Climate Driver Influences on Prediction of the Australian Fire Behaviour Index
Article
Taylor, Rachel, Marshall, Andrew G., Crimp, Steven, Cary, Geoffrey J. and Harris, Sarah. 2024. "Climate Driver Influences on Prediction of the Australian Fire Behaviour Index." Atmosphere. 15 (2). https://doi.org/10.3390/atmos15020203
Article Title | Climate Driver Influences on Prediction of the Australian Fire Behaviour Index |
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ERA Journal ID | 210170 |
Article Category | Article |
Authors | Taylor, Rachel, Marshall, Andrew G., Crimp, Steven, Cary, Geoffrey J. and Harris, Sarah |
Journal Title | Atmosphere |
Journal Citation | 15 (2) |
Article Number | 203 |
Number of Pages | 19 |
Year | 2024 |
Publisher | MDPI AG |
ISSN | 2073-4433 |
Digital Object Identifier (DOI) | https://doi.org/10.3390/atmos15020203 |
Web Address (URL) | https://www.mdpi.com/2073-4433/15/2/203 |
Abstract | Fire danger poses a pressing threat to ecosystems and societies worldwide. Adequate preparation and forewarning can help reduce these threats, but these rely on accurate prediction of extreme fire danger. With the knowledge that climatic conditions contribute heavily to overall fire danger, this study evaluates the skill with which episodes of extreme fire danger in Australia can be predicted from the activity of large-scale climate driver patterns. An extremal dependence index for extreme events is used to depict the historical predictive skill of the Australian Bureau of Meteorology’s subseasonal climate prediction system in replicating known relationships between the probability of top-decile fire danger and climate driver states at a lead time of 2–3 weeks. Results demonstrate that the El Niño Southern Oscillation, Southern Annular Mode, persistent modes of atmospheric blocking, Indian Ocean Dipole and Madden-Julian Oscillation are all key for contributing to predictability of fire danger forecasts in different regions during critical fire danger periods. Northwest Australia is found to be particularly predictable, with the highest mean index differences (>0.50) when certain climate drivers are active, compared with the climatological index mean. This integrated approach offers a valuable resource for decision-making in fire-prone regions, providing greater confidence to users relying on fire danger outlooks for key management decisions, such as those involved in the sectors of national park and forest estate management, agriculture, emergency services, health and energy. Furthermore, the results highlight strengths and weaknesses in both the Australian Fire Danger Rating System and the operational climate model, contributing additional information for improving and refining future iterations of these systems. |
Keywords | Australia; extreme event skill score; subseasonal prediction; forecast skill; climate drivers; fire danger |
Contains Sensitive Content | Does not contain sensitive content |
ANZSRC Field of Research 2020 | 370105. Atmospheric dynamics |
Byline Affiliations | Australian National University |
Centre for Applied Climate Sciences | |
Australian Bureau of Meteorology | |
Country Fire Authority, Victoria, Australia |
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https://research.usq.edu.au/item/z5vx4/climate-driver-influences-on-prediction-of-the-australian-fire-behaviour-index
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