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Global Ski Area Climate Vulnerability (2026-2036) Map

Ski areas facing the most immediate threat of closure over the next decade share distinct spatial characteristics: base elevations below 1,500 meters (roughly 4,900 feet), high exposure to maritime or transitional climates, and an inability to maintain the consistent sub-freezing temperature windows required for artificial snowmaking.



The European Alps: Austria and the Pre-Alps

The Alps are currently warming at roughly twice the global average, putting intense pressure on lower-latitude and lower-elevation winter infrastructure.

The North American West: Pacific Northwest and Sierra Fringes

While historically known for deep maritime snowpacks, western regions are increasingly vulnerable to volatile temperature spikes and persistent atmospheric blocking.

The North American East: New England & The Mid-Atlantic

Eastern resorts have long relied on intensive, wall-to-wall snowmaking to combat natural weather variability, but rising baseline temperatures are shrinking the viable operating windows for snow guns.

The Southern Hemisphere: Australia

The Australian Alps have the lowest peak elevations of any major global ski region, making them uniquely exposed to warming trends.



Data used for map - https://github.com/dhimmel/openskistats



with_variable('elev_risk', clamp(0, (2500 - "ski_area_metrics_min_elevation") / 1500, 1),

with_variable('lat_risk', clamp(0, (55 - abs("ski_area_metrics_latitude")) / 20, 1),

with_variable('solar_risk', (1 - "ski_area_metrics_poleward_affinity") / 2,


round(1 + ((@elev_risk * 0.5) + (@lat_risk * 0.3) + (@solar_risk * 0.2)) * 9, 1)

)))

How this scores the data -


Using Mammoth Lakes as an example:

Elevation (2461.4m): Extremely close to the 2500m "safe" threshold. Risk = ~0.02.

Latitude (37.64°): Fairly far south, increasing macro-climate risk. Risk = ~0.86.

Poleward Affinity (0.45): Mostly north-facing, decreasing micro-climate risk. Risk = ~0.27.

You can easily tweak the model to fit your exact assumptions by changing the numbers in the code block:

If you want to be harsher on elevation, change the 2500 to 3000.

If you want to change the importance of the variables, just adjust the multipliers (e.g., @elev_risk * 0.6 and @lat_risk * 0.2), ensuring the three decimals still add up exactly to 1.0.



Other climate variables like new weather patterns were not factored in. For example: The new Heat Dome Effect: In mid-to-late March 2026, a stubborn, high-pressure ridge parked itself over the Western United States. This heat dome trapped descending air, which compressed and heated up, effectively blocking cooler weather systems or spring storms from moving into the region.

Extreme Temperature Spikes: This atmospheric block drove temperatures 20 to 30 degrees Fahrenheit above average across almost every major ski region, from California and the Pacific Northwest all the way east through the Rockies.

Premature Snowmelt: The timing was a worst-case scenario. Hitting right when the mountain snowpack typically reaches its peak depth, the sustained heat aggressively baked the slopes. Areas that were already struggling with a lower-than-normal base lost their snow rapidly, forcing highly premature season closures at resorts across Tahoe, Utah, Idaho, and Colorado, while triggering early alarms for the upcoming fire season and summer water supply.





Data source OSM/Openskistats.


Map: CCCarto