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The Opening-Week Snow Reliability Index

Resorts publish an opening date. The weather does not read it. This index takes 10 seasons of weather-model history at 53 curated destinations and asks one question of each: in the week this mountain traditionally opens, was there real natural snow on the ground?

Destinations
53
Seasons each
10
Snow-ready 8+ seasons
16
Coin-flip, 4 to 6
5
Never snow-ready
13

Snow-ready means modelled snow depth of at least 30 cm on at least 3 of the 7 opening-week days. The same rule is applied to all 53 destinations, with no exceptions and no adjustments. Natural snow only: snowmaking is not modelled.

How the 53 destinations fall out

Each column counts the destinations that reached that many snow-ready seasons out of 10.

13 0 8 1 8 2 2 3 4 4 5 1 6 1 7 3 8 7 9 6 10 SNOW-READY SEASONS OUT OF 10

The ranking

Ten cells per destination, one per season, oldest on the left. A filled cell is a season that met the threshold. Ties are broken by mean opening-week depth.

#DestinationCountryOpening weekSeasons snow-readyScoreMean depthModel cell
1 Whistler Blackcomb Canada Late November 10/10 135.9CM 664M
2 Portillo Chile Late June 10/10 132.7CM 3223M
3 Revelstoke Canada Early December 10/10 95.2CM 2241M
4 Zermatt Switzerland Late November 10/10 76.6CM 1608M
5 St. Anton am Arlberg Austria December 10/10 68.6CM 1417M
6 Shymbulak Kazakhstan Late November 10/10 65.3CM 3222M
7 Las Leñas Argentina Mid June 9/10 101.8CM 2155M
8 Chamonix France December 9/10 72.7CM 1034M
9 Verbier Switzerland Early December 9/10 69.2CM 1555M
10 St. Moritz Switzerland Late November 9/10 66.9CM 2764M
11 Livigno Italy Late November 9/10 60.8CM 1931M
12 Val Thorens France Late November 9/10 54.8CM 2387M
13 Garmisch-Classic Germany Mid December 9/10 52.8CM 1915M
14 Valle Nevado Chile Mid June 8/10 82.5CM 3048M
15 Cerro Catedral Argentina Late June 8/10 57.3CM 2032M
16 Lake Louise Canada Early November 8/10 41.8CM 1652M
17 Gudauri Georgia Late December 7/10 44.4CM 2881M
18 Sölden Austria Mid November 6/10 37.6CM 2997M
19 Hakuba Valley Japan Mid December 5/10 33.3CM 720M
20 Val Gardena Italy Early December 5/10 31.9CM 2007M
21 Jackson Hole United States Late November 5/10 29.7CM 1966M
22 Big Sky United States Late November 5/10 25.9CM 3246M
23 Zakopane / Kasprowy Wierch Poland December 3/10 19.8CM 1926M
24 Trysil Norway Late November 3/10 18.1CM 1064M
25 Cortina d'Ampezzo Italy Late November 2/10 33.5CM 1258M
26 Grandvalira Andorra Early December 2/10 22.1CM 2402M
27 Telluride United States Late November 2/10 19CM 3820M
28 Kranjska Gora Slovenia Early December 2/10 17.8CM 1442M
29 Aspen Snowmass United States Late November 2/10 17.3CM 2587M
30 Palisades Tahoe United States Late November 2/10 16.7CM 1916M
31 Jasná – Chopok Slovakia December 2/10 15.6CM 1276M
32 Coronet Peak New Zealand Mid June 2/10 13CM 1456M
33 Tremblant Canada Late November 1/10 16.3CM 909M
34 Niseko United Japan Early December 1/10 15.3CM 302M
35 Alta & Snowbird United States Late November 1/10 14.9CM 3111M
36 Vail United States Mid November 1/10 13.5CM 3432M
37 Park City United States Late November 1/10 13.1CM 2146M
38 Bansko Bulgaria Mid December 1/10 10.1CM 2627M
39 Baqueira Beret Spain Late November 1/10 10CM 2364M
40 Mammoth Mountain United States Mid November 1/10 8.2CM 3202M
41 Špindlerův Mlýn Czechia Early December 0/10 11.7CM 1225M
42 Breckenridge United States Early November 0/10 10.7CM 3793M
43 Åre Sweden November 0/10 7.9CM 412M
44 Mt Hutt New Zealand Mid June 0/10 5.6CM 1979M
45 Killington United States Mid November 0/10 4.4CM 1196M
46 Perisher Australia Early June 0/10 4.4CM 1729M
47 Nozawa Onsen Japan Late November 0/10 4.3CM 1509M
48 Thredbo Australia Early June 0/10 3.5CM 2001M
49 Kitzbühel Austria Late October 0/10 1.2CM 745M
50 Yongpyong South Korea Late November 0/10 1.1CM 1392M
51 Afriski Lesotho Early June 0/10 0.8CM 3079M
52 Sierra Nevada Spain Late November 0/10 0.6CM 3190M
53 Levi Finland October 0/10 0.3CM 297M

Weather data by Open-Meteo.com (CC BY 4.0), adapted for display. Mean depth is the average modelled depth across all 70 opening-week days. Model cell is the elevation the reanalysis assigns to that destination's grid square, being the average of all the terrain inside it. It is the honest way to read a row: Garmisch-Classic's cell sits at 1,915 m, near the top of a ski area that starts at 740 m, while Kitzbühel's sits at 745 m, near the bottom of one that reaches 2,000 m. Compare the cell against the resort's own base and summit before you read a score as a verdict on the mountain.

Methodology, in full

The threshold, verbatim. A season counts as snow-ready when modelled snow depth reached at least 30 cm on at least 3 of the 7 opening-week days at the destination's registry grid point. A destination's score is the number of snow-ready seasons out of 10. Where two destinations tie, the higher mean opening-week depth ranks first.

The opening week. Each destination's opening window is the one already published on its own destination page, written as prose such as "Late November" or "Mid December". Those windows come from each resort's own stated traditional season, checked against dated openings from recent years. Where the record disagreed with what this site had on file, the entry was corrected and the row recomputed before publication: the input gets fixed, never the threshold. The words are then resolved to dates by a fixed table applied to every destination: "Early" means the 1st to the 7th, "Mid" the 11th to the 17th, "Late" the 21st to the 27th, and a bare month name is read as the 1st to the 7th. Southern-hemisphere destinations are scored in their own winter, so their windows fall between June and September. The resolved window is printed in the table above, so you can check the reading against the resort's own dates.

Traditional, not contractual. These are the windows a mountain has historically opened in, not promises. Resorts move their opening dates for snow, for staffing, for events and for holiday calendars. Nothing here is a claim about what any resort has committed to.

Natural snow only. The model knows about weather. It does not know about snow cannons, and no snowmaking is modelled anywhere in this index. Several destinations near the bottom of the table open reliably every year on manufactured snow, and their low score says nothing against them. It says only that the sky did not do the work.

The grid-point caveat, plainly. The data is the ERA5-Land reanalysis, read through the Open-Meteo historical archive, one call per destination for the whole period. ERA5-Land models the world on a grid of roughly nine kilometres, and each cell carries a single elevation that is the average of the terrain inside it. In steep mountains that average sits well below the summit: the cell used for Zermatt models terrain at about 1,600 m, not the 3,883 m top station. So these are not readings from the top of the lift. They are a consistent, reproducible measure of what the atmosphere put on each mountain's cell, applied identically to every destination, and they should be read as a comparison between places rather than as a depth you would find under your skis.

New resorts, old locations. A destination is scored over 10 seasons of weather whether or not it sold lift tickets in every one of them. The index measures the snow at a location, not the trading history of a business.

What is not in the index, and why. One destination was researched for this release and deliberately left out. Gulmarg, in Jammu and Kashmir, has the altitude and the snow record to belong here, but its gondola suffered a major failure in May 2026 that left several hundred people stranded, the closure was then extended indefinitely while a government inquiry sat, and although the lift resumed service in June no winter season had been confirmed when this index was built. There is also a standing UK Foreign Office advisory against all travel to the territory. The snow data existed; the confidence to send a reader there did not, so the row was held rather than published. It goes in when a season is confirmed.

What could make a row wrong. A reanalysis is a model, not a measurement: it can be too smooth over complex terrain, and it can miss a local storm. A grid cell can also straddle two very different aspects. Where a number here contradicts a resort's own record, the resort's own record is the better evidence for that resort, and this index is the better evidence for the comparison between them.

Take the data

Both tables are free to use and free to republish under CC BY 4.0, the same licence as the underlying weather data. A link back to this page is all the attribution we ask for.

  • The ranking table, one row per destination: score, mean and maximum opening-week depth, the resolved window, coordinates, and the elevation of the model grid cell.
  • The season-by-season table, one row per destination per season: the exact window dates, how many of the 7 days met the threshold, and all seven daily depths.

Questions, corrections and requests for a regional cut of the data are welcome on the contact page. If you can show that a row is wrong, we would rather fix it than defend it.