<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)

<div>Severe TC Ilsa crossed the Western Australian coastline approximately 120 km east of Port Hedland on Thursday 13 April 2023. Observations at Bedout Island were the highest wind speeds ever recorded on standard BoM instruments (gust wind speed of 289 km/h). In anticipation of the TC, residents in the mining township of Telfer were evacuated, along with a small number of evacuees in other townships (Marble Bar, South Hedland and Nullagine). As a category 5 TC, the threat of widespread destruction was front of mind for emergency managers in Western Australia.</div><div><br></div><div>Geoscience Australia (GA) has established the National Hazard Impact and Risk Service (NHIRS), which provides quantitative modelled impact forecast information for tropical cyclones, large-scale wind events and earthquakes in Australia. NHIRS has been used by the Department of Fire and Emergency Services (DFES) Intelligence Unit to support operational resource planning for TC events.</div><div><br></div><div>In TC Ilsa, DFES Intelligence (and GA) officers reviewed the impact predictions in the days leading up to landfall. Genuine questions were asked about the level of predicted damage, which was almost negligible across northern WA in spite of the predicted landfall intensity. Why was that the case? Was the service operating as expected? This paper highlights the challenge of educating users on the utility of impact forecasting products and communicating the components that are integrated in the impact forecast. Presented at the 30th Conference of the Australian Meteorological and Oceanographic Society (AMOS) 2024

<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.

<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>

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/)

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.

Tropical cyclones present a tangible risk to Australia’s tropical coastal communities, however extratropical transition (ETT) of these storms can result in significant impacts in mid-latitude regions as well. Tropical systems are driven by latent heat release in the inner core of the cyclone. A fully tropical system is highly axisymmetric; with a warm-cored vortex that is readily represented by a simple radial profile (wind speed is a function of distance from the centre in all directions). Extratropical cyclones on the other hand are driven by strong thermal gradients and as a result have a highly asymmetric wind field that cannot be as easily parameterised for use in stochastic models. In order to accurately model the risk of these transitioning storms on communities such as Perth, the wind field of these storms needs to be parameterised for inclusion in stochastic models. These models allow large numbers of storms to be quickly simulated for use in risk modelling applications. Some authors have attempted to develop parameterisations of these wind fields, with some recent success (Loridan et al. 2015), however an implementation for the Australian region has not yet been developed. Geoscience Australia currently undertakes tropical cyclone risk assessments using a parameterised, 2D stochastic model called the Tropical Cyclone Risk Model (TCRM). TCRM uses parameterised wind fields to allow quick generation of thousands of tropical cyclones in order to develop a probabilistic understanding of tropical cyclone risk for Australia. At present, this model is not capable of simulating tropical cyclones undergoing ETT as a parameterisation of the wind field of these storms around Australia is not available. This work aims to explore ETT around Australia using a 3D, dynamical numerical weather prediction model with the ultimate goal of developing a parameterised wind field, suitable for inclusion in TCRM. This would allow risk assessments for these storms to be undertaken, and improve our understanding of the potential impact of such an event on large urban areas, such as Geraldton or Perth. A modified version of the Weather Research and Forecast (WRF) model (Hybrid WRF) was used to simulate a number of hybrid idealised tropical cyclones, and steer them to undergo ETT. Hybrid WRF was developed to facilitate control over the track and location of landfall of a tropical cyclone, by introducing a steering flow to the boundary conditions of the model run. This method was used to steer a number of idealised tropical cyclones from off the northwest coast of Western Australia, south towards Perth, with the intent to force them to undergo ETT. Surface wind fields and other environmental characteristics (minimum pressure, latitude, thermal wind components, geopotential thickness and others) were analysed to determine the phase of ETT. This case study is the first example of Hybrid WRF being used to examine ETT, and while the steering flow did move the tropical cyclones into the extratropics as intended, only one storm was observed to undergo ETT. Further development of the code for Hybrid WRF is underway, with improvements in the initial and boundary conditions identified as a means to improve the representativeness of these experiments. Based on these simulated events, we intend to develop time-evolving, storm-centred wind fields, as well as statistics on cyclone phase space parameters that can be used to determine the stage of transition to be used in a future stochastic-parametric model of tropical cyclones. Abstract submitted to/presented at the 22nd International Congress on Modelling and Simulation 2017 (MODSIM2017) - https://www.mssanz.org.au/modsim2017/

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

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.

Archive of the data and outputs from the Assessment of Tropical Cyclone Risk in the Pacific Region project. See GA record 76213.