Texas Tech researcher is working to develop new means of predicting and communicating fire weather danger.
During the first five months of 2022, more than 800 wildfires scorched approximately 400,000 acres across Texas. Developing an improved tool to help forecasters assess fire weather conditions and more clearly communicate them is the objective of a Texas Tech University researcher.
Brian Ancell, an associate professor in the Department of Atmospheric Science, is working with the National Weather Service and several other collaborators to bring this product to life following a $500,000 grant from the National Oceanic and Atmospheric Association (NOAA).
“The grant involves fire weather prediction in terms of the atmospheric conditions that support wildfires,” he said. “The way it is done now is a bit unorganized because there are several different indicators forecasters can use, and that's because there has been no standardized way developed for predicting and forecasting fire weather.”
Ancell, who has worked at Texas Tech for 13 years, wants to change that. He and Todd Lindley, the science and operations manager at the National Weather Service Forecast Office in Norman, Oklahoma, are leading the effort.
“In general, the conditions that favor wildfire growth and spread are essentially temperature, wind speed and relative humidity,” Ancell said. “So, the worst conditions for fire to spread is hot, really dry and really windy.”
Compounding this are conditions on the ground, which include how moist an area is as well as the fuels present (for example, dead plant matter) that can support fire spread and growth.
The idea is to assess other products available to forecasters with the goal of pulling together the best aspects of each to create what would become a gold standard to be used by the National Weather Service in dispatching alerts to its offices across the country.
“The other products don't have probabilities,” Ancell said. “Those products say whether fire weather is likely or not, but weather forecasting is inherently probabilistic, and the right way to do weather forecasting is to give probability. So, for example, you might say our best guess for the high temperature today is 75, but the range could be between 72 and 78 because the truth is we don't know exactly what's going to happen. All we know is a range of possibilities, and that's what forecasters need.”
The second goal then becomes incorporating probability into fire weather prediction, providing a range regarding how likely wildfires are as well as how far they might spread. Ultimately, the product would be used by the Storm Prediction Center, which would communicate fire probability regarding areas where fire danger is greatest nationally, and individual forecast offices, which can communicate more closely with local organizations and the general public – similar to how tornado and thunderstorm watches and warnings are issued.
The grant covers a three-year period, which broadly speaking, breaks down with the first year devoted to data collection, the second year to product development and the third year to product testing.
“Success would mean that what we develop gets used operationally by the National Weather Service,” he said. “I don't think that will happen in just three years, but afterward having something that works is better than what we have now means we are on the way to making it fully operational.”