Physics-based coupled fire-atmosphere models are based on approximations to the governing equations of fluid dynamics, combustion, and the thermal degradation of solid fuel. They require significantly more computational resources than the most commonly used fire spread models, which are semi-empirical or empirical. However, there are a number of fire behaviour problems, of increasing relevance, that are outside the scope of empirical and semi-empirical models. Examples are wildland-urban interface fires, assessing how well fuel treatments work to reduce the intensity of wildland fires, and investigating the mechanisms and conditions underlying blow-up fires and fire spread through heterogeneous fuels. These problems are not amenable to repeatable full-scale field studies. Suitably validated coupled atmosphere-fire models are one way to address these problems. This paper describes the development of a three-dimensional, fully transient, physics-based computer simulation approach for modelling fire spread through surface fuels. Grassland fires were simulated and compared to findings from Australian experiments. Predictions of the head fire spread rate for a range of ambient wind speeds and ignition line-fire lengths compared favourably to experiments. In addition, two specific experimental cases were simulated in order to evaluate how well the model predicts the development of the entire fire perimeter.

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The major source of uncertainty in wildfire behavior prediction is the transient behavior of wildfire due to changes in flow in the fire’s environment. The changes in flow are dominated by two factors. The first is the interaction or ‘coupling’ between the fire and the fire-induced flow. The second is the interaction or ‘coupling’ between the fire and the ambient flow driven by turbulence due to wind gustiness and eddies in the atmospheric boundary layer (ABL). In the present study, coupled wildfire–atmosphere large-eddy simulations of grassland fires are used to examine the differences in the rate of spread and area burnt by grass fires in two types of ABL, a buoyancy-dominated ABL and a roll-dominated ABL. The simulations show how a buoyancy-dominated ABL affects fire spread, how a roll-dominated ABL affects fire spread, and how fire lines interact with these two different ABL flow types. The simulations also show how important are fire–atmosphere couplings or fire-induced circulations to fire line spread compared with the direct impact of the turbulence in the two different ABLs. The results have implications for operational wildfire behavior prediction. Ultimately, it will be important to use techniques that include an estimate of uncertainty in wildfire behavior forecasts.

In this study, we describe how WRF-Sfire is coupled with WRF-Chem to construct WRFSC, an integrated forecast system for wildfire and smoke prediction. The integrated forecast system has the advantage of not requiring a simple plume-rise model and assumptions about the size and heat release from the fire in order to determine fire emissions into the atmosphere. With WRF-Sfire, wildfire spread, plume and plume-top heights are predicted directly, at every WRF time-step, providing comprehensive meteorology and fire emissions to the chemical transport model WRF-Chem.Evaluation of WRFSC was based on comparisons between available observations to the results of two WRFSC simulations.The study found overall good agreement between forecasted and observed fire spread and smoke transport for the Witch-Guejito fire. Also the simulated PM2.5 (fine particulate matter) peak concentrations matched the observations. However, the NO and ozone levels were underestimated in the simulations and the peak concentrations were mistimed. Determining the terminal or plume-top height is one of the most important aspects of simulating wildfire plume transport, and the study found overall good agreement between simulated and observed plume-top heights, with some (10% or less) underestimation by the simulations. One of the most promising results of the study was the agreement between passive-tracer modeled plumetop heights for the Barker Canyon fire simulation and observations. This simulation took only 13h, with the first 24h forecast ready in almost 3h, making it a possible operational tool for providing emission profiles for external chemical transport models.