Ski tourism is a multi-billion dollar international market attracting between 300 and 350 million annual skier visits. With its strong reliance on specific climatic conditions, the ski industry is regarded as the tourism market most directly and immediately affected by climate change. A critical review of the 119 publications that have examined the climate change risk of ski tourism in 27 countries is provided. This growing and increasingly diverse literature has projected decreased reliability of slopes dependent on natural snow, increased snowmaking requirements, shortened and more variable ski seasons, a contraction in the number of operating ski areas, altered competitiveness among and within regional ski markets, and attendant implications for ski tourism employment and values of vacation property real estate values. The extent and timing of these consequences depend on the rate of climate change and the types of adaptive responses by skiers as well as ski tourism destinations and their competitors. The need to understanding differential climate risk grows as investors and financial regulators increasingly require climate risk disclosure at the destination and company scale. Key knowledge gaps to better assist ski tourism destinations to adapt to future climate risk are identified.

In this paper, the development and validation of a ski season simulation model (SkiSim 2.0) is described and results of the climate change assessment for 3 ski areas in Tyrol, Austria, are presented. The results of the validation process suggest that SkiSim 2.0 is an appropriate tool to simulate ski season lengths and snowmaking requirements at different altitudes and in different climatic subregions of the study area. Climate change impacts on ski season length are considerably less when incorporating snowmaking. All 3 modelled ski areas remain snow reliable until the 2040s (A1B) to the 2050s (B1). By then, current snowmaking technology has reached its technological limits. The required snow volume until the end of the century is projected to increase by up to 330%. Although snowmaking is a suitable adaptation strategy for the next decades, it is unlikely to be a sustainable adaptation strategy beyond the middle of the century. Besides altitude, local climate characteristics clearly influence ski season length, requiring the use of localized climate data. A comprehensive study of the research area, modelling all ski areas, is needed to assess the vulnerability of the ski marketplace in Tyrol.

PurposeThe purpose of this paper is to investigate the sensitivity of ski businesses and of the accommodation sector in Tyrol to warm winter seasons and to draw conclusions for climate change vulnerability.Design/methodology/approachOperational indicators of ski areas and overnight stays in the destinations were analysed in the record warm winter season 2006/2007. Comparing the climatic anomalies of that season with climate change scenarios, the season can serve as an analogue year for average future winter seasons. By interpreting changes in the analogue year, the potential vulnerability of the winter tourism industry in the study area can be assessed.FindingsWhile the impact on ski areas was relatively small on the province level, the analysis on the basis of individual businesses showed a high sensitivity of small to medium and low‐altitude ski areas as well as of ski areas with insufficient snowmaking facilities. Significant differences in the impact on the accommodation sector were found on the district level, with longer‐lasting negative effects on the regional tourism economy in two districts with low‐altitude ski areas. Climate change increases the risk of financial losses for individual ski businesses as well as for tourism‐dependent regional economies, as happened in the 2006/2007 season. As the season represents an extreme event, the long‐term effect of a rising frequency of warm winters on demand cannot be assessed.Originality/valueThe paper presents a valuable and inexpensive approach to assess the impact of warm winter seasons on the supply side as well as on the demand side.

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