The extensive electricity transmission network of Queensland is managed by Powerlink and has a significant exposure to both thunderstorms and tropical cyclones. In coastal North Queensland tropical cyclones (TC) dominate the severe wind hazard environment whereas in South East Queensland both storm types contribute significantly. Some parts of Powerlink’s network have high concentrations of older tower assets such as in the Gladstone region which supply electricity for the smelting and refining of aluminium. Other parts provide vital transmission links with limited redundancy between regions of generation in the south to large communities to the north, such as in far-North Queensland. These assets have been developed over many years, to design standards that have progressively changed, and some have been exposed to corrosive environments that are characteristic of the warm and humid coastal tropics. As a consequence of these factors, some assets within the system are particularly vulnerable to severe wind.

Australian Community Climate and Earth-System (ACCESS) Numerical Weather Prediction (NWP) data is made available by the Bureau of Meteorology for registered subscribers such as GA. ACCESS-C3 (City) model is a forecast-only model performed every 6 hours and consists of grid coordinates covering domains around Sydney, Victoria and Tasmania, Brisbane, Perth, Adelaide and Darwin. ACCESS Impact Modelling (ACCESS-IM) System utilise information from ACCESS-NWP on the forecast wind gust speeds ground surface (single-level) at 10 metres, simulated by the ACCESS-C3 model, for the time period of 0-12, 12-24, 24-36, 0-36.

Windstorms cause most of the damage to housing in Australia. Population growth is exposing more people and buildings to risks from these wind hazards. Houses and components are currently designed and built to standards aligned with the Building Code of Australia. Regulatory measures including building inspections are meant to ensure acceptable quality of construction. Inspections and post windstorm damage surveys have consistently shown that contemporary houses (post 1980) perform better than older houses (pre 1980) in cyclone and non cyclone areas. However, errors in design and construction found during recent surveys, reduce the resilience of contemporary housing. Geoscience Australia is developing a software tool for assessing the vulnerability of housing, using empirical models, expert opinion, and engineering methods. These models could be used to assess vulnerability of a range of house types and also recommend adaptation measure to account for increases in the intensity of windstorms in Australia.

Australian Community Climate and Earth-System (ACCESS) Numerical Weather Prediction (NWP) data is made available by the Bureau of Meteorology for registered subscribers such as GA. ACCESS-C3 (City) model is a forecast-only model performed every 6 hours and consists of grid coordinates covering domains around Sydney, Victoria and Tasmania, Brisbane, Perth, Adelaide and Darwin. ACCESS Impact Modelling (ACCESS-IM) System utilise information from ACCESS-NWP on the forecast wind gust speeds ground surface (single-level) at 10 metres, simulated by the ACCESS-C3 model, for the time period of 0-12, 12-24, 24-36, 0-36.

Modelling of the risk posed by the impacts of extreme weather events requires knowledge of the vulnerability, or performance, of building assets. Furthermore, to assess the benefits of mitigation an ability to quantitatively model the change in vulnerability associated with mitigation actions is required. In Australia past efforts at establishing vulnerability relationships between building damage and severe wind have centred on empirical techniques, using data from damage surveys or insurance losses, and heuristic techniques. Neither of these methods permits the change in vulnerability afforded by mitigation work to be quantitatively modelled. The Bushfire and Natural Hazards CRC project “Improving the Resilience of Existing Housing to Severe Wind Events” is developing a software tool, Vulnerability and Adaption to Wind Simulation (VAWS), to provide a quantitative vulnerability model for Australian house types. It is based on the premise that overall building damage is strongly related to the failure of key connections. The software uses a Monte Carlo approach whereby numerous realisations of a single generic house type are subjected to an increasing gust wind speed and the loss at each wind speed is calculated. Each realisation of the house varies from others as many key building parameters, such as connection strength, are sampled from probability distributions. For each instance, at each wind speed, the number and type of failed connections are related to damage states and extents of damage which permits the repair cost to be calculated. The repair cost is adjusted for the repair of debris impact damage and water ingress damage. The modelling of mitigation is easily accomplished by rerunning a house modelled with the probability distribution of an upgraded connection’s strength substituted. The software tool provides quantitative measures of reduced vulnerability that can be used in assessing the incremental effectiveness of a range of mitigation strategies in economic terms. Abstract submitted to/presented at AMOS-ICSHMO 2018 (https://www.ametsoc.org/index.cfm/ams/meetings-events/ams-meetings/amos-icshmo-2018/)

This dynamic dataset is composed of data layers representing the potential damage arising from the impacts of Tropical Cyclone (TC) related winds on residential houses. The impacts are determined using information on the forecast track of the TC issued by the Bureau of Meteorology, nationally consistent exposure (residential building) and vulnerability (likely level of damage) information maintained by Geoscience Australia. The tracks are based on the content of Technical Bulletins issued by the Bureau of Meteorology’s Tropical Cyclone Warning Centres every 6 hours for active TCs in the Australian region. As such, information is generated intermittently, depending on the occurrence of TCs. The tracks are a forecast only, so do not include past position information of the TC. Forecasts may extend up to 120 hours (5 days) ahead of the forecast time. A wind field around each track is simulated using Geoscience Australia’s Tropical Cyclone Risk Model (TCRM, https://pid.geoscience.gov.au/dataset/ga/77484). This provides an estimate of the maximum gust wind speed over open, flat terrain (e.g. airports). Local effects such as topography and land cover changes are incorporated via site wind multipliers (https://pid.geoscience.gov.au/dataset/ga/75299), resulting in a 0.2-second, 10-m above ground level wind speed, with a spatial resolution of approximately 30 metres. The impacts are calculated using Geoscience Australia’s HazImp code (https://pid.geoscience.gov.au/dataset/ga/110501), which utilises the National Exposure Information System building data and a suite of wind vulnerability curves to determine the level of damage sustained by individual buildings (a damage index). The damage index values are aggregated to Australian Bureau of Statistics Statistical Area Level 1 regions, and can be assigned a qualitative damage description based on the mean damage index.

<div>Knowledge of the nature of buildings within CBD areas is fundamental to a broad range of decision-making processes, including planning, emergency management and the mitigation of the impact of natural hazards. To support these activities, Geoscience Australia has developed a building information system called the National Exposure Information System (NEXIS) which provides information on buildings across Australia. Most of the building level information in NEXIS is statistically derived, but efforts are being made to include more detailed information on the nature of individual buildings, particularly in CBD areas. This is being achieved in Parramatta through field survey work.</div>

<div>The Severe Wind Hazard Assessment for South East Queensland (SWHA-SEQ) analysed risk from severe wind events in a marginal tropical cyclone (TC) region with a large exposed population, and historical severe thunderstorm and TC impacts. SWHA-SEQ was a collaborative effort bringing together 15 partners across government, academia and the insurance sector to improve the collective understanding of wind risk in the region and inform future strategies to reduce this risk, in the context of climate change, urban planning and socio-economic status of the population. </div><div>The project involved enhancing the understanding of hazard, exposure and physical vulnerability to strengthen the comprehension of risk, including local-scale wind hazard from thunderstorm and TC wind gusts, and a semi-quantitative analysis of future wind hazard. Structural characteristics of residential housing stock were updated through a combination of street surveys, national databases of built assets and insurance portfolio statistics. Vulnerability models for residential houses including retrofitted models for 5 common house types were developed, alongside identification of key vulnerability factors for residential strata buildings.</div><div>Local governments are building on the outcomes of the project, with the City of Gold Coast using the project outcomes as the key evidence base for a A$100m investment over 7 years to advocate for uplift of building design criteria, targeted community engagement and resilience of City-owned infrastructure. Other local governments have conducted specific exercises exploring how they would manage a severe TC impact. The investments and activities directly flowing from SWHA-SEQ are testament to the partner engagement through the project. Presented at the 2024 Symposium on Hurricane Risk in a Changing Climate (SHRCC2024)

Natural disasters provide an invaluable opportunity to capture data for improving our understanding of risk. Observed damage types and their predominance provide useful insights into the factors contributing to building vulnerability and consequential community risk. They also facilitate the appraisal of mitigation measures directed at reducing that risk where it is found to be high. Survey activities that followed the impact of Tropical Cyclone Larry have highlighted the benefits of a co-ordinated survey response to natural hazard impacts. The response to this event involved liaison with local emergency management and the broad participation of recognised wind engineering experts. Survey techniques were refined to achieve a more efficient and comprehensive approach that ensured consistency, utility and transferability of the data for all collaborators. The refined approach proved very successful and may provide a useful model for similar post-disaster exercises directed at earthquake damage. The sudden nature by which earthquakes inflict damage without warning points to having arrangements already established beforehand for the best survey outcomes. Proposals for advancing such preplanning are presented.

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.