A severe wind hazard model for non-cyclonic regions of Australia using simulated climate data

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Abstract

Severe wind is one of the major natural hazards affecting Australia. The main wind hazards contributing to economic loss in Australia are tropical cyclones, thunderstorms and mid-latitude storms. Geoscience Australia's Environmental Geoscience Division (EGD) has developed mathematical models to study a number of natural hazards including wind hazard. In this paper we describe a methodology to study "combined" gust wind hazard produced by thunderstorm and mid-latitude or synoptic storms. The methodology is aimed at applications in regions where these two wind types dominate the hazard spectrum across all return periods (most of the Australian continent apart from the coastal region stretching north from about 27°S where the hazard for large return periods is dominated by tropical cyclones). Each of these severe wind types is generated by different physical phenomena and poses a different hazard to the built environment. For these reasons, it is necessary to model them separately. The return period calculated for each wind type is then combined probabilistically to produce the combined gust wind return period, the indicator used to quantify severe wind hazard. The combined wind hazard model utilises climate model simulated wind speeds and hence it allows wind analysts to assess the impact of climate change on future wind hazard. It aims to study severe wind hazard in the non-cyclonic regions of Australia which is the region 'A', as defined in the Australian/NZ Wind Loading Standard (AS/NZS 1170.2:2011). This region is dominated by thunderstorm and synoptic winds. The synoptic wind component of the combined wind hazard comprises three sub-models: • A technique to extract and process mean wind speeds from a high-resolution regional climate model. The climate model used in these studies provides maximum time-step wind speeds each hour at a resolution of 14 km, which does not resolve thunderstorms or tropical cyclones. • A Monte Carlo method to generate gust wind speeds from the climate-modelled mean wind speeds; and • A statistical model to quantify wind hazard in terms of return period using extreme value distributions. The analysis of the thunderstorm wind hazard is made using the observational data from a number of Bureau of Meteorology (BoM) recording stations located around the country. Thunderstorm wind speeds are extracted by matching BoM weather description and wind speed datasets. An extreme value analysis is made on this dataset and the parameters of the resulting Generalised Pareto Distributions are interpolated spatially. This technique can be used to assess thunderstorm hazard under current climate conditions. For future climate, the model extracts two parameters from the regional climate model: the Convective Available Potential Energy (CAPE) and wind speed (surface and vertical profile). Using these two parameters it is possible to make an assessment of the likelihood of the formation of severe thunderstorms. The model allows estimation of possible changes in thunderstorm frequency and hence an assessment of thunderstorm wind hazard under future climate conditions, under the assumption that the intensity of thunderstorm downbursts remains constant. To illustrate the methodology, severe wind hazard calculations under current and future climate conditions for the Australian state of Tasmania will be presented. The results show increases particularly in the regions which currently have high hazard. This increase is however not uniform across the state and is more apparent in the later part of the 21 st century (greater greenhouse gas emissions forcing) than in the early part. Implications of this projected change for building standards will be discussed. © Commonwealth of Australia (Geoscience Australia) 2011.

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APA

Sanabria, L. A., Thomas, C. M., & Cechet, R. P. (2011). A severe wind hazard model for non-cyclonic regions of Australia using simulated climate data. In MODSIM 2011 - 19th International Congress on Modelling and Simulation - Sustaining Our Future: Understanding and Living with Uncertainty (pp. 2845–2851). https://doi.org/10.36334/modsim.2011.f7.sanabria

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