., Kjær, H. A., Koutnik, M., Kuramoto, T., Köhler, P., Laepple, T., Landais, A., Langen, P. L., Larsen, L. B., Leuenberger, D., Leuenberger, M., Leuschen, C., Li, J., Lipenkov, V., Martinerie, P., Maselli, O. J., Masson-Delmotte, V., McConnell, J. R., Miller, H., Mini, O., Miyamoto, a., Montagnat-Rentier, M., Mulvaney, R., Muscheler, R., Orsi, A. J., Paden, J., Panton, C., Pattyn, F., Petit, J.-R., Pol, K., Popp, T., Possnert, G., Prié, F., Prokopiou, M., Quiquet, A., Rasmussen, S. O., Raynaud, D., Ren, J., Reutenauer, C., Ritz, C., Röckmann, T., Rosen, J. L., Rubino, M., Rybak, O., Samyn, D., Sapart, C. J., Schilt, A., Schmidt, a. M. Z., Schwander, J., Schüpbach, S., Seierstad, I., Severinghaus, J. P., Sheldon, S., Simonsen, S. B., Sjolte, J., Solgaard, A. M., Sowers, T., Sperlich, P., Steen-Larsen, H. C., Steffen, K., Steffensen, J. P., Steinhage, D., Stocker, T. F., Stowasser, C., Sturevik, A. S., Sturges, W. T., Sveinbjörnsdottir, A., Svensson, A., Tison, J.-L., Uetake, J., Vallelonga, P., van de Wal, R. S. W., van der Wel, G., Vaughn, B. H., Vinther, B., Waddington, E., Wegner, A., Weikusat, I., White, J. W. C., Wilhelms, F., Winstrup, M., Witrant, E., Wolff, E. W., Xiao, C., and Zheng, J.: Eemian interglacial reconstructed from a Greenland folded ice core, Nature, 493, 489–494, https://doi.org/10.1038/nature11789, 2013. a
EPICA Community Members: One-to-one coupling of glacial climate variability in Greenland and Antarctica, Nature, 444, 195–198, https://doi.org/10.1038/nature05301, 2006. a
Fettweis, X., Box, J. E., Agosta, C., Amory, C., Kittel, C., Lang, C., van As, D., Machguth, H., and Gallée, H.: Reconstructions of the 1900–2015 Greenland ice sheet surface mass balance using the regional climate MAR model, The Cryosphere, 11, 1015–1033, https://doi.org/10.5194/tc-11-1015-2017, 2017. a
Goelles, T., Grosfeld, K., and Lohmann, G.: Semi-Lagrangian transport of oxygen isotopes in polythermal ice sheets: implementation and first results, Geosci. Model Dev., 7, 1395–1408, https://doi.org/10.5194/gmd-7-1395-2014, 2014. a
Greve, R. and Blatter, H.: Dynamics of ice sheets and glaciers, Springer Verlag, Berlin Heidelberg New York, https://doi.org/10.1007/978-3-642-03415-2, 2009. a
Joughin, I., Smith, B., and Howat, I.: A complete map of Greenland ice velocity derived from satellite data collected over 20 years, J. Glaciol., 64, 1–11, https://doi.org/10.1017/jog.2017.73, 2018. a, b
Kageyama, M., Harrison, S. P., Kapsch, M.-L., Lofverstrom, M., Lora, J. M., Mikolajewicz, U., Sherriff-Tadano, S., Vadsaria, T., Abe-Ouchi, A., Bouttes, N., Chandan, D., Gregoire, L. J., Ivanovic, R. F., Izumi, K., LeGrande, A. N., Lhardy, F., Lohmann, G., Morozova, P. A., Ohgaito, R., Paul, A., Peltier, W. R., Poulsen, C. J., Quiquet, A., Roche, D. M., Shi, X., Tierney, J. E., Valdes, P. J., Volodin, E., and Zhu, J.: The PMIP4 Last Glacial Maximum experiments: preliminary results and comparison with the PMIP3 simulations, Clim. Past, 17, 1065–1089, https://doi.org/10.5194/cp-17-1065-2021, 2021. a
Lhomme, N., Clarke, G. K. C., and Marshall, S. J.: Tracer transport in the Greenland Ice Sheet: constraints on ice cores and glacial history, Quaternary Sci. Rev., 24, 173–194, https://doi.org/10.1016/j.quascirev.2004.08.020, 2005. a
MacGregor, J. A., Fahnestock, M. A., Catania, G. A., Paden, J. D., Gogineni, S., Young, S. K., Rybarski, S. C., Mabrey, A. N., Wagman, B. M., and Morlighem, M.: Radiostratigraphy and age structure of the Greenland Ice Sheet, J. Geophys. Res., 120, 212–241, https://doi.org/10.1002/2014JF003215, 2015. a, b, c, d, e, f, g, h, i
MacGregor, J. A., Chu, W., Colgan, W. T., Fahnestock, M. A., Felikson, D., Karlsson, N. B., Nowicki, S. M. J., and Studinger, M.: GBaTSv2: a revised synthesis of the likely basal thermal state of the Greenland Ice Sheet, The Cryosphere, 16, 3033–3049, https://doi.org/10.5194/tc-16-3033-2022, 2022. a
Morlighem, M., Williams, C. N., Rignot, E., An, L., Arndt, J. E., Bamber, J. L., Catania, G., Chauché, N., Dowdeswell, J. A., Dorschel, B., Fenty, I., Hogan, K., Howat, I., Hubbard, A., Jakobsson, M., Jordan, T. M., Kjeldsen, K. K., Millan, R., Mayer, L., Mouginot, J., Noël, B. P. Y., O'Cofaigh, C., Palmer, S., Rysgaard, S., Seroussi, H., Siegert, M. J., Slabon, P., Straneo, F., van den Broeke, M. R., Weinrebe, W., Wood, M., and Zinglersen, K. B.: BedMachine v3: Complete Bed Topography and Ocean Bathymetry Mapping of Greenland From Multibeam Echo Sounding Combined With Mass Conservation, Geophys. Res. Lett., 44, 11051–11061, https://doi.org/10.1002/2017GL074954, 2017. a, b
Nishida, A.: Experience in Developing an Open Source Scalable Software Infrastructure in Japan. In: Computational Science and Its Applications – ICCSA 2010, edited by D. Taniar and O. Gervasi and B. Murgante and E. Pardede and B. O. Apduhan, Springer Berlin Heidelberg, Berlin, Heidelberg, 2010. a
North Greenland Ice Core Project members: High-resolution record of Norhtern Hemisphere climate extending into the last interglacial period, Nature, 431, 147–151, https://doi.org/10.1038/nature02805, 2004. a
Rieckh, T.: Code and data for “Introducing ELSA v2.0: an isochronal model for ice-sheet layer tracing”, Zenodo [code and data set], https://doi.org/10.5281/zenodo.10590358, 2024. a
Robinson, A., Alvarez-Solas, J., Montoya, M., Goelzer, H., Greve, R., and Ritz, C.: Description and validation of the ice-sheet model Yelmo (version 1.0), Geosci. Model Dev., 13, 2805–2823, https://doi.org/10.5194/gmd-13-2805-2020, 2020. a, b
Rybak, O. and Huybrechts, P.: A comparison of Eulerian and Lagrangian methods for dating in numerical ice-sheet models, Ann. Glaciol., 37, 150–158, https://doi.org/10.3189/172756403781815393, 2003. a
Shapiro, N. M. and Ritzwoller, M. H.: Inferring surface heat flux distributions guided by a global seismic model: Particular application to Antarctica, Earth Planet. Sc. Lett., 223, 213–224, https://doi.org/10.1016/j.epsl.2004.04.011, 2004. a
Tabone, I., Blasco, J., Robinson, A., Alvarez-Solas, J., and Montoya, M.: The sensitivity of the Greenland Ice Sheet to glacial–interglacial oceanic forcing, Clim. Past, 14, 455–472, https://doi.org/10.5194/cp-14-455-2018, 2018. a
Vasskog, K., Langebroek, P. M., Andrews, J. T., Nilsen, J. E. Ø., and Nesje, A.: The Greenland Ice Sheet during the last glacial cycle: Current ice loss and contribution to sea-level rise from a palaeoclimatic perspective, Earth-Sci. Rev., 150, 45–67, https://doi.org/10.1016/j.earscirev.2015.07.006, 2015. a
Short summary
We present the open-source model ELSA, which simulates the internal age structure of large ice sheets. It creates layers of snow accumulation at fixed times during the simulation, which are used to model the internal stratification of the ice sheet. Together with reconstructed isochrones from radiostratigraphy data, ELSA can be used to assess ice sheet models and to improve their parameterization. ELSA can be used coupled to an ice sheet model or forced with its output.
We present the open-source model ELSA, which simulates the internal age structure of large ice...
