The National Hazard Impact Risk Service for Tropical Cyclone Event Impact provides information on the potential impact to residential separate houses due to severe winds. The information is derived from Bureau of Meteorology tropical cyclone forecast tracks, in combination with building location and attributes from the National Exposure Information System and vulnerability models to define the level of impact. Impact data is aggregated to Statistical Area Level 1, categorised into five qualitative levels of impact.

We present the formulation of an open-source, statistical–parametric model of tropical cyclones (TCs) for use in hazard and risk assessment applications. The model derives statistical relations for TC behaviour (genesis rate and location, intensity, speed and direction of translation) from best-track datasets, then uses these relations to create a synthetic catalogue based on stochastic sampling, representing many thousands of years of activity. A parametric wind field, based on radial profiles and boundary layer models, is applied to each event in the catalogue that is then used to fit extreme-value distributions for evaluation of return period wind speeds. We demonstrate the capability of the model to replicate observed behaviour of TCs, including coastal landfall rates which are of significant importance for risk assessments. <b>Citation: </b>Arthur, W. C.: A statistical–parametric model of tropical cyclones for hazard assessment, Nat. Hazards Earth Syst. Sci., 21, 893–916, https://doi.org/10.5194/nhess-21-893-2021, 2021.

This resource contains surface sediment data for Bynoe Harbour collected by Geoscience Australia (GA), the Australian Institute of Marine Science (AIMS) and Department of Land Resource Management (Northern Territory Government) during the period from 2-29 May 2016 on the RV Solander (survey SOL6432/GA4452). This project was made possible through offset funds provided by INPEX-led Ichthys LNG Project to Northern Territory Government Department of Land Resource Management, and co-investment from Geoscience Australia and Australian Institute of Marine Science. The intent of this four year (2014-2018) program is to improve knowledge of the marine environments in the Darwin and Bynoe Harbour regions by collating and collecting baseline data that enable the creation of thematic habitat maps that underpin marine resource management decisions. The specific objectives of the survey were to: 1. Obtain high resolution geophysical (bathymetry) data for outer Darwin Harbour, including Shoal Bay; 2. Characterise substrates (acoustic backscatter properties, grainsize, sediment chemistry) for outer Darwin Harbour, including Shoal Bay; and 3. Collect tidal data for the survey area. Data acquired during the survey included: multibeam sonar bathymetry and acoustic backscatter; physical samples of seabed sediments, underwater photography and video of grab sample locations and oceanographic information including tidal data and sound velocity profiles. This dataset comprises O2 consumption and CO2 production rates measured from core incubation experiments conducted on seabed sediments. A detailed account of the survey is provided in Siwabessy, P.J.W., Smit, N., Atkinson, I., Dando, N., Harries, S., Howard, F.J.F., Li, J., Nicholas W.A., Picard, K., Radke, L.C., Tran, M., Williams, D. and Whiteway, T., 2016. Bynoe Harbour Marine Survey 2017: GA4452/SOL6432 – Post-survey report. Record 2017/04. Geoscience Australia, Canberra. Thanks to the crew of the RV Solander for help with sample collection, Matt Carey, Craig Wintle and Andrew Hislop from the Observatories and Science Support at Geoscience Australia for technical support and Jodie Smith for reviewing the data. This dataset is published with the permission of the CEO, Geoscience Australia

This dataset contains a collection of ESRI geodatabases that hold hazard and impact data derived as part of the Severe Wind Hazard Assessment for Western Australia (2017-2020) project. There are separate geodatabases for each community examined in the project. Within each community, multiple TC scenarios were analysed for each community. The list of scenarios is included below. Geodatabase structure --------------------- Within each geodatabase, the data is structured as set out below. The structure is repeated for each available scenario in that community. Note scenario id numbers have the hyphen ('-') removed in the <scenario id> string below. - Shapefiles |-- TCs within 50 km |-- Cat<X> <scenario id>_Impact [Polygon shape file of SA1-level mean damage state for residential housing] |-- Cat<X> <scenario id>_regionalwind [Polygon shape file of categorised regional wind speed] |-- Cat<X> <scenario id>_track_line [Line shape file of scenario track line segments] |-- Cat<X> <scenario id>_track_point [Point shape file of scenario track points] - Cat<X>_<scenario id>_localwind [Raster format local wind data] Scenarios --------- Scenairo Id number, TC intensity, Location 000-01322,3,Exmouth 013-00928,3,Exmouth 000-06481,5,Exmouth 003-03693,3,PortHedland 000-08534,5,PortHedland 012-06287,3,Broome 012-03435,5,Broome 006-00850,3,Karratha-Roebourne 009-07603,5,Karratha-Roebourne 011-01345,1,Carnarvon 003-05947,3,Carnarvon 011-02754,1,Geraldton 001-08611,3,Geraldton 007-05186,1,Perth bsh291978,1,Perth

<div>Ask a Queenslander where tropical cyclones (TCs) occur, and the inevitable response will be North Queensland. Whilst most of the tropical cyclones have made landfall north of Bundaberg, the cascading and concurrent effects are felt much further afield. The major flooding following TC Yasi in 2011 and TC Debbie in 2017, are just two examples where impacts were felt across the State, and of course, the wind impacts to the banana plantation following TC Larry (2006) was felt nationally.&nbsp;</div><div> &nbsp;</div><div>South East Queensland has not been forgotten when it comes to tropical cyclone impact with an event crossing Coolangatta in 1954. There was also the more recent TC Gabrielle which tracked offshore on its path southwards to New Zealand.&nbsp;&nbsp;</div><div>&nbsp;</div><div>Acknowledging that climate is influencing the intensity and frequency of more intense severe weather hazards, understanding how tropical cyclone hazard varies under future climate conditions is critical to risk-based planning in Queensland. With this climate influence, along with increasing population and more vulnerable building design in South East Queensland (relative to northern Queensland), there is an urgent need to assess the wind risk and set in place plans to reduce the impacts of a potential tropical cyclone impact in South East Queensland. <b>Citation:</b> Sexton, J., Tait, M., Turner, H., Arthur, C., Henderson, D., Edwards, M; Preparing for the expected: tropical cyclones in South East Queensland.<i> AJEM</i> 38:4, October 2023, pages 33-39.

The first step in understanding risk is understanding the hazard. This means knowing the likelihood of the hazard event and its intensity. During 2018, Geoscience Australia updated the Tropical Cyclone Hazard Assessment (TCHA) to better calculate the likelihood of tropical cyclones in Australia.

<div>Severe wind from tropical cyclones (TC) can cause significant damage to property and infrastructure, and accurately predicting these impacts is essential for ensuring community safety. At Geoscience Australia (GA), the Tropical Cyclone Risk Model (TCRM) is a statistical-parametric tool designed to estimate the severe wind hazards posed by TCs.</div><div><br></div><div>To assess the performance of TCRM, all TCs impacting Australia from 1998 to 2023 were simulated using various wind profile settings. Since TCRM currently lacks adjustments for local landscape effects on wind speed (e.g., topographic enhancements or variations due to vegetation or built environments), GA’s wind multiplier was applied to convert TCRM’s regional wind to local wind for each TC. Additionally, a new multiplier, derived from the Parallelized Large-Eddy Simulation Model (PALM), was used to calculate local wind. The local winds from these two multipliers were then compared and validated against 1-minute Automatic Weather Station (AWS) observations from the Bureau of Meteorology (BoM). </div><div><br></div><div>The results indicate that the Willoughby wind profile outperforms other wind profiles, with a mean sea level pressure error of just 0.2 hPa compared to AWS observations over the mainland. Although the local wind from both multipliers aligns closely across 82 AWS stations (a mean peak wind gust error of -1 m/s for the GA multiplier and 0.2 m/s for the new multiplier), significant discrepancies may occur in regions with steep mountain ranges, urban areas with high-rise buildings, and other areas with complex topography.</div><div><br></div>

<div>The wind hazard climate in South East Queensland is a combination of tropical cyclones, thunderstorms and synoptic storms. This dataset provides estimated average recurrence interval (ARI) or annual exceedance probability (AEP) wind speeds over the region, based on an evaluation of observational (thunderstorms and synoptic winds) and simulated data (tropical cyclones). </div><div><br></div><div>The tropical cyclone wind hazard was evaluated using Geoscience Australia's Tropical Cyclone Risk Model (TCRM), which provides a spatial representation of the AEP wind speeds arising from tropical cyclones. Thunderstorm wind hazard was evaluated from analysis of observed wind gusts across South East Queensland, aggregated into a single 'superstation' to provide a single representative hazard profile for the region.</div><div><br></div><div>The resulting combined wind hazard estimates reflect the dominant source of wind hazard in South East Queensland for the most frequent events (exceedance probabilities greater than 1:50) is thunderstorm-generated wind gusts. For rarer events, with exceedance probabilities less than 1:200, TC are the dominant source of extreme gusts.&nbsp;</div><div><br></div><div>Local effects of topography, land cover and the built environment were incorporated via site exposure multipliers (Arthur & Moghaddam, 2021), which are based on the site exposure multipliers defined in AS/NZS 1170.2 (2021).</div><div><br></div><div>The local wind hazard maps were used to evaluate the financial risk to residential separate houses in South East Queensland.</div><div><br></div><div>Wind speeds are provided for average recurrence intervals ranging from 1 year to 10,000 years. No confidence intervals are provided in the data. </div>

Tropical Cyclone (TC) Tracy impacted Darwin early on Christmas Day, 1974. The magnitude of damage was such that Tracy remains deeply ingrained in the Australian psyche. Several factors contributed to the widespread damage, including the intensity of the cyclone and construction materials employed in Darwin at the time. Since 1974, the population of Darwin has grown rapidly, from 46,000 in 1974 to nearly 115,000 in 2006. If TC Tracy were to strike Darwin in 2008, the impacts could be catastrophic. We perform a validation of Geoscience Australia's Tropical Cyclone Risk Model (TCRM) to assess the impacts TC Tracy would have on the 1974 landscape of Darwin, and compare the impacts to those determined from a post-impact survey. We then apply TCRM to the present-day landscape of Darwin to determine the damage incurred if a cyclone identical to TC Tracy impacted the city in 2008. In validating TCRM against the 1974 impact, we find an underestimate of the damage at 36% of replacement cost (RC), compared the survey estimate of 50-60% RC. Some of this deficit can be accounted for through the effects of large debris. Qualitatively, TCRM can spatially replicate the damage inflicted on Darwin by the small cyclone. The northern suburbs suffer the greatest damage, in line with the historical observations. For the 2008 scenario, TCRM indicates a nearly 90% reduction in the overall loss (% RC) over the Darwin region. Once again, the spatial nature of the damage is captured well, with the greatest damage incurred close to the eye of the cyclone. Areas that have been developed since 1974 such as Palmerston suffer very little damage due to the small extent of the severe winds. The northern suburbs, rebuilt in the years following TC Tracy, are much more resilient, largely due to the influence of very high building standards put in place between 1975 and 1980. Article published in the Australian Journal of Emergency Management

The Severe Wind Hazard Assessment project aims to provide DFES with intelligence on the scale of impacts that could arise from major tropical cyclone events in communities along the northwest and western coast of WA. We simulated category 3 and 5 scenarios in the northwest, and category 1 and 3 scenarios down the west coast. Simulations included translating the local-scale wind fields into the level of damage to residential housing, through the application of vulnerability models applied to residential buildings which had been categorised on the basis of attributes such as construction era, roof type, wall type and location. Some scenarios produce impacts that are comparable to past events (e.g. the category 5 scenario for Exmouth is similar to TC Vance). Other scenarios are catastrophic, such as the category 3 scenario for Geraldton, where nearly all residential buildings in the city are extensively or completely damaged. The different outcomes for communities arises because of the different profiles of residential buildings in each community. Geraldton lies outside the cyclonic regions defined in AS/NZS 1170.2, so houses are not explicitly designed cope with to the extreme winds that can arise in TCs, hence major impacts were found there in our analysis. DFES used these scenarios to guide planning and preparations for events, such as TC Veronica in March 2019, guiding decisions on preparations and recovery options, which are explored in a companion paper. Abstract presented at the 2020 Australian Meteorological and Oceanographic Society 2020 National Conference (http://amos-2020.w.amos.currinda.com/)