Articles | Volume 19, issue 1
https://doi.org/10.5194/tc-19-107-2025
© 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-19-107-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
10 Jan 2025
Research article |
| 10 Jan 2025
| 10 Jan 2025
Modelling GNSS-observed seasonal velocity changes of the Ross Ice Shelf, Antarctica, using the Ice-sheet and Sea-level System Model (ISSM)
Francesca Baldacchino
CORRESPONDING AUTHOR
Te Puna Pātiotio, Antarctic Research Centre, Te Herenga-Waka, Victoria University of Wellington, Aotearoa, New Zealand
Institute of Geodesy, Graz University of Technology, Graz, Austria
Nicholas R. Golledge
Te Puna Pātiotio, Antarctic Research Centre, Te Herenga-Waka, Victoria University of Wellington, Aotearoa, New Zealand
Mathieu Morlighem
Department of Earth Sciences, Dartmouth College, Hanover, NH 03755, USA
Huw Horgan
Te Puna Pātiotio, Antarctic Research Centre, Te Herenga-Waka, Victoria University of Wellington, Aotearoa, New Zealand
Laboratory of Hydraulics, Hydrology and Glaciology (VAW), ETH Zurich, Zurich, Switzerland
Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), Birmensdorf, Switzerland
Alanna V. Alevropoulos-Borrill
Te Puna Pātiotio, Antarctic Research Centre, Te Herenga-Waka, Victoria University of Wellington, Aotearoa, New Zealand
Alena Malyarenko
School of Earth and Environment, Te Kura Aronukurangi, University of Canterbury, Te Whare Wānanga o Waitaha, Ōtautahi, Christchurch, New Zealand
Te Puna Pātiotio, Antarctic Research Centre, Te Herenga-Waka, Victoria University of Wellington, Aotearoa, New Zealand
Alexandra Gossart
Te Puna Pātiotio, Antarctic Research Centre, Te Herenga-Waka, Victoria University of Wellington, Aotearoa, New Zealand
Daniel P. Lowry
Department of Surface Geosciences, GNS Science, Lower Hutt, New Zealand
Laurine van Haastrecht
Te Puna Pātiotio, Antarctic Research Centre, Te Herenga-Waka, Victoria University of Wellington, Aotearoa, New Zealand
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Johanna Beckmann, Ronja Reese, Felicity S. McCormack, Sue Cook, Lawrence Bird, Dawid Gwyther, Daniel Richards, Matthias Scheiter, Yu Wang, Hélène Seroussi, Ayako Abe‐Ouchi, Torsten Albrecht, Jorge Alvarez‐Solas, Xylar S. Asay‐Davis, Jean‐Baptiste Barre, Constantijn J. Berends, Jorge Bernales, Javier Blasco, Justine Caillet, David M. Chandler, Violaine Coulon, Richard Cullather, Christophe Dumas, Benjamin K. Galton‐Fenzi, Julius Garbe, Fabien Gillet‐Chaulet, Rupert Gladstone, Heiko Goelzer, Nicholas R. Golledge, Ralf Greve, G. Hilmar Gudmundsson, Holly Kyeore Han, Trevor R. Hillebrand, Matthew J. Hoffman, Philippe Huybrechts, Nicolas C. Jourdain, Ann Kristin Klose, Petra M. Langebroek, Gunter R. Leguy, William H. Lipscomb, Daniel P. Lowry, Pierre Mathiot, Marisa Montoya, Mathieu Morlighem, Sophie Nowicki, Frank Pattyn, Antony J. Payne, Tyler Pelle, Aurélien Quiquet, Alexander Robinson, Leopekka Saraste, Erika G. Simon, Sainan Sun, Jake P. Twarog, Luke D. Trusel, Benoit Urruty, Jonas Van Breedam, Roderik S. W. van de Wal, Chen Zhao, and Thomas Zwinger
EGUsphere, https://doi.org/10.5194/egusphere-2025-4069, https://doi.org/10.5194/egusphere-2025-4069, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
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Antarctica holds enough ice to raise sea levels by many meters, but its future is uncertain. Warm ocean water melts ice shelves from below, letting inland ice flow faster into the sea. By 2300, Antarctica could add 0.6–4.4 m to sea levels. Our study identifies two key factors—how strongly shelves melt and how the ice responds. These explain much of the range, and refining them in models may improve future predictions.
Mansa Krishna, Gong Cheng, and Mathieu Morlighem
EGUsphere, https://doi.org/10.5194/egusphere-2025-3964, https://doi.org/10.5194/egusphere-2025-3964, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
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Estimates of the Greenland Ice Sheet’s contribution to sea level rise are affected by uncertainties in the bed topography. Traditional, physics-based methods for inferring the bed elevation are limited to fast-flowing areas of the ice sheet. We use machine learning models informed with two physical laws to infer the bed elevation for different regions in Greenland, showing that this method can be used to infer the bed elevation in slower-moving, sparsely surveyed regions of the ice sheet.
Vincent Charnay, Daniel P. Lowry, Elizabeth D. Keller, and Abha Sood
Clim. Past, 21, 1611–1631, https://doi.org/10.5194/cp-21-1611-2025, https://doi.org/10.5194/cp-21-1611-2025, 2025
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Our study evaluates models' ability to simulate Antarctic regional climate features by comparing available Paleoclimate Modelling Intercomparison Project models to sets of Last Millennium Antarctic proxy-based reconstructions most relevant to the surface mass balance. We later look at their implications for 21st-century sea level rise. The best-scoring model predicts a higher surface mass balance by 2100, which implies stronger mitigation of the ice sheet contribution to sea level rise.
Jamie Barnett, Felicity A. Holmes, Joshua Cuzzone, Henning Åkesson, Mathieu Morlighem, Matt O'Regan, Johan Nilsson, Nina Kirchner, and Martin Jakobsson
The Cryosphere, 19, 3631–3653, https://doi.org/10.5194/tc-19-3631-2025, https://doi.org/10.5194/tc-19-3631-2025, 2025
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Understanding how ice sheets have changed in the past can allow us to make better predictions for the future. By running a state-of-the-art model of Ryder Glacier, North Greenland, over the past 12 000 years we find that both a warming atmosphere and the ocean play a key role in the evolution of the glacier. Our conclusions stress that accurately quantifying the ice sheet’s interactions with the ocean is required to predict future changes and reliable sea level rise estimates.
Gong Cheng, Mansa Krishna, and Mathieu Morlighem
Geosci. Model Dev., 18, 5311–5327, https://doi.org/10.5194/gmd-18-5311-2025, https://doi.org/10.5194/gmd-18-5311-2025, 2025
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Predicting ice sheet contributions to sea level rise is challenging due to limited data and uncertainties in key processes. Traditional models require complex methods that lack flexibility. We developed PINNICLE (Physics-Informed Neural Networks for Ice and CLimatE), an open-source Python library that integrates machine learning with physical laws to improve ice sheet modeling. By combining data and physics, PINNICLE enhances predictions and adaptability, providing a powerful tool for climate research and sea level rise projections.
Felicity A. Holmes, Jamie Barnett, Henning Åkesson, Mathieu Morlighem, Johan Nilsson, Nina Kirchner, and Martin Jakobsson
The Cryosphere, 19, 2695–2714, https://doi.org/10.5194/tc-19-2695-2025, https://doi.org/10.5194/tc-19-2695-2025, 2025
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Northern Greenland contains some of the ice sheet's last remaining glaciers with floating ice tongues. One of these is Ryder Glacier, which has been relatively stable in recent decades, in contrast to nearby glaciers. Here, we use a computer model to simulate Ryder Glacier until 2300 under both a low- and a high-emissions scenario. Very high levels of surface melt under a high-emissions future lead to a sea level rise contribution that is an order of magnitude higher than under a low-emissions future.
Daniel Abele, Thomas Kleiner, Yannic Fischler, Benjamin Uekermann, Gerasimos Chourdakis, Mathieu Morlighem, Achim Basermann, Christian Bischof, Hans-Joachim Bungartz, and Angelika Humbert
EGUsphere, https://doi.org/10.5194/egusphere-2025-3345, https://doi.org/10.5194/egusphere-2025-3345, 2025
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For accurate projections of the evolution of continental ice sheets in Greenland and Antartica, interactions between the ice and its environment must be included in simulations. For this purpose, we have implemented adapters for the ice sheet model ISSM and subglacial hydrology model CUAS-MPI for the coupling library preCICE. This simplifies the study of earth systems by allowing the models to interact with each other as well as with models of the oceans or atmosphere with very little effort.
Younghyun Koo, Gong Cheng, Mathieu Morlighem, and Maryam Rahnemoonfar
The Cryosphere, 19, 2583–2599, https://doi.org/10.5194/tc-19-2583-2025, https://doi.org/10.5194/tc-19-2583-2025, 2025
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Calving, the breaking of ice bodies from the terminus of a glacier, plays an important role in the mass losses of Greenland ice sheets. However, calving parameters have been poorly understood because of the intensive computational demands of traditional numerical models. To address this issue and find the optimal calving parameter that best represents real observations, we develop deep-learning emulators based on graph neural network architectures.
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.
Matthew Davis Tankersley, Huw Horgan, Fabio Caratori-Tontini, and Kirsty Tinto
EGUsphere, https://doi.org/10.5194/egusphere-2025-2380, https://doi.org/10.5194/egusphere-2025-2380, 2025
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We studied how gravity data can be used to estimate the shape of the seafloor beneath Antarctica’s floating ice shelves, where direct measurements are difficult. Using computer models based on real Antarctic data, we tested when this method works well and where it has limits. We found that it could greatly improve seafloor maps for most ice shelves. Better maps will help us understand how ocean water melts ice from below, which affects future sea level rise.
Joshua K. Cuzzone, Aaron Barth, Kelsey Barker, and Mathieu Morlighem
The Cryosphere, 19, 1559–1575, https://doi.org/10.5194/tc-19-1559-2025, https://doi.org/10.5194/tc-19-1559-2025, 2025
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We use an ice sheet model to simulate the Last Glacial Maximum conditions of the Laurentide Ice Sheet (LIS) across the northeastern United States. A complex thermal history existed for the LIS that caused high erosion across most of the NE USA but prevented erosion across high-elevation mountain peaks and areas where ice flow was slow. This has implications for geologic studies which rely on the erosional nature of the LIS to reconstruct its glacial history and landscape evolution.
Yoshihiro Nakayama, Alena Malyarenko, Hong Zhang, Ou Wang, Matthis Auger, Yafei Nie, Ian Fenty, Matthew Mazloff, Armin Köhl, and Dimitris Menemenlis
Geosci. Model Dev., 17, 8613–8638, https://doi.org/10.5194/gmd-17-8613-2024, https://doi.org/10.5194/gmd-17-8613-2024, 2024
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Global- and basin-scale ocean reanalyses are becoming easily accessible. However, such ocean reanalyses are optimized for their entire model domains and their ability to simulate the Southern Ocean requires evaluation. We conduct intercomparison analyses of Massachusetts Institute of Technology General Circulation Model (MITgcm)-based ocean reanalyses. They generally perform well for the open ocean, but open-ocean temporal variability and Antarctic continental shelves require improvements.
Gong Cheng, Mathieu Morlighem, and G. Hilmar Gudmundsson
Geosci. Model Dev., 17, 6227–6247, https://doi.org/10.5194/gmd-17-6227-2024, https://doi.org/10.5194/gmd-17-6227-2024, 2024
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We conducted a comprehensive analysis of the stabilization and reinitialization techniques currently employed in ISSM and Úa for solving level-set equations, specifically those related to the dynamic representation of moving ice fronts within numerical ice sheet models. Our results demonstrate that the streamline upwind Petrov–Galerkin (SUPG) method outperforms the other approaches. We found that excessively frequent reinitialization can lead to exceptionally high errors in simulations.
In-Woo Park, Emilia Kyung Jin, Mathieu Morlighem, and Kang-Kun Lee
The Cryosphere, 18, 1139–1155, https://doi.org/10.5194/tc-18-1139-2024, https://doi.org/10.5194/tc-18-1139-2024, 2024
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This study conducted 3D thermodynamic ice sheet model experiments, and modeled temperatures were compared with 15 observed borehole temperature profiles. We found that using incompressibility of ice without sliding agrees well with observed temperature profiles in slow-flow regions, while incorporating sliding in fast-flow regions captures observed temperature profiles. Also, the choice of vertical velocity scheme has a greater impact on the shape of the modeled temperature profile.
Anjali Sandip, Ludovic Räss, and Mathieu Morlighem
Geosci. Model Dev., 17, 899–909, https://doi.org/10.5194/gmd-17-899-2024, https://doi.org/10.5194/gmd-17-899-2024, 2024
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We solve momentum balance for unstructured meshes to predict ice flow for real glaciers using a pseudo-transient method on graphics processing units (GPUs) and compare it to a standard central processing unit (CPU) implementation. We justify the GPU implementation by applying the price-to-performance metric for up to million-grid-point spatial resolutions. This study represents a first step toward leveraging GPU processing power, enabling more accurate polar ice discharge predictions.
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.
Joel A. Wilner, Mathieu Morlighem, and Gong Cheng
The Cryosphere, 17, 4889–4901, https://doi.org/10.5194/tc-17-4889-2023, https://doi.org/10.5194/tc-17-4889-2023, 2023
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We use numerical modeling to study iceberg calving off of ice shelves in Antarctica. We examine four widely used mathematical descriptions of calving (
calving laws), under the assumption that Antarctic ice shelf front positions should be in steady state under the current climate forcing. We quantify how well each of these calving laws replicates the observed front positions. Our results suggest that the eigencalving and von Mises laws are most suitable for Antarctic ice shelves.
Yaowen Zheng, Nicholas R. Golledge, Alexandra Gossart, Ghislain Picard, and Marion Leduc-Leballeur
The Cryosphere, 17, 3667–3694, https://doi.org/10.5194/tc-17-3667-2023, https://doi.org/10.5194/tc-17-3667-2023, 2023
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Positive degree-day (PDD) schemes are widely used in many Antarctic numerical ice sheet models. However, the PDD approach has not been systematically explored for its application in Antarctica. We have constructed a novel grid-cell-level spatially distributed PDD (dist-PDD) model and assessed its accuracy. We suggest that an appropriately parameterized dist-PDD model can be a valuable tool for exploring Antarctic surface melt beyond the satellite era.
Alice C. Frémand, Peter Fretwell, Julien A. Bodart, Hamish D. Pritchard, Alan Aitken, Jonathan L. Bamber, Robin Bell, Cesidio Bianchi, Robert G. Bingham, Donald D. Blankenship, Gino Casassa, Ginny Catania, Knut Christianson, Howard Conway, Hugh F. J. Corr, Xiangbin Cui, Detlef Damaske, Volkmar Damm, Reinhard Drews, Graeme Eagles, Olaf Eisen, Hannes Eisermann, Fausto Ferraccioli, Elena Field, René Forsberg, Steven Franke, Shuji Fujita, Yonggyu Gim, Vikram Goel, Siva Prasad Gogineni, Jamin Greenbaum, Benjamin Hills, Richard C. A. Hindmarsh, Andrew O. Hoffman, Per Holmlund, Nicholas Holschuh, John W. Holt, Annika N. Horlings, Angelika Humbert, Robert W. Jacobel, Daniela Jansen, Adrian Jenkins, Wilfried Jokat, Tom Jordan, Edward King, Jack Kohler, William Krabill, Mette Kusk Gillespie, Kirsty Langley, Joohan Lee, German Leitchenkov, Carlton Leuschen, Bruce Luyendyk, Joseph MacGregor, Emma MacKie, Kenichi Matsuoka, Mathieu Morlighem, Jérémie Mouginot, Frank O. Nitsche, Yoshifumi Nogi, Ole A. Nost, John Paden, Frank Pattyn, Sergey V. Popov, Eric Rignot, David M. Rippin, Andrés Rivera, Jason Roberts, Neil Ross, Anotonia Ruppel, Dustin M. Schroeder, Martin J. Siegert, Andrew M. Smith, Daniel Steinhage, Michael Studinger, Bo Sun, Ignazio Tabacco, Kirsty Tinto, Stefano Urbini, David Vaughan, Brian C. Welch, Douglas S. Wilson, Duncan A. Young, and Achille Zirizzotti
Earth Syst. Sci. Data, 15, 2695–2710, https://doi.org/10.5194/essd-15-2695-2023, https://doi.org/10.5194/essd-15-2695-2023, 2023
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This paper presents the release of over 60 years of ice thickness, bed elevation, and surface elevation data acquired over Antarctica by the international community. These data are a crucial component of the Antarctic Bedmap initiative which aims to produce a new map and datasets of Antarctic ice thickness and bed topography for the international glaciology and geophysical community.
Alena Malyarenko, Alexandra Gossart, Rui Sun, and Mario Krapp
Geosci. Model Dev., 16, 3355–3373, https://doi.org/10.5194/gmd-16-3355-2023, https://doi.org/10.5194/gmd-16-3355-2023, 2023
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Simultaneous modelling of ocean, sea ice, and atmosphere in coupled models is critical for understanding all of the processes that happen in the Antarctic. Here we have developed a coupled model for the Ross Sea, P-SKRIPS, that conserves heat and mass between the ocean and sea ice model (MITgcm) and the atmosphere model (PWRF). We have shown that our developments reduce the model drift, which is important for long-term simulations. P-SKRIPS shows good results in modelling coastal polynyas.
Francesca Baldacchino, Mathieu Morlighem, Nicholas R. Golledge, Huw Horgan, and Alena Malyarenko
The Cryosphere, 16, 3723–3738, https://doi.org/10.5194/tc-16-3723-2022, https://doi.org/10.5194/tc-16-3723-2022, 2022
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Understanding how the Ross Ice Shelf will evolve in a warming world is important to the future stability of Antarctica. It remains unclear what changes could drive the largest mass loss in the future and where places are most likely to trigger larger mass losses. Sensitivity maps are modelled showing that the RIS is sensitive to changes in environmental and glaciological controls at regions which are currently experiencing changes. These regions need to be monitored in a warming world.
Joshua K. Cuzzone, Nicolás E. Young, Mathieu Morlighem, Jason P. Briner, and Nicole-Jeanne Schlegel
The Cryosphere, 16, 2355–2372, https://doi.org/10.5194/tc-16-2355-2022, https://doi.org/10.5194/tc-16-2355-2022, 2022
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We use an ice sheet model to determine what influenced the Greenland Ice Sheet to retreat across a portion of southwestern Greenland during the Holocene (about the last 12 000 years). Our simulations, constrained by observations from geologic markers, show that atmospheric warming and ice melt primarily caused the ice sheet to retreat rapidly across this domain. We find, however, that iceberg calving at the interface where the ice meets the ocean significantly influenced ice mass change.
Yannic Fischler, Martin Rückamp, Christian Bischof, Vadym Aizinger, Mathieu Morlighem, and Angelika Humbert
Geosci. Model Dev., 15, 3753–3771, https://doi.org/10.5194/gmd-15-3753-2022, https://doi.org/10.5194/gmd-15-3753-2022, 2022
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Ice sheet models are used to simulate the changes of ice sheets in future but are currently often run in coarse resolution and/or with neglecting important physics to make them affordable in terms of computational costs. We conducted a study simulating the Greenland Ice Sheet in high resolution and adequate physics to test where the ISSM ice sheet code is using most time and what could be done to improve its performance for future computer architectures that allow massive parallel computing.
Molly O. Patterson, Richard H. Levy, Denise K. Kulhanek, Tina van de Flierdt, Huw Horgan, Gavin B. Dunbar, Timothy R. Naish, Jeanine Ash, Alex Pyne, Darcy Mandeno, Paul Winberry, David M. Harwood, Fabio Florindo, Francisco J. Jimenez-Espejo, Andreas Läufer, Kyu-Cheul Yoo, Osamu Seki, Paolo Stocchi, Johann P. Klages, Jae Il Lee, Florence Colleoni, Yusuke Suganuma, Edward Gasson, Christian Ohneiser, José-Abel Flores, David Try, Rachel Kirkman, Daleen Koch, and the SWAIS 2C Science Team
Sci. Dril., 30, 101–112, https://doi.org/10.5194/sd-30-101-2022, https://doi.org/10.5194/sd-30-101-2022, 2022
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How much of the West Antarctic Ice Sheet will melt and how quickly it will happen when average global temperatures exceed 2 °C is currently unknown. Given the far-reaching and international consequences of Antarctica’s future contribution to global sea level rise, the SWAIS 2C Project was developed in order to better forecast the size and timing of future changes.
Thomas Frank, Henning Åkesson, Basile de Fleurian, Mathieu Morlighem, and Kerim H. Nisancioglu
The Cryosphere, 16, 581–601, https://doi.org/10.5194/tc-16-581-2022, https://doi.org/10.5194/tc-16-581-2022, 2022
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The shape of a fjord can promote or inhibit glacier retreat in response to climate change. We conduct experiments with a synthetic setup under idealized conditions in a numerical model to study and quantify the processes involved. We find that friction between ice and fjord is the most important factor and that it is possible to directly link ice discharge and grounding line retreat to fjord topography in a quantitative way.
Thiago Dias dos Santos, Mathieu Morlighem, and Douglas Brinkerhoff
The Cryosphere, 16, 179–195, https://doi.org/10.5194/tc-16-179-2022, https://doi.org/10.5194/tc-16-179-2022, 2022
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Projecting the future evolution of Greenland and Antarctica and their potential contribution to sea level rise often relies on computer simulations carried out by numerical ice sheet models. Here we present a new vertically integrated ice sheet model and assess its performance using different benchmarks. The new model shows results comparable to a three-dimensional model at relatively lower computational cost, suggesting that it is an excellent alternative for long-term simulations.
Jamey Stutz, Andrew Mackintosh, Kevin Norton, Ross Whitmore, Carlo Baroni, Stewart S. R. Jamieson, Richard S. Jones, Greg Balco, Maria Cristina Salvatore, Stefano Casale, Jae Il Lee, Yeong Bae Seong, Robert McKay, Lauren J. Vargo, Daniel Lowry, Perry Spector, Marcus Christl, Susan Ivy Ochs, Luigia Di Nicola, Maria Iarossi, Finlay Stuart, and Tom Woodruff
The Cryosphere, 15, 5447–5471, https://doi.org/10.5194/tc-15-5447-2021, https://doi.org/10.5194/tc-15-5447-2021, 2021
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Understanding the long-term behaviour of ice sheets is essential to projecting future changes due to climate change. In this study, we use rocks deposited along the margin of the David Glacier, one of the largest glacier systems in the world, to reveal a rapid thinning event initiated over 7000 years ago and endured for ~ 2000 years. Using physical models, we show that subglacial topography and ocean heat are important drivers for change along this sector of the Antarctic Ice Sheet.
Matt O'Regan, Thomas M. Cronin, Brendan Reilly, Aage Kristian Olsen Alstrup, Laura Gemery, Anna Golub, Larry A. Mayer, Mathieu Morlighem, Matthias Moros, Ole L. Munk, Johan Nilsson, Christof Pearce, Henrieka Detlef, Christian Stranne, Flor Vermassen, Gabriel West, and Martin Jakobsson
The Cryosphere, 15, 4073–4097, https://doi.org/10.5194/tc-15-4073-2021, https://doi.org/10.5194/tc-15-4073-2021, 2021
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Ryder Glacier is a marine-terminating glacier in north Greenland discharging ice into the Lincoln Sea. Here we use marine sediment cores to reconstruct its retreat and advance behavior through the Holocene. We show that while Sherard Osborn Fjord has a physiography conducive to glacier and ice tongue stability, Ryder still retreated more than 40 km inland from its current position by the Middle Holocene. This highlights the sensitivity of north Greenland's marine glaciers to climate change.
Ruth Mottram, Nicolaj Hansen, Christoph Kittel, J. Melchior van Wessem, Cécile Agosta, Charles Amory, Fredrik Boberg, Willem Jan van de Berg, Xavier Fettweis, Alexandra Gossart, Nicole P. M. van Lipzig, Erik van Meijgaard, Andrew Orr, Tony Phillips, Stuart Webster, Sebastian B. Simonsen, and Niels Souverijns
The Cryosphere, 15, 3751–3784, https://doi.org/10.5194/tc-15-3751-2021, https://doi.org/10.5194/tc-15-3751-2021, 2021
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We compare the calculated surface mass budget (SMB) of Antarctica in five different regional climate models. On average ~ 2000 Gt of snow accumulates annually, but different models vary by ~ 10 %, a difference equivalent to ± 0.5 mm of global sea level rise. All models reproduce observed weather, but there are large differences in regional patterns of snowfall, especially in areas with very few observations, giving greater uncertainty in Antarctic mass budget than previously identified.
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.
Jowan M. Barnes, Thiago Dias dos Santos, Daniel Goldberg, G. Hilmar Gudmundsson, Mathieu Morlighem, and Jan De Rydt
The Cryosphere, 15, 1975–2000, https://doi.org/10.5194/tc-15-1975-2021, https://doi.org/10.5194/tc-15-1975-2021, 2021
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Some properties of ice flow models must be initialised using observed data before they can be used to produce reliable predictions of the future. Different models have different ways of doing this, and the process is generally seen as being specific to an individual model. We compare the methods used by three different models and show that they produce similar outputs. We also demonstrate that the outputs from one model can be used in other models without introducing large uncertainties.
Huw J. Horgan, Laurine van Haastrecht, Richard B. Alley, Sridhar Anandakrishnan, Lucas H. Beem, Knut Christianson, Atsuhiro Muto, and Matthew R. Siegfried
The Cryosphere, 15, 1863–1880, https://doi.org/10.5194/tc-15-1863-2021, https://doi.org/10.5194/tc-15-1863-2021, 2021
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The grounding zone marks the transition from a grounded ice sheet to a floating ice shelf. Like Earth's coastlines, the grounding zone is home to interactions between the ocean, fresh water, and geology but also has added complexity and importance due to the overriding ice. Here we use seismic surveying – sending sound waves down through the ice – to image the grounding zone of Whillans Ice Stream in West Antarctica and learn more about the nature of this important transition zone.
Kate E. Ashley, Robert McKay, Johan Etourneau, Francisco J. Jimenez-Espejo, Alan Condron, Anna Albot, Xavier Crosta, Christina Riesselman, Osamu Seki, Guillaume Massé, Nicholas R. Golledge, Edward Gasson, Daniel P. Lowry, Nicholas E. Barrand, Katelyn Johnson, Nancy Bertler, Carlota Escutia, Robert Dunbar, and James A. Bendle
Clim. Past, 17, 1–19, https://doi.org/10.5194/cp-17-1-2021, https://doi.org/10.5194/cp-17-1-2021, 2021
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We present a multi-proxy record of Holocene glacial meltwater input, sediment transport, and sea-ice variability off East Antarctica. Our record shows that a rapid Antarctic sea-ice increase during the mid-Holocene (~ 4.5 ka) occurred against a backdrop of increasing glacial meltwater input and gradual climate warming. We suggest that mid-Holocene ice shelf cavity expansion led to cooling of surface waters and sea-ice growth, which slowed basal ice shelf melting.
Xiangbin Cui, Hafeez Jeofry, Jamin S. Greenbaum, Jingxue Guo, Lin Li, Laura E. Lindzey, Feras A. Habbal, Wei Wei, Duncan A. Young, Neil Ross, Mathieu Morlighem, Lenneke M. Jong, Jason L. Roberts, Donald D. Blankenship, Sun Bo, and Martin J. Siegert
Earth Syst. Sci. Data, 12, 2765–2774, https://doi.org/10.5194/essd-12-2765-2020, https://doi.org/10.5194/essd-12-2765-2020, 2020
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We present a topographic digital elevation model (DEM) for Princess Elizabeth Land (PEL), East Antarctica. The DEM covers an area of approximately 900 000 km2 and was built from radio-echo sounding data collected in four campaigns since 2015. Previously, to generate the Bedmap2 topographic product, PEL’s bed was characterised from low-resolution satellite gravity data across an otherwise large (>200 km wide) data-free zone.
Wei Ji Leong and Huw Joseph Horgan
The Cryosphere, 14, 3687–3705, https://doi.org/10.5194/tc-14-3687-2020, https://doi.org/10.5194/tc-14-3687-2020, 2020
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A machine learning technique similar to the one used to enhance everyday photographs is applied to the problem of getting a better picture of Antarctica's bed – the part which is hidden beneath the ice. By taking hints from what satellites can observe at the ice surface, the novel method learns to generate a rougher bed topography that complements existing approaches, with a result that is able to be used by scientists running fine-scale ice sheet models relevant to predicting future sea levels.
Eric Larour, Lambert Caron, Mathieu Morlighem, Surendra Adhikari, Thomas Frederikse, Nicole-Jeanne Schlegel, Erik Ivins, Benjamin Hamlington, Robert Kopp, and Sophie Nowicki
Geosci. Model Dev., 13, 4925–4941, https://doi.org/10.5194/gmd-13-4925-2020, https://doi.org/10.5194/gmd-13-4925-2020, 2020
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ISSM-SLPS is a new projection system for future sea level that increases the resolution and accuracy of current projection systems and improves the way uncertainty is treated in such projections. This will pave the way for better inclusion of state-of-the-art results from existing intercomparison efforts carried out by the scientific community, such as GlacierMIP2 or ISMIP6, into sea-level projections.
Cited articles
Agosta, C., Amory, C., Kittel, C., Orsi, A., Favier, V., Gallée, H., van den Broeke, M. R., Lenaerts, J. T. M., van Wessem, J. M., van de Berg, W. J., and Fettweis, X.: Estimation of the Antarctic surface mass balance using the regional climate model MAR (1979–2015) and identification of dominant processes, The Cryosphere, 13, 281–296, https://doi.org/10.5194/tc-13-281-2019, 2019. a
Alley, K. E., Scambos, T. A., Anderson, R. S., Rajaram, H., Pope, A., and Haran, T. M.: Continent-wide estimates of Antarctic strain rates from Landsat 8-derived velocity grids, J. Glaciol., 64, 321–332, https://doi.org/10.1017/jog.2018.23, 2018. a
Anandakrishnan, S., Voigt, D., Alley, R., and King, M.: Ice stream D flow speed is strongly modulated by the tide beneath the Ross Ice Shelf, Geophys. Res. Lett., 30, 1361, https://doi.org/10.1029/2002GL016329, 2003. a
Arndt, J. E., Larter, R. D., Friedl, P., Gohl, K., Höppner, K., and the Science Team of Expedition PS104: Bathymetric controls on calving processes at Pine Island Glacier, The Cryosphere, 12, 2039–2050, https://doi.org/10.5194/tc-12-2039-2018, 2018. a
Assmann, K., Hellmer, H. H., and Beckmann, A.: Seasonal variation in circulation and water mass distribution on the Ross Sea continental shelf, Antarct. Sci., 15, 3–11, https://doi.org/10.1017/S0954102003001007, 2003. a
Baldacchino, F.: Modelling GNSS-observed seasonal velocity changes of the Ross Ice Shelf, Antarctica, using the Ice-sheet and Sea-level System Model (ISSM), Zenodo [code], https://doi.org/10.5281/zenodo.11098089, 2024. a
Bindschadler, R. A., Vornberger, P. L., King, M. A., and Padman, L.: Tidally driven stick-slip motion in the mouth of Whillans Ice Stream, Antarctica, Ann. Glaciol., 36, 263–272, https://doi.org/10.3189/172756403781816284, 2003. a, b
Bougamont, M., Christoffersen, P., Price, S., Fricker, H. A., Tulaczyk, S., and Carter, S. P.: Reactivation of Kamb Ice Stream tributaries triggers century-scale reorganization of Siple Coast ice flow in West Antarctica, Geophys. Res. Lett., 42, 8471–8480, 2015. a
Brunt, K. M.: Tidal motion of the Ross Ice Shelf and its interaction with the Siple Coast ice streams, Antarctica, The University of Chicago, 2008. a
Brunt, K. M. and Macayeal, D. R.: Tidal modulation of ice-shelf flow: A viscous model of the Ross Ice Shelf, J. Glaciol., 60, 500–508, https://doi.org/10.3189/2014JoG13J203, 2014. a
Brunt, K. M., King, M. A., Fricker, H. A., and MacAyeal, D. R.: Flow of the Ross Ice Shelf, Antarctica, is modulated by the ocean tide, J. Glaciol., 56, 157–161, https://doi.org/10.3189/002214310791190875, 2010. 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
Catania, G., Hulbe, C., Conway, H., Scambos, T. A., and Raymond, C.: Variability in the mass flux of the Ross ice streams, West Antarctica, over the last millennium, J. Glaciol., 58, 741–752, https://doi.org/10.3189/2012JoG11J219, 2012. a
Cavanagh, J., Lampkin, D., and Moon, T.: Seasonal variability in regional ice flow due to meltwater injection into the shear margins of Jakobshavn Isbræ, J. Geophys. Res.-Earth Surf., 122, 2488–2505, https://doi.org/10.1002/2016JF004187, 2017. a
Chaput, J., Aster, R., McGrath, D., Baker, M., Anthony, R. E., Gerstoft, P., Bromirski, P., Nyblade, A., Stephen, R., Wiens, D., Das, S. B., and Stevens, L. A.: Near-surface environmentally forced changes in the Ross Ice Shelf observed with ambient seismic noise, Geophys. Res. Lett., 45, 11–187, https://doi.org/10.1029/2018GL079665, 2018. a, b
Das, I., Padman, L., Bell, R. E., Fricker, H. A., Tinto, K. J., Hulbe, C. L., Siddoway, C. S., Dhakal, T., Frearson, N. P., Mosbeux, C., Cordero, S. I., and Siegfried, M. R.: Multidecadal Basal Melt Rates and Structure of the Ross Ice Shelf, Antarctica, Using Airborne Ice Penetrating Radar, J. Geophys. Res.-Earth Surf., 125, e2019JF005241, https://doi.org/10.1029/2019JF005241, 2020. a, b
Davis, P. and Nicholls, K.: Turbulence observations beneath Larsen C Ice Shelf, Antarctica., J. Geophys. Res, 124, 5529–5550, https://doi.org/10.1029/2019jc015164, 2019. a
Depoorter, M. A., Bamber, J. L., Griggs, J. A., Lenaerts, J. T., Ligtenberg, S. R., Van Den Broeke, M. R., and Moholdt, G.: Calving fluxes and basal melt rates of Antarctic ice shelves, Nature, 502, 89–92, https://doi.org/10.1038/nature12567, 2013. a
Dinniman, Asay-Davis, X. S., Galton-Fenzi, B. K., Holland, P. R., Jenkins, A., and Timmermann, R.: Modeling ice shelf/ocean interaction in Antarctica: A review, Oceanography, 29, 144–153, https://doi.org/10.5670/oceanog.2016.106, 2016. a, b
Dirscherl, M., Dietz, A. J., Dech, S., and Kuenzer, C.: Remote sensing of ice motion in Antarctica – A review, Remote Sens. Environ., 237, 111595, https://doi.org/10.1016/j.rse.2019.111595, 2020. a
Dupont, T. and Alley, R.: Assessment of the importance of ice-shelf buttressing to ice-sheet flow., Geophys. Res. Lett., 32, L04503, https://doi.org/10.1029/2004GL022024, 2005. a
Gudmundsson, G.: Fortnightly variations in the flow velocity of Rutford Ice Stream, West Antarctica, Nature, 444, 1063–1064, https://doi.org/10.1038/nature05430, 2006. a
Gudmundsson, G. H.: Ice-shelf buttressing and the stability of marine ice sheets, The Cryosphere, 7, 647–655, https://doi.org/10.5194/tc-7-647-2013, 2013. a
Gudmundsson, G. H., Paolo, F. S., Adusumilli, S., and Fricker, H. A.: Instantaneous Antarctic Ice Sheet mass loss driven by thinning ice shelves, Geophys. Res. Lett., 46, 13903–13909, https://doi.org/10.1029/2019GL085027, 2019. a, b, c, d
Gwyther, D. E., O'Kane, T. J., Galton-Fenzi, B. K., Monselesan, D. P., and Greenbaum, J. S.: Intrinsic processes drive variability in basal melting of the Totten Glacier Ice Shelf, Nat. Commun., 9, 1–8, https://doi.org/10.1038/s41467-018-05618-2, 2018. a, b
Holland, D. 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. a
Holland, D. M., Jacobs, S. S., and Jenkins, A.: Modelling the ocean circulation beneath the Ross Ice Shelf, Antarct. Sci., 15, 13–23, https://doi.org/10.1017/S0954102003001019, 2003. a
Holland, P. R., Bracegirdle, T. J., Dutrieux, P., Jenkins, A., and Steig, E. J.: West Antarctic ice loss influenced by internal climate variability and anthropogenic forcing, Nat. Geosci., 12, 718–724, https://doi.org/10.1038/s41561-019-0420-9, 2019. a
Horgan, H. J.: Ross Ice Shelf GNSS data reported in EGUSphere-2023-2793, Baldacchino et al., 2024, Zenodo [data set], https://doi.org/10.5281/zenodo.14134876, 2024. a
Howat, I. M., Box, J. E., Ahn, Y., Herrington, A., and McFadden, E. M.: Seasonal variability in the dynamics of marine-terminating outlet glaciers in Greenland, J. Glaciol., 56, 601–613, https://doi.org/10.3189/002214310793146232, 2010. a
Hulbe, C., Scambos, T., Klinger, M., and Fahnestock, M.: Flow variability and ongoing margin shifts on Bindschadler and MacAyeal Ice Streams, West Antarctica, J. Geophys. Res.-Earth Surf., 121, 283–293, https://doi.org/10.1002/2015JF003670, 2016. a
Jendersie, S., Williams, M. J. M., Langhorne, P. J., and Robertson, R.: The Density-Driven Winter Intensification of the Ross Sea Circulation, J. Geophys. Res.-Oceans, 123, 7702–7724, https://doi.org/10.1029/2018JC013965, 2018. a, b, c
Jenkins, A., Shoosmith, D., Dutrieux, P., Jacobs, S., Kim, T. W., Lee, S. H., Ha, H. K., and Stammerjohn, S.: West Antarctic Ice Sheet retreat in the Amundsen Sea driven by decadal oceanic variability, Nat. Geosci., 11, 733–738, https://doi.org/10.1038/s41561-018-0207-4, 2018. a, b
Joughin, I., Alley, R. B., and Holland, D. M.: Oceanic Forcing, Science, 338, 1172–6, https://doi.org/10.1126/science.1226481, 2013. 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., Shapero, D., Smith, B., Dutrieux, P., and Barham, M.: Ice-shelf retreat drives recent Pine Island Glacier speedup, Sci. Adv., 7, eabg3080, https://doi.org/10.1126/sciadv.abg3080, 2021. a
King, M., Makinson, K., and Gudmundsson, G. H.: Nonlinear interaction between ocean tides and the Larsen C Ice Shelf system, Geophys. Res. Lett., 38, 1–5, https://doi.org/10.1029/2011GL046680, 2011. a
Klein, E., Mosbeux, C., Bromirski, P. D., Padman, L., Bock, Y., Springer, S. R., and Fricker, H. A.: Annual cycle in flow of Ross Ice Shelf, Antarctica: Contribution of variable basal melting, J. Glaciol., 66, 861–875, https://doi.org/10.1017/jog.2020.61, 2020. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q, r, s, t, u, v, w, x, y
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, J. Geophys. Res., 117, F01022, https://doi.org/10.1029/2011JF002140, 2012 (data available at: https://issm.jpl.nasa.gov, last access: 10 September 2024). a
Larter, R. D.: Basal Melting, Roughness and Structural Integrity of Ice Shelves, Geophys. Res. Lett., 49, e2021GL097421, https://doi.org/10.1029/2021GL097421, 2022. a
Lipscomb, W. H., Leguy, G. R., Jourdain, N. C., Asay-Davis, X., Seroussi, H., and Nowicki, S.: ISMIP6-based projections of ocean-forced Antarctic Ice Sheet evolution using the Community Ice Sheet Model, The Cryosphere, 15, 633–661, https://doi.org/10.5194/tc-15-633-2021, 2021. a
Losch, M.: Modeling ice shelf cavities in a z coordinate ocean general circulation model, J. Geophys. Res.-Oceans (1978–2012), 113, https://doi.org/10.1029/2007jc004368, 2008. a
Malyarenko, A., Robinson, N. J., Williams, M. J. M., and Langhorne, P. J.: A Wedge Mechanism for Summer Surface Water Inflow Into the Ross Ice Shelf Cavity, J. Geophys. Res.-Oceans, 124, 1196–1214, https://doi.org/10.1029/2018jc014594, 2019. a
Marsh, O. J., Fricker, H. A., Siegfried, M. R., Christianson, K., Nicholls, K. W., Corr, H. F., and Catania, G.: High basal melting forming a channel at the grounding line of Ross Ice Shelf, Antarctica, Geophys. Res. Lett., 43, 250–255, https://doi.org/10.1002/2015GL066612, 2016. a
Moholdt, G., Padman, L., and Fricker, H. A.: Basal mass budget of Ross and Filchner-Ronne ice shelves, Antarctica, derived from Lagrangian analysis of ICESat altimetry, J. Geophys. Res.-Earth Surf., 119, 2361–2380, https://doi.org/10.1002/2014JF003171, 2014. a, b
Morlighem, M.: MEaSUREs BedMachine Antarctica. (NSIDC-0756, Version 3), Boulder, Colorado USA, NASA National Snow and Ice Data Center Distributed Active Archive Center [data set], https://doi.org/10.5067/FPSU0V1MWUB6, 2022. 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, 1–6, https://doi.org/10.1029/2010GL043853, 2010. a
Morlighem, M., Seroussi, H., Larour, E., and Rignot, E.: Inversion of basal friction in Antarctica using exact and incomplete adjoints of a higher-order model, J. Geophys. Res.-Earth Surf., 118, 1746–1753, https://doi.org/10.1002/jgrf.20125, 2013. a
Mosbeux, C., Padman, L., Klein, E., Bromirski, P. D., and Fricker, H. A.: Seasonal variability in Antarctic ice shelf velocities forced by sea surface height variations, The Cryosphere, 17, 2585–2606, https://doi.org/10.5194/tc-17-2585-2023, 2023. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q, r, s, t, u, v, w, x, y
Mottram, R., Simonsen, S. B., Svendsen, S. H., Barletta, V. R., Sørensen, L. S., Nagler, T., Wuite, J., Groh, A., Horwath, M., Rosier, J., Solgaard, A., Hvidberg, C. S., and Forsberg, R.: An integrated view of Greenland Ice Sheet mass changes based on models and satellite observations, Remote Sens., 11, 1–26, https://doi.org/10.3390/rs11121407, 2019. a
Murray, T., Smith, A., King, M., and Weedon, G.: Ice flow modulated by tides at up to annual periods at Rutford Ice Stream, West Antarctica, Geophys. Res. Lett., 34, L18503, https://doi.org/10.1029/2007GL031207, 2007. a, b
Ng, F. and Conway, H.: Fast-flow signature in the stagnated Kamb Ice Stream, West Antarctica, Geology, 32, 481–484, https://doi.org/10.1130/G20317.1, 2004. a
Nicolas, J. P., Vogelmann, A. M., Scott, R. C., Wilson, A. B., Cadeddu, M. P., Bromwich, D. H., Verlinde, J., Lubin, D., Russell, L. M., Jenkinson, C., and Powers, H. H.: January 2016 extensive summer melt in West Antarctica favoured by strong El Niño, Nat. Commun., 8, 15799, https://doi.org/10.1038/ncomms15799, 2017. a, b, c
Padman, L., Erofeeva, S., and Joughin, I.: Tides of the Ross Sea and Ross Ice Shelf cavity, Antarct. Sci., 15, 31–40, https://doi.org/10.1017/S0954102003001032, 2003. a, b
Paolo, F. S., Fricker, H. A., and Padman, L.: Volume loss from Antarctic ice shelves is accelerating, Science, 348, 327–331, https://doi.org/10.1126/science.aaa0940, 2015. a
Pattyn, F.: Sea-level response to melting of Antarctic ice shelves on multi-centennial timescales with the fast Elementary Thermomechanical Ice Sheet model (f.ETISh v1.0), The Cryosphere, 11, 1851–1878, https://doi.org/10.5194/tc-11-1851-2017, 2017. a
Pattyn, F. and Durand, G.: Why marine ice sheet model predictions may diverge in estimating future sea level rise, Geophys. Res. Lett., 40, 4316–4320, https://doi.org/10.1002/grl.50824, 2013. a
Pattyn, F., Ritz, C., Hanna, E., Asay-Davis, X., DeConto, R., Durand, G., Favier, L., Fettweis, X., Goelzer, H., Golledge, N. R., Kuipers Munneke, P., Lenaerts, J. T., Nowicki, S., Payne, A. J., Robinson, A., Seroussi, H., Trusel, L. D., and van den Broeke, M.: The Greenland and Antarctic Ice Sheets under 1.5 °C global warming, Nat. Clim. Change, 8, 1053–1061, https://doi.org/10.1038/s41558-018-0305-8, 2018. a, b
Pawlowicz, R., Beardsley, B., and Lentz, S.: Classical tidal harmonic analysis including error estimates in MATLAB using T_TIDE, Comput. Geosci., 28, 929–937, 2002. a
Ranganathan, M., Minchew, B., Meyer, C. R., and Gudmundsson, G. H.: A new approach to inferring basal drag and ice rheology in ice streams, with applications to West Antarctic Ice Streams, J. Glaciol., 67, 229–242, https://doi.org/10.1017/jog.2020.95, 2021. a
Ray, R. D., Larson, K. M., and Haines, B. J.: New determinations of tides on the north-western Ross Ice Shelf., Antarct. Sci., 33, 89–102, https://doi.org/10.1017/S0954102020000498, 2021. a
Reese, R., Gudmundsson, G. H., Levermann, A., and Winkelmann, R.: The far reach of ice-shelf thinning in Antarctica, Nat. Clim. Change, 8, 53–57, https://doi.org/10.1038/s41558-017-0020-x, 2018. a, b, c
Retzlaff, R. and Bentley, C. R.: Timing of stagnation of Ice Stream C, West Antarctica, from short-pulse radar studies of buried surface crevasses, J. Glaciol., 39, 553–561, https://doi.org/10.3189/S0022143000016440, 1993. a
Rignot, Jacobs, S., Mouginot, J., and Scheuchl, B.: Ice-shelf melting around Antarctica, Science, 341, 266–270, https://doi.org/10.1126/science.1235798, 2013. a
Rignot, E., Mouginot, J., and Scheuchl, B.: MEaSUREs InSAR-Based Antarctica Ice Velocity Map (NSIDC-0484, Version 2), Boulder, Colorado USA, NASA National Snow and Ice Data Center Distributed Active Archive Center [data set], https://doi.org/10.5067/D7GK8F5J8M8R (last access: 20 February 2020), 2017. a, b
Rignot, E., Mouginot, J., Scheuchl, B., van den Broeke, M., van Wessem, M. J., and Morlighem, M.: Four decades of Antarctic Ice Sheet mass balance from 1979–2017, P. Natl. Acad. Sci. USA, 116, 1095–1103, https://doi.org/10.1073/pnas.1812883116, 2019. a, b
Rosier, S. H. R. and Gudmundsson, G. H.: Exploring mechanisms responsible for tidal modulation in flow of the Filchner–Ronne Ice Shelf, The Cryosphere, 14, 17–37, https://doi.org/10.5194/tc-14-17-2020, 2020. a
Sagebaum, M., Albring, T., and Gauger, N.: High-Performance Derivative Computations using CoDiPack, ACM T. Math. Software, 45, 38, https://doi.org/10.1145/3356900, 2019. a
Schlegel, N.-J., Seroussi, H., Schodlok, M. P., Larour, E. Y., Boening, C., Limonadi, D., Watkins, M. M., Morlighem, M., and van den Broeke, M. R.: Exploration of Antarctic Ice Sheet 100-year contribution to sea level rise and associated model uncertainties using the ISSM framework, The Cryosphere, 12, 3511–3534, https://doi.org/10.5194/tc-12-3511-2018, 2018. a
Schodlok, M., Menemenlis, D., and Rignot, E.: Ice shelf basal melt rates around Antarctica from simulations and observations, J. Geophys. Res., 121, 1085–1109, https://doi.org/10.1002/2015JC011117, 2016. a
Schoof, C.: Ice sheet grounding line dynamics: Steady states, stability, and hysteresis, J. Geophys. Res.-Earth Surf., 112, 1–19, https://doi.org/10.1029/2006JF000664, 2007. a
Shepherd, A., Ivins, E. R., Geruo, A., Barletta, V. R., Bentley, M. J., Bettadpur, S., Briggs, K. H., Bromwich, D. H., Forsberg, R., Galin, N., Horwath, M., Jacobs, S., Joughin, I., King, M. A., Lenaerts, J. T., Li, J., Ligtenberg, S. R., Luckman, A., Luthcke, S. B., McMillan, M., Meister, R., Milne, G., Mouginot, J., Muir, A., Nicolas, J. P., Paden, J., Payne, A. J., Pritchard, H., Rignot, E., Rott, H., Sørensen, L. S., Scambos, T. A., Scheuchl, B., Schrama, E. J., Smith, B., Sundal, A. V., Van Angelen, J. H., Van De Berg, W. J., Van Den Broeke, M. R., Vaughan, D. G., Velicogna, I., Wahr, J., Whitehouse, P. L., Wingham, D. J., Yi, D., Young, D., and Zwally, H. J.: A reconciled estimate of ice-sheet mass balance, Science, 338, 1183–1189, https://doi.org/10.1126/science.1228102, 2012. a
Shepherd, A., Fricker, H. A., and Farrell, S. L.: Trends and connections across the Antarctic cryosphere, Nature, 558, 223–232, https://doi.org/10.1038/s41586-018-0171-6, 2018. a, b
Stern, A. A., Dinniman, M. S., Zagorodnov, V., Tyler, S. W., and Holland, D. M.: Intrusion of warm surface water beneath the McMurdo ice shelf, Antarctica, J. Geophys. Res.-Oceans, 118, 7036–7048, https://doi.org/10.1002/2013JC008842, 2013. a
Stevens, C., Hulbe, C., Brewer, M., Stewart, C., Robinson, N., Ohneiser, C., and Jendersie, S.: Ocean mixing and heat transport processes observed under the Ross Ice Shelf control its basal melting, P. Natl. Acad. Sci. USA, 117, 16799–16804, https://doi.org/10.1073/pnas.1910760117, 2020. a, b, c
Stevens, L. A., Nettles, M., Davis, J. L., Creyts, T. T., Kingslake, J., Ahlstrøm, A. P., and Larsen, T. B.: Helheim Glacier diurnal velocity fluctuations driven by surface melt forcing, J. Glaciol., 68, 77–89, https://doi.org/10.1017/jog.2021.74, 2022. a
Still, H., Campbell, A., and Hulbe, C.: Mechanical analysis of pinning points in the Ross Ice Shelf, Antarctica, Ann. Glaciol., 60, 32–41, https://doi.org/10.1017/aog.2018.31, 2019. a, b, c
Tétreault, P., Kouba, J., Héroux, P., and Legree, P.: CSRS-PPP: an internet service for GPS user access to the Canadian Spatial Reference Frame, Geomatica, 59, 17–28, 2005. a
Thomas, R., Scheuchl, B., Frederick, E., Harpold, R., Martin, C., and Rignot, E.: Continued slowing of the Ross Ice Shelf and thickening of West Antarctic ice streams, J. Glaciol., 59, 838–844, https://doi.org/10.3189/2013JoG12J122, 2013. a
Tinto, K. J., Padman, L., Siddoway, C. S., Springer, S. R., Fricker, H. A., Das, I., Caratori Tontini, F., Porter, D. F., Frearson, N. P., Howard, S. L., Siegfried, M. R., Mosbeux, C., Becker, M. K., Bertinato, C., Boghosian, A., Brady, N., Burton, B. L., Chu, W., Cordero, S. I., Dhakal, T., Dong, L., Gustafson, C. D., Keeshin, S., Locke, C., Lockett, A., O'Brien, G., Spergel, J. J., Starke, S. E., Tankersley, M., Wearing, M. G., and Bell, R. E.: Ross Ice Shelf response to climate driven by the tectonic imprint on seafloor bathymetry, Nat. Geosci., 12, 441–449, https://doi.org/10.1038/s41561-019-0370-2, 2019. a, b, c
Trusel, L., Frey, K., Das, S., Karnauskas, K., Munneke, P., Meijgaard, E., and Van den Broeke, M.: Divergent trajectories of Antarctic surface melt under two twenty-first-century climate scenarios, Nat. Geosci., 8, 927–932, https://doi.org/10.1038/ngeo2563, 2015. a
van der Wel, N., Christoffersen, P., and Bougamont, M.: The influence of subglacial hydrology on the flow of Kamb Ice Stream, West Antarctica, J. Geophys. Res.-Earth Surf., 118, 97–110, https://doi.org/10.1002/2015GL065782, 2013. a
van Wessem, J. M., van de Berg, W. J., Noël, B. P. Y., van Meijgaard, E., Amory, C., Birnbaum, G., Jakobs, C. L., Krüger, K., Lenaerts, J. T. M., Lhermitte, S., Ligtenberg, S. R. M., Medley, B., Reijmer, C. H., van Tricht, K., Trusel, L. D., van Ulft, L. H., Wouters, B., Wuite, J., and van den Broeke, M. R.: Modelling the climate and surface mass balance of polar ice sheets using RACMO2 – Part 2: Antarctica (1979–2016), The Cryosphere, 12, 1479–1498, https://doi.org/10.5194/tc-12-1479-2018, 2018. a
van Wessem, J. M., van den Broeke, M. R., and Lhermitte, S.: Data set: Yearly RACMO2.3p2 variables, Zenodo [data set], https://doi.org/10.5281/zenodo.6602723, 2022. a
Vaughan, D. G. and Doake, C.: Recent atmospheric warming and retreat of ice shelves on the Antarctic Peninsula, Nature, 379, 328–331, https://doi.org/10.1038/379328a0, 1996. a
Whiteford, A., Horgan, H., Leong, W., and Forbes, M.: Melting and refreezing in an ice shelf basal channel at the grounding line of the Kamb Ice Stream, West Antarctica, J. Geophys. Res.-Earth Surf., 127, e2021JF006532, https://doi.org/10.1029/2021JF006532, 2022. a
Zou, X., Bromwich, D. H., Montenegro, A., Wang, S.-H., and Bai, L.: Major surface melting over the Ross Ice Shelf part I: Foehn effect, Q. J. Roy. Meteor. Soc., 147, 2874–2894, https://doi.org/10.1002/qj.4104, 2021a. a
Zou, X., Bromwich, D. H., Montenegro, A., Wang, S.-H., and Bai, L.: Major surface melting over the Ross Ice Shelf part II: Surface energy balance, Q. J. Roy. Meteor. Soc., 147, 2895–2916, https://doi.org/10.1002/qj.4105, 2021b. a
Zumberge, J., Heflin, M., Jefferson, D., Watkins, M., and Webb, F.: Precise point positioning for the efficient and robust analysis of GPS data from large networks, J. Geophys. Res.-Sol. Ea., 102, 5005–5017, https://doi.org/10.1029/96JB03860, 1997. a
Short summary
Understanding how the Ross Ice Shelf flow is changing in a warming world is important for predicting ice sheet change. Field measurements show clear intra-annual variations in ice flow; however, it is unclear what mechanisms drive this variability. We show that local perturbations in basal melt can have a significant impact on ice flow speed, but a combination of forcings is likely driving the observed variability in ice flow.
Understanding how the Ross Ice Shelf flow is changing in a warming world is important for...
