Articles | Volume 15, issue 9
https://doi.org/10.5194/gmd-15-3753-2022
© Author(s) 2022. 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-15-3753-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A scalability study of the Ice-sheet and Sea-level System Model (ISSM, version 4.18)
Yannic Fischler
CORRESPONDING AUTHOR
Department of Computer Science, Technical University of Darmstadt, Darmstadt, Germany
Martin Rückamp
Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung, Bremerhaven, Germany
now at: Bavarian Academy of Sciences and Humanities, Munich, Germany
Christian Bischof
Department of Computer Science, Technical University of Darmstadt, Darmstadt, Germany
Vadym Aizinger
Chair of Scientific Computing, University of Bayreuth, Bayreuth, Germany
Mathieu Morlighem
Department of Earth Sciences, Dartmouth College, Hanover, NH, USA
Department of Earth System Science, University of California, Irvine, CA, USA
Angelika Humbert
Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung, Bremerhaven, Germany
Faculty of Geosciences, University of Bremen, Bremen, Germany
Related authors
Yannic Fischler, Thomas Kleiner, Christian Bischof, Jeremie Schmiedel, Roiy Sayag, Raban Emunds, Lennart Frederik Oestreich, and Angelika Humbert
Geosci. Model Dev., 16, 5305–5322, https://doi.org/10.5194/gmd-16-5305-2023, https://doi.org/10.5194/gmd-16-5305-2023, 2023
Short summary
Short summary
Water underneath ice sheets affects the motion of glaciers. This study presents a newly developed code, CUAS-MPI, that simulates subglacial hydrology. It is designed for supercomputers and is hence a parallelized code. We measure the performance of this code for simulations of the entire Greenland Ice Sheet and find that the code works efficiently. Moreover, we validated the code to ensure the correctness of the solution. CUAS-MPI opens new possibilities for simulations of ice sheet hydrology.
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
Short summary
Short summary
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.
Martin Rückamp, Gong Cheng, Karlheinz Gutjahr, Marco Möller, Petri K. E. Pellikka, and Christoph Mayer
EGUsphere, https://doi.org/10.5194/egusphere-2025-3150, https://doi.org/10.5194/egusphere-2025-3150, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
Short summary
The study simulates the 21st-century evolution of Great Aletsch Glacier and Hintereisferner using full-Stokes ice dynamics and surface mass balance under different emission scenarios. Results show significant ice loss, with Hintereisferner expected to disappear by mid-century. Great Aletsch Glacier vanish by the end of the century under high-emission scenarios, but persist under lower-emission scenarios. These trends agree with large-scale models except some variability.
Angelika Humbert, Veit Helm, Ole Zeising, Niklas Neckel, Matthias H. Braun, Shfaqat Abbas Khan, Martin Rückamp, Holger Steeb, Julia Sohn, Matthias Bohnen, and Ralf Müller
The Cryosphere, 19, 3009–3032, https://doi.org/10.5194/tc-19-3009-2025, https://doi.org/10.5194/tc-19-3009-2025, 2025
Short summary
Short summary
We study the evolution of a massive lake on the Greenland Ice Sheet using satellite and airborne data and some modelling. The lake is emptying rapidly. Water flows to the glacier's base through cracks and triangular-shaped moulins that remain visible over the years. Some of them become reactivated. We find features inside the glacier that stem from drainage events with a width of even 1 km. These features are persistent over the years, although they are changing in shape.
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
Short summary
Short summary
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
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
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
Short summary
Short summary
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.
Katrina Lutz, Ilaria Tabone, Angelika Humbert, and Matthias Braun
The Cryosphere, 19, 2601–2614, https://doi.org/10.5194/tc-19-2601-2025, https://doi.org/10.5194/tc-19-2601-2025, 2025
Short summary
Short summary
Supraglacial lakes develop from meltwater collecting on the surface of glaciers. These lakes can drain rapidly, discharging meltwater to the glacier bed. In this study, we assess the spatial and temporal distribution of rapid drainages in Northeast Greenland using optical satellite images. After comparing rapid drainage occurrence with several environmental and geophysical parameters, little indication of the influencing conditions for a rapid drainage was found.
Theresa Dobler, Wilfried Hagg, Martin Rückamp, Thorsten Seehaus, and Christoph Mayer
EGUsphere, https://doi.org/10.5194/egusphere-2025-2513, https://doi.org/10.5194/egusphere-2025-2513, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
Short summary
We studied how a glacier in the Austrian Alps moves more slowly over time due to climate change. By combining long-term field data with recent aerial images, we show how thinning reduce glacier flow. Standard satellite methods failed to detect this slow movement, so we used manual tracking to create a reliable map. Our findings help understand changes in glacier behavior in a warming climate.
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
Short summary
Short summary
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.
Lea-Sophie Höyns, Thomas Kleiner, Andreas Rademacher, Martin Rückamp, Michael Wolovick, and Angelika Humbert
The Cryosphere, 19, 2133–2158, https://doi.org/10.5194/tc-19-2133-2025, https://doi.org/10.5194/tc-19-2133-2025, 2025
Short summary
Short summary
The sliding of glaciers over bedrock is influenced by water pressure in the underlying hydrological system and the roughness of the land underneath the glacier. We estimate this roughness through a modeling approach that optimizes this unknown parameter. Additionally, we simulate water pressure, enhancing the reliability of the computed drag at the ice sheet base. The resulting data are provided to other modelers and scientists conducting geophysical field observations.
Torsten Kanzow, Angelika Humbert, Thomas Mölg, Mirko Scheinert, Matthias Braun, Hans Burchard, Francesca Doglioni, Philipp Hochreuther, Martin Horwath, Oliver Huhn, Maria Kappelsberger, Jürgen Kusche, Erik Loebel, Katrina Lutz, Ben Marzeion, Rebecca McPherson, Mahdi Mohammadi-Aragh, Marco Möller, Carolyne Pickler, Markus Reinert, Monika Rhein, Martin Rückamp, Janin Schaffer, Muhammad Shafeeque, Sophie Stolzenberger, Ralph Timmermann, Jenny Turton, Claudia Wekerle, and Ole Zeising
The Cryosphere, 19, 1789–1824, https://doi.org/10.5194/tc-19-1789-2025, https://doi.org/10.5194/tc-19-1789-2025, 2025
Short summary
Short summary
The Greenland Ice Sheet represents the second-largest contributor to global sea-level rise. We quantify atmosphere, ice and ocean processes related to the mass balance of glaciers in northeast Greenland, focusing on Greenland’s largest floating ice tongue, the 79° N Glacier. We find that together, the different in situ and remote sensing observations and model simulations reveal a consistent picture of a coupled atmosphere–ice sheet–ocean system that has entered a phase of major change.
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
Short summary
Short summary
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.
Jamie Barnett, Felicity Alice Holmes, Joshua Cuzzone, Henning Åkesson, Mathieu Morlighem, Matt O'Regan, Johan Nilsson, Nina Kirchner, and Martin Jakobsson
EGUsphere, https://doi.org/10.5194/egusphere-2025-653, https://doi.org/10.5194/egusphere-2025-653, 2025
Short summary
Short summary
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 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 are required to predict future changes and reliable sea level rise estimates.
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
Short summary
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.
Katrina Lutz, Lily Bever, Christian Sommer, Thorsten Seehaus, Angelika Humbert, Mirko Scheinert, and Matthias Braun
The Cryosphere, 18, 5431–5449, https://doi.org/10.5194/tc-18-5431-2024, https://doi.org/10.5194/tc-18-5431-2024, 2024
Short summary
Short summary
The estimation of the amount of water found within supraglacial lakes is important for understanding how much water is lost from glaciers each year. Here, we develop two new methods for estimating supraglacial lake volume that can be easily applied on a large scale. Furthermore, we compare these methods to two previously developed methods in order to determine when it is best to use each method. Finally, three of these methods are applied to peak melt dates over an area in Northeast Greenland.
Veit Helm, Alireza Dehghanpour, Ronny Hänsch, Erik Loebel, Martin Horwath, and Angelika Humbert
The Cryosphere, 18, 3933–3970, https://doi.org/10.5194/tc-18-3933-2024, https://doi.org/10.5194/tc-18-3933-2024, 2024
Short summary
Short summary
We present a new approach (AWI-ICENet1), based on a deep convolutional neural network, for analysing satellite radar altimeter measurements to accurately determine the surface height of ice sheets. Surface height estimates obtained with AWI-ICENet1 (along with related products, such as ice sheet height change and volume change) show improved and unbiased results compared to other products. This is important for the long-term monitoring of ice sheet mass loss and its impact on sea level rise.
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
Short summary
Short summary
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.
Erik Loebel, Mirko Scheinert, Martin Horwath, Angelika Humbert, Julia Sohn, Konrad Heidler, Charlotte Liebezeit, and Xiao Xiang Zhu
The Cryosphere, 18, 3315–3332, https://doi.org/10.5194/tc-18-3315-2024, https://doi.org/10.5194/tc-18-3315-2024, 2024
Short summary
Short summary
Comprehensive datasets of calving-front changes are essential for studying and modeling outlet glaciers. Current records are limited in temporal resolution due to manual delineation. We use deep learning to automatically delineate calving fronts for 23 glaciers in Greenland. Resulting time series resolve long-term, seasonal, and subseasonal patterns. We discuss the implications of our results and provide the cryosphere community with a data product and an implementation of our processing system.
Niko Schmidt, Angelika Humbert, and Thomas Slawig
Geosci. Model Dev., 17, 4943–4959, https://doi.org/10.5194/gmd-17-4943-2024, https://doi.org/10.5194/gmd-17-4943-2024, 2024
Short summary
Short summary
Future sea-level rise is of big significance for coastal regions. The melting and acceleration of glaciers plays a major role in sea-level change. Computer simulation of glaciers costs a lot of computational resources. In this publication, we test a new way of simulating glaciers. This approach produces the same results but has the advantage that it needs much less computation time. As simulations can be obtained with fewer computation resources, higher resolution and physics become affordable.
Ole Zeising, Niklas Neckel, Nils Dörr, Veit Helm, Daniel Steinhage, Ralph Timmermann, and Angelika Humbert
The Cryosphere, 18, 1333–1357, https://doi.org/10.5194/tc-18-1333-2024, https://doi.org/10.5194/tc-18-1333-2024, 2024
Short summary
Short summary
The 79° North Glacier in Greenland has experienced significant changes over the last decades. Due to extreme melt rates, the ice has thinned significantly in the vicinity of the grounding line, where a large subglacial channel has formed since 2010. We attribute these changes to warm ocean currents and increased subglacial discharge from surface melt. However, basal melting has decreased since 2018, indicating colder water inflow into the cavity below the glacier.
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
Short summary
Short summary
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
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Michael Wolovick, Angelika Humbert, Thomas Kleiner, and Martin Rückamp
The Cryosphere, 17, 5027–5060, https://doi.org/10.5194/tc-17-5027-2023, https://doi.org/10.5194/tc-17-5027-2023, 2023
Short summary
Short summary
The friction underneath ice sheets can be inferred from observed velocity at the top, but this inference requires smoothing. The selection of smoothing has been highly variable in the literature. Here we show how to rigorously select the best smoothing, and we show that the inferred friction converges towards the best knowable field as model resolution improves. We use this to learn about the best description of basal friction and to formulate recommended best practices for other modelers.
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
Short summary
Short summary
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.
Yannic Fischler, Thomas Kleiner, Christian Bischof, Jeremie Schmiedel, Roiy Sayag, Raban Emunds, Lennart Frederik Oestreich, and Angelika Humbert
Geosci. Model Dev., 16, 5305–5322, https://doi.org/10.5194/gmd-16-5305-2023, https://doi.org/10.5194/gmd-16-5305-2023, 2023
Short summary
Short summary
Water underneath ice sheets affects the motion of glaciers. This study presents a newly developed code, CUAS-MPI, that simulates subglacial hydrology. It is designed for supercomputers and is hence a parallelized code. We measure the performance of this code for simulations of the entire Greenland Ice Sheet and find that the code works efficiently. Moreover, we validated the code to ensure the correctness of the solution. CUAS-MPI opens new possibilities for simulations of ice sheet hydrology.
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
Short summary
Short summary
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.
Angelika Humbert, Veit Helm, Niklas Neckel, Ole Zeising, Martin Rückamp, Shfaqat Abbas Khan, Erik Loebel, Jörg Brauchle, Karsten Stebner, Dietmar Gross, Rabea Sondershaus, and Ralf Müller
The Cryosphere, 17, 2851–2870, https://doi.org/10.5194/tc-17-2851-2023, https://doi.org/10.5194/tc-17-2851-2023, 2023
Short summary
Short summary
The largest floating glacier mass in Greenland, the 79° N Glacier, is showing signs of instability. We investigate how crack formation at the glacier's calving front has changed over the last decades by using satellite imagery and airborne data. The calving front is about to lose contact to stabilizing ice islands. Simulations show that the glacier will accelerate as a result of this, leading to an increase in ice discharge of more than 5.1 % if its calving front retreats by 46 %.
Michael J. Bentley, James A. Smith, Stewart S. R. Jamieson, Margaret R. Lindeman, Brice R. Rea, Angelika Humbert, Timothy P. Lane, Christopher M. Darvill, Jeremy M. Lloyd, Fiamma Straneo, Veit Helm, and David H. Roberts
The Cryosphere, 17, 1821–1837, https://doi.org/10.5194/tc-17-1821-2023, https://doi.org/10.5194/tc-17-1821-2023, 2023
Short summary
Short summary
The Northeast Greenland Ice Stream is a major outlet of the Greenland Ice Sheet. Some of its outlet glaciers and ice shelves have been breaking up and retreating, with inflows of warm ocean water identified as the likely reason. Here we report direct measurements of warm ocean water in an unusual lake that is connected to the ocean beneath the ice shelf in front of the 79° N Glacier. This glacier has not yet shown much retreat, but the presence of warm water makes future retreat more likely.
Ole Zeising, Tamara Annina Gerber, Olaf Eisen, M. Reza Ershadi, Nicolas Stoll, Ilka Weikusat, and Angelika Humbert
The Cryosphere, 17, 1097–1105, https://doi.org/10.5194/tc-17-1097-2023, https://doi.org/10.5194/tc-17-1097-2023, 2023
Short summary
Short summary
The flow of glaciers and ice streams is influenced by crystal fabric orientation. Besides sparse ice cores, these can be investigated by radar measurements. Here, we present an improved method which allows us to infer the horizontal fabric asymmetry using polarimetric phase-sensitive radar data. A validation of the method on a deep ice core from the Greenland Ice Sheet shows an excellent agreement, which is a large improvement over previously used methods.
Angelika Humbert, Julia Christmann, Hugh F. J. Corr, Veit Helm, Lea-Sophie Höyns, Coen Hofstede, Ralf Müller, Niklas Neckel, Keith W. Nicholls, Timm Schultz, Daniel Steinhage, Michael Wolovick, and Ole Zeising
The Cryosphere, 16, 4107–4139, https://doi.org/10.5194/tc-16-4107-2022, https://doi.org/10.5194/tc-16-4107-2022, 2022
Short summary
Short summary
Ice shelves are normally flat structures that fringe the Antarctic continent. At some locations they have channels incised into their underside. On Filchner Ice Shelf, such a channel is more than 50 km long and up to 330 m high. We conducted field measurements of basal melt rates and found a maximum of 2 m yr−1. Simulations represent the geometry evolution of the channel reasonably well. There is no reason to assume that this type of melt channel is destabilizing ice shelves.
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
Short summary
Short summary
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
Short summary
Short summary
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.
M. Reza Ershadi, Reinhard Drews, Carlos Martín, Olaf Eisen, Catherine Ritz, Hugh Corr, Julia Christmann, Ole Zeising, Angelika Humbert, and Robert Mulvaney
The Cryosphere, 16, 1719–1739, https://doi.org/10.5194/tc-16-1719-2022, https://doi.org/10.5194/tc-16-1719-2022, 2022
Short summary
Short summary
Radio waves transmitted through ice split up and inform us about the ice sheet interior and orientation of single ice crystals. This can be used to infer how ice flows and improve projections on how it will evolve in the future. Here we used an inverse approach and developed a new algorithm to infer ice properties from observed radar data. We applied this technique to the radar data obtained at two EPICA drilling sites, where ice cores were used to validate our results.
Martin Rückamp, Thomas Kleiner, and Angelika Humbert
The Cryosphere, 16, 1675–1696, https://doi.org/10.5194/tc-16-1675-2022, https://doi.org/10.5194/tc-16-1675-2022, 2022
Short summary
Short summary
We present a comparative modelling study between the full-Stokes (FS) and Blatter–Pattyn (BP) approximation applied to the Northeast Greenland Ice Stream. Both stress regimes are implemented in one single ice sheet code to eliminate numerical issues. The simulations unveil minor differences in the upper ice stream but become considerable at the grounding line of the 79° North Glacier. Model differences are stronger for a power-law friction than a linear friction law.
Ole Zeising, Daniel Steinhage, Keith W. Nicholls, Hugh F. J. Corr, Craig L. Stewart, and Angelika Humbert
The Cryosphere, 16, 1469–1482, https://doi.org/10.5194/tc-16-1469-2022, https://doi.org/10.5194/tc-16-1469-2022, 2022
Short summary
Short summary
Remote-sensing-derived basal melt rates of ice shelves are of great importance due to their capability to cover larger areas. We performed in situ measurements with a phase-sensitive radar on the southern Filchner Ice Shelf, showing moderate melt rates and low small-scale spatial variability. The comparison with remote-sensing-based melt rates revealed large differences caused by the estimation of vertical strain rates from remote sensing velocity fields that modern fields can overcome.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Timm Schultz, Ralf Müller, Dietmar Gross, and Angelika Humbert
The Cryosphere, 16, 143–158, https://doi.org/10.5194/tc-16-143-2022, https://doi.org/10.5194/tc-16-143-2022, 2022
Short summary
Short summary
Firn is the interstage product between snow and ice. Simulations describing the process of firn densification are used in the context of estimating mass changes of the ice sheets and past climate reconstructions. The first stage of firn densification takes place in the upper few meters of the firn column. We investigate how well a material law describing the process of grain boundary sliding works for the numerical simulation of firn densification in this stage.
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
Short summary
Short summary
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.
Ole Zeising and Angelika Humbert
The Cryosphere, 15, 3119–3128, https://doi.org/10.5194/tc-15-3119-2021, https://doi.org/10.5194/tc-15-3119-2021, 2021
Short summary
Short summary
Greenland’s largest ice stream – the Northeast Greenland Ice Stream (NEGIS) – extends far into the interior of the ice sheet. Basal meltwater acts as a lubricant for glaciers and sustains sliding. Hence, observations of basal melt rates are of high interest. We performed two time series of precise ground-based radar measurements in the upstream region of NEGIS and found high melt rates of 0.19 ± 0.04 m per year.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Coen Hofstede, Sebastian Beyer, Hugh Corr, Olaf Eisen, Tore Hattermann, Veit Helm, Niklas Neckel, Emma C. Smith, Daniel Steinhage, Ole Zeising, and Angelika Humbert
The Cryosphere, 15, 1517–1535, https://doi.org/10.5194/tc-15-1517-2021, https://doi.org/10.5194/tc-15-1517-2021, 2021
Short summary
Short summary
Support Force Glacier rapidly flows into Filcher Ice Shelf of Antarctica. As we know little about this glacier and its subglacial drainage, we used seismic energy to map the transition area from grounded to floating ice where a drainage channel enters the ocean cavity. Soft sediments close to the grounding line are probably transported by this drainage channel. The constant ice thickness over the steeply dipping seabed of the ocean cavity suggests a stable transition and little basal 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
Short summary
Short summary
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
Short summary
Short summary
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.
Martin Rückamp, Heiko Goelzer, and Angelika Humbert
The Cryosphere, 14, 3309–3327, https://doi.org/10.5194/tc-14-3309-2020, https://doi.org/10.5194/tc-14-3309-2020, 2020
Short summary
Short summary
Estimates of future sea-level contribution from the Greenland ice sheet have a large uncertainty based on different origins. We conduct numerical experiments to test the sensitivity of Greenland ice sheet projections to spatial resolution. Simulations with a higher resolution unveil up to 5 % more sea-level rise compared to coarser resolutions. The sensitivity depends on the magnitude of outlet glacier retreat. When no retreat is enforced, the sensitivity exhibits an inverse behaviour.
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
Short summary
Short summary
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.
Heiko Goelzer, Sophie Nowicki, Anthony Payne, Eric Larour, Helene Seroussi, William H. Lipscomb, Jonathan Gregory, Ayako Abe-Ouchi, Andrew Shepherd, Erika Simon, Cécile Agosta, Patrick Alexander, Andy Aschwanden, Alice Barthel, Reinhard Calov, Christopher Chambers, Youngmin Choi, Joshua Cuzzone, Christophe Dumas, Tamsin Edwards, Denis Felikson, Xavier Fettweis, Nicholas R. Golledge, Ralf Greve, Angelika Humbert, Philippe Huybrechts, Sebastien Le clec'h, Victoria Lee, Gunter Leguy, Chris Little, Daniel P. Lowry, Mathieu Morlighem, Isabel Nias, Aurelien Quiquet, Martin Rückamp, Nicole-Jeanne Schlegel, Donald A. Slater, Robin S. Smith, Fiamma Straneo, Lev Tarasov, Roderik van de Wal, and Michiel van den Broeke
The Cryosphere, 14, 3071–3096, https://doi.org/10.5194/tc-14-3071-2020, https://doi.org/10.5194/tc-14-3071-2020, 2020
Short summary
Short summary
In this paper we use a large ensemble of Greenland ice sheet models forced by six different global climate models to project ice sheet changes and sea-level rise contributions over the 21st century.
The results for two different greenhouse gas concentration scenarios indicate that the Greenland ice sheet will continue to lose mass until 2100, with contributions to sea-level rise of 90 ± 50 mm and 32 ± 17 mm for the high (RCP8.5) and low (RCP2.6) scenario, respectively.
Hélène Seroussi, Sophie Nowicki, Antony J. Payne, Heiko Goelzer, William H. Lipscomb, Ayako Abe-Ouchi, Cécile Agosta, Torsten Albrecht, Xylar Asay-Davis, Alice Barthel, Reinhard Calov, Richard Cullather, Christophe Dumas, Benjamin K. Galton-Fenzi, Rupert Gladstone, Nicholas R. Golledge, Jonathan M. Gregory, Ralf Greve, Tore Hattermann, Matthew J. Hoffman, Angelika Humbert, Philippe Huybrechts, Nicolas C. Jourdain, Thomas Kleiner, Eric Larour, Gunter R. Leguy, Daniel P. Lowry, Chistopher M. Little, Mathieu Morlighem, Frank Pattyn, Tyler Pelle, Stephen F. Price, Aurélien Quiquet, Ronja Reese, Nicole-Jeanne Schlegel, Andrew Shepherd, Erika Simon, Robin S. Smith, Fiammetta Straneo, Sainan Sun, Luke D. Trusel, Jonas Van Breedam, Roderik S. W. van de Wal, Ricarda Winkelmann, Chen Zhao, Tong Zhang, and Thomas Zwinger
The Cryosphere, 14, 3033–3070, https://doi.org/10.5194/tc-14-3033-2020, https://doi.org/10.5194/tc-14-3033-2020, 2020
Short summary
Short summary
The Antarctic ice sheet has been losing mass over at least the past 3 decades in response to changes in atmospheric and oceanic conditions. This study presents an ensemble of model simulations of the Antarctic evolution over the 2015–2100 period based on various ice sheet models, climate forcings and emission scenarios. Results suggest that the West Antarctic ice sheet will continue losing a large amount of ice, while the East Antarctic ice sheet could experience increased snow accumulation.
Cited articles
Arzt, P., Fischler, Y., Lehr, J.-P., and Bischof, C.: Automatic Low-Overhead Load-Imbalance Detection in MPI Applications, in: EuroPar 2021, Springer International Publishing, Cham, 19–34, ISBN 978-3-030-85665-6, 2021. a
Aschwanden, A., Aðalgeirsdóttir, G., and Khroulev, C.: Hindcasting to measure ice sheet model sensitivity to initial states, The Cryosphere, 7, 1083–1093, https://doi.org/10.5194/tc-7-1083-2013, 2013. a
Balay, S., Abhyankar, S., Adams, M. F., Brown, J., Brune, P., Buschelman, K.,
Dalcin, L., Dener, A., Eijkhout, V., Gropp, W. D., Karpeyev, D., Kaushik, D.,
Knepley, M. G., May, D. A., McInnes, L. C., Mills, R. T., Munson, T., Rupp,
K., Sanan, P., Smith, B. F., Zampini, S., Zhang, H., and Zhang, H.: PETSc
Users Manual, Tech. Rep. ANL-95/11 - Revision 3.15, Argonne National
Laboratory, https://www.mcs.anl.gov/petsc (last access: 8 April 2022),
2021a. a
Balay, S., Abhyankar, S., Adams, M. F., Brown, J., Brune, P., Buschelman, K.,
Dalcin, L., Dener, A., Eijkhout, V., Gropp, W. D., Karpeyev, D., Kaushik, D.,
Knepley, M. G., May, D. A., McInnes, L. C., Mills, R. T., Munson, T., Rupp,
K., Sanan, P., Smith, B. F., Zampini, S., Zhang, H., and Zhang, H.: PETSc
Web page, https://www.mcs.anl.gov/petsc (last access: 8 April 2022), 2021b. a
Bauer, P., Düben, P. D., Hoefler, T., Quintino, T., Schulthess, T. C., and
Wedi, N. P.: The digital revolution of Earth-system science, Nature
Computat. Sci., 1, 104–113, 2021. a
Berends, C. J., Goelzer, H., and van de Wal, R. S. W.: The Utrecht Finite Volume Ice-Sheet Model: UFEMISM (version 1.0), Geosci. Model Dev., 14, 2443–2470, https://doi.org/10.5194/gmd-14-2443-2021, 2021. a
Blatter, H.: Velocity and stress fields in grounded glaciers: a simple
algorithm for including deviatoric stress gradients, J. Glaciol.,
41, 333–344, https://doi.org/10.3189/S002214300001621X, 1995. a, b
Bnà, S., Spisso, I., Olesen, M., and Rossi, G.: PETSc4FOAM: A Library to
plug-in PETSc into the OpenFOAM Framework, Tech. Rep. ANL-95/11 – Revision
3.15, PRACE, https://prace-ri.eu (last access: 8 April 2022), 2020. 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
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
Bueler, E. and Brown, J.: Shallow shelf approximation as a “sliding law” in a
thermodynamically coupled ice sheet model, J. Geophys. Res., 114,
https://doi.org/10.1029/2008JF001179, 2009. a
Calotoiu, A., Hoefler, T., Poke, M., and Wolf, F.: Using automated performance
modeling to find scalability bugs in complex codes, Extra-P,
https://doi.org/10.1145/2503210.2503277, 2013. a
Calov, R. and Greve, R.: A semi-analytical solution for the positive degree-day
model with stochastic temperature variations, J. Glaciol., 51,
173–175, https://doi.org/10.3189/172756505781829601, 2005. a
Chang, J., Nakshatrala, K., Knepley, M., and Johnsson, L.: A performance
spectrum for parallel computational frameworks that solve PDEs, Concurrency
and Computation: Practice and Experience, 30, e4401, https://doi.org/10.1002/cpe.4401,
2018. a
Church, J., Clark, P., Cazenave, A., Gregory,
J., Jevrejeva, S., Levermann, A., Merrifield, M.,
Milne, G., Nerem, R., Nunn, P., Payne, A., Pfeffer, W., Stammer, D., and Alakkat, U.: Sea
level change, in: Climate Change 2013: The Physical Science Basis. Working
Group I Contribution to the Fifth Assessment Report of the Intergovernmental
Panel on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., et al., Cambridge University Press,
Cambridge, 1137–1216, https://doi.org/10.1017/CBO9781107415324.026, 2013. a
Cornford, S. L., Seroussi, H., Asay-Davis, X. S., Gudmundsson, G. H., Arthern, R., Borstad, C., Christmann, J., Dias dos Santos, T., Feldmann, J., Goldberg, D., Hoffman, M. J., Humbert, A., Kleiner, T., Leguy, G., Lipscomb, W. H., Merino, N., Durand, G., Morlighem, M., Pollard, D., Rückamp, M., Williams, C. R., and Yu, H.: Results of the third Marine Ice Sheet Model Intercomparison Project (MISMIP+), The Cryosphere, 14, 2283–2301, https://doi.org/10.5194/tc-14-2283-2020, 2020. a
Crawford, A., Benn, D., Todd, J., Astrom, J., Bassis, J., and Zwinger, T.:
Marine ice-cliff instability modeling shows mixed-mode ice-cliff failure and
yields calving rate parameterization, Nat. Commun., 12, 2701,
https://doi.org/10.1038/s41467-021-23070-7, 2021. a
Dickens, P.: A Performance and Scalability Analysis of the MPI Based Tools
Utilized in a Large Ice Sheet Model Executing in a Multicore Environment, in:
Algorithms and Architectures for Parallel Processing, edited by: Wang, G.,
Zomaya, A., Martinez, G., and Li, K., Springer International
Publishing, Cham, 131–147, https://doi.org/10.1007/978-3-319-27140-8_10, 2015. a
dos Santos, T. D., Morlighem, M., Seroussi, H., Devloo, P. R. B., and Simões, J. C.: Implementation and performance of adaptive mesh refinement in the Ice Sheet System Model (ISSM v4.14), Geosci. Model Dev., 12, 215–232, https://doi.org/10.5194/gmd-12-215-2019, 2019. a
Edwards, T. L., Nowicki, S. M., Marzeion, B., Hock, R., Goelzer, H., Seroussi,
H., Jourdain, N., Slater, D. A., Turner, F. E., Smith, C. J., McKenna, C. M.,
Simon, E. G., Abe-Ouchi, A., Gregory, J. M., Larour, E. Y., Lipscomb, W. H.,
Payne, A. J., Shepherd, A. P., Agosta, C., Alexander, P. M., Albrecht, T.,
Anderson, B. M., Asay-Davis, X. S., Aschwanden, A., Barthel, A. M., Bliss,
A. K., Calov, R., Chambers, C., Champollion, N., Choi, Y., Cullather, R. I.,
Cuzzone, J. K., Dumas, C., Felikson, D., Fettweis, X., Fujita, K.,
Galton-Fenzi, B. K., Gladstone, R. M., Golledge, N. R., Greve, R.,
Hattermann, T., Hoffman, M. J., Humbert, A., Huss, M., Huybrechts, P.,
Immerzeel, W. W. W., Kleiner, T., Kraaijenbrink, P. D., Le clec'h, S., Lee,
V., Leguy, G. R., Little, C. M., Lowry, D. P., Malles, J. H., Martin, D. F.,
Maussion, F., Morlighem, M., O'Neill, J. F., Nias, I. J., Pattyn, F., Pelle,
T., Price, S. F., Quiquet, A., Radić, V., Reese, R., Rounce, D. R.,
Rückamp, M., Sakai, A., Shafer, C., Schlegel, N. J., Shannon, S. R.,
Smith, R. S., Straneo, F., Sun, S., Tarasov, L., Trusel, L. D., Van Breedam,
J., Van De Wal, R. S., Van Den Broeke, M. R., Winkelmann, R., Zekollari, H.,
Zhao, C., Zhang, T., and Zwinger, T.: Projected land ice contributions to
twenty-first-century sea level rise, Nature, 593, 74–82,
https://doi.org/10.1038/s41586-021-03302-y, 2021. a
Fischler, Y.: GMD 2021 ISSM v4.18 Source Code and Build Scripts, TU data lib [code], https://doi.org/10.48328/tudatalib-613, 2021a. a
Fischler, Y.: GMD 2021 ISSM on HHLR Scaling Profiles, TU data lib [data set], https://doi.org/10.48328/tudatalib-612, 2021b. a
Fischler, Y. and
Rückamp, M.: GMD 2021 ISSM Greenland Setup, TU data lib [data set], https://doi.org/10.48328/tudatalib-614, 2021. a
Gagliardini, O., Zwinger, T., Gillet-Chaulet, F., Durand, G., Favier, L., de Fleurian, B., Greve, R., Malinen, M., Martín, C., Råback, P., Ruokolainen, J., Sacchettini, M., Schäfer, M., Seddik, H., and Thies, J.: Capabilities and performance of Elmer/Ice, a new-generation ice sheet model, Geosci. Model Dev., 6, 1299–1318, https://doi.org/10.5194/gmd-6-1299-2013, 2013. a, b
Geimer, M., Wolf, F., Wylie, B., Ábrahám, E., Becker, D., and Mohr, B.: The
SCALASCA performance toolset architecture, Concurr. Comp.
Pract. E., 22, 702–719, https://doi.org/10.1002/cpe.1556, 2010. a
Goelzer, H., Nowicki, S., Payne, A., Larour, E., Seroussi, H., Lipscomb, W. H., Gregory, J., Abe-Ouchi, A., Shepherd, A., Simon, E., Agosta, C., Alexander, P., Aschwanden, A., Barthel, A., Calov, R., Chambers, C., Choi, Y., Cuzzone, J., Dumas, C., Edwards, T., Felikson, D., Fettweis, X., Golledge, N. R., Greve, R., Humbert, A., Huybrechts, P., Le clec'h, S., Lee, V., Leguy, G., Little, C., Lowry, D. P., Morlighem, M., Nias, I., Quiquet, A., Rückamp, M., Schlegel, N.-J., Slater, D. A., Smith, R. S., Straneo, F., Tarasov, L., van de Wal, R., and van den Broeke, M.: The future sea-level contribution of the Greenland ice sheet: a multi-model ensemble study of ISMIP6, The Cryosphere, 14, 3071–3096, https://doi.org/10.5194/tc-14-3071-2020, 2020. a, b, c
Golaz, J.-C., Caldwell, P. M., Van Roekel, L. P., Petersen, M. R., Tang, Q.,
Wolfe, J. D., Abeshu, G., Anantharaj, V., Asay-Davis, X. S., Bader, D. C.,
Baldwin, S. A., Bisht, G., Bogenschutz, P. A., Branstetter, M., Brunke,
M. A., Brus, S. R., Burrows, S. M., Cameron-Smith, P. J., Donahue, A. S.,
Deakin, M., Easter, R. C., Evans, K. J., Feng, Y., Flanner, M., Foucar,
J. G., Fyke, J. G., Griffin, B. M., Hannay, C., Harrop, B. E., Hoffman,
M. J., Hunke, E. C., Jacob, R. L., Jacobsen, D. W., Jeffery, N., Jones,
P. W., Keen, N. D., Klein, S. A., Larson, V. E., Leung, L. R., Li, H.-Y.,
Lin, W., Lipscomb, W. H., Ma, P.-L., Mahajan, S., Maltrud, M. E., Mametjanov,
A., McClean, J. L., McCoy, R. B., Neale, R. B., Price, S. F., Qian, Y.,
Rasch, P. J., Reeves Eyre, J. E. J., Riley, W. J., Ringler, T. D., Roberts,
A. F., Roesler, E. L., Salinger, A. G., Shaheen, Z., Shi, X., Singh, B.,
Tang, J., Taylor, M. A., Thornton, P. E., Turner, A. K., Veneziani, M., Wan,
H., Wang, H., Wang, S., Williams, D. N., Wolfram, P. J., Worley, P. H., Xie,
S., Yang, Y., Yoon, J.-H., Zelinka, M. D., Zender, C. S., Zeng, X., Zhang,
C., Zhang, K., Zhang, Y., Zheng, X., Zhou, T., and Zhu, Q.: The DOE E3SM
Coupled Model Version 1: Overview and Evaluation at Standard Resolution,
J. Adv. Model. Earth Sy., 11, 2089–2129,
https://doi.org/10.1029/2018MS001603, 2019. a
Graham, R. L., Woodall, T. S., and Squyres, J. M.: Open MPI: A Flexible High
Performance MPI, in: Parallel Processing and Applied Mathematics, edited by:
Wyrzykowski, R., Dongarra, J., Meyer, N., and Waśniewski, J., Springer Berlin Heidelberg, Berlin, Heidelberg,
228–239, https://doi.org/10.1007/11752578_29, 2006. 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
Hoffman, M. J., Perego, M., Price, S. F., Lipscomb, W. H., Zhang, T., Jacobsen, D., Tezaur, I., Salinger, A. G., Tuminaro, R., and Bertagna, L.: MPAS-Albany Land Ice (MALI): a variable-resolution ice sheet model for Earth system modeling using Voronoi grids, Geosci. Model Dev., 11, 3747–3780, https://doi.org/10.5194/gmd-11-3747-2018, 2018. a, b
Huang, X., Tang, Q., Tseng, Y., Hu, Y., Baker, A. H., Bryan, F. O., Dennis, J., Fu, H., and Yang, G.: P-CSI v1.0, an accelerated barotropic solver for the high-resolution ocean model component in the Community Earth System Model v2.0, Geosci. Model Dev., 9, 4209–4225, https://doi.org/10.5194/gmd-9-4209-2016, 2016. a
Isaac, T., Stadler, G., and Ghattas, O.: Solution of Nonlinear Stokes Equations
Discretized By High-Order Finite Elements on Nonconforming and Anisotropic
Meshes, with Application to Ice Sheet Dynamics, SIAM J. Sci.
Comput., 37, B804–B833, https://doi.org/10.1137/140974407, 2015. a
Joughin, I.: MEaSUREs Greenland Ice Sheet Mosaics from SAR Data, Version 1.
Boulder, Colorado USA, NASA National Snow and Ice Data Center Distributed
Active Archive Center, https://doi.org/10.5067/6187DQUL3FR5, 2015. a
Joughin, I., Smith, B. E., Howat, I. M., Moon, T., and Scambos, T. A.: A SAR
record of early 21st century change in Greenland, J. Glaciol.,
62, 62–71, https://doi.org/10.1017/jog.2016.10, 2016. a
Kleiner, T., Rückamp, M., Bondzio, J. H., and Humbert, A.: Enthalpy benchmark experiments for numerical ice sheet models, The Cryosphere, 9, 217–228, https://doi.org/10.5194/tc-9-217-2015, 2015. a
Knüpfer, A., Rössel, C., Mey, D. a., Biersdorff, S., Diethelm, K.,
Eschweiler, D., Geimer, M., Gerndt, M., Lorenz, D., Malony, A., Nagel, W. E.,
Oleynik, Y., Philippen, P., Saviankou, P., Schmidl, D., Shende, S.,
Tschüter, R., Wagner, M., Wesarg, B., and Wolf, F.: Score-P: A Joint
Performance Measurement Run-Time Infrastructure for Periscope,Scalasca, TAU,
and Vampir, in: Tools for High Performance Computing 2011, edited by: Brunst,
H., Müller, M. S., Nagel, W. E., and Resch, M. M., Springer
Berlin Heidelberg, Berlin, Heidelberg, 79–91, https://doi.org/10.1007/978-3-642-31476-6_7, 2012. a, b
Koldunov, N. V., Aizinger, V., Rakowsky, N., Scholz, P., Sidorenko, D., Danilov, S., and Jung, T.: Scalability and some optimization of the Finite-volumE Sea ice–Ocean Model, Version 2.0 (FESOM2), Geosci. Model Dev., 12, 3991–4012, https://doi.org/10.5194/gmd-12-3991-2019, 2019. a, b, c
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
Neumann, P., Düben, P., Adamidis, P., Bauer, P., Brück, M., Kornblueh,
L., Klocke, D., Stevens, B., Wedi, N., and Biercamp, J.: Assessing the scales
in numerical weather and climate predictions: Will exascale be the rescue?,
Philos. T. Roy. Soc. A, 377, 2142, https://doi.org/10.1098/rsta.2018.0148, 2019. a
Pattyn, F.: A new three-dimensional higher-order thermomechanical ice-sheet
model: basic sensitivity, ice-stream development and ice flow across
subglacial lakes, J. Geophys. Res., 108, 2382,
https://doi.org/10.1029/2002JB002329, 2003. a, b
Perlin, N., Zysman, J. P., and Kirtman, B. P.: Practical scalability assessment
for parallel scientific numerical applications, CoRR, abs/1611.01598,
https://doi.org/10.48550/arXiv.1611.01598, 2016. a, b
Plach, A., Nisancioglu, K. H., Langebroek, P. M., Born, A., and Le clec'h, S.: Eemian Greenland ice sheet simulated with a higher-order model shows strong sensitivity to surface mass balance forcing, The Cryosphere, 13, 2133–2148, https://doi.org/10.5194/tc-13-2133-2019, 2019. a
Prims, O. T., Castrillo, M., Acosta, M. C., Mula-Valls, O., Lorente, A. S.,
Serradell, K., Cortés, A., and Doblas-Reyes, F. J.: Finding, analysing and
solving MPI communication bottlenecks in Earth System models, J.
Comput. Sci., 36, 100864, https://doi.org/10.1016/j.jocs.2018.04.015, 2018. a
Reeh, N.: Parameterization of melt rate and surface temperature on the
Greenland ice sheet, Polarforschung, 59, 113–28, 1991. a
Reuter, B., Aizinger, V., and Köstler, H.: A multi-platform scaling study
for an OpenMP parallelization of a discontinuous Galerkin ocean model,
Comput. Fluids, 117, 325–335, 2015. a
Rückamp, M., Goelzer, H., and Humbert, A.: Sensitivity of Greenland ice sheet projections to spatial resolution in higher-order simulations: the Alfred Wegener Institute (AWI) contribution to ISMIP6 Greenland using the Ice-sheet and Sea-level System Model (ISSM), The Cryosphere, 14, 3309–3327, https://doi.org/10.5194/tc-14-3309-2020, 2020a. a, b
Rückamp, M., Humbert, A., Kleiner, T., Morlighem, M., and Seroussi, H.: Extended enthalpy formulations in the Ice-sheet and Sea-level System Model (ISSM) version 4.17: discontinuous conductivity and anisotropic streamline upwind Petrov–Galerkin (SUPG) method, Geosci. Model Dev., 13, 4491–4501, https://doi.org/10.5194/gmd-13-4491-2020, 2020b. a, b, c
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
Tallent, N. R., Mellor-Crummey, J. M., and Fagan, M. W.: Binary Analysis for
Measurement and Attribution of Program Performance, SIGPLAN Not., 44,
441–452, https://doi.org/10.1145/1543135.1542526, 2009. 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, 2015a. a
Tezaur, I. K., Tuminaro, R. S., Perego, M., Salinger, A. G., and Price, S. F.:
On the Scalability of the Albany/FELIX first-order Stokes
Approximation ice Sheet Solver for Large-Scale Simulations of the
Greenland and Antarctic ice Sheets, Procedia Comp. Sci., 51,
2026–2035, https://doi.org/10.1016/j.procs.2015.05.467, 2015b. a
Wriggers, P.: Nonlinear Finite Element Methods, Springer, Berlin, Heidelberg, 4, https://doi.org/10.1007/978-3-642-56865-7,
2008. a
Short summary
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.
Ice sheet models are used to simulate the changes of ice sheets in future but are currently...