New snow viability indices for ski resorts

Which sectors in the ski area have been affected by a lack of snow in recent years? How often? Will snow conditions be adequate in the future? These questions are at the heart of development approaches for mountain resorts, with snow on the ground being an essential resource for winter tourism. The “100 day rule,” which states that a resort is viable if it has at least 30 cm of snow for at least 100 days, is currently an international benchmark, although it needs to be refined. Given the variability of the climate and increasing competition, snow management practices (packing and producing artificial snow) have developed significantly to improve the quality and quantity of snow on the slopes. For this reason, 32% of the ski slopes in the French Alps are equipped with snow guns[1]. In this context, researchers from Irstea and Météo France are working to offer operators more realistic decision-making support tools for previous snow conditions (height, mass, etc.) and to provide future projections.

Analyzing past snow conditions and...

Using interviews with managers from 55 Alpine resorts, Pierre Spandre, an Irstea/Météo- France (CNRM/CEN) researcher, has input the packing and artificial snow (production periods, threshold temperatures, etc.) processes into the Crocus natural snow digital model, created the Crocus Resort module. In this way, using meteorological conditions from 1958 to 2014[2], snow on packed slopes with or without artificial snow was simulated for all French alpine resorts. Two indicators were defined using these simulations:

  • Snow Viability Altitude (or the altitude at which the quantity of natural packed snow is higher than 20cm with a density of 500kg/m3 for at least 100 days, between December 15 and April 15), determined for 23 alpine mountains with an average of 1480m in the north and 2035m in the south.
  • “Combined holiday” index, which includes specific details of a resort (altitude, slope, orientation, mechanical lifts), with particular focus on the spatial distribution of snow guns, and is based on the snow viability during the Christmas and school winter holidays.

How does snow management affect the snow viability of a resort? As an example, while snow management significantly improved the viability of the Sept-Laux resort during the 2006-2007 season, it did not make up for the lack of natural snow at the start of the season, as the temperature was too mild to produce artificial snow[3].

These maps are useful diagnostic tools and also reveal the trends of previous decades (frequency of “poor years”, particularly affected areas, etc.) as well as making it possible to understand the effects of snow management.

…Simulating future snow conditions until 2100

Will snow cover be viable in the future? As part of this work, researchers from Irstea Grenoble are now looking at developing snow viability indices for the future as well as the past for 24 winter sport resorts in Isère. To develop these forecasting indicators, scientists have incorporated three climate scenarios from the IPCC [4](the most alarming to the most optimistic) into the Crocus Resort model, taking it to 2100, adapted for SAFRAN using the ADAMONT[5] scale descent method.

These indices will make it possible to estimate the viability of snow conditions for each season to come. Moreover, the amount of water and energy required to produce artificial snow will also be estimated to improve the overall impact of these snow management practices. The results of the study will be delivered in April 2018.


Optimizing snow management on a seasonal scale 

“Resort operators also need snow condition predictions for shorter periods, from 3 to 10 days up to the entire season,” explains Irstea researcher Emmanuelle George. “This data is essential to decide whether they need to prepare snow stockpiles, or if the production of artificial snow will not be affected by high temperatures.

It is for this reason that Irstea is working as part of the H2020 PROSNOW project led by Météo-France[6] to develop a decision-making support tool to improve snow production management. The tool will offer operators snow height or stock predictions for several days and several months, and will incorporate the characteristics of the ski areas. Eight pilot stations, including two in France, have been involved since the start of the project, to better define their requirements and test the tool. These projects help professionals adopt management strategies adapted to the challenges of tomorrow.

For more information

[1] SPANDRE P., FRANCOIS H., MORIN S., GEORGE-MARCELPOIL E., 2015. “Dynamique de la neige de culture dans les Alpes Françaises : Contexte climatique et état des lieux”. Journal of Alpine Research | Revue de géographie alpine.

[2] SAFRAN reanalysis, CEN

[4] IPCC - Intergovernmental Panel on Climate Change

[5] VERFAILLIE D., DÉQUÉ M., MORIN S., and LAFAYSSE M., 2017 "The method ADAMONT v1.0 for statistical adjustment of climate projections applicable to energy balance land surface models" Geosci. Model Dev., 10, 4257-4283.

[6] Coordinated by Météo-France, the H2020 PROSNOW project brings together 12 European partners. For more information: