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Local researchers use citizen science to predict fire-generated tornadoes

Smoke is overhead a large lake with lots of pine trees in the foreground and mountains in the background.
University of Nevada, Reno ALERTWildfire program
Smoke from the Caldor Fire over South Lake Tahoe, Calif., in Aug. 2021.

With an increase in deadly wildfires, local researchers are collecting data from residents in order to study extreme weather events, such as fire-generated thunderstorms and tornadoes.

Fire-generated tornadoes can produce winds of up to 140 miles per hour, posing a large threat to lives and property.

“This is something we've seen increasingly over the last five to 10 years here in the Western United States,” said Neil Lareau, an atmospheric scientist at the University of Nevada, Reno.

Lareau hopes to build predictive models in order to create warnings that will give residents and firefighters the necessary information to stay out of danger.

“That requires us to obtain these radar data for large fires and to go back and try to understand what those data are showing us. Part of the mystery is we don’t fully understand what those radar data are showing us,” said Lareau.

That’s why the project involves crowdsourcing data, such as photos of what’s called ashfall.

“When there is ash that’s actively falling from a wildfire, you can share photos of it, and those photos are then going to be used to inform the models,” said Meghan Collins, an environmental scientist from the Desert Research Institute.

Since the beginning of data collection last year, nearly 20,000 people have contributed to the project.

Nick Stewart is a senior studying at the Academy of Arts, Careers and Technology.

Nick Stewart is a student reporter for KUNR and is studying journalism at the Reynolds School of Journalism at the University of Nevada, Reno.
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