Return period cyclonic wind hazard in the Australian region
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A review commissioned by the Council of Australian Governments in 2001, Natural Disasters in Australia: reforming mitigation, relief and recovery arrangements, (COAG, 2002) recommended a fundamental shift in focus in relation to natural disasters; beyond relief and recovery towards cost-effective, evidence-based disaster mitigation. The severe wind activity at Geoscience Australia is developing a tropical cyclone (TC) hazard model, one of the three components of an infrastructure risk model, to rigorously assess the risk around the Australian coastline posed by TCs. The other two models are infrastructure exposure and vulnerability models for different types of infrastructure (e.g. residential, industrial and commercial) and within infrastructure types (e.g. residential; solid brick, brick veneer, timber and fibro-cement). The first stage in assessing the risk of tropical cyclones is to determine the level of hazard. The hazard model is a statistical model of tropical cyclone behaviour, similar to those of Powell et al (2005) and Hall and Jewson (2007). The model utilises distributions of tropical cyclone properties (speed, bearing, intensity), developed on a grid covering the regions of interest. Tropical cyclones are randomly initiated by sampling from a 2 dimensional probability density function (PDF) of tropical cyclone origins. Subsequent behaviour of the TC is determined by sampling from the prepared distributions. The hazard model is designed to permit as much flexibility for the user as possible. To this end, users can select the form of PDF kernel used to calculate distributions of parameters; wind fields applied to each synthetic track are parametric and can test the sensitivity of hazard levels to the choice of radial wind profile or asymmetry model, for example. As a preliminary validation exercise of the model, the hazard output is compared to the output from another statistical hazard model over northern Australia, and other existing estimates of the wind hazard. We compare the 0.2% annual exceedence probability (AEP) wind speed at selected locations and present a spatial estimate of this wind speed, incorporating the effects of shielding, terrain and topography where possible to arrive at a site-specific hazard estimate. The 0.2% AEP is chosen, as this is the standard which residential buildings are designed to survive. Some caveats on estimating the appropriate wind hazard across Australia are also highlighted, indicating the difficulties in correctly estimating the hazard levels in a changing climate.
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