Once a wildfire has begun, it is difficult to predict how it will evolve over time. Researchers tackle the challenge of forecasting wildfire growth, change, and smoke behavior in a new study supported by the Climate Program Office’s Atmospheric Chemistry, Carbon Cycle and Climate (AC4) Program. AC4- funded scientist Pablo Saide of the University of California, Los Angeles, worked with an international team of researchers to compare simple methods that are typically used in forecasting to a more complex modeling approach. This project was supported by the AC4 Program to improve our understanding of emissions from biogenic sources like wildfires.
As a case study, the researchers focused on the Williams Flats Fire, the largest fire sampled in the 2019 joint NOAA- and NASA-led FIREX-AQ (Fire Influence on Regional to Global Environments and Air Quality 2019) field campaign. They compared satellite and aircraft observations and forecasting methods that are currently in use with a model that takes both wildfire and weather conditions into account. The results, published in JGR Atmospheres, show that the biggest improvement in fire prediction happens when the model includes firefighting efforts. When the model also accounts for how much fuel, like dead leaves, is available to the fire, and how much moisture is in that fuel, the model consistently generates better forecasts than other methods. This work helps to alleviate some of the difficulty of forecasting wildfires, by identifying the most important factors to include in modeling.
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