This resource contains surface sediment data for Bynoe Harbour collected by Geoscience Australia (GA), the Australian Institute of Marine Science (AIMS) and Department of Land Resource Management (Northern Territory Government) during the period from 2-29 May 2016 on the RV Solander (survey SOL6432/GA4452). This project was made possible through offset funds provided by INPEX-led Ichthys LNG Project to Northern Territory Government Department of Land Resource Management, and co-investment from Geoscience Australia and Australian Institute of Marine Science. The intent of this four year (2014-2018) program is to improve knowledge of the marine environments in the Darwin and Bynoe Harbour regions by collating and collecting baseline data that enable the creation of thematic habitat maps that underpin marine resource management decisions. The specific objectives of the survey were to: 1. Obtain high resolution geophysical (bathymetry) data for outer Darwin Harbour, including Shoal Bay; 2. Characterise substrates (acoustic backscatter properties, grainsize, sediment chemistry) for outer Darwin Harbour, including Shoal Bay; and 3. Collect tidal data for the survey area. Data acquired during the survey included: multibeam sonar bathymetry and acoustic backscatter; physical samples of seabed sediments, underwater photography and video of grab sample locations and oceanographic information including tidal data and sound velocity profiles. This dataset comprises O2 consumption and CO2 production rates measured from core incubation experiments conducted on seabed sediments. A detailed account of the survey is provided in Siwabessy, P.J.W., Smit, N., Atkinson, I., Dando, N., Harries, S., Howard, F.J.F., Li, J., Nicholas W.A., Picard, K., Radke, L.C., Tran, M., Williams, D. and Whiteway, T., 2016. Bynoe Harbour Marine Survey 2017: GA4452/SOL6432 – Post-survey report. Record 2017/04. Geoscience Australia, Canberra. Thanks to the crew of the RV Solander for help with sample collection, Matt Carey, Craig Wintle and Andrew Hislop from the Observatories and Science Support at Geoscience Australia for technical support and Jodie Smith for reviewing the data. This dataset is published with the permission of the CEO, Geoscience Australia

The first step in understanding risk is understanding the hazard. This means knowing the likelihood of the hazard event and its intensity. During 2018, Geoscience Australia updated the Tropical Cyclone Hazard Assessment (TCHA) to better calculate the likelihood of tropical cyclones in Australia.

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.

Archive of the data and outputs from the Assessment of Tropical Cyclone Risk in the Pacific Region project. See GA record 76213.

We present the formulation of an open-source, statistical–parametric model of tropical cyclones (TCs) for use in hazard and risk assessment applications. The model derives statistical relations for TC behaviour (genesis rate and location, intensity, speed and direction of translation) from best-track datasets, then uses these relations to create a synthetic catalogue based on stochastic sampling, representing many thousands of years of activity. A parametric wind field, based on radial profiles and boundary layer models, is applied to each event in the catalogue that is then used to fit extreme-value distributions for evaluation of return period wind speeds. We demonstrate the capability of the model to replicate observed behaviour of TCs, including coastal landfall rates which are of significant importance for risk assessments. <b>Citation: </b>Arthur, W. C.: A statistical–parametric model of tropical cyclones for hazard assessment, Nat. Hazards Earth Syst. Sci., 21, 893–916, https://doi.org/10.5194/nhess-21-893-2021, 2021.

<div>Ask a Queenslander where tropical cyclones (TCs) occur, and the inevitable response will be North Queensland. Whilst most of the tropical cyclones have made landfall north of Bundaberg, the cascading and concurrent effects are felt much further afield. The major flooding following TC Yasi in 2011 and TC Debbie in 2017, are just two examples where impacts were felt across the State, and of course, the wind impacts to the banana plantation following TC Larry (2006) was felt nationally.&nbsp;</div><div> &nbsp;</div><div>South East Queensland has not been forgotten when it comes to tropical cyclone impact with an event crossing Coolangatta in 1954. There was also the more recent TC Gabrielle which tracked offshore on its path southwards to New Zealand.&nbsp;&nbsp;</div><div>&nbsp;</div><div>Acknowledging that climate is influencing the intensity and frequency of more intense severe weather hazards, understanding how tropical cyclone hazard varies under future climate conditions is critical to risk-based planning in Queensland. With this climate influence, along with increasing population and more vulnerable building design in South East Queensland (relative to northern Queensland), there is an urgent need to assess the wind risk and set in place plans to reduce the impacts of a potential tropical cyclone impact in South East Queensland. <b>Citation:</b> Sexton, J., Tait, M., Turner, H., Arthur, C., Henderson, D., Edwards, M; Preparing for the expected: tropical cyclones in South East Queensland.<i> AJEM</i> 38:4, October 2023, pages 33-39.

<div>Severe TC Ilsa crossed the Western Australian coastline approximately 120 km east of Port Hedland on Thursday 13 April 2023. Observations at Bedout Island were the highest wind speeds ever recorded on standard BoM instruments (gust wind speed of 289 km/h). In anticipation of the TC, residents in the mining township of Telfer were evacuated, along with a small number of evacuees in other townships (Marble Bar, South Hedland and Nullagine). As a category 5 TC, the threat of widespread destruction was front of mind for emergency managers in Western Australia.</div><div><br></div><div>Geoscience Australia (GA) has established the National Hazard Impact and Risk Service (NHIRS), which provides quantitative modelled impact forecast information for tropical cyclones, large-scale wind events and earthquakes in Australia. NHIRS has been used by the Department of Fire and Emergency Services (DFES) Intelligence Unit to support operational resource planning for TC events.</div><div><br></div><div>In TC Ilsa, DFES Intelligence (and GA) officers reviewed the impact predictions in the days leading up to landfall. Genuine questions were asked about the level of predicted damage, which was almost negligible across northern WA in spite of the predicted landfall intensity. Why was that the case? Was the service operating as expected? This paper highlights the challenge of educating users on the utility of impact forecasting products and communicating the components that are integrated in the impact forecast. Presented at the 30th Conference of the Australian Meteorological and Oceanographic Society (AMOS) 2024

<div>The wind hazard climate in South East Queensland is a combination of tropical cyclones, thunderstorms and synoptic storms. This dataset provides estimated average recurrence interval (ARI) or annual exceedance probability (AEP) wind speeds over the region, based on an evaluation of observational (thunderstorms and synoptic winds) and simulated data (tropical cyclones). </div><div><br></div><div>The tropical cyclone wind hazard was evaluated using Geoscience Australia's Tropical Cyclone Risk Model (TCRM), which provides a spatial representation of the AEP wind speeds arising from tropical cyclones. Thunderstorm wind hazard was evaluated from analysis of observed wind gusts across South East Queensland, aggregated into a single 'superstation' to provide a single representative hazard profile for the region.</div><div><br></div><div>The resulting combined wind hazard estimates reflect the dominant source of wind hazard in South East Queensland for the most frequent events (exceedance probabilities greater than 1:50) is thunderstorm-generated wind gusts. For rarer events, with exceedance probabilities less than 1:200, TC are the dominant source of extreme gusts.&nbsp;</div><div><br></div><div>Local effects of topography, land cover and the built environment were incorporated via site exposure multipliers (Arthur & Moghaddam, 2021), which are based on the site exposure multipliers defined in AS/NZS 1170.2 (2021).</div><div><br></div><div>The local wind hazard maps were used to evaluate the financial risk to residential separate houses in South East Queensland.</div><div><br></div><div>Wind speeds are provided for average recurrence intervals ranging from 1 year to 10,000 years. No confidence intervals are provided in the data. </div>

Tropical cyclones present a tangible risk to Australia’s tropical coastal communities, however extratropical transition (ETT) of these storms can result in significant impacts in mid-latitude regions as well. Tropical systems are driven by latent heat release in the inner core of the cyclone. A fully tropical system is highly axisymmetric; with a warm-cored vortex that is readily represented by a simple radial profile (wind speed is a function of distance from the centre in all directions). Extratropical cyclones on the other hand are driven by strong thermal gradients and as a result have a highly asymmetric wind field that cannot be as easily parameterised for use in stochastic models. In order to accurately model the risk of these transitioning storms on communities such as Perth, the wind field of these storms needs to be parameterised for inclusion in stochastic models. These models allow large numbers of storms to be quickly simulated for use in risk modelling applications. Some authors have attempted to develop parameterisations of these wind fields, with some recent success (Loridan et al. 2015), however an implementation for the Australian region has not yet been developed. Geoscience Australia currently undertakes tropical cyclone risk assessments using a parameterised, 2D stochastic model called the Tropical Cyclone Risk Model (TCRM). TCRM uses parameterised wind fields to allow quick generation of thousands of tropical cyclones in order to develop a probabilistic understanding of tropical cyclone risk for Australia. At present, this model is not capable of simulating tropical cyclones undergoing ETT as a parameterisation of the wind field of these storms around Australia is not available. This work aims to explore ETT around Australia using a 3D, dynamical numerical weather prediction model with the ultimate goal of developing a parameterised wind field, suitable for inclusion in TCRM. This would allow risk assessments for these storms to be undertaken, and improve our understanding of the potential impact of such an event on large urban areas, such as Geraldton or Perth. A modified version of the Weather Research and Forecast (WRF) model (Hybrid WRF) was used to simulate a number of hybrid idealised tropical cyclones, and steer them to undergo ETT. Hybrid WRF was developed to facilitate control over the track and location of landfall of a tropical cyclone, by introducing a steering flow to the boundary conditions of the model run. This method was used to steer a number of idealised tropical cyclones from off the northwest coast of Western Australia, south towards Perth, with the intent to force them to undergo ETT. Surface wind fields and other environmental characteristics (minimum pressure, latitude, thermal wind components, geopotential thickness and others) were analysed to determine the phase of ETT. This case study is the first example of Hybrid WRF being used to examine ETT, and while the steering flow did move the tropical cyclones into the extratropics as intended, only one storm was observed to undergo ETT. Further development of the code for Hybrid WRF is underway, with improvements in the initial and boundary conditions identified as a means to improve the representativeness of these experiments. Based on these simulated events, we intend to develop time-evolving, storm-centred wind fields, as well as statistics on cyclone phase space parameters that can be used to determine the stage of transition to be used in a future stochastic-parametric model of tropical cyclones. Abstract submitted to/presented at the 22nd International Congress on Modelling and Simulation 2017 (MODSIM2017) - https://www.mssanz.org.au/modsim2017/

This flythrough highlights seabed environments within two areas of Arafura Marine Park offshore northern Australia; Money Shoal and Pillar Bank. Located 250 km to the northeast of Darwin within the Arafura Sea, the marine park extends to the limit of Australia’s exclusive economic zone, covering an area of 22,924 km2. Money Shoal is an isolated carbonate reef platform on the continental shelf that rises from 70 m to shallow subtidal depths and supports a diverse coral and demersal fish community. The surrounding seabed comprises muddy substrate characterized by extensive fields of pockmark, interpreted as evidence for fluid escape from organic-rich sediment. Pillar Bank, in contrast, is representative of the deeper (150 – 200 m depths) outer shelf area of the marine park that supports sparse benthic communities of filter feeders on local outcrops of hard substrate, surrounded by expanses of muddy substrate. Demersal fish are also present, as observed using baited underwater cameras. Bathymetry data and seafloor imagery for this flythrough was collected in November 2020 by Geoscience Australia (GA) and the Australian Institute of Marine Science (AIMS) on board RV Solander during survey SOL7491/GA0366. Funding was provided by the Australian Government’s National Environmental Science Program (NESP) Marine Biodiversity Hub, with co-investment by GA and AIMS. For further information see: Picard, K. et al. 2020. Arafura Marine Park Post Survey Report. www.nespmarine.edu.au