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

The Grass Fire Danger Index (GFDI) is a fire weather potential index that describes how current weather conditions and recent precipitation patterns could support a fire in grassy areas. GFDI calculations are based on McArthur, A.G. (1966, 1973) and dependent on air temperature, relative humidity, wind speed and grass curing. The metric was developed with the worst event considered corresponding to a value of 100. Here we provide predicted upper-bound GFDI values across the Australian landscape, defined for a set of Annual Exceedance Probabilities. We calculate GFDI based on the latest Bureau of Meteorology historical weather reanalysis BARRA-R2, reporting modelled hourly weather conditions from 1979 to current at a spatial resolution of approximately 11 kilometres. Grass curing values are derived from the 99th percentile of the values modelled from 2000 to 2019 by the Bureau of Meteorology MODIS MapVictoria grass curing dataset. More than 400,000 data points at every location are then processed using the National Bushfire Intelligence Capability (NBIC) Extreme Values Analysis to predict extreme daily maximums and their likelihood. GFDI is used in operational contexts, including land use planning and Australian standards for building in bushfire prone areas, and it is a widely recognised fire weather metric. All these characteristics result in datasets that are a significant advancement in defining extreme fire weather, surpassing previous approaches and offering a robust foundation for informed decision-making in managing and mitigating Australia’s growing bushfire risks in a changing climate.\nLineage: The Grass Fire Danger Index (GFDI) data - baseline scenario is calculated using the historical weather reanalysis BARRA-R2 by Bureau of Meteorology (https://dx.doi.org/10.25914/90rq-d839). Variables used are near surface air temperature, near surface relative humidity and near surface wind speed.\nGrass Curing is 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 all (2015)[1]. The choice of percentile value used reflects the intention to capture “reasonable worst-case” conditions.\n\nThose 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\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., 1967. Fire behaviour in eucalypt forests: Forestry and Timber Bureau Leaflet 107. 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). \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.

草地火险指数（Grass Fire Danger Index, GFDI）是一种火天气潜力指数，用于描述当前气象条件与近期降水格局对草地火情的潜在支撑作用。GFDI的计算依据McArthur, A.G.（1966、1973）的研究方法，依赖气温、相对湿度、风速以及草地枯熟度。该指数以极端事件对应数值100作为基准设定。本数据集提供澳大利亚全境的预测上限GFDI数值，基于一组年度超越概率定义。我们基于澳大利亚气象局（Bureau of Meteorology）最新的历史气象再分析数据集BARRA-R2计算GFDI，该数据集提供1979年至今每小时的模拟气象条件，空间分辨率约为11公里。草地枯熟度数值取自澳大利亚气象局MODIS MapVictoria草地枯熟度数据集2000至2019年模拟值的99分位数。随后，我们利用国家林火智能能力（National Bushfire Intelligence Capability, NBIC）极端值分析方法，对每个点位超过40万个数据点进行处理，以预测极端日最大值及其发生概率。GFDI已应用于实际业务场景，包括土地利用规划以及澳大利亚林火易发区建筑标准，是一项被广泛认可的火天气评估指标。上述特性使得本数据集在界定极端火天气方面实现了显著进展，超越了以往的研究方法，可为气候变化背景下澳大利亚日益严峻的林火风险管控与减灾决策提供坚实可靠的支撑基础。
数据集溯源：本基线情景下的草地火险指数数据通过澳大利亚气象局的历史气象再分析数据集BARRA-R2（https://dx.doi.org/10.25914/90rq-d839）计算得到，所用变量为近地面气温、近地面相对湿度与近地面风速。
草地枯熟度通过澳大利亚气象局MODIS 8日草地枯熟度时间序列的99分位数计算得到，该时间序列基于Wright等人（2015）[1]所述方法，由MODIS数据模拟生成。选取该分位数的目的是为了捕捉“合理极端最差情景”条件。
上述输入变量通过Noble等人（1980）[2]开发的方程进行整合，该方程基于McArthur（1966）[3]与McArthur（1973）[4]的研究成果。GFDI基于43年以上的每小时气象数据计算得到，随后通过极端值分析方法，模拟不同年度超越概率下的预期GFDI数值。
[1] Wright, D., Nichols, D., Slijepcevic, A., Kidnie, S., Chen, A., & Bessell, R. (2015). 澳大利亚多辖区草地燃料的精准评估. 收录于《林火与自然灾害CRC与AFAC会议论文集》，阿德莱德：林火与自然灾害CRC.
[2] Noble, I.R., Gill, A.M. 和 Bary, G.A.V., 1980. 以方程形式表达的McArthur火险指数. 《澳大利亚生态学杂志》，5(2)，第201-203页. https://doi.org/10.1111/j.1442-9993.1980.tb01243.x
[3] McArthur, A.G., 1967. 桉树林火行为：林业与木材局手册107. 澳大利亚堪培拉：林业与木材局.
[4] McArthur, A.G.（1973）《第四代草地火险指数仪》. 澳大利亚首都领地堪培拉：国家发展部林业与木材局（以圆形计算尺形式出版）.
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