Articles | Volume 12, issue 3
https://doi.org/10.5194/gmd-12-909-2019
© Author(s) 2019. 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-12-909-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| Highlight paper
| 
08 Mar 2019
Model description paper | Highlight paper |
| 08 Mar 2019
| 08 Mar 2019
The Open Global Glacier Model (OGGM) v1.1
Fabien Maussion
CORRESPONDING AUTHOR
Department of Atmospheric and Cryospheric Sciences, University of Innsbruck, Innsbruck, Austria
Anton Butenko
Institute of Geography, University of Bremen, Bremen, Germany
Nicolas Champollion
Institute of Geography, University of Bremen, Bremen, Germany
Matthias Dusch
Department of Atmospheric and Cryospheric Sciences, University of Innsbruck, Innsbruck, Austria
Julia Eis
Institute of Geography, University of Bremen, Bremen, Germany
Kévin Fourteau
Department of Atmospheric and Cryospheric Sciences, University of Innsbruck, Innsbruck, Austria
Université Grenoble Alpes, CNRS, IRD, Grenoble INP, IGE, 38000 Grenoble, France
Philipp Gregor
Department of Atmospheric and Cryospheric Sciences, University of Innsbruck, Innsbruck, Austria
Alexander H. Jarosch
Department of Atmospheric and Cryospheric Sciences, University of Innsbruck, Innsbruck, Austria
Johannes Landmann
Department of Atmospheric and Cryospheric Sciences, University of Innsbruck, Innsbruck, Austria
Laboratory of Hydraulics, Hydrology and Glaciology (VAW), Swiss Federal Institute of Technology (ETH),
Zürich, Switzerland
Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), Birmensdorf, Switzerland
Felix Oesterle
Department of Atmospheric and Cryospheric Sciences, University of Innsbruck, Innsbruck, Austria
Institute of Mountain Risk Engineering, University of Natural Resources and Life Sciences, Vienna, Austria
Beatriz Recinos
Institute of Geography, University of Bremen, Bremen, Germany
MARUM – Center for Marine Environmental Sciences, Bremen, Germany
Timo Rothenpieler
Institute of Geography, University of Bremen, Bremen, Germany
Anouk Vlug
MARUM – Center for Marine Environmental Sciences, Bremen, Germany
Faculty of Geosciences, University of Bremen, Bremen, Germany
Christian T. Wild
Department of Atmospheric and Cryospheric Sciences, University of Innsbruck, Innsbruck, Austria
Gateway Antarctica, Centre for Antarctic Studies and Research, University of Canterbury, Christchurch, New Zealand
Ben Marzeion
Institute of Geography, University of Bremen, Bremen, Germany
MARUM – Center for Marine Environmental Sciences, Bremen, Germany
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S. Biskop, F. Maussion, P. Krause, and M. Fink
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F. Maussion, W. Gurgiser, M. Großhauser, G. Kaser, and B. Marzeion
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E. Collier, L. I. Nicholson, B. W. Brock, F. Maussion, R. Essery, and A. B. G. Bush
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E. Dietze, F. Maussion, M. Ahlborn, B. Diekmann, K. Hartmann, K. Henkel, T. Kasper, G. Lockot, S. Opitz, and T. Haberzettl
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E. Collier, T. Mölg, F. Maussion, D. Scherer, C. Mayer, and A. B. G. Bush
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The percolation of liquid water down snowpacks is a complex phenomenon, and its representation can sometimes be complicated for snowpack models. The goal of this article is to transpose some state-of-the-art strategies used for modeling liquid percolation in other media (such as rocks or soil) into snowpack models. With this, snowpack models can be made more efficient, requiring less time and power to perform their computation.
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Léon Roussel, Marie Dumont, Marion Réveillet, Delphine Six, Marin Kneib, Pierre Nabat, Kevin Fourteau, Diego Monteiro, Simon Gascoin, Emmanuel Thibert, Antoine Rabatel, Jean-Emmanuel Sicart, Mylène Bonnefoy, Luc Piard, Olivier Laarman, Bruno Jourdain, Mathieu Fructus, Matthieu Vernay, and Matthieu Lafaysse
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Christian T. Wild, Tasha Snow, Tiago S. Dotto, Peter E. D. Davis, Scott Tyler, Ted A. Scambos, Erin C. Pettit, and Karen J. Heywood
EGUsphere, https://doi.org/10.5194/egusphere-2025-1675, https://doi.org/10.5194/egusphere-2025-1675, 2025
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Thwaites Glacier is retreating due to warm ocean water melting it from below, but its thick ice shelf makes this heat hard to monitor. Using hot water drilling, we placed sensors beneath the floating ice, revealing how surface freezing in Pine Island Bay influences heat at depth. Alongside gradual warming, we found bursts of heat that could speed up melting at the grounding zone, which may become more common as sea ice declines.
Finn Wimberly, Lizz Ultee, Lilian Schuster, Matthias Huss, David R. Rounce, Fabien Maussion, Sloan Coats, Jonathan Mackay, and Erik Holmgren
The Cryosphere, 19, 1491–1511, https://doi.org/10.5194/tc-19-1491-2025, https://doi.org/10.5194/tc-19-1491-2025, 2025
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Glacier models have historically been used to understand glacier melt’s contribution to sea level rise. The capacity to project seasonal glacier runoff is a relatively recent development for these models. In this study we provide the first model intercomparison of runoff projections for the glacier evolution models capable of simulating future runoff globally. We compare model projections from 2000 to 2100 for all major river basins larger than 3000 km2 with over 30 km2 of initial glacier cover.
Lea Hartl, Patrick Schmitt, Lilian Schuster, Kay Helfricht, Jakob Abermann, and Fabien Maussion
The Cryosphere, 19, 1431–1452, https://doi.org/10.5194/tc-19-1431-2025, https://doi.org/10.5194/tc-19-1431-2025, 2025
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We use regional observations of glacier area and volume change to inform glacier evolution modeling in the Ötztal and Stubai range (Austrian Alps) until 2100 in different climate scenarios. Glaciers in the region lost 23 % of their volume between 2006 and 2017. Under current warming trajectories, glacier loss in the region is expected to be near-total by 2075. We show that integrating regional calibration and validation data in glacier models is important to improve confidence in projections.
Kamilla Hauknes Sjursen, Jordi Bolibar, Marijn van der Meer, Liss Marie Andreassen, Julian Peter Biesheuvel, Thorben Dunse, Matthias Huss, Fabien Maussion, David R. Rounce, and Brandon Tober
EGUsphere, https://doi.org/10.5194/egusphere-2025-1206, https://doi.org/10.5194/egusphere-2025-1206, 2025
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Understanding glacier mass changes is crucial for assessing freshwater availability in many regions of the world. We present the Mass Balance Machine, a machine learning model that learns from sparse measurements of glacier mass change to make predictions on unmonitored glaciers. Using data from Norway, we show that the model provides accurate estimates of mass changes at different spatiotemporal scales. Our findings show that machine learning can be a valuable tool to improve such predictions.
Jan-Hendrik Malles, Ben Marzeion, and Paul G. Myers
Earth Syst. Dynam., 16, 347–377, https://doi.org/10.5194/esd-16-347-2025, https://doi.org/10.5194/esd-16-347-2025, 2025
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Glaciers in the high-latitude Northern Hemisphere (outside Greenland) are losing mass at roughly half the Greenland ice sheet's rate. Still, this is usually not included in the freshwater input data for ocean circulation models. Also, the submarine melt of glaciers (outside the ice sheets) has not been quantified yet. We tackle both issues by using a glacier model's output as additional fresh water for the ocean model and by using the ocean model's output to model submarine melt.
Xavier Faïn, Sophie Szopa, Vaishali Naïk, Patricia Martinerie, David M. Etheridge, Rachael H. Rhodes, Cathy M. Trudinger, Vasilii V. Petrenko, Kévin Fourteau, and Philip Place
Atmos. Chem. Phys., 25, 1105–1119, https://doi.org/10.5194/acp-25-1105-2025, https://doi.org/10.5194/acp-25-1105-2025, 2025
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Carbon monoxide (CO) plays a crucial role in the atmosphere's oxidizing capacity. In this study, we analyse how historical (1850–2014) [CO] outputs from state-of-the-art global chemistry–climate models over Greenland and Antarctica are able to capture both absolute values and trends recorded in multi-site ice archives. A disparity in [CO] growth rates emerges in the Northern Hemisphere between models and observations from 1920–1975 CE, possibly linked to uncertainties in CO emission factors.
Christian T. Wild, Reinhard Drews, Niklas Neckel, Joohan Lee, Sihyung Kim, Hyangsun Han, Won Sang Lee, Veit Helm, Sebastian Harry Reid Rosier, Oliver J. Marsh, and Wolfgang Rack
EGUsphere, https://doi.org/10.5194/egusphere-2024-3593, https://doi.org/10.5194/egusphere-2024-3593, 2024
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The stability of the Antarctic Ice Sheet depends on how resistance along the sides of large glaciers slows down the flow of ice into the ocean. We present a method to map ice strength using the effect of ocean tides on floating ice shelves. Incorporating weaker ice in shear zones improves the accuracy of model predictions compared to satellite observations. This demonstrates the untapped potential of radar satellites to map ice stiffness in the most critical areas for ice sheet stability.
Colin Peter Morice, David I. Berry, Richard C. Cornes, Kathryn Cowtan, Thomas Cropper, Ed Hawkins, John J. Kennedy, Timothy J. Osborn, Nick A. Rayner, Beatriz R. Rivas, Andrew P. Schurer, Michael Taylor, Praveen R. Teleti, Emily J. Wallis, Jonathan Winn, and Elizabeth C. Kent
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-500, https://doi.org/10.5194/essd-2024-500, 2024
Revised manuscript accepted for ESSD
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We present a new data set of global gridded surface air temperature change extending back to the 1780s. This is achieved using marine air temperature observations with newly available estimates of diurnal heating biases together with an updated land station database that includes bias adjustments for early thermometer enclosures. These developments allow the data set to extend further into the past than current data sets that use sea surface temperature rather than marine air temperature data.
Eliot Jager, Fabien Gillet-Chaulet, Nicolas Champollion, Romain Millan, Heiko Goelzer, and Jérémie Mouginot
The Cryosphere, 18, 5519–5550, https://doi.org/10.5194/tc-18-5519-2024, https://doi.org/10.5194/tc-18-5519-2024, 2024
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Inspired by a previous intercomparison framework, our study better constrains uncertainties in glacier evolution using an innovative method to validate Bayesian calibration. Upernavik Isstrøm, one of Greenland's largest glaciers, has lost significant mass since 1985. By integrating observational data, climate models, human emissions, and internal model parameters, we project its evolution until 2100. We show that future human emissions are the main source of uncertainty in 2100, making up half.
Rodrigo Aguayo, Fabien Maussion, Lilian Schuster, Marius Schaefer, Alexis Caro, Patrick Schmitt, Jonathan Mackay, Lizz Ultee, Jorge Leon-Muñoz, and Mauricio Aguayo
The Cryosphere, 18, 5383–5406, https://doi.org/10.5194/tc-18-5383-2024, https://doi.org/10.5194/tc-18-5383-2024, 2024
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Predicting how much water will come from glaciers in the future is a complex task, and there are many factors that make it uncertain. Using a glacier model, we explored 1920 scenarios for each glacier in the Patagonian Andes. We found that the choice of the historical climate data was the most important factor, while other factors such as different data sources, climate models and emission scenarios played a smaller role.
Harry Zekollari, Matthias Huss, Lilian Schuster, Fabien Maussion, David R. Rounce, Rodrigo Aguayo, Nicolas Champollion, Loris Compagno, Romain Hugonnet, Ben Marzeion, Seyedhamidreza Mojtabavi, and Daniel Farinotti
The Cryosphere, 18, 5045–5066, https://doi.org/10.5194/tc-18-5045-2024, https://doi.org/10.5194/tc-18-5045-2024, 2024
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Glaciers are major contributors to sea-level rise and act as key water resources. Here, we model the global evolution of glaciers under the latest generation of climate scenarios. We show that the type of observations used for model calibration can strongly affect the projections at the local scale. Our newly projected 21st century global mass loss is higher than the current community estimate as reported in the latest Intergovernmental Panel on Climate Change (IPCC) report.
Alexander H. Jarosch, Paul Hofer, and Christoph Spötl
The Cryosphere, 18, 4811–4816, https://doi.org/10.5194/tc-18-4811-2024, https://doi.org/10.5194/tc-18-4811-2024, 2024
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Mechanical damage to stalagmites is commonly observed in mid-latitude caves. In this study we investigate ice flow along the cave bed as a possible mechanism for stalagmite damage. Utilizing models which simulate forces created by ice flow, we study the structural integrity of different stalagmite geometries. Our results suggest that structural failure of stalagmites caused by ice flow is possible, albeit unlikely.
Julien Westhoff, Johannes Freitag, Anaïs Orsi, Patricia Martinerie, Ilka Weikusat, Michael Dyonisius, Xavier Faïn, Kevin Fourteau, and Thomas Blunier
The Cryosphere, 18, 4379–4397, https://doi.org/10.5194/tc-18-4379-2024, https://doi.org/10.5194/tc-18-4379-2024, 2024
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We study the EastGRIP area, Greenland, in detail with traditional and novel techniques. Due to the compaction of the ice, at a certain depth, atmospheric gases can no longer exchange, and the atmosphere is trapped in air bubbles in the ice. We find this depth by pumping air from a borehole, modeling, and using a new technique based on the optical appearance of the ice. Our results suggest that the close-off depth lies at around 58–61 m depth and more precisely at 58.3 m depth.
Muhammad Shafeeque, Jan-Hendrik Malles, Anouk Vlug, Marco Möller, and Ben Marzeion
EGUsphere, https://doi.org/10.5194/egusphere-2024-2184, https://doi.org/10.5194/egusphere-2024-2184, 2024
This preprint is open for discussion and under review for The Cryosphere (TC).
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The study explores how Greenland's peripheral glaciers will change due to future climate change using OGGM. They might lose 52 % of ice mass. We predict changes in ice discharge versus melting, affecting fjords, sea levels, and ocean currents. Freshwater runoff composition, seasonality, and peak water timing vary by regions and scenarios. Our findings stress the importance of reducing greenhouse gases to minimize impacts on these glaciers, which influence local ecosystems and global sea level.
Gabriela Collao-Barrios, Ted A. Scambos, Christian T. Wild, Martin Truffer, Karen E. Alley, and Erin C. Pettit
EGUsphere, https://doi.org/10.5194/egusphere-2024-1895, https://doi.org/10.5194/egusphere-2024-1895, 2024
Preprint archived
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Destabilization of ice shelves frequently leads to significant acceleration and greater mass loss, affecting rates of sea level rise. Our results show a relation between tides, flow direction, and grounding-zone acceleration that result from changing stresses in the ice margins and around a nunatak in Dotson Ice Shelf. The study describes a new way tides can influence ice shelf dynamics, an effect that could become more common as ice shelves thin and weaken around Antarctica.
Sarah Hanus, Lilian Schuster, Peter Burek, Fabien Maussion, Yoshihide Wada, and Daniel Viviroli
Geosci. Model Dev., 17, 5123–5144, https://doi.org/10.5194/gmd-17-5123-2024, https://doi.org/10.5194/gmd-17-5123-2024, 2024
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This study presents a coupling of the large-scale glacier model OGGM and the hydrological model CWatM. Projected future increase in discharge is less strong while future decrease in discharge is stronger when glacier runoff is explicitly included in the large-scale hydrological model. This is because glacier runoff is projected to decrease in nearly all basins. We conclude that an improved glacier representation can prevent underestimating future discharge changes in large river basins.
Kévin Fourteau, Johannes Freitag, Mika Malinen, and Henning Löwe
The Cryosphere, 18, 2831–2846, https://doi.org/10.5194/tc-18-2831-2024, https://doi.org/10.5194/tc-18-2831-2024, 2024
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Understanding the settling of snow under its own weight has applications from avalanche forecasts to ice core interpretations. We study how this settling can be modeled using 3D images of the internal structure of snow and ice deformation mechanics. We found that classical ice mechanics, as used, for instance, in glacier flow, explain the compaction of dense polar snow but not that of lighter seasonal snow. How, exactly, the ice deforms during light snow compaction thus remains an open question.
Marin Kneib, Amaury Dehecq, Fanny Brun, Fatima Karbou, Laurane Charrier, Silvan Leinss, Patrick Wagnon, and Fabien Maussion
The Cryosphere, 18, 2809–2830, https://doi.org/10.5194/tc-18-2809-2024, https://doi.org/10.5194/tc-18-2809-2024, 2024
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Avalanches are important for the mass balance of mountain glaciers, but few data exist on where and when they occur and which glaciers they affect the most. We developed an approach to map avalanches over large glaciated areas and long periods of time using satellite radar data. The application of this method to various regions in the Alps and High Mountain Asia reveals the variability of avalanches on these glaciers and provides key data to better represent these processes in glacier models.
Alexis Caro, Thomas Condom, Antoine Rabatel, Nicolas Champollion, Nicolás García, and Freddy Saavedra
The Cryosphere, 18, 2487–2507, https://doi.org/10.5194/tc-18-2487-2024, https://doi.org/10.5194/tc-18-2487-2024, 2024
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The glacier runoff changes are still unknown in most of the Andean catchments, thereby increasing uncertainties in estimating water availability, especially during the dry season. Here, we simulate glacier evolution and related glacier runoff changes across the Andes between 2000 and 2019. Our results indicate a glacier reduction in 93 % of the catchments, leading to a 12 % increase in glacier melt. These results can be downloaded and integrated with discharge measurements in each catchment.
Alexander H. Jarosch, Eyjólfur Magnússon, Krista Hannesdóttir, Joaquín M. C. Belart, and Finnur Pálsson
The Cryosphere, 18, 2443–2454, https://doi.org/10.5194/tc-18-2443-2024, https://doi.org/10.5194/tc-18-2443-2024, 2024
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Geothermally active regions beneath glaciers not only influence local ice flow as well as the mass balance of glaciers but also control changes of subglacial water reservoirs and possible subsequent glacier lake outburst floods. In Iceland, such outburst floods impose danger to people and infrastructure and are therefore monitored. We present a novel computer-simulation-supported method to estimate the activity of such geothermal areas and to monitor its evolution.
Anna Braun, Kévin Fourteau, and Henning Löwe
The Cryosphere, 18, 1653–1668, https://doi.org/10.5194/tc-18-1653-2024, https://doi.org/10.5194/tc-18-1653-2024, 2024
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The specific surface of snow dictates key physical properties and continuously evolves in natural snowpacks. This is referred to as metamorphism. This work develops a rigorous physical model for this evolution, which is able to reproduce X-ray tomography measurements without using unphysical tuning parameters. Our results emphasize that snow crystal growth at the micrometer scale ultimately controls the pace of metamorphism.
Kavitha Sundu, Johannes Freitag, Kévin Fourteau, and Henning Löwe
The Cryosphere, 18, 1579–1596, https://doi.org/10.5194/tc-18-1579-2024, https://doi.org/10.5194/tc-18-1579-2024, 2024
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Ice crystals often show a rod-like, vertical orientation in snow and firn; they are said to be anisotropic. The stiffness in the vertical direction therefore differs from the horizontal, which, for example, impacts the propagation of seismic waves. To quantify this anisotropy, we conducted finite-element simulations of 391 snow, firn, and ice core microstructures obtained from X-ray tomography. We then derived a parameterization that may be employed for advanced seismic studies in polar regions.
Larissa van der Laan, Anouk Vlug, Adam A. Scaife, Fabien Maussion, and Kristian Förster
EGUsphere, https://doi.org/10.5194/egusphere-2024-387, https://doi.org/10.5194/egusphere-2024-387, 2024
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Usually, glacier models are supplied with climate information from long (e.g. 100 year) simulations by global climate models. In this paper, we test the feasibility of supplying glacier models with shorter simulations, to get more accurate information on 5–10 year time scales. Reliable information on these time scales is very important, especially for water management experts to know how much meltwater to expect, for rivers, agriculture and drinking water.
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.
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.
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.
Xavier Faïn, David M. Etheridge, Kévin Fourteau, Patricia Martinerie, Cathy M. Trudinger, Rachael H. Rhodes, Nathan J. Chellman, Ray L. Langenfelds, Joseph R. McConnell, Mark A. J. Curran, Edward J. Brook, Thomas Blunier, Grégory Teste, Roberto Grilli, Anthony Lemoine, William T. Sturges, Boris Vannière, Johannes Freitag, and Jérôme Chappellaz
Clim. Past, 19, 2287–2311, https://doi.org/10.5194/cp-19-2287-2023, https://doi.org/10.5194/cp-19-2287-2023, 2023
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We report on a 3000-year record of carbon monoxide (CO) levels in the Southern Hemisphere's high latitudes by combining ice core and firn air measurements with modern direct atmospheric samples. Antarctica [CO] remained stable (–835 to 1500 CE), decreased during the Little Ice Age, and peaked around 1985 CE. Such evolution reflects stable biomass burning CO emissions before industrialization, followed by growth from CO anthropogenic sources, which decline after 1985 due to improved combustion.
Beatriz Recinos, Daniel Goldberg, James R. Maddison, and Joe Todd
The Cryosphere, 17, 4241–4266, https://doi.org/10.5194/tc-17-4241-2023, https://doi.org/10.5194/tc-17-4241-2023, 2023
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Ice sheet models generate forecasts of ice sheet mass loss, a significant contributor to sea level rise; thus, capturing the complete range of possible projections of mass loss is of critical societal importance. Here we add to data assimilation techniques commonly used in ice sheet modelling (a Bayesian inference approach) and fully characterize calibration uncertainty. We successfully propagate this type of error onto sea level rise projections of three ice streams in West Antarctica.
Fanny Brun, Owen King, Marion Réveillet, Charles Amory, Anton Planchot, Etienne Berthier, Amaury Dehecq, Tobias Bolch, Kévin Fourteau, Julien Brondex, Marie Dumont, Christoph Mayer, Silvan Leinss, Romain Hugonnet, and Patrick Wagnon
The Cryosphere, 17, 3251–3268, https://doi.org/10.5194/tc-17-3251-2023, https://doi.org/10.5194/tc-17-3251-2023, 2023
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The South Col Glacier is a small body of ice and snow located on the southern ridge of Mt. Everest. A recent study proposed that South Col Glacier is rapidly losing mass. In this study, we examined the glacier thickness change for the period 1984–2017 and found no thickness change. To reconcile these results, we investigate wind erosion and surface energy and mass balance and find that melt is unlikely a dominant process, contrary to previous findings.
Philipp Gregor, Tobias Zinner, Fabian Jakub, and Bernhard Mayer
Atmos. Meas. Tech., 16, 3257–3271, https://doi.org/10.5194/amt-16-3257-2023, https://doi.org/10.5194/amt-16-3257-2023, 2023
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This work introduces MACIN, a model for short-term forecasting of direct irradiance for solar energy applications. MACIN exploits cloud images of multiple cameras to predict irradiance. The model is applied to artificial images of clouds from a weather model. The artificial cloud data allow for a more in-depth evaluation and attribution of errors compared with real data. Good performance of derived cloud information and significant forecast improvements over a baseline forecast were found.
Aaron Cremona, Matthias Huss, Johannes Marian Landmann, Joël Borner, and Daniel Farinotti
The Cryosphere, 17, 1895–1912, https://doi.org/10.5194/tc-17-1895-2023, https://doi.org/10.5194/tc-17-1895-2023, 2023
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Summer heat waves have a substantial impact on glacier melt as emphasized by the extreme summer of 2022. This study presents a novel approach for detecting extreme glacier melt events at the regional scale based on the combination of automatically retrieved point mass balance observations and modelling approaches. The in-depth analysis of summer 2022 evidences the strong correspondence between heat waves and extreme melt events and demonstrates their significance for seasonal melt.
Karina von Schuckmann, Audrey Minière, Flora Gues, Francisco José Cuesta-Valero, Gottfried Kirchengast, Susheel Adusumilli, Fiammetta Straneo, Michaël Ablain, Richard P. Allan, Paul M. Barker, Hugo Beltrami, Alejandro Blazquez, Tim Boyer, Lijing Cheng, John Church, Damien Desbruyeres, Han Dolman, Catia M. Domingues, Almudena García-García, Donata Giglio, John E. Gilson, Maximilian Gorfer, Leopold Haimberger, Maria Z. Hakuba, Stefan Hendricks, Shigeki Hosoda, Gregory C. Johnson, Rachel Killick, Brian King, Nicolas Kolodziejczyk, Anton Korosov, Gerhard Krinner, Mikael Kuusela, Felix W. Landerer, Moritz Langer, Thomas Lavergne, Isobel Lawrence, Yuehua Li, John Lyman, Florence Marti, Ben Marzeion, Michael Mayer, Andrew H. MacDougall, Trevor McDougall, Didier Paolo Monselesan, Jan Nitzbon, Inès Otosaka, Jian Peng, Sarah Purkey, Dean Roemmich, Kanako Sato, Katsunari Sato, Abhishek Savita, Axel Schweiger, Andrew Shepherd, Sonia I. Seneviratne, Leon Simons, Donald A. Slater, Thomas Slater, Andrea K. Steiner, Toshio Suga, Tanguy Szekely, Wim Thiery, Mary-Louise Timmermans, Inne Vanderkelen, Susan E. Wjiffels, Tonghua Wu, and Michael Zemp
Earth Syst. Sci. Data, 15, 1675–1709, https://doi.org/10.5194/essd-15-1675-2023, https://doi.org/10.5194/essd-15-1675-2023, 2023
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Earth's climate is out of energy balance, and this study quantifies how much heat has consequently accumulated over the past decades (ocean: 89 %, land: 6 %, cryosphere: 4 %, atmosphere: 1 %). Since 1971, this accumulated heat reached record values at an increasing pace. The Earth heat inventory provides a comprehensive view on the status and expectation of global warming, and we call for an implementation of this global climate indicator into the Paris Agreement’s Global Stocktake.
Nidheesh Gangadharan, Hugues Goosse, David Parkes, Heiko Goelzer, Fabien Maussion, and Ben Marzeion
Earth Syst. Dynam., 13, 1417–1435, https://doi.org/10.5194/esd-13-1417-2022, https://doi.org/10.5194/esd-13-1417-2022, 2022
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We describe the contributions of ocean thermal expansion and land-ice melting (ice sheets and glaciers) to global-mean sea-level (GMSL) changes in the Common Era. The mass contributions are the major sources of GMSL changes in the pre-industrial Common Era and glaciers are the largest contributor. The paper also describes the current state of climate modelling, uncertainties and knowledge gaps along with the potential implications of the past variabilities in the contemporary sea-level rise.
Xavier Faïn, Rachael H. Rhodes, Philip Place, Vasilii V. Petrenko, Kévin Fourteau, Nathan Chellman, Edward Crosier, Joseph R. McConnell, Edward J. Brook, Thomas Blunier, Michel Legrand, and Jérôme Chappellaz
Clim. Past, 18, 631–647, https://doi.org/10.5194/cp-18-631-2022, https://doi.org/10.5194/cp-18-631-2022, 2022
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Carbon monoxide (CO) is a regulated pollutant and one of the key components determining the oxidizing capacity of the atmosphere. In this study, we analyzed five ice cores from Greenland at high resolution for CO concentrations by coupling laser spectrometry with continuous melting. By combining these new datasets, we produced an upper-bound estimate of past atmospheric CO abundance since preindustrial times for the Northern Hemisphere high latitudes, covering the period from 1700 to 1957 CE.
Lorenz Hänchen, Cornelia Klein, Fabien Maussion, Wolfgang Gurgiser, Pierluigi Calanca, and Georg Wohlfahrt
Earth Syst. Dynam., 13, 595–611, https://doi.org/10.5194/esd-13-595-2022, https://doi.org/10.5194/esd-13-595-2022, 2022
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To date, farmers' perceptions of hydrological changes do not match analysis of meteorological data. In contrast to rainfall data, we find greening of vegetation, indicating increased water availability in the past decades. The start of the season is highly variable, making farmers' perceptions comprehensible. We show that the El Niño–Southern Oscillation has complex effects on vegetation seasonality but does not drive the greening we observe. Improved onset forecasts could help local farmers.
Martin Horwath, Benjamin D. Gutknecht, Anny Cazenave, Hindumathi Kulaiappan Palanisamy, Florence Marti, Ben Marzeion, Frank Paul, Raymond Le Bris, Anna E. Hogg, Inès Otosaka, Andrew Shepherd, Petra Döll, Denise Cáceres, Hannes Müller Schmied, Johnny A. Johannessen, Jan Even Øie Nilsen, Roshin P. Raj, René Forsberg, Louise Sandberg Sørensen, Valentina R. Barletta, Sebastian B. Simonsen, Per Knudsen, Ole Baltazar Andersen, Heidi Ranndal, Stine K. Rose, Christopher J. Merchant, Claire R. Macintosh, Karina von Schuckmann, Kristin Novotny, Andreas Groh, Marco Restano, and Jérôme Benveniste
Earth Syst. Sci. Data, 14, 411–447, https://doi.org/10.5194/essd-14-411-2022, https://doi.org/10.5194/essd-14-411-2022, 2022
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Global mean sea-level change observed from 1993 to 2016 (mean rate of 3.05 mm yr−1) matches the combined effect of changes in water density (thermal expansion) and ocean mass. Ocean-mass change has been assessed through the contributions from glaciers, ice sheets, and land water storage or directly from satellite data since 2003. Our budget assessments of linear trends and monthly anomalies utilise new datasets and uncertainty characterisations developed within ESA's Climate Change Initiative.
Christian T. Wild, Karen E. Alley, Atsuhiro Muto, Martin Truffer, Ted A. Scambos, and Erin C. Pettit
The Cryosphere, 16, 397–417, https://doi.org/10.5194/tc-16-397-2022, https://doi.org/10.5194/tc-16-397-2022, 2022
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Thwaites Glacier has the potential to significantly raise Antarctica's contribution to global sea-level rise by the end of this century. Here, we use satellite measurements of surface elevation to show that its floating part is close to losing contact with an underwater ridge that currently acts to stabilize. We then use computer models of ice flow to simulate the predicted unpinning, which show that accelerated ice discharge into the ocean follows the breakup of the floating part.
Karen E. Alley, Christian T. Wild, Adrian Luckman, Ted A. Scambos, Martin Truffer, Erin C. Pettit, Atsuhiro Muto, Bruce Wallin, Marin Klinger, Tyler Sutterley, Sarah F. Child, Cyrus Hulen, Jan T. M. Lenaerts, Michelle Maclennan, Eric Keenan, and Devon Dunmire
The Cryosphere, 15, 5187–5203, https://doi.org/10.5194/tc-15-5187-2021, https://doi.org/10.5194/tc-15-5187-2021, 2021
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We present a 20-year, satellite-based record of velocity and thickness change on the Thwaites Eastern Ice Shelf (TEIS), the largest remaining floating extension of Thwaites Glacier (TG). TG holds the single greatest control on sea-level rise over the next few centuries, so it is important to understand changes on the TEIS, which controls much of TG's flow into the ocean. Our results suggest that the TEIS is progressively destabilizing and is likely to disintegrate over the next few decades.
Johannes Marian Landmann, Hans Rudolf Künsch, Matthias Huss, Christophe Ogier, Markus Kalisch, and Daniel Farinotti
The Cryosphere, 15, 5017–5040, https://doi.org/10.5194/tc-15-5017-2021, https://doi.org/10.5194/tc-15-5017-2021, 2021
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In this study, we (1) acquire real-time information on point glacier mass balance with autonomous real-time cameras and (2) assimilate these observations into a mass balance model ensemble driven by meteorological input. For doing so, we use a customized particle filter that we designed for the specific purposes of our study. We find melt rates of up to 0.12 m water equivalent per day and show that our assimilation method has a higher performance than reference mass balance models.
Ben Marzeion
Earth Syst. Dynam., 12, 1057–1060, https://doi.org/10.5194/esd-12-1057-2021, https://doi.org/10.5194/esd-12-1057-2021, 2021
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The oceans are typically darker than land surfaces. Expanding oceans through sea-level rise may thus lead to a darker planet Earth, reflecting less sunlight. The additionally absorbed sunlight may heat planet Earth, leading to further sea-level rise. Here, we provide a rough estimate of the strength of this feedback: it turns out to be very weak, but clearly positive, thereby destabilizing the Earth system.
Jan-Hendrik Malles and Ben Marzeion
The Cryosphere, 15, 3135–3157, https://doi.org/10.5194/tc-15-3135-2021, https://doi.org/10.5194/tc-15-3135-2021, 2021
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To better estimate the uncertainty in glacier mass change modeling during the 20th century we ran an established model with an ensemble of meteorological data sets. We find that the total ensemble uncertainty, especially in the early 20th century, when glaciological and meteorological observations at glacier locations were sparse, increases considerably compared to individual ensemble runs. This stems from regions with a lot of ice mass but few observations (e.g., Greenland periphery).
Kévin Fourteau, Florent Domine, and Pascal Hagenmuller
The Cryosphere, 15, 2739–2755, https://doi.org/10.5194/tc-15-2739-2021, https://doi.org/10.5194/tc-15-2739-2021, 2021
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The thermal conductivity of snow is an important physical property governing the thermal regime of a snowpack and its substrate. We show that it strongly depends on the kinetics of water vapor sublimation and that previous experimental data suggest a rather fast kinetics. In such a case, neglecting water vapor leads to an underestimation of thermal conductivity by up to 50 % for light snow. Moreover, the diffusivity of water vapor in snow is then directly related to the thermal conductivity.
Gerard H. Roe, John Erich Christian, and Ben Marzeion
The Cryosphere, 15, 1889–1905, https://doi.org/10.5194/tc-15-1889-2021, https://doi.org/10.5194/tc-15-1889-2021, 2021
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The worldwide retreat of mountain glaciers and consequent loss of ice mass is one of the most obvious signs of a changing climate and has significant implications for the hydrology and natural hazards in mountain landscapes. Consistent with our understanding of the human role in temperature change, we demonstrate that the central estimate of the size of the human-caused mass loss is essentially 100 % of the observed loss. This assessment resolves some important inconsistencies in the literature.
Gabriella Koltai, Christoph Spötl, Alexander H. Jarosch, and Hai Cheng
Clim. Past, 17, 775–789, https://doi.org/10.5194/cp-17-775-2021, https://doi.org/10.5194/cp-17-775-2021, 2021
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This paper utilises a novel palaeoclimate archive from caves, cryogenic cave carbonates, which allow for precisely constraining permafrost thawing events in the past. Our study provides new insights into the climate of the Younger Dryas (12 800 to 11 700 years BP) in mid-Europe from the perspective of a high-elevation cave sensitive to permafrost development. We quantify seasonal temperature and precipitation changes by using a heat conduction model.
Kévin Fourteau, Florent Domine, and Pascal Hagenmuller
The Cryosphere, 15, 389–406, https://doi.org/10.5194/tc-15-389-2021, https://doi.org/10.5194/tc-15-389-2021, 2021
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There has been a long controversy to determine whether the effective diffusion coefficient of water vapor in snow is superior to that in free air. Using theory and numerical modeling, we show that while water vapor diffuses more than inert gases thanks to its interaction with the ice, the effective diffusion coefficient of water vapor in snow remains inferior to that in free air. This suggests that other transport mechanisms are responsible for the large vapor fluxes observed in some snowpacks.
Lilian Schuster, Fabien Maussion, Lukas Langhamer, and Gina E. Moseley
Weather Clim. Dynam., 2, 1–17, https://doi.org/10.5194/wcd-2-1-2021, https://doi.org/10.5194/wcd-2-1-2021, 2021
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Precipitation and moisture sources over an arid region in northeast Greenland are investigated from 1979 to 2017 by a Lagrangian moisture source diagnostic driven by reanalysis data. Dominant winter moisture sources are the North Atlantic above 45° N. In summer local and north Eurasian continental sources dominate. In positive phases of the North Atlantic Oscillation, evaporation and moisture transport from the Norwegian Sea are stronger, resulting in more precipitation.
Anna Wirbel and Alexander Helmut Jarosch
Geosci. Model Dev., 13, 6425–6445, https://doi.org/10.5194/gmd-13-6425-2020, https://doi.org/10.5194/gmd-13-6425-2020, 2020
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We present an open-source numerical tool to simulate the free-surface evolution of gravity-driven flows (e.g. glaciers) constrained by bed topography. No ad hoc post-processing is required to enforce positive ice thickness and mass conservation. We utilise finite elements, define benchmark tests, and showcase glaciological examples. In addition, we provide a thorough analysis of the applicability and robustness of different spatial stabilisation and time discretisation methods.
Ethan Welty, Michael Zemp, Francisco Navarro, Matthias Huss, Johannes J. Fürst, Isabelle Gärtner-Roer, Johannes Landmann, Horst Machguth, Kathrin Naegeli, Liss M. Andreassen, Daniel Farinotti, Huilin Li, and GlaThiDa Contributors
Earth Syst. Sci. Data, 12, 3039–3055, https://doi.org/10.5194/essd-12-3039-2020, https://doi.org/10.5194/essd-12-3039-2020, 2020
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Knowing the thickness of glacier ice is critical for predicting the rate of glacier loss and the myriad downstream impacts. To facilitate forecasts of future change, we have added 3 million measurements to our worldwide database of glacier thickness: 14 % of global glacier area is now within 1 km of a thickness measurement (up from 6 %). To make it easier to update and monitor the quality of our database, we have used automated tools to check and track changes to the data over time.
Denise Cáceres, Ben Marzeion, Jan Hendrik Malles, Benjamin Daniel Gutknecht, Hannes Müller Schmied, and Petra Döll
Hydrol. Earth Syst. Sci., 24, 4831–4851, https://doi.org/10.5194/hess-24-4831-2020, https://doi.org/10.5194/hess-24-4831-2020, 2020
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We analysed how and to which extent changes in water storage on continents had an effect on global ocean mass over the period 1948–2016. Continents lost water to oceans at an accelerated rate, inducing sea level rise. Shrinking glaciers explain 81 % of the long-term continental water mass loss, while declining groundwater levels, mainly due to sustained groundwater pumping for irrigation, is the second major driver. This long-term decline was partly offset by the impoundment of water in dams.
Karina von Schuckmann, Lijing Cheng, Matthew D. Palmer, James Hansen, Caterina Tassone, Valentin Aich, Susheel Adusumilli, Hugo Beltrami, Tim Boyer, Francisco José Cuesta-Valero, Damien Desbruyères, Catia Domingues, Almudena García-García, Pierre Gentine, John Gilson, Maximilian Gorfer, Leopold Haimberger, Masayoshi Ishii, Gregory C. Johnson, Rachel Killick, Brian A. King, Gottfried Kirchengast, Nicolas Kolodziejczyk, John Lyman, Ben Marzeion, Michael Mayer, Maeva Monier, Didier Paolo Monselesan, Sarah Purkey, Dean Roemmich, Axel Schweiger, Sonia I. Seneviratne, Andrew Shepherd, Donald A. Slater, Andrea K. Steiner, Fiammetta Straneo, Mary-Louise Timmermans, and Susan E. Wijffels
Earth Syst. Sci. Data, 12, 2013–2041, https://doi.org/10.5194/essd-12-2013-2020, https://doi.org/10.5194/essd-12-2013-2020, 2020
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Understanding how much and where the heat is distributed in the Earth system is fundamental to understanding how this affects warming oceans, atmosphere and land, rising temperatures and sea level, and loss of grounded and floating ice, which are fundamental concerns for society. This study is a Global Climate Observing System (GCOS) concerted international effort to obtain the Earth heat inventory over the period 1960–2018.
Kévin Fourteau, Laurent Arnaud, Xavier Faïn, Patricia Martinerie, David M. Etheridge, Vladimir Lipenkov, and Jean-Marc Barnola
Earth Syst. Sci. Data, 12, 1171–1177, https://doi.org/10.5194/essd-12-1171-2020, https://doi.org/10.5194/essd-12-1171-2020, 2020
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Measurements of the porosity of three polar firns were conducted in the 1990s by Jean-Marc Barnola using the method of gas pycnometry. From these data, a parametrization of firn pore closure was produced and used in different published articles. However, the data have not been published in their own right yet. We have made the data publicly accessible on the PANGAEA database and here propose describing how they were obtained and used to produce the pore closure parametrization.
Mathieu Casado, Gwenaëlle Gremion, Paul Rosenbaum, Jilda Alicia Caccavo, Kelsey Aho, Nicolas Champollion, Sarah L. Connors, Adrian Dahood, Alfonso Fernandez, Martine Lizotte, Katja Mintenbeck, Elvira Poloczanska, and Gerlis Fugmann
Geosci. Commun., 3, 89–97, https://doi.org/10.5194/gc-3-89-2020, https://doi.org/10.5194/gc-3-89-2020, 2020
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Early-career scientists (ECSs) are rarely invited to act as peer reviewers. Participating in a group peer review of the IPCC Special Report on Ocean and Cryosphere in a Changing Climate, PhD students spent more time reviewing than more established scientists and provided a similar proportion of substantive comments. By soliciting and including ECSs in peer review, the scientific community would reduce the burden on more established scientists and may improve the quality of that process.
Kévin Fourteau, Patricia Martinerie, Xavier Faïn, Alexey A. Ekaykin, Jérôme Chappellaz, and Vladimir Lipenkov
Clim. Past, 16, 503–522, https://doi.org/10.5194/cp-16-503-2020, https://doi.org/10.5194/cp-16-503-2020, 2020
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We quantify how the greenhouse gas records of East Antarctic ice cores (which are the oldest ice cores) might differ from the actual atmosphere history. It is required to properly interpret ice core data. For this, we measured the methane of five new East Antarctic ice core sections using a high-resolution technique. We found that in these very old ice cores, one can retrieve concentration variations occurring in only a few centuries, allowing climatologists to study climate's fast dynamics.
Kévin Fourteau, Patricia Martinerie, Xavier Faïn, Christoph F. Schaller, Rebecca J. Tuckwell, Henning Löwe, Laurent Arnaud, Olivier Magand, Elizabeth R. Thomas, Johannes Freitag, Robert Mulvaney, Martin Schneebeli, and Vladimir Ya. Lipenkov
The Cryosphere, 13, 3383–3403, https://doi.org/10.5194/tc-13-3383-2019, https://doi.org/10.5194/tc-13-3383-2019, 2019
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Understanding gas trapping in polar ice is essential to study the relationship between greenhouse gases and past climates. New data of bubble closure, used in a simple gas-trapping model, show inconsistency with the final air content in ice. This suggests gas trapping is not fully understood. We also use a combination of high-resolution measurements to investigate the effect of polar snow stratification on gas trapping and find that all strata have similar pores, but that some close in advance.
Julia Eis, Fabien Maussion, and Ben Marzeion
The Cryosphere, 13, 3317–3335, https://doi.org/10.5194/tc-13-3317-2019, https://doi.org/10.5194/tc-13-3317-2019, 2019
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To provide estimates of past glacier mass changes, an adequate initial state is required. However, information about past glacier states at regional or global scales is largely incomplete. Our study presents a new way to initialize the Open Global Glacier Model from past climate information and present-day geometries. We show that even with perfectly known but incomplete boundary conditions, the problem of model initialization leads to nonunique solutions, and we propose an ensemble approach.
Christian T. Wild, Oliver J. Marsh, and Wolfgang Rack
The Cryosphere, 13, 3171–3191, https://doi.org/10.5194/tc-13-3171-2019, https://doi.org/10.5194/tc-13-3171-2019, 2019
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In Antarctica, ocean tides control the motion of ice sheets near the coastline as well as melt rates underneath the floating ice. By combining the spatial advantage of rare but highly accurate satellite images with the temporal advantage of tide-prediction models, vertical displacement of floating ice due to ocean tides can now be predicted accurately. This allows the detailed study of ice-flow dynamics in areas that matter the most to the stability of Antarctica's ice sheets.
Beatriz Recinos, Fabien Maussion, Timo Rothenpieler, and Ben Marzeion
The Cryosphere, 13, 2657–2672, https://doi.org/10.5194/tc-13-2657-2019, https://doi.org/10.5194/tc-13-2657-2019, 2019
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We have implemented a frontal ablation parameterization into the Open Global Glacier Model and have shown that inversion methods based on mass conservation systematically underestimate the mass turnover (and therefore the thickness) of tidewater glaciers when neglecting frontal ablation. This underestimation can rise up to 19 % on a regional scale. Not accounting for frontal ablation will have an impact on the estimate of the glaciers’ potential contribution to sea level rise.
Johannes Horak, Marlis Hofer, Fabien Maussion, Ethan Gutmann, Alexander Gohm, and Mathias W. Rotach
Hydrol. Earth Syst. Sci., 23, 2715–2734, https://doi.org/10.5194/hess-23-2715-2019, https://doi.org/10.5194/hess-23-2715-2019, 2019
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This study presents an in-depth evaluation of the Intermediate Complexity Atmospheric Research (ICAR) model for high-resolution precipitation fields in complex topography. ICAR is evaluated with data from weather stations located in the Southern Alps of New Zealand. While ICAR underestimates rainfall amounts, it clearly improves over a coarser global model and shows potential to generate precipitation fields for long-term impact studies focused on the local impact of a changing global climate.
Nicolas Champollion, Ghislain Picard, Laurent Arnaud, Éric Lefebvre, Giovanni Macelloni, Frédérique Rémy, and Michel Fily
The Cryosphere, 13, 1215–1232, https://doi.org/10.5194/tc-13-1215-2019, https://doi.org/10.5194/tc-13-1215-2019, 2019
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The snow density close to the surface has been retrieved from satellite observations at Dome C on the Antarctic Ice Sheet. It shows a marked decrease between 2002 and 2011 of about 10 kg m-3 yr-1. This trend has been confirmed by in situ measurements and other satellite observations though no long-term meteorological evolution has been found. These results have implications for surface mass balance and energy budget.
Tobias Zolles, Fabien Maussion, Stephan Peter Galos, Wolfgang Gurgiser, and Lindsey Nicholson
The Cryosphere, 13, 469–489, https://doi.org/10.5194/tc-13-469-2019, https://doi.org/10.5194/tc-13-469-2019, 2019
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A mass and energy balance model was subjected to sensitivity and uncertainty analysis on two different Alpine glaciers. The global sensitivity analysis allowed for a mass balance measurement independent assessment of the model sensitivity and functioned as a reduction of the model free parameter space. A novel approach of a multi-objective optimization estimates the uncertainty of the simulated mass balance and the energy fluxes. The final model uncertainty is up to 1300 kg m−3 per year.
Hugues Goosse, Pierre-Yves Barriat, Quentin Dalaiden, François Klein, Ben Marzeion, Fabien Maussion, Paolo Pelucchi, and Anouk Vlug
Clim. Past, 14, 1119–1133, https://doi.org/10.5194/cp-14-1119-2018, https://doi.org/10.5194/cp-14-1119-2018, 2018
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Glaciers provide iconic illustrations of past climate change, but records of glacier length fluctuations have not been used systematically to test the ability of models to reproduce past changes. One reason is that glacier length depends on several complex factors and so cannot be simply linked to the climate simulated by models. This is done here, and it is shown that the observed glacier length fluctuations are generally well within the range of the simulations.
Giri Gopalan, Birgir Hrafnkelsson, Guðfinna Aðalgeirsdóttir, Alexander H. Jarosch, and Finnur Pálsson
The Cryosphere, 12, 2229–2248, https://doi.org/10.5194/tc-12-2229-2018, https://doi.org/10.5194/tc-12-2229-2018, 2018
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Geophysical systems can often contain scientific parameters whose values are uncertain, complex underlying dynamics, and field measurements with errors. These components are naturally modeled together within what is known as a Bayesian hierarchical model (BHM). This paper constructs such a model for shallow glaciers based on an approximation of the underlying dynamics. The evaluation of this model is aided by the use of exact analytical solutions from the literature.
Ulrich Strasser, Thomas Marke, Ludwig Braun, Heidi Escher-Vetter, Irmgard Juen, Michael Kuhn, Fabien Maussion, Christoph Mayer, Lindsey Nicholson, Klaus Niedertscheider, Rudolf Sailer, Johann Stötter, Markus Weber, and Georg Kaser
Earth Syst. Sci. Data, 10, 151–171, https://doi.org/10.5194/essd-10-151-2018, https://doi.org/10.5194/essd-10-151-2018, 2018
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A hydrometeorological and glaciological data set is presented with recordings from several research sites in the Rofental (1891–3772 m a.s.l., Ötztal Alps, Austria). The data sets are spanning 150 years and represent a unique pool of high mountain observations, enabling combined research of atmospheric, cryospheric and hydrological processes in complex terrain, and the development of state-of-the-art hydroclimatological and glacier mass balance models.
Anna Wirbel, Alexander H. Jarosch, and Lindsey Nicholson
The Cryosphere, 12, 189–204, https://doi.org/10.5194/tc-12-189-2018, https://doi.org/10.5194/tc-12-189-2018, 2018
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As debris cover affects the meltwater production and behaviour of glaciers it is important to understand how, and over what timescales, it forms. Here we develop an advanced 3-D numerical model that describes transport of sediment through a glacier to the point where it emerges at the surface. The numerical performance of the model is satisfactory and it reproduces debris structures observed within real-world glaciers, thereby offering a useful tool for future studies of debris-covered glaciers.
Kévin Fourteau, Xavier Faïn, Patricia Martinerie, Amaëlle Landais, Alexey A. Ekaykin, Vladimir Ya. Lipenkov, and Jérôme Chappellaz
Clim. Past, 13, 1815–1830, https://doi.org/10.5194/cp-13-1815-2017, https://doi.org/10.5194/cp-13-1815-2017, 2017
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We measured methane concentrations from a polar ice core to quantify the differences between the ice record and the past true atmospheric conditions. Two effects were investigated by combining data analysis and modeling: the stratification of polar snow before gas enclosure driving chronological hiatuses in the record and the gradual formation of bubbles in the ice attenuating fast atmospheric variations. This study will contribute to improving future climatic interpretations from ice archives.
Wolfgang Rack, Matt A. King, Oliver J. Marsh, Christian T. Wild, and Dana Floricioiu
The Cryosphere, 11, 2481–2490, https://doi.org/10.5194/tc-11-2481-2017, https://doi.org/10.5194/tc-11-2481-2017, 2017
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Predicting changes of the Antarctic Ice Sheet involves fully understanding ice dynamics at the transition between grounded and floating ice. We map tidal bending of ice by satellite using InSAR, and we use precise GPS measurements with assumptions of tidal elastic bending to better interpret the satellite signal. It allows us to better define the grounding-line position and to refine the shape of tidal flexure profiles.
Joaquín M. C. Belart, Etienne Berthier, Eyjólfur Magnússon, Leif S. Anderson, Finnur Pálsson, Thorsteinn Thorsteinsson, Ian M. Howat, Guðfinna Aðalgeirsdóttir, Tómas Jóhannesson, and Alexander H. Jarosch
The Cryosphere, 11, 1501–1517, https://doi.org/10.5194/tc-11-1501-2017, https://doi.org/10.5194/tc-11-1501-2017, 2017
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Sub-meter satellite stereo images (Pléiades and WorldView2) are used to accurately measure snow accumulation and winter mass balance of Drangajökull ice cap. This is done by creating and comparing accurate digital elevation models. A glacier-wide geodetic mass balance of 3.33 ± 0.23 m w.e. is derived between October 2014 and May 2015. This method could be easily transposable to remote glaciated areas where seasonal mass balance measurements (especially winter accumulation) are lacking.
Stephan Peter Galos, Christoph Klug, Fabien Maussion, Federico Covi, Lindsey Nicholson, Lorenzo Rieg, Wolfgang Gurgiser, Thomas Mölg, and Georg Kaser
The Cryosphere, 11, 1417–1439, https://doi.org/10.5194/tc-11-1417-2017, https://doi.org/10.5194/tc-11-1417-2017, 2017
Riccardo E. M. Riva, Thomas Frederikse, Matt A. King, Ben Marzeion, and Michiel R. van den Broeke
The Cryosphere, 11, 1327–1332, https://doi.org/10.5194/tc-11-1327-2017, https://doi.org/10.5194/tc-11-1327-2017, 2017
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The reduction of ice masses stored on land has made an important contribution to sea-level rise over the last century, as well as changed the Earth's shape. We model the solid-earth response to ice mass changes and find significant vertical deformation signals over large continental areas. We show how deformation rates have varied strongly throughout the last century, which affects the interpretation and extrapolation of recent observations of vertical land motion and sea-level change.
Daniel Farinotti, Douglas J. Brinkerhoff, Garry K. C. Clarke, Johannes J. Fürst, Holger Frey, Prateek Gantayat, Fabien Gillet-Chaulet, Claire Girard, Matthias Huss, Paul W. Leclercq, Andreas Linsbauer, Horst Machguth, Carlos Martin, Fabien Maussion, Mathieu Morlighem, Cyrille Mosbeux, Ankur Pandit, Andrea Portmann, Antoine Rabatel, RAAJ Ramsankaran, Thomas J. Reerink, Olivier Sanchez, Peter A. Stentoft, Sangita Singh Kumari, Ward J. J. van Pelt, Brian Anderson, Toby Benham, Daniel Binder, Julian A. Dowdeswell, Andrea Fischer, Kay Helfricht, Stanislav Kutuzov, Ivan Lavrentiev, Robert McNabb, G. Hilmar Gudmundsson, Huilin Li, and Liss M. Andreassen
The Cryosphere, 11, 949–970, https://doi.org/10.5194/tc-11-949-2017, https://doi.org/10.5194/tc-11-949-2017, 2017
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ITMIX – the Ice Thickness Models Intercomparison eXperiment – was the first coordinated performance assessment for models inferring glacier ice thickness from surface characteristics. Considering 17 different models and 21 different test cases, we show that although solutions of individual models can differ considerably, an ensemble average can yield uncertainties in the order of 10 ± 24 % the mean ice thickness. Ways forward for improving such estimates are sketched.
Kristian Förster, Felix Oesterle, Florian Hanzer, Johannes Schöber, Matthias Huttenlau, and Ulrich Strasser
Proc. IAHS, 374, 143–150, https://doi.org/10.5194/piahs-374-143-2016, https://doi.org/10.5194/piahs-374-143-2016, 2016
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We present first results of a coupled seasonal prediction modelling system that runs at monthly time steps for a small catchment in the Austrian Alps. Meteorological forecasts are obtained from the CFSv2 model which are downscaled to the Alpine Water balance And Runoff Estimation model AWARE. Initial conditions are obtained using the physically based, hydro-climatological snow model AMUNDSEN. In this way, ensemble simulations of the coupled model are compared to observations.
S. Biskop, F. Maussion, P. Krause, and M. Fink
Hydrol. Earth Syst. Sci., 20, 209–225, https://doi.org/10.5194/hess-20-209-2016, https://doi.org/10.5194/hess-20-209-2016, 2016
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In this study, the hydrological model J2000g was extended and applied to four selected endorheic lake basins in the southern-central part of the TP aiming to provide a more quantitative understanding of the key factors controlling their water balance. The model results indicated that the relative contribution of glacier runoff to total water inflow (between 14 and 30 %) plays a less important role compared to runoff generation from rainfall and snowmelt in non-glacierized land areas.
B. Marzeion, P. W. Leclercq, J. G. Cogley, and A. H. Jarosch
The Cryosphere, 9, 2399–2404, https://doi.org/10.5194/tc-9-2399-2015, https://doi.org/10.5194/tc-9-2399-2015, 2015
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We show that estimates of global glacier mass change during the 20th century, obtained from glacier-length-based reconstructions and from a glacier model driven by gridded climate observations are now consistent with each other and also with an estimate for the years 2003-2009 that is mostly based on remotely sensed data. This consistency is found throughout the entire common periods of the respective data sets. Inconsistencies of reconstructions and observations persist on regional scales.
F. Maussion, W. Gurgiser, M. Großhauser, G. Kaser, and B. Marzeion
The Cryosphere, 9, 1663–1683, https://doi.org/10.5194/tc-9-1663-2015, https://doi.org/10.5194/tc-9-1663-2015, 2015
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Using a newly developed open-source tool, we downscale the glacier surface energy and mass balance fluxes at Shallap Glacier. This allows an unprecedented quantification of the ENSO influence on a tropical glacier at climatological time scales (1980-2013). We find a stronger and steadier anti-correlation between Pacific sea-surface temperature (SST) and glacier mass balance than previously reported and provide keys to understand its mechanism.
E. Collier, F. Maussion, L. I. Nicholson, T. Mölg, W. W. Immerzeel, and A. B. G. Bush
The Cryosphere, 9, 1617–1632, https://doi.org/10.5194/tc-9-1617-2015, https://doi.org/10.5194/tc-9-1617-2015, 2015
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We investigate the impact of surface debris on glacier energy and mass fluxes and on atmosphere-glacier feedbacks in the Karakoram range, by including debris in an interactively coupled atmosphere-glacier model. The model is run from 1 May to 1 October 2004, with a simple specification of debris thickness. We find an appreciable reduction in ablation that exceeds 5m w.e. on glacier tongues, as well as significant alterations to near-surface air temperatures and boundary layer dynamics.
J. Curio, F. Maussion, and D. Scherer
Earth Syst. Dynam., 6, 109–124, https://doi.org/10.5194/esd-6-109-2015, https://doi.org/10.5194/esd-6-109-2015, 2015
M. Hofer, B. Marzeion, and T. Mölg
Geosci. Model Dev., 8, 579–593, https://doi.org/10.5194/gmd-8-579-2015, https://doi.org/10.5194/gmd-8-579-2015, 2015
E. Collier, L. I. Nicholson, B. W. Brock, F. Maussion, R. Essery, and A. B. G. Bush
The Cryosphere, 8, 1429–1444, https://doi.org/10.5194/tc-8-1429-2014, https://doi.org/10.5194/tc-8-1429-2014, 2014
E. Dietze, F. Maussion, M. Ahlborn, B. Diekmann, K. Hartmann, K. Henkel, T. Kasper, G. Lockot, S. Opitz, and T. Haberzettl
Clim. Past, 10, 91–106, https://doi.org/10.5194/cp-10-91-2014, https://doi.org/10.5194/cp-10-91-2014, 2014
B. Marzeion, A. H. Jarosch, and J. M. Gregory
The Cryosphere, 8, 59–71, https://doi.org/10.5194/tc-8-59-2014, https://doi.org/10.5194/tc-8-59-2014, 2014
W. Gurgiser, B. Marzeion, L. Nicholson, M. Ortner, and G. Kaser
The Cryosphere, 7, 1787–1802, https://doi.org/10.5194/tc-7-1787-2013, https://doi.org/10.5194/tc-7-1787-2013, 2013
E. Collier, T. Mölg, F. Maussion, D. Scherer, C. Mayer, and A. B. G. Bush
The Cryosphere, 7, 779–795, https://doi.org/10.5194/tc-7-779-2013, https://doi.org/10.5194/tc-7-779-2013, 2013
A. H. Jarosch, C. G. Schoof, and F. S. Anslow
The Cryosphere, 7, 229–240, https://doi.org/10.5194/tc-7-229-2013, https://doi.org/10.5194/tc-7-229-2013, 2013
Related subject area
Cryosphere
Computationally efficient subglacial drainage modelling using Gaussian process emulators: GlaDS-GP v1.0
Anisotropic metric-based mesh adaptation for ice flow modelling in Firedrake
Description and validation of the ice-sheet model Nix v1.0
The Utrecht Finite Volume Ice-Sheet Model (UFEMISM) version 2.0 – Part 1: Description and idealised experiments
A Flexible Snow Model (FSM 2.1.1) including a forest canopy
CMIP6 models overestimate sea ice melt, growth and conduction relative to ice mass balance buoy estimates
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 gradient-boosted tree framework to model the ice thickness of the world's glaciers (IceBoost v1.1)
Comparison of calibration methods of a PICO basal ice shelf melt module implemented in the GRISLI v2.0 ice sheet model
A Python library for solving ice sheet modeling problems using Physics Informed Neural Networks, PINNICLE v1.0
Towards deep-learning solutions for classification of automated snow height measurements (CleanSnow v1.0.2)
Constraining CMIP6 sea ice simulations with ICESat-2
Quantitative sub-ice and marine tracing of Antarctic sediment provenance (TASP v1.0)
Tuning parameters of a sea ice model using machine learning
WRF-Chem simulations of snow nitrate and other physicochemical properties in northern China
Implementation of an intermediate complexity snow-physics scheme (ISBA-Explicit Snow) into a sea-ice model (SI3): 1D thermodynamic coupling and validation
A framework for three-dimensional dynamic modeling of mountain glaciers in the Community Ice Sheet Model (CISM v2.2)
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
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
A new 3D full-Stokes calving algorithm within Elmer/Ice (v9.0)
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
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
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
Tim Hill, Derek Bingham, Gwenn E. Flowers, and Matthew J. Hoffman
Geosci. Model Dev., 18, 4045–4074, https://doi.org/10.5194/gmd-18-4045-2025, https://doi.org/10.5194/gmd-18-4045-2025, 2025
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Subglacial drainage models represent water flow beneath glaciers and ice sheets. Here, we train fast statistical models called Gaussian process (GP) emulators to accelerate subglacial drainage modelling by ~ 1000 times. We use the fast emulator predictions to show that three of the model parameters are responsible for > 90 % of the variance in model outputs. The fast GP emulators will enable future uncertainty quantification and calibration of these models.
Davor Dundovic, Joseph G. Wallwork, Stephan C. Kramer, Fabien Gillet-Chaulet, Regine Hock, and Matthew D. Piggott
Geosci. Model Dev., 18, 4023–4044, https://doi.org/10.5194/gmd-18-4023-2025, https://doi.org/10.5194/gmd-18-4023-2025, 2025
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Accurate numerical studies of glaciers often require high-resolution simulations, which often prove too demanding even for modern computers. In this paper we develop a method that identifies whether different parts of a glacier require high or low resolution based on its physical features, such as its thickness and velocity. We show that by doing so we can achieve a more optimal simulation accuracy for the available computing resources compared to uniform-resolution simulations.
Daniel Moreno-Parada, Alexander Robinson, Marisa Montoya, and Jorge Alvarez-Solas
Geosci. Model Dev., 18, 3895–3919, https://doi.org/10.5194/gmd-18-3895-2025, https://doi.org/10.5194/gmd-18-3895-2025, 2025
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We introduce Nix, an ice-sheet model designed for understanding how large masses of ice behave. Nix is a computer programme that simulates the movement and temperature evolution in ice sheets. It helps us study how ice sheets respond to changes in the atmosphere and ocean. We found that ice temperatures play an essential role in determining the motion and stability of ice sheets. Nix is a useful tool for learning how climate change affects polar ice sheets.
Constantijn J. Berends, Victor Azizi, Jorge A. Bernales, and Roderik S. W. van de Wal
Geosci. Model Dev., 18, 3635–3659, https://doi.org/10.5194/gmd-18-3635-2025, https://doi.org/10.5194/gmd-18-3635-2025, 2025
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Ice-sheet models are computer programs that can simulate how the Greenland and Antarctic ice sheets will evolve in the future. The accuracy of these models depends on their resolution: how small the details are that the model can resolve. We have created a model with a variable resolution that can resolve a lot of detail in areas where lots of changes happen in the ice and less detail in areas where the ice does not move so much. This makes the model both accurate and fast.
Richard Essery, Giulia Mazzotti, Sarah Barr, Tobias Jonas, Tristan Quaife, and Nick Rutter
Geosci. Model Dev., 18, 3583–3605, https://doi.org/10.5194/gmd-18-3583-2025, https://doi.org/10.5194/gmd-18-3583-2025, 2025
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How forests influence accumulation and melt of snow on the ground is of long-standing interest, but uncertainty remains in how best to model forest snow processes. We developed the Flexible Snow Model version 2 to quantify these uncertainties. In a first model demonstration, how unloading of intercepted snow from the forest canopy is represented is responsible for the largest uncertainty. Global mapping of forest distribution is also likely to be a large source of uncertainty in existing models.
Alex E. West and Edward W. Blockley
Geosci. Model Dev., 18, 3041–3064, https://doi.org/10.5194/gmd-18-3041-2025, https://doi.org/10.5194/gmd-18-3041-2025, 2025
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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 (1) melt and growth of Arctic sea ice and (2) 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 that models tend to show more melt, growth or conduction for a given ice thickness than the buoys, although the difference is smaller for models with more physically realistic thermodynamics.
Ole Richter, Ralph Timmermann, G. Hilmar Gudmundsson, and Jan De Rydt
Geosci. Model Dev., 18, 2945–2960, https://doi.org/10.5194/gmd-18-2945-2025, https://doi.org/10.5194/gmd-18-2945-2025, 2025
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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 timescales.
Niccolò Maffezzoli, Eric Rignot, Carlo Barbante, Troels Petersen, and Sebastiano Vascon
Geosci. Model Dev., 18, 2545–2568, https://doi.org/10.5194/gmd-18-2545-2025, https://doi.org/10.5194/gmd-18-2545-2025, 2025
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In this work we introduce 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 skilful estimates across all regions. This advancement will help in better assessing future sea level changes and freshwater resources, with significance for both the scientific community and society at large.
Maxence Menthon, Pepijn Bakker, Aurélien Quiquet, Didier M. Roche, and Ronja Reese
EGUsphere, https://doi.org/10.5194/egusphere-2025-777, https://doi.org/10.5194/egusphere-2025-777, 2025
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The ice-ocean interaction is a large source of uncertainty in future projections of the Antarctic ice sheet. Here we implement a basal ice shelf melt module (PICO) in a ice sheet model (GRISLI) and test six simple statistical methods to calibrate this module. We show that calculating the mean absolute error of bins best fits the observational datasets under multiple conditions. We also assess the impact of the module implementation and calibration choice on future projections until 2300.
Gong Cheng, Mansa Krishna, and Mathieu Morlighem
EGUsphere, https://doi.org/10.5194/egusphere-2025-1188, https://doi.org/10.5194/egusphere-2025-1188, 2025
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Predicting ice sheet contributions to sea level rise is challenging due to limited data and uncertainties in key processes. Traditional models require complex methods that lack flexibility. We developed PINNICLE, an open-source Python library that integrates machine learning with physical laws to improve ice sheet modeling. By combining data and physics, PINNICLE enhances predictions and adaptability, providing a powerful tool for climate research and sea level rise projections.
Jan Svoboda, Marc Ruesch, David Liechti, Corinne Jones, Michele Volpi, Michael Zehnder, and Jürg Schweizer
Geosci. Model Dev., 18, 1829–1849, https://doi.org/10.5194/gmd-18-1829-2025, https://doi.org/10.5194/gmd-18-1829-2025, 2025
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Accurately measuring snow height is key for modeling approaches in climate science, snow hydrology, and avalanche forecasting. Erroneous snow height measurements often occur when snow height is low or changes, for instance during snowfall in 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 in a data pipeline for snow modeling.
Alek Aaron Petty, Christopher Cardinale, and Madison Smith
EGUsphere, https://doi.org/10.5194/egusphere-2025-766, https://doi.org/10.5194/egusphere-2025-766, 2025
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We put global climate models to the test against NASA’s ICESat-2 satellite to see how well they simulate global sea ice cover. By adding fancy laser data from ICESat-2, we can better assess how well the models are performing compared to the standard assessments of sea ice area. Overall the models do a good job but there’s room for improvement, especially across the Southern Ocean. We should think a bit more about sea ice density if we want more reliable freeboard comparisons.
James W. Marschalek, Edward Gasson, Tina van de Flierdt, Claus-Dieter Hillenbrand, Martin J. Siegert, and Liam Holder
Geosci. Model Dev., 18, 1673–1708, https://doi.org/10.5194/gmd-18-1673-2025, https://doi.org/10.5194/gmd-18-1673-2025, 2025
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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 and 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.
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.
Théo Brivoal, Virginie Guemas, Martin Vancoppenolle, Clément Rousset, and Bertrand Decharme
EGUsphere, https://doi.org/10.5194/egusphere-2024-3220, https://doi.org/10.5194/egusphere-2024-3220, 2025
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Snow in polar regions is key to sea ice formation and the Earth's climate, but current climate models simplify snow cover on sea ice. This study integrates an intermediate complexity snow-physics scheme into a sea-ice model designed for climate applications. We show that modelling the temporal changes in properties such as the density and thermal conductivity of the snow layers leads to a more accurate representation of heat transfer between the underlying sea ice and the atmosphere.
Samar Minallah, William Lipscomb, Gunter Leguy, and Harry Zekollari
EGUsphere, https://doi.org/10.5194/egusphere-2024-4152, https://doi.org/10.5194/egusphere-2024-4152, 2025
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We implemented a new modeling framework within an Earth system model to study the evolution of mountain glaciers under different climate scenarios and applied it to the European Alps. Alpine glaciers will lose a large volume fraction under current temperatures, with near complete ice loss under warmer scenarios. This is the first use of a 3D, higher-order ice flow model for regional-scale glacier simulations that will enable assessments of coupled land ice and Earth system processes.
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.
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.
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.
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.
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.
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.
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Short summary
Mountain glaciers are one of the few remaining subsystems of the global climate system for which no globally applicable community-driven model exists. Here we present the Open Global Glacier Model (OGGM; www.oggm.org), developed to provide a modular and open-source numerical model framework for simulating past and future change of any glacier in the world.
Mountain glaciers are one of the few remaining subsystems of the global climate system for which...
