Wildfire Science and Modeling

Wildland fires present substantial scientific, computational, and forecasting challenges. Many of these challenges are common to other applications (an interdisciplinary nature, physical processes that span a vast range of scales, estimating the consequences of uncertainty, visualization of complex processes, and the urge to assimilate nontraditional data sources, often at disparate scales). Others are peculiar to this application, in that many of the fundamental physical processes are not understood, some have a stochastic nature and cannot be deterministically modeled, nowcasting of convective precipitation (often a factor in fire behavior) may show skill only on the order of a few hours, and the difficulty of gathering pertinent data for verification and initialization in a dangerous environment.

Starting with a basic understanding of what a wildland fire is, some 'new basics' in understanding of fire phenomena will be presented, tempered by our remaining fundamental unknowns about the speed at which fires spread, the mechanisms responsible, what a safe 'defensible space' should be near structures, when fires will change direction or jump roads or fire breaks. We will discuss approaches both empirical and physical to modeling wildfire for understanding and how fire behavior is forecast in the field along with capabilities on the horizon.