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  • Tropical cyclone return period wind hazard layers developed using the Tropical Cyclone Risk Model. The hazard layers are derived from a catalogue of synthetic tropical cyclone events representing 10000 years of activity. Annual maxima are evaluated from the catalogue and used to fit a generalised extreme value distribution at each grid point.

  • 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.

  • 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 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

  • 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.

  • There is increasing recognition that minimising methane emissions from the oil and gas sector is a key step in reducing global greenhouse gas emissions in the near term. Atmospheric monitoring techniques are likely to play an important future role in measuring the extent of existing emissions and verifying emission reductions. They can be very suitable for monitoring gas fields as they are continuous and integrate emissions from a number of potential point and diffuse sources that may vary in time. Geoscience Australia and CSIRO Marine & Atmospheric Research have collected three years of continuous methane and carbon dioxide measurements at their atmospheric composition monitoring station ('Arcturus') in the Bowen Basin, Australia. Methane signals in the Bowen Basin are likely to be influenced by cattle production, landfill, coal production, and conventional and coal seam gas (CSG) production. Australian CSG is typically 'dry' and is characterised by a mixed thermogenic-biogenic methane source with an absence of C3-C6+ alkanes. The range of '13C isotopic signatures of the CSG is similar to methane from landfill gas and cattle emissions. The absence of standard in-situ tracers for CSG fugitive emissions suggests that having a comprehensive baseline will be critical for successful measurement of fugitive emissions using atmospheric techniques. In this paper we report on the sensitivity of atmospheric techniques for the detection of fugitive emissions from a simulated new CSG field against a three year baseline signal. Simulation of emissions was performed for a 1-year period using the coupled prognostic meteorological and air pollution model TAPM at different fugitive emission rates (i.e. estimates of <1% to up to 10% of production lost) and distances (i.e. 10 - 50 km) from the station. Emissions from the simulated CSG field are based on well density, production volumes, and field size typical of CSG fields in Australia. The distributions of the perturbed and baseline signals were evaluated and statistically compared to test for the presence of fugitive methane emissions. In addition, a time series model of the methane baseline was developed in order to generate alternative realizations of the baseline signal. These were used to provide measures of both the likelihood of detecting fugitive emissions at various emission levels and of the false alarm rate. Results of the statistical analysis and an indicative minimum fugitive methane emission rate that can be detected using a single monitoring station are presented. Poster presented at the American Geophysical Union meeting, December 2013, San Francisco

  • 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 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

  • 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.

  • 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).