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
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Yannic Fischler, Martin Rückamp, Christian Bischof, Vadym Aizinger, Mathieu Morlighem, and Angelika Humbert
Geosci. Model Dev., 15, 3753–3771, https://doi.org/10.5194/gmd-15-3753-2022, https://doi.org/10.5194/gmd-15-3753-2022, 2022
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Ice sheet models are used to simulate the changes of ice sheets in future but are currently often run in coarse resolution and/or with neglecting important physics to make them affordable in terms of computational costs. We conducted a study simulating the Greenland Ice Sheet in high resolution and adequate physics to test where the ISSM ice sheet code is using most time and what could be done to improve its performance for future computer architectures that allow massive parallel computing.
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The Cryosphere, 18, 5431–5449, https://doi.org/10.5194/tc-18-5431-2024, https://doi.org/10.5194/tc-18-5431-2024, 2024
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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.
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EGUsphere, https://doi.org/10.5194/egusphere-2024-3056, https://doi.org/10.5194/egusphere-2024-3056, 2024
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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.
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The Cryosphere, 18, 3933–3970, https://doi.org/10.5194/tc-18-3933-2024, https://doi.org/10.5194/tc-18-3933-2024, 2024
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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
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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.
Lea-Sophie Höyns, Thomas Kleiner, Andreas Rademacher, Martin Rückamp, Michael Wolovick, and Angelika Humbert
EGUsphere, https://doi.org/10.5194/egusphere-2024-1251, https://doi.org/10.5194/egusphere-2024-1251, 2024
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Glaciers' sliding over bedrock is governed by water pressure in the hydrological system underneath the glacier and the roughness of the land underneath the glacier. We estimate this roughness using a modelling approach, which optimises this unknown parameter. The water pressure is simulated, too, which improves the robustness of the computed drag at the ice sheet base. We provide this data to other modellers and scientists doing geophysical field observations.
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
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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.
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
EGUsphere, https://doi.org/10.5194/egusphere-2024-1151, https://doi.org/10.5194/egusphere-2024-1151, 2024
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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. The water flows to the base of the glacier through cracks and gullies that remain visible over years. Some of them become reactive. We find features inside the glacier that stem from the drainage events with even 1 km width. These features are persistent over the years, although they are changing in shape.
Torsten Kanzow, Angelika Humbert, Thomas Mölg, Mirko Scheinert, Matthias Braun, Hans Burchard, Francesca Doglioni, Philipp Hochreuther, Martin Horwath, Oliver Huhn, 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
EGUsphere, https://doi.org/10.5194/egusphere-2024-757, https://doi.org/10.5194/egusphere-2024-757, 2024
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The Greenland Ice Sheet represents the second-largest contributor to global sea-level rise. We quantify atmosphere, ice and ocean-based processes related to the mass balance of glaciers in Northeast Greenland, focusing on Greenland’s largest floating ice tongue, the 79N Glacier. We find that together, the different in situ and remote sensing observations and model simulations to reveal a consistent picture of a coupled atmosphere-ice sheet-ocean system, that has entered a phase of major change.
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
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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
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Mass loss from Antarctica is a key contributor to sea level rise over the 21st century, and the associated uncertainty dominates sea level projections. We highlight here the Antarctic glaciers showing the largest changes and quantify the main sources of uncertainty in their future evolution using an ensemble of ice flow models. We show that on top of Pine Island and Thwaites glaciers, Totten and Moscow University glaciers show rapid changes and a strong sensitivity to warmer ocean conditions.
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
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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
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This paper presents the release of over 60 years of ice thickness, bed elevation, and surface elevation data acquired over Antarctica by the international community. These data are a crucial component of the Antarctic Bedmap initiative which aims to produce a new map and datasets of Antarctic ice thickness and bed topography for the international glaciology and geophysical community.
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
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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
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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
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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
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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
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Ice sheet models are used to simulate the changes of ice sheets in future but are currently often run in coarse resolution and/or with neglecting important physics to make them affordable in terms of computational costs. We conducted a study simulating the Greenland Ice Sheet in high resolution and adequate physics to test where the ISSM ice sheet code is using most time and what could be done to improve its performance for future computer architectures that allow massive parallel computing.
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
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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
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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
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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
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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
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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
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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
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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
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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
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We present enthalpy formulations within the Ice-Sheet and Sea-Level System model that show better performance than earlier implementations. A first experiment indicates that the treatment of discontinuous conductivities of the solid–fluid system with a geometric mean produce accurate results when applied to coarse vertical resolutions. In a second experiment, we propose a novel stabilization formulation that avoids the problem of thin elements. This method provides accurate and stable results.
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
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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
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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.
Tuukka Petäjä, Ella-Maria Duplissy, Ksenia Tabakova, Julia Schmale, Barbara Altstädter, Gerard Ancellet, Mikhail Arshinov, Yurii Balin, Urs Baltensperger, Jens Bange, Alison Beamish, Boris Belan, Antoine Berchet, Rossana Bossi, Warren R. L. Cairns, Ralf Ebinghaus, Imad El Haddad, Beatriz Ferreira-Araujo, Anna Franck, Lin Huang, Antti Hyvärinen, Angelika Humbert, Athina-Cerise Kalogridis, Pavel Konstantinov, Astrid Lampert, Matthew MacLeod, Olivier Magand, Alexander Mahura, Louis Marelle, Vladimir Masloboev, Dmitri Moisseev, Vaios Moschos, Niklas Neckel, Tatsuo Onishi, Stefan Osterwalder, Aino Ovaska, Pauli Paasonen, Mikhail Panchenko, Fidel Pankratov, Jakob B. Pernov, Andreas Platis, Olga Popovicheva, Jean-Christophe Raut, Aurélie Riandet, Torsten Sachs, Rosamaria Salvatori, Roberto Salzano, Ludwig Schröder, Martin Schön, Vladimir Shevchenko, Henrik Skov, Jeroen E. Sonke, Andrea Spolaor, Vasileios K. Stathopoulos, Mikko Strahlendorff, Jennie L. Thomas, Vito Vitale, Sterios Vratolis, Carlo Barbante, Sabine Chabrillat, Aurélien Dommergue, Konstantinos Eleftheriadis, Jyri Heilimo, Kathy S. Law, Andreas Massling, Steffen M. Noe, Jean-Daniel Paris, André S. H. Prévôt, Ilona Riipinen, Birgit Wehner, Zhiyong Xie, and Hanna K. Lappalainen
Atmos. Chem. Phys., 20, 8551–8592, https://doi.org/10.5194/acp-20-8551-2020, https://doi.org/10.5194/acp-20-8551-2020, 2020
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The role of polar regions is increasing in terms of megatrends such as globalization, new transport routes, demography, and the use of natural resources with consequent effects on regional and transported pollutant concentrations. Here we summarize initial results from our integrative project exploring the Arctic environment and pollution to deliver data products, metrics, and indicators for stakeholders.
Stephen L. Cornford, Helene Seroussi, Xylar S. Asay-Davis, G. Hilmar Gudmundsson, Rob Arthern, Chris Borstad, Julia Christmann, Thiago Dias dos Santos, Johannes Feldmann, Daniel Goldberg, Matthew J. Hoffman, Angelika Humbert, Thomas Kleiner, Gunter Leguy, William H. Lipscomb, Nacho Merino, Gaël Durand, Mathieu Morlighem, David Pollard, Martin Rückamp, C. Rosie Williams, and Hongju Yu
The Cryosphere, 14, 2283–2301, https://doi.org/10.5194/tc-14-2283-2020, https://doi.org/10.5194/tc-14-2283-2020, 2020
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We present the results of the third Marine Ice Sheet Intercomparison Project (MISMIP+). MISMIP+ is one in a series of exercises that test numerical models of ice sheet flow in simple situations. This particular exercise concentrates on the response of ice sheet models to the thinning of their floating ice shelves, which is of interest because numerical models are currently used to model the response to contemporary and near-future thinning in Antarctic ice shelves.
Michael Kern, Robert Cullen, Bruno Berruti, Jerome Bouffard, Tania Casal, Mark R. Drinkwater, Antonio Gabriele, Arnaud Lecuyot, Michael Ludwig, Rolv Midthassel, Ignacio Navas Traver, Tommaso Parrinello, Gerhard Ressler, Erik Andersson, Cristina Martin-Puig, Ole Andersen, Annett Bartsch, Sinead Farrell, Sara Fleury, Simon Gascoin, Amandine Guillot, Angelika Humbert, Eero Rinne, Andrew Shepherd, Michiel R. van den Broeke, and John Yackel
The Cryosphere, 14, 2235–2251, https://doi.org/10.5194/tc-14-2235-2020, https://doi.org/10.5194/tc-14-2235-2020, 2020
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The Copernicus Polar Ice and Snow Topography Altimeter will provide high-resolution sea ice thickness and land ice elevation measurements and the capability to determine the properties of snow cover on ice to serve operational products and services of direct relevance to the polar regions. This paper describes the mission objectives, identifies the key contributions the CRISTAL mission will make, and presents a concept – as far as it is already defined – for the mission payload.
Anders Levermann, Ricarda Winkelmann, Torsten Albrecht, Heiko Goelzer, Nicholas R. Golledge, Ralf Greve, Philippe Huybrechts, Jim Jordan, Gunter Leguy, Daniel Martin, Mathieu Morlighem, Frank Pattyn, David Pollard, Aurelien Quiquet, Christian Rodehacke, Helene Seroussi, Johannes Sutter, Tong Zhang, Jonas Van Breedam, Reinhard Calov, Robert DeConto, Christophe Dumas, Julius Garbe, G. Hilmar Gudmundsson, Matthew J. Hoffman, Angelika Humbert, Thomas Kleiner, William H. Lipscomb, Malte Meinshausen, Esmond Ng, Sophie M. J. Nowicki, Mauro Perego, Stephen F. Price, Fuyuki Saito, Nicole-Jeanne Schlegel, Sainan Sun, and Roderik S. W. van de Wal
Earth Syst. Dynam., 11, 35–76, https://doi.org/10.5194/esd-11-35-2020, https://doi.org/10.5194/esd-11-35-2020, 2020
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We provide an estimate of the future sea level contribution of Antarctica from basal ice shelf melting up to the year 2100. The full uncertainty range in the warming-related forcing of basal melt is estimated and applied to 16 state-of-the-art ice sheet models using a linear response theory approach. The sea level contribution we obtain is very likely below 61 cm under unmitigated climate change until 2100 (RCP8.5) and very likely below 40 cm if the Paris Climate Agreement is kept.
Johannes Sutter, Hubertus Fischer, Klaus Grosfeld, Nanna B. Karlsson, Thomas Kleiner, Brice Van Liefferinge, and Olaf Eisen
The Cryosphere, 13, 2023–2041, https://doi.org/10.5194/tc-13-2023-2019, https://doi.org/10.5194/tc-13-2023-2019, 2019
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The Antarctic Ice Sheet may have played an important role in moderating the transition between warm and cold climate epochs over the last million years. We find that the Antarctic Ice Sheet grew considerably about 0.9 Myr ago, a time when ice-age–warm-age cycles changed from a
40 000 to a 100 000 year periodicity. Our findings also suggest that ice as old as 1.5 Myr still exists at the bottom of the East Antarctic Ice Sheet despite the major climate reorganisations in the past.
Anna Winter, Daniel Steinhage, Timothy T. Creyts, Thomas Kleiner, and Olaf Eisen
Earth Syst. Sci. Data, 11, 1069–1081, https://doi.org/10.5194/essd-11-1069-2019, https://doi.org/10.5194/essd-11-1069-2019, 2019
Hélène Seroussi, Sophie Nowicki, Erika Simon, Ayako Abe-Ouchi, Torsten Albrecht, Julien Brondex, Stephen Cornford, Christophe Dumas, Fabien Gillet-Chaulet, Heiko Goelzer, Nicholas R. Golledge, Jonathan M. Gregory, Ralf Greve, Matthew J. Hoffman, Angelika Humbert, Philippe Huybrechts, Thomas Kleiner, Eric Larour, Gunter Leguy, William H. Lipscomb, Daniel Lowry, Matthias Mengel, Mathieu Morlighem, Frank Pattyn, Anthony J. Payne, David Pollard, Stephen F. Price, Aurélien Quiquet, Thomas J. Reerink, Ronja Reese, Christian B. Rodehacke, Nicole-Jeanne Schlegel, Andrew Shepherd, Sainan Sun, Johannes Sutter, Jonas Van Breedam, Roderik S. W. van de Wal, Ricarda Winkelmann, and Tong Zhang
The Cryosphere, 13, 1441–1471, https://doi.org/10.5194/tc-13-1441-2019, https://doi.org/10.5194/tc-13-1441-2019, 2019
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We compare a wide range of Antarctic ice sheet simulations with varying initialization techniques and model parameters to understand the role they play on the projected evolution of this ice sheet under simple scenarios. Results are improved compared to previous assessments and show that continued improvements in the representation of the floating ice around Antarctica are critical to reduce the uncertainty in the future ice sheet contribution to sea level rise.
Sebastian Beyer, Thomas Kleiner, Vadym Aizinger, Martin Rückamp, and Angelika Humbert
The Cryosphere, 12, 3931–3947, https://doi.org/10.5194/tc-12-3931-2018, https://doi.org/10.5194/tc-12-3931-2018, 2018
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The evolution of subglacial channels below ice sheets is very important for the dynamics of glaciers as the water acts as a lubricant. We present a new numerical model (CUAS) that generalizes existing approaches by accounting for two different flow situations within a single porous medium layer: (1) a confined aquifer if sufficient water supply is available and (2) an unconfined aquifer, otherwise. The model is applied to artificial scenarios as well as to the Northeast Greenland Ice Stream.
Martin Rückamp, Ulrike Falk, Katja Frieler, Stefan Lange, and Angelika Humbert
Earth Syst. Dynam., 9, 1169–1189, https://doi.org/10.5194/esd-9-1169-2018, https://doi.org/10.5194/esd-9-1169-2018, 2018
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Sea-level rise associated with changing climate is expected to pose a major challenge for societies. Based on the efforts of COP21 to limit global warming to 2.0 °C by the end of the 21st century (Paris Agreement), we simulate the future contribution of the Greenland ice sheet (GrIS) to sea-level change. The projected sea-level rise ranges between 21–38 mm by 2100
and 36–85 mm by 2300. Our results indicate that uncertainties in the projections stem from the underlying climate data.
Reinhard Calov, Sebastian Beyer, Ralf Greve, Johanna Beckmann, Matteo Willeit, Thomas Kleiner, Martin Rückamp, Angelika Humbert, and Andrey Ganopolski
The Cryosphere, 12, 3097–3121, https://doi.org/10.5194/tc-12-3097-2018, https://doi.org/10.5194/tc-12-3097-2018, 2018
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We present RCP 4.5 and 8.5 projections for the Greenland glacial system with the new glacial system model IGLOO 1.0, which incorporates the ice sheet model SICOPOLIS 3.3, a model of basal hydrology and a parameterization of submarine melt of outlet glaciers. Surface temperature and mass balance anomalies from the MAR climate model serve as forcing delivering projections for the contribution of the Greenland ice sheet to sea level rise and submarine melt of Helheim and Store outlet glaciers.
Heiko Goelzer, Sophie Nowicki, Tamsin Edwards, Matthew Beckley, Ayako Abe-Ouchi, Andy Aschwanden, Reinhard Calov, Olivier Gagliardini, Fabien Gillet-Chaulet, Nicholas R. Golledge, Jonathan Gregory, Ralf Greve, Angelika Humbert, Philippe Huybrechts, Joseph H. Kennedy, Eric Larour, William H. Lipscomb, Sébastien Le clec'h, Victoria Lee, Mathieu Morlighem, Frank Pattyn, Antony J. Payne, Christian Rodehacke, Martin Rückamp, Fuyuki Saito, Nicole Schlegel, Helene Seroussi, Andrew Shepherd, Sainan Sun, Roderik van de Wal, and Florian A. Ziemen
The Cryosphere, 12, 1433–1460, https://doi.org/10.5194/tc-12-1433-2018, https://doi.org/10.5194/tc-12-1433-2018, 2018
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We have compared a wide spectrum of different initialisation techniques used in the ice sheet modelling community to define the modelled present-day Greenland ice sheet state as a starting point for physically based future-sea-level-change projections. Compared to earlier community-wide comparisons, we find better agreement across different models, which implies overall improvement of our understanding of what is needed to produce such initial states.
Melanie Rankl, Johannes Jakob Fürst, Angelika Humbert, and Matthias Holger Braun
The Cryosphere, 11, 1199–1211, https://doi.org/10.5194/tc-11-1199-2017, https://doi.org/10.5194/tc-11-1199-2017, 2017
Eythor Gudlaugsson, Angelika Humbert, Thomas Kleiner, Jack Kohler, and Karin Andreassen
The Cryosphere, 10, 751–760, https://doi.org/10.5194/tc-10-751-2016, https://doi.org/10.5194/tc-10-751-2016, 2016
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This paper explores the influence of a subglacial lake on ice dynamics and internal layers by means of numerical modelling as well as simulating the effect of a subglacial drainage event on isochrones. We provide an explanation for characteristic dip and ridge features found at the edges of many subglacial lakes and conclude that draining lakes can result in travelling waves at depth within isochrones, thus indicating the possibility of detecting past drainage events with ice penetrating radar.
Johannes H. Bondzio, Hélène Seroussi, Mathieu Morlighem, Thomas Kleiner, Martin Rückamp, Angelika Humbert, and Eric Y. Larour
The Cryosphere, 10, 497–510, https://doi.org/10.5194/tc-10-497-2016, https://doi.org/10.5194/tc-10-497-2016, 2016
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We implemented a level-set method in the ice sheet system model. This method allows us to dynamically evolve a calving front subject to user-defined calving rates. We apply the method to Jakobshavn Isbræ, West Greenland, and study its response to calving rate perturbations. We find its behaviour strongly dependent on the calving rate, which was to be expected. Both reduced basal drag and rheological shear margin weakening sustain the acceleration of this dynamic outlet glacier.
J. Christmann, R. Müller, K. G. Webber, D. Isaia, F. H. Schader, S. Kipfstuhl, J. Freitag, and A. Humbert
Earth Syst. Sci. Data, 7, 87–92, https://doi.org/10.5194/essd-7-87-2015, https://doi.org/10.5194/essd-7-87-2015, 2015
N. Wilkens, J. Behrens, T. Kleiner, D. Rippin, M. Rückamp, and A. Humbert
The Cryosphere, 9, 675–690, https://doi.org/10.5194/tc-9-675-2015, https://doi.org/10.5194/tc-9-675-2015, 2015
T. Kleiner, M. Rückamp, J. H. Bondzio, and A. Humbert
The Cryosphere, 9, 217–228, https://doi.org/10.5194/tc-9-217-2015, https://doi.org/10.5194/tc-9-217-2015, 2015
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We present benchmark experiments and analytical solutions to test the implementation of enthalpy and the corresponding boundary conditions in numerical ice sheet models. The results of the applied models agree well with the analytical solutions if the change in conductivity between cold and temperate ice is properly considered in the model.
V. Helm, A. Humbert, and H. Miller
The Cryosphere, 8, 1539–1559, https://doi.org/10.5194/tc-8-1539-2014, https://doi.org/10.5194/tc-8-1539-2014, 2014
Related subject area
Cryosphere
Tuning parameters of a sea ice model using machine learning
WRF-Chem simulations of snow nitrate and other physicochemical properties in northern China
Clustering simulated snow profiles to form avalanche forecast regions
SnowQM 1.0: a fast R package for bias-correcting spatial fields of snow water equivalent using quantile mapping
Simulation of snow albedo and solar irradiance profile with the Two-streAm Radiative TransfEr in Snow (TARTES) v2.0 model
Evaluation of MITgcm-based ocean reanalyses for the Southern Ocean
Improvements in the land surface configuration to better simulate seasonal snow cover in the European Alps with the CNRM-AROME (cycle 46) convection-permitting regional climate model
A three-stage model pipeline predicting regional avalanche danger in Switzerland (RAvaFcast v1.0.0): a decision-support tool for operational avalanche forecasting
A global–land snow scheme (GLASS) v1.0 for the GFDL Earth System Model: formulation and evaluation at instrumented sites
A gradient-boosted tree framework to model the ice thickness of the World's glaciers (IceBoost v1)
Design and performance of ELSA v2.0: an isochronal model for ice-sheet layer tracing
Southern Ocean Ice Prediction System version 1.0 (SOIPS v1.0): description of the system and evaluation of synoptic-scale sea ice forecasts
Lagrangian tracking of sea ice in Community Ice CodE (CICE; version 5)
openAMUNDSEN v1.0: an open-source snow-hydrological model for mountain regions
OpenFOAM-avalanche 2312: depth-integrated models beyond dense-flow avalanches
Refactoring the elastic–viscous–plastic solver from the sea ice model CICE v6.5.1 for improved performance
CMIP6 models overestimate sea ice melt, growth & conduction relative to ice mass balance buoy estimates
A new 3D full-Stokes calving algorithm within Elmer/Ice (v9.0)
Towards deep learning solutions for classification of automated snow height measurements (CleanSnow v1.0.0)
Quantitative Sub-Ice and Marine Tracing of Antarctic Sediment Provenance (TASP v1.0)
Coupling framework (1.0) for the Úa (2023b) ice sheet model and the FESOM-1.4 z-coordinate ocean model in an Antarctic domain
A novel numerical implementation for the surface energy budget of melting snowpacks and glaciers
SnowPappus v1.0, a blowing-snow model for large-scale applications of the Crocus snow scheme
A stochastic parameterization of ice sheet surface mass balance for the Stochastic Ice-Sheet and Sea-Level System Model (StISSM v1.0)
Graphics-processing-unit-accelerated ice flow solver for unstructured meshes using the Shallow-Shelf Approximation (FastIceFlo v1.0.1)
A finite-element framework to explore the numerical solution of the coupled problem of heat conduction, water vapor diffusion, and settlement in dry snow (IvoriFEM v0.1.0)
AvaFrame com1DFA (v1.3): a thickness-integrated computational avalanche module – theory, numerics, and testing
Universal differential equations for glacier ice flow modelling
A new model for supraglacial hydrology evolution and drainage for the Greenland Ice Sheet (SHED v1.0)
Modeling sensitivities of thermally and hydraulically driven ice stream surge cycling
Automatic snow type classification of snow micropenetrometer profiles with machine learning algorithms
An empirical model to calculate snow depth from daily snow water equivalent: SWE2HS 1.0
A wind-driven snow redistribution module for Alpine3D v3.3.0: adaptations designed for downscaling ice sheet surface mass balance
The CryoGrid community model (version 1.0) – a multi-physics toolbox for climate-driven simulations in the terrestrial cryosphere
Glacier Energy and Mass Balance (GEMB): a model of firn processes for cryosphere research
Sensitivity of NEMO4.0-SI3 model parameters on sea ice budgets in the Southern Ocean
Introducing CRYOWRF v1.0: multiscale atmospheric flow simulations with advanced snow cover modelling
SUHMO: an adaptive mesh refinement SUbglacial Hydrology MOdel v1.0
Improving snow albedo modeling in the E3SM land model (version 2.0) and assessing its impacts on snow and surface fluxes over the Tibetan Plateau
The Multiple Snow Data Assimilation System (MuSA v1.0)
The Stochastic Ice-Sheet and Sea-Level System Model v1.0 (StISSM v1.0)
Improved representation of the contemporary Greenland ice sheet firn layer by IMAU-FDM v1.2G
Modeling the small-scale deposition of snow onto structured Arctic sea ice during a MOSAiC storm using snowBedFoam 1.0.
Benchmarking the vertically integrated ice-sheet model IMAU-ICE (version 2.0)
SnowClim v1.0: high-resolution snow model and data for the western United States
Snow Multidata Mapping and Modeling (S3M) 5.1: a distributed cryospheric model with dry and wet snow, data assimilation, glacier mass balance, and debris-driven melt
MPAS-Seaice (v1.0.0): sea-ice dynamics on unstructured Voronoi meshes
Explicitly modelling microtopography in permafrost landscapes in a land surface model (JULES vn5.4_microtopography)
Geometric remapping of particle distributions in the Discrete Element Model for Sea Ice (DEMSI v0.0)
Mapping high-resolution basal topography of West Antarctica from radar data using non-stationary multiple-point geostatistics (MPS-BedMappingV1)
Anton Korosov, Yue Ying, and Einar Ólason
Geosci. Model Dev., 18, 885–904, https://doi.org/10.5194/gmd-18-885-2025, https://doi.org/10.5194/gmd-18-885-2025, 2025
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We have developed a new method to improve the accuracy of sea ice models, which predict how ice moves and deforms due to wind and ocean currents. Traditional models use parameters that are often poorly defined. The new approach uses machine learning to fine-tune these parameters by comparing simulated ice drift with satellite data. The method identifies optimal settings for the model by analysing patterns in ice deformation. This results in more accurate simulations of sea ice drift forecasting.
Xia Wang, Tao Che, Xueyin Ruan, Shanna Yue, Jing Wang, Chun Zhao, and Lei Geng
Geosci. Model Dev., 18, 651–670, https://doi.org/10.5194/gmd-18-651-2025, https://doi.org/10.5194/gmd-18-651-2025, 2025
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We employed the WRF-Chem model to parameterize atmospheric nitrate deposition in snow and evaluate its performance in simulating snow cover, snow depth, and concentrations of dust and nitrate using new observations from northern China. The results generally exhibit reasonable agreement with field observations in northern China, demonstrating the model's capability to simulate snow properties, including concentrations of reservoir species.
Simon Horton, Florian Herla, and Pascal Haegeli
Geosci. Model Dev., 18, 193–209, https://doi.org/10.5194/gmd-18-193-2025, https://doi.org/10.5194/gmd-18-193-2025, 2025
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We present a method for avalanche forecasters to analyze patterns in snowpack model simulations. It uses fuzzy clustering to group small regions into larger forecast areas based on snow characteristics, locations, and temporal history. Tested in the Columbia Mountains in two winter seasons, it closely matched real forecast regions regions and identified major avalanche hazard patterns. This approach simplifies complex model outputs, helping forecasters make informed decisions.
Adrien Michel, Johannes Aschauer, Tobias Jonas, Stefanie Gubler, Sven Kotlarski, and Christoph Marty
Geosci. Model Dev., 17, 8969–8988, https://doi.org/10.5194/gmd-17-8969-2024, https://doi.org/10.5194/gmd-17-8969-2024, 2024
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We present a method to correct snow cover maps (represented in terms of snow water equivalent) to match better-quality maps. The correction can then be extended backwards and forwards in time for periods when better-quality maps are not available. The method is fast and gives good results. It is then applied to obtain a climatology of the snow cover in Switzerland over the past 60 years at a resolution of 1 d and 1 km. This is the first time that such a dataset has been produced.
Ghislain Picard and Quentin Libois
Geosci. Model Dev., 17, 8927–8953, https://doi.org/10.5194/gmd-17-8927-2024, https://doi.org/10.5194/gmd-17-8927-2024, 2024
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The Two-streAm Radiative TransfEr in Snow (TARTES) is a radiative transfer model to compute snow albedo in the solar domain and the profiles of light and energy absorption in a multi-layered snowpack whose physical properties are user defined. It uniquely considers snow grain shape flexibly, based on recent insights showing that snow does not behave as a collection of ice spheres but instead as a random medium. TARTES is user-friendly yet performs comparably to more complex models.
Yoshihiro Nakayama, Alena Malyarenko, Hong Zhang, Ou Wang, Matthis Auger, Yafei Nie, Ian Fenty, Matthew Mazloff, Armin Köhl, and Dimitris Menemenlis
Geosci. Model Dev., 17, 8613–8638, https://doi.org/10.5194/gmd-17-8613-2024, https://doi.org/10.5194/gmd-17-8613-2024, 2024
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Global- and basin-scale ocean reanalyses are becoming easily accessible. However, such ocean reanalyses are optimized for their entire model domains and their ability to simulate the Southern Ocean requires evaluation. We conduct intercomparison analyses of Massachusetts Institute of Technology General Circulation Model (MITgcm)-based ocean reanalyses. They generally perform well for the open ocean, but open-ocean temporal variability and Antarctic continental shelves require improvements.
Diego Monteiro, Cécile Caillaud, Matthieu Lafaysse, Adrien Napoly, Mathieu Fructus, Antoinette Alias, and Samuel Morin
Geosci. Model Dev., 17, 7645–7677, https://doi.org/10.5194/gmd-17-7645-2024, https://doi.org/10.5194/gmd-17-7645-2024, 2024
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Modeling snow cover in climate and weather forecasting models is a challenge even for high-resolution models. Recent simulations with CNRM-AROME have shown difficulties when representing snow in the European Alps. Using remote sensing data and in situ observations, we evaluate modifications of the land surface configuration in order to improve it. We propose a new surface configuration, enabling a more realistic simulation of snow cover, relevant for climate and weather forecasting applications.
Alessandro Maissen, Frank Techel, and Michele Volpi
Geosci. Model Dev., 17, 7569–7593, https://doi.org/10.5194/gmd-17-7569-2024, https://doi.org/10.5194/gmd-17-7569-2024, 2024
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By harnessing AI models, this work enables processing large amounts of data, including weather conditions, snowpack characteristics, and historical avalanche data, to predict human-like avalanche forecasts in Switzerland. Our proposed model can significantly assist avalanche forecasters in their decision-making process, thereby facilitating more efficient and accurate predictions crucial for ensuring safety in Switzerland's avalanche-prone regions.
Enrico Zorzetto, Sergey Malyshev, Paul Ginoux, and Elena Shevliakova
Geosci. Model Dev., 17, 7219–7244, https://doi.org/10.5194/gmd-17-7219-2024, https://doi.org/10.5194/gmd-17-7219-2024, 2024
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We describe a new snow scheme developed for use in global climate models, which simulates the interactions of snowpack with vegetation, atmosphere, and soil. We test the new snow model over a set of sites where in situ observations are available. We find that when compared to a simpler snow model, this model improves predictions of seasonal snow and of soil temperature under the snowpack, important variables for simulating both the hydrological cycle and the global climate system.
Niccolò Maffezzoli, Eric Rignot, Carlo Barbante, Troels Petersen, and Sebastiano Vascon
EGUsphere, https://doi.org/10.5194/egusphere-2024-2455, https://doi.org/10.5194/egusphere-2024-2455, 2024
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In this work we introduces IceBoost, a machine learning framework to model the ice thickness distribution of all the World's glaciers, with greater accuracy than state-of-the-art methods. The model is trained on 3.7 million measurements globally available and provides skillful estimates across all regions. This advancement will help in better assessing future sea level changes, freshwater resources, with significance for both the scientific community and society at large.
Therese Rieckh, Andreas Born, Alexander Robinson, Robert Law, and Gerrit Gülle
Geosci. Model Dev., 17, 6987–7000, https://doi.org/10.5194/gmd-17-6987-2024, https://doi.org/10.5194/gmd-17-6987-2024, 2024
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We present the open-source model ELSA, which simulates the internal age structure of large ice sheets. It creates layers of snow accumulation at fixed times during the simulation, which are used to model the internal stratification of the ice sheet. Together with reconstructed isochrones from radiostratigraphy data, ELSA can be used to assess ice sheet models and to improve their parameterization. ELSA can be used coupled to an ice sheet model or forced with its output.
Fu Zhao, Xi Liang, Zhongxiang Tian, Ming Li, Na Liu, and Chengyan Liu
Geosci. Model Dev., 17, 6867–6886, https://doi.org/10.5194/gmd-17-6867-2024, https://doi.org/10.5194/gmd-17-6867-2024, 2024
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In this work, we introduce a newly developed Antarctic sea ice forecasting system, namely the Southern Ocean Ice Prediction System (SOIPS). The system is based on a regional sea ice‒ocean‒ice shelf coupled model and can assimilate sea ice concentration observations. By assessing the system's performance in sea ice forecasts, we find that the system can provide reliable Antarctic sea ice forecasts for the next 7 d and has the potential to guide ship navigation in the Antarctic sea ice zone.
Chenhui Ning, Shiming Xu, Yan Zhang, Xuantong Wang, Zhihao Fan, and Jiping Liu
Geosci. Model Dev., 17, 6847–6866, https://doi.org/10.5194/gmd-17-6847-2024, https://doi.org/10.5194/gmd-17-6847-2024, 2024
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Sea ice models are mainly based on non-moving structured grids, which is different from buoy measurements that follow the ice drift. To facilitate Lagrangian analysis, we introduce online tracking of sea ice in Community Ice CodE (CICE). We validate the sea ice tracking with buoys and evaluate the sea ice deformation in high-resolution simulations, which show multi-fractal characteristics. The source code is openly available and can be used in various scientific and operational applications.
Ulrich Strasser, Michael Warscher, Erwin Rottler, and Florian Hanzer
Geosci. Model Dev., 17, 6775–6797, https://doi.org/10.5194/gmd-17-6775-2024, https://doi.org/10.5194/gmd-17-6775-2024, 2024
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openAMUNDSEN is a fully distributed open-source snow-hydrological model for mountain catchments. It includes process representations of an empirical, semi-empirical, and physical nature. It uses temperature, precipitation, humidity, radiation, and wind speed as forcing data and is computationally efficient, of a modular nature, and easily extendible. The Python code is available on GitHub (https://github.com/openamundsen/openamundsen), including documentation (https://doc.openamundsen.org).
Matthias Rauter and Julia Kowalski
Geosci. Model Dev., 17, 6545–6569, https://doi.org/10.5194/gmd-17-6545-2024, https://doi.org/10.5194/gmd-17-6545-2024, 2024
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Snow avalanches can form large powder clouds that substantially exceed the velocity and reach of the dense core. Only a few complex models exist to simulate this phenomenon, and the respective hazard is hard to predict. This work provides a novel flow model that focuses on simple relations while still encapsulating the significant behaviour. The model is applied to reconstruct two catastrophic powder snow avalanche events in Austria.
Till Andreas Soya Rasmussen, Jacob Poulsen, Mads Hvid Ribergaard, Ruchira Sasanka, Anthony P. Craig, Elizabeth C. Hunke, and Stefan Rethmeier
Geosci. Model Dev., 17, 6529–6544, https://doi.org/10.5194/gmd-17-6529-2024, https://doi.org/10.5194/gmd-17-6529-2024, 2024
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Earth system models (ESMs) today strive for better quality based on improved resolutions and improved physics. A limiting factor is the supercomputers at hand and how best to utilize them. This study focuses on the refactorization of one part of a sea ice model (CICE), namely the dynamics. It shows that the performance can be significantly improved, which means that one can either run the same simulations much cheaper or advance the system according to what is needed.
Alex Edward West and Edward William Blockley
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-121, https://doi.org/10.5194/gmd-2024-121, 2024
Preprint under review for GMD
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This study uses ice mass balance buoys – temperature and height-measuring devices frozen into sea ice – to find how well climate models simulate the melt & growth of, and conduction of heat through, Arctic sea ice. This may help understand why models produce varying amounts of sea ice in the present day. We find models tend to show more melt, growth or conduction for a given ice thickness than the buoys, though the difference is smaller for models with more physically realistic thermodynamics.
Iain Wheel, Douglas I. Benn, Anna J. Crawford, Joe Todd, and Thomas Zwinger
Geosci. Model Dev., 17, 5759–5777, https://doi.org/10.5194/gmd-17-5759-2024, https://doi.org/10.5194/gmd-17-5759-2024, 2024
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Calving, the detachment of large icebergs from glaciers, is one of the largest uncertainties in future sea level rise projections. This process is poorly understood, and there is an absence of detailed models capable of simulating calving. A new 3D calving model has been developed to better understand calving at glaciers where detailed modelling was previously limited. Importantly, the new model is very flexible. By allowing for unrestricted calving geometries, it can be applied at any location.
Jan Svoboda, Marc Ruesch, David Liechti, Corinne Jones, Michele Volpi, Michael Zehnder, and Jürg Schweizer
EGUsphere, https://doi.org/10.5194/egusphere-2024-1752, https://doi.org/10.5194/egusphere-2024-1752, 2024
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Accurately measuring snow height is key for modeling approaches in climate sciences, snow hydrology and avalanche forecasting. Erroneous snow height measurements often occur when the snow height is low or changes, for instance, during a snowfall in the summer. We prepare a new benchmark dataset with annotated snow height data and demonstrate how to improve the measurement quality using modern deep learning approaches. Our approach can be easily implemented into a data pipeline for snow modeling.
Jim Marschalek, Edward Gasson, Tina van de Flierdt, Claus-Dieter Hillenbrand, Martin Siegert, and Liam Holder
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-104, https://doi.org/10.5194/gmd-2024-104, 2024
Revised manuscript accepted for GMD
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Ice sheet models can help predict how Antarctica's ice sheets respond to environmental change, and such models benefit from comparison to geological data. Here, we use an ice sheet model output, plus other data, to predict the erosion of debris and trace its transport to where it is deposited on the ocean floor. This allows the results of ice sheet modelling to be directly and quantitively compared to real-world data, helping to reduce uncertainty regarding Antarctic sea level contribution.
Ole Richter, Ralph Timmermann, G. Hilmar Gudmundsson, and Jan De Rydt
EGUsphere, https://doi.org/10.5194/egusphere-2024-648, https://doi.org/10.5194/egusphere-2024-648, 2024
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The new coupled ice sheet-ocean model addresses challenges related to horizontal resolution through advanced mesh flexibility, enabled by the use of unstructured grids. We describe the new model, verify its functioning in an idealised setting and demonstrate its advantages in a global-ocean/Antarctic ice sheet domain. The results of this study comprise an important step towards improving predictions of the Antarctic contribution to sea level rise over centennial time scales.
Kévin Fourteau, Julien Brondex, Fanny Brun, and Marie Dumont
Geosci. Model Dev., 17, 1903–1929, https://doi.org/10.5194/gmd-17-1903-2024, https://doi.org/10.5194/gmd-17-1903-2024, 2024
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In this paper, we provide a novel numerical implementation for solving the energy exchanges at the surface of snow and ice. By combining the strong points of previous models, our solution leads to more accurate and robust simulations of the energy exchanges, surface temperature, and melt while preserving a reasonable computation time.
Matthieu Baron, Ange Haddjeri, Matthieu Lafaysse, Louis Le Toumelin, Vincent Vionnet, and Mathieu Fructus
Geosci. Model Dev., 17, 1297–1326, https://doi.org/10.5194/gmd-17-1297-2024, https://doi.org/10.5194/gmd-17-1297-2024, 2024
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Increasing the spatial resolution of numerical systems simulating snowpack evolution in mountain areas requires representing small-scale processes such as wind-induced snow transport. We present SnowPappus, a simple scheme coupled with the Crocus snow model to compute blowing-snow fluxes and redistribute snow among grid points at 250 m resolution. In terms of numerical cost, it is suitable for large-scale applications. We present point-scale evaluations of fluxes and snow transport occurrence.
Lizz Ultee, Alexander A. Robel, and Stefano Castruccio
Geosci. Model Dev., 17, 1041–1057, https://doi.org/10.5194/gmd-17-1041-2024, https://doi.org/10.5194/gmd-17-1041-2024, 2024
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The surface mass balance (SMB) of an ice sheet describes the net gain or loss of mass from ice sheets (such as those in Greenland and Antarctica) through interaction with the atmosphere. We developed a statistical method to generate a wide range of SMB fields that reflect the best understanding of SMB processes. Efficiently sampling the variability of SMB will help us understand sources of uncertainty in ice sheet model projections.
Anjali Sandip, Ludovic Räss, and Mathieu Morlighem
Geosci. Model Dev., 17, 899–909, https://doi.org/10.5194/gmd-17-899-2024, https://doi.org/10.5194/gmd-17-899-2024, 2024
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We solve momentum balance for unstructured meshes to predict ice flow for real glaciers using a pseudo-transient method on graphics processing units (GPUs) and compare it to a standard central processing unit (CPU) implementation. We justify the GPU implementation by applying the price-to-performance metric for up to million-grid-point spatial resolutions. This study represents a first step toward leveraging GPU processing power, enabling more accurate polar ice discharge predictions.
Julien Brondex, Kévin Fourteau, Marie Dumont, Pascal Hagenmuller, Neige Calonne, François Tuzet, and Henning Löwe
Geosci. Model Dev., 16, 7075–7106, https://doi.org/10.5194/gmd-16-7075-2023, https://doi.org/10.5194/gmd-16-7075-2023, 2023
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Vapor diffusion is one of the main processes governing snowpack evolution, and it must be accounted for in models. Recent attempts to represent vapor diffusion in numerical models have faced several difficulties regarding computational cost and mass and energy conservation. Here, we develop our own finite-element software to explore numerical approaches and enable us to overcome these difficulties. We illustrate the capability of these approaches on established numerical benchmarks.
Matthias Tonnel, Anna Wirbel, Felix Oesterle, and Jan-Thomas Fischer
Geosci. Model Dev., 16, 7013–7035, https://doi.org/10.5194/gmd-16-7013-2023, https://doi.org/10.5194/gmd-16-7013-2023, 2023
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Avaframe - the open avalanche framework - provides open-source tools to simulate and investigate snow avalanches. It is utilized for multiple purposes, the two main applications being hazard mapping and scientific research of snow processes. We present the theory, conversion to a computer model, and testing for one of the core modules used for simulations of a particular type of avalanche, the so-called dense-flow avalanches. Tests check and confirm the applicability of the utilized method.
Jordi Bolibar, Facundo Sapienza, Fabien Maussion, Redouane Lguensat, Bert Wouters, and Fernando Pérez
Geosci. Model Dev., 16, 6671–6687, https://doi.org/10.5194/gmd-16-6671-2023, https://doi.org/10.5194/gmd-16-6671-2023, 2023
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We developed a new modelling framework combining numerical methods with machine learning. Using this approach, we focused on understanding how ice moves within glaciers, and we successfully learnt a prescribed law describing ice movement for 17 glaciers worldwide as a proof of concept. Our framework has the potential to discover important laws governing glacier processes, aiding our understanding of glacier physics and their contribution to water resources and sea-level rise.
Prateek Gantayat, Alison F. Banwell, Amber A. Leeson, James M. Lea, Dorthe Petersen, Noel Gourmelen, and Xavier Fettweis
Geosci. Model Dev., 16, 5803–5823, https://doi.org/10.5194/gmd-16-5803-2023, https://doi.org/10.5194/gmd-16-5803-2023, 2023
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We developed a new supraglacial hydrology model for the Greenland Ice Sheet. This model simulates surface meltwater routing, meltwater drainage, supraglacial lake (SGL) overflow, and formation of lake ice. The model was able to reproduce 80 % of observed lake locations and provides a good match between the observed and modelled temporal evolution of SGLs.
Kevin Hank, Lev Tarasov, and Elisa Mantelli
Geosci. Model Dev., 16, 5627–5652, https://doi.org/10.5194/gmd-16-5627-2023, https://doi.org/10.5194/gmd-16-5627-2023, 2023
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Physically meaningful modeling of geophysical system instabilities is numerically challenging, given the potential effects of purely numerical artifacts. Here we explore the sensitivity of ice stream surge activation to numerical and physical model aspects. We find that surge characteristics exhibit a resolution dependency but converge at higher horizontal grid resolutions and are significantly affected by the incorporation of bed thermal and sub-glacial hydrology models.
Julia Kaltenborn, Amy R. Macfarlane, Viviane Clay, and Martin Schneebeli
Geosci. Model Dev., 16, 4521–4550, https://doi.org/10.5194/gmd-16-4521-2023, https://doi.org/10.5194/gmd-16-4521-2023, 2023
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Snow layer segmentation and snow grain classification are essential diagnostic tasks for cryospheric applications. A SnowMicroPen (SMP) can be used to that end; however, the manual classification of its profiles becomes infeasible for large datasets. Here, we evaluate how well machine learning models automate this task. Of the 14 models trained on the MOSAiC SMP dataset, the long short-term memory model performed the best. The findings presented here facilitate and accelerate SMP data analysis.
Johannes Aschauer, Adrien Michel, Tobias Jonas, and Christoph Marty
Geosci. Model Dev., 16, 4063–4081, https://doi.org/10.5194/gmd-16-4063-2023, https://doi.org/10.5194/gmd-16-4063-2023, 2023
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Snow water equivalent is the mass of water stored in a snowpack. Based on exponential settling functions, the empirical snow density model SWE2HS is presented to convert time series of daily snow water equivalent into snow depth. The model has been calibrated with data from Switzerland and validated with independent data from the European Alps. A reference implementation of SWE2HS is available as a Python package.
Eric Keenan, Nander Wever, Jan T. M. Lenaerts, and Brooke Medley
Geosci. Model Dev., 16, 3203–3219, https://doi.org/10.5194/gmd-16-3203-2023, https://doi.org/10.5194/gmd-16-3203-2023, 2023
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Ice sheets gain mass via snowfall. However, snowfall is redistributed by the wind, resulting in accumulation differences of up to a factor of 5 over distances as short as 5 km. These differences complicate estimates of ice sheet contribution to sea level rise. For this reason, we have developed a new model for estimating wind-driven snow redistribution on ice sheets. We show that, over Pine Island Glacier in West Antarctica, the model improves estimates of snow accumulation variability.
Sebastian Westermann, Thomas Ingeman-Nielsen, Johanna Scheer, Kristoffer Aalstad, Juditha Aga, Nitin Chaudhary, Bernd Etzelmüller, Simon Filhol, Andreas Kääb, Cas Renette, Louise Steffensen Schmidt, Thomas Vikhamar Schuler, Robin B. Zweigel, Léo Martin, Sarah Morard, Matan Ben-Asher, Michael Angelopoulos, Julia Boike, Brian Groenke, Frederieke Miesner, Jan Nitzbon, Paul Overduin, Simone M. Stuenzi, and Moritz Langer
Geosci. Model Dev., 16, 2607–2647, https://doi.org/10.5194/gmd-16-2607-2023, https://doi.org/10.5194/gmd-16-2607-2023, 2023
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The CryoGrid community model is a new tool for simulating ground temperatures and the water and ice balance in cold regions. It is a modular design, which makes it possible to test different schemes to simulate, for example, permafrost ground in an efficient way. The model contains tools to simulate frozen and unfrozen ground, snow, glaciers, and other massive ice bodies, as well as water bodies.
Alex S. Gardner, Nicole-Jeanne Schlegel, and Eric Larour
Geosci. Model Dev., 16, 2277–2302, https://doi.org/10.5194/gmd-16-2277-2023, https://doi.org/10.5194/gmd-16-2277-2023, 2023
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This is the first description of the open-source Glacier Energy and Mass Balance (GEMB) model. GEMB models the ice sheet and glacier surface–atmospheric energy and mass exchange, as well as the firn state. The model is evaluated against the current state of the art and in situ observations and is shown to perform well.
Yafei Nie, Chengkun Li, Martin Vancoppenolle, Bin Cheng, Fabio Boeira Dias, Xianqing Lv, and Petteri Uotila
Geosci. Model Dev., 16, 1395–1425, https://doi.org/10.5194/gmd-16-1395-2023, https://doi.org/10.5194/gmd-16-1395-2023, 2023
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State-of-the-art Earth system models simulate the observed sea ice extent relatively well, but this is often due to errors in the dynamic and other processes in the simulated sea ice changes cancelling each other out. We assessed the sensitivity of these processes simulated by the coupled ocean–sea ice model NEMO4.0-SI3 to 18 parameters. The performance of the model in simulating sea ice change processes was ultimately improved by adjusting the three identified key parameters.
Varun Sharma, Franziska Gerber, and Michael Lehning
Geosci. Model Dev., 16, 719–749, https://doi.org/10.5194/gmd-16-719-2023, https://doi.org/10.5194/gmd-16-719-2023, 2023
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Most current generation climate and weather models have a relatively simplistic description of snow and snow–atmosphere interaction. One reason for this is the belief that including an advanced snow model would make the simulations too computationally demanding. In this study, we bring together two state-of-the-art models for atmosphere (WRF) and snow cover (SNOWPACK) and highlight both the feasibility and necessity of such coupled models to explore underexplored phenomena in the cryosphere.
Anne M. Felden, Daniel F. Martin, and Esmond G. Ng
Geosci. Model Dev., 16, 407–425, https://doi.org/10.5194/gmd-16-407-2023, https://doi.org/10.5194/gmd-16-407-2023, 2023
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We present and validate a novel subglacial hydrology model, SUHMO, based on an adaptive mesh refinement framework. We propose the addition of a pseudo-diffusion to recover the wall melting in channels. Computational performance analysis demonstrates the efficiency of adaptive mesh refinement on large-scale hydrologic problems. The adaptive mesh refinement approach will eventually enable better ice bed boundary conditions for ice sheet simulations at a reasonable computational cost.
Dalei Hao, Gautam Bisht, Karl Rittger, Edward Bair, Cenlin He, Huilin Huang, Cheng Dang, Timbo Stillinger, Yu Gu, Hailong Wang, Yun Qian, and L. Ruby Leung
Geosci. Model Dev., 16, 75–94, https://doi.org/10.5194/gmd-16-75-2023, https://doi.org/10.5194/gmd-16-75-2023, 2023
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Snow with the highest albedo of land surface plays a vital role in Earth’s surface energy budget and water cycle. This study accounts for the impacts of snow grain shape and mixing state of light-absorbing particles with snow on snow albedo in the E3SM land model. The findings advance our understanding of the role of snow grain shape and mixing state of LAP–snow in land surface processes and offer guidance for improving snow simulations and radiative forcing estimates in Earth system models.
Esteban Alonso-González, Kristoffer Aalstad, Mohamed Wassim Baba, Jesús Revuelto, Juan Ignacio López-Moreno, Joel Fiddes, Richard Essery, and Simon Gascoin
Geosci. Model Dev., 15, 9127–9155, https://doi.org/10.5194/gmd-15-9127-2022, https://doi.org/10.5194/gmd-15-9127-2022, 2022
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Snow cover plays an important role in many processes, but its monitoring is a challenging task. The alternative is usually to simulate the snowpack, and to improve these simulations one of the most promising options is to fuse simulations with available observations (data assimilation). In this paper we present MuSA, a data assimilation tool which facilitates the implementation of snow monitoring initiatives, allowing the assimilation of a wide variety of remotely sensed snow cover information.
Vincent Verjans, Alexander A. Robel, Helene Seroussi, Lizz Ultee, and Andrew F. Thompson
Geosci. Model Dev., 15, 8269–8293, https://doi.org/10.5194/gmd-15-8269-2022, https://doi.org/10.5194/gmd-15-8269-2022, 2022
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We describe the development of the first large-scale ice sheet model that accounts for stochasticity in a range of processes. Stochasticity allows the impacts of inherently uncertain processes on ice sheets to be represented. This includes climatic uncertainty, as the climate is inherently chaotic. Furthermore, stochastic capabilities also encompass poorly constrained glaciological processes that display strong variability at fine spatiotemporal scales. We present the model and test experiments.
Max Brils, Peter Kuipers Munneke, Willem Jan van de Berg, and Michiel van den Broeke
Geosci. Model Dev., 15, 7121–7138, https://doi.org/10.5194/gmd-15-7121-2022, https://doi.org/10.5194/gmd-15-7121-2022, 2022
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Firn covers the Greenland ice sheet (GrIS) and can temporarily prevent mass loss. Here, we present the latest version of our firn model, IMAU-FDM, with an application to the GrIS. We improved the density of fallen snow, the firn densification rate and the firn's thermal conductivity. This leads to a higher air content and 10 m temperatures. Furthermore we investigate three case studies and find that the updated model shows greater variability and an increased sensitivity in surface elevation.
Océane Hames, Mahdi Jafari, David Nicholas Wagner, Ian Raphael, David Clemens-Sewall, Chris Polashenski, Matthew D. Shupe, Martin Schneebeli, and Michael Lehning
Geosci. Model Dev., 15, 6429–6449, https://doi.org/10.5194/gmd-15-6429-2022, https://doi.org/10.5194/gmd-15-6429-2022, 2022
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This paper presents an Eulerian–Lagrangian snow transport model implemented in the fluid dynamics software OpenFOAM, which we call snowBedFoam 1.0. We apply this model to reproduce snow deposition on a piece of ridged Arctic sea ice, which was produced during the MOSAiC expedition through scan measurements. The model appears to successfully reproduce the enhanced snow accumulation and deposition patterns, although some quantitative uncertainties were shown.
Constantijn J. Berends, Heiko Goelzer, Thomas J. Reerink, Lennert B. Stap, and Roderik S. W. van de Wal
Geosci. Model Dev., 15, 5667–5688, https://doi.org/10.5194/gmd-15-5667-2022, https://doi.org/10.5194/gmd-15-5667-2022, 2022
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The rate at which marine ice sheets such as the West Antarctic ice sheet will retreat in a warming climate and ocean is still uncertain. Numerical ice-sheet models, which solve the physical equations that describe the way glaciers and ice sheets deform and flow, have been substantially improved in recent years. Here we present the results of several years of work on IMAU-ICE, an ice-sheet model of intermediate complexity, which can be used to study ice sheets of both the past and the future.
Abby C. Lute, John Abatzoglou, and Timothy Link
Geosci. Model Dev., 15, 5045–5071, https://doi.org/10.5194/gmd-15-5045-2022, https://doi.org/10.5194/gmd-15-5045-2022, 2022
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We developed a snow model that can be used to quantify snowpack over large areas with a high degree of spatial detail. We ran the model over the western United States, creating a snow and climate dataset for three time periods. Compared to observations of snowpack, the model captured the key aspects of snow across time and space. The model and dataset will be useful in understanding historical and future changes in snowpack, with relevance to water resources, agriculture, and ecosystems.
Francesco Avanzi, Simone Gabellani, Fabio Delogu, Francesco Silvestro, Edoardo Cremonese, Umberto Morra di Cella, Sara Ratto, and Hervé Stevenin
Geosci. Model Dev., 15, 4853–4879, https://doi.org/10.5194/gmd-15-4853-2022, https://doi.org/10.5194/gmd-15-4853-2022, 2022
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Knowing in real time how much snow and glacier ice has accumulated across the landscape has significant implications for water-resource management and flood control. This paper presents a computer model – S3M – allowing scientists and decision makers to predict snow and ice accumulation during winter and the subsequent melt during spring and summer. S3M has been employed for real-world flood forecasting since the early 2000s but is here being made open source for the first time.
Adrian K. Turner, William H. Lipscomb, Elizabeth C. Hunke, Douglas W. Jacobsen, Nicole Jeffery, Darren Engwirda, Todd D. Ringler, and Jonathan D. Wolfe
Geosci. Model Dev., 15, 3721–3751, https://doi.org/10.5194/gmd-15-3721-2022, https://doi.org/10.5194/gmd-15-3721-2022, 2022
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We present the dynamical core of the MPAS-Seaice model, which uses a mesh consisting of a Voronoi tessellation with polygonal cells. Such a mesh allows variable mesh resolution in different parts of the domain and the focusing of computational resources in regions of interest. We describe the velocity solver and tracer transport schemes used and examine errors generated by the model in both idealized and realistic test cases and examine the computational efficiency of the model.
Noah D. Smith, Eleanor J. Burke, Kjetil Schanke Aas, Inge H. J. Althuizen, Julia Boike, Casper Tai Christiansen, Bernd Etzelmüller, Thomas Friborg, Hanna Lee, Heather Rumbold, Rachael H. Turton, Sebastian Westermann, and Sarah E. Chadburn
Geosci. Model Dev., 15, 3603–3639, https://doi.org/10.5194/gmd-15-3603-2022, https://doi.org/10.5194/gmd-15-3603-2022, 2022
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The Arctic has large areas of small mounds that are caused by ice lifting up the soil. Snow blown by wind gathers in hollows next to these mounds, insulating them in winter. The hollows tend to be wetter, and thus the soil absorbs more heat in summer. The warm wet soil in the hollows decomposes, releasing methane. We have made a model of this, and we have tested how it behaves and whether it looks like sites in Scandinavia and Siberia. Sometimes we get more methane than a model without mounds.
Adrian K. Turner, Kara J. Peterson, and Dan Bolintineanu
Geosci. Model Dev., 15, 1953–1970, https://doi.org/10.5194/gmd-15-1953-2022, https://doi.org/10.5194/gmd-15-1953-2022, 2022
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We developed a technique to remap sea ice tracer quantities between circular discrete element distributions. This is needed for a global discrete element method sea ice model being developed jointly by Los Alamos National Laboratory and Sandia National Laboratories that has the potential to better utilize newer supercomputers with graphics processing units and better represent sea ice dynamics. This new remapping technique ameliorates the effect of element distortion created by sea ice ridging.
Zhen Yin, Chen Zuo, Emma J. MacKie, and Jef Caers
Geosci. Model Dev., 15, 1477–1497, https://doi.org/10.5194/gmd-15-1477-2022, https://doi.org/10.5194/gmd-15-1477-2022, 2022
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We provide a multiple-point geostatistics approach to probabilistically learn from training images to fill large-scale irregular geophysical data gaps. With a repository of global topographic training images, our approach models high-resolution basal topography and quantifies the geospatial uncertainty. It generated high-resolution topographic realizations to investigate the impact of basal topographic uncertainty on critical subglacial hydrological flow patterns associated with ice velocity.
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...
