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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.

  • 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

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

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

  • The Atmospheric Tomography software is a command line tool written in python to estimate the emission rate of a point source from concentration data. It implements an extension of the Bayesian inversion method. Bhatia, S., Feitz, A. and Francis, A. (2017) Atmospheric Tomography, GitHub repository, https://github.com/GeoscienceAustralia/atmospheric_tomography_laser

  • 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.

  • 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.

  • 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.

  • 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)

  • 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).