The effects of fire-plume dynamics on the lateral and longitudinal spread of long-range spotting — ASN Events

The effects of fire-plume dynamics on the lateral and longitudinal spread of long-range spotting (#14)

William Thurston 1 2 , Kevin J Tory 1 2 , Robert J. B Fawcett 1 2 , Jeff D Kepert 1 2
  1. The Centre for Australian Weather and Climate Research, Melbourne, VIC, Australia
  2. Bushfire CRC, Melbourne, Victoria, Australia
The lofting of firebrands from bushfires into a background flow can lead to spotting downwind of the fire front. Spotting is a hazardous phenomenon because it leads to both unpredictable and accelerated fire spread, as winds aloft are often in a different direction from and faster than the near-surface winds. Here we use a two-stage modelling system to address some of the uncertainty associated with spotting, by quantifying the lateral and longitudinal spread in the landing location of potential firebrands and how this spread is affected by the dynamics of the fire plume.

Firstly, we present high resolution, three-dimensional numerical simulations of bushfire plumes using the UK Met Office Large Eddy Model (LEM). Plumes are simulated under a range of background wind conditions and the intensity, size, morphology and temporal stability of the resulting plumes are examined. Secondly, we use a Lagrangian particle transport model to calculate the trajectories of particles released near the base of each plume. Particles are assigned fall velocities representative of common firebrands and then advected by the three-dimensional velocity fields from the LEM simulations. By calculating the trajectories of tens of thousands of potential firebrands for each plume, distributions of flight time and landing position are constructed. We find that: (i) interaction between the plume updraft and background wind determines the distance travelled by firebrands, and (ii) the morphology of the plume determines the lateral and longitudinal spread of landing positions. These variations need to be properly accounted for in predictive models of fire spread and systematic studies such as these form the building blocks of better empirical spotting models.