Still, advances in computing are allowing researchers to crunch ever more data. At Los Alamos National Laboratory, atmospheric scientist Alexandra Jonko is using a supercomputer and a system called FIRETEC to model fires in extreme detail. It models, among other things, air density and temperature, as well as the properties of the grass or leaves in a particular area.
Jonko runs a bunch of simulations with different wind speeds, typically on the scale of 40 acres. “It’ll probably take me about four hours to simulate between 10 and 20 minutes of a fire spreading,” she says.
FIRETEC produces valuable physics-based data on fire dynamics to inform how fire managers do prescribed burns. This is pivotal for controlling vegetation that turns into fuel for fires. Wildfire agencies know generally the ideal conditions—low winds, for instance—but this type of modeling could help give even more granular insight.
To figure out where to do these burns, researchers are experimenting with lidar, the same kind of laser-spewing technology that helps self-driving cars find their way. This comes in the form of airborne lidar, which lets researchers visualize trees in 3D, supplemented with ground-based lidar, which details the vegetation underneath the trees.
That information is essential. “If we don’t know what the fuels are, then it’s a pretty big guess whether or not you’ve got dangerous fuels at a site,” says the University of Nevada, Reno’s Jonathan Greenberg.
The visualizations that come from lidar blasts are as stunning as they are useful. With this kind of data in hand, managers can more strategically deploy prescribed burns. California in particular has a serious problem with fire resources—in just the last year, the state has seen seven of its 20 most destructive fires ever. Money, then, goes to constantly fighting the infernos, leaving fewer resources for proactive measures like prescribed burns.