NBIC-ACS Stage 2 Fireline Intensity Potential - baseline and projected scenarios, 5%, 2% and 1% annual exceedance probabilities

Fireline intensity, expressed in kilowatts per metre (kW/m), quantifies the energy released along the leading edge (or head fire front) of a bushfire and is a key indicator of a fire’s behaviour and intensity. Fireline intensity calculations are dependent on type and condition of vegetation (often referred to as fuel), weather conditions and terrain. Empirical fire behaviour models describe the complex, non-linear relationships between those parameters, and are used to calculate fire intensity for different vegetation types. Evaluating those fire behaviour models at continental scale is a significant challenge, and therefore, a comprehensive, spatially explicit assessment of fireline intensity across Australia under current and future climate conditions has been so far lacking. \n\nHere we provide predicted upper-bound fireline intensity values based on plausible worst-case scenarios across the Australian landscape, defined for a set of annual exceedance probabilities. We calculate fireline intensity based on the 8 head fire rate of spread models used by the Australian Fire Danger Rating System, applied to 90m resolution fuel classification data and over 43 years of hourly weather timeseries. Fuel input parameters are derived from a variety of scientific principles and data sources, including satellite remote sensing timeseries of at least 500m resolution. Weather parameters are defined based on historical or projected conditions to 2090, resulting in one baseline scenario derived from historical reanalysis data, plus 18 projected scenarios derived from the latest climate modelling data. Terrain parameters are derived from a 30m resolution based on smoothed Digital Elevation Model. \n\nFireline intensity is a direct way to define bushfire hazard, higher fireline intensity means higher destructive potential from radiant heat, flames, embers and convective plume. Its applicability spans across climate adaptation, emergency planning, health and ecosystem resilience across Australia. This dataset marks a significant advancement in the quality of bushfire hazard assessment, surpassing previous efforts and providing a robust foundation for informed decision-making in managing and mitigating Australia’s escalating bushfire risks under a changing climate.\nLineage: The fireline intensity data is derived from 3 families of input datasets: weather and climate data, fuel typology and characteristics, and terrain information\n\nWeather and climate data:\n•\tHistorical weather reanalysis BARRA-R2 by Bureau of Meteorology [https://dx.doi.org/10.25914/90rq-d839],\n•\tCMIP6-era Regional Climate Model data produced with CCAM by CSIRO, comprised of 6 Global Climate Models (GCM) and 2 Shared Socioeconomical Pathways (SSP) [https://dx.doi.org/10.25914/rd73-4m38],\n•\tAustralian Water Availability Project (AWAP) v26s by CSIRO [Raupach MR, PR Briggs, V Haverd, EA King, M Paget, CM Trudinger (2009), Australian Water Availability Project (AWAP) CSIRO Marine and Atmospheric Research Component Final Report for Phase 3. CAWCR Technical Report No. 013. Bureau of Meteorology and CSIRO]\n\nFuel typology and characteristics:\n•\tNBIC Bushfire Fuel Classification fuel types by CSIRO [https://doi.org/10.25919/vnma-0j64]\n•\tNBIC Fuel Parameters rasters by CSIRO (unpublished), including wind adjustment factor, grass curing, spinifex cover, semi-arid mallee heath cover, surface and near surface fuel load and vegetation height\n•\tNBIC Total Fuel Load raster by CSIRO (unpublished)\n\nTerrain:\n•\tNBIC SRTM DEM-S derived terrain slope by CSIRO (https://data.csiro.au/collection/csiro:69661)\n\nThose inputs are then combined using one of the 7 fire behaviour model below:\n•\tForest: Cruz 2021 [https://doi.org/10.25919/hmsf-ad89]\n•\tPine: Cruz & Fernandes (2008) [https://doi.org/10.1080/00049158.2008.10676278]\n•\tGrassland/Northern grassland: Cheney et al. (1998) [http://dx.doi.org/10.1071/WF9980001]\n•\tSpinifex: Burrows et al (1991) [https://doi.org/10.1016/S0140-1963(18)30708-0]\n•\tSemi-arid Mallee Heath (SAMH): Cruz et al (2013) [https://doi.org/10.1016/j.envsoft.2012.07.003]\n•\tHeathland or Shrubland: Anderson et al (2014) [https://doi.org/10.1071/WF14130]\n•\tButtongrass or Sedgeland: Marsden-Smedleyl et al. (1995) [http://dx.doi.org/10.1071/WF01025]\n\nFire behaviour is calculated for more than 43 years of hourly weather data, and then processed using extreme values analysis to model the expected fireline intensities at annual exceedance probabilities\n\nImportant Disclaimer:\nCSIRO advises that the information contained in this dataset comprises general statements and information based on scientific research. The user is advised and needs to be aware that such information may be incomplete or unable to be used in any specific situation. No reliance or actions must therefore be made on that information without seeking prior expert professional, scientific and technical advice. To the extent permitted by law, CSIRO (including its employees and consultants) excludes all liability to any person for any consequences, including but not limited to all losses, damages, costs, expenses and any other compensation, arising directly or indirectly from using this publication (in part or in whole) and any information or material contained in it.\n