The importance of fire - atmosphere coupling and boundary-layer turbulence to wildfire spread

Abstract

The major source of uncertainty in wildfire behavior prediction is the transient behavior of wildfire due to changes in flow in the fire’s environment. The changes in flow are dominated by two factors. The first is the interaction or ‘coupling’ between the fire and the fire-induced flow. The second is the interaction or ‘coupling’ between the fire and the ambient flow driven by turbulence due to wind gustiness and eddies in the atmospheric boundary layer (ABL). In the present study, coupled wildfire–atmosphere large-eddy simulations of grassland fires are used to examine the differences in the rate of spread and area burnt by grass fires in two types of ABL, a buoyancy-dominated ABL and a roll-dominated ABL. The simulations show how a buoyancy-dominated ABL affects fire spread, how a roll-dominated ABL affects fire spread, and how fire lines interact with these two different ABL flow types. The simulations also show how important are fire–atmosphere couplings or fire-induced circulations to fire line spread compared with the direct impact of the turbulence in the two different ABLs. The results have implications for operational wildfire behavior prediction. Ultimately, it will be important to use techniques that include an estimate of uncertainty in wildfire behavior forecasts.

Kinematic structure of a wildland fire plume observed by Doppler lidar

“…One of the most comprehensive field studies to observe the dynamics of a fire plume and associated fire-atmosphere interactions is the FireFlux experiment [Clements et al, 2007[Clements et al, , 2008Clements, 2010], where a high-intensity, wind-driven head fire was allowed to spread through a suite of tower-based micrometeorological instrumentation. This study observed the turbulent structure of the fire plume and near-surface environment and observed strong downdrafts of~5 m s À1 occurring behind the fire front, in agreement with the modeling results of Sun et al [2009]. While the FireFlux experiment provided evidence of the downward motion behind the fire front, its observations were limited to the two tower locations within the experimental plot.…”

“…Another recognized dynamic feature of a wildfire plume is the rear inflow, which descends on the upwind side of the fire plume [Clements et al, 2007;Potter, 2011]. The rear inflow has been shown to exist in idealized numerical simulations in grass fires [Sun et al, 2009], and Clark et al [1996] suggested that low pressure develops downwind of the fire front, accelerating winds at the fire front. They hypothesized that the low pressure forms a convergence zone downwind of the fire since the convection column is advected downwind of the fire front by faster ambient wind speeds aloft tilting the plume downstream and shifting the center of the low-level convergence ahead of the fire.…”

Observations of fire‐induced turbulence regimes during low‐intensity wildland fires in forested environments: implications for smoke dispersion

“…The release of heat and moisture from fuel combustion during wildland fires alters the local thermal structure of the lower atmospheric boundary layer and induces turbulent circulations. These turbulent circulations, in combination with the ambient mean flow, can affect fire behavior and the transport and dispersion of smoke (Ward and Hardy, 1991;Clements et al, 2008;Sun et al, 2009). The presence of forest overstory vegetation can further complicate local turbulence regimes through its effect on ambient and fire-induced circulations within the fire environment (Kiefer et al, 2014).…”

The Spotting Distribution of Wildfires

“…As mentioned above, coupled fire-atmosphere models [2,17,18] may provide an improvement to static fluid dynamic computations currently employed in operational front prediction software (for North American examples see [19,20]). Indeed, Large Eddy Simulations (LES) coupled with firebrand dispersal have shown that the fire plume may be quite different from the plume used in standard models like the Baum and McCaffery plume [21], leading to different firebrand trajectories [22][23][24]. In addition, there is an extensive literature covering empirical measurement of plume characteristics; extensive measurement of plume heights and characteristics in [25] compared a variety of plume models (different from Baum and McCaffery) against measurements for approximately 2000 wildfire plumes.…”

“…The latter requires solving Equations (11) and (12) with negative signs in front of the terms on the RHS. It is clear, then, that the firebrand density, provided N firebrands are released above a canopy of height H, is given by p(t, x(t; x 0 ), z(t; z 0 ), m(t; m 0 )) (24) …”