In this Section:

	Background
	Project Components:
	Agriculture
	Park Visitations
	Ranching
	Riparian Corridors
	Ski Recreation
	Water Markets
	Related Links
	Contacts

Research and Products:
Economic Analysis of Water Resources and Ski Recreation

Background and Project Overview

Less snow and shorter snow seasons are no longer just a nightmare for ski enthusiasts. Climate change models actually predict such dismal events, especially for locations at low elevations and low latitudes. So how does this impending change affect the local economies of snow-dependent communities within these vulnerable locations? Investigators have asked such a question, prompting research that focused on impacts to low elevation ski resorts in Europe and Canada. But how will declining snow packs and diminishing snow seasons affect the snow-dependent local economies in low latitude locations? This research seeks to answer this question by investigating the likely impact of climate change on low latitude ski resorts in the southwestern United States.

The research is based upon a case study of Sunrise Park Ski Resort located in the White Mountains of Arizona. The particular case of the Sunrise resort highlights two interesting features of climate change in the Southwest: the availability of water supplies to make manmade snow to compensate for reduced snowfall conditions, and the importance of tribal management. The White Mountain Apache Tribe’s Sunrise Park Resort is located at latitude 34° and at a relatively high elevation that ranges from 2,862 m to 3,385 m. Currently, Sunrise can produce enough snow for just 10 percent of the skiable terrain. To put this into context, ski resorts in central Ontario, which are located at low elevations and high latitude, possess snowmaking capabilities for 100 percent of the skiable terrain (Scott, McBoyle, and Mills, 2003).

Methods

In addition to collecting detailed background information on climate change and ski recreation, snow depth data has been collected and extrapolated using snowpack telemetry (SNOTEL) and snow course data for the White Mountains region. Data on manmade snowmaking technical and water requirements and costs has also been collected. Researchers have developed a model of snow depth as related to recreational visits and local economic activity.

Findings

Arizona’s ski areas are already subject to high annual variability in snowfall and season length. Increased variability may be a result of climate change, but much of the variability can be explained by annual and decadal scale climate oscillations. The models of snow depth data from Sunrise, annual snowfall, and season length data from Snowbowl—another of Arizona’s ski areas—were constructed as a function of a key oscillation, the El Niño Southern Oscillation (ENSO) and the Pacific Decadal Oscillation modulated ENSO (ENSO-PDO). The modeling results show that snow depth at the Mt. Baldy (Sunrise) SNOTEL site is significantly and positively predicted by ENSO and ENSO-PDO (a binary variable that equals one when both the ENSO and PDO indices are positive and zero otherwise). This analysis predicts that a one unit increase in ENSO increases snow depth at the site by 14.3 cubic meters (m3), or by 23.03m3 when both ENSO and PDO are positive.

Furthermore, a one unit increase in ENSO raises annual snowfall by 114.03cm. An ENSO-PDO model (not shown) explains 21% of the variation and predicts snowfall will be 249.15cm higher than average. From the data it seems that ENSO is a better predictor of snow depth than total snowfall, this might be explained by generally cooler temperatures in an El Niño year.

Skier visitation is also impacted by ENSO. For example, a one unit increase in ENSO increases season length by 18 days and visits by 23,653 from the average. In an ENSO-PDO year these figures are 31 days and 41,449 visitors. However, we note that climate oscillations, although significant, explain less than a fifth of the variation in season length and visitation. Snowbowl is 100 percent dependent on natural snowfall. Other important factors explaining season length and visits are the timing of first snowfall, the depth of snow, the incidence of warm spells and powder events, and general economic conditions.

Snowmaking enables resorts to build snowpack even in the absence of natural snow. This improves the consistency of ski seasons and allows resorts to open for the crucial Christmas and Rodeo week vacations. Sunrise has snowmaking capability for 10 percent of its terrain while Snowbowl has plans for 100 percent snowmaking capacity.

Although new snowmaking investments could reduce ski season uncertainty at Sunrise, such investments would also make the tribe more economically dependent on winter recreation. Therefore, before investing further in snowmaking, the associated increased costs of snowmaking at higher temperatures, the relative competitive position of Sunrise, and the alternative uses of such capital and water, need to be assessed. In addition, the environmental impacts of expanded snowmaking—namely water supply issues and the impact of water withdrawals on winter fish habitat—need to be considered. Non-snowmaking adaptations are to: limit skiing to top slopes where snow is more reliable; plan hiring and marketing based on ENSO forecasts; and restructure prices to encourage opportunistic skiers.

References

Breiling, M. and P. Charamza. 1999. The impact of global warming on winter tourism and skiing: a regionalized model for Austrian snow conditions. Regional Environmental Change, 1 (1): 4-14.

König, U. 1998. Tourism in a warmer world: implications of climate change due to enhanced greenhouse effect for the ski industry in the Australian Alps. Wirtschaftsgeogrphie und Raumplanung, Volume 28. University of Zurich, Zurich, Switzerland.

Scott, D., G. McBoyle, and B. Mills. 2003. Climate change and the skiing industry in southern Ontario (Canada): exploring the importance of snowmaking as a technical adaptation. Climate Research 23: 171-181.

Ratnik Industries. Snowmaking 101. Available at http://www.ratnik.com/snowmaking.html, accessed 1.5.05.