If you want to understand how fire works, then you have to burn stuff. That’s where Ruddy Mell comes in. He’s a research combustion engineer and physicist at the U.S. Forest Service’s Pacific Wildland Fire Sciences Lab. Mell’s job is to work with teams of fire experts to create controlled burns, collect all the data they can, and then build physics-based models that can predict what could happen when seriously dangerous fires burn out of control. Mell talked with us about why our current wildfire models are so insufficient and how they go about trying to control the world’s most unpredictable element out in the field.
Why do we need to study wildfires?
At least three reasons. Two of them are kind of combined. They have to do with fires in the wildland and urban interface, where wildland vegetation is adjacent to where people live and fire causes damage to homes and roads and power lines and cell towers -- anything that people have built that causes enough damage that the consequences need to be addressed.
The other problem is smoke. That’s a significant problem. Even if it doesn’t burn buildings the smoke is a problem if people are downwind. The health effect has been shown to cause increased hospital visits for respiratory problems. In some parts of the country, the southeast in particular where there are a lot of old people that are retired, it can be a big problem.
Also in the southeast US the vegetation tends to grow back very quickly, so they have to deal with this smoke issue because the vegetation is there to burn. One of the ways they deal with fires there is to do fuel treatments, where fuel is vegetation. They’ll burn it periodically just to keep it down so it will be easier to contain if there’s a wildfire. They’re limited in doing prescribed fires because of all the people around. They want to do this to keep it safe, but it’s hard to do.
So the wildland fire problem is a fire problem, a vegetation problem, and smoke problem. To address the problem you have to think about all that. When modelling comes in, you need models for fire and better models for smoke.
The purpose of these research burns is to provide data sets for model testing and validation and development. The best example of a model that’s used by people everyday are weather models. Imagine the world if we couldn’t look up the forecast. You can’t use experiments alone to help with weather predictions. Suppose you go out and measure temperature and wind at some site, there’s no guarantee it will be like that a year from now. You need models to help predict out into the future.