Articles | Volume 19, issue 5
https://doi.org/10.5194/tc-19-1775-2025
© Author(s) 2025. 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-19-1775-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
08 May 2025
Research article |
| 08 May 2025
| 08 May 2025
Disentangling the oceanic drivers behind the post-2000 retreat of Sermeq Kujalleq, Greenland (Jakobshavn Isbræ)
Ziad Rashed
CORRESPONDING AUTHOR
School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA, USA
Alexander A. Robel
School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA, USA
Hélène Seroussi
Thayer School of Engineering, Dartmouth College, Hanover, NH, USA
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Vincent Verjans, Alexander A. Robel, Lizz Ultee, Helene Seroussi, Andrew F. Thompson, Lars Ackermann, Youngmin Choi, and Uta Krebs-Kanzow
The Cryosphere, 19, 3749–3783, https://doi.org/10.5194/tc-19-3749-2025, https://doi.org/10.5194/tc-19-3749-2025, 2025
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This study examines how random variations in climate may influence future ice loss from the Greenland ice sheet. We find that random climate variations are important for predicting future ice loss from the entire Greenland ice sheet over the next 20–30 years but relatively unimportant after that period. Thus, uncertainty in sea level projections from the effect of climate variability on Greenland may play a role in coastal decision-making about sea level rise over the next few decades.
Madeline S. Mamer, Alexander A. Robel, Chris C. K. Lai, Earle Wilson, and Peter Washam
The Cryosphere, 19, 3227–3251, https://doi.org/10.5194/tc-19-3227-2025, https://doi.org/10.5194/tc-19-3227-2025, 2025
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In this work, we simulate estuary-like seawater intrusions into the subglacial hydrologic system for marine outlet glaciers. We find the largest controls on seawater intrusion are the subglacial space geometry and meltwater discharge velocity. Further, we highlight the importance of extending ocean-forced ice loss to grounded portions of the ice sheet, which is currently not represented in models coupling ice sheets to ocean dynamics.
Samuel T. Kodama, Tamara Pico, Alexander A. Robel, John Erich Christian, Natalya Gomez, Casey Vigilia, Evelyn Powell, Jessica Gagliardi, Slawek Tulaczyk, and Terrence Blackburn
The Cryosphere, 19, 2935–2948, https://doi.org/10.5194/tc-19-2935-2025, https://doi.org/10.5194/tc-19-2935-2025, 2025
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We predicted how sea level changed in the Ross Sea (Antarctica) due to glacial isostatic adjustment, or solid Earth ice sheet interactions, over the last deglaciation (20 000 years ago to present) and calculated how these changes in bathymetry impacted ice stream stability. Glacial isostatic adjustment shifts stability from where ice reached its maximum 20 000 years ago, at the continental shelf edge, to the modern grounding line today, reinforcing ice-age climate endmembers.
Shfaqat A. Khan, Helene Seroussi, Mathieu Morlighem, William Colgan, Veit Helm, Gong Cheng, Danjal Berg, Valentina R. Barletta, Nicolaj K. Larsen, William Kochtitzky, Michiel van den Broeke, Kurt H. Kjær, Andy Aschwanden, Brice Noël, Jason E. Box, Joseph A. MacGregor, Robert S. Fausto, Kenneth D. Mankoff, Ian M. Howat, Kuba Oniszk, Dominik Fahrner, Anja Løkkegaard, Eigil Y. H. Lippert, Alicia Bråtner, and Javed Hassan
Earth Syst. Sci. Data, 17, 3047–3071, https://doi.org/10.5194/essd-17-3047-2025, https://doi.org/10.5194/essd-17-3047-2025, 2025
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The surface elevation of the Greenland Ice Sheet is changing due to surface mass balance processes and ice dynamics, each exhibiting distinct spatiotemporal patterns. Here, we employ satellite and airborne altimetry data with fine spatial (1 km) and temporal (monthly) resolutions to document this spatiotemporal evolution from 2003 to 2023. This dataset of fine-resolution altimetry data in both space and time will support studies of ice mass loss and be useful for GIS ice sheet modeling.
Paul T. Summers, Rebecca H. Jackson, and Alexander A. Robel
EGUsphere, https://doi.org/10.5194/egusphere-2025-1555, https://doi.org/10.5194/egusphere-2025-1555, 2025
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We develop a method that allows numerical ocean models to include drag from icebergs, even for icebergs smaller than the model grid scale. This builds upon previous models that have either neglected iceberg drag, or required higher resolution to model individual icebergs. We test our model against higher resolution models, as well as models without iceberg drag, and show that including drag from icebergs is important for capturing realistic ocean circulation, temperature, and ice melt rates.
Meghana Ranganathan, Alexander A. Robel, Alexander Huth, and Ravindra Duddu
The Cryosphere, 19, 1599–1619, https://doi.org/10.5194/tc-19-1599-2025, https://doi.org/10.5194/tc-19-1599-2025, 2025
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The rate of ice loss from ice sheets is controlled by the flow of ice from the center of the ice sheet and by the internal fracturing of the ice. These processes are coupled; fractures reduce the viscosity of ice and enable more rapid flow, and rapid flow causes the fracturing of ice. We present a simplified way of representing damage that is applicable to long-timescale flow estimates. Using this model, we find that including fracturing in an ice sheet simulation can increase the loss of ice by 13–29 %.
Peter Van Katwyk, Baylor Fox-Kemper, Sophie Nowicki, Hélène Seroussi, and Karianne J. Bergen
EGUsphere, https://doi.org/10.5194/egusphere-2025-870, https://doi.org/10.5194/egusphere-2025-870, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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We present ISEFlow, a machine learning emulator that predicts how the melting of the Antarctic and Greenland ice sheets will contribute to sea level. ISEFlow is fast and accurate, allowing scientists to explore different climate scenarios with greater confidence. ISEFlow distinguishes between high and low emissions scenarios, helping us understand how today’s choices impact future sea levels. ISEFlow supports more reliable climate predictions and helps scientists study the future of ice sheets.
Benjamin Keith Galton-Fenzi, Richard Porter-Smith, Sue Cook, Eva Cougnon, David E. Gwyther, Wilma G. C. Huneke, Madelaine G. Rosevear, Xylar Asay-Davis, Fabio Boeira Dias, Michael S. Dinniman, David Holland, Kazuya Kusahara, Kaitlin A. Naughten, Keith W. Nicholls, Charles Pelletier, Ole Richter, Helene L. Seroussi, and Ralph Timmermann
EGUsphere, https://doi.org/10.5194/egusphere-2024-4047, https://doi.org/10.5194/egusphere-2024-4047, 2025
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Melting beneath Antarctica’s floating ice shelves is key to future sea-level rise. We compare several different ocean simulations with satellite measurements, and provide the first multi-model average estimate of melting and refreezing driven by both ocean temperature and currents beneath ice shelves. The multi-model average can provide a useful tool for better understanding the role of ice shelf melting in present-day and future ice-sheet changes and informing coastal adaptation efforts.
James F. O'Neill, Tamsin L. Edwards, Daniel F. Martin, Courtney Shafer, Stephen L. Cornford, Hélène L. Seroussi, Sophie Nowicki, Mira Adhikari, and Lauren J. Gregoire
The Cryosphere, 19, 541–563, https://doi.org/10.5194/tc-19-541-2025, https://doi.org/10.5194/tc-19-541-2025, 2025
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We use an ice sheet model to simulate the Antarctic contribution to sea level over the 21st century under a range of future climates and varying how sensitive the ice sheet is to different processes. We find that ocean temperatures increase and more snow falls on the ice sheet under stronger warming scenarios. When the ice sheet is sensitive to ocean warming, ocean melt-driven loss exceeds snowfall-driven gains, meaning that the sea level contribution is greater with more climate warming.
Luc Houriez, Eric Larour, Lambert Caron, Nicole-Jeanne Schlegel, Surendra Adhikari, Erik Ivins, Tyler Pelle, Hélène Seroussi, Eric Darve, and Martin Fischer
EGUsphere, https://doi.org/10.5194/egusphere-2024-4136, https://doi.org/10.5194/egusphere-2024-4136, 2025
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We studied how interactions between the ice sheet and the Earth’s evolving surface affect the future of Thwaites Glacier in Antarctica. We find that small features in the bedrock play a major role in these interactions which can delay the glacier’s retreat by decades or even centuries. This can significantly reduce sea-level rise projections. Our work highlights resolution requirements for similar ice—earth models, and the importance of bedrock mapping efforts in Antarctica.
Jason M. Amundson, Alexander A. Robel, Justin C. Burton, and Kavinda Nissanka
The Cryosphere, 19, 19–35, https://doi.org/10.5194/tc-19-19-2025, https://doi.org/10.5194/tc-19-19-2025, 2025
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Some fjords contain dense packs of icebergs referred to as ice mélange. Ice mélange can affect the stability of marine-terminating glaciers by resisting the calving of new icebergs and by modifying fjord currents and water properties. We have developed the first numerical model of ice mélange that captures its granular nature and that is suitable for long-timescale simulations. The model is capable of explaining why some glaciers are more strongly influenced by ice mélange than others.
Jan De Rydt, Nicolas C. Jourdain, Yoshihiro Nakayama, Mathias van Caspel, Ralph Timmermann, Pierre Mathiot, Xylar S. Asay-Davis, Hélène Seroussi, Pierre Dutrieux, Ben Galton-Fenzi, David Holland, and Ronja Reese
Geosci. Model Dev., 17, 7105–7139, https://doi.org/10.5194/gmd-17-7105-2024, https://doi.org/10.5194/gmd-17-7105-2024, 2024
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Global climate models do not reliably simulate sea-level change due to ice-sheet–ocean interactions. We propose a community modelling effort to conduct a series of well-defined experiments to compare models with observations and study how models respond to a range of perturbations in climate and ice-sheet geometry. The second Marine Ice Sheet–Ocean Model Intercomparison Project will continue to lay the groundwork for including ice-sheet–ocean interactions in global-scale IPCC-class models.
Alexander A. Robel, Vincent Verjans, and Aminat A. Ambelorun
The Cryosphere, 18, 2613–2623, https://doi.org/10.5194/tc-18-2613-2024, https://doi.org/10.5194/tc-18-2613-2024, 2024
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The average size of many glaciers and ice sheets changes when noise is added to the system. The reasons for this drift in glacier state is intrinsic to the dynamics of how ice flows and the bumpiness of the Earth's surface. We argue that not including noise in projections of ice sheet evolution over coming decades and centuries is a pervasive source of bias in these computer models, and so realistic variability in glacier and climate processes must be included in models.
Lizz Ultee, Alexander A. Robel, and Stefano Castruccio
Geosci. Model Dev., 17, 1041–1057, https://doi.org/10.5194/gmd-17-1041-2024, https://doi.org/10.5194/gmd-17-1041-2024, 2024
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The surface mass balance (SMB) of an ice sheet describes the net gain or loss of mass from ice sheets (such as those in Greenland and Antarctica) through interaction with the atmosphere. We developed a statistical method to generate a wide range of SMB fields that reflect the best understanding of SMB processes. Efficiently sampling the variability of SMB will help us understand sources of uncertainty in ice sheet model projections.
Youngmin Choi, Helene Seroussi, Mathieu Morlighem, Nicole-Jeanne Schlegel, and Alex Gardner
The Cryosphere, 17, 5499–5517, https://doi.org/10.5194/tc-17-5499-2023, https://doi.org/10.5194/tc-17-5499-2023, 2023
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Ice sheet models are often initialized using snapshot observations of present-day conditions, but this approach has limitations in capturing the transient evolution of the system. To more accurately represent the accelerating changes in glaciers, we employed time-dependent data assimilation. We found that models calibrated with the transient data better capture past trends and more accurately reproduce changes after the calibration period, even with limited observations.
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.
Vincent Verjans, Alexander A. Robel, Helene Seroussi, Lizz Ultee, and Andrew F. Thompson
Geosci. Model Dev., 15, 8269–8293, https://doi.org/10.5194/gmd-15-8269-2022, https://doi.org/10.5194/gmd-15-8269-2022, 2022
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We describe the development of the first large-scale ice sheet model that accounts for stochasticity in a range of processes. Stochasticity allows the impacts of inherently uncertain processes on ice sheets to be represented. This includes climatic uncertainty, as the climate is inherently chaotic. Furthermore, stochastic capabilities also encompass poorly constrained glaciological processes that display strong variability at fine spatiotemporal scales. We present the model and test experiments.
John Erich Christian, Alexander A. Robel, and Ginny Catania
The Cryosphere, 16, 2725–2743, https://doi.org/10.5194/tc-16-2725-2022, https://doi.org/10.5194/tc-16-2725-2022, 2022
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Marine-terminating glaciers have recently retreated dramatically, but the role of anthropogenic forcing remains uncertain. We use idealized model simulations to develop a framework for assessing the probability of rapid retreat in the context of natural climate variability. Our analyses show that century-scale anthropogenic trends can substantially increase the probability of retreats. This provides a roadmap for future work to formally assess the role of human activity in recent glacier change.
Alexander A. Robel, Earle Wilson, and Helene Seroussi
The Cryosphere, 16, 451–469, https://doi.org/10.5194/tc-16-451-2022, https://doi.org/10.5194/tc-16-451-2022, 2022
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Warm seawater may intrude as a thin layer below glaciers in contact with the ocean. Mathematical theory predicts that this intrusion may extend over distances of kilometers under realistic conditions. Computer models demonstrate that if this warm seawater causes melting of a glacier bottom, it can cause rates of glacier ice loss and sea level rise to be up to 2 times faster in response to potential future ocean warming.
Thiago Dias dos Santos, Mathieu Morlighem, and Hélène Seroussi
Geosci. Model Dev., 14, 2545–2573, https://doi.org/10.5194/gmd-14-2545-2021, https://doi.org/10.5194/gmd-14-2545-2021, 2021
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Numerical models are routinely used to understand the past and future behavior of ice sheets in response to climate evolution. As is always the case with numerical modeling, one needs to minimize biases and numerical artifacts due to the choice of numerical scheme employed in such models. Here, we assess different numerical schemes in time-dependent simulations of ice sheets. We also introduce a new parameterization for the driving stress, the force that drives the ice sheet flow.
William H. Lipscomb, Gunter R. Leguy, Nicolas C. Jourdain, Xylar Asay-Davis, Hélène Seroussi, and Sophie Nowicki
The Cryosphere, 15, 633–661, https://doi.org/10.5194/tc-15-633-2021, https://doi.org/10.5194/tc-15-633-2021, 2021
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This paper describes Antarctic climate change experiments in which the Community Ice Sheet Model is forced with ocean warming predicted by global climate models. Generally, ice loss begins slowly, accelerates by 2100, and then continues unabated, with widespread retreat of the West Antarctic Ice Sheet. The mass loss by 2500 varies from about 150 to 1300 mm of equivalent sea level rise, based on the predicted ocean warming and assumptions about how this warming drives melting beneath ice shelves.
Martin Rückamp, Angelika Humbert, Thomas Kleiner, Mathieu Morlighem, and Helene Seroussi
Geosci. Model Dev., 13, 4491–4501, https://doi.org/10.5194/gmd-13-4491-2020, https://doi.org/10.5194/gmd-13-4491-2020, 2020
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We present enthalpy formulations within the Ice-Sheet and Sea-Level System model that show better performance than earlier implementations. A first experiment indicates that the treatment of discontinuous conductivities of the solid–fluid system with a geometric mean produce accurate results when applied to coarse vertical resolutions. In a second experiment, we propose a novel stabilization formulation that avoids the problem of thin elements. This method provides accurate and stable results.
Cited articles
Amaral, T., Bartholomaus, T. C., and Enderlin, E. M.: Evaluation of iceberg calving models against observations from Greenland outlet glaciers, J. Geophys. Res.-Earth Surf., 125, e2019JF005444, https://doi.org/10.1029/2019JF005444, 2020. a, b
Amundson, J. M. and Burton, J.: Quasi-static granular flow of ice mélange, J. Geophys. Res.-Earth Surf., 123, 2243–2257, 2018. a
Amundson, J. M., Fahnestock, M., Truffer, M., Brown, J., Lüthi, M. P., and Motyka, R. J.: Ice mélange dynamics and implications for terminus stability, Jakobshavn Isbræ, Greenland, J. Geophys. Res.-Earth Surf., 115, F01005, https://doi.org/10.1029/2009JF001405, 2010. a
Amundson, J. M., Robel, A. A., Burton, J. C., and Nissanka, K.: A quasi-one-dimensional ice mélange flow model based on continuum descriptions of granular materials, The Cryosphere, 19, 19–35, https://doi.org/10.5194/tc-19-19-2025, 2025. a
Benn, D. I., Warren, C. R., and Mottram, R. H.: Calving processes and the dynamics of calving glaciers, Earth-Sci. Rev., 82, 143–179, https://doi.org/10.1016/j.earscirev.2007.02.002, 2007. a
Benn, D. I., Cowton, T., Todd, J., and Luckman, A.: Glacier Calving in Greenland, Curr. Clim. Change Rep., 3, 282–290, https://doi.org/10.1007/s40641-017-0070-1, 2017. a
Bevan, S. L., Luckman, A. J., Benn, D. I., Cowton, T., and Todd, J.: Impact of warming shelf waters on ice mélange and terminus retreat at a large SE Greenland glacier, The Cryosphere, 13, 2303–2315, https://doi.org/10.5194/tc-13-2303-2019, 2019. a
Bondzio, J. H., Seroussi, H., Morlighem, M., Kleiner, T., Rückamp, M., Humbert, A., and Larour, E. Y.: Modelling calving front dynamics using a level-set method: application to Jakobshavn Isbræ, West Greenland, The Cryosphere, 10, 497–510, https://doi.org/10.5194/tc-10-497-2016, 2016. a
Bondzio, J. H., Morlighem, M., Seroussi, H., Kleiner, T., Rückamp, M., Mouginot, J., Moon, T., Larour, E. Y., and Humbert, A.: The mechanisms behind Jakobshavn Isbræ's acceleration and mass loss: A 3-D thermomechanical model study, Geophys. Res. Lett., 44, 6252–6260, https://doi.org/10.1002/2017GL073309, 2017. a, b
Budd, W. F., Jenssen, D., and Smith, I. N.: A Three-Dimensional Time-Dependent Model of the West Antarctic Ice Sheet, Ann. Glaciol., 5, 29–36, https://doi.org/10.3189/1984AoG5-1-29-36, 1984. a, b
Burton, J. C., Amundson, J. M., Cassotto, R., Kuo, C.-C., and Dennin, M.: Quantifying flow and stress in ice mélange, the world’s largest granular material, P. Natl. Acad. Sci. USA, 115, 5105–5110, 2018. a
Cassotto, R., Fahnestock, M., Amundson, J. M., Truffer, M., and Joughin, I.: Seasonal and interannual variations in ice melange and its impact on terminus stability, Jakobshavn Isbræ, Greenland, J. Glaciol., 61, 76–88, https://doi.org/10.3189/2015JoG13J235, 2015. a, b, c
Choi, Y., Morlighem, M., Wood, M., and Bondzio, J. H.: Comparison of four calving laws to model Greenland outlet glaciers, The Cryosphere, 12, 3735–3746, https://doi.org/10.5194/tc-12-3735-2018, 2018. a
Echelmeyer, K. and Harrison, W. D.: Jakobshavns Isbræ, West Greenland: Seasonal Variations in Velocity – or Lack Thereof, J. Glaciol., 36, 82–88, https://doi.org/10.3189/S0022143000005591, Cambridge University Press, 1990. a, b
Ettema, J., van den Broeke, M. R., van Meijgaard, E., van de Berg, W. J., Bamber, J. L., Box, J. E., and Bales, R. C.: Higher surface mass balance of the Greenland ice sheet revealed by high-resolution climate modeling, Geophys. Res. Lett., 36, L12501, https://doi.org/10.1029/2009GL038110, 2009. a
Gladish, C. V., Holland, D. M., and Lee, C. M.: Oceanic Boundary Conditions for Jakobshavn Glacier. Part II: Provenance and Sources of Variability of Disko Bay and Ilulissat Icefjord Waters, 1990–2011, J. Phys. Oceanogr., 45, 33–63, https://doi.org/10.1175/JPO-D-14-0045.1, 2015. a, b
Hanna, E., Huybrechts, P., Cappelen, J., Steffen, K., Bales, R. C., Burgess, E., McConnell, J. R., Peder Steffensen, J., Van den Broeke, M., Wake, L., Bigg, G., Griffiths, M., and Savas, D.: Greenland Ice Sheet surface mass balance 1870 to 2010 based on Twentieth Century Reanalysis, and links with global climate forcing, J. Geophys. Res.-Atmos., 116, D24121, https://doi.org/10.1029/2011JD016387, 2011. a
Holland, D. M. and Jenkins, A.: Modeling Thermodynamic Ice–Ocean Interactions at the Base of an Ice Shelf, J. Phys. Oceanogr., 29, 1787–1800, https://doi.org/10.1175/1520-0485(1999)029<1787:MTIOIA>2.0.CO;2, 1999. a
Holland, D. M., Thomas, R. H., de Young, B., Ribergaard, M. H., and Lyberth, B.: Acceleration of Jakobshavn Isbræ triggered by warm subsurface ocean waters, Nat. Geosci., 1, 659–664, https://doi.org/10.1038/ngeo316, 2008. a, b, c
Joughin, I., Smith, B., Howat, I., and Scambos, T.: MEaSUREs Greenland Ice Sheet Velocity Map from InSAR Data, (NSIDC-0478, Version 2), Boulder, Colorado USA, NASA National Snow and Ice Data Center Distributed Active Archive Center [data set], https://doi.org/10.5067/OC7B04ZM9G6Q, 2015. a
Joughin, I., Abdalati, W., and Fahnestock, M.: Large fluctuations in speed on Greenland's Jakobshavn Isbræ glacier, Nature, 432, 608–610, https://doi.org/10.1038/nature03130, 2004. a, b
Joughin, I., Howat, I., Alley, R. B., Ekstrom, G., Fahnestock, M., Moon, T., Nettles, M., Truffer, M., and Tsai, V. C.: Ice-front variation and tidewater behavior on Helheim and Kangerdlugssuaq Glaciers, Greenland, J. Geophys. Res.-Earth Surf., 113, F01004, https://doi.org/10.1029/2007JF000837, 2008. a
Joughin, I., Smith, B. E., and Medley, B.: Marine Ice Sheet Collapse Potentially Under Way for the Thwaites Glacier Basin, West Antarctica, Science, 344, 735–738, https://doi.org/10.1126/science.1249055, 2014. a
Joughin, I., Shean, D. E., Smith, B. E., and Floricioiu, D.: A decade of variability on Jakobshavn Isbræ: ocean temperatures pace speed through influence on mélange rigidity , The Cryosphere, 14, 211–227, https://doi.org/10.5194/tc-14-211-2020, 2020. a, b, c
Kajanto, K., Seroussi, H., de Fleurian, B., and Nisancioglu, K. H.: Present day Jakobshavn Isbræ (West Greenland) close to the Holocene minimum extent, Quaternary Sci. Rev., 246, 106492, https://doi.org/10.1016/j.quascirev.2020.106492, 2020. a
Kajanto, K., Straneo, F., and Nisancioglu, K.: Impact of icebergs on the seasonal submarine melt of Sermeq Kujalleq, The Cryosphere, 17, 371–390, https://doi.org/10.5194/tc-17-371-2023, 2023. a
Kehrl, L. M., Joughin, I., Shean, D. E., Floricioiu, D., and Krieger, L.: Seasonal and interannual variabilities in terminus position, glacier velocity, and surface elevation at Helheim and Kangerlussuaq Glaciers from 2008 to 2016, J. Geophys. Res.-Earth Surf., 122, 1635–1652, https://doi.org/10.1002/2016JF004133, 2017. a
Khazendar, A., Fenty, I. G., Carroll, D., Gardner, A., Lee, C. M., Fukumori, I., Wang, O., Zhang, H., Seroussi, H., Moller, D., Noël, B. P. Y., van den Broeke, M. R., Dinardo, S., and Willis, J.: Interruption of two decades of Jakobshavn Isbrae acceleration and thinning as regional ocean cools, Nat. Geosci., 12, 277–283, https://doi.org/10.1038/s41561-019-0329-3, 2019. a, b
Kim, J. H., Rignot, E., Holland, D., and Holland, D.: Seawater Intrusion at the Grounding Line of Jakobshavn Isbræ, Greenland, From Terrestrial Radar Interferometry, Geophys. Res. Lett., 51, e2023GL106181, https://doi.org/10.1029/2023GL106181, 2024. a
Korsgaard, N. J., Nuth, C., Khan, S. A., Kjeldsen, K. K., Bjørk, A. A., Schomacker, A., and Kjær, K. H.: Digital elevation model and orthophotographs of Greenland based on aerial photographs from 1978–1987, Sci. Data, 3, 160032, https://doi.org/10.1038/sdata.2016.32, 2016. a
Larour, E., Seroussi, H., Morlighem, M., and Rignot, E.: Continental scale, high order, high spatial resolution, ice sheet modeling using the Ice Sheet System Model (ISSM), J. Geophys. Res.-Earth Surf., 117, F01022, https://doi.org/10.1029/2011JF002140, 2012. a, b
Lee, R. W. and Schulson, E. M.: The Strength and Ductility of Ice Under Tension, J. Offshore Mech. Arct., 110, 187–191, https://doi.org/10.1115/1.3257049, 1988. a
Luckman, A., Benn, D. I., Cottier, F., Bevan, S., Nilsen, F., and Inall, M.: Calving rates at tidewater glaciers vary strongly with ocean temperature, Nat. Commun., 6, 8566, https://doi.org/10.1038/ncomms9566, 2015. a
MacAyeal, D. R.: Large-scale ice flow over a viscous basal sediment: Theory and application to ice stream B, Antarctica, J. Geophys. Res.-Solid Earth, 94, 4071–4087, https://doi.org/10.1029/JB094iB04p04071, 1989. a
Moon, T., Joughin, I., Smith, B., van den Broeke, M. R., van de Berg, W. J., Noël, B., and Usher, M.: Distinct patterns of seasonal Greenland glacier velocity, Geophys. Res. Lett., 41, 7209–7216, https://doi.org/10.1002/2014GL061836, 2014. a
Morland, L. W. and Zainuddin, R.: Plane and Radial Ice-Shelf Flow with Prescribed Temperature Profile, in: Dynamics of the West Antarctic Ice Sheet, edited by: Van der Veen, C. J. and Oerlemans, J., Glaciology and Quaternary Geology, 117–140 pp., Springer Netherlands, Dordrecht, https://doi.org/10.1007/978-94-009-3745-1_7, 1987. a
Morlighem, M., Rignot, E., Seroussi, H., Larour, E., Ben Dhia, H., and Aubry, D.: Spatial patterns of basal drag inferred using control methods from a full-Stokes and simpler models for Pine Island Glacier, West Antarctica, Geophys. Res. Lett., 37, L14502, https://doi.org/10.1029/2010GL043853, 2010. a
Morlighem, M., Bondzio, J., Seroussi, H., Rignot, E., Larour, E., Humbert, A., and Rebuffi, S.: Modeling of Store Gletscher's calving dynamics, West Greenland, in response to ocean thermal forcing, Geophys. Res. Lett., 43, 2659–2666, 2016. 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
Motyka, R. J., Truffer, M., Fahnestock, M., Mortensen, J., Rysgaard, S., and Howat, I.: Submarine melting of the 1985 Jakobshavn Isbræ floating tongue and the triggering of the current retreat, J. Geophys. Res.-Earth Surf., 116, https://doi.org/10.1029/2009JF001632, 2011. 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., 116, 9239–9244, https://doi.org/10.1073/pnas.1904242116, 2019. a, b
Myers, P. G. and Ribergaard, M. H.: Warming of the Polar Water Layer in Disko Bay and Potential Impact on Jakobshavn Isbrae, J. Phys. Oceanogr., 43, 2629–2640, https://doi.org/10.1175/JPO-D-12-051.1, 2013. a
Noël, B., van de Berg, W. J., van Meijgaard, E., Kuipers Munneke, P., van de Wal, R. S. W., and van den Broeke, M. R.: Evaluation of the updated regional climate model RACMO2.3: summer snowfall impact on the Greenland Ice Sheet, The Cryosphere, 9, 1831–1844, https://doi.org/10.5194/tc-9-1831-2015, 2015. a
Parsons, R., Sun, S., Gudmundsson, G. H., Wuite, J., and Nagler, T.: Quantifying the buttressing contribution of landfast sea ice and melange to Crane Glacier, Antarctic Peninsula, The Cryosphere, 18, 5789–5801, https://doi.org/10.5194/tc-18-5789-2024, 2024. a
Petrovic, J. J.: Review Mechanical properties of ice and snow, J. Mater. Sci., 38, 1–6, https://doi.org/10.1023/A:1021134128038, 2003. a
Pollard, D., DeConto, R. M., and Alley, R. B.: A continuum model (PSUMEL1) of ice mélange and its role during retreat of the Antarctic Ice Sheet, Geosci. Model Dev., 11, 5149–5172, https://doi.org/10.5194/gmd-11-5149-2018, 2018. a
Rashed, Z.: Run and analysis scripts for (Disentangling the drivers behind the post-2000 retreat of Sermeq Kujalleq, Greenland (Jakobshavn Isbrae)), Zenodo [data set], https://doi.org/10.5281/zenodo.11176342, 2024. a
Rignot, E., Xu, Y., Menemenlis, D., Mouginot, J., Scheuchl, B., Li, X., Morlighem, M., Seroussi, H., den Broeke, M. v., Fenty, I., Cai, C., An, L., and Fleurian, B. D.: Modeling of ocean-induced ice melt rates of five west Greenland glaciers over the past two decades, Geophys. Res. Lett., 43, 6374–6382, https://doi.org/10.1002/2016GL068784, 2016. a, b, c, d, e, f
Robel, A. A.: Thinning sea ice weakens buttressing force of iceberg mélange and promotes calving, Nat. Commun., 8, 14596, https://doi.org/10.1038/ncomms14596, 2017. a
Schlemm, T. and Levermann, A.: A simple parametrization of mélange buttressing for calving glaciers, The Cryosphere, 15, 531–545, https://doi.org/10.5194/tc-15-531-2021, 2021. a, b
Schweinsberg, A. D., Briner, J. P., Miller, G. H., Bennike, O., and Thomas, E. K.: Local glaciation in West Greenland linked to North Atlantic Ocean circulation during the Holocene, Geology, 45, 195–198, https://doi.org/10.1130/G38114.1, 2017. 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., Morlighem, M., Larour, E., Rignot, E., and Khazendar, A.: Hydrostatic grounding line parameterization in ice sheet models, The Cryosphere, 8, 2075–2087, https://doi.org/10.5194/tc-8-2075-2014, 2014. a
Slater, D. A., Straneo, F., Das, S. B., Richards, C. G., Wagner, T. J. W., and Nienow, P. W.: Localized Plumes Drive Front-Wide Ocean Melting of A Greenlandic Tidewater Glacier, Geophys. Res. Lett., 45, 12350–12358, https://doi.org/10.1029/2018GL080763, 2018. a
Slater, D. A., Benn, D. I., Cowton, T. R., Bassis, J. N., and Todd, J. A.: Calving Multiplier Effect Controlled by Melt Undercut Geometry, J. Geophys. Res.-Earth Surf., 126, e2021JF006191, https://doi.org/10.1029/2021JF006191, 2021. a
Smith, B., Fricker, H. A., Gardner, A. S., Medley, B., Nilsson, J., Paolo, F. S., Holschuh, N., Adusumilli, S., Brunt, K., Csatho, B., Harbeck, K., Markus, T., Neumann, T., Siegfried, M. R., and Zwally, H. J.: Pervasive ice sheet mass loss reflects competing ocean and atmosphere processes, Science, 368, 1239–1242, https://doi.org/10.1126/science.aaz5845, 2020. a, b
Vaňková, I. and Holland, D. M.: A model of icebergs and sea ice in a joint continuum framework, J. Geophys. Res.-Oceans, 122, 9110–9125, 2017. a
Vaughan, D. G.: Relating the occurrence of crevasses to surface strain rates, J. Glaciol., 39, 255–266, 1993. a
Wang, K., Cheng, X., Chen, Z., Hui, F., Liu, Y., and Tian, Y.: Ocean contributes to the melting of the Jakobshavn Glacier front, Sci. China Earth Sci., 63, 405–411, https://doi.org/10.1007/s11430-019-9394-6, 2020. a
Wehrlé, A., Lüthi, M. P., and Vieli, A.: The control of short-term ice mélange weakening episodes on calving activity at major Greenland outlet glaciers, The Cryosphere, 17, 309–326, https://doi.org/10.5194/tc-17-309-2023, 2023. a
Wheel, I., Benn, D. I., Crawford, A. J., Todd, J., and Zwinger, T.: A new 3D full-Stokes calving algorithm within Elmer/Ice (v9.0), Geosci. Model Dev., 17, 5759–5777, https://doi.org/10.5194/gmd-17-5759-2024, 2024. a
Xie, S., Dixon, T. H., Holland, D. M., Voytenko, D., and Vaňková, I.: Rapid iceberg calving following removal of tightly packed pro-glacial mélange, Nat. Commun., 10, 3250, https://doi.org/10.1038/s41467-019-10908-4, 2019. a, b
Xu, Y., Rignot, E., Fenty, I., Menemenlis, D., and Flexas, M. M.: Subaqueous melting of Store Glacier, west Greenland from three-dimensional, high-resolution numerical modeling and ocean observations, Geophys. Res. Lett., 40, 4648–4653, https://doi.org/10.1002/grl.50825, 2013. a
Short summary
Sermeq Kujalleq, Greenland's largest glacier, has significantly retreated since the late 1990s in response to warming ocean temperatures. Using a large-ensemble approach, our simulations show that the retreat is mainly initiated by the arrival of warm water but sustained and accelerated by the glacier's position over deeper bed troughs and vigorous calving. We highlight the need for models of ice mélange to project glacier behavior under rapid calving regimes.
Sermeq Kujalleq, Greenland's largest glacier, has significantly retreated since the late 1990s...
