How does PowCall forecast snow?

PowCall uses all 31 members of the NOAA GEFS ensemble model, applies per-resort PRISM-calibrated orographic precipitation multipliers based on wind direction, converts liquid precipitation to snow using the Kuchera temperature-dependent snow-to-liquid ratio, and validates forecasts daily against SNOTEL ground observation stations.

How accurate is PowCall?

PowCall provides transparent accuracy tracking. PowCall publishes how often its range actually held. The range we show (0 up to an 80th-percentile high) is scored against the 24-hour snowfall each resort reports, and we publish the measured share of days the report stayed within it, alongside how many snowy days that number rests on. Forecasts are also checked against USDA SNOTEL stations, with accuracy published for 1, 2, 3, 4, 5, 10 and 15-day lead times.

What is a GEFS ensemble forecast?

The Global Ensemble Forecast System (GEFS) runs 31 slightly different simulations of the atmosphere from NOAA. By looking at how these 31 members agree or disagree, we can quantify forecast uncertainty and provide probabilistic ranges rather than single-point forecasts.

What is orographic correction?

Mountains force air upward, increasing precipitation on windward slopes. Global weather models smooth terrain and underestimate this effect. PowCall applies per-resort, wind-direction-dependent multipliers calibrated against PRISM climatology data to correct for each resort's unique terrain and wind exposure.

How PowCall Forecasts Work

PowCall generates probabilistic 15-day snow forecasts for 120 ski resorts using ensemble weather models, terrain-aware corrections, and daily ground-truth verification. Every forecast includes uncertainty ranges so you can make better powder day decisions.

Forecast Pipeline

Each forecast update runs through a 5-step pipeline, executed 4 times daily when new GEFS model runs become available.

GEFS Ensemble Ingestion

We download all 31 members of the NOAA Global Ensemble Forecast System (GEFS) at 0.25-degree resolution. Each member represents a slightly different plausible evolution of the atmosphere out to 16 days. By processing all 31 members (not just the control run), we capture the full range of forecast uncertainty.

Orographic Precipitation Correction

Global models smooth terrain to ~25 km grid cells, dramatically underestimating precipitation in complex mountain terrain. We apply per-resort, wind-direction-dependent multipliers calibrated against 30 years of PRISM (Parameter-elevation Regressions on Independent Slopes Model) climatology data. For example, Alta receives a larger precipitation boost from NW flow than from SW flow, matching its Little Cottonwood Canyon geography.

Snow-to-Liquid Ratio (SLR)

Corrected precipitation (in liquid equivalent) is converted to snowfall using the Kuchera method, which calculates SLR based on the temperature profile of the lower atmosphere. Colder storms produce higher SLR (fluffier snow), while warmer storms produce denser, wetter snow. Typical values range from 8:1 (heavy/wet) to 20:1+ (ultra-light powder).

Probabilistic Aggregation

The 31 ensemble members produce 31 different snowfall estimates for each resort and time step. We extract the 50th percentile (median/expected) and the 80th percentile (a realistic upper estimate) to form a one-sided probability estimate: low is a fixed 0", since snowfall can't be negative, and high is the 80th percentile. The gap between the two shows how far the members spread above the median. That spread is the model's own; how often reported snowfall actually stays under the high estimate is measured separately, per lead time (see below).

Verification & Accuracy Tracking

The range we show is scored against the 24-hour snowfall each resort reports, the number skiers actually see. The range we score is the one we showed at 5 pm resort time the day before, frozen so it can't be revised after the fact. We publish the measured share of days the report stayed within our range, together with how many snowy days that measurement rests on.

Forecasts are also checked against SNOTEL (SNOpack TELemetry) ground observation stations operated by the USDA Natural Resources Conservation Service, an independent physical measurement that does not depend on how a resort reports. We compute accuracy metrics at 1, 2, 3, 4, 5, 10 and 15-day lead times and publish them on each resort's accuracy page.

Data Sources

Source	Resolution	Update Frequency	Purpose
NOAA GEFS	0.25° (~25 km)	4x daily (00/06/12/18Z)	31-member ensemble for probabilistic forecasts
PRISM	800m	Climatology	Orographic correction calibration
Resort snow reports	Per resort	Daily	What the range is scored against
USDA SNOTEL	Point stations	Daily	Independent physical check

Accuracy Metrics

We track forecast performance using several complementary metrics:

Metric	What It Measures	Ideal Value
Accuracy %	How close the median forecast was to observed snow	100%
MAE	Mean Absolute Error in inches	0
Bias	Systematic over- or under-prediction tendency	0
RMSE	Root Mean Square Error (penalizes large misses)	0
Range Containment	% of days the resort's reported snowfall did not exceed our high (80th pct.) estimate	80% (target, not a claim)
Skill vs Climatology	1 − (our total absolute error ÷ the total absolute error of the historical average for those dates) over the window; not shown below 10 days, or when the historical average already misses by less than 0.1" a day	> 0

Notice, effective 15 November 2026: a resort's "last 24 hours" snow report is a window that ends when it is posted, so a report posted in the morning describes mostly the previous day. From 15 November 2026 we pair each snow report with the day it describes when we measure Range Containment, and the season-to-date count on this site restarts on that date. Until enough North America reports have been scored, the figures show "not enough days" rather than a number.

How we state range containment: 80% is what the range is built to achieve, not something we claim until it has been measured. Until a lead time's range has passed our pre-registered calibration check, we show only the measured share so far this season, with the number of snowy days behind it. Below 10 snowy days we show no percentage at all, because a handful of storms can't support one.

Why a probabilistic estimate matters: Single-point forecasts give a false sense of precision. Our high (80th pct.) estimate shows how much more snow the ensemble members allow for beyond the median. A high estimate close to the median means the members mostly agree; a much higher one means some of them bring a lot more snow. Members agreeing is not the same as the forecast being right: whether reported snowfall stays under the high estimate as often as it should is the measured share described above, and we don't grade a forecast's confidence any other way. More snow than the high estimate can fall.

Orographic Correction Details

Each resort has a unique set of wind-direction-dependent precipitation multipliers. These account for the fact that mountains preferentially enhance precipitation when moisture-laden air flows from certain directions. The multipliers were calibrated by comparing GEFS raw QPF against PRISM's 30-year, terrain-aware precipitation climatology at each resort's coordinates.

For example, a resort in a west-facing canyon will see greater orographic enhancement from westerly flow (multiplier > 1.0) and less from easterly flow. These corrections are critical for mountain forecasting accuracy and are one of PowCall's key differentiators.

Covered Resorts

PowCall currently covers 120 Epic and Ikon Pass ski resorts across 31 states and provinces:

Region	Resorts
Utah	Alta, Brighton, Deer Valley, Park City, Powder Mountain, Snowbasin, Snowbird, Solitude
Colorado	Beaver Creek, Breckenridge, Crested Butte, Keystone, Loveland, Monarch, Vail, Arapahoe Basin, Aspen Snowmass, Copper Mountain, Eldora, Winter Park, Steamboat, Telluride
California	Big Bear Mountain Resort, Heavenly, June Mountain, Kirkwood, Mammoth Mountain, Northstar, Palisades Tahoe, Sierra-at-Tahoe, Snow Valley, Squaw/Alpine (Base), Sugar Bowl
Pacific Northwest	Crystal Mountain, Mt. Bachelor, Mt. Hood Meadows, Stevens Pass, The Summit at Snoqualmie
Wyoming	Grand Targhee Resort, Jackson Hole
Montana	Whitefish, Big Sky, Bridger Bowl
Idaho	Schweitzer, Brundage Mountain, Sun Valley
New Mexico	Taos Ski Valley
Alaska	Alyeska Resort
British Columbia	Revelstoke, Whistler Blackcomb, Cypress Mountain, Fernie Alpine Resort, Kicking Horse, Kimberley Alpine, Panorama Mountain Resort, RED Mountain Resort, SilverStar Mountain Resort, Sun Peaks Resort
Alberta	Banff Sunshine Village, Lake Louise Ski Resort, Marmot Basin, Mt. Norquay, Nakiska
New England	Attitash, Crotched Mountain, Jay Peak, Killington, Loon Mountain, Mount Snow, Mount Sunapee, Okemo, Stowe, Stratton, Sugarbush, Sugarloaf, Sunday River, Wildcat Mountain
New York & Mid-Atlantic	Big Boulder, Blue Mountain Resort, Camelback Resort, Hidden Valley, Hunter Mountain, Jack Frost, Laurel Mountain, Liberty Mountain, Roundtop, Seven Springs, Snowshoe Mountain, Whiteface, Whitetail
Midwest	Afton Alps, Hidden Valley, Snow Creek, Alpine Valley, Boston Mills, Boyne Highlands, Boyne Mountain, Brandywine, Granite Peak, Lutsen Mountains, Mad River Mountain, Mt. Brighton, Paoli Peaks, Snowriver Mountain Resort, Wilmot Mountain
Eastern Canada	Blue Mountain, Bromont, Le Massif de Charlevoix, Mont Sainte Anne, Stoneham, Tremblant
Australia	Perisher, Thredbo, Falls Creek, Hotham, Mt Buller
New Zealand	Mt Hutt, Coronet Peak, The Remarkables
Chile	Valle Nevado

Transparency Commitment

PowCall is built on a commitment to forecast transparency. We:

Publish probabilistic ranges, not just single numbers
Score our range against what resorts report, and check forecasts against independent SNOTEL observations
Show accuracy by lead time so you know how much to trust each day's forecast
Show no confidence grade we haven't measured: the range and its track record are the uncertainty we state
Track accuracy over 7-day, 30-day, and seasonal windows
Rank resorts by forecast accuracy on a public leaderboard