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Understanding bushfire–atmosphere interactions is essential for accurate prediction of fire behaviour, and for the safe and effective strategic management of fires to mitigate risk to people and property. Bushfires with feedbacks to thunderstorms represent the most extreme form of fire–atmosphere interaction, with potential to initiate tornadoes, lightning and hazardous winds causing dangerous fire behaviour and new ignitions many kilometres from the fire front. However, there is very little evidence that links quantitative fire behaviour with observed thunderstorm dynamics. Here we combine stochastic modelling of fire behaviour with satellite and mobile weather radar data of a bushfire thunderstorm in Queensland, Australia. The results show the coupling between fire behaviour and thunderstorm development in a conditionally unstable atmosphere. The process by which the coupling occurs raises questions as to the cause and effect relationship of the bushfire-initiated thunderstorms and associated fire behaviour. Recommendations for future research are made, highlighting the need for understanding links between modelled and observed fire behaviour dynamics and atmospheric thermodynamics. Bushfires can support the evolution of thunderstorms. Here, we combine a variety of observations of a bushfire thunderstorm with ensemble fire spread modelling and fire severity mapping. Results show the coupling between the intensity of the fire and its burning through forest canopy with thunderstorm updrafts. [ABSTRACT FROM AUTHOR]

High‐resolution regional reanalysis datasets have the potential to provide valuable guidance to emergency management agencies, highlighting areas at risk of severe weather, including estimates of return periods of various hazardous weather phenomena. The BARRA regional reanalysis for Australia comprises a reanalysis for a broad region around Australia at moderately high spatial and temporal resolution (12 km/hourly), together with four subdomains at high resolution (1.5 km/1 h). Here, we document four applications of BARRA developed for emergency management: optimal placement of portable automatic weather stations for fire weather monitoring; climatology of low‐level wind shear conducive to cool‐season tornadogenesis; development of rainfall intensity–frequency–duration curves based on the gridded reanalysis data; and development of a climatology across Australia of parameters associated with severe thunderstorm occurrence. [ABSTRACT FROM AUTHOR]

Climate projections indicate that dangerous fire weather will become more common over the coming century. We examine the potential of a network of temperature- and moisture-sensitive tree-ring sites in southeastern Australia to reconstruct the number of high fire-danger days for the January--March season. Using the Forest Fire Danger Index (FFDI), we show that modestly statistically skilful reconstructions for the far southeast of Australia (western Tasmania), where the majority of tree-ring predictors are located, can be developed. According to the averaged reconstructions for the 1590-2008 period, there have been 16 years prior to the start of the FFDI records (1950), and 7 years since 1950, with >48 (mean + 1σ) high fire-danger days in the 3-month season. The western Tasmanian reconstructions indicate extended relatively high firedanger periods in the 1650s-1660s and 1880s-1890s. Fire danger has also been relatively high since 2000 CE. A persistent increase in the number of high fire-danger days over the past four decades has not been matched over the previous 390 years. This work indicates it is possible to produce statistically useful reconstructions of high seasonal fire danger -- as opposed to fire occurrence -- but that availability of local proxy records is key. [ABSTRACT FROM AUTHOR]

Reconstructed weather datasets, such as reanalyses based on model output with data assimilation, often show systematic biases in magnitude when compared with observations. Postprocessing approaches can help adjust the distribution so that the reconstructed data resemble the observed data as closely as possible. In this study, we have compared various statistical bias-correction approaches based on quantile–quantile matching to correct the data from the Twentieth Century Reanalysis, version 2c (20CRv2c), with observation-based data. Methods included in the comparison utilize a suite of different approaches: a linear model, a median-based approach, a nonparametric linear method, a spline-based method, and approaches that are based on the lognormal and Weibull distributions. These methods were applied to daily data in the Australian region for rainfall, maximum temperature, relative humidity, and wind speed. Note that these are the variables required to compute the forest fire danger index (FFDI), widely used in Australia to examine dangerous fire weather conditions. We have compared the relative errors and performances of each method across various locations in Australia and applied the approach with the lowest mean-absolute error across multiple variables to produce a reliable long-term bias-corrected FFDI dataset across Australia. The spline-based data correction was found to have some benefits relative to the other methods in better representing the mean FFDI values and the extremes from the observed records for many of the cases examined here. It is intended that this statistical bias-correction approach applied to long-term reanalysis data will help enable new insight on climatological variations in hazardous phenomena, including dangerous wildfires in Australia extending over the past century. [ABSTRACT FROM AUTHOR]

Fire activity in Australia is strongly affected by high inter-annual climate variability and extremes. Through changes in the climate, anthropogenic climate change has the potential to alter fire dynamics. Here we compile satellite (19 and 32 years) and ground-based (90 years) burned area datasets, climate and weather observations, and simulated fuel loads for Australian forests. Burned area in Australia's forests shows a linear positive annual trend but an exponential increase during autumn and winter. The mean number of years since the last fire has decreased consecutively in each of the past four decades, while the frequency of forest megafire years (>1 Mha burned) has markedly increased since 2000. The increase in forest burned area is consistent with increasingly more dangerous fire weather conditions, increased risk factors associated with pyroconvection, including fire-generated thunderstorms, and increased ignitions from dry lightning, all associated to varying degrees with anthropogenic climate change. The degree to which wildfire activity in Australia is affected by climate change is not well quantified. Here, the authors show that the frequency of forest fires and the area burned have increased significantly over recent decades, mainly due to an increase in dangerous fire weather conditions through warmer temperature and circulation changes. [ABSTRACT FROM AUTHOR]

Understanding the relationships between large-scale, low-frequency climate variability modes, fire weather conditions and lighting-ignited wildfires has implications for fire-weather prediction, fire management and conservation. This article proposes a Bayesian network framework for quantifying the influence of climate modes on fire weather conditions and occurrence of lightning-ignited wildfires. The main objectives are to describe and demonstrate a probabilistic framework for identifying and quantifying the joint and individual relationships that comprise the climate-wildfire system; gain insight into potential causal mechanisms and pathways; gauge the influence of climate modes on fire weather and lightning-ignition relative to that of local-scale conditions alone; assess the predictive skill of the network; and motivate the use of techniques that are intuitive, flexible and for which user‐friendly software is freely available. A case study illustrates the application of the framework to a forested region in southwest Australia. Indices for six climate variability modes are considered along with two hazard variables (observed fire weather conditions and prescribed burn area), and a 41-year record of lightning-ignited wildfire counts. Using the case study data set, we demonstrate that the proposed framework: (1) is based on reasonable assumptions provided the joint density of the variables is converted to multivariate normal; (2) generates a parsimonious and interpretable network architecture; (3) identifies known or partially known relationships between the variables; (4) has potential to be used in a predictive setting for fire weather conditions; and (5) climate modes are more directly related to fire weather conditions than to lightning-ignition counts. [ABSTRACT FROM AUTHOR]

Pyrocumulonimbus (pyroCb) wildfires cause devastation in many regions globally. Given that fire‐atmosphere coupling is associated with pyroCbs, future changes in coincident high index values of atmospheric instability and dryness (C‐Haines) and near‐surface fire weather are assessed for southeastern Australia using a regional climate projection ensemble. We show that observed pyroCb events occur predominantly on forested, rugged landscapes during extreme C‐Haines conditions, but over a wide range of surface fire weather conditions. Statistically significant increases in the number of days where both C‐Haines and near‐surface fire weather values are conducive to pyroCb development are projected across southeastern Australia, predominantly for November (spring), and less strongly for December (summer) in 2060‐2079 versus 1990‐2009, with future C‐Haines increases linked to increased 850‐hPa dewpoint depression. The increased future occurrence of conditions conducive to pyroCb development and their extension into spring have implications for mitigating these dangerous wildfires and urbanizing fire‐prone landscapes. Plain Language Summary: Pyrocumulonimbus wildfires (pyroCb) are extreme wildfires. They involve a coupling between the fire and the atmosphere, which drives dangerous fire conditions that result in fatalities and considerable damage. Climate change could amplify the conditions associated with pyroCb development. We use high‐resolution regional climate projection data to assess future changes in the risk of pyroCb occurrence for southeastern Australia. We demonstrate that atmospheric instability and dryness is a better indicator of pyroCb development than surface fire weather conditions, with topographic roughness and vegetation type also playing roles. Coincidences of high index values of atmospheric conditions (tropospheric instability and dryness) and surface fire weather conditions (temperature, humidity, wind speed, and precipitation) associated with pyroCb development are projected to increase in frequency predominantly for November (spring) in 2060‐2079 versus 1990‐2009, but less so for summer. The extension of the season conducive to pyroCbs into spring is important because Australian pyroCbs are typically summer phenomena. A change in seasonality has implications for resource allocations by fire agencies. Projected changes in the conditions conducive to pyroCbs are primarily associated with increased dryness at 1.5‐km altitude. These findings are relevant to the mitigation of pyroCbs, and they have implications for continued urban expansion on fire‐prone landscapes. Key Points: Significant increases in the frequency of conditions conducive to pyrocumulonimbus fires occur in November (Spring) 2060‐2079 versus 1990‐2009Atmospheric instability and dryness are better indicators of pyrocumulonimbus fire development than surface fire weatherLocations in southeast Australia where these changes are projected to occur are identified [ABSTRACT FROM AUTHOR]

The article presents a study on the impact of the atmospheric carbon dioxide on the fire weather in eastern Australia in February 2017. Mentioned is the use McArthur Forest Fire Danger Index (FFDI) in determining fuel dryness and wildlife danger in the region. Information is also offered on Australian Bureau of Meteorology's operational seasonal forecast system.