Abstract
Wildland fires are responsible for large socio-economic impacts. Fires affect the environment, damage structures, threaten lives, cause health issues, and involve large suppression costs. These impacts can be mitigated via accurate fire spread forecast to inform the incident management team. We show that a fire forecast system based on a numerical weather prediction (NWP) model coupled with a wildland fire behavior model can provide this forecast. This was illustrated with the Chimney Tops II wildland fire responsible for large socio-economic impacts. The system was run at high horizontal resolution (111 m) over the region affected by the fire to provide a fine representation of the terrain and fuel heterogeneities and explicitly resolve atmospheric turbulence. Our findings suggest that one can use the high spatial resolution winds, fire spread and smoke forecast to minimize the adverse impacts of wildland fires.
Highlights
IntroductionWildland fires affect the environment, damage structures, threaten lives, cause health issues, and involve large suppression costs
The models range from physics-based models that resolve both the physics and chemistry of the fire spread, to empirical models that are based upon observational evidence to parameterize the fire behavior
To illustrate the potential of an operational coupled atmosphere-fire behavior prediction system, we present simulations performed with a similar set up to what the Colorado fire prediction system (CO-FPS) will be
Summary
Wildland fires affect the environment, damage structures, threaten lives, cause health issues, and involve large suppression costs. Accurate predictions of the fire spread can aid decision makers in mitigating the impacts [1]. A wide rage of models exists to predict the spread of wildland fires [2,3,4]. The models range from physics-based models that resolve both the physics and chemistry of the fire spread, to empirical models that are based upon observational evidence to parameterize the fire behavior. The complexity of physical processes involved in the simulation determines the computational resources necessary to perform a fire simulation
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