The current study has developed a national methodology for assessing the hazard that peak wind gusts pose to Australian communities. The key components of the hazard assessment model include the regional wind hazard and the hazard modification multipliers. The local effects on return period regional wind speeds were determined utilising remote sensing techniques, digital elevation data, and formulae presented in the wind loadings standard AS/NZS 1170.2 [1]. The estimation of the local wind speeds was evaluated by combining the local wind multipliers (terrain/height, shielding and topographic) for eight cardinal directions with the return period regional wind speeds (from [1]) on a 25 metre grid across the areas examined for each region. Here we seek to use the 500 year return period wind gust hazard from the Australian/New Zealand wind loadings standard (AS/NZS 1170.2) [1], which is a building design document that seeks to 'envelope' possible wind effects, as a proxy for the regional hazard. Arthur et al. [2] provide a new hazard assessment for the Australian continent, which we plan to utilise in future updates. Tanh and Letchford [3] compared current US, Australian/New Zealand, European and Japanese wind standards and reported that the treatment of topographic effects in these design standards is on the whole conservative. Holmes [4] proposed adjustments to remove the conservatism from the methods in the Australian wind loading standard to assess risk. These proposals and several other initiatives were adopted to improve various components of the model from its initial steps [5] towards a reliable nationally consistent wind hazard assessment for Australia.

The National Wind Risk Assessment (NWRA), a collaboration between Geoscience Australia and the Dept. Climate Change and Energy Efficiency, has developed a computational framework to evaluate both the wind hazard and risk due to severe wind gusts (based on modelling techniques and application of the National Exposure Information System; NEXIS). A combination of tropical cyclone, synoptic and thunderstorm wind hazard estimates is used to provide a revised estimate of the severe wind hazard across Australia. The hazard modelling utilises both 'current-climate' information and also simulations forced by IPCC SRES climate change scenarios, employed to determine how the wind hazard will be influenced by climate change. The results from the current climate regional wind hazard assessment are compared with the hazard based on the existing understanding as specified in the Australian/New Zealand Wind Loading Standard (AS/NZS 1170.2, 2011). Regions were mapped where the design wind speed depicted in AS/NZS 1170.2 is significantly lower than the hazard analysis provided by this study. Regions requiring more immediate attention regarding the development of adaptation options are discussed in the context of the minimum design standards in the building code regulations. A national assessment of localised wind speed modifiers including topography, terrain and the built environment (shielding), has also been undertaken to inform the local wind speed hazard that causes damage to structures. The effects of the wind speed modifiers are incorporated through a statistical modification of the regional wind speed. We report on an assessment of severe impact and wind risk to residential houses across the Australian continent (quantified in terms of annualised loss). Considering future climate scenarios of regional severe wind hazard, we consider the changing nature of severe wind risk focusing on the Southeast Queensland and Tasmanian regions, and illustrate where the wind loading stan...

This user guide describes the important instructions for using the Tasmanian Extreme Wind Hazard Standalone Tool (TEWHST). It aims to assist the Tasmanian State Emergency Service (SES) to view the spatial nature of extreme wind hazard (and how it varies depending on the direction of the extreme wind gusts). This information indicates detailed spatial texture for extreme hazard, which can provide guidance for understanding where the local-scale hazard (and impact) is expected to be the greatest for any particular event depending on the intensity and directional influence of the broad-scale severe storm. The tool provides spatial information at the local scale (25 metre resolution) of the return period extreme wind hazard (3-second gust at 10 metre height; variation with direction) where the broad-scale regional hazard is provided by the Australian and New Zealand Wind Loading Standard (AS/NZS 1170.2, 2002).

Meteorological data from the Arcturus (ARA) atmospheric greenhouse gas baseline station. Data includes time stamp (local time), air temperature, relative humidity, wind speed, wind direction, sigma, solar radiation, barometric pressure and rainfall total. Dataset limited to the 1/6/12 to 8/7/12.

A short animation of an atmospheric simulation of methane emissions from a coal mine (produced using TAPM) compared to actual methane concentrations detected by the Atmospheric Monitoring Station, Arcturus in Central Queensland. It illustrates the effectiveness of both the detection and simulation techniques in the monitoring of atmospheric methane emissions. The animation shows a moving trace of both the simulated and actual recorded emissions data, along with windspeed and direction indicators. Some data provided by CSIRO Marine and Atmospheric Research.

A model to assess severe wind hazard using climate-simulated wind speeds have been developed at Geoscience Australia (Sanabria and Cechet, 2010a). The model has a num-ber of advantages over wind hazard calculated from observational data: Firstly the use of climate-simulated data makes it possible to assess wind hazard over a region rather than at a recording station. Secondly climate-simulated data allows wind analysts to calculate wind hazard over a long climatology and, more importantly, to consider the impact of cli-mate change on wind hazard. In this paper we discuss model sensitivity to two IPCC scenarios: scenario B1, a low emissions scenario, and scenario A2, a high emissions scenario. Current and future climate is considered. Currently we deal only with gusts associated with synoptic winds (mid-latitude weather systems) as the climate model only provides mean winds at a resolution of 14 km, which does not resolve thunderstorms. MODEL DESCRIPTION The model involves three computationally processes: - Calculation of return period (RP) for gust wind speed using a statistical model; - Extraction of wind speeds from a high resolution climate model; and - A Monte Carlo method to generate synthetic gust speeds based on a convolution of modelled mean speeds and empirical gust factor measurements.

This folder contains WindRiskTech data used in preliminary stages of the National Wind Risk Assessment. The data are synthetic TC event sets, generated by a statistical-dynamical model of TCs that can be applied to general circulation models to provide projections of TC activity. Output from two GCMs is available here - the NCAR CCSM3 and the GFDL CM2.1 model. For each, there are a number of scenarios (based on the SRES scenarios from AR4 and previous IPCC reports) and time periods (the time periods are not the same for the A1B scenario). For each mode, scenario and time period, the data are a set of 1000 TC track files in tab-delimited format contained in the huur.zip files in each sub-folder. The output folder contains the output of running TCRM (pre-2011 version) on each of the datasets.

This report contains the preliminary results of Geoscience Australia survey 273 to northwest Torres Strait. This survey was undertaken as part of a research program within the Torres Strait CRC aimed at understanding marine biophysical processes in Torres Strait and their effect on seagrass habitats. Two Geoscience Australia surveys were undertaken as part of this program, survey 266 measured monsoon season conditions (Heap et al., 2005), and survey 273 measured trade wind conditions. Section 6 compares and contrasts the survey results acquired for both surveys. Section 7 addresses the results of the survey program in light of the objectives of the CRC proposal. Survey 273 acquired numerous different data types to assist with characterising the mobile sediments and hydrodynamic nature of the region. Multibeam sonar, current meters, grab samples, vibro-cores, underwater video, meteorological data (from the Bureau of Meteorology), Landsat imagery, were all used to characterise the seabed hydrodynamics of Torres Strait.

Geoscience Australia's Risk & Impact Analysis Group has developed a statistical model of wind hazard utilising the Generalised Pareto Distribution (GPD). The model calculates the return period of severe winds based on daily maximum wind gust observations. The model utilises an automated procedure to partition the data into the hazard constituents (thunderstorms, synoptic winds, tornadoes, etc) based on the World Meteorological Observation Codes 3-hourly coded observations. This observational data set records the archived and present weather at the station site. The model fits the GPD to the station data (daily maximum wind gust) by automating the selection of the appropriate threshold above which data is included in the extreme value distribution. This threshold <em>u</em> is selected as the maximum of all feasible return period values obtained by fitting the GPD. Published comparative findings, including same region results, demonstrate the model can produce similar results in a more efficient, fully computational way. Confidence intervals for return periods are calculated automatically to allow wind analysts to distinguish regions of greater reliability.

Regional and local wind gust hazard estimates are utilised in the Australian building codes through the Australia/New Zealand Wind Loadings Standard. The wind engineering community relies to a significant extent on the peak gust wind speed estimates derived from observations collected over more than 70 years by the Australian Bureau of Meteorology (BoM). The current wind loading code and the performance of our infrastructure (residential, commercial, industrial and critical infrastructure) is based primarily on hazard estimates from a small dataset, consisting of mainly airport sites. In this paper we present an alternative method for the calculation of gust wind hazard using limate-simulated data. Currently we deal only with gusts associated with synoptic winds as the climate model only provides mean winds at a resolution of 14 km, which does not resolve thunderstorms. The methodology involves three computationally demanding processes: - Calculation of return period (RP) for gust wind speed using a statistical model; - Extraction of wind speeds from a high resolution climate model; and - A Monte Carlo method to generate synthetic gust speeds by performing a numerical convolution of mean wind speeds and regional gust factors. Results of applying the methodology to assess severe wind hazard in Tasmania under current and future climate are shown in a poster also presented at this workshop. In this paper we present the methodology.