The Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia (BARRA) is the first atmospheric regional reanalysis over a large region covering Australia, New Zealand, and Southeast Asia. The production of the reanalysis with approximately 12 km horizontal resolution – BARRA-R – is well underway with completion expected in 2019. This paper describes the numerical weather forecast model, the data assimilation methods, the forcing and observational data used to produce BARRA-R, and analyses results from the 2003–2016 reanalysis. BARRA-R provides a realistic depiction of the meteorology at and near the surface over land as diagnosed by temperature, wind speed, surface pressure, and precipitation. Comparing against the global reanalyses ERA-Interim and MERRA-2, BARRA-R scores lower root mean square errors when evaluated against (point-scale) 2 m temperature, 10 m wind speed, and surface pressure observations. It also shows reduced biases in daily 2 m temperature maximum and minimum at 5 km resolution and a higher frequency of very heavy precipitation days at 5 and 25 km resolution when compared to gridded satellite and gauge analyses. Some issues with BARRA-R are also identified: biases in 10 m wind, lower precipitation than observed over the tropical oceans, and higher precipitation over regions with higher elevations in south Asia and New Zealand. Some of these issues could be improved through dynamical downscaling of BARRA-R fields using convective-scale (<2 km) models.

Regional reanalyses provide a dynamically consistent recreation of past weather observations at scales useful for local-scale environmental applications. The development of convection-permitting models (CPMs) in numerical weather prediction has facilitated the creation of kilometre-scale (1–4 km) regional reanalysis and climate projections. The Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia (BARRA) also aims to realize the benefits of these high-resolution models over Australian sub-regions for applications such as fire danger research by nesting them in BARRA's 12 km regional reanalysis (BARRA-R). Four midlatitude sub-regions are centred on Perth in Western Australia, Adelaide in South Australia, Sydney in New South Wales (NSW), and Tasmania. The resulting 29-year 1.5 km downscaled reanalyses (BARRA-C) are assessed for their added skill over BARRA-R and global reanalyses for near-surface parameters (temperature, wind, and precipitation) at observation locations and against independent 5 km gridded analyses. BARRA-C demonstrates better agreement with point observations for temperature and wind, particularly in topographically complex regions and coastal regions. BARRA-C also improves upon BARRA-R in terms of the intensity and timing of precipitation during the thunderstorm seasons in NSW and spatial patterns of sub-daily rain fields during storm events. BARRA-C reflects known issues of CPMs: overestimation of heavy rain rates and rain cells, as well as underestimation of light rain occurrence. As a hindcast-only system, BARRA-C largely inherits the domain-averaged bias pattern from BARRA-R but does produce different climatological extremes for temperature and precipitation. An added-value analysis of temperature and precipitation extremes shows that BARRA-C provides additional skill over BARRA-R when compared to gridded observations. The spatial patterns of BARRA-C warm temperature extremes and wet precipitation extremes are more highly correlated with observations. BARRA-C adds value in the representation of the spatial pattern of cold extremes over coastal regions but remains biased in terms of magnitude.

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

Lightning strikes are pervasive, however, their distributions vary both spatially and in time, resulting in a complex pattern of lightning-ignited wildfires. Over the last decades, lightning-ignited wildfires have become an increasing threat in south-east Australia. Lightning in combination with drought conditions preceding the fire season can increase probability of sustained ignitions. In this study, we investigate spatial and seasonal patterns in cloud-to-ground lightning strikes in the island state of Tasmania using data from the Global Position and Tracking System (GPATS) for the period January 2011 to June 2019. The annual number of lightning strikes and the ratio of negative to positive lightning (78:22 overall) were considerably different from one year to the next. There was an average of 80 lightning days per year, however, 50% of lightning strikes were concentrated over just four days. Most lightning strikes were observed in the west and north of the state consistent with topography and wind patterns. We searched the whole population of lightning strikes for those most likely to cause wildfires up to 72 h before fire detection and within 10 km of the ignition point derived from in situ fire ignition records. Only 70% of lightning ignitions were matched up with lightning records. The lightning ignition efficiency per stroke/flash was also estimated, showing an annual average efficiency of 0.24% ignition per lightning stroke with a seasonal maximum during summer. The lightning ignition efficiency as a function of different fuel types also highlighted the role of buttongrass moorland (0.39%) in wildfire incidents across Tasmania. Understanding lightning climatology provides vital information about lightning characteristics that influence the probability that an individual stroke causes ignition over a particular landscape. This research provides fire agencies with valuable information to minimize the potential impacts of lightning-induced wildfires through early detection and effective response.

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