SAN DIEGO (KGTV) -- As wildfires become more common in California, researchers are working to develop better ways to predict their dangerous side effects and warn people in harm’s way.
Wildfire smoke is easy to see from space. It can stretch for hundreds of miles, blanketing nearby states, as was the case during California’s record wildfires in 2020.
Less than an hour of exposure to certain smoke particles can have health impacts.
But for years, there’s been one big flaw with satellite images: you couldn’t tell how high the smoke was from the ground.
Smoke high up in the atmosphere might appear on a satellite image, but it’s not necessarily harmful to people far below, explained Dr. Marcela Loría-Salazar, an assistant professor at the University of Oklahoma’s School of Meteorology. Smoke has the biggest impact on people when tiny particles dip close to the ground.
“This is a puzzle that has been taking more than 20 years to solve,” she said. “What we need actually to target is where the smoke is in the atmosphere.”
Dr. Loría-Salazar and collaborators at NASA found an algorithm based on geography and weather patterns that can accurately predict if the smoke is low enough to be dangerous.
Their data on California’s Rim Fire in August 2013 showed that far-flung communities in Nevada and Idaho were more affected by smoke than some areas much closer to the fire.
Once the smoke from a fire dies out, rain can trigger a type of deadly landslide called a debris flow.
“This is not the type of hazard you can outrun,” said U.S. Geological Survey researcher Dr. Matthew Thomas.
After a wildfire, just a short burst of heavy rainfall can unleash the fast-moving earth.
On-the-ground measurements and historical records can help forecast the risk of future landslides, he said, but researchers are working on new ways to assess dangers from the sky.
Landslides can happen months or even years after a fire, but forecasting them gets more challenging as time goes on and more vegetation grows back, he said.
Dr. Thomas and his collaborators found that by analyzing the color from satellite images, they could estimate how much vegetation is missing and build that into a formula with hydrologic data to predict the risk of a landslide years later.
A study inGeophysical Research showed the model worked well when tested against areas affected by the 2016 Fish Fire in the San Gabriel Mountains, but Dr. Thomas said the framework will need to be refined with more research before it’s used in an early warning system.