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.

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

The Tropical Cyclone Scenario Selection tool enables users (e.g. emergency managers, engineers, researchers, etc.) to query the catalogue of tropical cyclone scenarios, developed as part of the 2018 Tropical Cyclone Hazard Assessment (TCHA18). The TCHA18 catalogue is comprised of 10,000 simulated years of tropical cyclone activity in the Australian region, amounting to over 160,000 tropical cyclone events. Using the search tools, the tracks and wind fields of individual events affecting a location or region can be discovered and explored. The returned scenarios are retrieved from a catalogue of synthetic tropical cyclones and can queried within the map and/or downloaded in various formats for follow-on analysis.

This wind field was produced within v2.0 of TCRM, using data from the Bureau of Meteorology to constrain the wind field. Wind multipliers were calculated using a landcover dataset derived from Landsat and Digital Earth Australia. This wind field may be refined in the future as new data becomes available. This record includes - the track data from the Bureau of Meteorology used to model Tropical Cyclone Debbie - the landcover dataset produced for the Airlie Beach region - the preliminary local wind field

The local wind multiplier data for Tongatapu is used to generate local wind speeds over the island of Tongatapu, Tonga.

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).

Tropical cyclone Gita impacted the Kingdom of Tonga in February 2018, causing significant damage across the main island of Tongatapu. This dataset is a best estimate of the maximum local gust wind speed across Tongatapu, based on the best-available track information, elevation and land cover data. The data represents the maximum 0.2 second, 10-metre above ground level wind speed at (approximately) 25 metre horizontal resolution. The wind field was generated using: Geoscience Australia's Tropical Cyclone Risk Model - https://github.com/GeoscienceAustralia/tcrm Wind Multipliers code - https://github.com/GeoscienceAusralia/Wind_Multipliers TC Gita track was sourced from the Joint Typhoon Warning Center (http://www.metoc.navy.mil/jtwc/jtwc.html)

In March 1999, TC Vance swept through Exmouth, with the eye wall of the cyclone passing directly over the township generating gusts to 267 km/h. Around 10% of residential houses showed structural failure, with some types of housing experiencing significantly greater damage. By revisiting the impacts of TC Vance, we hope to guide thinking of emergency managers and local government on planning for when another category 5 TC strikes Exmouth. Using the best track information provided by the Bureau of Meteorology, we simulate the wind field of TC Vance using Geoscience Australia’s Tropical Cyclone Risk Model (TCRM), incorporating the local effects of topography, terrain and shielding afforded by neighbouring structures. This simulation is validated against observations of peak wind speed recorded at Learmonth Airport and other regional weather stations. The impacts of TC Vance are calculated for the present building stock in Exmouth, which has grown by nearly a third since 1999. Modern residential buildings perform very well, in line with the performance levels established by the wind loading standards for the region. Some groups of older buildings – specifically the U.S. Navy block houses that survived TC Vance unscathed – also perform very well. The analysis shows the town of Exmouth would still suffer substantial impacts, with around 700 buildings likely to suffer moderate to complete damage. This translates to around 1400 people, with at least half of those requiring temporary accommodation in the days and weeks immediately after the cyclone. These types of analysis help to reduce uncertainty and enhances decision-making for emergency services, enabling a more proportional response for rescue, damage assessments and initial recovery at the State, regional and local levels. From a strategic perspective it can also be used to identify and verify current and future capability needs for agencies involved in managing the cyclone hazard. Presented at the Australian Meteorological and Oceanographic Society Annual Meeting and the International Conference on Tropical Meteorology and Oceanography (AMOS-ICTMO 2019) Conference

Natural hazard data supports the nation to respond effectively to emergencies, reduce the threat natural hazards pose to Australia¿s national interests and address issues relating to community safety, urban development, building design, climate change and insurance. A baseline understanding of hazards, impacts and risk can help to enhance community resilience to extreme events and a changing environment. Probabilistic hazard and risk information provides planners and designers opportunity to investigate the cost and benefit of policy options to mitigate natural hazard impacts. Modelled disaster scenario information can enable disaggregation of probabilistic hazard to identify the most probable event contributing to hazard. Tropical cyclone return period wind hazard maps developed using the Tropical Cyclone Risk Model. The hazard maps are derived from a catalogue of synthetic tropical cyclone events representing 10,000 years of activity. Annual maxima are evaluated from the catalogue and used to fit a generalised extreme value distribution at each grid point. Wind multipliers are factors that transform regional wind speed to local wind speed, mathematically describing the influences of terrain, shielding and topographic effects. Local wind speeds are critical to wind-related activities that include hazard and risk assessment. The complete dataset is comprised of: - Stochastic tracks, wind fields and impact data; - Probabilistic wind speed data (hazard); - Site-exposure wind multipliers.

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.