Fire weather potential
New methods and workflows in the calculation of historical and projected national fire weather data
Fire weather is influenced by a range of weather variables including recent precipitation, current wind speed, humidity and temperature.
As the effects of climate change become more pronounced over time fire weather conditions and bushfire behaviour are projected to change.
The National Bushfire Intelligence Capability climate and weather processing workflow has 2 parts: historical and projected national fire weather.
Bushfire specific weather indices are calculated and combined with vegetation and terrain data to model fire behaviour.
NBIC applies an enhanced approach to fire weather potential analytics by considering extreme events and hourly concurrent weather data.
Hourly weather produces more detailed and relevant estimates of potential intensity and persistence of threats to the built assets at a specific location.
Understanding extreme events (using Extreme Value Analysis) identifies fire weather conditions that lead to catastrophic fires instead of looking at averages.
Forest Fire Danger Index (FFDI) for an event that has a 2% chance of occurring in any given year (i.e. a 2% annual exceedance probability)
Forest Fire Danger Index (FFDI) for an event that has a 2% chance of occurring in any given year (i.e. a 2% annual exceedance probability)FFDI is used as a measure of fire weather potential and is strongly embedded into state and territory legislation. FFDI is calculated using hourly concurrent conditions across 40+ years of data at 10 km resolution using historical weather reanalysis (BARRA-R2). This data is then processed using NBIC extreme value analysis to model a range of annual exceedance probabilities up to 0.5%.
Existing products
Stage 1 data: Fire Weather Potential is defined by both a historical weather reanalysis dataset (ERA5, baseline scenario) drawing on hourly concurrent data and a climate biased future weather dataset (based on 6 Global Climate Models and 2 Representative Concentrations Pathways from CMIP5, projected scenarios).
Methodology: Section 3 of the Stage 1 Methodology
Planned products
Stage 2 data: Fire weather potential suite of datasets expressed as Forest Fire Danger Index (FFDI), Grass Fire Danger Index (GFDI), Fire Weather Indices (FWI), 2 emissions scenarios and 7 Global Climate Models expressed for different Annual Exceedance Probabilities (AEP).
Methodology: Updates to Stage 2 Methodology
Use cases
Examples of how fire weather potential data has been applied.
Forthcoming