Ski areas, weather and climate: time series models for New England case studies

Abstract

Abstract:Wintertime warming trends experienced in recent decades, and predicted to increase in the future, present serious challenges for ski areas and whole regions that depend on winter tourism. Most research on this topic examines past or future climatechange impacts at yearly to decadal resolution, to obtain a perspective on climate-change impacts. We focus instead on local-scale impacts of climate variability, using detailed daily data from two individual ski areas. Our analysis fits ARMAX (autoregressive moving average with exogenous variables) time series models that predict day-to-day variations in skier attendance from a combination of mountain and urban weather, snow cover and cyclical factors. They explain half to twothirds of the variation in these highly erratic series, with no residual autocorrelation. Substantively, model results confirm the "backyard hypothesis" that urban snow conditions significantly affect skier activity; quantify these effects alongside those of mountain snow and weather; show that previous-day conditions provide a practical time window; find no monthly effects net of weather; and underline the importance of a handful of high-attendance days in making or breaking the season. Viewed in the larger context of climate change, our findings suggest caution regarding the efficacy of artificial snowmaking as an adaptive strategy, and of smoothed yearly summaries to characterize the timing-sensitive impacts of weather (and hence, high-variance climate change) on skier activity. These results elaborate conclusions from our previous annual-level analysis. More broadly, they illustrate the potential for using ARMAX models to conduct integrated, dynamic analysis across environmental and social domains.

Impact of snow variability on the Swiss winter tourism sector: implications in an era of climate change

“…Therefore, one should control for the intra-seasonal distribution to avoid underestimating the effect of good snow conditions. Eventually, it has been sometimes empirically tested in the literature that weather and snow conditions outside a ski area could also affect its visitation rate (Hamilton et al 2007;Shih et al 2009). These conditions should be controlled so that we could be a little more confident that our estimates of the snow sensitivity of skier visits represent the pure effect of improving snow conditions at the ski area itself.…”

“…Another strand of the literature has more specifically dealt with potential and/or actual behavioral adaptations on the demand side (Behringer et al 2000;Hamilton et al 2007;Unbehaun et al 2008;Shih et al 2009;Pickering et al 2010;Dawson et al 2011;Töglhofer et al 2011). Methodologically, these studies rely either on surveys of skiers or on quantitative analyses based on regression techniques.…”

“…Also potentially important for visitation rates at ski areas are snow conditions in skiers' areas of origin ("backyard hypothesis"). However, two studies, which both used detailed daily data from two individual ski areas, have provided conflicting evidence about this effect (Hamilton et al 2007;Shih et al 2009). …”

Regional variation in perceptions about climate change

“…The sprawl question was among a set of five items that included one on climate change: Looking at these results, we noticed that the three regions showing the highest levels of concern represent snow-country areas (in northern New Hampshire, western Maine and central Colorado) that recently experienced trends toward warmer and less-snowy winters, with newsworthy impacts on winter recreation, forest health and daily life (Hamilton et al, 2003(Hamilton et al, , 2007NERA, 2001;USGCRP, 2003). Does the pattern of climate responses in Figure 2 partly reflect a winter-warming effect, as the pattern of sprawl responses reflects population growth?…”

Toward understanding the human dimensions of the rapidly changing arctic system: insights and approaches from five HARC projects

“…These methods are data-hungry, however, requiring long time series that in many cases do not exist, and might not even be definable, for human-dimensions indicators in the North. As more years of data become available, or where finer temporal scales such as daily resolution make sense, the ARMAX approach looks quite promising (for an integrated although non-arctic example, see Hamilton et al (2007) In the arctic system, retrospective and prospective studies are part of a continuum and reinforce each other Four of the five early HARC studies mentioned above are primarily retrospective, looking backwards in time. They aim to learn about causal processes and thereby shed light on the future, and they accomplish these aims by examining complex stories that unfolded in the distant or immediate past.…”