Articles | Volume 19, issue 2
https://doi.org/10.5194/tc-19-805-2025
© 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-19-805-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A minimal machine-learning glacier mass balance model
Laboratory of Hydraulics, Hydrology, and Glaciology (VAW), ETH Zürich, Zurich, Switzerland
Swiss Federal Institute for Forest, Snow, and Landscape Research (WSL), Birmensdorf, Switzerland
Harry Zekollari
Laboratory of Hydraulics, Hydrology, and Glaciology (VAW), ETH Zürich, Zurich, Switzerland
Swiss Federal Institute for Forest, Snow, and Landscape Research (WSL), Birmensdorf, Switzerland
Department of Water and Climate, Vrije Universiteit Brussel (VUB), Brussels, Belgium
Laboratoire de Glaciologie, Université libre de Bruxelles (ULB), Brussels, Belgium
Matthias Huss
Laboratory of Hydraulics, Hydrology, and Glaciology (VAW), ETH Zürich, Zurich, Switzerland
Swiss Federal Institute for Forest, Snow, and Landscape Research (WSL), Birmensdorf, Switzerland
Department of Geosciences, University of Fribourg, Fribourg, Switzerland
Jordi Bolibar
Institut des Géosciences de l’Environnement, CNRS, IRD, G-INP, Univ. Grenoble Alpes, Grenoble, France
Department of Geosciences and Civil Engineering, TU Delft, Delft, the Netherlands
Kamilla Hauknes Sjursen
Department of Civil Engineering and Environmental Sciences, Western Norway University of Applied Sciences (HVL), Sogndal, Norway
Daniel Farinotti
Laboratory of Hydraulics, Hydrology, and Glaciology (VAW), ETH Zürich, Zurich, Switzerland
Swiss Federal Institute for Forest, Snow, and Landscape Research (WSL), Birmensdorf, Switzerland
Related authors
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
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
Short summary
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.
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
Short summary
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.
Lucille Gimenes, Romain Millan, Nicolas Champollion, and Jordi Bolibar
EGUsphere, https://doi.org/10.5194/egusphere-2025-3460, https://doi.org/10.5194/egusphere-2025-3460, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
Short summary
This study looks how changes in glacier thickness estimates and temperature affect 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 smaller 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.
Magali Ponds, Sarah Hanus, Harry Zekollari, Marie-Claire ten Veldhuis, Gerrit Schoups, Roland Kaitna, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 29, 3545–3568, https://doi.org/10.5194/hess-29-3545-2025, https://doi.org/10.5194/hess-29-3545-2025, 2025
Short summary
Short summary
This research examines how future climate changes impact root zone storage, a key hydrological model parameter. Root zone storage – the soil water accessible to plants – adapts to climate but is often kept constant in models. We estimated climate-adapted storage in six Austrian Alps catchments. While storage increased, streamflow projections showed minimal change, which suggests that dynamic root zone representation is less critical in humid regions but warrants further study in arid areas.
Ian Delaney, Andrew J. Tedstone, Mauro A. Werder, and Daniel Farinotti
The Cryosphere, 19, 2779–2795, https://doi.org/10.5194/tc-19-2779-2025, https://doi.org/10.5194/tc-19-2779-2025, 2025
Short summary
Short summary
Sediment transport capacity depends on water velocity and channel width. In rivers, water discharge changes affect flow depth, width, and velocity. Yet, under glaciers, discharge variations alter velocity more than channel shape. Due to these differences, this study shows that sediment transport capacity under glaciers varies widely and peaks before water flow, creating a complex relationship. Understanding these dynamics helps interpret sediment discharge from glaciers in different climates.
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
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
Short summary
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.
Jane Walden, Mylène Jacquemart, Bretwood Higman, Romain Hugonnet, Andrea Manconi, and Daniel Farinotti
Nat. Hazards Earth Syst. Sci., 25, 2045–2073, https://doi.org/10.5194/nhess-25-2045-2025, https://doi.org/10.5194/nhess-25-2045-2025, 2025
Short summary
Short summary
We studied eight glacier-adjacent landslides in Alaska and found that slope movement increased at four sites as the glacier retreated past the landslide area. Movement at other sites may be due to heavy precipitation or increased glacier thinning, and two sites showed little to no motion. We suggest that landslides near waterbodies may be especially vulnerable to acceleration, which we guess is due to faster retreat rates of water-terminating glaciers and changing water flow in the slope.
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
Short summary
Short summary
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.
Kaian Shahateet, Johannes J. Fürst, Francisco Navarro, Thorsten Seehaus, Daniel Farinotti, and Matthias Braun
The Cryosphere, 19, 1577–1597, https://doi.org/10.5194/tc-19-1577-2025, https://doi.org/10.5194/tc-19-1577-2025, 2025
Short summary
Short summary
In the present work, we provide a new ice thickness reconstruction of the Antarctic Peninsula Ice Sheet north of 70º S using inversion modeling. This model consists of two steps: the first uses basic assumptions of the rheology of the glacier, and the second uses mass conservation to improve the reconstruction where the assumptions made previously are expected to fail. Validation with independent data showed that our reconstruction improved compared to other reconstructions that are available.
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
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.
Marit van Tiel, Matthias Huss, Massimiliano Zappa, Tobias Jonas, and Daniel Farinotti
EGUsphere, https://doi.org/10.5194/egusphere-2025-404, https://doi.org/10.5194/egusphere-2025-404, 2025
Short summary
Short summary
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.
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
EGUsphere, https://doi.org/10.5194/egusphere-2025-467, https://doi.org/10.5194/egusphere-2025-467, 2025
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Laura Gabriel, Marian Hertrich, Christophe Ogier, Mike Müller-Petke, Raphael Moser, Hansruedi Maurer, and Daniel Farinotti
EGUsphere, https://doi.org/10.5194/egusphere-2024-3741, https://doi.org/10.5194/egusphere-2024-3741, 2025
Short summary
Short summary
Surface nuclear magnetic resonance (SNMR) is a geophysical technique directly sensitive to liquid water. We expand the limited applications of SNMR on glaciers by detecting water within Rhonegletscher, Switzerland. By carefully processing the data to reduce noise, we identified signals indicating a water layer near the base of the glacier, surrounded by ice with low water content. Our findings, validated by radar measurements, show SNMR's potential and limitations in studying water in glaciers.
Alexandra von der Esch, Matthias Huss, Marit van Tiel, Justine Berg, and Daniel Farinotti
EGUsphere, https://doi.org/10.5194/egusphere-2024-3965, https://doi.org/10.5194/egusphere-2024-3965, 2025
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Bastien Ruols, Johanna Klahold, Daniel Farinotti, and James Irving
EGUsphere, https://doi.org/10.5194/egusphere-2024-3074, https://doi.org/10.5194/egusphere-2024-3074, 2024
Short summary
Short summary
We demonstrate the use of a drone-based ground-penetrating radar (GPR) system to gather high-resolution, high-density 4D data over a near-terminus glacier collapse feature. We monitor the growth of an air cavity and the evolution of the subglacial drainage system, providing new insights into the dynamics of collapse events. This work highlights potential future applications of drone-based GPR for monitoring glaciers, in particular in regions which are inaccessible with surface-based methods.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Anja Løkkegaard, Kenneth D. Mankoff, Christian Zdanowicz, Gary D. Clow, Martin P. Lüthi, Samuel H. Doyle, Henrik H. Thomsen, David Fisher, Joel Harper, Andy Aschwanden, Bo M. Vinther, Dorthe Dahl-Jensen, Harry Zekollari, Toby Meierbachtol, Ian McDowell, Neil Humphrey, Anne Solgaard, Nanna B. Karlsson, Shfaqat A. Khan, Benjamin Hills, Robert Law, Bryn Hubbard, Poul Christoffersen, Mylène Jacquemart, Julien Seguinot, Robert S. Fausto, and William T. Colgan
The Cryosphere, 17, 3829–3845, https://doi.org/10.5194/tc-17-3829-2023, https://doi.org/10.5194/tc-17-3829-2023, 2023
Short summary
Short summary
This study presents a database compiling 95 ice temperature profiles from the Greenland ice sheet and peripheral ice caps. Ice viscosity and hence ice flow are highly sensitive to ice temperature. To highlight the value of the database in evaluating ice flow simulations, profiles from the Greenland ice sheet are compared to a modeled temperature field. Reoccurring discrepancies between modeled and observed temperatures provide insight on the difficulties faced when simulating ice temperatures.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Fabian Walter, Elias Hodel, Erik S. Mannerfelt, Kristen Cook, Michael Dietze, Livia Estermann, Michaela Wenner, Daniel Farinotti, Martin Fengler, Lukas Hammerschmidt, Flavia Hänsli, Jacob Hirschberg, Brian McArdell, and Peter Molnar
Nat. Hazards Earth Syst. Sci., 22, 4011–4018, https://doi.org/10.5194/nhess-22-4011-2022, https://doi.org/10.5194/nhess-22-4011-2022, 2022
Short summary
Short summary
Debris flows are dangerous sediment–water mixtures in steep terrain. Their formation takes place in poorly accessible terrain where instrumentation cannot be installed. Here we propose to monitor such source terrain with an autonomous drone for mapping sediments which were left behind by debris flows or may contribute to future events. Short flight intervals elucidate changes of such sediments, providing important information for landscape evolution and the likelihood of future debris flows.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Adrien Michel, Bettina Schaefli, Nander Wever, Harry Zekollari, Michael Lehning, and Hendrik Huwald
Hydrol. Earth Syst. Sci., 26, 1063–1087, https://doi.org/10.5194/hess-26-1063-2022, https://doi.org/10.5194/hess-26-1063-2022, 2022
Short summary
Short summary
This study presents an extensive study of climate change impacts on river temperature in Switzerland. Results show that, even for low-emission scenarios, water temperature increase will lead to adverse effects for both ecosystems and socio-economic sectors throughout the 21st century. For high-emission scenarios, the effect will worsen. This study also shows that water seasonal warming will be different between the Alpine regions and the lowlands. Finally, efficiency of models is assessed.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Lander Van Tricht, Philippe Huybrechts, Jonas Van Breedam, Alexander Vanhulle, Kristof Van Oost, and Harry Zekollari
The Cryosphere, 15, 4445–4464, https://doi.org/10.5194/tc-15-4445-2021, https://doi.org/10.5194/tc-15-4445-2021, 2021
Short summary
Short summary
We conducted innovative research on the use of drones to determine the surface mass balance (SMB) of two glaciers. Considering appropriate spatial scales, we succeeded in determining the SMB in the ablation area with large accuracy. Consequently, we are convinced that our method and the use of drones to monitor the mass balance of a glacier’s ablation area can be an add-on to stake measurements in order to obtain a broader picture of the heterogeneity of the SMB of glaciers.
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
Short summary
Short summary
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.
Sarah Hanus, Markus Hrachowitz, Harry Zekollari, Gerrit Schoups, Miren Vizcaino, and Roland Kaitna
Hydrol. Earth Syst. Sci., 25, 3429–3453, https://doi.org/10.5194/hess-25-3429-2021, https://doi.org/10.5194/hess-25-3429-2021, 2021
Short summary
Short summary
This study investigates the effects of climate change on runoff patterns in six Alpine catchments in Austria at the end of the 21st century. Our results indicate a substantial shift to earlier occurrences in annual maximum and minimum flows in high-elevation catchments. Magnitudes of annual extremes are projected to increase under a moderate emission scenario in all catchments. Changes are generally more pronounced for high-elevation catchments.
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
Short summary
Short summary
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.
Rebecca Gugerli, Matteo Guidicelli, Marco Gabella, Matthias Huss, and Nadine Salzmann
Adv. Sci. Res., 18, 7–20, https://doi.org/10.5194/asr-18-7-2021, https://doi.org/10.5194/asr-18-7-2021, 2021
Short summary
Short summary
To obtain reliable snowfall estimates in high mountain remains a challenge. This study uses daily snow water equivalent (SWE) estimates by a cosmic ray sensor on two Swiss glaciers to assess three
readily-available high-quality precipitation products. We find a large bias between in situ SWE and snowfall, which differs among the precipitation products, the two sites, the winter seasons and in situ meteorological conditions. All products have great potential for various applications in the Alps.
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
Short summary
Short summary
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.
Cited articles
Adams, P.: Glossary of Glacier Mass Balance and Related Terms, prepared by the Working Group on Mass-Balance Terminology and Methods of the International Association of Cryospheric Sciences (IASC), ARCTIC, 64, 47, https://doi.org/10.14430/arctic4151, 2011. a
Arthur, D. and Vassilvitskii, S.: K-Means++: The Advantages of Careful Seeding, Proc. Annu. ACM-SIAM Symp. on Discrete Algorithms, 8, 1027–1035, 2007. a
Azam, M. F., Wagnon, P., Berthier, E., Vincent, C., Fujita, K., and Kargel, J. S.: Review of the status and mass changes of Himalayan-Karakoram glaciers, J. Glaciol., 64, 61–74, https://doi.org/10.1017/jog.2017.86, 2018. a
Benn, D. and Evans, D. J. A.: Glaciers and Glaciation, 2nd edition, Routledge, ISBN 9781444128390, https://doi.org/10.4324/9780203785010, 2014. a
Blake, E. W.: Glacier Mass-Balance Measurements: A Manual for Field and Office Work, edited by: Østrem, G. and Brugman, M., ARCTIC, 46, 284–285, https://doi.org/10.14430/arctic1836, 1993. a
Bolibar, J., Rabatel, A., Gouttevin, I., Zekollari, H., and Galiez, C.: Nonlinear sensitivity of glacier mass balance to future climate change unveiled by deep learning, Nat. Commun., 13, 409, https://doi.org/10.1038/s41467-022-28033-0, 2022. a, b
Bottou, L. and Bousquet, O.: The Tradeoffs of Large-Scale Learning, p. The MIT Press, 351–368, ISBN 9780262298773, https://doi.org/10.7551/mitpress/8996.003.0015, 2011. a
Braithwaite, R. J.: Temperature and precipitation climate at the equilibrium-line altitude of glaciers expressed by the degree-day factor for melting snow, J. Glaciol., 54, 437–444, https://doi.org/10.3189/002214308785836968, 2008. a
Braithwaite, R. J. and Olesen, O. B.: A Simple Energy-Balance Model to Calculate Ice Ablation at the Margin of the Greenland Ice Sheet, J. Glaciol., 36, 222–228, https://doi.org/10.3189/S0022143000009473, 1990. a
Chen, J. and Funk, M.: Mass Balance of Rhonegletscher During 1882/83–1986/87, J. Glaciol., 36, 199–209, https://doi.org/10.1017/s0022143000009448, 1990. a
Chen, T. and Guestrin, C.: XGBoost: A Scalable Tree Boosting System, in: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '16, ACM, https://doi.org/10.1145/2939672.2939785, 2016. a, b
Cogley, J. G., Hock, R., Rasmussen, L. A., Arendt, A. A., Bauder, A., Braithwaite, R. J., Jansson, P., Kaser, G., Möller, M., Nicholson, L., and Zemp, M.: Glossary of Glacier Mass Balance and Related Terms, IHP-VII Technical Documents in Hydrology No. 86, IACS Contribution No. 2, UNESCO-IHP, Paris, https://wgms.ch/downloads/Cogley_etal_2011.pdf (last access: April 2024), 2011. a
Cook, S. J., Jouvet, G., Millan, R., Rabatel, A., Zekollari, H., and Dussaillant, I.: Committed Ice Loss in the European Alps Until 2050 Using a Deep-Learning-Aided 3D Ice-Flow Model With Data Assimilation, Geophys. Res. Lett., 50, e2023GL105029, https://doi.org/https://doi.org/10.1029/2023GL105029, 2023a. a
Cook, S. J., Jouvet, G., Millan, R., Rabatel, A., Zekollari, H., and Dussaillant, I.: Committed Ice Loss in the European Alps Until 2050 Using a Deep‐Learning‐Aided 3D Ice‐Flow Model With Data Assimilation, Geophys. Res. Lett., 50, e2023GL105029, https://doi.org/10.1029/2023gl105029, 2023b. a
Dube, P., Bhattacharjee, B., Petit-Bois, E., and Hill, M.: Improving Transferability of Deep Neural Networks, Springer International Publishing, 51–64, ISBN 9783030306717, https://doi.org/10.1007/978-3-030-30671-7_4, 2020. a
Friedman, J. H.: Greedy function approximation: A gradient boosting machine, Ann. Stat., 29, 1189–1232, https://doi.org/10.1214/aos/1013203451, 2001. a
Geibel, L., Huss, M., Kurzböck, C., Hodel, E., Bauder, A., and Farinotti, D.: Rescue and homogenization of 140 years of glacier mass balance data in Switzerland, Earth Syst. Sci. Data, 14, 3293–3312, https://doi.org/10.5194/essd-14-3293-2022, 2022. a
GLAMOS: Swiss Glacier Mass Balance, release 2023, Glacier Monitoring Switzerland [data set], https://doi.org/10.18750/massbalance.point.2023.r2023, 2023a. a, b
GLAMOS: Swiss Glacier Mass Balance, release 2023, Glacier Monitoring Switzerland [data set], https://doi.org/10.18750/massbalance.swisswide.2023.r2023, 2023b. a
Greuell, W.: Hintereisferner, Austria: mass-balance reconstruction and numerical modelling of the historical length variations, J. Glaciol., 38, 233–244, https://doi.org/10.3189/s0022143000003646, 1992. a
Grinsztajn, L., Oyallon, E., and Varoquaux, G.: Why do tree-based models still outperform deep learning on typical tabular data?, arXiv [preprint], https://doi.org/10.48550/arXiv.2207.08815, 2022. a, b
Hengl, T., Nussbaum, M., Wright, M. N., Heuvelink, G. B. M., and Gräler, B.: Random forest as a generic framework for predictive modeling of spatial and spatio-temporal variables, PeerJ, 6, e5518, https://doi.org/10.7717/peerj.5518, 2018. a
Hock, R.: A distributed temperature-index ice- and snowmelt model including potential direct solar radiation, J. Glaciol., 45, 101–111, https://doi.org/10.3189/s0022143000003087, 1999. a
Hock, R.: Temperature index melt modelling in mountain areas, J. Hydrol., 282, 104–115, https://doi.org/10.1016/s0022-1694(03)00257-9, 2003. a, b, c
Huss, M. and Bauder, A.: 20th-century climate change inferred from four long-term point observations of seasonal mass balance, Ann. Glaciol., 50, 207–214, https://doi.org/10.3189/172756409787769645, 2009. a, b, c
Huss, M. and Hock, R.: A new model for global glacier change and sea-level rise, Frontiers in Earth Science, 3, 54, https://doi.org/10.3389/feart.2015.00054, 2015. a, b, c, d
Huss, M., Farinotti, D., Bauder, A., and Funk, M.: Modelling runoff from highly glacierized alpine drainage basins in a changing climate, Hydrol. Process., 22, 3888–3902, https://doi.org/10.1002/hyp.7055, 2008. a
Huss, M., Funk, M., and Ohmura, A.: Strong Alpine glacier melt in the 1940s due to enhanced solar radiation, Geophys. Res. Lett., 36, L23501, https://doi.org/10.1029/2009GL040789, 2009. a
Huss, M., Dhulst, L., and Bauder, A.: New long-term mass-balance series for the Swiss Alps, J. Glaciol., 61, 551–562, https://doi.org/10.3189/2015jog15j015, 2015. a
Huss, M., Bauder, A., Linsbauer, A., Gabbi, J., Kappenberger, G., Steinegger, U., and Farinotti, D.: More than a century of direct glacier mass-balance observations on Claridenfirn, Switzerland, J. Glaciol., 67, 697–713, https://doi.org/10.1017/jog.2021.22, 2021. a, b
IPCC: Climate Change 2023: Synthesis Report. Contribution of Working Groups I, II and III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, 35–115, https://doi.org/10.59327/IPCC/AR6-9789291691647, 2023. a
Ismail, M. F., Bogacki, W., Disse, M., Schäfer, M., and Kirschbauer, L.: Estimating degree-day factors of snow based on energy flux components, The Cryosphere, 17, 211–231, https://doi.org/10.5194/tc-17-211-2023, 2023. a
Jouvet, G.: Inversion of a Stokes glacier flow model emulated by deep learning, J. Glaciol., 69, 13–26, https://doi.org/10.1017/jog.2022.41, 2023. a
Jouvet, G. and Cordonnier, G.: Ice-flow model emulator based on physics-informed deep learning, J. Glaciol., 69, 1941–1955, https://doi.org/10.1017/jog.2023.73, 2023. a
Jouvet, G., Cordonnier, G., Kim, B., Lüthi, M., Vieli, A., and Aschwanden, A.: Deep learning speeds up ice flow modeling by several orders of magnitude, J. Glaciol., 68, 651–664, https://doi.org/10.1017/jog.2021.120, 2022. a
Kuhn, M., Dreiseitl, E., Hofinger, S., Markl, G., Span, N., and Kaser, G.: Measurements and Models of the Mass Balance of Hintereisferner, Geogr. Ann. A, 81, 659–670, https://doi.org/10.1111/j.0435-3676.1999.00094.x, 1999. a
Marzeion, B., Cogley, J. G., Richter, K., and Parkes, D.: Attribution of global glacier mass loss to anthropogenic and natural causes, Science, 345, 919–921, https://doi.org/10.1126/science.1254702, 2014. a
Mernild, S. H., Beckerman, A. P., Yde, J. C., Hanna, E., Malmros, J. K., Wilson, R., and Zemp, M.: Mass loss and imbalance of glaciers along the Andes Cordillera to the sub-Antarctic islands, Global Planet. Change, 133, 109–119, https://doi.org/10.1016/j.gloplacha.2015.08.009, 2015. a
MeteoSwiss: Monthly Precipitation: RhiresM, release 2023, MeteoSwiss Grid-Data Products [data set], https://www.meteoswiss.admin.ch/dam/jcr:d4f53a4a-d7f4-4e1e-a594-8ff4bfd1aca5/ProdDoc_RhiresM.pdf (last access: October 2023), 2023a. a
MeteoSwiss: Monthly Mean Temperature: TabsM, release 2023, MeteoSwiss Grid-Data Products [data set], https://www.meteoswiss.admin.ch/dam/jcr:33e26211-9937-4f80-80a3-09cfe54663bc/ProdDoc_TabsM.pdf (last access: October 2023), 2023b. a
Miles, E., McCarthy, M., Dehecq, A., Kneib, M., Fugger, S., and Pellicciotti, F.: Health and sustainability of glaciers in High Mountain Asia, Nat. Commun., 12, 2868, https://doi.org/10.1038/s41467-021-23073-4, 2021. a
Muñoz Sabater, J.: ERA5-Land monthly averaged data from 1950 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.68d2bb30, 2019. a
Oerlemans, J. and Reichert, B. K.: Relating glacier mass balance to meteorological data by using a seasonal sensitivity characteristic, J. Glaciol., 46, 1–6, https://doi.org/10.3189/172756500781833269, 2000. a
Ohmura, A.: Physical Basis for the Temperature-Based Melt-Index Method, J. Appl. Meteorol., 40, 753–761, https://doi.org/10.1175/1520-0450(2001)040<0753:pbfttb>2.0.co;2, 2001. a
Pellicciotti, F., Brock, B., Strasser, U., Burlando, P., Funk, M., and Corripio, J.: An enhanced temperature-index glacier melt model including the shortwave radiation balance: development and testing for Haut Glacier d’Arolla, Switzerland, J. Glaciol., 51, 573–587, https://doi.org/10.3189/172756505781829124, 2005. a
Peng, D., Gui, Z., and Wu, H.: Interpreting the Curse of Dimensionality from Distance Concentration and Manifold Effect, https://arxiv.org/abs/2401.00422 (last access: December 2024), 2024. a
Rounce, D. R., Hock, R., Maussion, F., Hugonnet, R., Kochtitzky, W., Huss, M., Berthier, E., Brinkerhoff, D., Compagno, L., Copland, L., Farinotti, D., Menounos, B., and McNabb, R. W.: Global glacier change in the 21st century: Every increase in temperature matters, Science, 379, 78–83, https://doi.org/10.1126/science.abo1324, 2023. a
Stamen Design: Map tiles under CC BY 4.0. Data by OpenStreetMap, under ODbL, https://stamen.com/, last access: December 2024. a
Torinesi, O., Letréguilly, A., and Valla, F.: A century reconstruction of the mass balance of Glacier de Sarennes, French Alps, J. Glaciol., 48, 142–148, https://doi.org/10.3189/172756502781831584, 2002. a
van der Meer, M., Zekollari, H., Huss, M., Bolibar, J., Sjursen, K. H., and Farinotti, D.: A minimal machine learning glacier mass balance model, Zenodo [code], https://doi.org/10.5281/zenodo.12905503, 2024. a
Van Tricht, L., Huybrechts, P., Van Breedam, J., Vanhulle, A., Van Oost, K., and Zekollari, H.: Estimating surface mass balance patterns from unoccupied aerial vehicle measurements in the ablation area of the Morteratsch–Pers glacier complex (Switzerland), The Cryosphere, 15, 4445–4464, https://doi.org/10.5194/tc-15-4445-2021, 2021. a
Vincent, C., Kappenberger, G., Valla, F., Bauder, A., Funk, M., and Le Meur, E.: Ice ablation as evidence of climate change in the Alps over the 20th century, J. Geophys. Res.-Atmos., 109, D10104, https://doi.org/10.1029/2003jd003857, 2004. a
Vincent, C., Fischer, A., Mayer, C., Bauder, A., Galos, S. P., Funk, M., Thibert, E., Six, D., Braun, L., and Huss, M.: Common climatic signal from glaciers in the European Alps over the last 50 years, Geophys. Res. Lett., 44, 1376–1383, https://doi.org/10.1002/2016gl072094, 2017. a
Vincent, C., Cusicanqui, D., Jourdain, B., Laarman, O., Six, D., Gilbert, A., Walpersdorf, A., Rabatel, A., Piard, L., Gimbert, F., Gagliardini, O., Peyaud, V., Arnaud, L., Thibert, E., Brun, F., and Nanni, U.: Geodetic point surface mass balances: a new approach to determine point surface mass balances on glaciers from remote sensing measurements, The Cryosphere, 15, 1259–1276, https://doi.org/10.5194/tc-15-1259-2021, 2021. a
Voordendag, A., Prinz, R., Schuster, L., and Kaser, G.: Brief communication: The Glacier Loss Day as an indicator of a record-breaking negative glacier mass balance in 2022, The Cryosphere, 17, 3661–3665, https://doi.org/10.5194/tc-17-3661-2023, 2023. a
Wester, P., Mishra, A., Mukherji, A., and Shrestha, A. B.: The Hindu Kush Himalaya assessment: mountains, climate change, sustainability and people, Springer Nature, p. 627, https://doi.org/10.1007/978-3-319-92288-1, 2019. a
WGMS: Fluctuations of Glaciers (FoG), release 2023, World Glacier Monitoring Service [data set], https://doi.org/10.18750/massbalance.2023.r2023, 2023. a
Woul, M. D. and Hock, R.: Static mass-balance sensitivity of Arctic glaciers and ice caps using a degree-day approach, Ann. Glaciol., 42, 217–224, https://doi.org/10.3189/172756405781813096, 2005. a
Xu, H., Kinfu, K. A., LeVine, W., Panda, S., Dey, J., Ainsworth, M., Peng, Y. C., Kusmanov, M., Engert, F., White, C. M., and Vogelstein, J. T.: When are deep networks really better than decision forests at small sample sizes, and how?, arXiv [preprint], https://doi.org/10.48550/arXiv.2108.13637, 2021. a
Zekollari, H. and Huybrechts, P.: Statistical modelling of the surface mass-balance variability of the Morteratsch glacier, Switzerland: strong control of early melting season meteorological conditions, J. Glaciol., 64, 275–288, https://doi.org/10.1017/jog.2018.18, 2018. a, b
Zemp, M., Paul, F., Hoelzle, M., and Haeberli, W.: Glacier fluctuations in the European Alps, 1850–2000: an overview and spatio-temporal analysis of available data, in: Darkening Peaks: Glacier Retreat, Science, and Society, edited by: Orlove, B., Wiegandt, E., and Luckman, B. H., Berkeley, US, University of California Press, 152–167, https://doi.org/10.5167/uzh-9024, 2008. a
Short summary
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).
Glacier retreat poses big challenges, making understanding how climate affects glaciers vital....