The 2018 Tropical Cyclone Hazard Assessment (TCHA18) provides an evaluation of the likelihood and intensity (“how big and how often”) of the occurrence of tropical cyclone winds across the Australian region, covering mainland Australia, islands and adjacent waters. It is a probabilistic evaluation of the expected maximum gust wind speeds with a range of annual exceedance probabilities (or conversely, average recurrence intervals). The assessment is derived using a statistical-parametric model developed by Geoscience Australia called the Tropical Cyclone Risk Model (TCRM). Maximum 0.2-second duration, 10-metre above ground wind speeds are calculated for Standard Australia's AS/NZS 1170.2 (2011) terrain category 2 (0.02 m roughness length) surface conditions, over a 0.02 degree grid across Australia. Maps of average recurrence interval (ARI) wind speeds of 100- and 500-year ARI are provided in a separate product suite.

The region of coastal South East Queensland (SEQ) represents a large concentration of population, business activity and infrastructure important to the economy of Queensland and Australia. The region is also subject to severe storms that can generate damaging winds, particularly as a result of thunderstorm and tropical cyclone activity. Older residential homes have historically been the most damaged in such storms, contributing disproportionately to community risk, and recent storm damage in Western Australia has indicated that there are issues with modern SEQ homes also. This risk posed by severe wind is not well understood, nor are the optimal strategies for managing and potentially reducing this risk. Previous work has provided insights into the potential impacts of rare storm events in the SEQ region and the vulnerability of residential homes that contribute to them. The Severe Wind Hazard Assessment for Queensland (SWHAQ) project (Arthur, et al., 2021) provided valuable insights on the potential impacts of rare tropical cyclones making landfall in the region. The SWHA-Q project included two storms impacting the Gold Coast that highlighted that credible cyclone events in South East Queensland generating no more than design level wind gusts can have challenging consequences. Five tropical cyclone scenario events were selected by the project partners and modelled to provide a demonstration of the residential housing damage outcomes that could result from plausible storms that could impact South East Queensland. Four storms generated category 3 winds (gusts over 165 km/h) on landfall and were essentially design level events for ordinary residential structures. The fifth (Scenario 3) generated category 4 winds (gusts over 225 km/h) at landfall but was still quite a credible storm for the region. The events highlighted, as did the previous SWHA-Q work, that rare cyclone events of this kind affect all parts of the study region and produce very significant consequences. One design level event (Scenario 2) was found to inflict moderate or greater damage to 39% of the homes in the region, representing a major need for temporary accommodation. One of the events was used as the evidence-based scenario that underpinned Exercise Averruncus – A SEQ Tropical Cyclone Impact held in Brisbane on 15 June 2022 that explored critical issues around preparation for, response to, and initial recovery from the event. It is noted that the scale of impacts from any scenario is contingent on the characteristics of the TC itself (size, intensity, landfall location) and on the landscape in which buildings are located. However, while each scenario is unique, the suite of scenario impacts provide a useful resource for EM planning by local government, emergency services and other agencies with a role in disaster recovery.

The Tropical Cyclone Scenario Selector Tool (TC SST) provides an interactive application to interrogate the stochastic event catalogue which underpins the 2018 Tropical Cyclone Hazard Assessment (TCHA18). The application allows users to search for TC events in the catalogue based on location and intensity (either TC intensity category, or maximum wind speed), visualise the tracks and the wind fields of those events, and download the data for further analysis.

The northwest Australian coastline from Broome to Exmouth has experienced the greatest number of landfalling Tropical Cyclones (TCs) in Australia since records began in 1908 (Bureau of Meteorology, 2020). Despite this, direct impacts of a TC on individual communities are comparatively unusual, especially for severe TCs (category 3-5) as the coastline is sparsely populated. Communities are generally hundreds of kilometres apart, and a TC can cross the coast between them with little impact. However, the highest recorded wind gust in the world was 408 km/h (category 5) at Barrow Island during TC Olivia on 10 April 1996 (Courtney et al., 2012). The highest wind gust on the Australian mainland was 267 km/h (category 4) at Learmonth during TC Vance on 22 March 1999 (Australian Bureau of Meteorology, 2000). This emphasises the fact that no regional centre in WA, with the exception of Exmouth, has experienced a high-end TC impact in the past 30 years, but there is the potential for extreme events to strike these communities. While the impacts of past cyclone events have been well-documented, it is unlikely that communities have experienced the ‘worst-possible’ (either most intense or most damaging) cyclone impact in the past 30 years. To understand the scale of impacts that would occur if a TC were to make a direct impact on any of these communities the West Australian Department of Fire and Emergency Services (DFES) applied for funding through the Natural Disaster Resilience Program. In July 2017 funding was obtained to conduct the Severe Wind Hazard Assessment (SWHA) project. This initiative is aligned with the National Disaster Risk Reduction Framework (Department of Home Affairs, 2018), which outlines a national, comprehensive approach to proactively reducing disaster risk in Australia. To better understand the potential impacts of cyclones and extra-tropical transitioning cyclones on Western Australian communities, the project has modelled a number of scenarios to demonstrate the impacts of realistic, but perhaps not experienced, cyclones for Broome, Port Hedland, South Hedland and Wedgefield, Karratha, Dampier, Roebourne, Wickham and Point Samson, Exmouth, Carnarvon, Geraldton and Perth A consistent message that comes from this analysis is the excellent performance of modern residential construction to withstand the impacts of these scenario TCs. However, a house built to code’s performance is reliant on being maintained during its life so that its resilience is retained; just because a building was built to standard doesn’t mean it has been maintained to that standard. Investigations conducted into previous cyclones demonstrate that houses built pre-1980s (pre-code) under perform and offer lesser protection compared to those houses built to code post-1980s. In line with that the work undertaken in this report shows clearly that communities with a larger proportion of pre-code residential construction will suffer greater damage, due to the greater vulnerability of older building stock. Houses not originally built to current standards cannot, in general, be expected to perform to the current design levels, irrespective of the maintenance level. The only way to increase performance of these older residential buildings is to retrofit to modern standards. The analysis undertaken in the project has provided emergency managers from local, district and State level with a wealth of information on the potential impacts a major cyclone would have on Western Australia. This information has provided opportunity to strengthen planning processes and raise community awareness of mitigation actions that can reduce impacts. This collection comprises reporting and data developed as part of the Severe Wind Hazard Assessment for Western Australia. The collection includes all reports, publications (e.g. conference presentations, posters and news articles, etc.), and data delivered to Department of Fire and Emergency Services (Western Australia).

The TCHA18 Stochastic Event Catalogue contains artificially generated tropical cyclone tracks and wind fields representing 10000 years of tropical cyclone activity. The catalogue stores the track of each event in annual collections (i.e. one simulated year per file). The wind field of each event is stored in a separate file, containing the maximum wind speed, the components (eastward and northward wind) corresponding to the maximum wind speed, and the minimum sea level pressure from the event. All events are recorded in a relational database file, which contains records of the distance of closest passage, maximum wind speeds and the direction of the maximum wind speed for over 400 locations in Australia. The database also contains records of the average recurrence interval wind speeds at those stations. The database is intended to simplify the process of identifying individual events in the catalogue for more detailed modelling to support scenario planning for emergency management, for example.

Geoscience Australia has produced a National Tropical Cyclone Hazard Assessment (TCHA18). The 1%/0.2% Annual Exceedance Probability Maps provides 0.2-second duration, 10-metre above ground level gust wind speeds across Australia arising from tropical cyclone events over a 2-km grid, for 1% and 0.2% annual exceedance probability (100- and 500-year annual recurrence interval respectively). Surface conditions are assumed to correspond to terrain category 2 conditions as defined in AS/NZS 1170.2 (2011).

Tropical cyclone scenario prepared for Tonga National Emergency Management Office (NEMO) as part of the PacSAFE Project (2016-2018)

Tropical cyclone scenario prepared for Tonga National Emergency Management Office (NEMO) as part of the PacSAFE Project (2016-2018)

Tropical Cyclone (TC) Debbie made landfall near Airlie Beach, Queensland on the 28th March 2017 as a category four system. After TC Debbie had dissipated, survey teams from James Cook University (JCU) and Geoscience Australia conducted post-disaster damage surveys to assess the extent of damage caused by the storm. Observations of wind speeds during TC Debbie were recorded at a number of Bureau of Meteorology automatic weather stations, as well as six mobile anemometers deployed by JCU prior to landfall. While these stations provide valuable measurements of wind speed at their locations, an estimate of the winds throughout the landscape is required to assign maximum wind speeds to the observed level of damage at each surveyed location. This relationship will be used to develop vulnerability curves for building stock in the affected region. These curves can assist emergency managers prepare for and respond to future severe wind events, through developing an understanding of the vulnerability of local building stock to severe wind events. We use the following workflow to develop a corrected, local wind field for TC Debbie: 1. Model the maximum wind gust over the lifetime of TC Debbie across the landfall region using the Tropical Cyclone Risk Model (TCRM); 2. Apply a correction for local wind factors, including topography, land cover, shielding and wind direction; 3. Validate the local wind field against observations; 4. Apply a correction based on the difference between the observed and modelled wind fields. The final wind field is a product of the modelled wind field, local and observational corrections to produce the best estimate of the spatial distribution of the maximum wind gust throughout the lifetime of TC Debbie. Poster presented at the 2018 Amos-ICSHMO Conference Sydney, NSW (https://www.ametsoc.org/index.cfm/ams/meetings-events/ams-meetings/amos-icshmo-2018/)

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.