Articles | Volume 20, issue 10
https://doi.org/10.5194/tc-20-5813-2026
© 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-20-5813-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
12 Oct 2026
Research article |
| 12 Oct 2026
| 12 Oct 2026
Temperature sensitivity of snow viscoplasticity: Evidence from controlled creep experiments
Météo-France, CNRS, Centre d’Études de la Neige, 38000 Grenoble, France.
Université Grenoble Alpes, 38000 Grenoble, France
Université de Toulouse, Toulouse 31000, France
Marius Brun
Météo-France, CNRS, Centre d’Études de la Neige, 38000 Grenoble, France.
Université Grenoble Alpes, 38000 Grenoble, France
Université de Toulouse, Toulouse 31000, France
Department of Physics, École Normale Supérieure de Lyon, 69364, Lyon, France
Mathis Bozon
Météo-France, CNRS, Centre d’Études de la Neige, 38000 Grenoble, France.
Université Grenoble Alpes, 38000 Grenoble, France
Université de Toulouse, Toulouse 31000, France
Benoit Laurent
Météo-France, CNRS, Centre d’Études de la Neige, 38000 Grenoble, France.
Université Grenoble Alpes, 38000 Grenoble, France
Université de Toulouse, Toulouse 31000, France
Pascal Hagenmuller
Météo-France, CNRS, Centre d’Études de la Neige, 38000 Grenoble, France.
Université Grenoble Alpes, 38000 Grenoble, France
Université de Toulouse, Toulouse 31000, France
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Cited articles
Bader, H.: Der Schnee und seine Metamorphose, vol. 3, Kommissionsverlag Kummerly & Frey, Druck von Aschmann & Scheller AG, Zurich, 1939. a
Barnett, T. P., Pierce, D. W., Hidalgo, H. G., Bonfils, C., Santer, B. D., Das, T., Bala, G., Wood, A. W., Nozawa, T., Mirin, A. A., Cayan, D. R., and Dettinger, M. D.: Human-Induced Changes in the Hydrology of the Western United States, Science, 319, 1080–1083, https://doi.org/10.1126/science.1152538, 2008. a
Barnola, J. M., Raynaud, D., Korotkevich, Y. S., and Lorius, C.: Vostok ice core provides 160 000-year record of atmospheric CO2, Nature, 329, 408–414, https://doi.org/10.1038/329408a0, 1987. a
Brun, E., David, P., Sudul, M., and Brunot, G.: A numerical model to simulate snow-cover stratigraphy for operational avalanche forecasting, J. Glaciol., 38, 13–22, https://doi.org/10.3189/S0022143000009552, 1992. a, b, c, d
Bucher, E.: Beitrag zu den theoretischen Grundlagen des Lawinenverbaus, PhD thesis, ETH Zürich, https://doi.org/10.3929/ethz-a-000103484, 1948. a
Budd, W. F. and Jacka, T. H.: A review of ice rheology for ice sheet modelling, Cold Reg. Sci. Technol., 16, 107–144, https://doi.org/10.1016/0165-232X(89)90014-1, 1989. a
DeBeer, C. M. and Pomeroy, J. W.: Influence of snowpack and melt energy heterogeneity on snow cover depletion and snowmelt runoff simulation in a cold mountain environment, J. Hydrol., 553, 199–213, https://doi.org/10.1016/j.jhydrol.2017.07.051, 2017. a
Delmas, L.: Influence of snow type and temperature on snow viscosity, J. Glaciol., 59, 87–92, https://doi.org/10.3189/2013JoG11J231, 2013. a, b, c, d
Dick, O., Calonne, N., Laurent, B., and Hagenmuller, P.: Monitoring dry snow metamorphism using 4D tomography across 20 experimental conditions, Earth Syst. Sci. Data, 18, 2875–2889, https://doi.org/10.5194/essd-18-2875-2026, 2026. a
Hagenmuller, P., Chambon, G., Lesaffre, B., Flin, F., and Naaim, M.: Energy-based binary segmentation of snow microtomographic images, J. Glaciol., 59, 859–873, https://doi.org/10.3189/2013JoG13J035, 2013. a
Hagenmuller, P., Matzl, M., Chambon, G., and Schneebeli, M.: Sensitivity of snow density and specific surface area measured by microtomography to different image processing algorithms, The Cryosphere, 10, 1039–1054, https://doi.org/10.5194/tc-10-1039-2016, 2016. a
Horlings, B. I., Courville, Z., Murdza, A., and Keegan, K. M.: Applicability of two-phase modeling with compression experiments for snow compaction dynamics, Cold Reg. Sci. Technol., 229, 104336, https://doi.org/10.1016/j.coldregions.2024.104336, 2025. a
Jacka, T. H. and Maccagnan, M.: Ice crystallographic and strain rate changes with strain in compression and extension, Cold Reg. Sci. Technol., 8, 269–286, https://doi.org/10.1016/0165-232X(84)90058-2, 1984. a, b
Kojima, K.: A field experiment on the rate of densification of natural snow layers under low stresses, in: Snow Mechanics Symposium, International Conference on Low Temperature Science, I. Conference on Physics of Snow and Ice, II. Conference on Cryobiology, 14–19 August 1966, Sapporo, Japan, https://cir.nii.ac.jp/crid/1570854175146603264 (last access: 13 September 2026), 1975. a, b, c
Lehning, M., Bartelt, P., Brown, B., Fierz, C., and Satyawali, P.: A physical SNOWPACK model for the Swiss avalanche warning: Part II. Snow microstructure, Cold Reg. Sci. Technol., 35, 147–167, https://doi.org/10.1016/S0165-232X(02)00073-3, 2002. a, b
Lejeune, Y., Dumont, M., Panel, J.-M., Lafaysse, M., Lapalus, P., Le Gac, E., Lesaffre, B., and Morin, S.: 57 years (1960–2017) of snow and meteorological observations from a mid-altitude mountain site (Col de Porte, France, 1325 m of altitude), Earth Syst. Sci. Data, 11, 71–88, https://doi.org/10.5194/essd-11-71-2019, 2019. a
Li, Y., Keegan, K., and Baker, I.: Observations of creep of polar firn at different temperatures, The Cryosphere, 20, 981–1000, https://doi.org/10.5194/tc-20-981-2026, 2026. a, b, c, d
Mellor, M. and Smith, J. H.: Strength studies of snow, 168, US Army Materiel Command, Cold Regions Research & Engineering Laboratory, https://books.google.fr/books?hl=fr&lr=&id=lTsMi8AP41gC&oi=fnd&pg=PR4&dq=strength+studies+of+snow+mellor&ots=t_dg-csgQw&sig=OXLUv79KJUoYW5Wce76AXTDSKNc (last access: 8 October 2026), 1966. a
Mellor, M. and Testa, R.: Creep of Ice under Low Stress, J. Glaciol., 8, 147–152, https://doi.org/10.3189/S0022143000020815, 1969a. a, b
Mellor, M. and Testa, R.: Effect of Temperature on the Creep of Ice, J. Glaciol., 8, 131–145, https://doi.org/10.3189/S0022143000020803, 1969b. a, b
Meyssonnier, J., Philip, A., Capolo, L., and Mansuy, P.: Experimental studies of the viscoplasticty of ice and snow, in: Mechanics of Natural Solids, edited by: Kolymbas, D. and Viggiani, G., Springer, Berlin, Heidelberg, 203–221, https://doi.org/10.1007/978-3-642-03578-4_9, 2009. a
Morgan, V. I.: High-temperature ice creep tests, Cold Reg. Sci. Technol., 19, 295–300, https://doi.org/10.1016/0165-232X(91)90044-H, 1991. a, b
Morin, S., Horton, S., Techel, F., Bavay, M., Coléou, C., Fierz, C., Gobiet, A., Hagenmuller, P., Lafaysse, M., Ližar, M., Mitterer, C., Monti, F., Müller, K., Olefs, M., Snook, J. S., van Herwijnen, A., and Vionnet, V.: Application of physical snowpack models in support of operational avalanche hazard forecasting: A status report on current implementations and prospects for the future, Cold Reg. Sci. Technol., 170, 102910, https://doi.org/10.1016/j.coldregions.2019.102910, 2020. a
Morris, E. M. and Wingham, D. J.: Densification of polar snow: Measurements, modeling, and implications for altimetry, J. Geophys. Res.-Earth, 119, 349–365, https://doi.org/10.1002/2013JF002898, 2014. a
Okada, Y., Hondoh, T., and Mae, S.: Basal glide of dislocations in ice observed by synchrotron radiation topography, Philos. Mag. A, 79, 2853–2868, https://doi.org/10.1080/01418619908212028, 1999. a
Quéno, L., Vionnet, V., Dombrowski-Etchevers, I., Lafaysse, M., Dumont, M., and Karbou, F.: Snowpack modelling in the Pyrenees driven by kilometric-resolution meteorological forecasts, The Cryosphere, 10, 1571–1589, https://doi.org/10.5194/tc-10-1571-2016, 2016. a
Ramseier, R. O.: Growth and mechanical properties of river and lake ice, PhD Thesis, éditeur non identifié, l'Université Laval (Québec, Canada), 1975. a
Schleef, S., Löwe, H., and Schneebeli, M.: Hot-pressure sintering of low-density snow analyzed by X-ray microtomography and in situ microcompression, Acta Mater., 71, 185–194, https://doi.org/10.1016/j.actamat.2014.03.004, 2014a. a, b
Schleef, S., Löwe, H., and Schneebeli, M.: Influence of stress, temperature and crystal morphology on isothermal densification and specific surface area decrease of new snow, The Cryosphere, 8, 1825–1838, https://doi.org/10.5194/tc-8-1825-2014, 2014b. a, b, c, d
Simson, A., Löwe, H., and Kowalski, J.: Elements of future snowpack modeling – Part 2: A modular and extendable Eulerian–Lagrangian numerical scheme for coupled transport, phase changes and settling processes, The Cryosphere, 15, 5423–5445, https://doi.org/10.5194/tc-15-5423-2021, 2021. a
Spitzig, W. A. and Keh, A. S.: Orientation dependence of the strain-rate sensitivity and thermally activated flow in iron single crystals, Acta Metall. Mater, 18, 1021–1033, https://doi.org/10.1016/0001-6160(70)90058-1, 1970. a
Stamati, O., Andò, E., Roubin, E., Cailletaud, R., Wiebicke, M., Pinzon, G., Couture, C., Hurley, R., Caulk, R., Caillerie, D., Matsushima, T., Bésuelle, P., Bertoni, F., Arnaud, T., Laborin, A., Rorato, R., Sun, Y., Tengattini, A., Okubadejo, O., Colliat, J.-B., Saadatfar, M., Garcia, F., Papazoglou, C., Vego, I., Brisard, S., Dijkstra, J., and Birmpilis, G.: spam: Software for Practical Analysis of Materials, Journal of Open Source Software, 5, 2286, https://doi.org/10.21105/joss.02286, 2020. a
Steinemann, S.: Results of Preliminary Experiments on the Plasticity of Ice Crystals, J. Glaciol., 2, 404–416, https://doi.org/10.3189/002214354793702533, 1954. a, b
Vionnet, V., Brun, E., Morin, S., Boone, A., Faroux, S., Le Moigne, P., Martin, E., and Willemet, J.-M.: The detailed snowpack scheme Crocus and its implementation in SURFEX v7.2, Geosci. Model Dev., 5, 773–791, https://doi.org/10.5194/gmd-5-773-2012, 2012. a
Védrine, L., Hagenmuller, P., Gélébart, L., Montagnat, M., and Bernard, A.: Role of Ice Mechanics on Snow Viscoplasticity, Geophys. Res. Lett., 51, e2023GL107676, https://doi.org/10.1029/2023GL107676, 2024. a, b, c
Védrine, L., Hagenmuller, P., Gélébart, L., Montagnat, M., and Löwe, H.: Sensitivity of the viscoplasticity of polycrystals to porosity and pore-to-crystal size ratio, Acta Mater., 301, 121507, https://doi.org/10.1016/j.actamat.2025.121507, 2025. a
Védrine, L., Brun, M., Bozon, M., Laurent, B., and Hagenmuller, P.: Dataset for: Sensitivity of snow viscoplasticity to temperature: evidence from controlled creep experiments, Zenodo [data set and video], https://doi.org/10.5281/zenodo.18824419, 2026. a, b
Wiese, M. and Schneebeli, M.: Snowbreeder 5: a Micro-CT device for measuring the snow-microstructure evolution under the simultaneous influence of a temperature gradient and compaction, J. Glaciol., 63, 355–360, https://doi.org/10.1017/jog.2016.143, 2017. a
Wollgramm, P., Bürger, D., Parsa, A. B., Neuking, K., and Eggeler, G.: The effect of stress, temperature and loading direction on the creep behaviour of Ni-base single crystal superalloy miniature tensile specimens, Mater. High Temp., 33, 346–360, https://doi.org/10.1080/09603409.2016.1186414, 2016. a
Short summary
Snow slowly compacts under its own weight, and this process depends strongly on temperature, but past estimates vary widely. We developed a device to precisely control temperature and tested the same snow sample under different conditions. We found two distinct temperature regimes and a stronger sensitivity than assumed in existing snowpack models, improving how snow compaction is represented.
Snow slowly compacts under its own weight, and this process depends strongly on temperature, but...
