Articles | Volume 11, issue 11
https://doi.org/10.5194/gmd-11-4563-2018
© Author(s) 2018. 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-11-4563-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
16 Nov 2018
Development and technical paper |
| 16 Nov 2018
| 16 Nov 2018
Dynamically coupling full Stokes and shallow shelf approximation for marine ice sheet flow using Elmer/Ice (v8.3)
Eef C. H. van Dongen
CORRESPONDING AUTHOR
Laboratory of Hydraulics, Hydrology and Glaciology, ETHZ, Zurich, Switzerland
Department of Physical Geography, Stockholm University, Stockholm, Sweden
Department of Applied Mathematical Analysis, Delft University of Technology, Delft, the Netherlands
Institute for Marine and Atmospheric Research Utrecht, Utrecht University, Utrecht, the Netherlands
Nina Kirchner
Department of Physical Geography, Stockholm University, Stockholm, Sweden
Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden
Martin B. van Gijzen
Department of Applied Mathematical Analysis, Delft University of Technology, Delft, the Netherlands
Roderik S. W. van de Wal
Institute for Marine and Atmospheric Research Utrecht, Utrecht University, Utrecht, the Netherlands
Thomas Zwinger
CSC-IT Center for Science, Espoo, Finland
Gong Cheng
Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden
Division of Scientific Computing, Department of Information Technology, Uppsala University, Uppsala, Sweden
Per Lötstedt
Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden
Division of Scientific Computing, Department of Information Technology, Uppsala University, Uppsala, Sweden
Lina von Sydow
Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden
Division of Scientific Computing, Department of Information Technology, Uppsala University, Uppsala, Sweden
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Meike Scherrenberg, Constantijn Berends, and Roderik van de Wal
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Meike D. W. Scherrenberg, Constantijn J. Berends, Lennert B. Stap, and Roderik S. W. van de Wal
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Lennert B. Stap, Constantijn J. Berends, Meike D. W. Scherrenberg, Roderik S. W. van de Wal, and Edward G. W. Gasson
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Earth Syst. Dynam., 13, 457–593, https://doi.org/10.5194/esd-13-457-2022, https://doi.org/10.5194/esd-13-457-2022, 2022
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Constantijn J. Berends, Heiko Goelzer, and Roderik S. W. van de Wal
Geosci. Model Dev., 14, 2443–2470, https://doi.org/10.5194/gmd-14-2443-2021, https://doi.org/10.5194/gmd-14-2443-2021, 2021
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The largest uncertainty in projections of sea-level rise comes from ice-sheet retreat. To better understand how these ice sheets respond to the changing climate, ice-sheet models are used, which must be able to reproduce both their present and past evolution. We have created a model that is fast enough to simulate an ice sheet at a high resolution over the course of an entire 120 000-year glacial cycle. This allows us to study processes that cannot be captured by lower-resolution models.
Gong Cheng, Nina Kirchner, and Per Lötstedt
The Cryosphere, 15, 715–742, https://doi.org/10.5194/tc-15-715-2021, https://doi.org/10.5194/tc-15-715-2021, 2021
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We present an inverse modeling approach to improve the understanding of spatiotemporally variable processes at the inaccessible base of an ice sheet by determining the sensitivity of direct surface observations to perturbations of basal conditions. Time dependency is proved to be important in these types of problems. The effect of perturbations is analyzed based on analytical and numerical solutions.
Rupert Gladstone, Benjamin Galton-Fenzi, David Gwyther, Qin Zhou, Tore Hattermann, Chen Zhao, Lenneke Jong, Yuwei Xia, Xiaoran Guo, Konstantinos Petrakopoulos, Thomas Zwinger, Daniel Shapero, and John Moore
Geosci. Model Dev., 14, 889–905, https://doi.org/10.5194/gmd-14-889-2021, https://doi.org/10.5194/gmd-14-889-2021, 2021
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Retreat of the Antarctic ice sheet, and hence its contribution to sea level rise, is highly sensitive to melting of its floating ice shelves. This melt is caused by warm ocean currents coming into contact with the ice. Computer models used for future ice sheet projections are not able to realistically evolve these melt rates. We describe a new coupling framework to enable ice sheet and ocean computer models to interact, allowing projection of the evolution of melt and its impact on sea level.
Eef C. H. van Dongen, Guillaume Jouvet, Shin Sugiyama, Evgeny A. Podolskiy, Martin Funk, Douglas I. Benn, Fabian Lindner, Andreas Bauder, Julien Seguinot, Silvan Leinss, and Fabian Walter
The Cryosphere, 15, 485–500, https://doi.org/10.5194/tc-15-485-2021, https://doi.org/10.5194/tc-15-485-2021, 2021
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The dynamic mass loss of tidewater glaciers is strongly linked to glacier calving. We study calving mechanisms under a thinning regime, based on 5 years of field and remote-sensing data of Bowdoin Glacier. Our data suggest that Bowdoin Glacier ungrounded recently, and its calving behaviour changed from calving due to surface crevasses to buoyancy-induced calving resulting from basal crevasses. This change may be a precursor to glacier retreat.
Constantijn J. Berends, Bas de Boer, and Roderik S. W. van de Wal
Clim. Past, 17, 361–377, https://doi.org/10.5194/cp-17-361-2021, https://doi.org/10.5194/cp-17-361-2021, 2021
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For the past 2.6 million years, the Earth has experienced glacial cycles, where vast ice sheets periodically grew to cover large parts of North America and Eurasia. In the earlier part of this period, this happened every 40 000 years. This value changed 1.2 million years ago to 100 000 years: the Mid-Pleistocene Transition. We investigate this interesting period using an ice-sheet model, studying the interactions between ice sheets and the global climate.
Xavier Fettweis, Stefan Hofer, Uta Krebs-Kanzow, Charles Amory, Teruo Aoki, Constantijn J. Berends, Andreas Born, Jason E. Box, Alison Delhasse, Koji Fujita, Paul Gierz, Heiko Goelzer, Edward Hanna, Akihiro Hashimoto, Philippe Huybrechts, Marie-Luise Kapsch, Michalea D. King, Christoph Kittel, Charlotte Lang, Peter L. Langen, Jan T. M. Lenaerts, Glen E. Liston, Gerrit Lohmann, Sebastian H. Mernild, Uwe Mikolajewicz, Kameswarrao Modali, Ruth H. Mottram, Masashi Niwano, Brice Noël, Jonathan C. Ryan, Amy Smith, Jan Streffing, Marco Tedesco, Willem Jan van de Berg, Michiel van den Broeke, Roderik S. W. van de Wal, Leo van Kampenhout, David Wilton, Bert Wouters, Florian Ziemen, and Tobias Zolles
The Cryosphere, 14, 3935–3958, https://doi.org/10.5194/tc-14-3935-2020, https://doi.org/10.5194/tc-14-3935-2020, 2020
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We evaluated simulated Greenland Ice Sheet surface mass balance from 5 kinds of models. While the most complex (but expensive to compute) models remain the best, the faster/simpler models also compare reliably with observations and have biases of the same order as the regional models. Discrepancies in the trend over 2000–2012, however, suggest that large uncertainties remain in the modelled future SMB changes as they are highly impacted by the meltwater runoff biases over the current climate.
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.
Sophie Nowicki, Heiko Goelzer, Hélène Seroussi, Anthony J. Payne, William H. Lipscomb, Ayako Abe-Ouchi, Cécile Agosta, Patrick Alexander, Xylar S. Asay-Davis, Alice Barthel, Thomas J. Bracegirdle, Richard Cullather, Denis Felikson, Xavier Fettweis, Jonathan M. Gregory, Tore Hattermann, Nicolas C. Jourdain, Peter Kuipers Munneke, Eric Larour, Christopher M. Little, Mathieu Morlighem, Isabel Nias, Andrew Shepherd, Erika Simon, Donald Slater, Robin S. Smith, Fiammetta Straneo, Luke D. Trusel, Michiel R. van den Broeke, and Roderik van de Wal
The Cryosphere, 14, 2331–2368, https://doi.org/10.5194/tc-14-2331-2020, https://doi.org/10.5194/tc-14-2331-2020, 2020
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This paper describes the experimental protocol for ice sheet models taking part in the Ice Sheet Model Intercomparion Project for CMIP6 (ISMIP6) and presents an overview of the atmospheric and oceanic datasets to be used for the simulations. The ISMIP6 framework allows for exploring the uncertainty in 21st century sea level change from the Greenland and Antarctic ice sheets.
Heiko Goelzer, Brice P. Y. Noël, Tamsin L. Edwards, Xavier Fettweis, Jonathan M. Gregory, William H. Lipscomb, Roderik S. W. van de Wal, and Michiel R. van den Broeke
The Cryosphere, 14, 1747–1762, https://doi.org/10.5194/tc-14-1747-2020, https://doi.org/10.5194/tc-14-1747-2020, 2020
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Future sea-level change projections with process-based ice sheet models are typically driven with surface mass balance forcing derived from climate models. In this work we address the problems arising from a mismatch of the modelled ice sheet geometry with the one used by the climate model. The proposed remapping method reproduces the original forcing data closely when applied to the original geometry and produces a physically meaningful forcing when applied to different modelled geometries.
Gong Cheng, Per Lötstedt, and Lina von Sydow
Geosci. Model Dev., 13, 2245–2258, https://doi.org/10.5194/gmd-13-2245-2020, https://doi.org/10.5194/gmd-13-2245-2020, 2020
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A full Stokes subgrid scheme in two dimensions for the grounding line migration problem is presented in the open-source finite-element framework Elmer/ICE. This method can achieve comparable results to previous research using a more than 20 times larger mesh size, which can be used to improve the efficiency in marine ice sheet simulations.
Thomas Zwinger, Grace A. Nield, Juha Ruokolainen, and Matt A. King
Geosci. Model Dev., 13, 1155–1164, https://doi.org/10.5194/gmd-13-1155-2020, https://doi.org/10.5194/gmd-13-1155-2020, 2020
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We present a newly developed flat-earth model, Elmer/Earth, for viscoelastic treatment of solid earth deformation under ice loads. Unlike many previous approaches with proprietary software, this model is based on the open-source FEM code Elmer, with the advantage for scientists to apply and alter the model without license constraints. The new-generation full-stress ice-sheet model Elmer/Ice shares the same code base, enabling future coupled ice-sheet–glacial-isostatic-adjustment simulations.
Heiko Goelzer, Violaine Coulon, Frank Pattyn, Bas de Boer, and Roderik van de Wal
The Cryosphere, 14, 833–840, https://doi.org/10.5194/tc-14-833-2020, https://doi.org/10.5194/tc-14-833-2020, 2020
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In our ice-sheet modelling experience and from exchange with colleagues in different groups, we found that it is not always clear how to calculate the sea-level contribution from a marine ice-sheet model. This goes hand in hand with a lack of documentation and transparency in the published literature on how the sea-level contribution is estimated in different models. With this brief communication, we hope to stimulate awareness and discussion in the community to improve on this situation.
Gong Cheng and Per Lötstedt
The Cryosphere, 14, 673–691, https://doi.org/10.5194/tc-14-673-2020, https://doi.org/10.5194/tc-14-673-2020, 2020
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We present a time-dependent inverse method for ice sheet modeling. By investigating the sensitivity of the observations of the velocity and the height at the surface to the basal conditions of the ice, we show that if the basal parameters are time dependent, then time cannot be ignored in the inversion. By looking at the numerical features, we conclude that adding the height information of an ice sheet in the velocity inversion procedure could improve the robustness of the inference.
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.
Guillaume Jouvet, Eef van Dongen, Martin P. Lüthi, and Andreas Vieli
Geosci. Instrum. Method. Data Syst., 9, 1–10, https://doi.org/10.5194/gi-9-1-2020, https://doi.org/10.5194/gi-9-1-2020, 2020
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We report the first-ever in situ measurements of ice flow motion using a remotely controlled drone. We used a quadcopter to land on a highly crevassed area of Eqip Sermia Glacier, Greenland. The drone measured 70 cm of ice displacement over more than 4 h thanks to an accurate onboard GPS. Our study demonstrates that drones have great potential for geoscientists, especially to deploy sensors in hostile environments such as glaciers.
Constantijn J. Berends, Bas de Boer, Aisling M. Dolan, Daniel J. Hill, and Roderik S. W. van de Wal
Clim. Past, 15, 1603–1619, https://doi.org/10.5194/cp-15-1603-2019, https://doi.org/10.5194/cp-15-1603-2019, 2019
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The Late Pliocene, 3.65–2.75 million years ago, is the most recent period in Earth's history that was warmer than the present. This makes it interesting for climatological research, because it provides a possible analogue for the near future. We used a coupled ice-sheet–climate model to simulate the behaviour of these systems during this period. We show that the warmest moment saw a sea-level rise of 8–14 m, with a CO2 concentration of 320–400 ppmv.
Shahbaz Memon, Dorothée Vallot, Thomas Zwinger, Jan Åström, Helmut Neukirchen, Morris Riedel, and Matthias Book
Geosci. Model Dev., 12, 3001–3015, https://doi.org/10.5194/gmd-12-3001-2019, https://doi.org/10.5194/gmd-12-3001-2019, 2019
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Scientific workflows enable complex scientific computational scenarios, which include data intensive scenarios, parametric executions, and interactive simulations. In this article, we applied the UNICORE workflow management system to automate a formerly hard-coded coupling of a glacier flow model and a calving model, which contain many tasks and dependencies, ranging from pre-processing and data management to repetitive executions on heterogeneous high-performance computing (HPC) resources.
Sergey Marchenko, Gong Cheng, Per Lötstedt, Veijo Pohjola, Rickard Pettersson, Ward van Pelt, and Carleen Reijmer
The Cryosphere, 13, 1843–1859, https://doi.org/10.5194/tc-13-1843-2019, https://doi.org/10.5194/tc-13-1843-2019, 2019
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Thermal conductivity (k) of firn at Lomonosovfonna, Svalbard, is estimated using measured temperature evolution and density. The optimized k values (0.2–1.6 W (m K)−1) increase downwards and over time and are most sensitive to systematic errors in measured temperature values and their depths, particularly in the lower part of the profile. Compared to the density-based parameterizations, derived k values are consistently larger, suggesting a faster conductive heat exchange in firn.
Joe Todd, Poul Christoffersen, Thomas Zwinger, Peter Råback, and Douglas I. Benn
The Cryosphere, 13, 1681–1694, https://doi.org/10.5194/tc-13-1681-2019, https://doi.org/10.5194/tc-13-1681-2019, 2019
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The Greenland Ice Sheet loses 30 %–60 % of its ice due to iceberg calving. Calving processes and their links to climate are not well understood or incorporated into numerical models of glaciers. Here we use a new 3-D calving model to investigate calving at Store Glacier, West Greenland, and test its sensitivity to increased submarine melting and reduced support from ice mélange (sea ice and icebergs). We find Store remains fairly stable despite these changes, but less so in the southern side.
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.
Constantijn J. Berends, Bas de Boer, and Roderik S. W. van de Wal
Geosci. Model Dev., 11, 4657–4675, https://doi.org/10.5194/gmd-11-4657-2018, https://doi.org/10.5194/gmd-11-4657-2018, 2018
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We have devised a novel way to couple a climate model to an ice-sheet model. Usually, climate models are too slow to simulate more than a few centuries, whereas our new model set-up can simulate a full 120 000-year ice age in about 12 h. This makes it possible to look at the interactions between global climate and ice sheets on long timescales, something which is relevant for both research into past climate and future projections.
Chen Zhao, Rupert M. Gladstone, Roland C. Warner, Matt A. King, Thomas Zwinger, and Mathieu Morlighem
The Cryosphere, 12, 2637–2652, https://doi.org/10.5194/tc-12-2637-2018, https://doi.org/10.5194/tc-12-2637-2018, 2018
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A combination of computer modelling and observational data were used to infer the resistance to ice flow at the bed of the Fleming Glacier on the Antarctic Peninsula. The model was also used to simulate the distribution of temperature within the ice, which governs the rate at which the ice can deform. This is especially important for glaciers like the Fleming Glacier, which has both regions of rapid deformation and regions of rapid sliding at the bed.
Chen Zhao, Rupert M. Gladstone, Roland C. Warner, Matt A. King, Thomas Zwinger, and Mathieu Morlighem
The Cryosphere, 12, 2653–2666, https://doi.org/10.5194/tc-12-2653-2018, https://doi.org/10.5194/tc-12-2653-2018, 2018
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A combination of computer modelling and observational data were used to infer the resistance to ice flow at the bed of the Fleming Glacier on the Antarctic Peninsula in both 2008 and 2015. The comparison suggests the grounding line retreated by ~ 9 km from 2008 to 2015. The retreat may be enhanced by a positive feedback between friction, melting and sliding at the glacier bed.
Sue Cook, Jan Åström, Thomas Zwinger, Benjamin Keith Galton-Fenzi, Jamin Stevens Greenbaum, and Richard Coleman
The Cryosphere, 12, 2401–2411, https://doi.org/10.5194/tc-12-2401-2018, https://doi.org/10.5194/tc-12-2401-2018, 2018
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The growth of fractures on Antarctic ice shelves is important because it controls the amount of ice lost as icebergs. We use a model constructed of multiple interconnected blocks to predict the locations where fractures will form on the Totten Ice Shelf in East Antarctica. The results show that iceberg calving is controlled not only by fractures forming near the front of the ice shelf but also by fractures which formed many kilometres upstream.
Sarah L. Bradley, Thomas J. Reerink, Roderik S. W. van de Wal, and Michiel M. Helsen
Clim. Past, 14, 619–635, https://doi.org/10.5194/cp-14-619-2018, https://doi.org/10.5194/cp-14-619-2018, 2018
Yongmei Gong, Thomas Zwinger, Jan Åström, Bas Altena, Thomas Schellenberger, Rupert Gladstone, and John C. Moore
The Cryosphere, 12, 1563–1577, https://doi.org/10.5194/tc-12-1563-2018, https://doi.org/10.5194/tc-12-1563-2018, 2018
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In this study we apply a discrete element model capable of simulating ice fracturing. A microscopic-scale discrete process is applied in addition to a continuum ice dynamics model to investigate the mechanisms facilitated by basal meltwater production, surface meltwater and ice crack opening, for the surge in Basin 3, Austfonna ice cap. The discrete element model is used to locate the ice cracks that can penetrate though the full thickness of the glacier and deliver surface water to the bed.
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.
Brice Noël, Willem Jan van de Berg, J. Melchior van Wessem, Erik van Meijgaard, Dirk van As, Jan T. M. Lenaerts, Stef Lhermitte, Peter Kuipers Munneke, C. J. P. Paul Smeets, Lambertus H. van Ulft, Roderik S. W. van de Wal, and Michiel R. van den Broeke
The Cryosphere, 12, 811–831, https://doi.org/10.5194/tc-12-811-2018, https://doi.org/10.5194/tc-12-811-2018, 2018
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We present a detailed evaluation of the latest version of the regional climate model RACMO2.3p2 at 11 km resolution (1958–2016) over the Greenland ice sheet (GrIS). The model successfully reproduces the present-day climate and surface mass balance, i.e. snowfall minus meltwater run-off, of the GrIS compared to in situ observations. Since run-off from marginal narrow glaciers is poorly resolved at 11 km, further statistical downscaling to 1 km resolution is required for mass balance studies.
Dorothée Vallot, Jan Åström, Thomas Zwinger, Rickard Pettersson, Alistair Everett, Douglas I. Benn, Adrian Luckman, Ward J. J. van Pelt, Faezeh Nick, and Jack Kohler
The Cryosphere, 12, 609–625, https://doi.org/10.5194/tc-12-609-2018, https://doi.org/10.5194/tc-12-609-2018, 2018
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This paper presents a new perspective on the role of ice dynamics and ocean interaction in glacier calving processes applied to Kronebreen, a tidewater glacier in Svalbard. A global modelling approach includes ice flow modelling, undercutting estimation by a combination of glacier energy balance and plume modelling as well as calving by a discrete particle model. We show that modelling undercutting is necessary and calving is influenced by basal friction velocity and geometry.
Werner M. J. Lazeroms, Adrian Jenkins, G. Hilmar Gudmundsson, and Roderik S. W. van de Wal
The Cryosphere, 12, 49–70, https://doi.org/10.5194/tc-12-49-2018, https://doi.org/10.5194/tc-12-49-2018, 2018
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Basal melting of ice shelves is a major factor in the decline of the Antarctic Ice Sheet, which can contribute significantly to sea-level rise. Here, we investigate a new basal melt model based on the dynamics of meltwater plumes. For the first time, this model is applied to all Antarctic ice shelves. The model results in a realistic melt-rate pattern given suitable data for the topography and ocean temperature, making it a promising tool for future simulations of the Antarctic Ice Sheet.
Renske C. de Winter, Thomas J. Reerink, Aimée B. A. Slangen, Hylke de Vries, Tamsin Edwards, and Roderik S. W. van de Wal
Nat. Hazards Earth Syst. Sci., 17, 2125–2141, https://doi.org/10.5194/nhess-17-2125-2017, https://doi.org/10.5194/nhess-17-2125-2017, 2017
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This paper provides a full range of possible future sea levels on a regional scale, since it includes extreme, but possible, contributions to sea level change from dynamical mass loss from the Greenland and Antarctica ice sheets. In contrast to the symmetric distribution used in the IPCC report, it is found that an asymmetric distribution toward high sea level change values locally can increase the mean sea level by 1.8 m this century.
Matt O'Regan, Jan Backman, Natalia Barrientos, Thomas M. Cronin, Laura Gemery, Nina Kirchner, Larry A. Mayer, Johan Nilsson, Riko Noormets, Christof Pearce, Igor Semiletov, Christian Stranne, and Martin Jakobsson
Clim. Past, 13, 1269–1284, https://doi.org/10.5194/cp-13-1269-2017, https://doi.org/10.5194/cp-13-1269-2017, 2017
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Past glacial activity on the East Siberian continental margin is poorly known, partly due to the lack of geomorphological evidence. Here we present geophysical mapping and sediment coring data from the East Siberian shelf and slope revealing the presence of a glacially excavated cross-shelf trough reaching to the continental shelf edge north of the De Long Islands. The data provide direct evidence for extensive glacial activity on the Siberian shelf that predates the Last Glacial Maximum.
Lennert B. Stap, Roderik S. W. van de Wal, Bas de Boer, Richard Bintanja, and Lucas J. Lourens
Clim. Past, 13, 1243–1257, https://doi.org/10.5194/cp-13-1243-2017, https://doi.org/10.5194/cp-13-1243-2017, 2017
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We show the results of transient simulations with a coupled climate–ice sheet model over the past 38 million years. The CO2 forcing of the model is inversely obtained from a benthic δ18O stack. These simulations enable us to study the influence of ice sheet variability on climate change on long timescales. We find that ice sheet–climate interaction strongly enhances Earth system sensitivity and polar amplification.
Hakime Seddik, Ralf Greve, Thomas Zwinger, and Shin Sugiyama
The Cryosphere, 11, 2213–2229, https://doi.org/10.5194/tc-11-2213-2017, https://doi.org/10.5194/tc-11-2213-2017, 2017
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The Shirase Glacier in Antarctica is studied by means of a computer model. This model implements two physical approaches to represent the glacier flow dynamics. This study finds that it is important to use the more precise and sophisticated method in order to better understand and predict the evolution of fast flowing glaciers. This may be important to more accurately predict the sea level change due to global warming.
Michiel M. Helsen, Roderik S. W. van de Wal, Thomas J. Reerink, Richard Bintanja, Marianne S. Madsen, Shuting Yang, Qiang Li, and Qiong Zhang
The Cryosphere, 11, 1949–1965, https://doi.org/10.5194/tc-11-1949-2017, https://doi.org/10.5194/tc-11-1949-2017, 2017
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Ice sheets reflect most incoming solar radiation back into space due to their high reflectivity (albedo). The albedo of ice sheets changes as a function of, for example, liquid water content and ageing of snow. In this study we have improved the description of albedo over the Greenland ice sheet in a global climate model. This is an important step, which also improves estimates of the annual ice mass gain or loss over the ice sheet using this global climate model.
Johan Nilsson, Martin Jakobsson, Chris Borstad, Nina Kirchner, Göran Björk, Raymond T. Pierrehumbert, and Christian Stranne
The Cryosphere, 11, 1745–1765, https://doi.org/10.5194/tc-11-1745-2017, https://doi.org/10.5194/tc-11-1745-2017, 2017
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Recent data suggest that a 1 km thick ice shelf extended over the glacial Arctic Ocean during MIS 6, about 140 000 years ago. Here, we theoretically analyse the development and equilibrium features of such an ice shelf. The ice shelf was effectively dammed by the Fram Strait and the mean ice-shelf thickness was controlled primarily by the horizontally integrated mass balance. Our results can aid in resolving some outstanding questions of the state of the glacial Arctic Ocean.
Markella Prokopiou, Patricia Martinerie, Célia J. Sapart, Emmanuel Witrant, Guillaume Monteil, Kentaro Ishijima, Sophie Bernard, Jan Kaiser, Ingeborg Levin, Thomas Blunier, David Etheridge, Ed Dlugokencky, Roderik S. W. van de Wal, and Thomas Röckmann
Atmos. Chem. Phys., 17, 4539–4564, https://doi.org/10.5194/acp-17-4539-2017, https://doi.org/10.5194/acp-17-4539-2017, 2017
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Nitrous oxide is the third most important anthropogenic greenhouse gas with an increasing mole fraction. To understand its natural and anthropogenic sources
we employ isotope measurements. Results show that while the N2O mole fraction increases, its heavy isotope content decreases. The isotopic changes observed underline the dominance of agricultural emissions especially at the early part of the record, whereas in the later decades the contribution from other anthropogenic sources increases.
Rupert Michael Gladstone, Roland Charles Warner, Benjamin Keith Galton-Fenzi, Olivier Gagliardini, Thomas Zwinger, and Ralf Greve
The Cryosphere, 11, 319–329, https://doi.org/10.5194/tc-11-319-2017, https://doi.org/10.5194/tc-11-319-2017, 2017
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Computer models are used to simulate the behaviour of glaciers and ice sheets. It has been found that such models are required to be run at very high resolution (which means high computational expense) in order to accurately represent the evolution of marine ice sheets (ice sheets resting on bedrock below sea level), in certain situations which depend on sub-glacial physical processes.
Constantijn J. Berends and Roderik S. W. van de Wal
Geosci. Model Dev., 9, 4451–4460, https://doi.org/10.5194/gmd-9-4451-2016, https://doi.org/10.5194/gmd-9-4451-2016, 2016
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This paper describes several improvements to the so-called "flood-fill algorithm" – a computer program widely known for its use in the "paint bucket" tool in several drawing programs such as MS Paint. However, it can also be used to determine the extent and depth of lakes in a topography map, which is useful in hydrology and climatology. In such cases, the default algorithm can be too slow to be of much use. Our improvements can make it up to 100 times faster, making it much more feasible.
Thomas J. Reerink, Willem Jan van de Berg, and Roderik S. W. van de Wal
Geosci. Model Dev., 9, 4111–4132, https://doi.org/10.5194/gmd-9-4111-2016, https://doi.org/10.5194/gmd-9-4111-2016, 2016
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Ice sheets are part of the climate system and interact with the atmosphere and the ocean. OBLIMAP is a powerful tool to map climate fields between GCMs and ISMs (ice sheet models), which run on grids that differ in curvature, resolution and extent. OBLIMAP uses optimal aligned oblique projections, which minimize area distortions. OBLIMAP 2.0 allows for high-frequency embedded coupling and masked mapping. A fast search strategy realizes a huge performance gain and enables high-resolution mapping.
Peter Köhler, Lennert B. Stap, Anna S. von der Heydt, Bas de Boer, and Roderik S. W. van de Wal
Clim. Past Discuss., https://doi.org/10.5194/cp-2016-23, https://doi.org/10.5194/cp-2016-23, 2016
Revised manuscript not accepted
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Evidence indicate that specific equilibrium climate sensitivity, the global annual mean surface temperature change as a response to a change in radiative forcing, is state dependent. We here show that the interpretation of data in the state-dependent case is not straightforward. We analyse the differences of a point-wise approach and one based on a piece-wise linear analysis, combine both, compare with potential model results and apply the theoretical concepts to data of the last 800 kyr.
P. Köhler, B. de Boer, A. S. von der Heydt, L. B. Stap, and R. S. W. van de Wal
Clim. Past, 11, 1801–1823, https://doi.org/10.5194/cp-11-1801-2015, https://doi.org/10.5194/cp-11-1801-2015, 2015
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We find that the specific equilibrium climate sensitivity due to radiative forcing of CO2 and land ice albedo has been state-dependent for the last 2.1Myr (most of the Pleistocene). Its value is ~45% larger during intermediate glaciated climates and interglacial periods than during Pleistocene full glacial conditions. The state dependency is mainly caused by a latitudinal dependency in ice sheet area changes. Due to uncertainties in CO2, firm conclusions for the Pliocene are not yet possible.
B. Noël, W. J. van de Berg, E. van Meijgaard, P. Kuipers Munneke, R. S. W. van de Wal, and M. R. van den Broeke
The Cryosphere, 9, 1831–1844, https://doi.org/10.5194/tc-9-1831-2015, https://doi.org/10.5194/tc-9-1831-2015, 2015
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We compare Greenland Ice Sheet surface mass balance (SMB) from the updated polar version of the regional climate model RACMO2.3 and the previous version 2.1. RACMO2.3 has an adjusted rainfall-to-snowfall conversion favouring summer snowfall over rainfall. Enhanced summer snowfall reduce melt rates in the ablation zone by covering dark ice with highly reflective fresh snow. This improves the modelled SMB-elevation gradient and surface energy balance compared to observations in west Greenland.
T. Zwinger, T. Malm, M. Schäfer, R. Stenberg, and J. C. Moore
The Cryosphere, 9, 1415–1426, https://doi.org/10.5194/tc-9-1415-2015, https://doi.org/10.5194/tc-9-1415-2015, 2015
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By deploying a large-scale high-resolution turbulent CFD simulation using the present-day topography of the Scharffenbergbotnen (SBB) valley, we show how the surrounding topography redirects incoming easterly katabatic storm fronts to impact the blue ice areas (BIA) inside the valley, where the snow cover frequently is removed. A further simulation of a reconstructed topography at the Late Glacial Maximum further reveals that the BIA at SBB must have formed after this period.
L. G. van der Wel, H. A. Been, R. S. W. van de Wal, C. J. P. P. Smeets, and H. A. J. Meijer
The Cryosphere, 9, 1089–1103, https://doi.org/10.5194/tc-9-1089-2015, https://doi.org/10.5194/tc-9-1089-2015, 2015
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We performed 2H isotope diffusion measurements in the upper 3 metres of firn at Summit, Greenland, by following over a 4-year period isotope-enriched snow that we deposited.
We found that the diffusion process was much less rapid than in the most commonly used model. We discuss several aspects of the diffusion process that are still poorly constrained and might lead to this discrepancy. Quantitative knowledge of diffusion is necessary for use of the diffusion process itself as a climate proxy.
B. de Boer, A. M. Dolan, J. Bernales, E. Gasson, H. Goelzer, N. R. Golledge, J. Sutter, P. Huybrechts, G. Lohmann, I. Rogozhina, A. Abe-Ouchi, F. Saito, and R. S. W. van de Wal
The Cryosphere, 9, 881–903, https://doi.org/10.5194/tc-9-881-2015, https://doi.org/10.5194/tc-9-881-2015, 2015
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We present results from simulations of the Antarctic ice sheet by means of an intercomparison project with six ice-sheet models. Our results demonstrate the difficulty of all models used here to simulate a significant retreat or re-advance of the East Antarctic ice grounding line. Improved grounding-line physics could be essential for a correct representation of the migration of the grounding line of the Antarctic ice sheet during the Pliocene.
R. S. W. van de Wal, C. J. P. P. Smeets, W. Boot, M. Stoffelen, R. van Kampen, S. H. Doyle, F. Wilhelms, M. R. van den Broeke, C. H. Reijmer, J. Oerlemans, and A. Hubbard
The Cryosphere, 9, 603–611, https://doi.org/10.5194/tc-9-603-2015, https://doi.org/10.5194/tc-9-603-2015, 2015
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This paper addresses the feedback between ice flow and melt rates. Using 20 years of data covering the whole ablation area, we show that there is not a strong positive correlation between annual ice velocities and melt rates. Rapid variations around the equilibrium line indicate the possibility of rapid variations high on the ice sheet.
S. J. Koenig, A. M. Dolan, B. de Boer, E. J. Stone, D. J. Hill, R. M. DeConto, A. Abe-Ouchi, D. J. Lunt, D. Pollard, A. Quiquet, F. Saito, J. Savage, and R. van de Wal
Clim. Past, 11, 369–381, https://doi.org/10.5194/cp-11-369-2015, https://doi.org/10.5194/cp-11-369-2015, 2015
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The paper assess the Greenland Ice Sheet’s sensitivity to a warm period in the past, a time when atmospheric CO2 concentrations were comparable to current levels. We quantify ice sheet volume and locations in Greenland and find that the ice sheets are less sensitive to differences in ice sheet model configurations than to changes in imposed climate forcing. We conclude that Pliocene ice was most likely to be limited to highest elevations in eastern and southern Greenland.
P. M. Alexander, M. Tedesco, X. Fettweis, R. S. W. van de Wal, C. J. P. P. Smeets, and M. R. van den Broeke
The Cryosphere, 8, 2293–2312, https://doi.org/10.5194/tc-8-2293-2014, https://doi.org/10.5194/tc-8-2293-2014, 2014
L. B. Stap, R. S. W. van de Wal, B. de Boer, R. Bintanja, and L. J. Lourens
Clim. Past, 10, 2135–2152, https://doi.org/10.5194/cp-10-2135-2014, https://doi.org/10.5194/cp-10-2135-2014, 2014
M. Schäfer, F. Gillet-Chaulet, R. Gladstone, R. Pettersson, V. A. Pohjola, T. Strozzi, and T. Zwinger
The Cryosphere, 8, 1951–1973, https://doi.org/10.5194/tc-8-1951-2014, https://doi.org/10.5194/tc-8-1951-2014, 2014
B. de Boer, P. Stocchi, and R. S. W. van de Wal
Geosci. Model Dev., 7, 2141–2156, https://doi.org/10.5194/gmd-7-2141-2014, https://doi.org/10.5194/gmd-7-2141-2014, 2014
R. Gladstone, M. Schäfer, T. Zwinger, Y. Gong, T. Strozzi, R. Mottram, F. Boberg, and J. C. Moore
The Cryosphere, 8, 1393–1405, https://doi.org/10.5194/tc-8-1393-2014, https://doi.org/10.5194/tc-8-1393-2014, 2014
B. Sun, J. C. Moore, T. Zwinger, L. Zhao, D. Steinhage, X. Tang, D. Zhang, X. Cui, and C. Martín
The Cryosphere, 8, 1121–1128, https://doi.org/10.5194/tc-8-1121-2014, https://doi.org/10.5194/tc-8-1121-2014, 2014
A. B. A. Slangen, R. S. W. van de Wal, Y. Wada, and L. L. A. Vermeersen
Earth Syst. Dynam., 5, 243–255, https://doi.org/10.5194/esd-5-243-2014, https://doi.org/10.5194/esd-5-243-2014, 2014
S. Cook, I. C. Rutt, T. Murray, A. Luckman, T. Zwinger, N. Selmes, A. Goldsack, and T. D. James
The Cryosphere, 8, 827–841, https://doi.org/10.5194/tc-8-827-2014, https://doi.org/10.5194/tc-8-827-2014, 2014
T. Zwinger, M. Schäfer, C. Martín, and J. C. Moore
The Cryosphere, 8, 607–621, https://doi.org/10.5194/tc-8-607-2014, https://doi.org/10.5194/tc-8-607-2014, 2014
T. Sato, T. Shiraiwa, R. Greve, H. Seddik, E. Edelmann, and T. Zwinger
Clim. Past, 10, 393–404, https://doi.org/10.5194/cp-10-393-2014, https://doi.org/10.5194/cp-10-393-2014, 2014
B. de Fleurian, O. Gagliardini, T. Zwinger, G. Durand, E. Le Meur, D. Mair, and P. Råback
The Cryosphere, 8, 137–153, https://doi.org/10.5194/tc-8-137-2014, https://doi.org/10.5194/tc-8-137-2014, 2014
J. Ahlkrona, N. Kirchner, and P. Lötstedt
Geosci. Model Dev., 6, 2135–2152, https://doi.org/10.5194/gmd-6-2135-2013, https://doi.org/10.5194/gmd-6-2135-2013, 2013
J. A. Åström, T. I. Riikilä, T. Tallinen, T. Zwinger, D. Benn, J. C. Moore, and J. Timonen
The Cryosphere, 7, 1591–1602, https://doi.org/10.5194/tc-7-1591-2013, https://doi.org/10.5194/tc-7-1591-2013, 2013
O. Gagliardini, T. Zwinger, F. Gillet-Chaulet, G. Durand, L. Favier, B. de Fleurian, R. Greve, M. Malinen, C. Martín, P. Råback, J. Ruokolainen, M. Sacchettini, M. Schäfer, H. Seddik, and J. Thies
Geosci. Model Dev., 6, 1299–1318, https://doi.org/10.5194/gmd-6-1299-2013, https://doi.org/10.5194/gmd-6-1299-2013, 2013
M. M. Helsen, W. J. van de Berg, R. S. W. van de Wal, M. R. van den Broeke, and J. Oerlemans
Clim. Past, 9, 1773–1788, https://doi.org/10.5194/cp-9-1773-2013, https://doi.org/10.5194/cp-9-1773-2013, 2013
A. S. Drouet, D. Docquier, G. Durand, R. Hindmarsh, F. Pattyn, O. Gagliardini, and T. Zwinger
The Cryosphere, 7, 395–406, https://doi.org/10.5194/tc-7-395-2013, https://doi.org/10.5194/tc-7-395-2013, 2013
L. Zhao, L. Tian, T. Zwinger, R. Ding, J. Zong, Q. Ye, and J. C. Moore
The Cryosphere Discuss., https://doi.org/10.5194/tcd-7-145-2013, https://doi.org/10.5194/tcd-7-145-2013, 2013
Revised manuscript not accepted
F. Gillet-Chaulet, O. Gagliardini, H. Seddik, M. Nodet, G. Durand, C. Ritz, T. Zwinger, R. Greve, and D. G. Vaughan
The Cryosphere, 6, 1561–1576, https://doi.org/10.5194/tc-6-1561-2012, https://doi.org/10.5194/tc-6-1561-2012, 2012
M. M. Helsen, R. S. W. van de Wal, M. R. van den Broeke, W. J. van de Berg, and J. Oerlemans
The Cryosphere, 6, 255–272, https://doi.org/10.5194/tc-6-255-2012, https://doi.org/10.5194/tc-6-255-2012, 2012
R. S. W. van de Wal, B. de Boer, L. J. Lourens, P. Köhler, and R. Bintanja
Clim. Past, 7, 1459–1469, https://doi.org/10.5194/cp-7-1459-2011, https://doi.org/10.5194/cp-7-1459-2011, 2011
A. B. A. Slangen and R. S. W. van de Wal
The Cryosphere, 5, 673–686, https://doi.org/10.5194/tc-5-673-2011, https://doi.org/10.5194/tc-5-673-2011, 2011
D. Liebrand, L. J. Lourens, D. A. Hodell, B. de Boer, R. S. W. van de Wal, and H. Pälike
Clim. Past, 7, 869–880, https://doi.org/10.5194/cp-7-869-2011, https://doi.org/10.5194/cp-7-869-2011, 2011
I. G. M. Wientjes, R. S. W. Van de Wal, G. J. Reichart, A. Sluijs, and J. Oerlemans
The Cryosphere, 5, 589–601, https://doi.org/10.5194/tc-5-589-2011, https://doi.org/10.5194/tc-5-589-2011, 2011
M. R. van den Broeke, C. J. P. P. Smeets, and R. S. W. van de Wal
The Cryosphere, 5, 377–390, https://doi.org/10.5194/tc-5-377-2011, https://doi.org/10.5194/tc-5-377-2011, 2011
M. A. G. den Ouden, C. H. Reijmer, V. Pohjola, R. S. W. van de Wal, J. Oerlemans, and W. Boot
The Cryosphere, 4, 593–604, https://doi.org/10.5194/tc-4-593-2010, https://doi.org/10.5194/tc-4-593-2010, 2010
T. J. Reerink, M. A. Kliphuis, and R. S. W. van de Wal
Geosci. Model Dev., 3, 13–41, https://doi.org/10.5194/gmd-3-13-2010, https://doi.org/10.5194/gmd-3-13-2010, 2010
M. van den Broeke, P. Smeets, J. Ettema, C. van der Veen, R. van de Wal, and J. Oerlemans
The Cryosphere, 2, 179–189, https://doi.org/10.5194/tc-2-179-2008, https://doi.org/10.5194/tc-2-179-2008, 2008
J. Oerlemans, M. Dyurgerov, and R. S. W. van de Wal
The Cryosphere, 1, 59–65, https://doi.org/10.5194/tc-1-59-2007, https://doi.org/10.5194/tc-1-59-2007, 2007
J. O. Sewall, R. S. W. van de Wal, K. van der Zwan, C. van Oosterhout, H. A. Dijkstra, and C. R. Scotese
Clim. Past, 3, 647–657, https://doi.org/10.5194/cp-3-647-2007, https://doi.org/10.5194/cp-3-647-2007, 2007
Related subject area
Cryosphere
Refactoring the EVP solver for improved performance – a case study based on CICE v6.5
openAMUNDSEN v 0.8.3: an open source snow-hydrological model for mountain regions
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
OpenFOAM-avalanche 2312: Depth-integrated Models Beyond Dense Flow Avalanches
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)
Introducing ELSA v2.0: an isochronal model for ice-sheet layer tracing
A new 3D full-Stokes calving algorithm within Elmer/Ice (v9.0)
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
A parallel implementation of the confined–unconfined aquifer system model for subglacial hydrology: design, verification, and performance analysis (CUAS-MPI v0.1.0)
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
SnowQM 1.0: A fast R Package for bias-correcting spatial fields of snow water equivalent using quantile mapping
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)
NEMO-Bohai 1.0: a high-resolution ocean and sea ice modelling system for the Bohai Sea, China
An improved regional coupled modeling system for Arctic sea ice simulation and prediction: a case study for 2018
WIFF1.0: a hybrid machine-learning-based parameterization of wave-induced sea ice floe fracture
The Whole Antarctic Ocean Model (WAOM v1.0): development and evaluation
SNICAR-ADv3: a community tool for modeling spectral snow albedo
STEMMUS-UEB v1.0.0: integrated modeling of snowpack and soil water and energy transfer with three complexity levels of soil physical processes
A versatile method for computing optimized snow albedo from spectrally fixed radiative variables: VALHALLA v1.0
Ice Algae Model Intercomparison Project phase 2 (IAMIP2)
A Gaussian process emulator for simulating ice sheet–climate interactions on a multi-million-year timescale: CLISEMv1.0
SITool (v1.0) – a new evaluation tool for large-scale sea ice simulations: application to CMIP6 OMIP
fenics_ice 1.0: a framework for quantifying initialization uncertainty for time-dependent ice sheet models
Development of adjoint-based ocean state estimation for the Amundsen and Bellingshausen seas and ice shelf cavities using MITgcm–ECCO (66j)
Sensitivity of Northern Hemisphere climate to ice–ocean interface heat flux parameterizations
icepack: a new glacier flow modeling package in Python, version 1.0
Till Andreas Soya Rasmussen, Jacob Poulsen, Mads Hvid Ribergaard, Ruchira Sasanka, Anthony P. Craig, Elizabeth Clare Hunke, and Stefan Rethmeier
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-40, https://doi.org/10.5194/gmd-2024-40, 2024
Revised manuscript accepted for GMD
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Earth system models (ESM) today strive towards better quality based on improved resolution and improved physics. One of the limiting factors is the super computers at hand and how to utilize these. This study focus on a refactorization of one part of a sea ice model (CICE), namely the dynamics. The study shows that the performance can be significantly reduced, which means that one can either run the same simulations much cheaper or advance the system according to what is needed.
Ulrich Strasser, Michael Warscher, Erwin Rottler, and Florian Hanzer
EGUsphere, https://doi.org/10.5194/egusphere-2024-193, https://doi.org/10.5194/egusphere-2024-193, 2024
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openAMUNDSEN is a fully distributed open source snow-hydrological model for mountain catchments. The model includes process representations of empirical, semi-empirical and physical nature. It uses temperature, precipitation, humidity, radiation and wind speed as forcing data, is computationally efficient, of modular nature and easily extendible. The Python model code is available on GitHub (https://github.com/openamundsen/openamundsen), including a documentation (https://doc.openamundsen.org).
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.
Matthias Rauter and Julia Kowalski
EGUsphere, https://doi.org/10.5194/egusphere-2024-210, https://doi.org/10.5194/egusphere-2024-210, 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 and 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.
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.
Therese Rieckh, Andreas Born, Alexander Robinson, Robert Law, and Gerrit Gülle
EGUsphere, https://doi.org/10.5194/egusphere-2023-3127, https://doi.org/10.5194/egusphere-2023-3127, 2024
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We present the open-source model ELSA, which simulates the internal age structure of large ice sheets. ELSA is used coupled to a full ice sheet model and creates individual layers of accumulation with fixed time stamps during the simulation, modeling 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 parametrization.
Iain Wheel, Douglas I. Benn, Anna J. Crawford, Joe A. Todd, and Thomas Zwinger
EGUsphere, https://doi.org/10.5194/egusphere-2023-2778, https://doi.org/10.5194/egusphere-2023-2778, 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.
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.
Yannic Fischler, Thomas Kleiner, Christian Bischof, Jeremie Schmiedel, Roiy Sayag, Raban Emunds, Lennart Frederik Oestreich, and Angelika Humbert
Geosci. Model Dev., 16, 5305–5322, https://doi.org/10.5194/gmd-16-5305-2023, https://doi.org/10.5194/gmd-16-5305-2023, 2023
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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.
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.
Adrien Michel, Johannes Aschauer, Tobias Jonas, Stefanie Gubler, Sven Kotlarski, and Christoph Marty
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-298, https://doi.org/10.5194/gmd-2022-298, 2023
Revised manuscript accepted for GMD
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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 last 60 years at a resolution of one day and one kilometre. This is the first time that such a dataset has been produced.
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.
Yu Yan, Wei Gu, Andrea M. U. Gierisch, Yingjun Xu, and Petteri Uotila
Geosci. Model Dev., 15, 1269–1288, https://doi.org/10.5194/gmd-15-1269-2022, https://doi.org/10.5194/gmd-15-1269-2022, 2022
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In this study, we developed NEMO-Bohai, an ocean–ice model for the Bohai Sea, China. This study presented the scientific design and technical choices of the parameterizations for the NEMO-Bohai model. The model was calibrated and evaluated with in situ and satellite observations of ocean and sea ice. NEMO-Bohai is intended to be a valuable tool for long-term ocean and ice simulations and climate change studies.
Chao-Yuan Yang, Jiping Liu, and Dake Chen
Geosci. Model Dev., 15, 1155–1176, https://doi.org/10.5194/gmd-15-1155-2022, https://doi.org/10.5194/gmd-15-1155-2022, 2022
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We present an improved coupled modeling system for Arctic sea ice prediction. We perform Arctic sea ice prediction experiments with improved/updated physical parameterizations, which show better skill in predicting sea ice state as well as atmospheric and oceanic state in the Arctic compared with its predecessor. The improved model also shows extended predictive skill of Arctic sea ice after the summer season. This provides an added value of this prediction system for decision-making.
Christopher Horvat and Lettie A. Roach
Geosci. Model Dev., 15, 803–814, https://doi.org/10.5194/gmd-15-803-2022, https://doi.org/10.5194/gmd-15-803-2022, 2022
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Sea ice is a composite of individual pieces, called floes, ranging in horizontal size from meters to kilometers. Variations in sea ice geometry are often forced by ocean waves, a process that is an important target of global climate models as it affects the rate of sea ice melting. Yet directly simulating these interactions is computationally expensive. We present a neural-network-based model of wave–ice fracture that allows models to incorporate their effect without added computational cost.
Ole Richter, David E. Gwyther, Benjamin K. Galton-Fenzi, and Kaitlin A. Naughten
Geosci. Model Dev., 15, 617–647, https://doi.org/10.5194/gmd-15-617-2022, https://doi.org/10.5194/gmd-15-617-2022, 2022
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Here we present an improved model of the Antarctic continental shelf ocean and demonstrate that it is capable of reproducing present-day conditions. The improvements are fundamental and regard the inclusion of tides and ocean eddies. We conclude that the model is well suited to gain new insights into processes that are important for Antarctic ice sheet retreat and global ocean changes. Hence, the model will ultimately help to improve projections of sea level rise and climate change.
Mark G. Flanner, Julian B. Arnheim, Joseph M. Cook, Cheng Dang, Cenlin He, Xianglei Huang, Deepak Singh, S. McKenzie Skiles, Chloe A. Whicker, and Charles S. Zender
Geosci. Model Dev., 14, 7673–7704, https://doi.org/10.5194/gmd-14-7673-2021, https://doi.org/10.5194/gmd-14-7673-2021, 2021
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We present the technical formulation and evaluation of a publicly available code and web-based model to simulate the spectral albedo of snow. Our model accounts for numerous features of the snow state and ambient conditions, including the the presence of light-absorbing matter like black and brown carbon, mineral dust, volcanic ash, and snow algae. Carbon dioxide snow, found on Mars, is also represented. The model accurately reproduces spectral measurements of clean and contaminated snow.
Lianyu Yu, Yijian Zeng, and Zhongbo Su
Geosci. Model Dev., 14, 7345–7376, https://doi.org/10.5194/gmd-14-7345-2021, https://doi.org/10.5194/gmd-14-7345-2021, 2021
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We developed an integrated soil–snow–atmosphere model (STEMMUS-UEB) dedicated to the physical description of snow and soil processes with various complexities. With STEMMUS-UEB, we demonstrated that the snowpack affects not only the soil surface moisture conditions (in the liquid and ice phase) and energy-related states (albedo, LE) but also the subsurface soil water and vapor transfer, which contributes to a better understanding of the hydrothermal implications of the snowpack in cold regions.
Florent Veillon, Marie Dumont, Charles Amory, and Mathieu Fructus
Geosci. Model Dev., 14, 7329–7343, https://doi.org/10.5194/gmd-14-7329-2021, https://doi.org/10.5194/gmd-14-7329-2021, 2021
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In climate models, the snow albedo scheme generally calculates only a narrowband or broadband albedo. Therefore, we have developed the VALHALLA method to optimize snow spectral albedo calculations through the determination of spectrally fixed radiative variables. The development of VALHALLA v1.0 with the use of the snow albedo model TARTES and the spectral irradiance model SBDART indicates a considerable reduction in calculation time while maintaining an adequate accuracy of albedo values.
Hakase Hayashida, Meibing Jin, Nadja S. Steiner, Neil C. Swart, Eiji Watanabe, Russell Fiedler, Andrew McC. Hogg, Andrew E. Kiss, Richard J. Matear, and Peter G. Strutton
Geosci. Model Dev., 14, 6847–6861, https://doi.org/10.5194/gmd-14-6847-2021, https://doi.org/10.5194/gmd-14-6847-2021, 2021
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Ice algae are tiny plants like phytoplankton but they grow within sea ice. In polar regions, both phytoplankton and ice algae are the foundation of marine ecosystems and play an important role in taking up carbon dioxide in the atmosphere. However, state-of-the-art climate models typically do not include ice algae, and therefore their role in the climate system remains unclear. This project aims to address this knowledge gap by coordinating a set of experiments using sea-ice–ocean models.
Jonas Van Breedam, Philippe Huybrechts, and Michel Crucifix
Geosci. Model Dev., 14, 6373–6401, https://doi.org/10.5194/gmd-14-6373-2021, https://doi.org/10.5194/gmd-14-6373-2021, 2021
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Ice sheets are an important component of the climate system and interact with the atmosphere through albedo variations and changes in the surface height. On very long timescales, it is impossible to directly couple ice sheet models with climate models and other techniques have to be used. Here we present a novel coupling method between ice sheets and the atmosphere by making use of an emulator to simulate ice sheet–climate interactions for several million years.
Xia Lin, François Massonnet, Thierry Fichefet, and Martin Vancoppenolle
Geosci. Model Dev., 14, 6331–6354, https://doi.org/10.5194/gmd-14-6331-2021, https://doi.org/10.5194/gmd-14-6331-2021, 2021
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This study introduces a new Sea Ice Evaluation Tool (SITool) to evaluate the model skills on the bipolar sea ice simulations by providing performance metrics and diagnostics. SITool is applied to evaluate the CMIP6 OMIP simulations. By changing the atmospheric forcing from CORE-II to JRA55-do data, many aspects of sea ice simulations are improved. SITool will be useful for helping teams managing various versions of a sea ice model or tracking the time evolution of model performance.
Conrad P. Koziol, Joe A. Todd, Daniel N. Goldberg, and James R. Maddison
Geosci. Model Dev., 14, 5843–5861, https://doi.org/10.5194/gmd-14-5843-2021, https://doi.org/10.5194/gmd-14-5843-2021, 2021
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Sea level change due to the loss of ice sheets presents great risk for coastal communities. Models are used to forecast ice loss, but their evolution depends strongly on properties which are hidden from observation and must be inferred from satellite observations. Common methods for doing so do not allow for quantification of the uncertainty inherent or how it will affect forecasts. We provide a framework for quantifying how this
initialization uncertaintyaffects ice loss forecasts.
Yoshihiro Nakayama, Dimitris Menemenlis, Ou Wang, Hong Zhang, Ian Fenty, and An T. Nguyen
Geosci. Model Dev., 14, 4909–4924, https://doi.org/10.5194/gmd-14-4909-2021, https://doi.org/10.5194/gmd-14-4909-2021, 2021
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High ice shelf melting in the Amundsen Sea has attracted many observational campaigns in the past decade. One method to combine observations with numerical models is the adjoint method. After 20 iterations, the cost function, defined as a sum of the weighted model–data difference, is reduced by 65 % by adjusting initial conditions, atmospheric forcing, and vertical diffusivity. This study demonstrates adjoint-method optimization with explicit representation of ice shelf cavity circulation.
Xiaoxu Shi, Dirk Notz, Jiping Liu, Hu Yang, and Gerrit Lohmann
Geosci. Model Dev., 14, 4891–4908, https://doi.org/10.5194/gmd-14-4891-2021, https://doi.org/10.5194/gmd-14-4891-2021, 2021
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The ice–ocean heat flux is one of the key elements controlling sea ice changes. It motivates our study, which aims to examine the responses of modeled climate to three ice–ocean heat flux parameterizations, including two old approaches that assume one-way heat transport and a new one describing a double-diffusive ice–ocean heat exchange. The results show pronounced differences in the modeled sea ice, ocean, and atmosphere states for the latter as compared to the former two parameterizations.
Daniel R. Shapero, Jessica A. Badgeley, Andrew O. Hoffman, and Ian R. Joughin
Geosci. Model Dev., 14, 4593–4616, https://doi.org/10.5194/gmd-14-4593-2021, https://doi.org/10.5194/gmd-14-4593-2021, 2021
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This paper describes a new software package called "icepack" for modeling the flow of ice sheets and glaciers. Glaciologists use tools like icepack to better understand how ice sheets flow, what role they have played in shaping Earth's climate, and how much sea level rise we can expect in the coming decades to centuries. The icepack package includes several innovations to help researchers describe and solve interesting glaciological problems and to experiment with the underlying model physics.
Cited articles
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coupling the non-linear Stokes equations with the shallow ice approximation
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Short summary
Ice flow forced by gravity is governed by the full Stokes (FS) equations, which are computationally expensive to solve. Therefore, approximations to the FS equations are used, especially when modeling an ice sheet on long time spans. Here, we report a combination of an approximation with the FS equations that allows simulating the dynamics of ice sheets over long time spans without introducing artifacts caused by application of approximations in parts of the domain where they are not valid.
Ice flow forced by gravity is governed by the full Stokes (FS) equations, which are...
