Skip to content

Helpful resources

Snow cover models

  • SNOWPACK: maintained by the Swiss WSL Institute for Snow and Avalanche Research SLF. Access the Source code and documentation for MeteoIO and Snowpack.
  • Crocus: maintained by the French National Centre for Meteorological Research. Access the Source code (coming to GitHub soon) and scientific documentation.

Toolchains

  • AWSOME: toolchain for automated meteorological calculations and operational avalanche forecasts. Access the Source code.
  • Canadian Hydrological Model: modular unstructured mesh-based approach for hydrological modelling. Access the Source code.

Post-processing

Publications

Community publications

  • 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., 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.

Core snow cover model publications

  • SNOWACK..
  • Crocus...

Research studies

  • Hagenmuller, P. and Pilloix, T.: A new method for comparing and matching snow profiles, application for profiles measured by penetrometers, Front. Earth Sci., 4, 52, https://doi.org/10.3389/feart.2016.00052, 2016.
  • Herla, F., Horton, S., Mair, P., and Haegeli, P.: Snow profile alignment and similarity assessment for aggregating, clustering, and evaluating snowpack model output for avalanche forecasting, Geosci. Model Dev., 14, 239-258, https://doi.org/10.5194/gmd-14-239-2021, 2021.
  • Herla, F., Haegeli, P., and Mair, P.: A data exploration tool for averaging and accessing large data sets of snow stratigraphy profiles useful for avalanche forecasting, Cryosphere, 16, 3149-3162, https://doi.org/10.5194/tc-16-3149-2022, 2022.
  • Horton, S., Nowak, S., and Haegeli, P.: Enhancing the operational value of snowpack models with visualization design principles, Nat. Hazards Earth Syst. Sci., 20, 1557-1572, https://doi.org/10.5194/nhess-20-1557-2020, 2020.
  • Horton, S., Towell, M., and Haegeli, P.: Examining the operational use of avalanche problems with decision trees and model-generated weather and snowpack variables, Nat. Hazards Earth Syst. Sci., 20, 3551-3576, https://doi.org/10.5194/nhess-20-3551-2020, 2020.
  • Horton, Horton, S. and Haegeli, P.: Using snow depth observations to provide insight into the quality of snowpack simulations for regional-scale avalanche forecasting, Cryosphere, 16, 3393-3411, https://doi.org/10.5194/tc-16-3393-2022, 2022.
  • Mayer, S., van Herwijnen, A., Techel, F., and Schweizer, J.: A random forest model to assess snow instability from simulated snow stratigraphy, Cryosphere, 16, 4593-4615, https://doi.org/10.5194/tc-16-4593-2022, 2022.
  • Pérez-Guillén, C., Techel, F., Hendrick, M., Volpi, M., van Herwijnen, A., Olevski, T., Obozinski, G., Pérez-Cruz, F., and Schweizer, J.: Data-driven automated predictions of the avalanche danger level for dry-snow conditions in Switzerland, Nat. Hazards Earth Syst. Sci., 22, 2031––2056, https://doi.org/10.5194/nhess-22-2031-2022, 2022.