Title: Coupled Weather-Fire Modeling Across Scales for Biomass Emissions
Abstract: Computational modeling of wildland fire events unites numerical weather prediction models developed by atmospheric scientists and knowledge fire scientists have gathered about how fires respond to environmental factors such as terrain, fuel characteristics and state, and weather. The methodology I will describe involves the use of numerical weather prediction models capable of modeling fine scale atmospheric flows in complex terrain. The wildland fire component contains a surface fire model based upon semi-empirical relationships between a surface fire's rate of spread as a function of local conditions and a canopy fire model. The fire behavior is coupled to the atmospheric model such that low level winds drive the spread of the surface fire, which in turn release sensible heat, latent heat, and smoke fluxes into the lower atmosphere, in turn feeding back to affect the winds directing the fire - i.e. how all fires, to some degree, 'create their own weather'. In this modeling framework, simulated smoke (currently treated simply as a fixed percentage of the fuel mass burned being transformed to tracer particles) rises in the buoyant plume created by fuel consumption along the flaming front and in the residual burning behind it. How much smoke is produced and how deeply it is transported thus depends on the intensity of the fire, which varies spatially across the fire and temporally as the fire burning rate increases and decreases throughout its lifetime, and the evolving environmental conditions.
Starting with a basic understanding of what a wildland fire is, some 'new basics' in the understanding of fire phenomena will be presented, tempered by remaining fundamental unknowns. I will present case studies of landscape-scale wildland fires to illustrate our current capabilities to model these phenomena. I will describe the lingering issues in such models, including physical processes that span a vast range of scales, processes such as spotting that cannot be modeled deterministically, estimating the consequences of uncertainty, and the difficulty of gathering pertinent data for verification and initialization in a dangerous environment, as well as capabilities on the horizon.
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Janice Coen
Title: Coupled Weather-Fire Modeling Across Scales for Biomass Emissions
Abstract: Computational modeling of wildland fire events unites numerical weather prediction models developed by atmospheric scientists and knowledge fire scientists have gathered about how fires respond to environmental factors such as terrain, fuel characteristics and state, and weather. The methodology I will describe involves the use of numerical weather prediction models capable of modeling fine scale atmospheric flows in complex terrain. The wildland fire component contains a surface fire model based upon semi-empirical relationships between a surface fire's rate of spread as a function of local conditions and a canopy fire model. The fire behavior is coupled to the atmospheric model such that low level winds drive the spread of the surface fire, which in turn release sensible heat, latent heat, and smoke fluxes into the lower atmosphere, in turn feeding back to affect the winds directing the fire - i.e. how all fires, to some degree, 'create their own weather'. In this modeling framework, simulated smoke (currently treated simply as a fixed percentage of the fuel mass burned being transformed to tracer particles) rises in the buoyant plume created by fuel consumption along the flaming front and in the residual burning behind it. How much smoke is produced and how deeply it is transported thus depends on the intensity of the fire, which varies spatially across the fire and temporally as the fire burning rate increases and decreases throughout its lifetime, and the evolving environmental conditions.
Starting with a basic understanding of what a wildland fire is, some 'new basics' in the understanding of fire phenomena will be presented, tempered by remaining fundamental unknowns. I will present case studies of landscape-scale wildland fires to illustrate our current capabilities to model these phenomena. I will describe the lingering issues in such models, including physical processes that span a vast range of scales, processes such as spotting that cannot be modeled deterministically, estimating the consequences of uncertainty, and the difficulty of gathering pertinent data for verification and initialization in a dangerous environment, as well as capabilities on the horizon.