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

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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.

The Bushfire Attack Level Toolbox provides access to ArcGIS geoprocessing scripts that calculate the Bushfire Attack Level (BAL) as per Method 1 in AS-3959 (2009). BAL is a measure of the severity of a building's potential exposure to ember attack, radiant heat and direct flame contact in the event of a bushfire. It serves as a basis for establishing the requirements for construction to improve protection of building elements from attack by bushfire. The BAL Maps and Exposure report provide maps of three communities in Western Australia, with indicative BAL levels, and the aggregate inventory of assets and population exposed to the different levels of BAL.

To determine the magnitude of severe wind gust hazard due to thunderstorm downbursts using regional climate model output and analysis of observed data (including radar reflectivity and proximity soundings).

Eddy Covariance (EC) has been proposed as a surface monitoring solution for long-term deployment at CCS sites. However, its suitability when applied to a highly inhomogeneous source area- as would be the case for a small-scale CO2 surface leak- has been poorly established. For this reason, EC has been implemented for two controlled CO2 releases conducted at the Ginninderra controlled release facility, with the aim of determining the technique's suitability for the location, detection and quantification of a small magnitude CO2 leak (144 kg/d). By comparing results from the two release experiments, this poster highlights the variable success of using EC for detection, and how this may depend on changing experimental and climatic variables such as leak location, tower height and depth to groundwater. The detection significance of grouped EC measurements will be established through statistical analysis using Cramer-Von Mises tests. In addition, the application of two EC towers concurrently for leak detection and location will be explored, with a second tower deployed for the latter portion of the 2013 release experiment. Quantification of the leak using EC was attempted, but due to the problems in the fundamental assumptions of the technique, no substantive progress could be made. This will be explained with respect to the 'lost' CO2 from the system in part due to advection and diffusion. Presented at the 2014 CO2CRC Research Symposium

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.

We have developed an autonomous CO2 monitoring station, based around the Vaisala GMP343 sensor. The station is powered by a solar panel and incorporates a data logger and a directional antenna for line-of-sight wireless communication with a base station. The base station communicates via the Telstra mobile phone data network. The concept of atmospheric tomography was tested at the Ginninderra site and proved very successful as a method of locating and quantifying a spatially small release of CO2. In this case the sensors were separated from the source by 40 m. The opportunity to test the method over a larger distance arose during the controlled release of Buttress gas during the stage 2B experiment at the Otway site. Gas was released at 8 tpd during daylight hours, and an approximate ring of 8 monitoring stations was deployed around the release point; the ring was about 800 m in diameter. Gas was released on 12 occasions, chosen to match wind directions that would carry the plume in the direction of one of the sensors. The dataset was too limited to carry out the full-scale Bayesian inversion that was demonstrated in the Ginninderra test (which lasted two months) but a simple inversion was possible. This located the source of the release correctly to within 20 m. The test demonstrated that inexpensive sensors could achieve enough stability and sensitivity to work (in this particular application) at the few ppm level. Moreover quite simple dispersion models could be used to predict plume geometry up to 500 m from the release. Overall the experiment indicates the basis of an inexpensive method for remotely monitoring areas of around a km2 for spatially small leakages.

This dataset contains various code and outputs developed in demonstrating potential methods of generating 3-D topographic (and possibly other) multipliers for use in wind risk modelling activities. The 'wrf' folder contains output and configuration settings Chris Thomas developed in 2010 to test the feasibility of using WRF locally to derive topographic multipliers.

Geological storage of CO2 is a leading strategy for large-scale greenhouse gas emission mitigation. Monitoring and verification is important for assuring that CO2 storage poses minimal risk to people's health and the environment, and that it is effective at reducing anthropogenic CO2 emissions. Eddy Covariance (EC) has been proposed as a long-term monitoring solution for geological storage projects and is considered suitable for monitoring areas 1000 - 100,000 m2 in size. Eddy Covariance is a key micrometeorological technique which has traditionally been used for assessing ecosystem exchange of CO2 in a variety of natural and agricultural settings. It measures the vertical transfer of scalar variables such as CO2 via eddies from upwind of the instrumentation, and correlates the measured CO2 flux to the upwind source area based on several key assumptions. These assumptions include that the upwind source area is homogeneous, flat and uniform, which in turn requires that horizontal gradients in CO2 concentration are zero and that horizontal and vertical gradients in the covariance of CO2 concentration and orthogonal wind directions are zero. Work undertaken at the GA-CO2CRC Gininnderra controlled release facility, where CO2 is released from the shallow subsurface (at 2 m depth), suggests that CO2 leakage in the near subsurface will follow paths of least resistance up to the surface. Similar observations have been observed at the ZERT facility in Montana and CO2 Field Lab in Norway. This leads to CO2 leaks having localised, patchy surface expression, rather than a diffuse wide-scale leak which one typically expects (Lewicki et al. 2010). The implication of this is that the source area for a leak is highly inhomogeneous, meaning the magnitudes of CO2 flux values measured using EC are grossly unreliable. These limitations were discussed in Leuning et al.'s (2008) review on CCS atmospheric monitoring technologies yet are not addressed in much of the recent EC leak quantification literature. This presentation will present findings from the first subsurface release at the CO2CRC facility in Canberra (March - May 2012), where EC data was analysed for application in leak detection and quantification. The CO2 release rate was 144 kg/d. Eddy Covariance was successfully used to detect the leak by comparing CO2 fluxes in the direction of the leak to baseline wind sectors. Median CO2 fluxes in the leak direction were 9.1 µmol/m2/s, while the median background flux was 1.0 µmol/m2/s. Separate measurements taken using a soil flux meter found that the daytime background soil flux had a median flux of 1.8 µmol/m2/s but the peak soil flux over a leak was 1100 µmol/m2/s. Quantification and spatially locating the leak were attempted, but due to the problem of source area inhomogeneity, no substantive progress could be made. How an inhomogeneous source area contributes to 'lost' CO2 from the system, through advection and diffusion, will be discussed, coupled with suggestions for how these parameters can be evaluated in future experimental design. Leuning R., Etheridge D., Luhar A., and Dunse B., 2008. Atmospheric monitoring and verification technologies for CO2 sequestration. International Journal of Greenhouse Gas Control, 2(3), 401-414. Lewicki J. L., Hilley G. E., Dobeck L., and Spangler L., 2010. Dynamics of CO2 fluxes and concentrations during a shallow subsurface CO2 release. Environmental Earth Sciences, 60(2), 285-297. Presented at the 2014 Australian Earth Sciences Convention (AESC)