Articles | Volume 18, issue 11
https://doi.org/10.5194/tc-18-5519-2024
© 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/tc-18-5519-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The future of Upernavik Isstrøm through the ISMIP6 framework: sensitivity analysis and Bayesian calibration of ensemble prediction
IGE, Univ. Grenoble Alpes, CNRS, IRD, 38000 Grenoble, France
Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, Helsinki, Finland
Fabien Gillet-Chaulet
IGE, Univ. Grenoble Alpes, CNRS, IRD, 38000 Grenoble, France
Nicolas Champollion
IGE, Univ. Grenoble Alpes, CNRS, IRD, 38000 Grenoble, France
Romain Millan
IGE, Univ. Grenoble Alpes, CNRS, IRD, 38000 Grenoble, France
Heiko Goelzer
NORCE Norwegian Research Centre, Bjerknes Centre for Climate Research, Bergen, Norway
Jérémie Mouginot
IGE, Univ. Grenoble Alpes, CNRS, IRD, 38000 Grenoble, France
deceased, 28 September 2022
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Anna Derkacheva, Fabien Gillet-Chaulet, Jeremie Mouginot, Eliot Jager, Nathan Maier, and Samuel Cook
The Cryosphere, 15, 5675–5704, https://doi.org/10.5194/tc-15-5675-2021, https://doi.org/10.5194/tc-15-5675-2021, 2021
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Along the edges of the Greenland Ice Sheet surface melt lubricates the bed and causes large seasonal fluctuations in ice speeds during summer. Accurately understanding how these ice speed changes occur is difficult due to the inaccessibility of the glacier bed. We show that by using surface velocity maps with high temporal resolution and numerical modelling we can infer the basal conditions that control seasonal fluctuations in ice speed and gain insight into seasonal dynamics over large areas.
Heiko Goelzer, Constantijn J. Berends, Fredrik Boberg, Gael Durand, Tamsin Edwards, Xavier Fettweis, Fabien Gillet-Chaulet, Quentin Glaude, Philippe Huybrechts, Sébastien Le clec'h, Ruth Mottram, Brice Noël, Martin Olesen, Charlotte Rahlves, Jeremy Rohmer, Michiel van den Broeke, and Roderik S. W. van de Wal
EGUsphere, https://doi.org/10.5194/egusphere-2025-3098, https://doi.org/10.5194/egusphere-2025-3098, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
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We present an ensemble of ice sheet model projections for the Greenland ice sheet. The focus is on providing projections that improve our understanding of the range future sea-level rise and the inherent uncertainties over the next 100 to 300 years. Compared to earlier work we more fully account for some of the uncertainties in sea-level projections. We include a wider range of climate model output, more climate change scenarios and we extend projections schematically up to year 2300.
Lucille Gimenes, Romain Millan, Nicolas Champollion, and Jordi Bolibar
EGUsphere, https://doi.org/10.5194/egusphere-2025-3460, https://doi.org/10.5194/egusphere-2025-3460, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
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This study looks how changes in glacier thickness estimates and temperature affect when meltwater from glaciers in the western Kunlun Mountains will reach its peak. Using a global glacier model and two different datasets, we found that smaller glaciers and warmer temperatures cause peak meltwater to happen sooner. This is of interests since it affects future water supplies for people relying on glacier runoff, highlighting the need for accurate ice volume estimates.
Cyrille Mosbeux, Peter Råback, Adrien Gilbert, Julien Brondex, Fabien Gillet-Chaulet, Nicolas C. Jourdain, Mondher Chekki, Olivier Gagliardini, and Gaël Durand
EGUsphere, https://doi.org/10.5194/egusphere-2025-3039, https://doi.org/10.5194/egusphere-2025-3039, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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Transport processes like rocks carried by ice flow and damage evolution – a proxy for crevasses – are key in ice sheet modeling and should occur without diffusion. Yet, standard numerical methods often blur these features. We explore a particle-based Semi-Lagrangian approach, comparing it to a Discontinuous Galerkin method, and show it can accurately simulate such transport when run at high enough resolution.
Davor Dundovic, Joseph G. Wallwork, Stephan C. Kramer, Fabien Gillet-Chaulet, Regine Hock, and Matthew D. Piggott
Geosci. Model Dev., 18, 4023–4044, https://doi.org/10.5194/gmd-18-4023-2025, https://doi.org/10.5194/gmd-18-4023-2025, 2025
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Accurate numerical studies of glaciers often require high-resolution simulations, which often prove too demanding even for modern computers. In this paper we develop a method that identifies whether different parts of a glacier require high or low resolution based on its physical features, such as its thickness and velocity. We show that by doing so we can achieve a more optimal simulation accuracy for the available computing resources compared to uniform-resolution simulations.
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).
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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.
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
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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.
Jonas K. Andersen, Rasmus P. Meyer, Flora S. Huiban, Mads L. Dømgaard, Romain Millan, and Anders A. Bjørk
The Cryosphere, 19, 1717–1724, https://doi.org/10.5194/tc-19-1717-2025, https://doi.org/10.5194/tc-19-1717-2025, 2025
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Storstrømmen Glacier in northeastern Greenland goes through cycles of sudden flow speed-ups (known as surges) followed by long quiet phases. It is currently in its quiet phase, but recent measurements suggest it may be nearing conditions for a new surge, possibly between 2027 and 2040. We also observed several lake drainages that caused brief increases in glacier flow but did not trigger a surge. Continued monitoring is essential to understand how these processes influence glacier behavior.
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
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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.
Etienne Ducasse, Romain Millan, Jonas Kvist Andersen, and Antoine Rabatel
The Cryosphere, 19, 911–917, https://doi.org/10.5194/tc-19-911-2025, https://doi.org/10.5194/tc-19-911-2025, 2025
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Our study examines glacier movement in the tropical Andes from 2013 to 2022 using satellite data. Despite challenges like small glacier size and frequent cloud cover, we tracked annual speeds and seasonal changes. We found stable annual speeds but significant shifts between wet and dry seasons, likely due to changes in meltwater production and glacier–bedrock conditions. This research enhances understanding of how tropical glaciers react to climate change.
Justine Caillet, Nicolas C. Jourdain, Pierre Mathiot, Fabien Gillet-Chaulet, Benoit Urruty, Clara Burgard, Charles Amory, Mondher Chekki, and Christoph Kittel
Earth Syst. Dynam., 16, 293–315, https://doi.org/10.5194/esd-16-293-2025, https://doi.org/10.5194/esd-16-293-2025, 2025
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Internal climate variability, resulting from processes intrinsic to the climate system, modulates the Antarctic response to climate change by delaying or offsetting its effects. Using climate and ice-sheet models, we highlight that irreducible internal climate variability significantly enlarges the likely range of Antarctic contribution to sea-level rise until 2100. Thus, we recommend considering internal climate variability as a source of uncertainty for future ice-sheet projections.
Jeremy Rohmer, Heiko Goelzer, Tamsin Edwards, Goneri Le Cozannet, and Gael Durand
EGUsphere, https://doi.org/10.5194/egusphere-2025-52, https://doi.org/10.5194/egusphere-2025-52, 2025
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Developing robust protocols to design multi-model ensembles is of primary importance for the uncertainty quantification of sea level projections. Here, we set up a series of computer experiments to reflect design decisions for the prediction of future sea level contribution of the Greenland ice sheet. We show the importance of including the most extreme climate scenario, and the benefit of having diversity in numerical models for ice sheet modelling and regional climate assessments.
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
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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
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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.
Laurane Charrier, Amaury Dehecq, Lei Guo, Fanny Brun, Romain Millan, Nathan Lioret, Luke Copland, Nathan Maier, Christine Dow, and Paul Halas
EGUsphere, https://doi.org/10.5194/egusphere-2024-3409, https://doi.org/10.5194/egusphere-2024-3409, 2025
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While global annual glacier velocities are openly accessible, sub-annual velocity time series are still lacking. This hinders our ability to understand flow processes and the integration of these observations in numerical models. We introduce an open source Python package called TICOI to fuses multi-temporal and multi-sensor image-pair velocities produced by different processing chains to produce standardized sub-annual velocity products.
Michele Petrini, Meike D. W. Scherrenberg, Laura Muntjewerf, Miren Vizcaino, Raymond Sellevold, Gunter R. Leguy, William H. Lipscomb, and Heiko Goelzer
The Cryosphere, 19, 63–81, https://doi.org/10.5194/tc-19-63-2025, https://doi.org/10.5194/tc-19-63-2025, 2025
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Anthropogenic warming is causing accelerated Greenland ice sheet melt. Here, we use a computer model to understand how prolonged warming and ice melt could threaten ice sheet stability. We find a threshold beyond which Greenland will lose more than 80 % of its ice over several thousand years, due to the interaction of surface and solid-Earth processes. Nearly complete Greenland ice sheet melt occurs when the ice margin disconnects from a region of high elevation in western Greenland.
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
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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.
Harry Zekollari, Matthias Huss, Lilian Schuster, Fabien Maussion, David R. Rounce, Rodrigo Aguayo, Nicolas Champollion, Loris Compagno, Romain Hugonnet, Ben Marzeion, Seyedhamidreza Mojtabavi, and Daniel Farinotti
The Cryosphere, 18, 5045–5066, https://doi.org/10.5194/tc-18-5045-2024, https://doi.org/10.5194/tc-18-5045-2024, 2024
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Glaciers are major contributors to sea-level rise and act as key water resources. Here, we model the global evolution of glaciers under the latest generation of climate scenarios. We show that the type of observations used for model calibration can strongly affect the projections at the local scale. Our newly projected 21st century global mass loss is higher than the current community estimate as reported in the latest Intergovernmental Panel on Climate Change (IPCC) report.
Alexis Caro, Thomas Condom, Antoine Rabatel, Nicolas Champollion, Nicolás García, and Freddy Saavedra
The Cryosphere, 18, 2487–2507, https://doi.org/10.5194/tc-18-2487-2024, https://doi.org/10.5194/tc-18-2487-2024, 2024
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The glacier runoff changes are still unknown in most of the Andean catchments, thereby increasing uncertainties in estimating water availability, especially during the dry season. Here, we simulate glacier evolution and related glacier runoff changes across the Andes between 2000 and 2019. Our results indicate a glacier reduction in 93 % of the catchments, leading to a 12 % increase in glacier melt. These results can be downloaded and integrated with discharge measurements in each catchment.
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.
Emily A. Hill, Benoît Urruty, Ronja Reese, Julius Garbe, Olivier Gagliardini, Gaël Durand, Fabien Gillet-Chaulet, G. Hilmar Gudmundsson, Ricarda Winkelmann, Mondher Chekki, David Chandler, and Petra M. Langebroek
The Cryosphere, 17, 3739–3759, https://doi.org/10.5194/tc-17-3739-2023, https://doi.org/10.5194/tc-17-3739-2023, 2023
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The grounding lines of the Antarctic Ice Sheet could enter phases of irreversible retreat or advance. We use three ice sheet models to show that the present-day locations of Antarctic grounding lines are reversible with respect to a small perturbation away from their current position. This indicates that present-day retreat of the grounding lines is not yet irreversible or self-enhancing.
Ronja Reese, Julius Garbe, Emily A. Hill, Benoît Urruty, Kaitlin A. Naughten, Olivier Gagliardini, Gaël Durand, Fabien Gillet-Chaulet, G. Hilmar Gudmundsson, David Chandler, Petra M. Langebroek, and Ricarda Winkelmann
The Cryosphere, 17, 3761–3783, https://doi.org/10.5194/tc-17-3761-2023, https://doi.org/10.5194/tc-17-3761-2023, 2023
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We use an ice sheet model to test where current climate conditions in Antarctica might lead. We find that present-day ocean and atmosphere conditions might commit an irreversible collapse of parts of West Antarctica which evolves over centuries to millennia. Importantly, this collapse is not irreversible yet.
Ugo Nanni, Dirk Scherler, Francois Ayoub, Romain Millan, Frederic Herman, and Jean-Philippe Avouac
The Cryosphere, 17, 1567–1583, https://doi.org/10.5194/tc-17-1567-2023, https://doi.org/10.5194/tc-17-1567-2023, 2023
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Surface melt is a major factor driving glacier movement. Using satellite images, we have tracked the movements of 38 glaciers in the Pamirs over 7 years, capturing their responses to rapid meteorological changes with unprecedented resolution. We show that in spring, glacier accelerations propagate upglacier, while in autumn, they propagate downglacier – all resulting from changes in meltwater input. This provides critical insights into the interplay between surface melt and glacier movement.
Jeremy Rohmer, Remi Thieblemont, Goneri Le Cozannet, Heiko Goelzer, and Gael Durand
The Cryosphere, 16, 4637–4657, https://doi.org/10.5194/tc-16-4637-2022, https://doi.org/10.5194/tc-16-4637-2022, 2022
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To improve the interpretability of process-based projections of the sea-level contribution from land ice components, we apply the machine-learning-based
SHapley Additive exPlanationsapproach to a subset of a multi-model ensemble study for the Greenland ice sheet. This allows us to quantify the influence of particular modelling decisions (related to numerical implementation, initial conditions, or parametrisation of ice-sheet processes) directly in terms of sea-level change contribution.
Nidheesh Gangadharan, Hugues Goosse, David Parkes, Heiko Goelzer, Fabien Maussion, and Ben Marzeion
Earth Syst. Dynam., 13, 1417–1435, https://doi.org/10.5194/esd-13-1417-2022, https://doi.org/10.5194/esd-13-1417-2022, 2022
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We describe the contributions of ocean thermal expansion and land-ice melting (ice sheets and glaciers) to global-mean sea-level (GMSL) changes in the Common Era. The mass contributions are the major sources of GMSL changes in the pre-industrial Common Era and glaciers are the largest contributor. The paper also describes the current state of climate modelling, uncertainties and knowledge gaps along with the potential implications of the past variabilities in the contemporary sea-level rise.
Romain Millan, Jeremie Mouginot, Anna Derkacheva, Eric Rignot, Pietro Milillo, Enrico Ciraci, Luigi Dini, and Anders Bjørk
The Cryosphere, 16, 3021–3031, https://doi.org/10.5194/tc-16-3021-2022, https://doi.org/10.5194/tc-16-3021-2022, 2022
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We detect for the first time a dramatic retreat of the grounding line of Petermann Glacier, a major glacier of the Greenland Ice Sheet. Using satellite data, we also observe a speedup of the glacier and a fracturing of the ice shelf. This sequence of events is coherent with ocean warming in this region and suggests that Petermann Glacier has initiated a phase of destabilization, which is of prime importance for the stability and future contribution of the Greenland Ice Sheet to sea level rise.
Constantijn J. Berends, Heiko Goelzer, Thomas J. Reerink, Lennert B. Stap, and Roderik S. W. van de Wal
Geosci. Model Dev., 15, 5667–5688, https://doi.org/10.5194/gmd-15-5667-2022, https://doi.org/10.5194/gmd-15-5667-2022, 2022
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The rate at which marine ice sheets such as the West Antarctic ice sheet will retreat in a warming climate and ocean is still uncertain. Numerical ice-sheet models, which solve the physical equations that describe the way glaciers and ice sheets deform and flow, have been substantially improved in recent years. Here we present the results of several years of work on IMAU-ICE, an ice-sheet model of intermediate complexity, which can be used to study ice sheets of both the past and the future.
L. Charrier, Y. Yan, E. Colin Koeniguer, J. Mouginot, R. Millan, and E. Trouvé
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2022, 311–318, https://doi.org/10.5194/isprs-annals-V-3-2022-311-2022, https://doi.org/10.5194/isprs-annals-V-3-2022-311-2022, 2022
Anna Derkacheva, Fabien Gillet-Chaulet, Jeremie Mouginot, Eliot Jager, Nathan Maier, and Samuel Cook
The Cryosphere, 15, 5675–5704, https://doi.org/10.5194/tc-15-5675-2021, https://doi.org/10.5194/tc-15-5675-2021, 2021
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Along the edges of the Greenland Ice Sheet surface melt lubricates the bed and causes large seasonal fluctuations in ice speeds during summer. Accurately understanding how these ice speed changes occur is difficult due to the inaccessibility of the glacier bed. We show that by using surface velocity maps with high temporal resolution and numerical modelling we can infer the basal conditions that control seasonal fluctuations in ice speed and gain insight into seasonal dynamics over large areas.
Constantijn J. Berends, Heiko Goelzer, and Roderik S. W. van de Wal
Geosci. Model Dev., 14, 2443–2470, https://doi.org/10.5194/gmd-14-2443-2021, https://doi.org/10.5194/gmd-14-2443-2021, 2021
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The largest uncertainty in projections of sea-level rise comes from ice-sheet retreat. To better understand how these ice sheets respond to the changing climate, ice-sheet models are used, which must be able to reproduce both their present and past evolution. We have created a model that is fast enough to simulate an ice sheet at a high resolution over the course of an entire 120 000-year glacial cycle. This allows us to study processes that cannot be captured by lower-resolution models.
Nathan Maier, Florent Gimbert, Fabien Gillet-Chaulet, and Adrien Gilbert
The Cryosphere, 15, 1435–1451, https://doi.org/10.5194/tc-15-1435-2021, https://doi.org/10.5194/tc-15-1435-2021, 2021
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In Greenland, ice motion and the surface geometry depend on the friction at the bed. We use satellite measurements and modeling to determine how ice speeds and friction are related across the ice sheet. The relationships indicate that ice flowing over bed bumps sets the friction across most of the ice sheet's on-land regions. This result helps simplify and improve our understanding of how ice motion will change in the future.
Vincent Peyaud, Coline Bouchayer, Olivier Gagliardini, Christian Vincent, Fabien Gillet-Chaulet, Delphine Six, and Olivier Laarman
The Cryosphere, 14, 3979–3994, https://doi.org/10.5194/tc-14-3979-2020, https://doi.org/10.5194/tc-14-3979-2020, 2020
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Alpine glaciers are retreating at an accelerating rate in a warming climate. Numerical models allow us to study and anticipate these changes, but the performance of a model is difficult to evaluate. So we compared an ice flow model with the long dataset of observations obtained between 1979 and 2015 on Mer de Glace (Mont Blanc area). The model accurately reconstructs the past evolution of the glacier. We simulate the future evolution of Mer de Glace; it could retreat by 2 to 6 km by 2050.
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
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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.
Jonas Van Breedam, Heiko Goelzer, and Philippe Huybrechts
Earth Syst. Dynam., 11, 953–976, https://doi.org/10.5194/esd-11-953-2020, https://doi.org/10.5194/esd-11-953-2020, 2020
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We made projections of global mean sea-level change during the next 10 000 years for a range in climate forcing scenarios ranging from a peak in carbon dioxide concentrations in the next decades to burning most of the available carbon reserves over the next 2 centuries. We find that global mean sea level will rise between 9 and 37 m, depending on the emission of greenhouse gases. In this study, we investigated the long-term consequence of climate change for sea-level rise.
Martin Rückamp, Heiko Goelzer, and Angelika Humbert
The Cryosphere, 14, 3309–3327, https://doi.org/10.5194/tc-14-3309-2020, https://doi.org/10.5194/tc-14-3309-2020, 2020
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Estimates of future sea-level contribution from the Greenland ice sheet have a large uncertainty based on different origins. We conduct numerical experiments to test the sensitivity of Greenland ice sheet projections to spatial resolution. Simulations with a higher resolution unveil up to 5 % more sea-level rise compared to coarser resolutions. The sensitivity depends on the magnitude of outlet glacier retreat. When no retreat is enforced, the sensitivity exhibits an inverse behaviour.
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
Short summary
Short summary
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.
Cited articles
Albrecht, T., Winkelmann, R., and Levermann, A.: Glacial-cycle simulations of the Antarctic Ice Sheet with the Parallel Ice Sheet Model (PISM) – Part 2: Parameter ensemble analysis, The Cryosphere, 14, 633–656, https://doi.org/10.5194/tc-14-633-2020, 2020. a, b, c
Applegate, P. J., Kirchner, N., Stone, E. J., Keller, K., and Greve, R.: An assessment of key model parametric uncertainties in projections of Greenland Ice Sheet behavior, The Cryosphere, 6, 589–606, https://doi.org/10.5194/tc-6-589-2012, 2012. a
Aschwanden, A., Fahnestock, M. A., Truffer, M., Brinkerhoff, D. J., Hock, R., Khroulev, C., Mottram, R., and Khan, S. A.: Contribution of the Greenland Ice Sheet to sea level over the next millennium, Sci. Adv., 5, eaav9396, https://doi.org/10.1126/sciadv.aav9396, 2019. a, b, c, d
Aschwanden, A., Bartholomaus, T. C., Brinkerhoff, D. J., and Truffer, M.: Brief communication: A roadmap towards credible projections of ice sheet contribution to sea level, The Cryosphere, 15, 5705–5715, https://doi.org/10.5194/tc-15-5705-2021, 2021. a, b, c, d
Bondzio, J. H., Morlighem, M., Seroussi, H., Wood, M. H., and Mouginot, J.: Control of Ocean Temperature on Jakobshavn Isbraes Present and Future Mass Loss, Geophys. Res. Lett., 45, 12912–12921, https://doi.org/10.1029/2018GL079827, 2018. a, b, c
Brown, T.: Admissible scoring systems for continuous distributions, Manuscript P-5235, The Rand Corporation, Santa Monica, CA, 22 pp., 1974. a
Bulthuis, K., Arnst, M., Sun, S., and Pattyn, F.: Uncertainty quantification of the multi-centennial response of the Antarctic ice sheet to climate change, The Cryosphere, 13, 1349–1380, https://doi.org/10.5194/tc-13-1349-2019, 2019. a
Chang, W., Applegate, P. J., Haran, M., and Keller, K.: Probabilistic calibration of a Greenland Ice Sheet model using spatially resolved synthetic observations: toward projections of ice mass loss with uncertainties, Geosci. Model Dev., 7, 1933–1943, https://doi.org/10.5194/gmd-7-1933-2014, 2014. 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. Geophys. Res.-Earth, 127, e2022JF006710, https://doi.org/10.1029/2022JF006710, 2022. a
Cuffey, K. and Paterson, W.: The physics of Glaciers, Elsevier, ISBN 9781493300761, 2010. a
DeConto, R. and Pollard, D.: Contribution of Antarctica to past and future sea-level rise, Nature, 531, 591–597, https://doi.org/10.1038/nature17145, 2016. a
Durand, G., van den Broeke, M. R., Le Cozannet, G., Edwards, T. L., Holland, P. R., Jourdain, N. C., Marzeion, B., Mottram, R., Nicholls, R. J., Pattyn, F., Paul, F., Slangen, A. B. A., Winkelmann, R., Burgard, C., van Calcar, C. J., Barré, J.-B., Bataille, A., and Chapuis, A.: Sea-Level Rise: From Global Perspectives to Local Services, Front. Mar. Sci., 8, 709595, https://doi.org/10.3389/fmars.2021.709595, 2022. a
Edwards, T. L., Brandon, M. A., Durand, G., Edwards, N. R., Golledge, N. R., Holden, P. B., Nias, I. J., Payne, A. J., Ritz, C., and Wernecke, A.: Revisiting Antarctic ice loss due to marine ice-cliff instability, Nature, 566, 58–64, 2019. 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
Fettweis, X., Hofer, S., Krebs-Kanzow, U., Amory, C., Aoki, T., Berends, C. J., Born, A., Box, J. E., Delhasse, A., Fujita, K., Gierz, P., Goelzer, H., Hanna, E., Hashimoto, A., Huybrechts, P., Kapsch, M.-L., King, M. D., Kittel, C., Lang, C., Langen, P. L., Lenaerts, J. T. M., Liston, G. E., Lohmann, G., Mernild, S. H., Mikolajewicz, U., Modali, K., Mottram, R. H., Niwano, M., Noël, B., Ryan, J. C., Smith, A., Streffing, J., Tedesco, M., van de Berg, W. J., van den Broeke, M., van de Wal, R. S. W., van Kampenhout, L., Wilton, D., Wouters, B., Ziemen, F., and Zolles, T.: GrSMBMIP: intercomparison of the modelled 1980–2012 surface mass balance over the Greenland Ice Sheet, The Cryosphere, 14, 3935–3958, https://doi.org/10.5194/tc-14-3935-2020, 2020. a
Gagliardini, O., Zwinger, T., Gillet-Chaulet, F., Durand, G., Favier, L., de Fleurian, B., Greve, R., Malinen, M., Martín, C., Råback, P., Ruokolainen, J., Sacchettini, M., Schäfer, M., Seddik, H., and Thies, J.: Capabilities and performance of Elmer/Ice, a new-generation ice sheet model, Geosci. Model Dev., 6, 1299–1318, https://doi.org/10.5194/gmd-6-1299-2013, 2013. a, b
Gilford, D. M., Ashe, E. L., DeConto, R. M., Kopp, R. E., Pollard, D., and Rovere, A.: Could the last interglacial constrain projections of future Antarctic Ice mass loss and sea-level rise?, J. Geophys. Res.-Earth, 125, e2019JF005418, https://doi.org/10.1029/2019JF005418, 2020. a
Gillet-Chaulet, F.: Assimilation of surface observations in a transient marine ice sheet model using an ensemble Kalman filter, The Cryosphere, 14, 811–832, https://doi.org/10.5194/tc-14-811-2020, 2020. a
Gillet-Chaulet, F., Gagliardini, O., Seddik, H., Nodet, M., Durand, G., Ritz, C., Zwinger, T., Greve, R., and Vaughan, D. G.: Greenland ice sheet contribution to sea-level rise from a new-generation ice-sheet model, The Cryosphere, 6, 1561–1576, https://doi.org/10.5194/tc-6-1561-2012, 2012. a, b, c
Gladstone, R. M., Lee, V., Rougier, J., Payne, A. J., Hellmer, H., Le Brocq, A., Shepherd, A., Edwards, T. L., Gregory, J., and Cornford, S. L.: Calibrated prediction of Pine Island Glacier Retreat during the 21st and 22nd centuries with a coupled flowline model, Earth Planet. Sc. Lett., 333, 191–199, https://doi.org/10.1016/j.epsl.2012.04.022, 2012. a
Glen, J. W. and Perutz, M. F.: The creep of polycrystalline ice, P. Roy. Soc. Lond. Ser. A-Math., 228, 519–538, https://doi.org/10.1098/rspa.1955.0066, 1955. a
Goelzer, H., Nowicki, S., Edwards, T., Beckley, M., Abe-Ouchi, A., Aschwanden, A., Calov, R., Gagliardini, O., Gillet-Chaulet, F., Golledge, N. R., Gregory, J., Greve, R., Humbert, A., Huybrechts, P., Kennedy, J. H., Larour, E., Lipscomb, W. H., Le clec'h, S., Lee, V., Morlighem, M., Pattyn, F., Payne, A. J., Rodehacke, C., Rückamp, M., Saito, F., Schlegel, N., Seroussi, H., Shepherd, A., Sun, S., van de Wal, R., and Ziemen, F. A.: Design and results of the ice sheet model initialisation experiments initMIP-Greenland: an ISMIP6 intercomparison, The Cryosphere, 12, 1433–1460, https://doi.org/10.5194/tc-12-1433-2018, 2018. a, b
Goelzer, H., Nowicki, S., Payne, A., Larour, E., Seroussi, H., Lipscomb, W. H., Gregory, J., Abe-Ouchi, A., Shepherd, A., Simon, E., Agosta, C., Alexander, P., Aschwanden, A., Barthel, A., Calov, R., Chambers, C., Choi, Y., Cuzzone, J., Dumas, C., Edwards, T., Felikson, D., Fettweis, X., Golledge, N. R., Greve, R., Humbert, A., Huybrechts, P., Le clec'h, S., Lee, V., Leguy, G., Little, C., Lowry, D. P., Morlighem, M., Nias, I., Quiquet, A., Rückamp, M., Schlegel, N.-J., Slater, D. A., Smith, R. S., Straneo, F., Tarasov, L., van de Wal, R., and van den Broeke, M.: The future sea-level contribution of the Greenland ice sheet: a multi-model ensemble study of ISMIP6, The Cryosphere, 14, 3071–3096, https://doi.org/10.5194/tc-14-3071-2020, 2020. a, b, c, d, e, f, g
Goldberg, D. N., Heimbach, P., Joughin, I., and Smith, B.: Committed retreat of Smith, Pope, and Kohler Glaciers over the next 30 years inferred by transient model calibration, The Cryosphere, 9, 2429–2446, https://doi.org/10.5194/tc-9-2429-2015, 2015. a, b
Greve, R.: Application of a Polythermal Three-Dimensional Ice Sheet Model to the Greenland Ice Sheet: Response to Steady-State and Transient Climate Scenarios, J. Climate, 10, 901–918, https://doi.org/10.1175/1520-0442(1997)010<0901:AOAPTD>2.0.CO;2, 1997. a
Hallouin, T., Bruen, M., and O'Loughlin, F. E.: Calibration of hydrological models for ecologically relevant streamflow predictions: a trade-off between fitting well to data and estimating consistent parameter sets?, Hydrol. Earth Syst. Sci., 24, 1031–1054, https://doi.org/10.5194/hess-24-1031-2020, 2020. a
Haubner, K., Box, J. E., Schlegel, N. J., Larour, E. Y., Morlighem, M., Solgaard, A. M., Kjeldsen, K. K., Larsen, S. H., Rignot, E., Dupont, T. K., and Kjær, K. H.: Simulating ice thickness and velocity evolution of Upernavik Isstrøm 1849–2012 by forcing prescribed terminus positions in ISSM, The Cryosphere, 12, 1511–1522, https://doi.org/10.5194/tc-12-1511-2018, 2018. a
Hausfather, Z. and Moore, F. C.: Net-zero commitments could limit warming to below 2 °C, Nature, 604, 247–248, https://doi.org/10.1038/d41586-022-00874-1, 2022. a
Hausfather, Z. and Peters, G.: Emissions – the “business as usual” story is misleading, Nature, 577, 618–620, https://doi.org/10.1038/d41586-020-00177-3, 2020. a, b
Hawkins, E. and Sutton, R.: The Potential to Narrow Uncertainty in Regional Climate Predictions, B. Am. Meteorol. Soc., 90, 1095–1108, https://doi.org/10.1175/2009BAMS2607.1, 2009. a
Hersbach, H.: Decomposition of the Continuous Ranked Probability Score for Ensemble Prediction Systems, Weather Forecast., 15, 559–570, https://doi.org/10.1175/1520-0434(2000)015<0559:DOTCRP>2.0.CO;2, 2000. a
Hill, E. A., Rosier, S. H. R., Gudmundsson, G. H., and Collins, M.: Quantifying the potential future contribution to global mean sea level from the Filchner–Ronne basin, Antarctica, The Cryosphere, 15, 4675–4702, https://doi.org/10.5194/tc-15-4675-2021, 2021. a, b
Hill, E. A., Urruty, B., Reese, R., Garbe, J., Gagliardini, O., Durand, G., Gillet-Chaulet, F., Gudmundsson, G. H., Winkelmann, R., Chekki, M., Chandler, D., and Langebroek, P. M.: The stability of present-day Antarctic grounding lines – Part 1: No indication of marine ice sheet instability in the current geometry, The Cryosphere, 17, 3739–3759, https://doi.org/10.5194/tc-17-3739-2023, 2023. a
Intergovernmental Panel on Climate Change (IPCC): Summary for Policymakers, Cambridge University Press, Cambridge, UK and New York, NY, USA, https://doi.org/10.1017/9781009157926.001, 2022. a, b
Jager, E.: The future of Upernavik Isstrøm: Sensitivity analysis and Bayesian calibration of ensemble prediction, Zenodo [code and data set], https://doi.org/10.5281/zenodo.10794469, 2024. a
Jager, E., Gillet-Chaulet, F., Mouginot, J., and Millan, R.: Validating ensemble historical simulations of Upernavik Isstrøm (1985–2019) using observations of surface velocity and elevation, J. Glaciol., 1–18, https://doi.org/10.1017/jog.2024.10, online first, 2024. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q, r, s, t, u, v, w, x
Jiang, W. and Forssén, C.: Bayesian probability updates using sampling/importance resampling: Applications in nuclear theory, Front. Phys., 10, 1058809, https://doi.org/10.3389/fphy.2022.1058809, 2022. a
Joughin, I., Smith, B. E., and Schoof, C. G.: Regularized Coulomb Friction Laws for Ice Sheet Sliding: Application to Pine Island Glacier, Antarctica, Geophys. Res. Lett., 46, 4764–4771, https://doi.org/10.1029/2019GL082526, 2019. a, b, c, d
King, M. D., Howat, I. M., Jeong, S., Noh, M. J., Wouters, B., Noël, B., and van den Broeke, M. R.: Seasonal to decadal variability in ice discharge from the Greenland Ice Sheet, The Cryosphere, 12, 3813–3825, https://doi.org/10.5194/tc-12-3813-2018, 2018. a, b
Lamboni, M., Monod, H., and Makowski, D.: Multivariate sensitivity analysis to measure global contribution of input factors in dynamic models, Reliab. Eng. Syst. Safe., 96, 450–459, https://doi.org/10.1016/j.ress.2010.12.002, 2011. a
Leeuwen, P. J. V.: Nonlinear data assimilation in geosciences: An extremely efficient particle filter, Q. J. Roy. Meteor. Soc., 136, 1991–1999, https://doi.org/10.1002/qj.699, 2010. a
MacAyeal, D. R.: Large-scale ice flow over a viscous basal sediment: Theory and application to ice stream B, Antarctica, J. Geophys. Res.-Sol. Ea., 94, 4071–4087, https://doi.org/10.1029/JB094iB04p04071, 1989. a
Mankoff, K. D., Colgan, W., Solgaard, A., Karlsson, N. B., Ahlstrøm, A. P., van As, D., Box, J. E., Khan, S. A., Kjeldsen, K. K., Mouginot, J., and Fausto, R. S.: Greenland Ice Sheet solid ice discharge from 1986 through 2017, Earth Syst. Sci. Data, 11, 769–786, https://doi.org/10.5194/essd-11-769-2019, 2019. a, b, c, d
Marzeion, B., Hock, R., Anderson, B., Bliss, A., Champollion, N., Fujita, K., Huss, M., Immerzeel, W. W., Kraaijenbrink, P., Malles, J.-H., Maussion, F., Radić, V., Rounce, D. R., Sakai, A., Shannon, S., van de Wal, R., and Zekollari, H.: Partitioning the Uncertainty of Ensemble Projections of Global Glacier Mass Change, Earth's Future, 8, e2019EF001470, https://doi.org/10.1029/2019EF001470, 2020. a
Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J., Maycock, T., Waterfield, T., Yelekçi, O., Yu, R., and Zhou, B.: Summary for Policymakers, in: Climate Change 2021: The Physical Science Basis, Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, IPCC, edited by: Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekçi, O., Yu, R., and Zhou, B., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 3−-32, https://doi.org/10.1017/9781009157896.001, 2021. a, b
Matheson, J. and Winkler, R.: Scoring rules for continuous probability distributions, Management Science, 22, 1087–1095, 1976. a
McKay, D. I. A., Staal, A., Abrams, J. F., Winkelmann, R., Sakschewski, B., Loriani, S., Fetzer, I., Cornell, S. E., Rockström, J., and Lenton, T. M.: Exceeding 1.5°C global warming could trigger multiple climate tipping points, Science, 377, eabn7950, https://doi.org/10.1126/science.abn7950, 2022. a
McNeall, D. J., Challenor, P. G., Gattiker, J. R., and Stone, E. J.: The potential of an observational data set for calibration of a computationally expensive computer model, Geosci. Model Dev., 6, 1715–1728, https://doi.org/10.5194/gmd-6-1715-2013, 2013. a
Mouginot, J., Rignot, E., Bjørk, A. A., van den Broeke, M., Millan, R., Morlighem, M., Noël, B., Scheuchl, B., and Wood, M.: Forty-six years of Greenland Ice Sheet mass balance from 1972 to 2018, P. Natl. Acad. Sci. USA, 116, 9239–9244, https://doi.org/10.1073/pnas.1904242116, 2019. a, b, c, d, e, f, g
Nias, I. J., Cornford, S. L., Edwards, T. L., Gourmelen, N., and Payne, A. J.: Assessing Uncertainty in the Dynamical Ice Response to Ocean Warming in the Amundsen Sea Embayment, West Antarctica, Geophys. Res. Lett., 46, 11253–11260, https://doi.org/10.1029/2019GL084941, 2019. a, b
Nias, I. J., Nowicki, S., Felikson, D., and Loomis, B.: Modeling the Greenland Ice Sheet's Committed Contribution to Sea Level During the 21st Century, J. Geophys. Res.-Earth, 128, e2022JF006914, https://doi.org/10.1029/2022JF006914, 2023. a, b, c, d
Noël, B., van de Berg, W. J., Machguth, H., Lhermitte, S., Howat, I., Fettweis, X., and van den Broeke, M. R.: A daily, 1 km resolution data set of downscaled Greenland ice sheet surface mass balance (1958–2015), The Cryosphere, 10, 2361–2377, https://doi.org/10.5194/tc-10-2361-2016, 2016. a
Noël, B., van de Berg, W. J., van Wessem, J. M., van Meijgaard, E., van As, D., Lenaerts, J. T. M., Lhermitte, S., Kuipers Munneke, P., Smeets, C. J. P. P., van Ulft, L. H., van de Wal, R. S. W., and van den Broeke, M. R.: Modelling the climate and surface mass balance of polar ice sheets using RACMO2 – Part 1: Greenland (1958–2016), The Cryosphere, 12, 811–831, https://doi.org/10.5194/tc-12-811-2018, 2018. a, b
Nowicki, S., Goelzer, H., Seroussi, H., Payne, A. J., Lipscomb, W. H., Abe-Ouchi, A., Agosta, C., Alexander, P., Asay-Davis, X. S., Barthel, A., Bracegirdle, T. J., Cullather, R., Felikson, D., Fettweis, X., Gregory, J. M., Hattermann, T., Jourdain, N. C., Kuipers Munneke, P., Larour, E., Little, C. M., Morlighem, M., Nias, I., Shepherd, A., Simon, E., Slater, D., Smith, R. S., Straneo, F., Trusel, L. D., van den Broeke, M. R., and van de Wal, R.: Experimental protocol for sea level projections from ISMIP6 stand-alone ice sheet models, The Cryosphere, 14, 2331–2368, https://doi.org/10.5194/tc-14-2331-2020, 2020. a, b, c, d, e
Pielke Jr, R., Burgess, M. G., and Ritchie, J.: Plausible 2005–2050 emissions scenarios project between 2 °C and 3 °C of warming by 2100, Environ. Res. Lett., 17, 024027, https://doi.org/10.1088/1748-9326/ac4ebf, 2022. a
Pollard, D., Chang, W., Haran, M., Applegate, P., and DeConto, R.: Large ensemble modeling of the last deglacial retreat of the West Antarctic Ice Sheet: comparison of simple and advanced statistical techniques, Geosci. Model Dev., 9, 1697–1723, https://doi.org/10.5194/gmd-9-1697-2016, 2016. a, b, c
Raftery, A. E., Zimmer, A., Frierson, D. M. W., Startz, R., and Liu, P.: Less than 2 °C warming by 2100 unlikely, Nat. Clim. Change, 7, 637–641, https://doi.org/10.1038/nclimate3352, 2017. a, b
Reed, P. M., Hadjimichael, A., Malek, K., Karimi, T., Vernon, C. R., Srikrishnan, V., Gupta, R. S., Gold, D. F., Lee, B., Keller, K., Thurber, T. B., and Rice, J. S.: Addressing Uncertainty in Multisector Dynamics Research, Zenodo [code], https://doi.org/10.5281/zenodo.6110623, 2022. a, b
Ritz, C., Edwards, T. L., Durand, G., Payne, A. J., Peyaud, V., and Hindmarsh, R. C. A.: Potential sea-level rise from Antarctic ice-sheet instability constrained by observations, Nature, 528, 1–14, https://doi.org/10.1038/nature16147, 2015. a, b
Robel, A. A., Seroussi, H., and Roe, G. H.: Marine ice sheet instability amplifies and skews uncertainty in projections of future sea-level rise, P. Natl. Acad. Sci. USA, 116, 14887–14892, https://doi.org/10.1073/pnas.1904822116, 2019. a
Rohmer, J., Thieblemont, R., Le Cozannet, G., Goelzer, H., and Durand, G.: Improving interpretation of sea-level projections through a machine-learning-based local explanation approach, The Cryosphere, 16, 4637–4657, https://doi.org/10.5194/tc-16-4637-2022, 2022. a
Rounce, D. R., Hock, R., Maussion, F., Hugonnet, R., Kochtitzky, W., Huss, M., Berthier, E., Brinkerhoff, D., Compagno, L., Copland, L., Farinotti, D., Menounos, B., and McNabb, R. W.: Global glacier change in the 21st century: Every increase in temperature matters, Science, 379, 78–83, https://doi.org/10.1126/science.abo1324, 2023. a
Seroussi, H., Morlighem, M., Rignot, E., Khazendar, A., Larour, E., and Mouginot, J.: Dependence of century-scale projections of the Greenland ice sheet on its thermal regime, J. Glaciol., 59, 1024–1034, https://doi.org/10.3189/2013JoG13J054, 2013. a
Seroussi, H., Nowicki, S., Simon, E., Abe-Ouchi, A., Albrecht, T., Brondex, J., Cornford, S., Dumas, C., Gillet-Chaulet, F., Goelzer, H., Golledge, N. R., Gregory, J. M., Greve, R., Hoffman, M. J., Humbert, A., Huybrechts, P., Kleiner, T., Larour, E., Leguy, G., Lipscomb, W. H., Lowry, D., Mengel, M., Morlighem, M., Pattyn, F., Payne, A. J., Pollard, D., Price, S. F., Quiquet, A., Reerink, T. J., Reese, R., Rodehacke, C. B., Schlegel, N.-J., Shepherd, A., Sun, S., Sutter, J., Van Breedam, J., van de Wal, R. S. W., Winkelmann, R., and Zhang, T.: initMIP-Antarctica: an ice sheet model initialization experiment of ISMIP6, The Cryosphere, 13, 1441–1471, https://doi.org/10.5194/tc-13-1441-2019, 2019. a
Seroussi, H., Nowicki, S., Payne, A. J., Goelzer, H., Lipscomb, W. H., Abe-Ouchi, A., Agosta, C., Albrecht, T., Asay-Davis, X., Barthel, A., Calov, R., Cullather, R., Dumas, C., Galton-Fenzi, B. K., Gladstone, R., Golledge, N. R., Gregory, J. M., Greve, R., Hattermann, T., Hoffman, M. J., Humbert, A., Huybrechts, P., Jourdain, N. C., Kleiner, T., Larour, E., Leguy, G. R., Lowry, D. P., Little, C. M., Morlighem, M., Pattyn, F., Pelle, T., Price, S. F., Quiquet, A., Reese, R., Schlegel, N.-J., Shepherd, A., Simon, E., Smith, R. S., Straneo, F., Sun, S., Trusel, L. D., Van Breedam, J., van de Wal, R. S. W., Winkelmann, R., Zhao, C., Zhang, T., and Zwinger, T.: ISMIP6 Antarctica: a multi-model ensemble of the Antarctic ice sheet evolution over the 21st century, The Cryosphere, 14, 3033–3070, https://doi.org/10.5194/tc-14-3033-2020, 2020. a, b, c, d, e
Seroussi, H., Verjans, V., Nowicki, S., Payne, A. J., Goelzer, H., Lipscomb, W. H., Abe-Ouchi, A., Agosta, C., Albrecht, T., Asay-Davis, X., Barthel, A., Calov, R., Cullather, R., Dumas, C., Galton-Fenzi, B. K., Gladstone, R., Golledge, N. R., Gregory, J. M., Greve, R., Hattermann, T., Hoffman, M. J., Humbert, A., Huybrechts, P., Jourdain, N. C., Kleiner, T., Larour, E., Leguy, G. R., Lowry, D. P., Little, C. M., Morlighem, M., Pattyn, F., Pelle, T., Price, S. F., Quiquet, A., Reese, R., Schlegel, N.-J., Shepherd, A., Simon, E., Smith, R. S., Straneo, F., Sun, S., Trusel, L. D., Van Breedam, J., Van Katwyk, P., van de Wal, R. S. W., Winkelmann, R., Zhao, C., Zhang, T., and Zwinger, T.: Insights into the vulnerability of Antarctic glaciers from the ISMIP6 ice sheet model ensemble and associated uncertainty, The Cryosphere, 17, 5197–5217, https://doi.org/10.5194/tc-17-5197-2023, 2023. a
Slater, D. A., Straneo, F., Felikson, D., Little, C. M., Goelzer, H., Fettweis, X., and Holte, J.: Estimating Greenland tidewater glacier retreat driven by submarine melting, The Cryosphere, 13, 2489–2509, https://doi.org/10.5194/tc-13-2489-2019, 2019. a, b, c, d
Slater, D. A., Felikson, D., Straneo, F., Goelzer, H., Little, C. M., Morlighem, M., Fettweis, X., and Nowicki, S.: Twenty-first century ocean forcing of the Greenland ice sheet for modelling of sea level contribution , The Cryosphere, 14, 985–1008, https://doi.org/10.5194/tc-14-985-2020, 2020. a
Smith, A. F. M. and Gelfand, A. E.: Bayesian Statistics without Tears: A Sampling – Resampling Perspective, Am. Statist., 46, 84–88, https://doi.org/10.1080/00031305.1992.10475856, 1992. a
Sobol, I. M.: Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates, Math. Comput. Sim., 55, 271–280, https://doi.org/10.1016/S0378-4754(00)00270-6, 2001. a
Tollefson, J.: Top climate scientists are sceptical that nations will rein in global warming, Nature, 599, 22–24, https://doi.org/10.1038/d41586-021-02990-w, 2021. a
Unger, D.: A method to estimate the continuous ranked probability score, in: Preprints, Ninth Conf. on Probability and Statistics in Atmospheric Sciences, American Meteorological Society, Virginia Beach, VA, 206–213, 1985. a
Vernon, C. L., Bamber, J. L., Box, J. E., van den Broeke, M. R., Fettweis, X., Hanna, E., and Huybrechts, P.: Surface mass balance model intercomparison for the Greenland ice sheet, The Cryosphere, 7, 599–614, https://doi.org/10.5194/tc-7-599-2013, 2013. a
Weertman, J.: On the Sliding of Glaciers, J. Glaciol., 3, 33–38, https://doi.org/10.3189/S0022143000024709, 1957. a
Wernecke, A., Edwards, T. L., Nias, I. J., Holden, P. B., and Edwards, N. R.: Spatial probabilistic calibration of a high-resolution Amundsen Sea Embayment ice sheet model with satellite altimeter data, The Cryosphere, 14, 1459–1474, https://doi.org/10.5194/tc-14-1459-2020, 2020. a, b, c
Wood, M., Rignot, E., Fenty, I., An, L., Bjørk, A., van den Broeke, M., Cai, C., Kane, E., Menemenlis, D., Millan, R., Morlighem, M., Mouginot, J., Noël, B., Scheuchl, B., Velicogna, I., Willis, J. K., and Zhang, H.: Ocean forcing drives glacier retreat in Greenland, Sci. Adv., 7, eaba7282, https://doi.org/10.1126/sciadv.aba7282, 2021. a, b, c
Co-editor-in-chief
This work examines what determines the future of a glacier system in Greenland and represents an important advance in data-constrained forecasting for glacier systems. The manuscript investigates how sea-level rise predictions may be improved by leveraging a range of glaciological, climate, and modelling disciplines. Bringing together models and data, the authors demonstrate that human behaviour is the main determining factor of the glacier's future development.
This work examines what determines the future of a glacier system in Greenland and represents an...
Short summary
Inspired by a previous intercomparison framework, our study better constrains uncertainties in glacier evolution using an innovative method to validate Bayesian calibration. Upernavik Isstrøm, one of Greenland's largest glaciers, has lost significant mass since 1985. By integrating observational data, climate models, human emissions, and internal model parameters, we project its evolution until 2100. We show that future human emissions are the main source of uncertainty in 2100, making up half.
Inspired by a previous intercomparison framework, our study better constrains uncertainties in...