Articles | Volume 20, issue 5
https://doi.org/10.5194/tc-20-3111-2026
© Author(s) 2026. 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-20-3111-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
28 May 2026
Research article |
| 28 May 2026
| 28 May 2026
Seasonal mass balance drivers for Swiss glaciers over 2010–2024 inferred from remote-sensing observations and modelling
Aaron Cremona
CORRESPONDING AUTHOR
Laboratory of Hydraulics, Hydrology and Glaciology (VAW), ETH Zurich, Zurich, Switzerland
Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), bâtiment ALPOLE, Sion, Switzerland
Matthias Huss
Laboratory of Hydraulics, Hydrology and Glaciology (VAW), ETH Zurich, Zurich, Switzerland
Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), bâtiment ALPOLE, Sion, Switzerland
Department of Geosciences, University of Fribourg, Fribourg, Switzerland
Johannes Marian Landmann
Federal Office of Meteorology and Climatology MeteoSwiss, Zurich-Airport, Switzerland
Mauro Marty
Swiss Federal Institute for Forest, Snow, and Landscape Research (WSL), Birmensdorf, Switzerland
Marijn van der Meer
Laboratory of Hydraulics, Hydrology and Glaciology (VAW), ETH Zurich, Zurich, Switzerland
Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), bâtiment ALPOLE, Sion, Switzerland
Christian Ginzler
Swiss Federal Institute for Forest, Snow, and Landscape Research (WSL), Birmensdorf, Switzerland
Daniel Farinotti
Laboratory of Hydraulics, Hydrology and Glaciology (VAW), ETH Zurich, Zurich, Switzerland
Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), bâtiment ALPOLE, Sion, Switzerland
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Manuscript not accepted for further review
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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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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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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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Robert Pazúr, Nica Huber, Dominique Weber, Christian Ginzler, and Bronwyn Price
Earth Syst. Sci. Data, 14, 295–305, https://doi.org/10.5194/essd-14-295-2022, https://doi.org/10.5194/essd-14-295-2022, 2022
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We mapped the distribution of cropland and permanent grassland across Switzerland, where the agricultural land is considerably spatially heterogeneous due to strong variability in topography and climate, thus presenting challenges to mapping. The resulting map has high accuracy in lowlands as well as in mountainous areas. Thus, we believe that the presented mapping approach and resulting map will provide a solid ground for further research in agricultural land cover and landscape structure.
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.
Cited articles
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Cremona, A., Huss, M., Landmann, J. M., Borner, J., and Farinotti, D.: European heat waves 2022: contribution to extreme glacier melt in Switzerland inferred from automated ablation readings, The Cryosphere, 17, 1895–1912, https://doi.org/10.5194/tc-17-1895-2023, 2023. a, b, c
Cremona, A., Huss, M., Landmann, J. M., Marty, M., van der Meer, M., Ginzler, C., and Farinotti, D.: Seasonal mass balance drivers for Swiss glaciers over 2010–2024 inferred from remote-sensing observations and modelling, Version v1, Zenodo [code/data set], https://doi.org/10.5281/zenodo.19624839, 2026. a
Denzinger, F., Machguth, H., Barandun, M., Berthier, E., Girod, L., Kronenberg, M., Usubaliev, R., and Hoelzle, M.: Geodetic mass balance of Abramov Glacier from 1975 to 2015, J. Glaciol., 67, 331–342, https://doi.org/10.1017/jog.2020.108, 2021. a
de Roda Husman, S., Lhermitte, S., Bolibar, J., Izeboud, M., Hu, Z., Shukla, S., van der Meer, M., Long, D., and Wouters, B.: A high-resolution record of surface melt on Antarctic ice shelves using multi-source remote sensing data and deep learning, Remote Sens. Environ., 301, 113950, https://doi.org/10.1016/j.rse.2023.113950, 2024. a
Draeger, C., Radić, V., White, R. H., and Tessema, M. A.: Evaluation of reanalysis data and dynamical downscaling for surface energy balance modeling at mountain glaciers in western Canada, The Cryosphere, 18, 17–42, https://doi.org/10.5194/tc-18-17-2024, 2024. a
Dumont, M., Monteiro, D., Filhol, S., Gascoin, S., Marty, C., Hagenmuller, P., Morin, S., Choler, P., and Thuiller, W.: The European Alps in a changing climate: physical trends and impacts, C.R. Géosci., 357, 25–42, https://doi.org/10.5802/crgeos.288, 2025. a
Dussaillant, I., Berthier, E., and Brun, F.: Geodetic mass balance of the Northern Patagonian Icefield from 2000 to 2012 using two independent methods, Front. Earth Sci., 6, 8, https://doi.org/10.3389/feart.2018.00008, 2018. a
Dussaillant, I., Hugonnet, R., Huss, M., Berthier, E., Bannwart, J., Paul, F., and Zemp, M.: Annual mass change of the world's glaciers from 1976 to 2024 by temporal downscaling of satellite data with in situ observations, Earth Syst. Sci. Data, 17, 1977–2006, https://doi.org/10.5194/essd-17-1977-2025, 2025. a, b
Elsberg, D., Harrison, W., Echelmeyer, K., and Krimmel, R.: Quantifying the effects of climate and surface change on glacier mass balance, J. Glaciol., 47, 649–658, https://doi.org/10.3189/172756501781831783, 2001. a
Farinotti, D., Usselmann, S., Huss, M., Bauder, A., and Funk, M.: Runoff evolution in the Swiss Alps: projections for selected high-alpine catchments based on ENSEMBLES scenarios, Hydrol. Process., 26, 1909–1924, https://doi.org/10.1002/hyp.8276, 2012. a
Farinotti, D., Pistocchi, A., and Huss, M.: From dwindling ice to headwater lakes: could dams replace glaciers in the European Alps?, Environ. Res. Lett., 11, 054022, https://doi.org/10.1088/1748-9326/11/5/054022, 2016. a
Finger, D., Pellicciotti, F., Konz, M., Rimkus, S., and Burlando, P.: The value of glacier mass balance, satellite snow cover images, and hourly discharge for improving the performance of a physically based distributed hydrological model, Water Resour. Res., 47, https://doi.org/10.1029/2010WR009824, 2011. a
Fischer, M., Huss, M., and Hoelzle, M.: Surface elevation and mass changes of all Swiss glaciers 1980–2010, The Cryosphere, 9, 525–540, https://doi.org/10.5194/tc-9-525-2015, 2015. a, b, c
Freudiger, D., Kohn, I., Seibert, J., Stahl, K., and Weiler, M.: Snow redistribution for the hydrological modeling of alpine catchments, WIRES Water, 4, e1232, https://doi.org/10.1002/wat2.1232, 2017. a
Gabbi, J., Carenzo, M., Pellicciotti, F., Bauder, A., and Funk, M.: A comparison of empirical and physically based glacier surface melt models for long-term simulations of glacier response, J. Glaciol., 60, 1140–1154, https://doi.org/10.3189/2014JoG14J011, 2014. a
Gabbi, J., Huss, M., Bauder, A., Cao, F., and Schwikowski, M.: The impact of Saharan dust and black carbon on albedo and long-term mass balance of an Alpine glacier, The Cryosphere, 9, 1385–1400, https://doi.org/10.5194/tc-9-1385-2015, 2015. a
Ginzler, C. and Hobi, M. L.: Countrywide stereo-image matching for updating digital surface models in the framework of the Swiss National Forest Inventory, Remote Sens.-Basel, 7, 4343–4370, https://doi.org/10.3390/rs70404343, 2015. a
GLAMOS: Swiss Glacier Mass Balance, release 2024, Glacier Monitoring Switzerland [data set], https://doi.org/10.18750/massbalance.2024.r2024, 2024a. a, b, c
GLAMOS: Swiss Glacier Point Mass Balance Observations, release 2024, Glacier Monitoring Switzerland [data set], https://doi.org/10.18750/massbalance.point.2024.r2024, 2024b. a, b
GLAMOS: Swiss Glacier Volume Change, release 2024, Glacier Monitoring Switzerland [data set], https://doi.org/10.18750/volumechange.2024.r2024, 2024d. a, b, c
Grab, M., Mattea, E., Bauder, A., Huss, M., Rabenstein, L., Hodel, E., Linsbauer, A., Langhammer, L., Schmid, L., Church, G., Hellmann, S., Délèze, K., Schaer, P., Lathion, P., Farinotti, D., and Maurer, H.: Ice thickness distribution of all Swiss glaciers based on extended ground-penetrating radar data and glaciological modeling, J. Glaciol., 67, 1074–1092, https://doi.org/10.1017/jog.2021.55, 2021. a
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Hock, R., Jansson, P., and Braun, L. N.: Modelling the Response of Mountain Glacier Discharge to Climate Warming, Springer Netherlands, Dordrecht, https://doi.org/10.1007/1-4020-3508-X_25, 243–252, 2005. a
Hock, R., Kootstra, D.-S., and Reijmer, C.: Deriving glacier mass balance from accumulation area ratio on Storglaciären, Sweden, in: Glacier mass balance changes and meltwater discharge, edited by: Ginot, P. and Sicart, J. E., IAHS Press, Wallingford, United Kingdom, 163–170, ISBN 978-1-901502-39-8, 2007. a
Hock, R., Bliss, A., Marzeion, B., Giesen, R. H., Hirabayashi, Y., Huss, M., Radić, V., and Slangen, A. B.: GlacierMIP–A model intercomparison of global-scale glacier mass-balance models and projections, J. Glaciol., 65, 453–467, https://doi.org/10.1017/jog.2019.22, 2019. a
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Hugonnet, R., McNabb, R., Berthier, E., Menounos, B., Nuth, C., Girod, L., Farinotti, D., Huss, M., Dussaillant, I., Brun, F., and Kääb, A.: Accelerated global glacier mass loss in the early twenty-first century, Nature, 592, 726–731, https://doi.org/10.1038/s41586-021-03436-z, 2021. a, b, c
Hulth, J., Denby, C. R., and Hock, R.: Estimating glacier snow accumulation from backward calculation of melt and snowline tracking, Ann. Glaciol., 54, 1–7, https://doi.org/10.3189/2013AoG62A083, 2013. a
Huss, M.: Density assumptions for converting geodetic glacier volume change to mass change, The Cryosphere, 7, 877–887, https://doi.org/10.5194/tc-7-877-2013, 2013. a, b
Huss, M. and Hock, R.: Global-scale hydrological response to future glacier mass loss, Nat. Clim. Change, 8, 135–140, https://doi.org/10.1038/s41558-017-0049-x, 2018. a
Huss, M., Bauder, A., Funk, M., and Hock, R.: Determination of the seasonal mass balance of four Alpine glaciers since 1865, J. Geophys. Res.-Earth, 113, https://doi.org/10.1029/2007JF000803, 2008. a, b
Huss, M., Hock, R., Bauder, A., and Funk, M.: Conventional versus reference-surface mass balance, J. Glaciol., 58, 278–286, https://doi.org/10.3189/2012JoG11J216, 2012. a
Huss, M., Sold, L., Hoelzle, M., Stokvis, M., Salzmann, N., Farinotti, D., and Zemp, M.: Towards remote monitoring of sub-seasonal glacier mass balance, Ann. Glaciol., 54, 75–83, https://doi.org/10.3189/2013AoG63A427, 2013. 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
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Landmann, J. M., Künsch, H. R., Huss, M., Ogier, C., Kalisch, M., and Farinotti, D.: Assimilating near-real-time mass balance stake readings into a model ensemble using a particle filter, The Cryosphere, 15, 5017–5040, https://doi.org/10.5194/tc-15-5017-2021, 2021. a, b
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Menounos, B., Huss, M., Marshall, S., Ednie, M., Florentine, C., and Hartl, L.: Glaciers in Western Canada-conterminous US and Switzerland experience unprecedented mass loss over the last four years (2021–2024), Geophys. Res. Lett., 52, e2025GL115235, https://doi.org/10.1029/2025GL115235, 2025. a, b
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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.
Our study provides daily mass balance estimates for every Swiss glacier from 2010–2024 using...
