A framework for conducting and communicating probabilistic wildland fire forecasts

However, there is a need to know how confident users can be in forecasts. This work developed a probabilistic methodology based on ensemble simulations that incorporated uncertainty in weather, fuel loading, and model physics parameters.

It provided information on the most likely forecast scenario, confidence levels, and potential outliers. It also introduced novel ways to communicate uncertainty in calculation and graphical representation and applied this to diverse wildfires using ensemble simulations of the CAWFE coupled weather–fire model ranging from 12 to 26 members. The ensembles captured many features but spread was narrower than expected, especially with varying weather and fuel inputs, suggesting errors may not be easily mitigated by improving input data.