Extreme wildfires have recently caused disastrous impacts in Australia and other regions of the world,
including events with strong convective processes in their plumes (i.e., strong pyroconvection).
Dangerous wildfire events such as these could potentially be influenced by anthropogenic climate
change, however, there are large knowledge gaps on how these events might change in the future.
The McArthur Forest Fire Danger Index (FFDI) is used to represent near-surface weather conditions
and the Continuous Haines index (CH) is used here to represent lower to mid-tropospheric vertical
atmospheric stability and humidity measures relevant to dangerous wildfires and pyroconvective
processes. Projected changes in extreme measures of CH and FFDI are examined using a multi-method
approach, including an ensemble of global climate models together with two ensembles of regional
climate models. The projections show a clear trend towards more dangerous near-surface fire weather
conditions for Australia based on the FFDI, as well as increased pyroconvection risk factors for some
regions of southern Australia based on the CH. These results have implications for fields such as disaster
risk reduction, climate adaptation, ecology, policy and planning, noting that improved knowledge on
how climate change can influence extreme wildfires can help reduce future impacts of these events.
Figure 6. Spatial changes in near-surface fire weather condition for three different modelling methods.
Changes are shown for the number of days per year that the FFDI exceeds a threshold value, based on changes
from the period 1990–2009 to the period 2060–2079. Results are presented for the number of days per year
that FFDI is above 25 for different data sets: (a) GCMs; (b) CCAM; and (c) WRF. Results are also presented for
the number of days per year that FFDI is above its historical period 95th percentile for different data sets: (d)
GCMs; (e) CCAM; and (f) WRF. Coloured regions represent locations where at least two thirds of the ensemble
members for each modelling method agree of the sign of the change.
This page is maintained by Jason Evans |
Last updated 23 January 2018