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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 fire behaviour models. The system is modular and allows for ongoing incorporation of new scientific research and improved datasets. Aims: Prior to operational implementation of the AFDRS, a Research Prototype (AFDRSRP), described here, was built to test the input data and systems and evaluate the performance and potential outputs. Methods: Fire spread models were selected and aligned with fuel types in a process that captured bioregional variation in fuel characteristics. National spatial datasets were created to identify fuel types and fire history in alignment with existing spatial weather forecast layers. Key results: The AFDRSRP demonstrated improvements over the McArthur Forest and Grass Fire Danger systems due to its use of improved fire behaviour models, as well as more accurately reflecting the variation in fuels. Conclusions: The system design was robust and allowed for the incorporation of updates to the models and datasets prior to implementation of the AFDRS. A spatially explicit forecast calculation system was designed and implemented to assess a new fire danger rating system for Australia based on fire behaviour models, weather inputs and a national fuel spatial data layer. This article is part of a collection about the Australian Fire Danger Rating System. This article belongs to the Collection Australian Fire Danger Rating System. [ABSTRACT FROM AUTHOR]

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

Background. In Australia, grassland curing (senescence) is an essential component in fire danger calculations. In seven (out of eight) states/territories in Australia, operational curing data are derived from the MapVictoria satellite model. From 2013 to 2023, MapVictoria data have been calculated using MODerate resolution Imaging Spectroradiometer (MODIS) data from the Terra satellite. Terra has exceeded its designed mission lifetime, but the continuation of satellite curing data is crucial for fire agencies to continue fire danger calculations. Aims. The aim of this study was to adjust the MapVictoria model so it could be calculated using a newer satellite sensor system: Visible Infrared Imaging Radiometer Suite (VIIRS). Methods. Data from the VIIRS bands were adjusted to match those of MODIS using timeseries from 2013 to 2020. The adjusted VIIRS bands were used to derive a VIIRS curing model: ‘viirs-mvcuring’. Key results. The viirs–mvcuring model exhibited lower curing estimates than MODIS by up to 2.6% in Northern sites and 1.4% in Southern sites and exhibited lower curing estimates than groundbased curing by 0.1% in Northern sites and 3.5% in Southern sites. Conclusions. The development of the viirs–mvcuring model has ensured continued availability of satellite curing data. Implications. The transition to VIIRS will provide continued input of curing into fire danger calculations across Australia. [ABSTRACT FROM AUTHOR]

Wildfires are not only a natural part of many ecosystems, but they can also have disastrous consequences for humans, including in Australia. Rugged terrain adds to the difficulty of predicting fire behavior and fire spread, as fires often propagate contrary to expectations. Even though fire models generally incorporate weather, fuels, and topography, which are important factors affecting fire behavior, they usually only consider the surface wind; however, the more elevated winds should also be accounted for, in addition to surface winds, when predicting fire spread in rugged terrain because valley winds are often dynamically altered by the interaction of a layered atmosphere and the topography. Here, fire spread in rugged terrain was examined in a case study of the Riveaux Road Fire, which was ignited by multiple lightning strikes in January 2019 in southern Tasmania, Australia and burnt approximately 637.19 km2. Firstly, the number of conducive wind structures, which are defined as the combination of wind and temperature layers likely to result in enhanced surface wind, were counted by examining the vertical wind structure of the atmosphere, and the potential for above-surface winds to affect fire propagation was identified. Then, the multiple fire propagations were simulated using a new fire simulator (Prototype 2) motivated by the draft specification of the forthcoming new fire danger rating system, the Australian Fire Danger Rating System (AFDRS). Simulations were performed with one experiment group utilizing wind fields that included upper-air interactions, and two control groups that utilized downscaled wind from a model that only incorporated surface winds, to identify the impact of upper air interactions. Consequently, a detailed analysis showed that more conducive structures were commonly observed in the rugged terrain than in the other topography. In addition, the simulation of the experiment group performed better in predicting fire spread than those of the control groups in rugged terrain. In contrast, the control groups based on the downscaled surface wind model performed well in less rugged terrain. These results suggest that not only surface winds but also the higher altitude winds above the surface are required to be considered, especially in rugged terrain. [ABSTRACT FROM AUTHOR]