Application of physical snowpack models in support of operational avalanche hazard forecasting: A status report on current implementations and prospects for the future

Samuel Morin (1) , Simon Horton , Frank Techel , Mathias Bavay , Cécile Coléou (2) , Charles Fierz , Andreas Gobiet , Pascal Hagenmuller (1) , Matthieu Lafaysse (1) , Matjaž Ližar , Christoph Mitterer , Fabiano Monti , Karsten Müller , Marc Olefs , John S Snook , Alec van Herwijnen , Vincent Vionnet (1)

1 CNRM - Centre national de recherches météorologiques
2 DIROP/MAR - Département Prévision Marine et Océanographique de Météo-France

The application of numerical modelling of the snowpack in support of avalanche hazard prediction is increasing. Modelling, in complement to direct observations and weather forecasting, provides information otherwise unavailable on the present and future state of the snowpack and its mechanical stability. However, there is often a perceived mismatch between the capabilities of modelling tools developed by research organizations and implemented by some operational services, and the actual operational use of those by avalanche forecasters. This causes frustration on both sides. By summarizing currently implemented modelling tools specifically designed for avalanche forecasting, we intend to diminish and contribute to bridging this gap. We highlight specific features and potential added value, as well as challenges preventing a more widespread use of these modelling tools. Lessons learned from currently used methods are explored and provided, as well as prospects for the future, including a list of the most critical issues to be addressed.

Domaines: Planète et Univers [physics]

Samuel Morin, Simon Horton, Frank Techel, Mathias Bavay, Cécile Coléou, et al.. Application of physical snowpack models in support of operational avalanche hazard forecasting: A status report on current implementations and prospects for the future. Cold Regions Science and Technology, 2020, 170, pp.102910. ⟨10.1016/j.coldregions.2019.102910⟩. ⟨insu-03211809⟩