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Snow is being melted by dust, but current models are unable to accurately predict this phenomenon.


Brown dust darkens large areas of snow.

In the arid western region of the United States, the accumulation of snow in mountains plays a crucial role in providing water resources.

As temperatures gradually increase, the arrival of spring leads to the replenishment of rivers downstream. However, unpredictable changes in precipitation and temperature due to climate change have made it difficult to effectively manage this crucial water source. Experts caution that existing models for predicting snowmelt are outdated.

The existing models rely on statistical correlations that assume the future will resemble the past.

According to McKenzie Skiles, a snow researcher at the University of Utah, the existing models rely on statistical connections that assume the future will be similar to the past. However, this assumption is no longer dependable.

Skiles conducted research that was published in Environmental Research Letters, emphasizing the importance of dust as a crucial factor for snow forecasting models to adjust to the rapid changes in our world.

Cycles of Dusty Snow

Dust, being darker than the underlying snow, absorbs more energy from the Sun and speeds up snowmelt. Fast-melting snow is a problem because mountain snowpack shelters soil from the heat of the Sun, Skiles explained. When snow melts quickly, soil loses that protective blanket and dries out earlier in the season.

Brown dust darkens large areas of snow with a rectangular pit dug into the snow.

Scientists gathered information on the impact of dust on the melting of snow in the Wasatch Mountains. Credit: McKenzie Skiles

In 2021 and 2022, scientists observed a phenomenon in Utah where the Great Salt Lake reached its lowest water levels on record due to higher water usage and a long-lasting drought. This led to dust from the lake bed being blown onto the nearby Wasatch Mountains, which were covered in snow.

According to data published by Skiles and her colleagues in June 2023, the dust from the Great Salt Lake caused the snow in the Wasatch region to melt 17 days earlier during the 2022 snowmelt season.

According to Skiles, the landscape is arid, so any extra moisture is absorbed by the landscape instead of returning to the Great Salt Lake.

This process is a continuous loop: As the lake receives less water, the dry lakebed enlarges and increases the amount of dust blown onto the Wasatch snowpack. This cycle continues to repeat itself.

Skiles mentioned that these results support multiple investigations that were carried out between 2010 and 2018 in the Colorado Rockies. In the San Juan Mountains, strong winds carrying dust particles from the Colorado Plateau caused snow to melt 3-5 weeks earlier than usual, and this was found to be linked to inaccuracies in predicting when the snow would melt.

Improved Forecasts

To ensure timely flood alerts and efficient reservoir control, precise forecasts for snowmelt are necessary. The National Oceanic and Atmospheric Administration uses river models to estimate the rate of snowmelt and the volume of water that will enter rivers each year.

Although dust has a significant effect on the rate of snowmelt, most river forecasting models, including NOAA’s, do not consider it.

Hydrologists at the Colorado Basin River Forecast Center (CBRFC) are revising models in order to make adjustments.

A suggested approach is to increase the temperature input for the models, as this can mimic the effects of dust by adding a small amount of heat. John Lhotak, a hydrologist at CBRFC who was not involved in the Utah study, explained that these adjustments are informed by data from past dust events.

“Things keep shifting.”

According to Lhotak, there is a constant change happening, which is why it is necessary to revise the previous model. Climate change has caused changes in precipitation, temperature, and dust patterns. Lhotak further explained that when calibrating the model, one must take into account the ever-changing historical data.

Lhotak’s team is currently experimenting with a more interactive physical model that utilizes various factors, such as solar radiation, wind, humidity, and dust on snow, to accurately replicate the constantly changing snow conditions observed in real-time.

According to Lhotak, in the Colorado River Basin, each drop of water is valuable. Therefore, accurately predicting the water supply, down to the smallest decimal, is crucial for communities to prepare and adjust. This is our current focus and the reason why every drop is being carefully examined.

—Kara West (@karasmith_west), Science Writer

This work was created thanks to the assistance of the David Perlman Virtual Mentoring Program of the National Association of Science Writers.

Reference: West, K. (2023), Snow is being melted by dust – and current theories are insufficient, Eos, 104, https://doi.org/10.1029/2023EO230409. Published on October 25, 2023.

Text © 2023. The authors. CC BY-NC-ND 3.0

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