Queensland Fire and Emergency Services are leading the development of consistent risk information relating to the potential impacts of disasters across Queensland. The stated aim is to ensure all local, district and state government stakeholders have access to the same information to guide risk-based planning in the preparation for natural disasters. This extends to future projections natural hazard activity, including tropical cyclones (TC), in the Queensland region. To achieve this last objective, Queensland’s Department of Environment and Science (DES) have undertaken a program of regional climate simulations, with a view to informing long-term planning decisions. When it comes to TCs – a major cause of disasters in Queensland – many of the stakeholders want to answer the question: “How many severe tropical cyclones will the future hold for us?”, or similar questions around the likelihood of TC occurrence. To answer this, DES and Geoscience Australia are interrogating the regional climate simulations to extract Tropical Cyclone-Like Vortices (TCLVs). The behaviour of these TCLVs is then analysed to understand changes in frequency, intensity and spatial distribution. The TCLVs – with some additional bias corrections - can also be used as input to stochastic models that can provide probabilistic wind hazard information across the entire state of Queensland. In this paper we demonstrate the challenges of extracting TCLVs from regional climate models and the bias corrections required to make useful projections of TC activity into the future. Abstract presented at the 2020 Australian Meteorological and Oceanographic Society 2020 National Conference (http://amos-2020.w.amos.currinda.com/)

<div>The Severe Wind Hazard Assessment for Queensland arose as a project to better understand the potential impacts of tropical cyclones (TCs) on population centres and elements of critical infrastructure in Queensland. The rationale for the project was reinforced by lessons from Severe Tropical Cyclone (STC) Debbie, the direct and indirect impacts of which affected a significant area of Queensland, stretching from Bowen to the City of Gold Coast and Northern New South Wales between 28 March and 7 April 2017, resulting in 14 mostly flood associated deaths, and more than A$3.5 billion in direct losses. The intent of the project is to explore and assess a range of scenarios that extend beyond the contemporary recollection of severe events in order to challenge decision making for rarer but higher-consequence events. The scenarios described in the report can be used to improve planning for severe tropical cyclone (TC) events and their impacts. This includes developing a better understanding of how the capabilities of emergency services and supporting elements may be impacted in actual events.&nbsp;</div><div><br></div><div>Scenarios were selected from the catalogue of synthetic events (i.e. events that did not actually occur but whose occurrence was as probable as those that did occur) generated for the 2018 Tropical Cyclone Hazard Assessment (TCHA; Arthur, 2018), in consultation with Queensland Fire and Emergency Services (QFES) and those local governments involved within the project. Two TC events were modelled for each location for this project – a Category 3 and a Category 5 TC -with ‘favourable’ tracks for impact analysis. In all scenarios, consideration was given to regional historical analogues for the selected synthetic tracks to better relate the scenario outputs to known or “lived” events. These categories were chosen as they represent events with a moderate and very low likelihood with respect to intensity, based on historical observations. This also accounts for the future climate of less TCs but more intense occurrences, highlighting the different impacts arising from different events. It is important to emphasise and understand that each individual TC event will be different and lead to different impacts.&nbsp;</div><div><br></div>

Here we demonstrate a workflow for the development of a local, corrected wind field for severe Tropical Cyclone (TC) Debbie. We combine modelling with corrections based on observations, and local wind effects including topography, land cover, shielding and direction to provide the best estimate of actual wind speeds. This is important, as wind speed observations are sparse, and do not necessarily provide even coverage of the TC landfall region. The final corrected wind field records the maximum 0.2 second wind gust, at 10 metres above ground, throughout the lifetime of TC Debbie, and provides a best estimate of maximum wind gust speeds associated with TC Debbie. Through the development of this workflow we will demonstrate the importance of observational data for validating wind field modelling outputs, and highlight the usefulness of James Cook University’s mobile anemometers for collecting wind speed data where gaps exist in the Bureau of Meteorology’s automatic weather station network. We identify the limitations in the availability of national land cover datasets at high resolution, and demonstrate the development of a fit-for-purpose land cover dataset using GA’s Digital Earth Australia Landsat archives (Lewis et al. 2017). This report and the accompanying datasets have been released with the aim of showcasing a method, which can be refined by others to develop a standard methodology for the production of local TC wind fields. This workflow can be applied in the same way following future TC events to support the post-disaster field surveys that are routinely carried out by a range of parties following a severe TC making landfall. The local wind fields, combined with the damage surveys ultimately help to refine our vulnerability models of housing stock in Australia.

To provide the solar power industry with a data resource to allow them to assess the economic potential of a site for a solar power plant. Specifically under the Solar Flagship program.

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/)

As part of the 2018 Tropical Cyclone Hazard Assessment (TCHA), we compiled the geospatial raster dataset that can be accessible to internal and external users via ArcGIS online and can be integrated for building additional geoprocessing applications. This web service gives more stable and easy access to data and interactive maps. With having separate geospatial layers for each recurrence interval- i.e. 5 through 10000 years, users can toggle between the layers and evaluate the changes in wind speed (km/hr) and potential areas at risk on the fly.

<p>The wind hazard posed to Australia based on the frequency and intensity of tropical cyclones making landfall around the Australian coastline has been assessed using Tropical Cyclone Hazard Assessment (TCHA). This dataset is a derived product from the original raster layers. <p>We compiled geospatial raster layers for each recurrence interval - i.e. 5 through 10000 years in km/hr unit and classified in 19 classes to better present to a public audience.

Using the wind multiplier code (https://pid.geoscience.gov.au/dataset/ga/82481) and an appropriate source of classified terrain data, wind multipliers for all of Queensland at (approximately) 25 metre resolution were created. The wind multipliers have been used to guide impact assessments as part of the Severe Wind Hazard Assessment for Queensland.

Included fields: Record identifier - hm Bureau of Meteorology Station Number. Year Month Day Hours Minutes in YYYY,MM,DD,HH24,MI format in Local time Year Month Day Hours Minutes in YYYY,MM,DD,HH24,MI format in Local standard time Air Temperature in degrees C Quality of Air Temperature Wet bulb temperature in degrees C Quality of Wet Bulb Temperature Dew point temperature in degrees C Quality of Dew point Temperature Relative humidity in percentage % Quality of Relative humidity Wind speed in km/h Quality of Wind speed Wind direction in degrees Quality of Wind direction Speed of maximum wind gust in last 10 minutes in km/h Quality of speed of maximum wind gust in last 10 minutes Automatic Weather Station Flag

Included fields: Bureau of Meteorology Station Number. Year month day in YYYY,MM,DD format. Present weather at (00, 03, 06, 09, 12, 15, 18, 21) hours Local Time, as international code. Quality of present weather at (00, 03, 06, 09, 12, 15, 18, 21) hours Local Time. Past weather at (00, 03, 06, 09, 12, 15, 18, 21) hours Local Time, as international code. Quality of past weather at (00, 03, 06, 09, 12, 15, 18, 21) hours Local Time.