Articles | Volume 18, issue 8
https://doi.org/10.5194/tc-18-3787-2024
© Author(s) 2024. 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-18-3787-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
23 Aug 2024
Research article |
| 23 Aug 2024
| 23 Aug 2024
Microstructure-based modelling of snow mechanics: experimental evaluation of the cone penetration test
Clémence Herny
CORRESPONDING AUTHOR
Centre d'Etude de la Neige, Univ. Grenoble Alpes, Université de Toulouse, Météo-France, CNRS, CNRM, Grenoble, France
IGE, Univ. Grenoble Alpes, CNRS, INRAE, IRD, Grenoble INP, Grenoble, France
Pascal Hagenmuller
Centre d'Etude de la Neige, Univ. Grenoble Alpes, Université de Toulouse, Météo-France, CNRS, CNRM, Grenoble, France
Guillaume Chambon
IGE, Univ. Grenoble Alpes, CNRS, INRAE, IRD, Grenoble INP, Grenoble, France
Isabel Peinke
Centre d'Etude de la Neige, Univ. Grenoble Alpes, Université de Toulouse, Météo-France, CNRS, CNRM, Grenoble, France
Jacques Roulle
Centre d'Etude de la Neige, Univ. Grenoble Alpes, Université de Toulouse, Météo-France, CNRS, CNRM, Grenoble, France
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Oscar Dick, Neige Calonne, Benoît Laurent, and Pascal Hagenmuller
Earth Syst. Sci. Data, 18, 2875–2889, https://doi.org/10.5194/essd-18-2875-2026, https://doi.org/10.5194/essd-18-2875-2026, 2026
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Snow microstructure undergoes constant shape transformations known as snow metamorphism. Observing first-hand snow metamorphism is key to improving the modelling of these transformations. In this work, we monitor snow microstructure evolution during metamorphism by X-ray tomography. We provide a data set at high spatial and temporal resolution of 3D images of snow microstructure evolving through a wide range of experimental conditions, along with videos showing these transformations.
Mohit Mishra, Gildas Besançon, Guillaume Chambon, and Laurent Baillet
Nat. Hazards Earth Syst. Sci., 26, 1621–1633, https://doi.org/10.5194/nhess-26-1621-2026, https://doi.org/10.5194/nhess-26-1621-2026, 2026
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This work was initiated in the context of a large interdisciplinary research project about Risk at Grenoble University, France. It relates to the challenging topic of landslide monitoring, and combines geotechnical sciences with techniques from control system engineering. Considering a specific modelling approach, the study provides a methodology towards estimation of some landslide parameters and their use in motion prediction. This could then be extended to the design of alert systems.
Simon Filhol, Clément Misset, Noélie Bontemps, Diego Cusicanqui, Emmanuel Paquet, Marie Dumont, Olivier Gagliardini, Pascal Lacroix, Simon Gascoin, Guillaume Thirel, Julien Brondex, Pascal Hagenmuller, Eric Larose, Philipp Schoeneich, Denis Roy, Emmanuel Thibert, Nicolas Eckert, Félix de Montety, Robin Mainieri, Alexandre Hauet, Frédéric Gottardi, Johan Berthet, Alexandre Baratier, Frédéric Liébault, Małgorzata Chmiel, Guillaume Piton, Guillaume Chambon, Guillaume James, Philippe Frey, Philip Deline, Laurent Astrade, Christian Vincent, Dominique Laigle, Alain Recking, Fatima Karbou, Adrien Mauss, Mylène Bonnefoy-Demongeot, Firmin Fontaine, Mickael Langlais, Etienne Berthier, and Antoine Blanc
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This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
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Diego Monteiro, Léo Viallon-Galinier, Kévin Fourteau, Oscar Dick, and Pascal Hagenmuller
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This preprint is open for discussion and under review for The Cryosphere (TC).
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Louis Védrine and Pascal Hagenmuller
The Cryosphere, 20, 1257–1277, https://doi.org/10.5194/tc-20-1257-2026, https://doi.org/10.5194/tc-20-1257-2026, 2026
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Lucie Armand, Guillaume Chambon, Olivier Cerdan, Yannick Thiery, Nathalie Marçot, Louis Ferradou, Nicolas Saby, and Séverine Bernardie
EGUsphere, https://doi.org/10.5194/egusphere-2026-458, https://doi.org/10.5194/egusphere-2026-458, 2026
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François Doussot, Léo Viallon-Galinier, Nicolas Eckert, and Pascal Hagenmuller
EGUsphere, https://doi.org/10.5194/egusphere-2026-336, https://doi.org/10.5194/egusphere-2026-336, 2026
This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
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Avalanches are sensitive to climate warming, but long and reliable records are rare. We combined avalanche observations with weather and snow simulations in the Haute-Maurienne valley (French Alps). This allowed us to reconstruct past avalanche activity and explore future changes. The results show a strong long-term decline in avalanche occurrence, especially in spring, while extreme events decrease more slowly. This study provides quantitative insights to support mountain risk management.
Anna Wirbel, Felix Oesterle, Guillaume Chambon, Thierry Faug, Johan Gaume, Julia Glaus, Stefan Hergarten, Dieter Issler, Yoichi Ito, Marco Martini, Martin Mergili, Matthias Rauter, Jörg Robl, Giorgio Rosatti, Kae Tsunematsu, Christian Tollinger, Hervé Vicari, Daniel Zugliani, and Jan-Thomas Fischer
EGUsphere, https://doi.org/10.5194/egusphere-2025-6053, https://doi.org/10.5194/egusphere-2025-6053, 2026
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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We present the first extended intercomparison of snow avalanche flow simulation tools. In this pilot-study, simulation results of mainly thickness/depth-integrated shallow flow models are compared for three simple test cases representative of standard applications. This analysis serves as a first quantitative assessment of the uncertainty introduced by the different implementation workflows (e.g., numerical schemes, ad-hoc treatments, geo-data handling, curvature treatment, etc.).
Matthieu Lafaysse, Marie Dumont, Basile De Fleurian, Mathieu Fructus, Rafife Nheili, Léo Viallon-Galinier, Matthieu Baron, Aaron Boone, Axel Bouchet, Julien Brondex, Carlo Carmagnola, Bertrand Cluzet, Kévin Fourteau, Ange Haddjeri, Pascal Hagenmuller, Giulia Mazzotti, Marie Minvielle, Samuel Morin, Louis Quéno, Léon Roussel, Pierre Spandre, François Tuzet, and Vincent Vionnet
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This article is a comprehensive description of the 3.0 stable release of the Crocus snowpack model. It describes various new implementations since the last reference article in 2012 and a review of the available scientific evaluations and applications of the model. This provides guidance for the future of numerical snow modelling.
Suzanne Lapillonne, Georgios Fourtakas, Vincent Richefeu, Guillaume Piton, and Guillaume Chambon
Geosci. Model Dev., 18, 7059–7075, https://doi.org/10.5194/gmd-18-7059-2025, https://doi.org/10.5194/gmd-18-7059-2025, 2025
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Debris flows are fast-flowing events that are saturated with granular material. They naturally occur in steep creeks and are a threat to local communities. Scientists have turned to numerical models to better understand how they behave. We investigate the accuracy of a numerical model that relies on modelling the debris flow as a mixture of a granular phase and a fluid phase. We focus on a demonstration of the capacity of the model to reliably represent the behaviour of the flow at different scales.
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Preprint withdrawn
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This paper considers how we can objectivity define stoppage of numerically-modelled snow avalanches. When modelling real topographies, numerically-modelled avalanche snow velocities typically do not converge to 0, so stoppage is defined with arbitrary criteria, which must be tuned on a case-by-case basis. We propose a new objective arrest criterion based on local flow properties, in tandem with a newly-implemented physical yielding criterion.
Julien Brondex, Kévin Fourteau, Marie Dumont, Pascal Hagenmuller, Neige Calonne, François Tuzet, and Henning Löwe
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Vapor diffusion is one of the main processes governing snowpack evolution, and it must be accounted for in models. Recent attempts to represent vapor diffusion in numerical models have faced several difficulties regarding computational cost and mass and energy conservation. Here, we develop our own finite-element software to explore numerical approaches and enable us to overcome these difficulties. We illustrate the capability of these approaches on established numerical benchmarks.
Marie Dumont, Simon Gascoin, Marion Réveillet, Didier Voisin, François Tuzet, Laurent Arnaud, Mylène Bonnefoy, Montse Bacardit Peñarroya, Carlo Carmagnola, Alexandre Deguine, Aurélie Diacre, Lukas Dürr, Olivier Evrard, Firmin Fontaine, Amaury Frankl, Mathieu Fructus, Laure Gandois, Isabelle Gouttevin, Abdelfateh Gherab, Pascal Hagenmuller, Sophia Hansson, Hervé Herbin, Béatrice Josse, Bruno Jourdain, Irene Lefevre, Gaël Le Roux, Quentin Libois, Lucie Liger, Samuel Morin, Denis Petitprez, Alvaro Robledano, Martin Schneebeli, Pascal Salze, Delphine Six, Emmanuel Thibert, Jürg Trachsel, Matthieu Vernay, Léo Viallon-Galinier, and Céline Voiron
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Saharan dust outbreaks have profound effects on ecosystems, climate, health, and the cryosphere, but the spatial deposition pattern of Saharan dust is poorly known. Following the extreme dust deposition event of February 2021 across Europe, a citizen science campaign was launched to sample dust on snow over the Pyrenees and the European Alps. This campaign triggered wide interest and over 100 samples. The samples revealed the high variability of the dust properties within a single event.
Léo Viallon-Galinier, Pascal Hagenmuller, and Nicolas Eckert
The Cryosphere, 17, 2245–2260, https://doi.org/10.5194/tc-17-2245-2023, https://doi.org/10.5194/tc-17-2245-2023, 2023
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Avalanches are a significant issue in mountain areas where they threaten recreationists and human infrastructure. Assessments of avalanche hazards and the related risks are therefore an important challenge for local authorities. Meteorological and snow cover simulations are thus important to support operational forecasting. In this study we combine it with mechanical analysis of snow profiles and find that observed avalanche data improve avalanche activity prediction through statistical methods.
Oscar Dick, Léo Viallon-Galinier, François Tuzet, Pascal Hagenmuller, Mathieu Fructus, Benjamin Reuter, Matthieu Lafaysse, and Marie Dumont
The Cryosphere, 17, 1755–1773, https://doi.org/10.5194/tc-17-1755-2023, https://doi.org/10.5194/tc-17-1755-2023, 2023
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Saharan dust deposition can drastically change the snow color, turning mountain landscapes into sepia scenes. Dust increases the absorption of solar energy by the snow cover and thus modifies the snow evolution and potentially the avalanche risk. Here we show that dust can lead to increased or decreased snowpack stability depending on the snow and meteorological conditions after the deposition event. We also show that wet-snow avalanches happen earlier in the season due to the presence of dust.
Pyei Phyo Lin, Isabel Peinke, Pascal Hagenmuller, Matthias Wächter, M. Reza Rahimi Tabar, and Joachim Peinke
The Cryosphere, 16, 4811–4822, https://doi.org/10.5194/tc-16-4811-2022, https://doi.org/10.5194/tc-16-4811-2022, 2022
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Characterization of layers of snowpack with highly resolved micro-cone penetration tests leads to detailed fluctuating signals. We used advanced stochastic analysis to differentiate snow types by interpreting the signals as a mixture of continuous and discontinuous random fluctuations. These two types of fluctuation seem to correspond to different mechanisms of drag force generation during the experiments. The proposed methodology provides new insights into the characterization of snow layers.
Matthieu Vernay, Matthieu Lafaysse, Diego Monteiro, Pascal Hagenmuller, Rafife Nheili, Raphaëlle Samacoïts, Deborah Verfaillie, and Samuel Morin
Earth Syst. Sci. Data, 14, 1707–1733, https://doi.org/10.5194/essd-14-1707-2022, https://doi.org/10.5194/essd-14-1707-2022, 2022
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This paper introduces the latest version of the freely available S2M dataset which provides estimates of both meteorological and snow cover variables, as well as various avalanche hazard diagnostics at different elevations, slopes and aspects for the three main French high-elevation mountainous regions. A complete description of the system and the dataset is provided, as well as an overview of the possible uses of this dataset and an objective assessment of its limitations.
Marie Dumont, Frederic Flin, Aleksey Malinka, Olivier Brissaud, Pascal Hagenmuller, Philippe Lapalus, Bernard Lesaffre, Anne Dufour, Neige Calonne, Sabine Rolland du Roscoat, and Edward Ando
The Cryosphere, 15, 3921–3948, https://doi.org/10.5194/tc-15-3921-2021, https://doi.org/10.5194/tc-15-3921-2021, 2021
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The role of snow microstructure in snow optical properties is only partially understood despite the importance of snow optical properties for the Earth system. We present a dataset combining bidirectional reflectance measurements and 3D images of snow. We show that the snow reflectance is adequately simulated using the distribution of the ice chord lengths in the snow microstructure and that the impact of the morphological type of snow is especially important when ice is highly absorptive.
Kévin Fourteau, Florent Domine, and Pascal Hagenmuller
The Cryosphere, 15, 2739–2755, https://doi.org/10.5194/tc-15-2739-2021, https://doi.org/10.5194/tc-15-2739-2021, 2021
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The thermal conductivity of snow is an important physical property governing the thermal regime of a snowpack and its substrate. We show that it strongly depends on the kinetics of water vapor sublimation and that previous experimental data suggest a rather fast kinetics. In such a case, neglecting water vapor leads to an underestimation of thermal conductivity by up to 50 % for light snow. Moreover, the diffusivity of water vapor in snow is then directly related to the thermal conductivity.
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Short summary
This paper presents the evaluation of a numerical discrete element method (DEM) by simulating cone penetration tests in different snow samples. The DEM model demonstrated a good ability to reproduce the measured mechanical behaviour of the snow, namely the force evolution on the cone and the grain displacement field. Systematic sensitivity tests showed that the mechanical response depends not only on the microstructure of the sample but also on the mechanical parameters of grain contacts.
This paper presents the evaluation of a numerical discrete element method (DEM) by simulating...
