Modeling Firebrand Spotting in WRF-Fire for Coupled Fire–Weather Prediction

This study develops, implements, and evaluates the Firebrand Spotting parameterization within the WRF-Fire coupled fire–atmosphere modeling system. Fire spotting is an important mechanism characterizing fire spread in wind-driven events. It can accelerate the rate of spread and enable the fire to spread over streams and barriers such as highways. Without the capability to simulate fire spotting, wind-driven fire simulations cannot accurately represent fire behavior. In the Firebrand Spotting parameterization, firebrands are generated with a set of fixed properties, from locations vertically aligned with the leading fire line. Firebrands are transported using a Lagrangian framework accounting for particle burnout (combustion) through an MPI-compatible implementation within WRF-Fire. Fire spots may occur when firebrands land on unburned grid points. The parameterization is verified through idealized simulations and its application is demonstrated for the 2021 Marshall Fire, Colorado. The simulations are assessed using the observed fire perimeter and time of arrival at multiple locations identified from social media footage and official documents. All simulations using a range of ignition thresholds outperform the control without spotting. Simulations accounting for fire spots show more accurate fire arrival times (i.e., reflecting a better fire rate of spread), despite producing a generally larger fire area. The Heidke Skill Score (Cohen’s Kappa) for the burn area ranges between 0.62 and 0.78 for simulations with fire spots compared to 0.47 for the control. These results show that the parameterization consistently improves the fire forecast verification metrics, while also underscoring future work priorities, including advancing the generation and ignition components.