Articles | Volume 16, issue 18
https://doi.org/10.5194/gmd-16-5305-2023
© Author(s) 2023. 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-16-5305-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
15 Sep 2023
Development and technical paper |
| 15 Sep 2023
| 15 Sep 2023
A parallel implementation of the confined–unconfined aquifer system model for subglacial hydrology: design, verification, and performance analysis (CUAS-MPI v0.1.0)
Yannic Fischler
CORRESPONDING AUTHOR
Department of Computer Science, Technical University Darmstadt, Darmstadt, Hesse, Germany
Thomas Kleiner
Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung, Bremerhaven, Bremen, Germany
Christian Bischof
Department of Computer Science, Technical University Darmstadt, Darmstadt, Hesse, Germany
Jeremie Schmiedel
Department of Environmental Physics, BIDR, Ben-Gurion University of the Negev, Sde Boker, Israel
Roiy Sayag
Department of Environmental Physics, BIDR, Ben-Gurion University of the Negev, Sde Boker, Israel
Raban Emunds
Department of Computer Science, Technical University Darmstadt, Darmstadt, Hesse, Germany
Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung, Bremerhaven, Bremen, Germany
Lennart Frederik Oestreich
Department of Computer Science, Technical University Darmstadt, Darmstadt, Hesse, Germany
Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung, Bremerhaven, Bremen, Germany
Angelika Humbert
Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung, Bremerhaven, Bremen, Germany
Faculty of Geosciences, University of Bremen, Bremen, Germany
Related authors
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
Short summary
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.
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.
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.
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.
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.
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.
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.
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.
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.
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
Short summary
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.
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.
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.
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.
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.
Christian B. Rodehacke, Madlene Pfeiffer, Tido Semmler, Özgür Gurses, and Thomas Kleiner
Earth Syst. Dynam., 11, 1153–1194, https://doi.org/10.5194/esd-11-1153-2020, https://doi.org/10.5194/esd-11-1153-2020, 2020
Short summary
Short summary
In the warmer future, Antarctica's ice sheet will lose more ice due to enhanced iceberg calving and a warming ocean that melts more floating ice from below. However, the hydrological cycle is also stronger in a warmer world. Hence, more snowfall will precipitate on Antarctica and may balance the amplified ice loss. We have used future climate scenarios from various global climate models to perform numerous ice sheet simulations to show that precipitation may counteract mass loss.
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
Ahlstrøm, A. P., Mottram, R., Nielsen, C., Reeh, N., and Andersen, S. B.:
Evaluation of the future hydropower potential at Paakitsoq, Ilulissat, West
Greenland, Tech. Rep. 31, GEUS, https://doi.org/10.22008/gpub/27154, 2009. a
Amestoy, P., Duff, I. S., Koster, J., and L'Excellent, J.-Y.: A Fully
Asynchronous Multifrontal Solver Using Distributed Dynamic Scheduling, SIAM
J. Matrix Anal. A., 23, 15–41, 2001. a
Amestoy, P., Buttari, A., L'Excellent, J.-Y., and Mary, T.: Performance and
Scalability of the Block Low-Rank Multifrontal Factorization on Multicore
Architectures, ACM T. Math. Software, 45, 2:1–2:26,
2019. a
Arnold, N. and Sharp, M.: Flow variability in the Scandinavian ice sheet:
modelling the coupling between ice sheet flow and hydrology, Quaternary
Sci. Rev., 21, 485–502, https://doi.org/10.1016/S0277-3791(01)00059-2, 2002. a
Aschwanden, A., Fahnestock, M. A., and Truffer, M.: Complex Greenland outlet
glacier flow captured, Nat. Commun., 7, 10524, https://doi.org/10.1038/ncomms10524,
2016. a, b
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://petsc.org/release/ (last access: 5 September 2023), 2021. a, b
Benn, D. I. and Evans, D. J. A.: Glaciers and glaciation, Routledge, 2nd edn.,
https://doi.org/10.4324/9780203785010, 2010. a
Bindschadler, R. A., Vornberger, P. L., King, M. A., and Padman, L.: Tidally
driven stick-slip motion in the mouth of Whillans Ice Stream,
Antarctica, Ann. Glaciol., 36, 263–272,
https://doi.org/10.3189/172756403781816284, 2003. a
Braithwaite, R. J. and Højmark Thomsen, H.: Simulation of Run-Off from the
Greenland Ice Sheet for Planning Hydro-Electric Power, Ilulissat/Jakobshavn,
West Greenland, Ann. Glaciol., 13, 12–15,
https://doi.org/10.3189/S0260305500007540, 1989. a
Budd, W. F. and Jenssen, D.: Numerical modelling of the large scale basal water
flux under the west Antarctic ice sheet., in: Dynamics of the west Antarctic
ice sheet, edited by: Van der Veen, C. J. and Oerlemens, J.,
Dordrecht, Reidel, 293–320, https://doi.org/10.1007/978-94-009-3745-1_16, 1987. a
Bueler, E. and van Pelt, W.: Mass-conserving subglacial hydrology in the Parallel Ice Sheet Model version 0.6, Geosci. Model Dev., 8, 1613–1635, https://doi.org/10.5194/gmd-8-1613-2015, 2015. a
Chourdakis, G., Davis, K., Rodenberg, B., Schulte, M., Simonis, F., Uekermann,
B., Abrams, G., Bungartz, H.-J., Yau, L. C., Desai, I., Eder, K., Hertrich,
R., Lindner, F., Rusch, A., Sashko, D., Schneider, D., Totounferoush, A.,
Volland, D., Vollmer, P., and Koseomur, O. Z.: preCICE v2: A sustainable
and user-friendly coupling library, Open Research Europe, 2, 51,
https://doi.org/10.12688/openreseurope.14445.2, 2022. a
Christmann, J., Helm, V., Khan, S. A., Kleiner, T., Müller, R., Morlighem,
M., Neckel, N., Rückamp, M., Steinhage, D., Zeising, O., and Humbert, A.:
Elastic deformation plays a non-negligible role in Greenland's outlet
glacier flow, Commun. Earth Environ., 2, 232,
https://doi.org/10.1038/s43247-021-00296-3, 2021. a
Colosio, P., Tedesco, M., Ranzi, R., and Fettweis, X.: Surface melting over the Greenland ice sheet derived from enhanced resolution passive microwave brightness temperatures (1979–2019), The Cryosphere, 15, 2623–2646, https://doi.org/10.5194/tc-15-2623-2021, 2021. a
Cook, S. J., Christoffersen, P., Todd, J., Slater, D., and Chauché, N.: Coupled modelling of subglacial hydrology and calving-front melting at Store Glacier, West Greenland , The Cryosphere, 14, 905–924, https://doi.org/10.5194/tc-14-905-2020, 2020. a
Cook, S. J., Christoffersen, P., and Todd, J.: A fully-coupled 3D model of a
large Greenlandic outlet glacier with evolving subglacial hydrology,
frontal plume melting and calving, J. Glaciol., 68, 486–502,
https://doi.org/10.1017/jog.2021.109, 2022. a
de Fleurian, B., Gagliardini, O., Zwinger, T., Durand, G., Le Meur, E., Mair, D., and Råback, P.: A double continuum hydrological model for glacier applications, The Cryosphere, 8, 137–153, https://doi.org/10.5194/tc-8-137-2014, 2014. a, b, c
de Fleurian, B., Morlighem, M., Seroussi, H., Rignot, E., van den Broeke,
M. R., Munneke, P. K., Mouginot, J., Smeets, P. C. J. P., and Tedstone,
A. J.: A modeling study of the effect of runoff variability on the effective
pressure beneath Russell Glacier, West Greenland, J.
Geophys. Res.-Earth, 121, 1834–1848,
https://doi.org/10.1002/2016jf003842, 2016. a, b
Dow, C. F.: The role of subglacial hydrology in Antarctic ice sheet dynamics
and stability: a modelling perspective, Ann. Glaciol., 1–6,
https://doi.org/10.1017/aog.2023.9, 2023. a
Dow, C. F., Ross, N., Jeofry, H., Siu, K., and Siegert, M. J.: Antarctic basal
environment shaped by high-pressure flow through a subglacial river system,
Nat. Geosci., 15, 892–898, https://doi.org/10.1038/s41561-022-01059-1, 2022. a
Ehlig, C. and Halepaska, J. C.: A numerical study of confined-unconfined
aquifers including effects of delayed yield and leakage, Water Resour.
Res., 12, 1175–183, https://doi.org/10.1029/WR012i006p01175, 1976. a, b, c
Ehrenfeucht, S., Morlighem, M., Rignot, E., Dow, C. F., and Mouginot, J.:
Seasonal Acceleration of Petermann Glacier, Greenland, From Changes in
Subglacial Hydrology, Geophys. Res. Lett., 50, e2022GL098009,
https://doi.org/10.1029/2022GL098009, 2023. a
Engelhardt, H. and Kamb, B.: Basal sliding of Ice Stream B, West
Antarctica, J. Glaciol., 44, 223–230,
https://doi.org/10.3189/S0022143000002562, 1997. a
Ferris, J. G., Knowles, D. B., Brown, R. H., and Stallman, R. W.: Theory of
Aquifer Tests, Tech. rep., U.S. Government Print. Office,
https://doi.org/10.3133/wsp1536E, 1962. a, b, c, d
Ferziger, J. H. and Perić, M.: Computational Methods for Fluid Dynamics,
Springer, 3rd edn., https://doi.org/10.1007/978-3-642-56026-2, 2002. a
Fischler, Y.: GMD 2022 CUAS-MPI on HHLR Scaling Profiles, TUdatalib [data set], https://doi.org/10.48328/tudatalib-1034, 2022. a
Fischler, Y., Rückamp, M., Bischof, C., Aizinger, V., Morlighem, M., and Humbert, A.: A scalability study of the Ice-sheet and Sea-level System Model (ISSM, version 4.18), Geosci. Model Dev., 15, 3753–3771, https://doi.org/10.5194/gmd-15-3753-2022, 2022. a
Fischler, Y., Kleiner, T., Bischof, C., Schmiedel, J., Sayag, R., Emunds, R., Oestreich, L. F., and Humbert, A.: A parallel implementation of the confined-unconfined aquifer system model for subglacial hydrology: design, verification, and performance analysis (CUAS-MPI v0.1.0) (0.1.0), Zenodo [code], https://doi.org/10.5281/zenodo.7554686, 2023. a
Flowers, G. E.: Modelling water flow under glaciers and ice sheets, P. Roy. Soc. A, 471,
20140907, https://doi.org/10.1098/rspa.2014.0907, 2015. a
Flowers, G. E. and Clarke, G. K. C.: A multicomponent coupled model of glacier
hydrology 1. Theory and synthetic examples, J. Geophys. Res.-Sol. Ea., 107, 2287, https://doi.org/10.1029/2001JB001122, 2002. a
Fountain, A. G. and Walder, J. S.: Water flow through temperate glaciers,
Rev. Geophys., 36, 299–328, https://doi.org/10.1029/97RG03579,
1998. a
Fowler, A. C.: A theory of glacier surges, J. Geophys. Res., 92,
9111–9120, https://doi.org/10.1029/JB092iB09p09111, 1987. a
Franke, S., Jansen, D., Beyer, S., Neckel, N., Binder, T., Paden, J., and
Eisen, O.: Complex Basal Conditions and Their Influence on Ice Flow at the
Onset of the Northeast Greenland Ice Stream, J. Geophys. Res.-Earth, 126, e2020JF005689, https://doi.org/10.1029/2020jf005689, 2021. 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
Hartnett, E. and Edwards, J.: The parallelio (pio) c/fortran libraries for
scalable hpc performance, in: 37th Conference on Environmental Information
Processing Technologies, American Meteorological Society Annual Meeting,,
2021. a
Hewitt, I. J.: Modelling distributed and channelized subglacial drainage: the
spacing of channels, J. Glaciol., 57, 302–314,
https://doi.org/10.3189/002214311796405951, 2011. a
Hoffman, M. J., Catania, G. A., Neumann, T. A., Andrews, L. C., and Rumrill,
J. A.: Links between acceleration, melting, and supraglacial lake drainage of
the western Greenland Ice Sheet, J. Geophys. Res.-Earth, 116, F04035, https://doi.org/10.1029/2010JF001934, 2011. a
Jacob, C. E.: Determining the permeability of water-table aquifers, in: Methods
of determining permeability, transmissibility and drawdown, edited by
Bentall, R., no. 1536 in Geological survey water-supply paper, chap. I,
272–292, US Government Printing Office,
https://pubs.usgs.gov/wsp/1536i/report.pdf (last access: 5 September 2023), 1963. a, b
Joughin, I., Smith, B., Howat, I., and Scambos, T.: MEaSUREs Multi-year
Greenland Ice Sheet Velocity Mosaic, Version 1, Boulder, Colorado USA, NASA
National Snow and Ice Data Center Distributed Active Archive Center,
https://doi.org/10.5067/QUA5Q9SVMSJG, 2016. a
Joughin, I., Smith, B. E., and Howat, I. M.: A complete map of Greenland ice
velocity derived from satellite data collected over 20 years, J. Glaciol.,
64, 243, https://doi.org/10.1017/jog.2017.73, 2018. a
Kleiner, T. and Humbert, A.: Numerical simulations of major ice streams in
western Dronning Maud Land, Antarctica, under wet and dry basal
conditions, J. Glaciol., 60, 215–232, https://doi.org/10.3189/2014JoG13J006,
2014. 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
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, F01022, https://doi.org/10.1029/2011JF002140, 2012. a
Latham, R., Zingale, M., Thakur, R., Gropp, W., Gallagher, B., Liao, W.,
Siegel, A., Ross, R., Choudhary, A., and Li, J.: Parallel netCDF: A
High-Performance Scientific I/O Interface, in: SC Conference, p. 39, IEEE
Computer Society, Los Alamitos, CA, USA, SC Conference 2003, 15–21 November, https://doi.org/10.1109/SC.2003.10053, 2003. a
Le Brocq, A. M., Payne, A. J., Siegert, M. J., and Alley, R. B.: A subglacial
water-flow model for West Antarctica, J. Glaciol., 55, 879–888,
https://doi.org/10.3189/002214309790152564, 2009. a
Lliboutry, L.: Glissement d'un glacier sur un plan de parsemé d'obstacles
hémisphériques, Ann. Géophys., 34, 147–162, 1978. a
MacGregor, J. A., Chu, W., Colgan, W. T., Fahnestock, M. A., Felikson, D., Karlsson, N. B., Nowicki, S. M. J., and Studinger, M.: GBaTSv2: a revised synthesis of the likely basal thermal state of the Greenland Ice Sheet, The Cryosphere, 16, 3033–3049, https://doi.org/10.5194/tc-16-3033-2022, 2022. a
Morlighem, M., Williams, C. N., Rignot, E., An, L., Arndt, J. E., Bamber,
J. L., Catania, G., Chauché, N., Dowdeswell, J. A., Dorschel, B.,
Fenty, I., Hogan, K., Howat, I., Hubbard, A., Jakobsson, M., Jordan, T. M.,
Kjeldsen, K. K., Millan, R., Mayer, L., Mouginot, J., Noël, B. P. Y.,
O'Cofaigh, C., Palmer, S., Rysgaard, S., Seroussi, H.,
Siegert, M. J., Slabon, P., Straneo, F., van den Broeke, M. R., Weinrebe, W.,
Wood, M., and Zinglersen, K. B.: BedMachine v3: Complete Bed Topography and
Ocean Bathymetry Mapping of Greenland From Multibeam Echo Sounding Combined
With Mass Conservation, Geophys. Res. Lett., 44, 11051–11061,
https://doi.org/10.1002/2017gl074954, 2017. a
Morlighem, M. E. A.: IceBridge BedMachine Greenland, Version 4,
IceBridge BedMachine Greenland, Version 4 [data Set], https://doi.org/10.5067/VLJ5YXKCNGXO, 2021. a
Neckel, N., Zeising, O., Steinhage, D., Helm, V., and Humbert, A.: Seasonal
Observations at 79∘N Glacier (Greenland) From Remote Sensing
and in situ Measurements, Front. Earth Sci., 8, 142,
https://doi.org/10.3389/feart.2020.00142, 2020. a
Nowicki, S. M. J., Payne, A., Larour, E., Seroussi, H., Goelzer, H., Lipscomb, W., Gregory, J., Abe-Ouchi, A., and Shepherd, A.: Ice Sheet Model Intercomparison Project (ISMIP6) contribution to CMIP6, Geosci. Model Dev., 9, 4521–4545, https://doi.org/10.5194/gmd-9-4521-2016, 2016. a
Orgogozo, L., Renon, N., Soulaine, C., Hénon, F., Tomer, S., Labat, D.,
Pokrovsky, O., Sekhar, M., Ababou, R., and Quintard, M.: An open source
massively parallel solver for Richards equation: Mechanistic modelling of
water fluxes at the watershed scale, Comput. Phys. Commun., 185,
3358–3371, https://doi.org/10.1016/j.cpc.2014.08.004, 2014. a
Patankar, S. V.: Numerical Heat Transfer and Fluid Flow, McGraw-Hill, New York,
1980. a
Rew, R. and Davis, G.: NetCDF: an interface for scientific data access,
IEEE Comput. Graph., 10, 76–82, https://doi.org/10.1109/38.56302, 1990. a, b
Schröder, L., Neckel, N., Zindler, R., and Humbert, A.: Perennial
Supraglacial Lakes in Northeast Greenland Observed by Polarimetric SAR,
Remote Sensing, 12, 2798, https://doi.org/10.3390/rs12172798, 2020. a
Seroussi, H., Nowicki, S., Payne, A. J., Goelzer, H., Lipscomb, W. H., Abe-Ouchi, A., Agosta, C., Albrecht, T., Asay-Davis, X., Barthel, A., Calov, R., Cullather, R., Dumas, C., Galton-Fenzi, B. K., Gladstone, R., Golledge, N. R., Gregory, J. M., Greve, R., Hattermann, T., Hoffman, M. J., Humbert, A., Huybrechts, P., Jourdain, N. C., Kleiner, T., Larour, E., Leguy, G. R., Lowry, D. P., Little, C. M., Morlighem, M., Pattyn, F., Pelle, T., Price, S. F., Quiquet, A., Reese, R., Schlegel, N.-J., Shepherd, A., Simon, E., Smith, R. S., Straneo, F., Sun, S., Trusel, L. D., Van Breedam, J., van de Wal, R. S. W., Winkelmann, R., Zhao, C., Zhang, T., and Zwinger, T.: ISMIP6 Antarctica: a multi-model ensemble of the Antarctic ice sheet evolution over the 21st century, The Cryosphere, 14, 3033–3070, https://doi.org/10.5194/tc-14-3033-2020, 2020. a, b
Siegert, M. J.: Antarctic subglacial lakes, Earth-Sci. Rev., 50, 29–50,
https://doi.org/10.1016/S0012-8252(99)00068-9, 2000. a
Smith-Johnsen, S., de Fleurian, B., and Nisancioglu, K. H.: The role of
subglacial hydrology in ice streams with elevated geothermal heat flux,
J. Glaciol., 66, 303–312, https://doi.org/10.1017/jog.2020.8, 2020. a
Sommers, A., Rajaram, H., and Morlighem, M.: SHAKTI: Subglacial Hydrology and Kinetic, Transient Interactions v1.0, Geosci. Model Dev., 11, 2955–2974, https://doi.org/10.5194/gmd-11-2955-2018, 2018. a
Theis, C. V.: The relation between the lowering of the Piezometric surface and
the rate and duration of discharge of a well using ground-water storage, Eos,
Transactions American Geophysical Union, 16, 519–524,
https://doi.org/10.1029/TR016i002p00519, 1935. a, b
van der Walt, S., Schönberger, J. L., Nunez-Iglesias, J., Boulogne, F.,
Warner, J. D., Yager, N., Gouillart, E., Yu, T., and the scikit-image
contributors: scikit-image: image processing in Python, PeerJ, 2, e453,
https://doi.org/10.7717/peerj.453, 2014.
a
Werder, M. A., Hewitt, I. J., Schoof, C. G., and Flowers, G.: Modeling
channelized and distributed subglacial drainage in two dimensions, J.
Geophys. Res.-Earth, 118, 2140–2158,
https://doi.org/10.1002/jgrf.20146, 2013. a
Young, T. J., Christoffersen, P., Bougamont, M., and Stewart, C. L.: Rapid
basal melting of the Greenland Ice Sheet from surface meltwater drainage,
P. Natl. Acad. Sci. USA, 119, e2116036119, https://doi.org/10.1073/pnas.2116036119, 2022. a
Zeising, O. and Humbert, A.: Indication of high basal melting at the EastGRIP drill site on the Northeast Greenland Ice Stream, The Cryosphere, 15, 3119–3128, https://doi.org/10.5194/tc-15-3119-2021, 2021. a
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.
Water underneath ice sheets affects the motion of glaciers. This study presents a newly...
