The National Hazard Impact Risk Service for Tropical Cyclone Event Impact provides information on the potential impact to residential separate houses due to severe winds. The information is derived from Bureau of Meteorology tropical cyclone forecast tracks, in combination with building location and attributes from the National Exposure Information System and vulnerability models to define the level of impact. Impact data is aggregated to Statistical Area Level 1, categorised into five qualitative levels of impact.

People, homes, businesses and infrastructure have been severely impacted by the recent flooding in Tweed Shire. Information is needed on the nature of these impacts to assess losses, assess community recovery and contribute to the development of strategies to reduce risk in the future. To collect this information a survey team has been established to gather data on the impact on buildings and businesses. The survey team is being led by Geoscience Australia, the national agency for geoscience research and spatial information, in collaboration with RMIT University and the Tweed Shire Council.

Wind multipliers are factors that transform wind speeds over open, flat terrain (regional wind speeds) to local wind speeds that consider the effects of direction, terrain (surface roughness), shielding (buildings and structures) and topography (hills and ridges). During the assessment of local wind hazards (spatial significance in the order 10's of metres), wind multipliers allow for regional wind speeds (order 10 to 100's of kilometres) to be factored to provide local wind speeds. <b>Value: </b>The wind multiplier data is used in modelling the impacts (i.e. physical damage) of wind-related events such as tropical cyclones (an input for Tropical Cyclone Risk assessment), thunderstorms and other windstorms. <b>Scope: </b>Includes terrain, shielding and topographic multipliers for national coverage. Each multiplier further contains 8 directions.

Australian Community Climate and Earth-System (ACCESS) Numerical Weather Prediction (NWP) data is made available by the Bureau of Meteorology for registered subscribers such as GA. ACCESS-C3 (City) model is a forecast-only model performed every 6 hours and consists of grid coordinates covering domains around Sydney, Victoria and Tasmania, Brisbane, Perth, Adelaide and Darwin. ACCESS Impact Modelling (ACCESS-IM) System utilise information from ACCESS-NWP on the forecast wind gust speeds ground surface (single-level) at 10 metres, simulated by the ACCESS-C3 model, for the time period of 0-12, 12-24, 24-36, 0-36.

This dynamic dataset is composed of data layers representing the potential damage arising from the impacts of Tropical Cyclone (TC) related winds on residential houses. The impacts are determined using information on the forecast track of the TC issued by the Bureau of Meteorology, nationally consistent exposure (residential building) and vulnerability (likely level of damage) information maintained by Geoscience Australia. The tracks are based on the content of Technical Bulletins issued by the Bureau of Meteorology’s Tropical Cyclone Warning Centres every 6 hours for active TCs in the Australian region. As such, information is generated intermittently, depending on the occurrence of TCs. The tracks are a forecast only, so do not include past position information of the TC. Forecasts may extend up to 120 hours (5 days) ahead of the forecast time. A wind field around each track is simulated using Geoscience Australia’s Tropical Cyclone Risk Model (TCRM, https://pid.geoscience.gov.au/dataset/ga/77484). This provides an estimate of the maximum gust wind speed over open, flat terrain (e.g. airports). Local effects such as topography and land cover changes are incorporated via site wind multipliers (https://pid.geoscience.gov.au/dataset/ga/75299), resulting in a 0.2-second, 10-m above ground level wind speed, with a spatial resolution of approximately 30 metres. The impacts are calculated using Geoscience Australia’s HazImp code (https://pid.geoscience.gov.au/dataset/ga/110501), which utilises the National Exposure Information System building data and a suite of wind vulnerability curves to determine the level of damage sustained by individual buildings (a damage index). The damage index values are aggregated to Australian Bureau of Statistics Statistical Area Level 1 regions, and can be assigned a qualitative damage description based on the mean damage index.

<div>To set out how Geoscience Australia is meeting its vision for the Exploring for the Future program, we have summarised the ways our scientific activities, outputs and intended outcomes and impacts are linked, using the Impact Pathway diagram. This updated brochure includes program impact infographics.</div>

Strong surface wind gusts and heavy rain are meteorological hazards that are predominantly produced by storms such as east coast lows, tropical cyclones or thunderstorms. Interest in these hazards from a response agency point of view lies in their impact on the natural and built environment. At present, weather forecast models still predict mostly 'raw' meteorological output such as surface wind speeds at certain times, or rain accumulations over a specified period. This model output needs to be combined with exposure and vulnerability information to translate the forecast hazard into predicted impact. The Bushfire and Natural Hazards CRC project Impact-based forecasting for the coastal zone: East-Coast Lows attempts to demonstrate a pilot capability to deliver impact forecasts for residential housing from an ensemble of weather prediction models runs. The project is a collaborative effort between the Australian Bureau of Meteorology and Geoscience Australia. The project is initially focusing on the wind and rainfall impact from the 20-22 April 2015 east coast low event in NSW. The wind and rainfall hazard data are provided by a 24-member ensemble of the ACCESS model on a 1.3 km grid, with damage data acquired from NSW State Emergency Services (SES) and the Emergency Information Coordination Unit (EICU) for the 2015 event. We will show that the multi-hazard nature of an east coast low event makes attributing the observed building damage to a single hazard difficult. Wind damage to residential housing in this case is largely due to tree fall. This 'damage-by-intermediary' mechanism requires not just the knowledge of building properties in an exposed area, but also additional knowledge of the surrounding vegetation and its response to strong winds. We will discuss enhancements to the SES/EICU damage survey templates that would lead to improvements in the development of the hazard-damage relationships. Abstract presented at the 2018 Bushfire and Natural Hazards CRC (bnhcrc) and Australasian Fire And Emergency Services Authorities Council (AFAC) Conference

This report presents the results of research conducted by Geoscience Australia (GA) in Bundaberg following the January 2013 floods. The report covers responses from both householders who were either inundated by the flood waters or who were fortunate to have escaped inundation. Irrespective of the inundation status, Bundaberg’s householders were still impacted by the flood event. Some may not have been able to access their place of work; some may have experienced physical and mental health issues. The report also discusses the impact of the flood on Bundaberg’s business community.

Australian Community Climate and Earth-System (ACCESS) Numerical Weather Prediction (NWP) data is made available by the Bureau of Meteorology for registered subscribers such as GA. ACCESS-C3 (City) model is a forecast-only model performed every 6 hours and consists of grid coordinates covering domains around Sydney, Victoria and Tasmania, Brisbane, Perth, Adelaide and Darwin. ACCESS Impact Modelling (ACCESS-IM) System utilise information from ACCESS-NWP on the forecast wind gust speeds ground surface (single-level) at 10 metres, simulated by the ACCESS-C3 model, for the time period of 0-12, 12-24, 24-36, 0-36.

Limited data from emergency services for the April 2015 East Coast Low (ECL) event initially investigated. SES call-out data provides spatial coverage, but does not capture detail of the damage to buildings. EICU data has detailed information, including indicative damage state, but limited spatial coverage. Neither dataset consistently links the damage to the hazard that caused it. Showing that the impact forecasting process adds value beyond the underlying hazard forecasts in this situation is challenging. EICU data can help to calibrate the vulnerability functions applied to model-based hazard forecast data. The SES callout data can help evaluate whether the indicative damage rates for an area are reasonable, through use of a service demand metric. Service demand is the number of callouts compared to the number of buildings for a statistical area (e.g. mesh block, SA1 or local government area). We use the total building count in each area, as the SES callout data does not differentiate between residential and non-residential buildings. It also includes callouts for downed trees or power lines that may not have directly caused structural damage to buildings. Service demand is compared to mesh block-based impact forecast data for the 2015 ECL, using existing heuristic vulnerability functions for severe wind. We recognise these functions are not calibrated against forecast model data, but provide a starting point from which we can establish the workflow while working towards refined vulnerability functions in parallel. The project has sourced EICU and SES post-event survey data, and high-resolution model (reanalysis) data for two additional severe wind and rain events to improve the calibration of the vulnerability functions. Poster presentation at the 2019 AFAC Conference