RandomFront 2.3: a physical parameterisation of fire spotting for operational fire spread models – implementation in WRF-SFIRE and response analysis with LSFire+
<p>Fire spotting is often responsible for dangerous flare-ups in wildfires and causes secondary ignitions isolated from the primary fire zone, which lead to perilous situations. The main aim of the present research is to provide a versatile probabilistic model for fire spotting that is sui...
Main Authors: | , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2019-01-01
|
Series: | Geoscientific Model Development |
Online Access: | https://www.geosci-model-dev.net/12/69/2019/gmd-12-69-2019.pdf |
Summary: | <p>Fire spotting is often responsible for dangerous flare-ups in
wildfires and causes secondary
ignitions isolated from the primary fire zone, which lead to perilous
situations. The main aim of the present research is to provide a versatile
probabilistic model for fire spotting that is suitable for implementation as
a post-processing scheme at each time step in any of the existing operational
large-scale wildfire propagation models, without calling for any major
changes in the original framework. In particular, a complete physical
parameterisation of fire spotting is presented and the corresponding updated
model RandomFront 2.3 is implemented in a coupled fire–atmosphere model:
WRF-SFIRE. A test case is simulated and discussed. Moreover, the results from
different simulations with a simple model based on the level set method,
namely <span style="" class="text typewriter">LSFire+</span>, highlight the response of
the parameterisation to varying fire intensities, wind conditions and
different firebrand radii. The contribution of the firebrands to increasing
the fire perimeter varies according to different concurrent conditions, and
the simulations show results in agreement with the physical processes. Among
the many rigorous approaches available in the literature to model firebrand
transport and distribution, the approach presented here proves to be simple
yet versatile for application to operational large-scale fire spread models.</p> |
---|---|
ISSN: | 1991-959X 1991-9603 |