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Previous research has suggested that the frequency and intensity of surface hazards associated with thunderstorms and convection, such as severe convective winds (SCWs), could potentially change in a future climate due to global warming. However, because of the small spatial scales associated with SCWs, they are unresolved in global climate models, and future climate projections are uncertain. Here, we evaluate the representation of SCW events in a convection-permitting climate model (Bureau of Meteorology Regional Projections for Australia, BARPAC-M), run over southeastern Australia for December–February months. We also assess changes in SCW event frequency in a projected future climate for the year 2050, and compare this with an approach based on identifying large-scale environments favourable for SCWs from a regional parent model (BARPA-R). This is done for three different types of SCW events that have been identified in this region, based on clustering of the large-scale environment. Results show that BARPAC-M representation of the extreme daily maximum wind gust distribution is improved relative to the gust distribution simulated by the regional parent model. This is due to the high spatial resolution of BARPAC-M output, as well as partly resolving strong and short-lived gusts associated with convection. However, BARPAC-M significant overestimates the frequency of simulated SCW events, particularly in environments having steep low-level temperature lapse rates. A future decrease in SCW frequency under steep lapse rate conditions is projected by BARPAC-M, along with less frequently favourable large-scale environments. In contrast, an increase in SCW frequency is projected under high surface moisture conditions, with more frequently favourable large-scale environments. Therefore, overall changes in SCWs for this region remain uncertain, due to different responses between event types, combined with historical model biases. [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]

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]

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]

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]

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]

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]

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.

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]

Extratropical cyclones are the main generators of the strong winds that cause large ocean waves in temperate regions of the world. The severity of the winds associated with these storms is poorly represented by the coarse resolution of current global climate models (GCMs), making it challenging to produce projections of the future climate of large waves. Wind data from GCMs can be downscaled in resolution using dynamical methods, resulting in a successful reproduction of the mean wave climate, but a suboptimal reproduction of the storm wave climate. Projections of large wave occurrence can also be produced using statistical downscaling methods, although such methods have previously been applied only to three or less GCMs, preventing a robust assessment of confidence in projections based on variation between models. Consequently, considerable uncertainty remains in projections of the future storm wave climate. Here we apply a statistical diagnostic of large wave occurrence in eastern Australia to 18 different GCMs, allowing model variations to be examined in greater detail than previously possible. Results are remarkably consistent between different GCMs, allowing anthropogenic influences to be clearly demonstrated, with fewer days with large waves expected to occur in eastern Australia due to increasing greenhouse gas concentrations. [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]

• 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]