Abstract
Forecasting fire growth, plume rise and smoke impacts on air quality remains a challenging task. Wildland fires dynamically interact with the atmosphere, which can impact fire behavior, plume rises, and smoke dispersion. For understory fires, the fire propagation is driven by winds attenuated by the forest canopy. However, most numerical weather prediction models providing meteorological forcing for fire models are unable to resolve canopy winds. In this study, an improved canopy model parameterization was implemented within a coupled fire-atmosphere model (WRF-SFIRE) to simulate a prescribed burn within a forested plot. Simulations with and without a canopy wind model were generated to determine the sensitivity of fire growth, plume rise, and smoke dispersion to canopy effects on near-surface wind flow. Results presented here found strong linkages between the simulated fire rate of spread, heat release and smoke plume evolution. The standard WRF-SFIRE configuration, which uses a logarithmic interpolation to estimate sub-canopy winds, overestimated wind speeds (by a factor 2), fire growth rates and plume rise heights. WRF-SFIRE simulations that implemented a canopy model based on a non-dimensional wind profile, saw significant improvements in sub-canopy winds, fire growth rates and smoke dispersion when evaluated with observations.
Highlights
Wildland fires across North America are projected to increase in frequency and in size through the21st century as a result of climate change [1,2,3]
As wildfires continue to increase in frequency and intensity, numerical models are needed that can assist with forecasting fire evolution and smoke impacts on regional air quality
In an effort to quantify the impacts of canopy winds on forecasted fire growth and smoke dispersion, we modeled a prescribed burn within a forest during the Prescribed Fire Combustion and Atmospheric Dynamics Research Experiment (RxCADRE)
Summary
Wildland fires across North America are projected to increase in frequency and in size through the21st century as a result of climate change [1,2,3]. Wildland fires across North America are projected to increase in frequency and in size through the. Air quality across the western U.S has started to deteriorate, especially across the Pacific Northwest and Northern Rockies as a result of increased wildfire activity and smoke [7]. Air quality across these regions is expected to deteriorate through the foreseeable future [8]. As wildfires continue to increase in frequency and intensity, numerical models are needed that can assist with forecasting fire evolution and smoke impacts on regional air quality. A number of models currently exist that forecast wildland fires and/or smoke. One-way coupled modeling frameworks such as BlueSky [9] and the High-Resolution Rapid Refresh model (HRRR)
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