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.

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).

This dataset provides an assessment of the tropical cyclone wind hazard for the Kingdom of Tonga. The data was generated to provide a collection of scenarios for detailed impact mapping as part of the PacSAFE project (2016-2018), funded by the Australian Department of Foreign Affairs and Trade. The dataset includes a catalogue of synthetic tropical cyclone tracks and the corresponding maximum wind swaths, average recurrence interval (ARI) wind speeds for ARIs from 5 to 10,000 years, and hazard profiles for selected locations within the simulation domain.

The Assessment of Tropical Cyclone Risks in the Pacific Region project represents a collaboration between DIICCSRTE and Geoscience Australia with PCRAFI and AIR Worldwide. Building on the expertise of each organisation, the project will deliver an assessment of the financial risks to buildings, infrastructure and agriculture arising from tropical cyclones (TCs) under current and future climate regimes. This extends previous risk assessments undertaken by incorporating the influence of climate change on the hazard (TCs) into the assessment process. The output of this study is a set of peril matrices, which detail the relative change in parameters describing TC behaviour: e.g. annual mean frequency, mean maximum intensity and mean latitude of genesis. The relative changes are evaluated as the fractional change between TC behavior in current climate GCM simulations and future climate GCM simulations.

The Bushfire Attack Level Toolbox provides access to ArcGIS geoprocessing scripts that calculate the Bushfire Attack Level (BAL) as per Method 1 in AS3959-2009. BAL is a measure of the severity of a building's potential exposure to ember attack, radiant head and direct flame contact. It is defined in AS3959-2009 to serve as a basis for establishing the requirements for construction to improve protection of building elements from attack by bushfire. In the BAL Toolbox, the calculation method (as defined in AS3959-2009) is adapted to be applied spatially. Input information required are a digital elevation model and classified vegetation data. The BAL Toolbox allows users to calculate BAL for small regions, without the need for large computational resources or for executing code in command-line environments. This will provide stakeholders with the ability to efficiently generate rigorous and robust maps of Bushfire Attack Level that adhere to the national standard, compared to products generated by manual techniques. The BAL Toolbox code is written in Python, utilising the ArcGIS "arcpy" module to enable easy reading/writing of raster data and to provide methods for a graphical user interface in the standard ArcGIS tool style. The BAL Toolbox User Guide provides users an overview of the Toolbox, instructions on installation, any customisations execution and evaluation of results.

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), and 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)

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.

Australian Community Climate and Earth-System (ACCESS) Numerical Weather Prediction (NWP) data is made available by the Bureau of Meteorology for registered subscribers such as GA. ACCESS-C3 (City) model is a forecast-only model performed every 6 hours and consists of grid coordinates covering domains around Sydney, Victoria and Tasmania, Brisbane, Perth, Adelaide and Darwin. ACCESS Impact Modelling (ACCESS-IM) System utilise information from ACCESS-NWP on the forecast wind gust speeds ground surface (single-level) at 10 metres, simulated by the ACCESS-C3 model, for the time period of 0-12, 12-24, 24-36, 0-36.

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

The collection of products released for the 2018 National Tropical Cyclone Hazard Assessment (TCHA18). - 2018 National Tropical Cyclone Hazard Assessment - 2018 National Tropical Cyclone Hazard Assessment Stochastic Event Catalogue - 2018 National Tropical Cyclone Hazard Assessment Hazard Map - Tropical Cyclone Risk Model