Australian Fire Danger Rating System Research Prototype: a climatology† DOI Creative Commons
Stéphane Sauvage, Paul Fox‐Hughes,

Stuart Matthews

et al.

International Journal of Wildland Fire, Journal Year: 2024, Volume and Issue: 33(3)

Published: March 21, 2024

Background Historical records of fire weather phenomena provide valuable insights into spatial and temporal trends which can inform further research are important tools for planning. Aims We outline a 19-year climatology Research Prototype (AFDRSRP), the new Australian Fire Danger Rating System, documenting its characteristics. Methods The analysis utilises Bureau Meteorology’s high-resolution reanalysis suite (BARRA), together with fuel data provided by agencies. examine distribution AFDRSRP. Distributions categorised type, analysing relative variability across time space. Key results validate broad behaviour system insight variation danger throughout Australia, adding detail to understanding timing peak both diurnally annually. Conclusions While AFDRSRP differs from operational in rating categories tuning algorithms, it nonetheless provides useful implementation. Implications These will be essential planning during seasons.

Language: Английский

Introduction to the Australian Fire Danger Rating System† DOI Creative Commons
J. J. Hollis,

Stuart Matthews,

Paul Fox‐Hughes

et al.

International Journal of Wildland Fire, Journal Year: 2024, Volume and Issue: 33(3)

Published: March 18, 2024

Background Fire danger rating systems are used daily across Australia to support fire management operations and communications the general public regarding potential danger. Aims In this paper, we introduce Australian Danger Rating System (AFDRS), providing a short historical account of in as well requirements for an improved forecast system. Methods The AFDRS combines nationally consistent, spatially explicit fuel information with weather advanced behaviour models knowledge produce locally relevant ratings potential. Key results A well-defined framework is essential categorising defining based on operational response, impact observable characteristics incidents. modular, supporting continuous incremental improvements allowing upgrades components response new science. Conclusions provides method estimate best available models, leading potentially significant way calculated, interpreted. Implications was implemented 2022, most change forecasting more than 50 years.

Language: Английский

Citations

19
Wildfire risk in a changing climate: Evaluating fire weather indices and their global patterns with CMIP6 multi-model projections DOI Creative Commons
Yan He, Zixuan Zhou, Eun‐Soon Im

et al.

Weather and Climate Extremes, Journal Year: 2025, Volume and Issue: unknown, P. 100751 - 100751

Published: Feb. 1, 2025

Language: Английский

Citations

1
A framework for defining fire danger to support fire management operations in Australia† DOI Creative Commons
J. J. Hollis,

Stuart Matthews,

Wendy R. Anderson

et al.

International Journal of Wildland Fire, Journal Year: 2024, Volume and Issue: 33(3)

Published: March 18, 2024

Background Development of the Australian Fire Danger Rating System began in 2017 with a project aimed at demonstrating feasibility new fire danger rating system through Research Prototype (AFDRSRP) that accounted for variability vegetation types, was nationally applicable, modular and open to continuous improvement. Aims In this manuscript, we identify define transition points categories AFDRSRP. We discuss user responses categorisation during live trial evaluation AFDRSRP reflect on limitations potential improvements. Methods A review available literature, broad consultation stakeholders reanalysis impact data were used determine suitable thresholds categorising within Key results transitions behaviour result application different management strategies or are associated variation serious consequences impacts. Conclusions The incorporated best science, supported by well-defined framework defining making it across jurisdictions range fuel types. Implications allows managers assess accuracy appropriateness forecasted danger.

Language: Английский

Citations

6
Australian Fire Danger Rating System: implementing fire behaviour calculations to forecast fire danger in a research prototype† DOI Creative Commons

B. J. Kenny,

Stuart Matthews,

Stéphane Sauvage

et al.

International Journal of Wildland Fire, Journal Year: 2024, Volume and Issue: 33(4)

Published: April 10, 2024

Background The Australian Fire Danger Rating System (AFDRS) was implemented operationally throughout Australia in September 2022, providing calculation of fire danger forecasts based on peer-reviewed behaviour models. system is modular and allows for ongoing incorporation new scientific research improved datasets. Aims Prior to operational implementation the AFDRS, a Research Prototype (AFDRSRP), described here, built test input data systems evaluate performance potential outputs. Methods spread models were selected aligned with fuel types process that captured bioregional variation characteristics. National spatial datasets created identify history alignment existing weather forecast layers. Key results AFDRSRP demonstrated improvements over McArthur Forest Grass due its use models, as well more accurately reflecting fuels. Conclusions design robust allowed updates prior AFDRS.

Language: Английский

Citations

5
Australian Fire Danger Rating System Research Prototype: a climatology† DOI Creative Commons
Stéphane Sauvage, Paul Fox‐Hughes,

Stuart Matthews

et al.

International Journal of Wildland Fire, Journal Year: 2024, Volume and Issue: 33(3)

Published: March 21, 2024

Background Historical records of fire weather phenomena provide valuable insights into spatial and temporal trends which can inform further research are important tools for planning. Aims We outline a 19-year climatology Research Prototype (AFDRSRP), the new Australian Fire Danger Rating System, documenting its characteristics. Methods The analysis utilises Bureau Meteorology’s high-resolution reanalysis suite (BARRA), together with fuel data provided by agencies. examine distribution AFDRSRP. Distributions categorised type, analysing relative variability across time space. Key results validate broad behaviour system insight variation danger throughout Australia, adding detail to understanding timing peak both diurnally annually. Conclusions While AFDRSRP differs from operational in rating categories tuning algorithms, it nonetheless provides useful implementation. Implications These will be essential planning during seasons.

Language: Английский

Citations

4