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A large literature on the sensitivity of streamflow response to climate variations has emerged over the past several decades, but the underlying mechanisms are not fully understood. The usual approaches to this problem have been simple and do not fully address its complexity, which involves the individual and joint effects of large‐scale climate modes and smaller‐scale weather features on streamflow volumes, the presence of persistence in these time series and their effects on antecedent conditions. Ongoing improvements in observational and reanalysis datasets and online access allow for better quantification of the connections between streamflow response, climate variability modes and regional weather features. The purpose of this paper is to determine whether Bayesian networks can be used to better identify key factors and their associated pathways leading to streamflow generation. A Markov blanket approach is described and illustrated using monthly streamflow series recorded at eight gauging stations within or immediately adjacent to the coastal region of eastern mainland Australia. The method is compared and contrasted with conventional multiple linear regression with discussion around this type of approach as part of a growing interest in machine learning applications. One example is used to illustrate the application of both approaches to a streamflow series exhibiting strong non‐stationarity. Results for the other streamflow series are included in a concise synthesis. Overall, the results suggest that Bayesian networks have several desirable features in terms of transparency, interpretability and explanatory insight. The findings from this study lend support to the use of Bayesian networks for modelling connections between streamflow volume and the variability of climate and regional weather. This improved understanding of the key controls of streamflow variability is intended to help address growing needs around informing social, cultural, economic and ecological aspects of water planning and management. [ABSTRACT FROM AUTHOR]

Regional understanding of severe surface winds produced by convective processes [severe convective winds (SCWs)] is important for decision-making in several areas of society, including weather forecasting and engineering design. Meteorological studies have demonstrated that SCWs can occur due to a number of different mesoscale and microscale processes, in a range of large-scale atmospheric environments. However, long-term observational studies of SCW characteristics often have not considered this diversity in physical processes, particularly in Australia. Here, a statistical clustering method is used to separate a large dataset of SCW events, measured by automatic weather stations around Australia, into three types, associated with strong background wind, steep lapse rate, and high moisture environments. These different types of SCWs are shown to have different seasonal and spatial variations in their occurrence, as well as different measured wind gust, lightning, and parent-storm characteristics. In addition, various convective diagnostics are tested in their ability to discriminate between measured SCW events and nonsevere events, with significant variations in skill between event types. Differences in environmental conditions and wind gust characteristics between event types suggests potentially different physical processes for SCW production. These findings are intended to improve regional understanding of severe wind characteristics, as well as environmental prediction of SCWs in weather and climate applications, by considering different event types. Significance Statement: The purpose of this study is to improve regional understanding of different types of severe wind events in Australia, specifically those associated with atmospheric convection. We did this by constructing a dataset of 413 severe convective wind events, using weather station and radar data within 20 regions around Australia. We then split those events into three different types, based on the environmental conditions that they occur within. We found that each event type tends to occur at different times of the year and in different regions, while also having different wind gust and lightning characteristics. In addition, the atmospheric conditions that are helpful for prediction of severe wind events differs between each type. These results are intended to be useful for prediction of severe wind events associated with convection and assessing their variability, characteristics, and impacts, in both weather forecasting and climate analysis. [ABSTRACT FROM AUTHOR]

Severe winds associated with thunderstorms and convection are a hazard affecting key aspects of society, including emergency management and infrastructure design. Several studies around the world have shown that severe convective winds (SCWs) can occur due to several different processes, in a range of atmospheric environments, with significant regional and temporal variations. However, in eastern Australia, the types of SCWs and their variability have not been assessed outside of individual case studies. Here, a combination of reanalysis, lightning, radar, and station data are used to characterize a set of 36 SCW events in four locations in eastern Australia. These events are objectively chosen based on the strongest measured wind gusts from station data (greater than 25 m s−1) over a 14-yr period, with 6-hourly lightning data and a 30-dBZ radar reflectivity threshold used to infer moist convective processes. Radar data analysis suggests that these SCW events are produced by several different types of parent thunderstorms, with station observations suggesting a range of temporal characteristics for these different event types. A clustering algorithm applied to environmental data is used to suggest three dominant types of events, based on low-level moisture, low-level temperature lapse rate, and deep-layer mean wind speed and vertical shear. Based on the distribution of synoptic conditions and thunderstorm properties for each environmental cluster, it is suggested that these three event types correspond to the following: 1) shallow vertical transport of strong synoptic-scale winds to the surface, 2) downbursts driven by subcloud evaporation, and 3) intense thunderstorms including supercells. Significance Statement: The purpose of this study is to better understand the different types of severe wind events in eastern Australia that are produced by convective storms. We looked at 36 historical cases in four locations and find that severe winds can be produced by very different classes of convective storms. We also suggest that there are three key types of atmospheric environment that are associated with events in this region. These environments vary in terms of the vertical structure of temperature, moisture, and wind speed above the surface. Understanding the different types of environments that lead to severe convective winds can help to reduce uncertainties in future climate projections for this region based on environmental changes. [ABSTRACT FROM AUTHOR]

Extratropical cyclones are responsible for the majority of total and extreme rainfall in many regions of the extratropics, including in southern Australia. Using an ensemble of projections from 12 regional climate models, we show that both the number of cyclone days and total cyclone-related rainfall are projected to decline across southern Australia during the twenty-first century. This is a robust signal in projections across models and explains more than 80% of projected declines in total cool-season rainfall in the region. Using cyclone-centered composites, we show that cyclone intensity based on wind speed is projected to decrease but cyclone maximum rainfall is projected to increase by close to 7% K−1 in the southeast. This results in a shift in the distribution of cyclone rainfall, with a decrease in moderate rainfall but little change or an increase in extreme rainfall. Significance Statement: Extratropical cyclones are very important for southern Australian rainfall, and they are expected to become less frequent in a warming climate. Our research shows this explains at least 80% of the projected decline in cool-season rainfall in southern Australia. However, the frequency of extratropical cyclones with very heavy rainfall may increase, particularly in Tasmania and the southeast coast, with increases in rainfall intensity in line with the Clausius–Clapeyron relationship. This contributes to increases in the frequency of very heavy rainfall in the future. [ABSTRACT FROM AUTHOR]

Epidemic asthma events represent a significant risk to emergency services as well as the wider community. In southeastern Australia, these events occur in conjunction with relatively high amounts of grass pollen during the late spring and early summer, which may become concentrated in populated areas through atmospheric convergence caused by a number of physical mechanisms including thunderstorm outflow. Thunderstorm forecasts are therefore important for identifying epidemic asthma risk factors. However, the representation of thunderstorm environments using regional numerical weather prediction models, which are a key aspect of the construction of these forecasts, have not yet been systematically evaluated in the context of epidemic asthma events. Here, we evaluate diagnostics of thunderstorm environments from historical simulations of weather conditions in the vicinity of Melbourne, Australia, in relation to the identification of epidemic asthma cases based on hospital data from a set of controls. Skillful identification of epidemic asthma cases is achieved using a thunderstorm diagnostic that describes near-surface water vapor mixing ratio. This diagnostic is then used to gain insights on the variability of meteorological environments related to epidemic asthma in this region, including diurnal variations, long-term trends, and the relationship with large-scale climate drivers. Results suggest that there has been a long-term increase in days with high water vapor mixing ratio during the grass pollen season, with large-scale climate drivers having a limited influence on these conditions. Significance Statement: We investigate the atmospheric conditions associated with epidemic thunderstorm asthma events in Melbourne, Australia, using historical model simulations of the weather. Conditions appear to be associated with high atmospheric moisture content, which relates to environments favorable for severe thunderstorms, but also potentially pollen rupturing as suggested by previous studies. These conditions are shown to be just as important as the concentration of grass pollen for a set of epidemic thunderstorm asthma events in this region. This means that weather model simulations of thunderstorm conditions can be incorporated into the forecasting process for epidemic asthma in Melbourne, Australia. We also investigate long-term variability in atmospheric conditions associated with severe thunderstorms, including relationships with the large-scale climate and long-term trends. [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]

Most of the rainfall in southern Australia is associated with cyclones, cold fronts, and thunderstorms, and cases when these weather systems co-occur are particularly likely to cause extreme rainfall. Rainfall declines in some parts of southern Australia during the cool half of the year in recent decades have previously been attributed to decreases in the rainfall from fronts and/or cyclones, while thunderstorm-related rainfall has been observed to increase, particularly in the warm half of the year. However, the co-occurrence of these systems, particularly the co-occurrence of cyclones or fronts with thunderstorms, can be very important for rainfall in some areas, particularly heavy rainfall, and changes in the frequency of these combined weather systems have not been previously assessed. In this paper we show that the majority of the observed cool season rainfall decline between 1979–1996 and 1997–2015 in southeast Australia is associated with a decrease in the frequency of fronts and cyclones that produce rainfall, while there has simultaneously been an increase in the frequency of cold fronts and thunderstorms that do not produce rainfall in some regions. Thunderstorm rainfall has increased in much of southern Australia, particularly during the warm half of the year, including an increase in rainfall where a thunderstorm environment occurs at the same time as a cyclone or front. [ABSTRACT FROM AUTHOR]

A systematic analysis of the main weather types influencing southern Australian rainfall is presented for the period 1979–2015. This incorporates two multi-method datasets of cold fronts and low pressure systems, which indicate the more robust fronts and lows as distinguished from the weaker and less impactful events that are often indicated only by a single method. The front and low pressure system datasets are then combined with a dataset of environmental conditions associated with thunderstorms, as well as datasets of warm fronts and high pressure systems. The results demonstrate that these weather types collectively account for about 86% of days and more than 98% of rainfall in Australia south of 25° S. We also show how the key rain-bearing weather systems vary throughout the year and for different regions, with the co-occurrence of simultaneous lows, fronts and thunderstorm conditions particularly important during the spring and summer months in southeast Australia. [ABSTRACT FROM AUTHOR]

Cyclones can be identified from gridded pressure data at different levels of the troposphere, with vertical structure known to influence the temporal development and impacts of midlatitude cyclones. However, studies of midlatitude cyclones typically focus on cyclones identified at a single atmospheric level. This paper examines how the frequency of vertically organized or deep cyclones varies around the world, with a focus on southeastern Australia. About 50% of global cyclones identified from mean sea level pressure show a coherent vertical structure extending to at least 500 hPa, based on ERA-Interim reanalysis data, and shallow cyclones are most common in the global midlatitudes. Using a combination of reanalysis data and satellite-based rainfall and lightning, we show that in southeast Australia deep cyclones have higher intensities, longer durations, and more severe winds and rainfall than either shallow surface cyclones or upper-level cyclones with no surface low, motivating a three-dimensional approach for future cyclone analyses. [ABSTRACT FROM AUTHOR]

The thunderstorm climatology of Australia is examined, including convective rainfall events. Lightning observations are used to train a systematic method for indicating thunderstorm activity, with the method applied to environmental variables obtained from reanalysis data from 1979 to 2016. A range of maps showing seasonal averages in thunderstorm conditions as well as associated rainfall are presented. Long-term climate change trends are also examined, as well as the influence of large-scale drivers such as the El Niño-Southern Oscillation, Indian Ocean Dipole and Southern Annular Mode. Rainfall observations are examined for days on which thunderstorm activity is indicated based on this method, enabling new insight on convection-related rainfall. Low rainfall days are also used to examine the climatology of dry lightning as this is important for understanding the risk of wildfire ignitions. A long-term decrease in thunderstorm activity is indicated for many regions of Australia, as well as some regions of increase. The results also indicate a long-term increase in thunderstorm-related rainfall, noting implications for water availability, design standards and flood risk factors. The findings for northern Australia help provide insight on some aspects of the Australian monsoon, including based on a reduced frequency of days with convective environments as well as indicating an increased intensity of convective rainfall events. An increase in convective rainfall is indicated for both northern and southern Australia, while for non-convective rainfall the results indicate an increase in northern Australia and a decrease in southern Australia. Long-term changes in dry lightning events are also identified, depending on the region and season, noting implications for wildfire management. [ABSTRACT FROM AUTHOR]

Intense cyclones often result in severe impacts on mid-latitude coastal regions of southeastern Australia, including those due to associated natural hazards such as extreme winds, ocean waves, storm surges, precipitation, flooding, erosion, lightning and tornadoes in some cases. These low-pressure systems, known as east coast lows (ECLs), have been examined in a wide range of different studies, with considerable variations between such studies in what they consider to be an ECL, and their findings on the characteristics of these storm systems. Here we present reviews of literature and other information such as operational forecasting approaches, which are then used to produce a comprehensive synthesis of knowledge on ECLs and associated weather and ocean extremes. This includes aspects such as their definition, formation, meteorology, climatology and drivers of variability from short-term weather time scales up to long-term historical climate trends and future projections. Australian ECLs are also considered here in relation to similar phenomena from other regions of the world. A definition based on this synthesis of knowledge is as follows: ECLs are cyclones near southeastern Australia that can be caused by both mid-latitude and tropical influences over a range of levels in the atmosphere; Intense ECLs have at least one major hazard associated with their occurrence, including extreme winds, waves, rain or flooding. Knowledge gaps are examined and used to provide recommendations for future research priorities. This study is intended to lead to improved guidance and preparedness in relation to the impacts of these storms. [ABSTRACT FROM AUTHOR]

A global climatology of anticyclones identified at mean sea level pressure is presented based on multiple reanalyses over the period 1960–2016, including assessment of regional and seasonal variations, interannual variability, and long-term trends. Interannual variability is associated with the El Niño-Southern Oscillation (ENSO), particularly in the Pacific region during November–April. Anticyclones vary in phase with the strength and intensity of the local mean subtropical ridge, with anticyclone variability also associated with the Southern Annular Mode (SAM) in the Southern Hemisphere and the Arctic Oscillation (AO) in parts of the Northern Hemisphere, particularly during the cooler months of the year. Long-term climatological trends in anticyclone occurrence are presented, including back to 1960 using 20CR reanalysis data. The strongest trends occur in the Southern Hemisphere, including increases in anticyclone frequency in the latitudes 30–40 S and decreases for adjacent latitudes in both seasons, which can be partially attributed to changes in SAM during November–April. [ABSTRACT FROM AUTHOR]

The subtropical east coast region of Australia is characterized by the frequent occurrence of low pressure systems, known as east coast lows (ECLs). The more intense ECLs can cause severe damage and disruptions to this region. While the term 'east coast low' refers to a broad classification of events, it has been argued that different ECLs can have substantial differences in their nature, being dominated by baroclinic and barotropic processes in different degrees. Here we reexamine two well-known historical ECL case studies under this perspective: the Duck storm of March 2001 and the Pasha Bulker storm of June 2007. Exploiting the cyclone phase space analysis to study the storms' full three-dimensional structure, we show that one storm has features similar to a typical extratropical frontal cyclone, while the other has hybrid tropical-extratropical characteristics. Furthermore, we examine the energetics of the atmosphere in a limited area including both systems for the ECL occurrence times, and show that the two cyclones are associated with different signatures in the energy conversion terms. We argue that the systematic use of the phase space and energetics diagnostics can form the basis for a physically based classification of ECLs, which is important to advance the understanding of ECL risk in a changing climate. [ABSTRACT FROM AUTHOR]

Lightning is a natural hazard that can lead to the ignition of wildfires, disruption and damage to power and telecommunication infrastructures, human and livestock injuries and fatalities, and disruption to airport activities. This paper examines the ability of six statistical and machine-learning classification techniques to distinguish between nonlightning and lightning days at the coarse spatial and temporal scales of current general circulation models and reanalyses. The classification techniques considered were 1) a combination of principal component analysis and logistic regression, 2) classification and regression trees, 3) random forests, 4) linear discriminant analysis, 5) quadratic discriminant analysis, and 6) logistic regression. Lightning-flash counts at six locations across Australia for 2004-13 were used, together with atmospheric variables from the ERA-Interim dataset. Tenfold cross validation was used to evaluate classification performance. It was found that logistic regression was superior to the other classifiers considered and that its prediction skill is much better than using climatological values. The sets of atmospheric variables included in the final logistic-regression models were primarily composed of spatial mean measures of instability and lifting potential, along with atmospheric water content. The memberships of these sets varied among climatic zones. [ABSTRACT FROM AUTHOR]

Abstract: Extreme wildfires with strong convective processes in their plumes have recently led to disastrous impacts on various regions of the world. The Continuous Haines index (CH) is used in Australia to represent vertical atmospheric stability and humidity measures relating to pyroconvective processes. CH climatology is examined here using reanalysis data from 1979 to 2016, revealing large spatial and seasonal variations throughout Australia. Various measures of severity are investigated, including regionally specific thresholds. CH is combined with near‐surface fire weather conditions, as a type of compound event, and is examined in relation to environmental conditions associated with pyroconvection. Significant long‐term changes in CH are found for some regions and seasons, with these changes corresponding to changes in near‐surface conditions in some cases. In particular, an increased risk of pyroconvection is identified for southeast Australia during spring and summer, due to decreased vertical atmospheric stability and humidity combined with more severe near‐surface conditions. [ABSTRACT FROM AUTHOR]

Long-term variations in fire weather conditions are examined throughout Australia from gridded daily data from 1950 to 2016. The McArthur forest fire danger index is used to represent fire weather conditions throughout this 67-yr period, calculated on the basis of a gridded analysis of observations over this time period. This is a complementary approach to previous studies (e.g., those based primarily on model output, reanalysis, or individual station locations), providing a spatially continuous and long-term observations-based dataset to expand on previous research and produce climatological guidance information for planning agencies. Long-term changes in fire weather conditions are apparent in many regions. In particular, there is a clear trend toward more dangerous conditions during spring and summer in southern Australia, including increased frequency and magnitude of extremes, as well as indicating an earlier start to the fire season. Changes in fire weather conditions are attributable at least in part to anthropogenic climate change, including in relation to increasing temperatures. The influence of El Niño-Southern Oscillation (ENSO) on fire weather conditions is found to be broadly consistent with previous studies (indicating more severe fire weather in general for El Niño conditions than for La Niña conditions), but it is demonstrated that this relationship is highly variable (depending on season and region) and that there is considerable potential in almost all regions of Australia for long-range prediction of fire weather (e.g., multiweek and seasonal forecasting). It is intended that improved understanding of the climatological variability of fire weather conditions will help lead to better preparedness for risks associated with dangerous wildfires in Australia. [ABSTRACT FROM AUTHOR]

Lightning accompanied by inconsequential rainfall (i.e., 'dry' lightning) is the primary natural ignition source for wildfires globally. This paper presents a machine-learning and statistical-classification analysis of dry and 'wet' thunderstorm days in relation to associated atmospheric conditions. The study is based on daily data for lightning-flash count and precipitation from ground-based sensors and gauges and a comprehensive set of atmospheric variables that are based on ERA-Interim for the period from 2004 to 2013 at six locations in Australia. These locations represent a wide range of climatic zones (temperate, subtropical, and tropical). Quadratic surface representations and low-dimensional summary statistics were used to characterize the main features of the atmospheric fields. Four prediction skill scores were considered, and 10-fold cross validation was used to evaluate the performance of each classifier. The results were compared with those obtained by adopting the approach used in an earlier study for the U.S. Pacific Northwest. It was found that both approaches have prediction skill when tested against independent data, that mean atmospheric field quantities proved to be the most influential variables in determining dry-lightning activity, and that no single classifier or set of atmospheric variables proved to be consistently superior to its counterpart for the six sites examined here. [ABSTRACT FROM AUTHOR]

Tropical cyclone ( TC) observations are used to examine changes in the TC climatology of the Australian region. The ability to investigate long-term changes in TC numbers improves when the El Niño-Southern Oscillation ( ENSO) is considered. Removing variability in TC numbers associated with ENSO shows a significant decreasing trend in TC numbers at the 93-98% confidence level. Additionally, there is some indication of a temporal change in the relationship between ENSO and TC numbers, with ENSO accounting for about 35-50% of the variance in TC numbers during the first half of the study period, but only 10% during the second half. [ABSTRACT FROM AUTHOR]

ABSTRACT Extratropical cyclones that develop near the east coast of Australia often have severe consequences such as flash flooding and damaging winds and seas, as well as beneficial consequences such as being responsible for heavy rainfall events that contribute significantly to total rainfall and runoff. There is subjective evidence that the development of most major events, commonly known as East Coast Lows ( ECLs), is associated with the movement of a high amplitude upper-tropospheric trough system over eastern Australia. To test this hypothesis, this study examines a number of large-scale diagnostic quantities in the upper-troposphere associated with extratropical cyclogenesis. Climatologies of these diagnostic quantities, based on reanalyses, are examined and compared with a database of observed ECL events. Results are examined in relation to seasonal and geographic variations. A diagnostic quantity based on geostrophic vorticity is shown to provide a good indication of the likely occurrence of east-coast cyclogenesis. The potential application of these diagnostics to global climate model simulations of past and future climates is also discussed. [ABSTRACT FROM AUTHOR]

In the original published version of the paper, the figures reported in Sect. 4 relating the proportion of rainfall in southern Australia that is due to each of the weather types, were incorrectly stated for the entire Australian landmass, with the same error also affecting Figs. 6 and 8. [ABSTRACT FROM AUTHOR]

The east coast of Australia is a region of the world where a particular type of extratropical cyclone, known locally as an east coast low, frequently occurs with severe consequences such as extreme rainfall, winds, and waves. The likelihood of formation of these storms is examined using an upper-tropospheric diagnostic applied to three reanalyses and three global climate models (GCMs). Strong similarities exist among the results derived from the individual reanalyses in terms of their seasonal variability (e.g., winter maxima and summer minima) and interannual variability. Results from reanalyses indicate that the threshold value used in the diagnostic method is dependent on the spatial resolution. Results obtained when applying the diagnostic to two of the three GCMs are similar to expectations given their spatial resolutions, and produce seasonal cycles similar to those from the reanalyses. Applying the methodology to simulations from these two GCMs for both current and future climate in response to increases in greenhouse gases indicates a reduction in extratropical cyclone occurrence of about 30% from the late twentieth century to the late twenty-first century for eastern Australia. In addition to the absolute risk of formation of these extratropical cyclones, spatial climatologies of occurrence are examined for the broader region surrounding eastern Australia. The influence of large-scale modes of atmospheric and oceanic variability on the occurrence of these storms in this region is also discussed. [ABSTRACT FROM AUTHOR]

Satellite remote sensing is vital to accurately estimate tropical cyclone (TC) parameters such as position and intensity. A TC archive for the Southern Hemisphere (SH) has been prepared for the ‘satellite era’, and it now consists of best track data, covering name (and/or unique identification number), position and intensity (in terms of central pressure). Based on these best track data, TC climatologies for the South Indian Ocean (SIO) and South Pacific Ocean (SPO) are investigated. Variability in TC activity is examined depending on different phases of the El Niño-Southern Oscillation (ENSO). The outcomes demonstrate prospects for improving the regional seasonal prediction of TC activity. The growth in the availability of satellite data is found to have a significant influence on the quantity and quality of available TC data, particularly in relation to the intensity of TCs. To provide a means of accessing detailed information and data on historical TCs in the SH, a specialized website for disseminating results and data was developed using the OpenLayers platform. This allows dynamic map navigation of detailed information for user-selected regions. [ABSTRACT FROM AUTHOR]

A systematic examination is presented of the relationship between lightning occurrence and fires attributed to lightning ignitions. Lightning occurrence data are matched to a database of fires attributed to lightning ignition over southeastern Australia and are compared with atmospheric and fuel characteristics at the time of the lightning occurrence. Factors influencing the chance of fire per lightning stroke are examined, including the influence of fuel moisture and weather parameters, as well as seasonal and diurnal variations. The fuel moisture parameters of the Canadian Fire Weather Index System are found to be useful in indicating whether a fire will occur, given the occurrence of lightning. The occurrence of 'dry lightning' (i.e., lightning that occurs without significant rainfall) is found to have a large influence on the chance of fire per lightning stroke. Through comparison of the results presented here with the results of studies from other parts of the world, a considerable degree of universality is shown to exist in the characteristics of lightning fires and the atmospheric conditions associated with them, suggesting the potential for these results to be applied more widely than just in the area of the study. [ABSTRACT FROM AUTHOR]

Climatological features of tropical cyclones in the South Pacific Ocean have been analyzed based on a new archive for the Southern Hemisphere. A vortex tracking and statistics package is used to examine features such as climatological maps of system intensity and the change in intensity with time, average tropical cyclone system movement, and system density. An examination is presented of the spatial variability of these features, as well as changes in relation to phase changes of the El Niño-Southern Oscillation phenomenon. A critical line is defined in this study based on maps of cyclone intensity to describe the statistical geographic boundary for cyclone intensification. During El Niño events, the critical line shifts equatorward, while during La Niña events the critical line is generally displaced poleward. Regional variability in tropical cyclone activity associated with El Niño-Southern Oscillation phases is examined in relation to the variability of large-scale atmospheric or oceanic variables associated with tropical cyclone activity. Maps of the difference fields between different phases of El Niño-Southern Oscillation are examined for sea surface temperature, vertical wind shear, lower-tropospheric vorticity, and midtropospheric relative humidity. Results are also examined in relation to the South Pacific convergence zone. The common region where each of the large-scale variables showed favorable conditions for cyclogenesis coincided with the location of maximum observed cyclogenesis for El Niño events as well as for La Niña years. [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]

The Australian Bureau of Meteorology has developed a national hydrological projections (NHP) service for Australia. The NHP aimed to provide nationally consistent hydrological projections across jurisdictional boundaries to support planning of water-dependent industries. NHP is complementary to those previously produced by federal and state governments, universities, and other organisations for limited geographical domains. The projections comprise an ensemble of application-ready bias-corrected climate model data, derived hydrological projections at daily temporal and 0.05° × 0.05° spatial resolution for the period 1960–2099, and two emission scenarios (Representative Concentration Pathway (RCP) 4.5 and RCP8.5). The spatial resolution of the projections matches that of gridded historical reference data used to perform the bias correction and the Bureau of Meteorology's operational gridded hydrological model. Three bias correction techniques were applied to four CMIP5 global climate models (GCMs), and one method was applied to a regional climate model (RCM) forced by the same four GCMs, resulting in a 16-member ensemble of bias-corrected GCM data for each emission scenario. The bias correction was applied to fields of precipitation, minimum and maximum temperature, downwelling shortwave radiation, and surface winds. These variables are required inputs to the Bureau of Meteorology's landscape water balance hydrological model (AWRA-L), which was forced using the bias-corrected GCM and RCM data to produce a 16-member ensemble of hydrological output. The hydrological output variables include root zone soil moisture (moisture in the top 1 m soil layer), potential evapotranspiration, and runoff. Here we present an overview of the production of the hydrological projections, including GCM selection, bias correction methods and their evaluation, technical aspects of their implementation, and examples of analysis performed to construct the NHP service. The data are publicly available on the National Computing Infrastructure (10.25914/6130680dc5a51, Bureau of Meteorology, 2021), and a user interface is accessible at https://awo.bom.gov.au/products/projection/ (last access: 24 November 2023). [ABSTRACT FROM AUTHOR]

Extreme wildfires have recently caused disastrous impacts in Australia and other regions of the world, including events with strong convective processes in their plumes (i.e., strong pyroconvection). Dangerous wildfire events such as these could potentially be influenced by anthropogenic climate change, however, there are large knowledge gaps on how these events might change in the future. The McArthur Forest Fire Danger Index (FFDI) is used to represent near-surface weather conditions and the Continuous Haines index (CH) is used here to represent lower to mid-tropospheric vertical atmospheric stability and humidity measures relevant to dangerous wildfires and pyroconvective processes. Projected changes in extreme measures of CH and FFDI are examined using a multi-method approach, including an ensemble of global climate models together with two ensembles of regional climate models. The projections show a clear trend towards more dangerous near-surface fire weather conditions for Australia based on the FFDI, as well as increased pyroconvection risk factors for some regions of southern Australia based on the CH. These results have implications for fields such as disaster risk reduction, climate adaptation, ecology, policy and planning, noting that improved knowledge on how climate change can influence extreme wildfires can help reduce future impacts of these events. [ABSTRACT FROM AUTHOR]

Anthropogenic climate change is changing the Earth system processes that control the characteristics of natural hazards both globally and across Australia. Model projections of hazards under future climate change are necessary for effective adaptation. This paper presents BARPA-R (the Bureau of Meteorology Atmospheric Regional Projections for Australia), a regional climate model designed to downscale climate projections over the Australasian region with the purpose of investigating future hazards. BARPA-R, a limited-area model, has a 17 km horizontal grid spacing and makes use of the Met Office Unified Model (MetUM) atmospheric model and the Joint UK Land Environment Simulator (JULES) land surface model. To establish credibility and in compliance with the Coordinated Regional Climate Downscaling Experiment (CORDEX) experiment design, the BARPA-R framework has been used to downscale ERA5 reanalysis. Here, an assessment of this evaluation experiment is provided. Performance-based evaluation results are benchmarked against ERA5, with comparable performance between the free-running BARPA-R simulations and observationally constrained reanalysis interpreted as a good result. First, an examination of BARPA-R's representation of Australia's surface air temperature, precipitation, and 10 m winds finds good performance overall, with biases including a 1 ∘ C cold bias in daily maximum temperatures, reduced diurnal temperature range, and wet biases up to 25 mm per month in inland Australia. Recent trends in daily maximum temperatures are consistent with observational products, while trends in minimum temperatures show overestimated warming and trends in precipitation show underestimated wetting in northern Australia. Precipitation and temperature teleconnections are effectively represented in BARPA-R when present in the driving boundary conditions, while 10 m winds are improved over ERA5 in six out of eight of the Australian regions considered. Secondly, the paper considers the representation of large-scale atmospheric circulation features and weather systems. While generally well represented, convection-related features such as tropical cyclones, the South Pacific Convergence Zone (SPCZ), the Northwest Cloudband, and the monsoon westerlies show more divergence from observations and internal interannual variability than mid-latitude phenomena such as the westerly jets and extratropical cyclones. Having simulated a realistic Australasian climate, the BARPA-R framework will be used to downscale two climate change scenarios from seven CMIP6 global climate models (GCMs). [ABSTRACT FROM AUTHOR]

Anticyclones are one of the main synoptic features of the global midlatitudes, where they are associated with dry, settled conditions. Previous studies have identified southern Australia as a region where significant long-term changes have occurred in recent decades, including a decline in cool season rainfall and an increase in the frequency of anticyclones. This paper uses several reanalyses to assess the climatology, variability, trends and impacts of anticyclones in southern Australia and several subregions. A robust increase in the frequency of anticyclones in southern Australia is demonstrated between 1960–1979 and 1997–2014, particularly in southeast Australia and the Tasman Sea during the cool months of the year. At least 30% of the recent cool season rainfall decline in southeast Australia can be associated with an increased frequency of anticyclones in this region. However, there are no clear trends in anticyclone frequency near southwestern Western Australia, where long-term rainfall declines are due to changes in other weather systems. [ABSTRACT FROM AUTHOR]

Anthropogenic climate change is changing the earth system processes that control the characteristics of natural hazards both globally and across Australia. Model projections of hazards under future climate change are necessary for effective adaptation. This paper presents BARPA-R (the Bureau of Meteorology Atmospheric Regional Projections for Australia), a regional climate model designed to downscale climate projections over the Australasian region with the purpose to investigate future hazards. BARPA-R, a limited area model, has a 17 km horizontal grid-spacing and makes use of the Met Office Unified Model (MetUM) atmospheric model and the Joint UK Land Environment Simulator (JULES) land surface model. To establish credibility and in compliance with the Coordinated Regional Climate Downscaling Experiment (CORDEX) experiment design, the BARPA-R framework has been used to downscale ERA-5 reanalysis. Here, an assessment of this evaluation experiment is provided. First, an examination of BARPA-R's representation of Australia's surface air temperature, rainfall and 10-m winds finds good performance overall, with biases including a 1K cold bias in daily maximum temperatures, reduced diurnal temperature range, and wet biases up to 25 mm/month in inland Australia. Recent trends in diurnal maximum temperatures are consistent with observational products, while trends in minimum temperatures show overestimated warming and trends in rainfall show underestimated wetting in northern Australia. Rainfall and temperature teleconnections are effectively represented in BARPA-R when present in the driving boundary conditions, while 10-metre winds are improved over ERA5 in six out of eight of the Australian regions considered. The second section of the paper considers the representation of large-scale atmospheric circulation features and weather systems. While generally well represented, convection-related features such as tropical cyclones, the SPCZ, Northwest Cloud-Bands and the monsoon westerlies show more divergence from observations and internal interannual variability than mid-latitude phenomena such as the westerly jets and extra-tropical cyclones. Having simulated a realistic Australasian climate, the BARPA-R framework will be used to downscale two climate change scenarios from seven CMIP6 GCMs. [ABSTRACT FROM AUTHOR]

Preparing for environmental risks requires estimating the frequencies of extreme events, often from data records that are too short to confirm them directly. This requires fitting a statistical distribution to the data. To improve precision, investigators often pool data from neighboring sites into single samples, referred to as "superstations," before fitting. We demonstrate that this technique can introduce unexpected biases in typical situations, using wind and rainfall extremes as case studies. When the combined locations have even small differences in the underlying statistics, the regionalization approach gives a fit that may tend toward the highest levels suggested by any of the individual sites. This bias may be large or small compared to the sampling error, for realistic record lengths, depending on the distribution of the quantity analyzed. The results of this analysis indicate that previous analyses could potentially have overestimated the likelihood of extreme events arising from natural weather variability. Plain Language Summary: We report a previously unknown bias in a common method for estimating how often extremely rare events such as extreme wind bursts or rain events will occur, when return periods are longer than the available data record. The method analyzed is one where an investigator combines data from nearby locations to reduce sampling error. We find by looking at new, high‐resolution data that variations in behavior across sites can sometimes produce biases much larger than the sampling error. The implication is that some observed extreme events are even less likely to have occurred than previously thought, assuming the underlying distribution hasn't changed over the period of observation. Key Points: Grouping data of nearby locations into one larger sample or "superstation" can induce biases at long recurrence intervalsThe superstation fit tends to the highest levels suggested by any of the pooled locationsThe bias may be large or small compared to random uncertainty, depending on the distribution of the extreme event analyzed [ABSTRACT FROM AUTHOR]

Phenomena such as cyclones, fronts and thunderstorms can cause extreme weather in various regions throughout the world. Although these phenomena have been examined in numerous studies, they have not all been systematically examined in combination with each other, including in relation to extreme precipitation and extreme winds throughout the world. Consequently, the combined influence of these phenomena represents a substantial gap in the current understanding of the causes of extreme weather events. Here we present a systematic analysis of cyclones, fronts and thunderstorms in combination with each other, as represented by seven different types of storm combinations. Our results highlight the storm combinations that most frequently cause extreme weather in various regions of the world. The highest risk of extreme precipitation and extreme wind speeds is found to be associated with a triple storm type characterized by concurrent cyclone, front and thunderstorm occurrences. Our findings reveal new insight on the relationships between cyclones, fronts and thunderstorms and clearly demonstrate the importance of concurrent phenomena in causing extreme weather. [ABSTRACT FROM AUTHOR]

The subtropical part of the eastern Australian seaboard experiences intense cyclonic activity. The severe damage caused by the intense storms in the region, known as east coast lows (ECLs), has motivated a number of recent studies. Cyclones in this region appear to be driven by a combination of different (barotropic and baroclinic) formation mechanisms, consistent with the view emerging in the last decades that cyclones span a continuous spectrum of dynamical structures, with the barotropically driven tropical cyclone and the baroclinically driven extratropical cyclone being only the extremes of such a spectrum. In this work we revisit the climatology of cyclone occurrence in the subtropical east coast of Australia as seen in a global reanalysis, systematically applying classification criteria based on the cyclone vertical structure and thermal core. Moreover, we investigate the underlying processes driving the cyclone rapid intensification by means of an atmospheric limited-area energetics analysis. We show that ECLs have different spatial patterns according to the cyclone thermal structure, with the fraction of hybrid cyclones being larger toward the tropics and closer to the coast. Moreover, we find that explosively deepening cyclones in this region are driven by a different combination of processes with respect to the global case, with barotropic processes in the surrounding environment having a more dominant role in the energetics of cyclone rapid intensification. The findings of this work contribute to understanding the physical processes underlying the formation and intensification of Australian east coast lows and the associated coastal damage and risk. [ABSTRACT FROM AUTHOR]

Abstract An exploratory analysis of lightning-ignited wildfire data for the Warren Region of Western Australia was carried out for the period from April 1976 to December 2016. Temporal patterns in the series were examined in terms of characterizing the seasonal cycle, and detecting long-term trends and changes in seasonality over time. A generalized additive modelling approach was used to ensure that temporal features were determined by the data rather than a priori assumed mathematical forms (e.g. linear or low-order polynomial functions). The spatial organization of the data was evaluated using concepts from the theory of stochastic point processes. Results indicate a strong seasonality in the monthly lightning ignition series, the presence of a long-term trend and an interaction between trend and seasonality. There is also strong evidence of spatial variation in the number of ignitions per unit area in terms of location and distance from nearest ignition. Within the Warren Region, observation platforms for fire detection and reporting protocols have remained stable over the period of record, and changes in land use are unlikely to have altered the pattern of lightning ignition. Thus, the above results might reflect an interplay between: landscape attributes (e.g. vegetation classes, elevation, slope, aspect); changes in rainfall and fuel moisture; changes in fuel management practices; and, perhaps, an increase in the frequency of dry thunderstorms and fire weather conditions. Highlights • Lightning-ignited wildfires exhibit a changing seasonal cycle and long-term trend. • Sizeable proportion of lightning ignitions originated from strikes on or near trees. • Point pattern of ignitions does not exhibit complete spatial randomness. • Point pattern is consistent with an inhomogeneous Poisson process. [ABSTRACT FROM AUTHOR]

The Australian Bureau of Meteorology has developed a national hydrological projections (NHP) service for Australia. With the focus on hydrological change assessment, the NHP service aims at being complementary to climate projections work carried out by many federal and state governments, universities, and other organisations across Australia. The projections comprise an ensemble of application-ready bias-corrected climate model data and derived hydrological projections at daily temporal and 0.05° × 0.05° spatial resolution for the period 1960-2099 and two emission scenarios (RCP 4.5 and RCP 8.5). The spatial resolution of the projections matches that of gridded historical reference data used to perform the bias correction and the Bureau's operational gridded hydrological model. Three bias correction techniques were applied to four CMIP5 global climate models (GCMs) and one to output from a regional climate model forced by the same four GCMs, resulting in a 16-member ensemble of bias-corrected GCM data for each emission scenario. The bias correction was applied to fields of precipitation, minimum and maximum temperature, downwelling shortwave radiation and surface winds. These variables are required inputs to the Bureau's landscape water balance hydrological model (AWRA-L) which was forced using the bias-corrected GCM and RCM data to produce a 16-member ensemble of hydrological output. The hydrological output variables include root-zone soil moisture (moisture in the top 1 m soil layer), potential evapotranspiration and runoff. Here we present an overview of the production of the hydrological projections, including GCM selection, bias correction methods and their evaluation, technical aspects of their implementation and examples of analysis performed to construct the NHP service. The data are publicly available on the National Computing Infrastructure (https://dx.doi.org/10.25914/6130680dc5a51) and a user interface is accessible at https://awo.bom.gov.au/products/projection/. [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]

This study offers an overview of the low-frequency (i.e., monthly to seasonal) evolution, dynamics, predictability, and surface impacts of a rare Southern Hemisphere (SH) stratospheric warming that occurred in austral spring 2019. Between late August and mid-September 2019, the stratospheric circumpolar westerly jet weakened rapidly, and Antarctic stratospheric temperatures rose dramatically. The deceleration of the vortex at 10 hPa was as drastic as that of the first-ever-observed major sudden stratospheric warming in the SH during 2002, while the mean Antarctic warming over the course of spring 2019 broke the previous record of 2002 by ∼50% in the midstratosphere. This event was preceded by a poleward shift of the SH polar night jet in the uppermost stratosphere in early winter, which was then followed by record-strong planetary wave-1 activity propagating upward from the troposphere in August that acted to dramatically weaken the polar vortex throughout the depth of the stratosphere. The weakened vortex winds and elevated temperatures moved downward to the surface from mid-October to December, promoting a record strong swing of the southern annular mode (SAM) to its negative phase. This record-negative SAM appeared to be a primary driver of the extreme hot and dry conditions over subtropical eastern Australia that accompanied the severe wildfires that occurred in late spring 2019. State-of-the-art dynamical seasonal forecast systems skillfully predicted the significant vortex weakening of spring 2019 and subsequent development of negative SAM from as early as late July. [ABSTRACT FROM AUTHOR]

The world's most severe thunderstorm asthma event occurred in Melbourne, Australia on 21 November 2016, coinciding with the peak of the grass pollen season. The aetiological role of thunderstorms in these events is thought to cause pollen to rupture in high humidity conditions, releasing large numbers of sub-pollen particles (SPPs) with sizes very easily inhaled deep into the lungs. The humidity hypothesis was implemented into a three-dimensional atmospheric model and driven by inputs from three meteorological models. However, the mechanism could not explain how the Melbourne event occurred as relative humidity was very low throughout the atmosphere, and most available grass pollen remained within 40 m of the surface. Our tests showed humidity induced rupturing occurred frequently at other times and would likely lead to recurrent false alarms if used in a predictive capacity. We used the model to investigate a range of other possible pollen rupturing mechanisms which could have produced high concentrations of SPPs in the atmosphere during the storm. The mechanisms studied involve mechanical friction from wind gusts, electrical build up and discharge incurred during conditions of low relative humidity, and lightning strikes. Our results suggest that these mechanisms likely operated in tandem with one another, but the lightning method was the only mechanism to generate a pattern in SPPs following the path of the storm. If humidity induced rupturing cannot explain the 2016 Melbourne event, then new targeted laboratory studies of alternative pollen rupture mechanisms would be of considerable value to help constrain the parameterisation of the pollen rupturing process. [ABSTRACT FROM AUTHOR]

In the original publication of the article, a minor error in analysis [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]

A recently validated algorithm for detecting and tracking tropical cyclones (TCs) in coarse resolution climate models was applied to a selected group of 12 models from the Coupled Model Intercomparison Project (CMIP5) to assess potential changes in TC track characteristics in the Southern Hemisphere (SH) due to greenhouse warming. Current-climate simulations over the period 1970–2000 are first evaluated against observations using measures of TC genesis location and frequency, as well as track trajectory and lifetime in seven objectively defined genesis regions. The 12-model (12-M) ensemble showed substantial skill in reproducing a realistic TC climatology over the evaluation period. To address potential biases associated with model interdependency, analyses were repeated with an ensemble of five independent models (5-M). Results from both the 12-M and 5-M ensembles were very similar, instilling confidence in the models for climate projections if the current TC-climate relationship is to remain stationary. Projected changes in TC track density between the current- and future-climate (2070–2100) simulations under the Representatives Concentration 8.5 Pathways (RCP8.5) are also assessed. Overall, projection results showed a substantial decrease (~ 1–3 per decade) in track density over most parts of the SH by the end of the twenty-first century. This decrease is attributed to a significant reduction in TC numbers (~ 15–42%) consistent with changes in large-scale environmental parameters such as relative vorticity, environmental vertical wind shear and relative humidity. This study may assist with adaption pathways and implications for regional-scale climate change for vulnerable regions in the SH. [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.

• Downscaling and bias correction (DSBC) are commonly used in climate impact studies. • We developed an impact-centric evaluation framework to assess DSBC methods. • We use this framework to assess DSBC for hydrological projections in Australia. • Multi-variate and multi-time scale bias correction performed best in this context. • We outline the application of the evaluation framework to other impact domains. Climate change impact studies commonly use impact models (such as hydrological or crop models) forced with corrected climate input data from global climate models. A range of downscaling and bias correction methods have been developed to increase the spatial resolution and remove systematic biases in climate model outputs to be applied before use in impact models. Many studies have focused on evaluating such approaches for the climate variables they aim to correct. However, due to nonlinear error propagation there can be large remaining biases in model outputs, even when ingesting bias corrected climate forcings. Here we propose an impact-centric evaluation framework for downscaling and bias correction methods to be used in climate change risk assessments. This framework evaluates and compares the strengths and limitations of downscaling and bias correction in the impact domain, highlighting approaches that lead to reduced biases in impact variables of interest. We demonstrate the evaluation framework in the context of assessing downscaling and bias correction methods for hydrological projections in Australia. Our results show that although all downscaling and bias correction methods evaluated perform adequately for the input climate variables, their errors vary markedly when the impact is modelled. Our proposed evaluation framework involves selecting a number of key performance metrics, and ranking the four downscaling and bias correction methods to compute an overall ranking, highlighting the best-performing methods for each statistical metric and the overall best-performing approach. We present an application of this approach using performance metrics relevant to hydrological applications, relating to mean biases, variability, heavy precipitation and peak runoff days, and dry conditions. For impact studies related to hydrological applications, we find that multi-variate bias correction that considers cross-correlations, temporal auto-correlations and biases at multiple time scales (daily to annual) performs best in reducing biases in hydrological output variables for Australia. Our proposed evaluation approach can be applied to a wide range of climate change applications where downscaling and bias correction are required, including impacts on agricultural production, wildfires, energy generation, human health, ecosystem functioning, and water resource management. [ABSTRACT FROM AUTHOR]

The process of pyroconvection occurs when fire-released heat, moisture, and/or aerosols induce or augment convection in the atmosphere. Prediction of pyroconvection presents a set of complex problems for meteorologists and wildfire managers. In particular, the turbulent characteristics of a pyroconvective plume exert bidirectional feedback on fire behavior, often with resulting severe impacts on life and property. Here, we present the motivation, field strategy, and initial results from the Bushfire Convective Plume Experiment, which through the use of mobile radar aims to quantify the kinematics of pyroconvection and its role in fire behavior. The case studies presented include world-first observations from two wildfires and one prescribed burn using the University of Queensland’s portable, dual-polarized X-band Doppler radar (UQ-XPOL). The initial analyses of reflectivity, Doppler winds, polarimetric variables, and spectrum width data provide insights into these relatively unexplored datasets within the context of pyroconvection. Weather radar data are supported by mesonet observations, time-lapse photography, airborne multispectral imaging, and spot-fire mapping. The ability to combine ground-validated fire intensity and progression at an hourly scale with quantitative data documenting the evolution of the convective plume kinematics at the scale of hundreds of meters represents a new capability for advancing our understanding of wildfires. The results demonstrate the suitability of portable, dual-polarized X-band Doppler radar to investigate pyroconvection and associated plume dynamics. [ABSTRACT FROM AUTHOR]