Snowfall data is trickier than temperature or rainfall for a simple reason: snow doesn’t fall everywhere. A temperature station in Florida still records temperatures. A precipitation gauge in Phoenix still measures the occasional monsoon rain. But a weather station in southern California will report zero snowfall year after year—that’s accurate data, just not very interesting.
This creates practical problems when you’re trying to analyze historical snowfall by zip code. You need to distinguish between “no data available” and “no snow fell.” You need stations that reliably report snowfall, not just precipitation that might sometimes include frozen forms. And you need to account for the huge variation in snowfall within relatively small geographic areas—Buffalo gets buried while Rochester, 70 miles east, gets half as much.
Who Uses Historical Snowfall Data?
Retailers and distributors are the most common customers. Snow shovels, ice melt, winter apparel, and automotive accessories like wiper blades and batteries all see demand that correlates with actual snowfall—not just cold temperatures. A cold but dry winter means different buying patterns than a snowy one.
Insurance companies use snowfall history for underwriting and claims. A roof collapse claim is easier to evaluate when you know the zip code received 28 inches of heavy wet snow the week before. Property insurers in the Northeast and Mountain West pay close attention to historical snow loads.
Municipal planners and contractors need snowfall records for budgeting salt and plow services, designing drainage systems, and building code compliance. Structural engineers reference historical snow loads when designing roofs—a barn in Minnesota faces different requirements than one in Tennessee.
Ski resorts and tourism businesses analyze snowfall patterns to understand their best and worst seasons, market to regions that get less natural snow, and make capital investment decisions.
The Challenge with Snow Measurement
Snow measurement isn’t as straightforward as it sounds. NOAA stations report both snowfall (how much fell during a period) and snow depth (how much is on the ground at observation time). These tell you different things.
Six inches of snowfall doesn’t mean six inches of snow on the ground—some melts, some compacts, some blows away. Conversely, a foot of snow depth doesn’t tell you whether it fell in one storm or accumulated over two weeks. For most business applications, cumulative snowfall totals over a period (monthly or seasonally) are the most useful metric.
Station coverage is another complication. Not every weather station measures snowfall. The GHCN-Daily network includes thousands of stations, but snowfall reporting is inconsistent—especially outside traditional snow belt regions. We use stations with reliable multi-year snowfall records and flag zip codes where the nearest reporting station is far away.
What Our Snowfall Datasets Include
Our monthly snowfall by zip code dataset covers 10 years of records for all US zip codes, delivered in Excel or CSV format. Each row shows a zip code, month, and total monthly snowfall in inches. Zip codes in regions with minimal snowfall will show zeros—which is useful information for logistics and planning.
We also include a reference file mapping each zip code to its assigned weather station, with the distance between them. In snow country, station density is typically good—most zip codes have a reporting station within 10-15 miles. In transitional zones where snow is rare but possible, stations may be further away.
For users who need daily resolution—tracking individual storms or verifying specific dates—we offer daily snowfall data with the same coverage and format.
Regional Considerations
Lake Effect Zones
The Great Lakes create extreme local variation. Syracuse averages over 120 inches annually while Rochester—70 miles away—gets about 100 inches. Cleveland’s east side gets hammered while the west side stays relatively clear. Zip-code-level data captures these differences in ways that city or county averages cannot.
Mountain West
Elevation drives snowfall more than latitude in Colorado, Utah, and the Sierra Nevada. A ski resort at 10,000 feet might get 300+ inches while a town in the valley 20 miles away gets 60 inches. Our data assigns each zip code to the most appropriate station given its elevation and location.
Transition Zones
The mid-Atlantic and parts of the Midwest sit in zones where snow totals vary dramatically year to year. Washington DC might get 3 inches one winter and 30 the next. Historical data helps distinguish between genuine trends and random variation—useful for anyone making multi-year plans.
Combining Snowfall with Other Weather Data
Snowfall data is most valuable when combined with temperature records. Heavy snow followed by a warm spell means flooding risk. Consistent cold with moderate snow means accumulation. Snow that falls and melts the same day has different retail implications than snow that sticks for weeks.
We offer bundled packages that include temperature, precipitation, and snowfall data for customers who need the complete picture. This is common for demand forecasting applications where winter weather affects multiple product categories differently.
Pricing and Availability
Our snowfall datasets start at $99.95 for average monthly snowfall by zip code. The 10-year monthly time series is $599.95. Both cover all US zip codes and are delivered as ready-to-use Excel or CSV files.
For custom date ranges, daily data, or packages combining snowfall with temperature and precipitation, contact us for a quote.
Not sure if our coverage meets your needs? Request a free sample showing the format and a subset of zip codes in your region.
