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Mesoscale models are a class of atmospheric numerical model designed to simulate atmospheric phenomena with horizontal scales of about 2–200 km, although they are also applied to microscale phenomena with horizontal scales of less than about 2 km. Mesoscale models are capable of simulating wildland fire impacts on atmospheric flows if combustion byproducts (e.g., heat, smoke) are properly represented in the model. One of the primary challenges encountered in applying a mesoscale model to studies of fire-perturbed flows is the representation of the fire sensible heat source in the model. Two primary methods have been implemented previously: turbulent sensible heat flux, either in the form of an exponentially-decaying vertical heat flux profile or surface heat flux; and soil temperature perturbation. In this study, the ARPS-CANOPY model, a version of the Advanced Regional Prediction System (ARPS) model with a canopy submodel, is utilized to simulate the turbulent atmosphere during a low-intensity operational prescribed fire in the New Jersey Pine Barrens. The study takes place in two phases: model assessment and model sensitivity. In the model assessment phase, analysis is limited to a single control simulation in which the fire sensible heat source is represented as an exponentially decaying vertical profile of turbulent sensible heat flux. In the model sensitivity phase, a series of simulations are conducted to explore the sensitivity of model–observation agreement to (i) the method used to represent the fire sensible heat source in the model and (ii) parameters controlling the magnitude and vertical distribution of the sensible heat source. In both phases, momentum and scalar fields are compared between the model simulations and data obtained from six flux towers located within and adjacent to the burn unit. The multi-dimensional model assessment confirms that the model reproduces the background and fire-perturbed atmosphere as depicted by the tower observations, although the model underestimates the turbulent kinetic energy at the top of the canopy at several towers. The model sensitivity tests reveal that the best agreement with observations occurs when the fire sensible heat source is represented as a turbulent sensible heat flux profile, with surface heat flux magnitude corresponding to the peak 1 min mean observed heat flux averaged across the flux towers, and an e -folding extinction depth corresponding to the average canopy height in the burn unit. The study findings provide useful guidance for improving the representation of the sensible heat released from low-intensity prescribed fires in mesoscale models. [ABSTRACT FROM AUTHOR]

Mesoscale models are a class of atmospheric numerical model designed to simulate atmospheric phenomena with horizontal scales of about 2-200 km, although they are also applied to microscale phenomena, with horizontal scales less than about 2 km. Mesoscale models are capable of simulating wildland fire impacts on atmospheric flows if combustion by-products (e.g., heat, smoke) are properly represented in the model. One of the primary challenges encountered in applying a mesoscale model to studies of fire-perturbed flows is the representation of the fire sensible heat source in the model. Two primary methods have been implemented previously: turbulent sensible heat flux, either in the form of an exponentially-decaying vertical heat flux profile or surface heat flux; and soil temperature perturbation. In this study, the ARPS-CANOPY model, a version of the Advanced Regional Prediction System (ARPS) model with a canopy submodel, is utilized to simulate the turbulent atmosphere during a low-intensity operational prescribed fire in the New Jersey Pine Barrens. The study takes place in two phases: model assessment and model sensitivity. In the model assessment phase, analysis is limited to a single control simulation in which the fire sensible heat source is represented as an exponentially-decaying vertical profile of turbulent sensible heat flux. In the model sensitivity phase, a series of simulations are conducted to explore the sensitivity of model-observation agreement to (i) the method used to represent the fire sensible heat source in the model and (ii) parameters controlling the magnitude and vertical distribution of the sensible heat source. In both phases, momentum and scalar fields are compared between the model simulations and data obtained from six flux towers located within and adjacent to the burn unit. The multi-dimensional model assessment confirms that the model reproduces the background and fire-perturbed atmosphere as depicted by the tower observations, although the model underestimates the turbulent kinetic energy at the top of the canopy at several towers. The model sensitivity tests reveal that the best agreement with observations occurs when the fire sensible heat source is represented as a turbulent sensible heat flux profile, with surface heat flux magnitude corresponding to the peak 1-min mean observed heat flux averaged across the flux towers, and an e-folding extinction depth corresponding to the average canopy height in the burn unit. The study findings provide useful guidance for improving the representation of the sensible heat released from low-intensity prescribed fires in mesoscale models. [ABSTRACT FROM AUTHOR]

Low-intensity wildland fires occurring beneath forest canopies can result in particularly adverse local air-quality conditions. Ambient and fire-induced turbulent circulations play a substantial role in the transport and dispersion of smoke during these fire events. Recent in situ measurements of fire-atmosphere interactions during low-intensity wildland fires have provided new insight into the structure of fire-induced turbulence regimes and how forest overstory vegetation can affect the horizontal and vertical dispersion of smoke. In this paper, we provide a summary of the key turbulence observations made during two low-intensity wildland fire events that occurred in the New Jersey Pine Barrens. [ABSTRACT FROM AUTHOR]

The impact of a forest canopy on smoke concentration is assessed by applying a numerical weather prediction model coupled with a Lagrangian particle dispersion model to two low-intensity wildland (prescribed) fires in the New Jersey Pine Barrens. A comparison with observations indicates that the coupled numerical model can reproduce some of the observed variations in surface smoke concentrations and plume heights. Model sensitivity analyses highlight the effect of the forest canopy on simulated meteorological conditions, smoke concentrations, and plume heights. The forest canopy decreases near-surface wind speed, increases buoyancy, and increases turbulent mixing. Sensitivities to the time of day, plant area density profiles, and fire heat fluxes are documented. Analyses of temporal variations in smoke concentrations indicate that the effect of the transition from a daytime to a nocturnal planetary boundary layer is weaker when sensible heat fluxes from the fires are stronger. The results illustrate the challenges in simulating meteorological conditions and smoke concentrations at scales where interactions between the fire, fuels, and atmosphere are critically important. The study demonstrates the potential for predictive tools to be developed and implemented that could help fire and air-quality managers assess local air-quality impacts during low-intensity wildland fires in forested environments. [ABSTRACT FROM AUTHOR]