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

旅游 背景(考古学) 气候变化 地理 比例(比率) 气候学 自然地理学 环境资源管理 环境科学 气象学 地图学 生态学 地质学 考古 生物
作者
Samuel Morin,Raphaëlle Samacoïts,Hugues François,Carlo Maria Carmagnola,Bruno Abegg,O. Cenk Demiroglu,Marc Pons,Jean‐Michel Soubeyroux,Matthieu Lafaysse,Sam Franklin,Guy Griffiths,Debbie Kite,Anna Amacher Hoppler,Emmanuelle George,Carlo Buontempo,Samuel Almond,Ghislain Dubois,Adeline Cauchy
出处
期刊:Climate Services [Elsevier BV]
卷期号:22: 100215-100215 被引量:81
标识
DOI:10.1016/j.cliser.2021.100215
摘要

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.
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