This winter was ; as a result, many snowy, alpine areas have seen bouts of winter rainfall where there would ordinarily only be snow. These unusual weather patterns have contributed to an abysmal ski season, but they can also set the stage for dangerous avalanches. At temperatures close to freezing, precipitation can fall as rain but freeze when it hits the snow, forming an icy crust. Snow that accumulates on top of that crust is unstable and prone to abrupt slides, causing an avalanche that can close down a major highway in moments, endanger backcountry skiers and more.

Avalanche experts in Western Washington know how to manage the risks associated with rain-on-snow events, but many of their counterparts in colder regions like Eastern Washington, Idaho and Montana are less familiar with these dynamics. New research from the 91̽�� shows that as winters in these regions warm, their snowpacks may come to resemble those of maritime areas, with more rain-on-snow events, icy crusts and complex avalanche forecasting. 

The findings in ARC Geophysical Research.

“This winter’s warmth is a harbinger,” said lead author , a 91̽��graduate student of civil and environmental engineering. “We know that temperatures will keep rising, and our work is a red flag for cooler regions of the greater Pacific Northwest, such as Idaho and Western Montana, that aren’t used to dealing with ice crusts and their resulting avalanche problems.”

The study is part of a larger effort to understand the structure of snow as it accumulates, which has implications for weather and avalanche forecasting, wildlife dynamics and more. 

“Snow scientists are pretty good at measuring snow depth and volume,” said senior author , a 91̽��professor of civil and environmental engineering. “We’re also pretty good at figuring out how much water you get if all that snow melts. But our models aren’t as good at representing snow structure, such as layers of different densities and crystal types that increase avalanche risks. And we really want to know how the structure of snow changes as the climate changes. That’s a tricky question that no one has tackled, particularly for rain-on-snow conditions.”

To dig into that question, the researchers studied how warming influences ice layer formation in seasonal snowpacks. First, they collected temperature and precipitation data captured by 53 monitoring stations across the Pacific Northwest for the past 25 years. They used a computer model to identify days when ice layers likely formed at each location. They then checked the model against real-world measurements at one of the locations — a station at Snoqualmie Pass — and found that the model matched the measurements with 74% accuracy.

Finally, they used the same model to simulate those same 25 winters at 2 C and 4 C warmer than they were, and looked for changes to the number of ice crusts across the region. , the Pacific Northwest is expected to warm by 2 C to 5 C by 2050 as compared to pre-2000 temperatures.

The results were split regionally by the Cascade mountains. In colder, inland parts of the Pacific Northwest — places like Eastern Washington, Idaho and Montana — higher temperatures created more rain-on-snow days and more avalanche-prone ice layers. Locations in the warmer, maritime Cascades saw the opposite effect: Higher temperatures created slush instead of ice, potentially reducing the avalanche risk associated with ice crusts. 

The predicted snowpack changes may also impact wildlife behavior. Some foraging mammals, such as reindeer, dig down into the snow in search of food and may have a hard time breaking through an icy crust. Conversely, firm ice might provide a better running surface for animals fleeing predators. Specific regional effects will require additional study.

What’s clear now is that those who work or play in avalanche terrain in broad swaths of the Pacific Northwest — and even beyond — may need to adjust to a new set of risk factors.

“I’d love to see this shared with avalanche forecasters widely, both as a call to action and as a way to help them understand what their snowpack might look like in the future,” Alden said.

, the director of geospatial science at Audubon Alaska and former doctoral student of environmental and forest sciences at the UW, is a co-author.

This research was funded by the NASA Interdisciplinary Research in Earth Science program and the 91̽��Program on Climate Change’s Graubard Fellowship.

For more information, contact Alden at cdalden@uw.edu.

The Colorado River and its tributaries . Much of this water comes from the snowpack that builds up over the winter and then melts each spring. Every year in early April, water managers use the snowpack to predict how much water will be available for the upcoming year.

But since 2000, these predictions have been incorrect, with the actual streamflow being consistently lower than the predicted streamflow. That’s left water managers and researchers flummoxed — where’s the water going?

The problem lies with the lack of rainfall in the spring, according to new research from the 91̽��. The researchers found that recent warmer, drier springs account for almost 70% of the discrepancy. With less rain, the plants in the area rely more on the snowmelt for water, leaving less water to make its way into the nearby streams. Decreased rain also means sunny skies, which encourages plant growth and water evaporation from the soil.

The researchers Aug. 16 in Geophysical Research Letters.

“The period of time when we were wondering, ‘Oh no, where’s our water going?’ started around the same time when we saw this drop in spring precipitation — the beginning of the ‘Millennium drought,’ which started in 2000 and has been ongoing to the current day,” said lead author , a 91̽��doctoral student in the civil and environmental engineering department. “We wanted to focus on the cascading consequences of this. Less springtime rain means you likely have fewer clouds. And if it’s going to be sunny, the plants are going to say, ‘Oh, I’m so happy. The snow just melted and I have a ton of water, so I’m going to grow like gangbusters.’ This research really centers the importance of studying the whole snow season, not just when the snowpack is the deepest.”

Hogan and senior author , a 91̽��professor of civil and environmental engineering, studied this phenomenon as part of a . At first, the researchers wondered if the snowpack was decreasing because the snow was simply turning into water vapor — a process called sublimation. But the team , meaning something else was the main culprit.

“There are only so many possible culprits, so I started to compare things that might be important,” Hogan said. “And we saw that springtime changes are a lot more exaggerated than they are in other seasons. It’s this really dramatic shift where you’re going from feet of snowpack to wildflowers blooming over a very short amount of time, relatively speaking. And without spring rains, the plants — from wildflowers to trees — are like giant straws, all drawing on the snowpack.”

The researchers looked at springtime changes in 26 headwater basins at various elevations in the Upper Colorado River Basin. To paint a picture of what was happening at each basin over time, the team used a variety of datasets, including streamflow and precipitation measurements dating back to 1964. The researchers then modeled how much water the plants at each basin would likely consume.

“We make an important assumption in the paper,” Hogan said. “We assume that the plants have an unlimited amount of water even with less-than-average precipitation, because they have access to snowmelt.”

All the basins the team studied showed reduced streamflow without springtime rain. But basins at lower elevations had an even more pronounced deficit in streamflow. This is because the snow at these basins is likely to melt earlier in the season, giving the plants more time to grow and consume the snowmelt, the researchers said.

Now that spring rain has been identified as the main culprit, the researchers are working to further refine their understanding of what’s happening during this season. For example, one project is investigating whether residual patches of snow are acting as mini-reservoirs that can provide a constant stream of water to nearby plants.

Regardless, the longer the Millennium drought continues, the more these results will affect the water calculations that happen each April.

“April is when everybody wants to know how much water is in the snowpack each year,” Lundquist said. “But the problem with doing these calculations in April is that obviously spring hasn’t occurred yet. Now that we know spring rain is actually more important than rain any other times of the year, we’re going to have to get better at predicting what’s going to happen rainwise to make these April predictions more accurate.”

In this video, Jessica Lundquist gives more background on this project

This research was funded by the National Science Foundation, the Sublimation of Snow Project and the Department of Energy Environmental System Science Division (the Seasonal Cycles Unravel Mysteries of Missing Mountain Water project).

For more information, contact Hogan at dlhogan@uw.edu and Lundquist at jdlund@uw.edu.

As climate change warms the planet, weather patterns are likely to shift. Even the consistency of snow — how fluffy it is, for example — could change.

, a wildlife ecologist and 91̽�� associate professor in the School of Environmental & Forest Sciences, wants to know how these changing conditions will affect how predators hunt prey.

“When you wear snowshoes in deep snow, you stay on top of the snow. But if you take the snowshoes off, you might go in up to your waist. Certain species, such as wolves and lynx, have adapted to deep snow conditions because their feet act like snowshoes,” Prugh said. “But their prey, such as caribou and moose, are heavier and have hooves instead of paws, so they sink in more. As climate change is making things warmer and changing the amount of precipitation, it’s going to affect how deep and hard the snow is. And that’s going to affect how deep the animals are sinking into the snow. Few scientists have looked at this before.”

To answer this question, Prugh needed a snow expert. She teamed up with , a 91̽��professor of civil and environmental engineering. Together with a group of researchers, the two measured snow properties that led to a “danger zone,” where prey would sink but predators would not. In a recent paper, the team defined .

The first step was to figure out how to measure changes in the snow that would affect animals’ ability to stay on top of the snow.

“Imagine having a snow fort — you’ve got this cave under the snow and it has a roof. And when people run on top of your snow fort, you hope it doesn’t collapse on you, right? This is what we are trying to measure: the strength of the snow to support itself against collapsing,” Lundquist said. “But snow is such a dynamic thing. It’s not even one phase; you can’t call it a solid, liquid or gas. It’s all of the above, and that makes snow really fun to study.”

The researchers used snow density as a proxy for its strength. Denser, more tightly packed snow, they reasoned, would be more likely to hold up an animal, compared to light, fluffy “powder skiing” snow.

To test this theory, the team traveled through Denali National Park and the Methow Valley via snowmobile or on cross-country skis in search of animal prints in the snow. Upon finding tracks, the researchers could then investigate the density and other properties of the surrounding snow.

Both Prugh and Lundquist agreed that one of the best parts of the collaboration was being able to learn from each other — Prugh learned to appreciate different types of snow, and Lundquist learned how to identify different animal tracks. The researchers also enjoyed working outside.

“There’s this where Calvin’s standing in front of his class holding a box of water. And he says, ‘this was a snowflake outside,'” Lundquist said. “It’s unique and exquisite, but when you bring it into the classroom, it melts. The science is outside. You cannot bring snow inside and have the same characteristics as the snow outside.”

For more information, contact Prugh at lprugh@uw.edu and Lundquist at jdlund@uw.edu.

Spring break can be a good time for ski trips — the days are longer and a little warmer. But if people are booking their spring skiing trips the fall before, it’s hard to know which areas will have the best snow coverage later in the season.

Researchers who study water resources also want to know how much snow an area will get in a season. The total snowpack gives scientists a better idea of how much water will be available for hydropower, irrigation and drinking later in the year.

A team led by researchers at the 91̽�� has found that in some western states, the amount of snow already on the ground by the end of December is a good predictor of how much total snow that area will get. This prediction works well in northern states such as Alaska, Oregon and Washington, as well as in parts of Utah, Wyoming and Colorado. Other states, such as California, Nevada, New Mexico and Arizona, were harder to predict — these regions either had too much variation in their weather patterns and/or got the most of their precipitation after December.

The researchers Sept. 12 in Geophysical Research Letters.

“The main thing water managers are asking for — aside from making it snow more, which is usually everyone’s first request — is longer lead-time forecasts,” said senior author , 91̽��professor of civil and environmental engineering. “These are hard predictions to make. We’re fairly good at long-term average forecasts: what will happen 50 years from now. And we can do short-term forecasts: what will happen less than a week from now. But as for what’s going to happen in the next three to four months, that’s been kind of a no-go zone. It was really interesting to find that the amount of snow on the ground by the end of December ended up being a good predictor of peak spring snow.”

To look for trends, the team collected data from a across the western U.S., including Alaska. The researchers analyzed air temperature and accumulated precipitation from 2001 to 2022 for 873 sites. Then the team compared accumulated snow by the end of December (fall snow) to the maximum amount of snow accumulated over the entire winter-spring season (peak season snow).

There were a few different reasons for why fall snow levels predicted peak season snowpack levels. Some areas, such as Alaska, simply receive most of their snow before January. This means their early season snow is close to their peak season snow.

In other places, including Interior Alaska, northeast Utah and southwestern Wyoming, the weather patterns are such that above-average snowfall earlier in the season indicates above-average snowfall is also likely later in the season.

Cooler air temperatures also helped with predictability. In northern states — such as Alaska, Washington and Oregon — or in places at higher elevation, snow on the ground in the fall was less likely to melt between storms because the air remained cool. That means this snow will stick around and add to the total snowpack.

“Another really interesting pattern happens in Oregon and Washington,” Lundquist said. “We get mixed rain and snow all along the west slope of the Cascades. This ‘wintry mix’ is so close to freezing that it could freeze or melt when it hits the ground. If you have above-average snowpack early in the year, then the wintry mix will stick to that snowpack and add to it. But if you have a below-average snowpack, that wintry mix is more likely to melt that snowpack and actually decrease it.”

When it comes to how climate change will affect which areas are predictable, the results are mixed, Lundquist said. Places that are farther north or at higher elevation are colder to start with, meaning they might not see much change.

But some weather patterns are shifting north. Areas where the prediction works now — such as northern Oregon — might go the way of California, having weather that’s too variable for any prediction.

It’s going to be important to continue tracking these trends, Lundquist said.

“These snow sensors are in long-term stations, so it’s easy to get the most recent data every year,” Lundquist said. “And then it’s just a simple analysis to predict which areas will likely have the largest snowpack. Though, as my family reminds me, it unfortunately does not let me predict powder days.”

Additional co-authors are , 91̽��professor of environmental and forest sciences; at the National Oceanic and Atmospheric Administration; and at The Ohio State University. This research was funded by NASA. Lundquist wrote this paper during sponsored by the 91̽��ADVANCE Center for Institutional Change.

For more information, contact Lundquist at jdlund@uw.edu.