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Incorporating a Canopy Parameterization within a Coupled Fire-Atmosphere Model to Improve a Smoke Simulation for a Prescribed Burn
by
Kochanski, Adam K.
, Farguell, Angel
, Krueger, Steven K.
, Mallia, Derek V.
, Mandel, Jan
, Urbanski, Shawn P.
in
Air quality
/ Aircraft
/ Atmosphere
/ Atmospheric forcing
/ Atmospheric models
/ Canopies
/ Canopy
/ canopy winds
/ Computer simulation
/ coupled-fire atmosphere model
/ Dispersion
/ Fire behavior
/ Fires
/ Forest & brush fires
/ Forest canopy
/ Growth rate
/ Heat transfer
/ Humidity
/ Interpolation
/ Leaves
/ Numerical weather forecasting
/ Parameterization
/ Plume rise
/ Prediction models
/ Prescribed fire
/ Sensors
/ Simulation
/ Smoke
/ Smoke dispersion
/ smoke modeling
/ Surface wind
/ Understory
/ Weather forecasting
/ Wildfires
/ wildland fire
/ Wind
/ Wind effects
/ Wind flow
/ Wind profiles
/ Wind speed
/ Winds
2020
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Incorporating a Canopy Parameterization within a Coupled Fire-Atmosphere Model to Improve a Smoke Simulation for a Prescribed Burn
by
Kochanski, Adam K.
, Farguell, Angel
, Krueger, Steven K.
, Mallia, Derek V.
, Mandel, Jan
, Urbanski, Shawn P.
in
Air quality
/ Aircraft
/ Atmosphere
/ Atmospheric forcing
/ Atmospheric models
/ Canopies
/ Canopy
/ canopy winds
/ Computer simulation
/ coupled-fire atmosphere model
/ Dispersion
/ Fire behavior
/ Fires
/ Forest & brush fires
/ Forest canopy
/ Growth rate
/ Heat transfer
/ Humidity
/ Interpolation
/ Leaves
/ Numerical weather forecasting
/ Parameterization
/ Plume rise
/ Prediction models
/ Prescribed fire
/ Sensors
/ Simulation
/ Smoke
/ Smoke dispersion
/ smoke modeling
/ Surface wind
/ Understory
/ Weather forecasting
/ Wildfires
/ wildland fire
/ Wind
/ Wind effects
/ Wind flow
/ Wind profiles
/ Wind speed
/ Winds
2020
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Incorporating a Canopy Parameterization within a Coupled Fire-Atmosphere Model to Improve a Smoke Simulation for a Prescribed Burn
by
Kochanski, Adam K.
, Farguell, Angel
, Krueger, Steven K.
, Mallia, Derek V.
, Mandel, Jan
, Urbanski, Shawn P.
in
Air quality
/ Aircraft
/ Atmosphere
/ Atmospheric forcing
/ Atmospheric models
/ Canopies
/ Canopy
/ canopy winds
/ Computer simulation
/ coupled-fire atmosphere model
/ Dispersion
/ Fire behavior
/ Fires
/ Forest & brush fires
/ Forest canopy
/ Growth rate
/ Heat transfer
/ Humidity
/ Interpolation
/ Leaves
/ Numerical weather forecasting
/ Parameterization
/ Plume rise
/ Prediction models
/ Prescribed fire
/ Sensors
/ Simulation
/ Smoke
/ Smoke dispersion
/ smoke modeling
/ Surface wind
/ Understory
/ Weather forecasting
/ Wildfires
/ wildland fire
/ Wind
/ Wind effects
/ Wind flow
/ Wind profiles
/ Wind speed
/ Winds
2020
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Incorporating a Canopy Parameterization within a Coupled Fire-Atmosphere Model to Improve a Smoke Simulation for a Prescribed Burn
Journal Article
Incorporating a Canopy Parameterization within a Coupled Fire-Atmosphere Model to Improve a Smoke Simulation for a Prescribed Burn
2020
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Overview
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.
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