Articles | Volume 17, issue 2
https://doi.org/10.5194/gmd-17-899-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-17-899-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
02 Feb 2024
Development and technical paper |
| 02 Feb 2024
| 02 Feb 2024
Graphics-processing-unit-accelerated ice flow solver for unstructured meshes using the Shallow-Shelf Approximation (FastIceFlo v1.0.1)
Department of Mechanical Engineering, University of North Dakota, North Dakota, USA
Ludovic Räss
Laboratory of Hydraulics, Hydrology and Glaciology (VAW), ETH Zurich, Zurich, Switzerland
Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), Birmensdorf, Switzerland
now at: Swiss Geocomputing Centre, Faculty of Geosciences and Environment, University of Lausanne, Lausanne, Switzerland
Mathieu Morlighem
Department of Earth Sciences, Dartmouth College, New Hampshire, USA
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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.
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.
Arne Spang, Marcel Thielmann, Casper Pranger, Albert de Montserrat, and Ludovic Räss
EGUsphere, https://doi.org/10.5194/egusphere-2025-2417, https://doi.org/10.5194/egusphere-2025-2417, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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Concentration of deformation is difficult to capture accurately in computer simulations. We present a number of challenges associated with concentrated viscous deformation and demonstrate strategies to overcome them. These strategies include automatic selection of appropriate time steps to react to rapid changes in model behavior, automatic rescaling to avoid rounding errors, and two methods to prevent model instability. This way, we are able to accurately capture very fast viscous deformation.
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.
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.
Francesca Baldacchino, Nicholas R. Golledge, Mathieu Morlighem, Huw Horgan, Alanna V. Alevropoulos-Borrill, Alena Malyarenko, Alexandra Gossart, Daniel P. Lowry, and Laurine van Haastrecht
The Cryosphere, 19, 107–127, https://doi.org/10.5194/tc-19-107-2025, https://doi.org/10.5194/tc-19-107-2025, 2025
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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.
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.
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.
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.
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.
Ludovic Räss, Ivan Utkin, Thibault Duretz, Samuel Omlin, and Yuri Y. Podladchikov
Geosci. Model Dev., 15, 5757–5786, https://doi.org/10.5194/gmd-15-5757-2022, https://doi.org/10.5194/gmd-15-5757-2022, 2022
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Continuum mechanics-based modelling of physical processes at large scale requires huge computational resources provided by massively parallel hardware such as graphical processing units. We present a suite of numerical algorithms, implemented using the Julia language, that efficiently leverages the parallelism. We demonstrate that our implementation is efficient, scalable and robust and showcase applications to various geophysical problems.
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.
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.
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.
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.
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.
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
Aschwanden, A., Bartholomaus, T. C., Brinkerhoff, D. J., and Truffer, M.: Brief communication: A roadmap towards credible projections of ice sheet contribution to sea level, The Cryosphere, 15, 5705–5715, https://doi.org/10.5194/tc-15-5705-2021, 2021. a
Brædstrup, C. F., Damsgaard, A., and Egholm, D. L.: Ice-sheet modelling accelerated by graphics cards, Comput. Geosci., 72, 210–220, https://doi.org/10.1016/j.cageo.2014.07.019, 2014. a
Castleman, B. A., Schlegel, N.-J., Caron, L., Larour, E., and Khazendar, A.: Derivation of bedrock topography measurement requirements for the reduction of uncertainty in ice-sheet model projections of Thwaites Glacier, The Cryosphere, 16, 761–778, https://doi.org/10.5194/tc-16-761-2022, 2022. a
Chen, X., Zhang, X., Church, J. A., Watson, C. S., King, M. A., Monselesan, D., Legresy, B., and Harig, C.: The increasing rate of global mean sea-level rise during 1993–2014, Nat. Clim. Change, 7, 492–495, https://doi.org/10.1038/nclimate3325, 2017. a
Cornford, S. L., Martin, D. F., Graves, D. T., Ranken, D. F., Le Brocq, A. M., Gladstone, R. M., Payne, A. J., Ng, E. G., and Lipscomb, W. H.: Adaptive mesh, finite volume modeling of marine ice sheets, J. Comput. Phys., 232, 529–549, https://doi.org/10.1016/j.jcp.2012.08.037, 2013. a
Duretz, T., Räss, L., Podladchikov, Y., and Schmalholz, S.: Resolving thermomechanical coupling in two and three dimensions: spontaneous strain localization owing to shear heating, Geophys. J. Int., 216, 365–379, https://doi.org/10.1093/gji/ggy434, 2019. a, b
Gilbarg, D. and Trudinger, N. S.: Elliptic partial differential equations of second order, vol. 224, Springer, https://doi.org/10.1007/978-3-642-61798-0, 1977. a
Glen, J. W.: The creep of polycrystalline ice, P. Roy. Soc. Lond.-Ser. A, 228, 519–538, https://doi.org/10.1098/rspa.1955.0066, 1955. a
Goelzer, H., Robinson, A., Seroussi, H., and Van De Wal, R. S.: Recent progress in Greenland ice sheet modelling, Curr. Clim. Change Rep., 3, 291–302, https://doi.org/10.1007/s40641-017-0073-y, 2017. a
Habbal, F., Larour, E., Morlighem, M., Seroussi, H., Borstad, C. P., and Rignot, E.: Optimal numerical solvers for transient simulations of ice flow using the Ice Sheet System Model (ISSM versions 4.2.5 and 4.11), Geosci. Model Dev., 10, 155–168, https://doi.org/10.5194/gmd-10-155-2017, 2017. a
Häfner, D., Nuterman, R., and Jochum, M.: Fast, cheap, and turbulent – Global ocean modeling with GPU acceleration in python, J. Adv. Model. Earth Sy., 13, e2021MS002717, https://doi.org/10.1029/2021MS002717, 2021. a
Hinkel, J., Lincke, D., Vafeidis, A. T., Perrette, M., Nicholls, R. J., Tol, R. S., Marzeion, B., Fettweis, X., Ionescu, C., and Levermann, A.: Coastal flood damage and adaptation costs under 21st century sea-level rise, P. Natl. Acad. Sci. USA, 111, 3292–3297, https://doi.org/10.1073/pnas.1222469111, 2014. a
IPCC: Climate Change 2021 The Physical Science Basis, Working Group 1 (WG1) Contribution to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, Tech. rep., Intergovernmental Panel on Climate Change, 2021. a
Jouvet, G., Cordonnier, G., Kim, B., Lüthi, M., Vieli, A., and Aschwanden, A.: Deep learning speeds up ice flow modelling by several orders of magnitude, J. Glaciol., 68, 651–664, https://doi.org/10.1017/jog.2021.120, 2022. a
Kelley, C. and Liao, L.-Z.: Explicit pseudo-transient continuation, Computing, 15, 18, 2013. a
Kopp, R. E., Kemp, A. C., Bittermann, K., Horton, B. P., Donnelly, J. P., Gehrels, W. R., Hay, C. C., Mitrovica, J. X., Morrow, E. D., and Rahmstorf, S.: Temperature-driven global sea-level variability in the Common Era, P. Natl. Acad. Sci. USA, 113, E1434–E1441, https://doi.org/10.1073/pnas.1517056113, 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, 117, 22, https://doi.org/10.1029/2011JF002140, 2012. a, b, c
MacAyeal, D. R.: Large-scale ice flow over a viscous basal sediment: Theory and application to ice stream B, Antarctica, J. Geophys. Res.-Sol. Ea., 94, 4071–4087, 1989. 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., Noel, 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, 11–51, https://doi.org/10.1002/2017GL074954, 2017. a
Morlighem, M., Rignot, E., Binder, T., Blankenship, D., Drews, R., Eagles, G., Eisen, O., Ferraccioli, F., Forsberg, R., Fretwell, P., Goel, V., Greenbaum, J. S., Gudmundsson, H., Guo, J., Helm, V., Hofstede, C., Howat, I., Humbert, A., Jokat, W., Karlsson, N., Lee, W. S., Matsuoka, K., Millan, R., Mouginot, J., Paden, J., Pattyn, F., Roberts, J., Rosier, S., Ruppel, A., Seroussi, H., Smith, E. C., Steinhage, D., Sun, B., Van Den Broeke, M. R., Van Ommen, T. D., Wessem, M. V., and Young, D. A.: Deep glacial troughs and stabilizing ridges unveiled beneath the margins of the Antarctic ice sheet, Nat. Geosci., 13, 132–137, https://doi.org/10.1038/s41561-019-0510-8, 2020. a
Omlin, S., Räss, L., and Podladchikov, Y. Y.: Simulation of three-dimensional viscoelastic deformation coupled to porous fluid flow, Tectonophysics, 746, 695–701, https://doi.org/10.1016/j.tecto.2017.08.012, 2018. a
Pattyn, F. and Morlighem, M.: The uncertain future of the Antarctic Ice Sheet, Science, 367, 1331–1335, https://doi.org/10.1126/science.aaz5487, 2020. a
Poliakov, A. N., Cundall, P. A., Podladchikov, Y. Y., and Lyakhovsky, V. A.: An explicit inertial method for the simulation of viscoelastic flow: an evaluation of elastic effects on diapiric flow in two- and three- layers models, Flow and creep in the solar system: observations, modeling and theory, in: Flow and Creep in the Solar System: Observations, Modeling and Theory, edited by: Stone, D. B. and Runcorn, S. K., NATO ASI Series, vol. 391, Springer, Dordrecht, 175–195, https://doi.org/10.1007/978-94-015-8206-3_12, 1993. a
Räss, L., Duretz, T., and Podladchikov, Y.: Resolving hydromechanical coupling in two and three dimensions: spontaneous channelling of porous fluids owing to decompaction weakening, Geophys. J. Int., 218, 1591–1616, https://doi.org/10.1093/gji/ggz239, 2019. a, b, c
Räss, L., Licul, A., Herman, F., Podladchikov, Y. Y., and Suckale, J.: Modelling thermomechanical ice deformation using an implicit pseudo-transient method (FastICE v1.0) based on graphical processing units (GPUs), Geosci. Model Dev., 13, 955–976, https://doi.org/10.5194/gmd-13-955-2020, 2020. a, b, c, d, e, f, g, h
Räss, L., Utkin, I., Duretz, T., Omlin, S., and Podladchikov, Y. Y.: Assessing the robustness and scalability of the accelerated pseudo-transient method, Geosci. Model Dev., 15, 5757–5786, https://doi.org/10.5194/gmd-15-5757-2022, 2022. a, b, c
Rietbroek, R., Brunnabend, S.-E., Kusche, J., Schröter, J., and Dahle, C.: Revisiting the contemporary sea-level budget on global and regional scales, P. Natl. Acad. Sci. USA, 113, 1504–1509, https://doi.org/10.1073/pnas.1519132113, 2016. a
Rignot, E., Mouginot, J., and Scheuchl, B.: Antarctic grounding line mapping from differential satellite radar interferometry, Geophys. Res. Lett., 38, 49, https://doi.org/10.1029/2011GL047109, 2011. a
Sandip, A., Morlighem, M., and Räss, L.: AnjaliSandip/FastIceFlo: FastIceFlo v1.0.1 (v1.0.1), Zenodo [code], https://doi.org/10.5281/zenodo.8356351, 2023. a
Tezaur, I. K., Perego, M., Salinger, A. G., Tuminaro, R. S., and Price, S. F.: Albany/FELIX: a parallel, scalable and robust, finite element, first-order Stokes approximation ice sheet solver built for advanced analysis, Geosci. Model Dev., 8, 1197–1220, https://doi.org/10.5194/gmd-8-1197-2015, 2015. a
Short summary
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.
We solve momentum balance for unstructured meshes to predict ice flow for real glaciers using a...
