Global climate change is putting Australia's infrastructure and in particular coastal infrastructure at risk. More than 80% of Australians live within the coastal zone. Almost 800,000 residences are within 3km of the coast and less than 6m above sea level. Much of Australia's land transport is built around road and rail infrastructure which is within the threatened coastal zone. A significant number of Australia's ports, harbours and airports are under threat. Australia's coastal zone contains several major cities, and supports agriculture, fisheries, tourism, coastal wetlands and estuaries, mangroves and other coastal vegetation, coral reefs, heritage areas and threatened species or habitats. Sea level rise is one physical effect of rising sea temperatures and is estimated at about 0.146m for 2030 (IPCC 2007) and up to 1.1m for 2100 (Antarctic and Climate Ecosystems CRC). The warming is likely to result in increases in intensity of both extra-tropical and tropical storms (spatially dependent) which are predicted to increase storm surge and severe wind hazard. Beaches, estuaries, coastal wetlands, and reefs which have adapted naturally to past changes in climate (storminess) and sea level over long time scales, now are likely to face faster rates of change. In many cases landward migration may be blocked by human land uses and infrastructure. Adaptation options include integrated coastal zone assessments and management; redesign, rebuilding, or relocation of capital assets; protection of beaches, dunes and maritime infrastructure; development zone control; and retreat plans.

Wildfires are one of the major natural hazards facing the Australian continent. Chen (2004) rated wildfires as the third largest cause of building damage in Australia during the 20th Century. Most of this damage was due to a few extreme wildfire events. For a vast country like Australia with its sparse network of weather observation sites and short temporal length of records, it is important to employ a range of modelling techniques that involve both observed and modelled data in order to produce fire hazard and risk information/products with utility. This presentation details the use of statistical and deterministic modelling of both observations and synthetic climate model output (downscaled gridded reanalysis information) in the development of extreme fire weather potential maps. Fire danger indices such as the McArthur Fire Forest Danger Index (FFDI) are widely used by fire management agencies to assess fire weather conditions and issue public warnings. FFDI is regularly calculated at weather stations using measurements of weather variables and fuel information. As it has been shown that relatively few extreme events cause most of the impacts, the ability to derive the spatial distribution of the return period of extreme FFDI values contributes important information to the understanding of how potential risk is distributed across the continent. The long-term spatial tendency FFDI has been assessed by calculating the return period of its extreme values from point-based observational data. The frequency and intensity as well as the spatial distribution of FFDI extremes were obtained by applying an advanced spatial interpolation algorithm to the recording stations' measurements. As an illustration maps of 50 and 100-year return-period (RP) of FFDI under current climate conditions are presented (based on both observations and reanalysis climate model output). MODSIM 2013 Conference

Extreme events in a changing climate A climate event is 'extreme' when it (or a series of events) occurs with greater intensity, frequency or duration than is normally expected. Every region of the world experiences extreme events from time to time and natural climate variability already produces extreme events in Tasmania. This includes heat waves, cold waves, floods, droughts and storms. Extreme events can have devastating and wide ranging effects on society and the environment, impacting infrastructure, agriculture, utilities, water resources and emergency planning.

This presentation will provide an overview of some of the work currently being undertaken at Geoscience Australia GA) as part of the National Coastal Vulnerability Assessment (NCVA), funded by the Department of Climate Change (DCC). The presentation will summarise the methodology applied, and highlight the issues, including the limitations and data gaps.

Overhead transmission lines are a key element of the electrical power system for transferring bulk power from generators to communities. Lattice type transmission towers carrying conductors form the physical backbone of the power transmission system. Transmission tower safety and reliability assessment is necessary to plan for minimisation of the risk of disruption of power supply resulting from in-service tower failure. Lattice type transmission towers are constructed using angle section members and are eccentrically connected. They are regarded as one of the most difficult forms of lattice structures to analyse for dynamic loads. Analysis is difficult due to fabrication errors, inadequate joint details and material properties being hard to quantify as a combination. Proof loading and full-scale tower testing is a traditional form of design validation for lattice type towers [1]. However, loading conditions experienced in severe wind events are dynamic and relatively short term loads and this behavior is confirmed in a limited way through full scale measurements of aero-elastic models in wind tunnels [2].

Geoscience Australia has developed a model to assess severe wind hazard for large-scale numerical model-derived grided data. The severe wind modelling approach integrates two models developed at Geoscience Australia: a) A statistical model based on observations which determines return periods (RP) of severe winds using Extreme Value distributions (EVD), and b) A model which extracts mean wind speeds from high resolution numerical models (climate simulations) and generates wind gust from the mean speeds using Monte Carlo simulation (convolution with empirical gust factors) This methodology is particularly suitable for the study of wind hazard over large regions, and is being developed to provide improved spatial information for the Australia/NZ Wind Loading Standard (AS/NZS 1170.2, 2002). The methodology also allows comparison of current and future wind hazard under changing climate conditions. To illustrate the characteristics and capabilities of the methodology, the determination of severe wind hazard for a high-resolution grid encompassing the state of Tasmania (south of the Australian continent) will be presented and discussed, considering both the current and a range of possible future climate conditions (utilising IPCC B1 & A2 emission scenarios).

The National Exposure Information System (NEXIS) project is an initiative of Geoscience Australia in response to the Australian Government's research priority of safeguarding Australian communities from natural hazards, critical infrastructure failures and policy development. The governmental priority urges the implementation of a 'nationally consistent system of data collection, research and analysis to ensure a sound knowledge-base on natural disasters and disaster mitigation'. The infrastructure exposure definition and development framework suitable for multi hazards and climate change impact analysis is highly complex. NEXIS aims to meet the challenge by collecting, collating and maintaining nationally consistent exposure information at the individual building level. This requires detailed spatial analysis and the integration of available demographic, structural and statistical data for various sectors. The system integrates data from several national spatial databases, such as the Geocoded National Address File, the Property Cadastre, Australian Bureau of Statistics (ABS) census data, and building data from Australian state governments. It also includes post disaster survey information and data from several infrastructure agencies and local government bodies. NEXIS provides a representative assessment of asset exposure to several hazard models which can be aggregated to an appropriate level from State to mesh block level for the required application. By integrating the information with the decision-support tools of alert systems and early warning, it can enable the rapid forecasting of the impacts due to various hazards (infrastructure damage and casualties). Currently it is being used for tactical response for emergency managers and strategic policy and planning development. In addition to enabling research in Geoscience Australia's risk and impact analysis projects, it supports several government initiatives across the departments and national committees.

A model to assess severe wind hazard using climate-simulated wind speeds has been recently completed at Geoscience Australia. The model can calculate return period of wind speeds over a given region considering current as well as future climate conditions. The winds extracted from the climate simulations are winds at 10m height over open terrain. In hazard studies it is important however, to refer the wind speeds to the characteristics of the given location in order to calculate the actual severe wind hazard at the regional level. This is achieved by multiplying the generic wind hazard by a number of wind multipliers. One of those multipliers is wind direction. The wind direction multiplier recognises the prevailing direction of the strongest winds and affects the wind hazard accordingly. Lower wind hazard would correspond to the direction of low wind speeds. In practical applications engineers calculate the wind load in structures by multiplying the design wind speeds recommended by the Australian/NZ standards for wind loading in structures (AS/NZS 1170.2:2010) by some generic multipliers also given in the standards. The multipliers have been developed considering a number of Bureau of Meteorology (BoM) weather recording stations at particular locations in Australia; this method cannot capture the actual regional characteristics in such a vast country like Australia. In this paper we propose a new methodology for calculation of wind direction multipliers based on wind speeds and direction extracted from climate simulations. Our method allows a more realistic assessment of the wind direction multiplier at a particular region.

Severe wind is one of the major natural hazards in Australia. The main contributors to economic loss in Australia are tropical cyclones, thunderstorms and sub-tropical (synoptic) storms. Geoscience Australia's Risk and Impact Analysis Group (RIAG) is developing mathematical models to study a number of natural hazards including wind hazard. This study examines synoptic wind hazard under current and future climate scenarios using RIAG's synoptic wind hazard model. This model can be used in non-cyclonic regions of Australia (Region A in the Australian-New Zealand Wind Loading Standard; AS/NZS 1170.2:2002) which are dominated by synoptic and thunderstorm winds. The methodology to study synoptic wind hazard involves a combination of three models: - a statistical model (ie. a model based on observed data) to quantify wind hazard using extreme value distributions; - a technique to extract and process wind speeds from a high-resolution regional climate model (RCM), which produces gridded hourly 'maximum time-step mean' wind speed and direction fields; and - a Monte Carlo method to generate gust wind speeds from the RCM mean winds. Gust wind speeds are generated by a numerical convolution of the modelled mean wind speed distribution and a distribution of observed 'regional' gust factor. To illustrate the methodology, wind hazard calculations under current and future climate conditions for the Australian state of Tasmania will be presented. The results show increases in synoptic wind hazard in some parts of the state especially at the end of this century.

The islands in the west Pacific are highly vulnerable to tropical cyclones. These severe storms can devastate communities by destroying homes, crops and infrastructure, and result in loss of life. As part of the Pacific Climate Change Science Program, Geoscience Australia assessed the wind hazard from tropical cyclones for fourteen islands in the west Pacific as well as East Timor. The wind hazard was estimated for the current climate and projections were made for 2090 under the SRES A2 emissions scenario. This was achieved using a combination of historical tracks, tracks of tropical cyclone-like vortices detected in downscaled climate models and the Tropical Cyclone Risk Model (TCRM), developed by Geoscience Australia. The current climate wind hazard was found to exceed the wind loading design standards (HB 212-2002, 2002) by 15%-30%. The climate projections indicate a general decrease in wind hazard for the fifteen countries by 2090, associated with a poleward shift in storm genesis and peak intensity.