Articles | Volume 23, issue 11
https://doi.org/10.5194/nhess-23-3445-2023
https://doi.org/10.5194/nhess-23-3445-2023
Research article
 | 
09 Nov 2023
Research article |  | 09 Nov 2023

Prediction of natural dry-snow avalanche activity using physics-based snowpack simulations

Stephanie Mayer, Frank Techel, Jürg Schweizer, and Alec van Herwijnen

Related authors

Changes in snow avalanche activity in response to climate warming in the Swiss Alps
Stephanie Mayer, Martin Hendrick, Adrien Michel, Bettina Richter, Jürg Schweizer, Heini Wernli, and Alec van Herwijnen
EGUsphere, https://doi.org/10.5194/egusphere-2024-1026,https://doi.org/10.5194/egusphere-2024-1026, 2024
Short summary
A random forest model to assess snow instability from simulated snow stratigraphy
Stephanie Mayer, Alec van Herwijnen, Frank Techel, and Jürg Schweizer
The Cryosphere, 16, 4593–4615, https://doi.org/10.5194/tc-16-4593-2022,https://doi.org/10.5194/tc-16-4593-2022, 2022
Short summary
On the correlation between a sub-level qualifier refining the danger level with observations and models relating to the contributing factors of avalanche danger
Frank Techel, Stephanie Mayer, Cristina Pérez-Guillén, Günter Schmudlach, and Kurt Winkler
Nat. Hazards Earth Syst. Sci., 22, 1911–1930, https://doi.org/10.5194/nhess-22-1911-2022,https://doi.org/10.5194/nhess-22-1911-2022, 2022
Short summary
Effect of snowfall on changes in relative seismic velocity measured by ambient noise correlation
Antoine Guillemot, Alec van Herwijnen, Eric Larose, Stephanie Mayer, and Laurent Baillet
The Cryosphere, 15, 5805–5817, https://doi.org/10.5194/tc-15-5805-2021,https://doi.org/10.5194/tc-15-5805-2021, 2021
Short summary

Related subject area

Other Hazards (e.g., Glacial and Snow Hazards, Karst, Wildfires Hazards, and Medical Geo-Hazards)
Modelling the vulnerability of urban settings to wildland–urban interface fires in Chile
Paula Aguirre, Jorge León, Constanza González-Mathiesen, Randy Román, Manuela Penas, and Alonso Ogueda
Nat. Hazards Earth Syst. Sci., 24, 1521–1537, https://doi.org/10.5194/nhess-24-1521-2024,https://doi.org/10.5194/nhess-24-1521-2024, 2024
Short summary
Modeling of indoor 222Rn in data-scarce regions: an interactive dashboard approach for Bogotá, Colombia
Martín Domínguez Durán, María Angélica Sandoval Garzón, and Carme Huguet
Nat. Hazards Earth Syst. Sci., 24, 1319–1339, https://doi.org/10.5194/nhess-24-1319-2024,https://doi.org/10.5194/nhess-24-1319-2024, 2024
Short summary
A regional early warning for slushflow hazard
Monica Sund, Heidi A. Grønsten, and Siv Å. Seljesæter
Nat. Hazards Earth Syst. Sci., 24, 1185–1201, https://doi.org/10.5194/nhess-24-1185-2024,https://doi.org/10.5194/nhess-24-1185-2024, 2024
Short summary
A new approach for drought index adjustment to clay-shrinkage-induced subsidence over France: advantages of the interactive leaf area index
Sophie Barthelemy, Bertrand Bonan, Jean-Christophe Calvet, Gilles Grandjean, David Moncoulon, Dorothée Kapsambelis, and Séverine Bernardie
Nat. Hazards Earth Syst. Sci., 24, 999–1016, https://doi.org/10.5194/nhess-24-999-2024,https://doi.org/10.5194/nhess-24-999-2024, 2024
Short summary
Automated Avalanche Terrain Exposure Scale (ATES) mapping – local validation and optimization in western Canada
John Sykes, Håvard Toft, Pascal Haegeli, and Grant Statham
Nat. Hazards Earth Syst. Sci., 24, 947–971, https://doi.org/10.5194/nhess-24-947-2024,https://doi.org/10.5194/nhess-24-947-2024, 2024
Short summary

Cited articles

Ancey, C., Gervasoni, C., and Meunier, M.: Computing extreme avalanches, Cold Reg. Sci. Technol., 39, 161–180, https://doi.org/10.1016/j.coldregions.2004.04.004, 2004. a, b
Bartelt, P. and Lehning, M.: A physical SNOWPACK model for the Swiss avalanche warning Part I: Numerical model, Cold Reg. Sci. Technol., 35, 123–145, https://doi.org/10.1016/S0165-232X(02)00074-5, 2002. a
Bartelt, P., Bühler, Y., Christen, M., Deubelbeiss, Y., Salz, M., Schneider, M., and Schumacher, L.: RAMMS::AVALANCHE User Manual – A numerical model for snow avalanches in research and practice, WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland, https://ramms.slf.ch/fileadmin/user_upload/WSL/Microsite/RAMMS/Downloads/RAMMS_AVAL_Manual.pdf (last access: 28 July 2022), 2017. a
Bavay, M. and Egger, T.: MeteoIO 2.4.2: a preprocessing library for meteorological data, Geosci. Model Dev., 7, 3135–3151, https://doi.org/10.5194/gmd-7-3135-2014, 2014. a
Bellaire, S. and Jamieson, B.: On estimating avalanche danger from simulated snow profiles, in: Proceedings of the International Snow Science Workshop, 7–11 October 2013, Grenoble and Chamonix, France, 154–161, https://arc.lib.montana.edu/snow-science/item/1740 (last access: 7 November 2023), 2013a. a, b, c
Download
Short summary
We present statistical models to estimate the probability for natural dry-snow avalanche release and avalanche size based on the simulated layering of the snowpack. The benefit of these models is demonstrated in comparison with benchmark models based on the amount of new snow. From the validation with data sets of quality-controlled avalanche observations and danger levels, we conclude that these models may be valuable tools to support forecasting natural dry-snow avalanche activity.
Altmetrics
Final-revised paper
Preprint