NBIC-ACS Stage 2 Grass Fire Danger Index - projected scenario, 20% and 10% annual exceedance probabilities

Grass Fire Danger Index (GFDI) is a fire weather potential index that describes how current weather conditions and the proportion of dry dead grass could support a fire in grassy areas. GFDI Mark 4 (MK4) calculations are based on McArthur, A.G. (1966) and McArthur, A.G. (1973) and are dependent on air temperature, relative humidity, wind speed and grass curing. GFDI MK4 was originally implemented as a circular slide rule that constrained the returned index between 0 and 100. The data provided here is unbounded.\nHere we provide predicted upper-bound GFDI values across the Australian landscape, defined for a set of annual exceedance probabilities (AEP) modelled using extreme values analysis on more than 43 years of daily data. The GFDI potential rasters represent reasonable worst case extreme conditions. Specifically, the rasters represent the GFDI potential for given AEPs of 20%, 10%, 5%, 2% and 1%. These GFDI AEPs are based on the projected weather timeseries developed by NBIC using the historical regional weather reanalysis dataset BARRA-R2 [1], and CMIP6-CCAM Regional Climate Models (RCM) [2].\nThe Regional Climate Models (RCM) considered are:\n•\tACCESS ESM 1.5\n•\tEC-Earth 3\n•\tCMCC ESM2\n•\tCNRM ESM 2.1\n•\tNCAR CESM2\n•\tNorESM2 MM\nThe future climate change scenarios considered are:\n•\tShared Socioeconomic Pathway (SSP) SSP 1-26: Sustainability \n•\tSSP 3-70: Regional Rivalry\n•\tSSP 3-70: Regional Rivalry, using wind speed from the baseline scenario \nThe combination of RCMs and future climate change scenarios results in 18 different projected GFDI potential datasets.\nLineage: The Grass Fire Danger Index (GFDI) - projected scenario is calculated using the CMIP6-ERA Regional Climate Model data produced with CCAM by CSIRO (https://dx.doi.org/10.25914/rd73-4m38). Variables used are near surface air temperature, near surface relative humidity, near surface wind speed. The 99th percentile of estimated curing was used as a constant [1].\nGrass curing values are calculated using the 99th percentile of the Bureau of Meteorology MODIS 8-day grass curing time series that are modelled from MODIS data using the method described in Wright et al (2015) [1]. The choice of percentile value used reflects the intention to capture ‘reasonable worst-case’ conditions. \nThe inputs are combined using the equations developed by Noble et al. (1980) [2] based on the work by McArthur (1966) [3] and McArthur (1973) [4]. GFDI is calculated for more than 43 years of hourly weather data and then processed using extreme values analysis to model the expected GFDI values at annual exceedance probabilities.\n[1] Wright, D., Nichols, D., Slijepcevic, A., Kidnie, S., Chen, A., & Bessell, R. (2015). Improved assessment of grassland fuels in multiple jurisdictions across Australia. In Bushfire and Natural Hazards CRC & AFAC conference. Adelaide: Bushfire and Natural Hazards CRC.\n[2] Noble, I.R., Gill, A.M. and Bary, G.A.V., 1980. McArthur's fire‐danger meters expressed as equations. Australian journal of ecology, 5(2), pp.201-203. https://doi.org/10.1111/j.1442-9993.1980.tb01243.x\n[3] McArthur, A. G., 1966. Weather and grassland fire behaviour. Forestry and Timber Bureau Leaflet 100. Forestry and Timber Bureau: Canberra, Australia\n[4] McArthur, A.G. (1973) Grassland Fire Danger Meter Mark IV. Commonwealth Department of National Development Forestry and Timber Bureau, Canberra, ACT. (published as a circular slide rule).