News Release

The future is likely less skiable, thanks to climate change

Snow scarcity may push popular ski hubs to more remote areas and threaten livelihoods of local populations

Peer-Reviewed Publication


Global reduction of snow cover in ski areas under climate change


Climate change is predicted to alter snowfall patterns, impacting ski areas with economic and ecological consequences. In this study, researchers predicted trends in natural snow cover days this century under three different climate change scenarios: (low CO2 emissions (SSP1-2.6), high emissions (SSP3-7.0) and very high emissions (SSP5-8.5). The results suggest significant decreases in snow cover days across all ski areas (from an average of 216 snow cover days in the past to 141 snow cover days in a high emission scenario), with a particularly fast decrease in lower elevations. The authors expect an expansion of infrastructure toward higher elevations, threatening biodiversity among high-altitude species.

view more 

Credit: Anne-Lise Paris, (, PLOS, CC-BY 4.0 (

Annual snow cover days in all major skiing regions are projected to decrease dramatically as a result of climate change, with 1 in 8 ski areas losing all natural snow cover this century under high emission scenarios. These results are published in a new study in the open-access journal PLOS ONE by Veronika Mitterwallner from the University of Bayreuth, Germany and colleagues.

Popular skiing destinations experience the impacts of climate change, which include reduced snowfall in regions around the world. Despite the social, economic, and ecological significance of the skiing industry, little research exists on how ski area distributions are affected by climate change globally. Existing studies are small-scale and focused on Europe, North America, and Australia.

Mitterwallner and colleagues examined the impact of climate change on annual natural snow cover in seven major skiing regions: the European Alps, Andes Mountains, Appalachian Mountains, Australian Alps, Japanese Alps, Southern Alps (located in New Zealand), and Rocky Mountains.

The researchers identified specific skiing locations within these seven regions using OpenStreetMap. As the largest global ski market, the European Alps accounted for 69% of these areas. The researchers also used the public climate database CHELSA, enabling them to predict annual snow cover days for each ski area for 2011-2040, 2041-2070, and 2071-2100 under low, high, and very high carbon emissions scenarios.

Under the high emissions scenario, 13% of ski areas are predicted to lose all natural snow cover by 2071-2100 relative to their historic baselines. Twenty percent will lose more than half of their snow cover days per year. By 2071–2100, average annual snow cover days were predicted to decline most in the Australian Alps (78%) and Southern Alps (51%), followed by the Japanese Alps (50%), Andes (43%), European Alps (42%), and Appalachians (37%), with the Rocky Mountains predicted to experience the least decline at 23% relative to historic baselines.

The researchers state that diminishing snow cover may prompt ski resorts to move or expand into less populated areas, potentially threatening alpine plants and animals already under climate-induced strain. Resorts favoring faux snow may rely on “technical snowmaking” practices like artificial snow production, but regardless, the authors predict that the economic profitability of ski resorts will fall globally.

The authors add: “This study demonstrates significant future losses in natural snow cover of current ski areas worldwide, indicating spatial shifts of ski area distributions, potentially threatening high-elevation ecosystems.”


In your coverage please use this URL to provide access to the freely available article in PLOS ONE:

Citation: Mitterwallner V, Steinbauer M, Mathes G, Walentowitz A (2024) Global reduction of snow cover in ski areas under climate change. PLoS ONE 19(3): e0299735.

Author Countries: Germany, Switzerland

Funding: Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – 491183248. Funded by the Open Access Publishing Fund of the University of Bayreuth. The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.