Forest Fire Danger Index (FFDI)

These maps show the values of the average annual, monthly and seasonal Forest Fire Danger Index (FFDI) over Australia.

Average FFDI - January

Product code: IDCJCM0051

About these maps

These maps show the mean Forest Fire Danger Index (FFDI) over Australia for each month for the period 1950 to 2016. Higher values represent more dangerous weather conditions for bushfires: for example, FFDI above 50 is classed as 'Severe'.

The FFDI is based on a combination of different weather conditions known to influence the risk of dangerous bushfire conditions in Australia, including temperature, rainfall, humidity and wind speed. In addition to the weather, bushfire events in Australia are also influenced by factors such as vegetation conditions, terrain and ignition sources.

This dataset provides observations-based information using a 67-year time period. It is intended for use in examining broad-scale features in fire weather conditions for regions throughout Australia. In addition to mean values, the total number of days over this time period with FFDI higher than 50 is presented for each month. Maps are also presented for the total number of days over this time period with FFDI higher than its 90th percentile (which represents the highest 10% of values for all months of the year). Further information on this dataset is available in a research publication, including details on the influence of the El Niño/Southern Oscillation (ENSO) and climate change trends.

In addition, information on future projected changes in bushfire conditions based on the FFDI is also available, as detailed in the publication Dowdy et al. [2019].

How are the values calculated?

These fire weather climatology data products were produced based on daily values of the FFDI from 1950 to 2016. The FFDI is calculated from input variables of temperature, relative humidity and wind speed on a given day, as well as a number representing fuel availability called the Drought Factor. The Drought Factor is based on the accumulated soil moisture deficit, calculated here using the Keetch-Byram Drought Index (KBDI [Keetch and Byram 1968]) using daily rainfall and maximum temperature. Additional details on how the FFDI dataset is calculated are documented in Dowdy [2018].

The input variables for calculating the FFDI values consist primarily of a gridded analysis of observations from the Australian Water Availability Project, AWAP [Jones et al. 2009], with a grid of 0.05° in both latitude and longitude throughout Australia. This includes daily maximum temperatures, as well as vapour pressure at 1500 Local Time (used here together with temperature to calculate relative humidity near the time of maximum temperature) and daily-accumulated precipitation totals for the 24-hour period to 0900 Local Time each day. A global dataset with 6-hourly values is used for surface wind speeds (from the NCEP/NCAR reanalysis [Kalnay et al. 1996]), with the value at a time of 0600 UT used, representing mid-afternoon conditions over the longitude range spanned by Australia. The wind data were bilinearly interpolated to the AWAP grid spacing (of 0.05° in both latitude and longitude), with bias correction subsequently applied to provide a better match to the wind speeds used for issuing forecasts of the FFDI.

This dataset was calculated as part of the Extreme weather projections project supported by the Australian Government's National Environmental Science Program (NESP).


  • Dowdy, A.J., Ye, H., Pepler, A., Thatcher, M., Osbrough, S.L., Evans, J.P., Di Virgilio, G. and McCarthy, N., (2019): Future changes in extreme weather and pyroconvection risk factors for Australian wildfires. Scientific Reports, 9, 1-11,
  • Dowdy, A. J. (2018): Climatological Variability of Fire Weather in Australia. Journal of Applied Meteorology and Climatology, doi:10.1175/JAMC-D-17-0167.1
  • Jones, D., W. Wang, and R. Fawcett (2009): High-quality spatial climate datasets for Australia. Aust. Meteorol. Mag., 58, 233-248.
  • Keetch, J. J., and G. M. Byram (1968): A drought index for forest fire control. Res. Pap. SE-38. Asheville, NC: US Department of Agriculture, Forest Service, Southeastern Forest Experiment Station.
  • Kalnay, E., and Coauthors (1996): The NCEP/NCAR 40-year reanalysis project. Bulletin of the American Meteorological Society, 77(3), 437-471.

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