Articles | Volume 19, issue 11
https://doi.org/10.5194/tc-19-5801-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-19-5801-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
17 Nov 2025
Research article |
| 17 Nov 2025
| 17 Nov 2025
Machine learning improves seasonal mass balance prediction for unmonitored glaciers
Department of Civil Engineering and Environmental Sciences, Western Norway University of Applied Sciences (HVL), Sogndal, Norway
Jordi Bolibar
Univ. Grenoble Alpes, CNRS, IRD, G-INP, Institut des Géosciences de l'Environnement, Grenoble, France
Faculty of Civil Engineering and Geosciences, Delft University of Technology, Delft, the Netherlands
Marijn van der Meer
Laboratory of Hydraulics, Hydrology, and Glaciology (VAW), ETH Zürich, Zurich, Switzerland
Swiss Federal Institute for Forest, Snow, and Landscape Research (WSL), Sion, Switzerland
Liss Marie Andreassen
Norwegian Water Resources and Energy Directorate (NVE), Oslo, Norway
Julian Peter Biesheuvel
Faculty of Civil Engineering and Geosciences, Delft University of Technology, Delft, the Netherlands
Thorben Dunse
Department of Civil Engineering and Environmental Sciences, Western Norway University of Applied Sciences (HVL), Sogndal, Norway
Matthias Huss
Laboratory of Hydraulics, Hydrology, and Glaciology (VAW), ETH Zürich, Zurich, Switzerland
Swiss Federal Institute for Forest, Snow, and Landscape Research (WSL), Sion, Switzerland
Department of Geosciences, University of Fribourg, Fribourg, Switzerland
Fabien Maussion
Bristol Glaciology Centre, School of Geographical Sciences, University of Bristol, Bristol, UK
Department of Atmospheric and Cryospheric Sciences, University of Innsbruck, Innsbruck, Austria
David R. Rounce
Department of Civil and Environmental Engineering, Carnegie Mellon University, Pittsburgh, PA, USA
Brandon Tober
Department of Civil and Environmental Engineering, Carnegie Mellon University, Pittsburgh, PA, USA
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Earth Syst. Sci. Data, 18, 1665–1681, https://doi.org/10.5194/essd-18-1665-2026, https://doi.org/10.5194/essd-18-1665-2026, 2026
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Many mountain glaciers around the world flow into lakes – exactly how many however, has never been mapped. Across a large team of experts we have now identified all glaciers that end in lakes. Only about 1% do so, but they are generally larger than those which end on land. This is important to understand, as lakes can influence the behaviour of glacier ice, including how fast it disappears. This new dataset allows us to better model glaciers at a global scale, accounting for the effect of lakes.
Patrick Schmitt, Fabien Maussion, Daniel N. Goldberg, and Philipp Gregor
Geosci. Model Dev., 19, 1301–1319, https://doi.org/10.5194/gmd-19-1301-2026, https://doi.org/10.5194/gmd-19-1301-2026, 2026
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To improve large-scale understanding of glaciers, we developed a new data assimilation method that integrates available observations in a dynamically consistent way, while taking their timestamps into account. It is designed to flexibly include new glacier data as it becomes available. We tested the method with idealized experiments and found promising results in terms of accuracy and efficiency, showing strong potential for real-world applications.
Jan Niklas Richter, Anselm Arndt, Nikolina Ban, Nicolas Gampierakis, Fabien Maussion, Rainer Prinz, Matthias Scheiter, Nikolaus Umlauf, and Lindsey Nicholson
EGUsphere, https://doi.org/10.5194/egusphere-2025-6249, https://doi.org/10.5194/egusphere-2025-6249, 2026
This preprint is open for discussion and under review for The Cryosphere (TC).
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We developed a multi-objective Bayesian framework to calibrate a surface energy balance (SEB) model using only publicly available satellite data and climate simulations. The framework constrains model parameters well but also reveals biases in the forcing, affecting the SEB and the simulated mass balance and snowlines. The results indicate that an uncertainty-aware model chain can help identify model errors and provides a first step towards physical glacier modelling without in-situ data.
Lucille Gimenes, Romain Millan, Nicolas Champollion, and Jordi Bolibar
The Cryosphere, 20, 171–182, https://doi.org/10.5194/tc-20-171-2026, https://doi.org/10.5194/tc-20-171-2026, 2026
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This study looks how changes in glacier thickness estimates and temperature will affect the timing when meltwater from glaciers in the western Kunlun Mountains will reach its peak. Using a global glacier model and two different datasets, we found that thinner glaciers and warmer temperatures cause peak meltwater to happen sooner. This is of interests since it affects future water supplies for people relying on glacier runoff, highlighting the need for accurate ice volume estimates.
Marit van Tiel, Matthias Huss, Massimiliano Zappa, Tobias Jonas, and Daniel Farinotti
Hydrol. Earth Syst. Sci., 30, 23–43, https://doi.org/10.5194/hess-30-23-2026, https://doi.org/10.5194/hess-30-23-2026, 2026
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The summer of 2022 was extremely warm and dry in Europe, severely impacting water availability. We calculated water balance anomalies for 88 glacierized catchments in Switzerland, showing that glaciers played a crucial role in alleviating the drought situation by melting at record rates, partially compensating for the lack of rain and snowmelt. By comparing 2022 with past extreme years, we show that while glacier meltwater remains essential during droughts, its contribution is declining.
Alexandra von der Esch, Matthias Huss, Marit van Tiel, Justine Berg, and Daniel Farinotti
Hydrol. Earth Syst. Sci., 29, 6761–6780, https://doi.org/10.5194/hess-29-6761-2025, https://doi.org/10.5194/hess-29-6761-2025, 2025
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Glaciers are vital water sources, especially in alpine regions. Using the Glacier Evolution Runoff Model (GERM), we examined how forcing data and model resolution impact glacio-hydrological model results. We find that precipitation biases greatly affect results, and coarse resolutions miss critical small-scale details. This highlights the trade-offs between computational efficiency and model accuracy, emphasizing the need for high-resolution data and precise calibration for reliable predictions.
Henning Åkesson, Kamilla Hauknes Sjursen, Thomas Vikhamar Schuler, Thorben Dunse, Liss Marie Andreassen, Mette Kusk Gillespie, Benjamin Aubrey Robson, Thomas Schellenberger, and Jacob Clement Yde
The Cryosphere, 19, 5871–5902, https://doi.org/10.5194/tc-19-5871-2025, https://doi.org/10.5194/tc-19-5871-2025, 2025
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We model the historical and future evolution of the Jostedalsbreen ice cap in Norway, projecting substantial and largely irreversible mass loss for the 21st century, and that the ice cap will split into three parts. Further mass loss is in the pipeline, with a disappearance during the 22nd century under high emissions. Our study demonstrates an approach to model complex ice masses, highlights uncertainties due to precipitation, and calls for further research on long-term future glacier change.
Larissa Nora van der Laan, Anouk Vlug, Adam A. Scaife, Fabien Maussion, and Kristian Förster
The Cryosphere, 19, 3879–3896, https://doi.org/10.5194/tc-19-3879-2025, https://doi.org/10.5194/tc-19-3879-2025, 2025
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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 timescales. Reliable information on these timescales is very important, especially for water management experts, to know how much meltwater to expect, affecting rivers, agriculture and drinking water.
Francesca Pellicciotti, Adrià Fontrodona-Bach, David R. Rounce, Catriona L. Fyffe, Leif S. Anderson, Álvaro Ayala, Ben W. Brock, Pascal Buri, Stefan Fugger, Koji Fujita, Prateek Gantayat, Alexander R. Groos, Walter Immerzeel, Marin Kneib, Christoph Mayer, Shelley MacDonell, Michael McCarthy, James McPhee, Evan Miles, Heather Purdie, Ekaterina Rets, Akiko Sakai, Thomas E. Shaw, Jakob Steiner, Patrick Wagnon, and Alex Winter-Billington
EGUsphere, https://doi.org/10.5194/egusphere-2025-3837, https://doi.org/10.5194/egusphere-2025-3837, 2025
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Rock debris covers many of the world glaciers, modifying the transfer of atmospheric energy to the debris and into the ice. Models of different complexity simulate this process, and we compare 14 models at 9 sites to show that the most complex models at the debris-atmosphere interface have the highest performance. However, we lack debris properties and their derivation from measurements is ambiguous, hindering global modelling and calling for both model development and data collection.
Aaron Cremona, Matthias Huss, Johannes Marian Landmann, Mauro Marty, Marijn van der Meer, Christian Ginzler, and Daniel Farinotti
EGUsphere, https://doi.org/10.5194/egusphere-2025-2929, https://doi.org/10.5194/egusphere-2025-2929, 2025
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Our study provides daily mass balance estimates for every Swiss glacier from 2010–2024 using modelling, remote sensing observations, and machine learning. Over the period, Swiss glaciers lost nearly a quarter of their ice volume. The approach enables investigating the spatio-temporal variability of glacier mass balance in relation to the driving climatic factors.
Douglas J. Brinkerhoff, Brandon S. Tober, Michael Daniel, Victor Devaux-Chupin, Michael S. Christoffersen, John W. Holt, Christopher F. Larsen, Mark Fahnestock, Michael G. Loso, Kristin M. F. Timm, Russell C. Mitchell, and Martin Truffer
The Cryosphere, 19, 2321–2353, https://doi.org/10.5194/tc-19-2321-2025, https://doi.org/10.5194/tc-19-2321-2025, 2025
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Sít' Tlein is one of the largest glaciers in the world outside of the polar regions, and we know that it has been rapidly thinning. To forecast how this glacier will change in the future, we combine a computer model of ice flow with measurements from many different sources. Our model tells us that with high probability, Sít' Tlein's lower reaches are going to disappear in the next century and a half, creating a new bay or lake along Alaska's coastline.
Lorenz Hänchen, Emily Potter, Cornelia Klein, Pierluigi Calanca, Fabien Maussion, Wolfgang Gurgiser, and Georg Wohlfahrt
Hydrol. Earth Syst. Sci., 29, 2727–2747, https://doi.org/10.5194/hess-29-2727-2025, https://doi.org/10.5194/hess-29-2727-2025, 2025
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In semi-arid regions, the timing and duration of the rainy season are crucial for agriculture. This study introduces a new framework for improving estimations of the onset and end of the rainy season by testing how well they fit local vegetation data. We improve the performance of existing methods and present a new one with higher performance. Our findings can help us to make informed decisions about water usage, and the framework can be applied to other regions as well.
Inés Dussaillant, Romain Hugonnet, Matthias Huss, Etienne Berthier, Jacqueline Bannwart, Frank Paul, and Michael Zemp
Earth Syst. Sci. Data, 17, 1977–2006, https://doi.org/10.5194/essd-17-1977-2025, https://doi.org/10.5194/essd-17-1977-2025, 2025
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Our research observes glacier mass changes worldwide from 1976 to 2024, revealing an alarming increase in melt, especially in the last decade and the record year of 2023. By combining field and satellite observations, we provide annual mass changes for all glaciers in the world, showing significant contributions to global sea level rise. This work underscores the need for ongoing local monitoring and global climate action to mitigate the effects of glacier loss and its broader environmental impacts.
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.
Janneke van Ginkel, Fabian Walter, Fabian Lindner, Miroslav Hallo, Matthias Huss, and Donat Fäh
The Cryosphere, 19, 1469–1490, https://doi.org/10.5194/tc-19-1469-2025, https://doi.org/10.5194/tc-19-1469-2025, 2025
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This study on Glacier de la Plaine Morte in Switzerland employs various passive seismic analysis methods to identify complex hydraulic behaviours at the ice–bedrock interface. In 4 months of seismic records, we detect spatio-temporal variations in the glacier's basal interface, following the drainage of an ice-marginal lake. We identify a low-velocity layer, whose properties are determined using modelling techniques. This low-velocity layer results from temporary water storage subglacially.
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.
Marijn van der Meer, Harry Zekollari, Matthias Huss, Jordi Bolibar, Kamilla Hauknes Sjursen, and Daniel Farinotti
The Cryosphere, 19, 805–826, https://doi.org/10.5194/tc-19-805-2025, https://doi.org/10.5194/tc-19-805-2025, 2025
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Glacier retreat poses big challenges, making understanding how climate affects glaciers vital. But glacier measurements worldwide are limited. We created a simple machine-learning model called miniML-MB, which estimates annual changes in glacier mass in the Swiss Alps. As input, miniML-MB uses two climate variables: average temperature (May–Aug) and total precipitation (Oct–Feb). Our model can accurately predict glacier mass from 1961 to 2021 but struggles for extreme years (2022 and 2023).
Mette K. Gillespie, Liss M. Andreassen, Matthias Huss, Simon de Villiers, Kamilla H. Sjursen, Jostein Aasen, Jostein Bakke, Jan M. Cederstrøm, Hallgeir Elvehøy, Bjarne Kjøllmoen, Even Loe, Marte Meland, Kjetil Melvold, Sigurd D. Nerhus, Torgeir O. Røthe, Eivind W. N. Støren, Kåre Øst, and Jacob C. Yde
Earth Syst. Sci. Data, 16, 5799–5825, https://doi.org/10.5194/essd-16-5799-2024, https://doi.org/10.5194/essd-16-5799-2024, 2024
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We present an extensive ice thickness dataset from Jostedalsbreen ice cap that will serve as a baseline for future studies of regional climate-induced change. Results show that Jostedalsbreen currently (~2020) has a maximum ice thickness of ~630 m, a mean ice thickness of 154 ± 22 m and an ice volume of 70.6 ±10.2 km3. Ice of less than 50 m thickness covers two narrow regions of Jostedalsbreen, and the ice cap is likely to separate into three parts in a warming climate.
Etienne Berthier, Jérôme Lebreton, Delphine Fontannaz, Steven Hosford, Joaquín Muñoz-Cobo Belart, Fanny Brun, Liss M. Andreassen, Brian Menounos, and Charlotte Blondel
The Cryosphere, 18, 5551–5571, https://doi.org/10.5194/tc-18-5551-2024, https://doi.org/10.5194/tc-18-5551-2024, 2024
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Repeat elevation measurements are crucial for monitoring glacier health and to understand how glaciers affect river flows and sea level. Until recently, high-resolution elevation data were mostly available for polar regions and High Mountain Asia. Our project, the Pléiades Glacier Observatory, now provides high-resolution topographies of 140 glacier sites worldwide. This is a novel and open dataset to monitor the impact of climate change on glaciers at high resolution and accuracy.
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.
Livia Piermattei, Michael Zemp, Christian Sommer, Fanny Brun, Matthias H. Braun, Liss M. Andreassen, Joaquín M. C. Belart, Etienne Berthier, Atanu Bhattacharya, Laura Boehm Vock, Tobias Bolch, Amaury Dehecq, Inés Dussaillant, Daniel Falaschi, Caitlyn Florentine, Dana Floricioiu, Christian Ginzler, Gregoire Guillet, Romain Hugonnet, Matthias Huss, Andreas Kääb, Owen King, Christoph Klug, Friedrich Knuth, Lukas Krieger, Jeff La Frenierre, Robert McNabb, Christopher McNeil, Rainer Prinz, Louis Sass, Thorsten Seehaus, David Shean, Désirée Treichler, Anja Wendt, and Ruitang Yang
The Cryosphere, 18, 3195–3230, https://doi.org/10.5194/tc-18-3195-2024, https://doi.org/10.5194/tc-18-3195-2024, 2024
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Satellites have made it possible to observe glacier elevation changes from all around the world. In the present study, we compared the results produced from two different types of satellite data between different research groups and against validation measurements from aeroplanes. We found a large spread between individual results but showed that the group ensemble can be used to reliably estimate glacier elevation changes and related errors from satellite data.
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.
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.
Jérôme Lopez-Saez, Christophe Corona, Lenka Slamova, Matthias Huss, Valérie Daux, Kurt Nicolussi, and Markus Stoffel
Clim. Past, 20, 1251–1267, https://doi.org/10.5194/cp-20-1251-2024, https://doi.org/10.5194/cp-20-1251-2024, 2024
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Glaciers in the European Alps have been retreating since the 1850s. Monitoring glacier mass balance is vital for understanding global changes, but only a few glaciers have long-term data. This study aims to reconstruct the mass balance of the Silvretta Glacier in the Swiss Alps using stable isotopes and tree ring proxies. Results indicate increased glacier mass until the 19th century, followed by a sharp decline after the Little Ice Age with accelerated losses due to anthropogenic warming.
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.
Lander Van Tricht, Harry Zekollari, Matthias Huss, Daniel Farinotti, and Philippe Huybrechts
The Cryosphere Discuss., https://doi.org/10.5194/tc-2023-87, https://doi.org/10.5194/tc-2023-87, 2023
Manuscript not accepted for further review
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Detailed 3D models can be applied for well-studied glaciers, whereas simplified approaches are used for regional/global assessments. We conducted a comparison of six Tien Shan glaciers employing different models and investigated the impact of in-situ measurements. Our results reveal that the choice of mass balance and ice flow model as well as calibration have minimal impact on the projected volume. The initial ice thickness exerts the greatest influence on the future remaining ice volume.
Christian Sommer, Johannes J. Fürst, Matthias Huss, and Matthias H. Braun
The Cryosphere, 17, 2285–2303, https://doi.org/10.5194/tc-17-2285-2023, https://doi.org/10.5194/tc-17-2285-2023, 2023
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Knowledge on the volume of glaciers is important to project future runoff. Here, we present a novel approach to reconstruct the regional ice thickness distribution from easily available remote-sensing data. We show that past ice thickness, derived from spaceborne glacier area and elevation datasets, can constrain the estimated ice thickness. Based on the unique glaciological database of the European Alps, the approach will be most beneficial in regions without direct thickness measurements.
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.
Matteo Guidicelli, Matthias Huss, Marco Gabella, and Nadine Salzmann
The Cryosphere, 17, 977–1002, https://doi.org/10.5194/tc-17-977-2023, https://doi.org/10.5194/tc-17-977-2023, 2023
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Spatio-temporal reconstruction of winter glacier mass balance is important for assessing long-term impacts of climate change. However, high-altitude regions significantly lack reliable observations, which is limiting the calibration of glaciological and hydrological models. We aim at improving knowledge on the spatio-temporal variations in winter glacier mass balance by exploring the combination of data from reanalyses and direct snow accumulation observations on glaciers with machine learning.
Pau Wiersma, Jerom Aerts, Harry Zekollari, Markus Hrachowitz, Niels Drost, Matthias Huss, Edwin H. Sutanudjaja, and Rolf Hut
Hydrol. Earth Syst. Sci., 26, 5971–5986, https://doi.org/10.5194/hess-26-5971-2022, https://doi.org/10.5194/hess-26-5971-2022, 2022
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We test whether coupling a global glacier model (GloGEM) with a global hydrological model (PCR-GLOBWB 2) leads to a more realistic glacier representation and to improved basin runoff simulations across 25 large-scale basins. The coupling does lead to improved glacier representation, mainly by accounting for glacier flow and net glacier mass loss, and to improved basin runoff simulations, mostly in strongly glacier-influenced basins, which is where the coupling has the most impact.
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.
Jonathan P. Conway, Jakob Abermann, Liss M. Andreassen, Mohd Farooq Azam, Nicolas J. Cullen, Noel Fitzpatrick, Rianne H. Giesen, Kirsty Langley, Shelley MacDonell, Thomas Mölg, Valentina Radić, Carleen H. Reijmer, and Jean-Emmanuel Sicart
The Cryosphere, 16, 3331–3356, https://doi.org/10.5194/tc-16-3331-2022, https://doi.org/10.5194/tc-16-3331-2022, 2022
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We used data from automatic weather stations on 16 glaciers to show how clouds influence glacier melt in different climates around the world. We found surface melt was always more frequent when it was cloudy but was not universally faster or slower than under clear-sky conditions. Also, air temperature was related to clouds in opposite ways in different climates – warmer with clouds in cold climates and vice versa. These results will help us improve how we model past and future glacier melt.
Erik Schytt Mannerfelt, Amaury Dehecq, Romain Hugonnet, Elias Hodel, Matthias Huss, Andreas Bauder, and Daniel Farinotti
The Cryosphere, 16, 3249–3268, https://doi.org/10.5194/tc-16-3249-2022, https://doi.org/10.5194/tc-16-3249-2022, 2022
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How glaciers have responded to climate change over the last 20 years is well-known, but earlier data are much more scarce. We change this in Switzerland by using 22 000 photographs taken from mountain tops between the world wars and find a halving of Swiss glacier volume since 1931. This was done through new automated processing techniques that we created. The data are interesting for more than just glaciers, such as mapping forest changes, landslides, and human impacts on the terrain.
Lea Geibel, Matthias Huss, Claudia Kurzböck, Elias Hodel, Andreas Bauder, and Daniel Farinotti
Earth Syst. Sci. Data, 14, 3293–3312, https://doi.org/10.5194/essd-14-3293-2022, https://doi.org/10.5194/essd-14-3293-2022, 2022
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Glacier monitoring in Switzerland started in the 19th century, providing exceptional data series documenting snow accumulation and ice melt. Raw point observations of surface mass balance have, however, never been systematically compiled so far, including complete metadata. Here, we present an extensive dataset with more than 60 000 point observations of surface mass balance covering 60 Swiss glaciers and almost 140 years, promoting a better understanding of the drivers of recent glacier change.
Tim Steffen, Matthias Huss, Rebekka Estermann, Elias Hodel, and Daniel Farinotti
Earth Surf. Dynam., 10, 723–741, https://doi.org/10.5194/esurf-10-723-2022, https://doi.org/10.5194/esurf-10-723-2022, 2022
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Climate change is rapidly altering high-alpine landscapes. The formation of new lakes in areas becoming ice free due to glacier retreat is one of the many consequences of this process. Here, we provide an estimate for the number, size, time of emergence, and sediment infill of future glacier lakes that will emerge in the Swiss Alps. We estimate that up to ~ 680 potential lakes could form over the course of the 21st century, with the potential to hold a total water volume of up to ~ 1.16 km3.
Loris Compagno, Matthias Huss, Evan Stewart Miles, Michael James McCarthy, Harry Zekollari, Amaury Dehecq, Francesca Pellicciotti, and Daniel Farinotti
The Cryosphere, 16, 1697–1718, https://doi.org/10.5194/tc-16-1697-2022, https://doi.org/10.5194/tc-16-1697-2022, 2022
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We present a new approach for modelling debris area and thickness evolution. We implement the module into a combined mass-balance ice-flow model, and we apply it using different climate scenarios to project the future evolution of all glaciers in High Mountain Asia. We show that glacier geometry, volume, and flow velocity evolve differently when modelling explicitly debris cover compared to glacier evolution without the debris-cover module, demonstrating the importance of accounting for debris.
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.
Thorben Dunse, Kaixing Dong, Kjetil Schanke Aas, and Leif Christian Stige
Biogeosciences, 19, 271–294, https://doi.org/10.5194/bg-19-271-2022, https://doi.org/10.5194/bg-19-271-2022, 2022
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We investigate the effect of glacier meltwater on phytoplankton dynamics in Svalbard. Phytoplankton forms the basis of the marine food web, and its seasonal dynamics depend on the availability of light and nutrients, both of which are affected by glacier runoff. We use satellite ocean color, an indicator of phytoplankton biomass, and glacier mass balance modeling to find that the overall effect of glacier runoff on marine productivity is positive within the major fjord systems of Svalbard.
Christophe Ogier, Mauro A. Werder, Matthias Huss, Isabelle Kull, David Hodel, and Daniel Farinotti
The Cryosphere, 15, 5133–5150, https://doi.org/10.5194/tc-15-5133-2021, https://doi.org/10.5194/tc-15-5133-2021, 2021
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Glacier-dammed lakes are prone to draining rapidly when the ice dam breaks and constitute a serious threat to populations downstream. Such a lake drainage can proceed through an open-air channel at the glacier surface. In this study, we present what we believe to be the most complete dataset to date of an ice-dammed lake drainage through such an open-air channel. We provide new insights for future glacier-dammed lake drainage modelling studies and hazard assessments.
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.
Hannah R. Field, William H. Armstrong, and Matthias Huss
The Cryosphere, 15, 3255–3278, https://doi.org/10.5194/tc-15-3255-2021, https://doi.org/10.5194/tc-15-3255-2021, 2021
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The growth of a glacier lake alters the hydrology, ecology, and glaciology of its surrounding region. We investigate modern glacier lake area change across northwestern North America using repeat satellite imagery. Broadly, we find that lakes downstream from glaciers grew, while lakes dammed by glaciers shrunk. Our results suggest that the shape of the landscape surrounding a glacier lake plays a larger role in determining how quickly a lake changes than climatic or glaciologic factors.
Loris Compagno, Sarah Eggs, Matthias Huss, Harry Zekollari, and Daniel Farinotti
The Cryosphere, 15, 2593–2599, https://doi.org/10.5194/tc-15-2593-2021, https://doi.org/10.5194/tc-15-2593-2021, 2021
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Recently, discussions have focused on the difference in limiting the increase in global average temperatures to below 1.0, 1.5, or 2.0 °C compared to preindustrial levels. Here, we assess the impacts that such different scenarios would have on both the future evolution of glaciers in the European Alps and the water resources they provide. Our results show that the different temperature targets have important implications for the changes predicted until 2100.
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Short summary
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.
Understanding glacier mass changes is crucial for assessing freshwater availability in many...
