To ensure that wildfire models have the right data inputs, our scientists are developing a methodology that identifies blindspots in our network of weather stations, and providing a plan to pinpoint where additional stations are needed. 

In addition, our scientists have tested the benefits of an upper-air profiler—a device that measures winds above ground level—and determined that this technology could provide advance warning of the strong surface winds that can drive fast-spreading fires. 

Pyregence scientists are also running simulations to identify locations that are particularly vulnerable to dangerous fire weather conditions.

Finally, we’re analyzing historical wildfires to identify the weather conditions—including hyper-local factors—associated with large fires over the past two decades.