Snowfall pattern discovered that could change forecasting forever

Snow shapes the rhythm of life across the Western United States. It feeds rivers, supports winter travel, and draws people to high slopes each year. Yet the same snow creates uncertainty because storms change from ridge to ridge.

Forecast teams often work with rough estimates rather than clear numbers. The region’s jagged terrain scatters clouds, redirects wind, and reshapes temperature patterns. This creates tiny pockets of weather that confuse standard tools.

Scientists now search for better ways to read these shifting patterns, and they have turned to a rich source of mountain data to do so.

Changing snowfall patterns

Snowfall forecasts in the West often come as wide ranges because the snow-to-liquid ratio shifts sharply from place to place.

“If you don’t have a good snow-to-liquid ratio, your snowfall forecasts are not going to be as good,” noted Peter Veals of the University of Utah, the study’s first author.

The ratio decides how much water hides inside each inch of snow. In this region, that number can swing from very dense slush to powder that barely weighs anything.

These rapid changes frustrate forecasting teams who want clear values for each storm cycle.

Factors that affect snowfall

Veals and his colleagues learned that snow water equivalent (SWE) shapes the ratio more than anything else. Storms with high SWE produce snow that compresses under its own weight.

“It’s because the more SWE you have, the more the storm’s snow weighs and it densifies itself. It compacts under its own weight,” explained Veals.

Other forces also play roles. Elevation shifts temperature. Wind reshapes drifting snow. Moisture levels guide crystal formation.

Together, these elements create a sliding scale of density that cannot rely on the common 10 to 1 value.

“Somebody cooked that up in some place a long time ago. It’s easy to use. It’s just multiplying by 10,” said Professor Jim Steenburgh. That simple rule rarely matches Western storms.

How the data was collected

To build a model suited for the region, the Utah team gathered snowfall information from 14 mountain sites.

These locations stretch across Utah, Colorado, Idaho, Wyoming, Montana, the Cascades, and the Sierra Nevada.

Avalanche safety teams and highway crews already collect detailed observations at these places. Their work gave the researchers a strong data base shaped by real mountain patterns.

Each site sees storms that behave differently because of slope angle, canyon shape, and local wind behavior.

Why manual work matters

Manual measurements proved essential because automated tools often misread snowfall during windy periods. Trained workers visited each site daily or twice daily during storms.

They recorded snow height, weighed water content, and cleared boards for the next reading. “There’s a bit of a mad scientist component to this,” Steenburgh said.

“You have to be more meticulous than the average person to do this work,” Veals said. Ski patrol teams follow these steps to protect avalanche paths, so their data has high quality.

Models for snowfall forecasts

The scientists used these detailed records to train new machine learning systems. They added weather factors such as temperature, wind speed, and specific humidity.

One method, known as a random forest, performed especially well. It explained nearly half of the variation in snow density. Current tools explain less than a quarter.

Veals noted that another system worked slightly better but demanded ten times the computing power.

“You need to run this stuff on a huge data set every six hours and you need it to be done in two minutes,” he said. Speed matters when storms move quickly across the region.

New era of snowfall forecasting

The new model offers clearer snowfall predictions for the Western states. It helps water managers understand how much water each storm adds to seasonal supplies.

This information supports better planning during dry years and wet years. It also helps cities prepare for changing runoff patterns in spring.

Highway teams gain safer planning tools for winter traffic. Crews can decide when to treat roads or close dangerous routes.

Avalanche forecasters receive better guidance on snow structure. They can judge when slopes may weaken or shift. Weather teams across the region benefit from readings that fit the terrain rather than broad national rules.

As the method expands toward a study of snowfall at 900 sites across the continental United States, the work may shape a new era of mountain forecasting.

Better predictions can support families, travelers, farms, and entire communities. This research offers a path toward clearer winter guidance for people who depend on accurate information.

The study is published in the journal Weather and Forecasting.

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