Pan-European meteorological and snow indicators of climate change impact on ski tourism - PubMed (original) (raw)

doi: 10.1016/j.cliser.2021.100215.

Raphaëlle Samacoïts 1 2, Hugues François 3, Carlo M Carmagnola 1, Bruno Abegg 4, O Cenk Demiroglu 5, Marc Pons 6, Jean-Michel Soubeyroux 2, Matthieu Lafaysse 1, Sam Franklin 7, Guy Griffiths 7, Debbie Kite 7, Anna Amacher Hoppler 8, Emmanuelle George 3, Carlo Buontempo 9, Samuel Almond 9, Ghislain Dubois 10, Adeline Cauchy 10

Affiliations

Pan-European meteorological and snow indicators of climate change impact on ski tourism

Samuel Morin et al. Clim Serv. 2021 Apr.

Abstract

Ski tourism plays a major socio-economic role in the snowy and mountainous areas of Europe such as the Alps, the Pyrenees, Nordic Europe, Eastern Europe, Anatolia, etc. Past and future climate change has an impact on the operating conditions of ski resorts, due to their reliance on natural snowfall and favorable conditions for snowmaking. However, there is currently a lack of assessment of past and future operating conditions of ski resorts at the pan-European scale in the context of climate change. The presented work aims at filling this gap, as part of the "European Tourism" Sectoral Information System (SIS) of the Copernicus Climate Change Services (C3S). The Mountain Tourism Meteorological and Snow Indicators (MTMSI) were co-designed with representatives of the ski tourism industry, including consulting companies. They were derived from statistically adjusted EURO-CORDEX climate projections (multiple GCM/RCM pairs for RCP2.6, RCP4.5 and RCP8.5) using the UERRA 5.5 km resolution surface reanalysis as a reference, used as input to the snow cover model Crocus, with and without accounting for snow management (grooming, snowmaking). Results are generated for 100 m elevation bands for NUTS-3 geographical areas spanning all areas relevant to ski tourism in Europe. This article introduces the underpinning elements for the generation of this product, and illustrates results at the pan-European scale as well as for smaller scale case studies. A dedicated visualization app allows for easy navigation into the multiple dimensions of this dataset, thereby fulfilling the needs of a broad range of users.

Keywords: Climate change; Copernicus; Europe; Mountain tourism; Ski tourism.

© 2021 The Author(s).

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1

Fig. 1

Overview of the NUTS-3 areas classified as holding ski tourism character, or not.

Fig. 2

Fig. 2

Overview of the App used to navigate through the dataset. The map displays values only for NUTS-3 areas where the selected elevation is included in the dataset.

Fig. 3

Fig. 3

Time series of the annual number of days with more than 30 cm of natural snow at 1500 m elevation, for the Oberkärnten (Upper Carinthia) NUTS-3 area (Austria), and corresponding multi-annual aggregations visualizations and numerical values. See text for more details.

Fig. 4

Fig. 4

Same as 3 for managed snow (grooming .and snowmaking).

Fig. 5

Fig. 5

Evolution of the number of days with more than 30 cm of natural snow at 800 m elevation across Europe, based on climate projections, for the reference period 1986–2005 using historical simulations (top left corner), and relative change from the reference values for RCP8.5 projections for the time period 2021–2040 (top right), 2041–2060 (bottom left) and 2081–2100 (bottom right). The map displays values only for NUTS-3 areas where the selected elevation is included in the dataset. See text for more details.

Fig. 6

Fig. 6

Same as 5 for managed snow (grooming and snowmaking).

Fig. 7

Fig. 7

Simulated snow production for RCP2.6, RCP4.5 and RCP8.5 as a function of elevation for the NUTS-2 region Auvergne Rhône Alpes (France) for the time period 2021–2040 (left), 2041–2060 (middle) and 2081–2100 (right), compared to the historical time period (1986–2005, grey line on all plots). See text for more details.

Fig. 8

Fig. 8

Illustration of the the Uludağ ski resort case study in Turkey. MTMSI results illustrating the winter temperature and snow reliability projections along with increased water consumption requirements for snowmaking at 1900–2000 m elevation band are shown on the upper graph. The black line represents the actual winter/ski season (NDJFMA) average temperature. The scene, created in ArcGIS Pro with a three times vertical exaggeration, shows the critical elevation bands for existing ski area as well as the slope diversity of existing and extendable ski areas.

Fig. 9

Fig. 9

Illustration of the SBS case study in Switzerland. (a) Change in early-season potential snowmaking hours across time periods and RCPs. (b) Screenshot of the MTMSI app showing the number of days with more than 30 cm of groomed snow over the Christmas/New Year’s period (mean values; near future: 2021–2040; RCP8.5).

Fig. 10

Fig. 10

Comparison of the number of days with more than 30 cm of managed snow (sd-days-30-MS indicator) between Andorra and Lleida, Spain (left) and Ariège, France (right) for end of century RCP8.5. The figure highlights the elevation range for the GrandValira and Vallnord ski resorts.

Fig. 11

Fig. 11

Comparison of the number of days with more than 100 kg m−2 SWE for natural snow between the MTMSI dataset, for the Savoie NUTS-3 (Northern French Alps) and the S2M reanalysis for the ”massifs” included in this NUTS-3 area. Time series for the time period 1960–2019 (left hand side) and evaluation metrics for each elevation band (mean deviation and root mean square deviation, right hand side).

Fig. 12

Fig. 12

Illustration of the representative points within the UERRA5.5 km reanalysis attributed to each elevation band, in the example of the Vaud canton in Switzerland (NUTS-3 CH011).

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