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How Supercomputers Can Help Fix Our Wildfire Problem


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A wildfire burns on a hillside.

At Los Alamos National Laboratory, atmospheric scientist Alexandra Jonko is using a supercomputer and a system called FIRETEC to model fires in extreme detail.

Credit: David McNew/Getty Images

Fire is chaos. Fire doesn't care what it destroys or who it kills—it spreads without mercy, leaving total destruction in its wake, as California's Camp and Woolsey fires proved so dramatically this month.

But fire is to a large degree predictable. It follows certain rules and prefers certain fuels and follows certain wind patterns. That means its moves with a complexity that scientists can pick apart little by little, thanks to lasers, fancy sensors, and some of the most powerful computers on the planet. We can't end wildfires altogether, but by better understanding their dynamics, ideally we can stop a disaster like the destruction of Paradise from happening again.

You could argue that a wildfire is the most complicated natural disaster, because it's both a product of atmospheric conditions—themselves extremely complex—and a manipulator of atmospheric conditions. So for instance, California's recent fires were driven by hot, dry winds coming from the east. These winds dried out vegetation that was already dry due to lack of rainfall, fueling conflagrations that burn more intensely and move faster.

But wildfires also create their own weather patterns. Blazes produce hot air, which rises. "You can imagine that if something moves from the surface up, there must be some kind of horizontal movement of air filling the gap" near ground level, says Adam Kochanski, an atmospheric scientist at the University of Utah. Thus the fire sucks in surface winds.

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