Tropical cyclone
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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
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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.
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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.
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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.
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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.
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The TCHA18 Data collection covers the model output generated by the Tropical Cyclone Risk Model as part of the assessment. This includes average recurrence interval wind speeds, stochastic track catalogues, wind fields and intermediary data. It also includes an evaluation track catalogue, used to evaluate the performance of the model with respect to historical landfall rates, frequency and track density.
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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
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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)
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The local wind multiplier data for Tongatapu is used to generate local wind speeds over the island of Tongatapu, Tonga.
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Tropical cyclone scenario prepared for Tonga National Emergency Management Office (NEMO) as part of the PacSAFE Project (2016-2018)