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Assessing the role of anthropogenic warming from temporally inhomogeneous historical data in the presence of large natural variability is difficult and has caused conflicting conclusions on detection and attribution of tropical cyclone (TC) trends. Here, using a reconstructed long-term proxy of annual TC numbers together with high-resolution climate model experiments, we show robust declining trends in the annual number of TCs at global and regional scales during the twentieth century. The Twentieth Century Reanalysis (20CR) dataset is used for reconstruction because, compared with other reanalyses, it assimilates only sea-level pressure fields rather than utilize all available observations in the troposphere, making it less sensitive to temporal inhomogeneities in the observations. It can also capture TC signatures from the pre-satellite era reasonably well. The declining trends found are consistent with the twentieth century weakening of the Hadley and Walker circulations, which make conditions for TC formation less favourable.

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]

There is growing need to understand wind variability in various regions through the world, including in relation to wind energy resources. Here we examine wind variability in southeast Australia in relation to the El Niño-Southern Oscillation (ENSO) as a dominant mode of atmospheric and oceanic variability for this region. The analysis covers variability from seasonal to diurnal time scales for both land and maritime regions of relevance to wind energy generation. Wind speeds were obtained from the 12 km grid-length BARRA reanalysis produced for the Australian region, with focus on wind at a typical hub-height of 100 m above the surface. Results show spatiotemporal variations in how ENSO influences wind speeds, including consistency in these variations over the wind speed distribution. For example, ENSO-related variations in mean winds were mostly similar in sign to ENSO-related variations in weak winds, noting uncertainties for strong winds given available data. Diurnal variability in wind speed was larger for summer than winter and for land than ocean regions, with the diurnal cycle maxima typically occurring in the afternoon and evening rather than morning, plausibly associated with sensible heating of air above land following solar radiation. Localised variations in the diurnal cycle were identified around mountains and coastal regions. The results show some indication of ENSO influences on the diurnal variability. These findings are intended to help enhance scientific understanding on wind variability including in relation to ENSO, as well as contribute information towards practical guidance in planning such as for use in energy sector applications. [ABSTRACT FROM AUTHOR]

There is growing need to understand wind variability in various regions through the world, including in relation to wind energy resources. Here we examine wind variability in southeast Australia in relation to the El Nino-Southern Oscillation ENSO) as a dominant mode of atmospheric and oceanic variability for this region. The analysis covers variability from seasonal to diurnal time scales for both land and maritime regions of relevance to wind energy generation. Wind speeds were obtained from the 12 km grid-length BARRA reanalysis produced for the Australian region, with focus on wind at a typical hub-height of 100 m above the surface. Results show spatiotemporal variations in how ENSO influences wind speeds, including consistency in these variations over the wind speed distribution. For example, ENSO-related variations in mean winds were mostly similar in sign to ENSO-related variations in weak winds, noting uncertainties for strong winds given available data. Diurnal variability in wind speed was larger for summer than winter and for land than ocean regions, with the diurnal cycle maxima typically occurring in the afternoon and evening rather than morning, plausibly associated with sensible heating of air above land following solar radiation. Localised variations in the diurnal cycle were identified around mountains and coastal regions. The results show some indication of ENSO influences on the diurnal variability. These findings are intended to help enhance scientific understanding on wind variability including in relation to ENSO, as well as contribute information towards practical guidance in planning such as for use in energy sector applications. [ABSTRACT FROM AUTHOR]

In response to flood risk, design flood estimation is a cornerstone of planning, infrastructure design, setting of insurance premiums, and emergency response planning. Under stationary assumptions, flood guidance and the methods used in design flood estimation are firmly established in practice and mature in their theoretical foundations, but under climate change, guidance is still in its infancy. Human-caused climate change is influencing factors that contribute to flood risk such as rainfall extremes and soil moisture, and there is a need for updated flood guidance. However, a barrier to updating flood guidance is the translation of the science into practical application. For example, most science pertaining to historical changes to flood risk focuses on examining trends in annual maximum flood events or the application of non-stationary flood frequency analysis. Although this science is valuable, in practice, design flood estimation focuses on exceedance probabilities much rarer than annual maximum events, such as the 1 % annual exceedance probability event or even rarer, using rainfall-based procedures, at locations where there are few to no observations of streamflow. Here, we perform a systematic review to summarize the state-of-the-art understanding of the impact of climate change on design flood estimation in the Australian context, while also drawing on international literature. In addition, a meta-analysis, whereby results from multiple studies are combined, is conducted for extreme rainfall to provide quantitative estimates of possible future changes. This information is described in the context of contemporary design flood estimation practice to facilitate the inclusion of climate science into design flood estimation practice. [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]

In response to flood risk, design flood estimation is a cornerstone of planning, infrastructure design, setting of insurance premiums and emergency response planning. Under stationary assumptions, flood guidance and the methods used in design flood estimation are firmly established in practice and mature in their theoretical foundations, but under climate change, guidance is still in its infancy. Human-caused climate change is influencing factors that contribute to flood risk such as rainfall extremes and soil moisture, and that there is a need for updated flood guidance. However, a barrier to updating flood guidance is the translation of the science into practical application. For example, most science focuses on examining trends in annual maximum flood events, or the application of non-stationary flood frequency analysis. Although this science is valuable, in practice design flood estimation focuses on exceedance probabilities much rarer than annual maximum events, such as the 1% annual exceedance probability event or even rarer, using rainfall-based procedures, at locations where there are little to no observations of streamflow. Here, we perform a systematic review to summarise the state-of-the-art understanding of the impact of climate change on design flood estimation in the Australian context, while also drawing on international literature. In addition, a meta-analysis, whereby results from multiple studies are combined, is conducted for extreme rainfall to provide quantitative estimates of possible future changes. This information is described in the context of contemporary design flood estimation practice, to facilitate the inclusion of climate science into design flood estimation practice. [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]

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]