An Accurate Fire‐Spread Algorithm in the Weather Research and Forecasting Model Using the Level‐Set Method

Abstract The level‐set method is typically used to track and propagate the fire perimeter in wildland fire models. Herein, a high‐order level‐set method using fifth‐order WENO scheme for the discretization of spatial derivatives and third‐order explicit Runge‐Kutta temporal integration is implemented within the Weather Research and Forecasting model wildland fire physics package, WRF‐Fire. The algorithm includes solution of an additional partial differential equation for level‐set reinitialization. The accuracy of the fire‐front shape and rate of spread in uncoupled simulations is systematically analyzed. It is demonstrated that the common implementation used by level‐set‐based wildfire models yields to rate‐of‐spread errors in the range 10–35% for typical grid sizes (Δ = 12.5–100 m) and considerably underestimates fire area. Moreover, the amplitude of fire‐front gradients in the presence of explicitly resolved turbulence features is systematically underestimated. In contrast, the new WRF‐Fire algorithm results in rate‐of‐spread errors that are lower than 1% and that become nearly grid independent. Also, the underestimation of fire area at the sharp transition between the fire front and the lateral flanks is found to be reduced by a factor of ≈7. A hybrid‐order level‐set method with locally reduced artificial viscosity is proposed, which substantially alleviates the computational cost associated with high‐order discretizations while preserving accuracy. Simulations of the Last Chance wildfire demonstrate additional benefits of high‐order accurate level‐set algorithms when dealing with complex fuel heterogeneities, enabling propagation across narrow fuel gaps and more accurate fire backing over the lee side of no fuel clusters.