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Coupled atmosphere/fire models are recognized as an efficient and representative way to simulate wildland fire behavior at geographical-to-meteorological scales by representing the two-way interactions between the fire front propagation and the surrounding atmosphere. They rely on a rate-of-spread (ROS) parameterization to represent the fire front propagation speed with respect to environmental factors characterizing biomass fuel properties and moisture content, near-surface wind conditions and terrain slope. In actual wildfire events, these input parameters are only partially known and induce significant uncertainties in the coupled model predictions. To estimate the envelope of plausible wildland fire behavior for a given event, we aim at designing a perturbed-physics ensemble prediction capability based on a coupled atmosphere/fire model. To make the approach feasible, it is essential to identify the relevant subset of parameters to perturb to generate an ensemble of fire front positions and shapes. In the present study, we perform a global sensitivity analysis based on Sobol’ indices to rank the environmental factors by order of influence on the Balbi’s ROS parameterization, and thereby identify the parameters that contribute most to the variability of ROS. Results show the predominance of the near-surface wind speed on the ROS variability, followed by the leaf area index LAI, the ignition temperature T_i, the dead fuel moisture content M_d, the dead fuel particle mass density ho_d, and the fuel layer height e. Results also indicate that the sensitivity of each fuel parameter to the ROS is not constant with respect to the near-surface wind speed, and that the most influential input parameters differ between the head and the back of a fire. This indicates the importance of exploring the spatial and temporal dependencies of coupled model sensitivities in future work.

Wildfires result from complex physical, chemical and biological processes interacting over a wide range of spatial and temporal scales (Gollner et al., 2015). Understanding the fundamental processes driving wildfire behavior is a key point for predicting fire spread across the landscape and the induced atmospheric dynamics, as well as for the anticipation of the human and environmental impacts of extreme wildfire events (Tedim et al., 2018). During a wildfire event, active flaming areas release very large amounts of heat into the atmosphere, which induces the development of a buoyant plume, creating air entrainment effects (fire-induced flow) toward the active flaming areas that can enhance fire propagation and more generally modify wildfire behavior. They are subject to significant temperature and air density gradients and these are important to capture so as to correctly predict the interactions between a wildland fire and the atmosphere.