This job was part of the Coastal capture program. It captures from the coast to the 10m contour interval.

We report on an assessment of severe wind hazard across the Australian continent, and severe wind risk to residential houses (quantified in terms of annualised loss). A computational framework has been developed to quantify both the wind hazard and risk due to severe winds, based on innovative modelling techniques and application of the National Exposure Information System (NEXIS). A combination of tropical cyclone, synoptic and thunderstorm wind hazard estimates is used to provide a revised estimate of the severe wind hazard across Australia. The hazard modelling utilises both 'current-climate' information and also simulations forced by IPCC SRES climate change scenarios, which have been employed to determine how the wind hazard will be influenced by climate change. We have also undertaken a national assessment of localised wind speed modifiers including topography, terrain and the built environment (shielding). It is important to account for these effects in assessment of risk as it is the local wind speed that causes damage to structures. The effects of the wind speed modifiers are incorporated through a statistical modification of the regional wind speed. The results from this current climate hazard assessment are compared with the hazard based on the existing understanding as specified in the Australian/New Zealand Wind Loading Standard (AS/NZS 1170.2, 2002). Our analysis has identified regions where the design wind speed depicted in AS/NZS 1170.2 is significantly lower than 'new' hazard analysis. These are regions requiring more immediate attention regarding the development of adaptation options including consideration by the wind loading standards committee for detailed study in the context of the minimum design standards in the current building code regulations.

Much of the deep sea comprises soft-sediment habitats dominated by low abundances of small infauna, and traditional methods of biological sampling may therefore fail to sufficiently quantify biodiversity. During feeding and burrowing, many deep sea animals bioturbate the sediment, leaving signs of their activities called lebensspuren ('life traces'). In this study, we use three criteria to assess whether the quantification of lebensspuren from high resolution still images is an appropriate technique to broadly quantify biological activity in the deep sea: 1) The ability to differentiate biological assemblages between geographic regions; 2) the ability to reveal known biological patterns across environmental gradients; and 3) correlation with other methods of biological characterisation often used in the deep sea (e.g. video). Lebensspuren were quantified using a univariate measure of track richness and a multivariate measure of lebensspuren assemblages from the eastern (1712 images, 13 stations) and western (949 images, 11 stations) Australian margins. A total of 46 lebensspuren types were identified, including those matching named trace fossils. Assemblages were significantly different between the two regions, with five lebensspuren types accounting for over 95% of the differentiation (ovoid pinnate trace, crater row, spider feature, matchstick feature, mesh feature). Track richness in the combined margins dataset was correlated to depth, chlorin index (i.e. organic freshness), and possibly mud, although the strength of the relationships varied according to the dataset used. There was no relationship to total organic carbon. Lebensspuren richness from still images was significantly related to lebensspuren from video but not to occurrence of epifauna. Based on these results, the quantification of lebensspuren from still images seems an appropriate measure to broadly characterise biological activity in deep sea soft sediment ecosystems.

This user guide describes the important instructions for using the Tasmanian Extreme Wind Hazard Standalone Tool (TEWHST). It aims to assist the Tasmanian State Emergency Service (SES) to view the spatial nature of extreme wind hazard (and how it varies depending on the direction of the extreme wind gusts). This information indicates detailed spatial texture for extreme hazard, which can provide guidance for understanding where the local-scale hazard (and impact) is expected to be greatest for any particular event depending on the intensity and directional influence of the broad-scale severe storm.

To follow

AUSPOS, Geoscience Australia's online GPS positioning service, has now been in worldwide use since 2000 and has processed over 150,000 user data files. In 2011, the AUSPOS service was fully upgraded to use the Bernese Software as the processing engine together with more sophisticated GPS data analysis strategies, new ITRF to GDA transformations and the recently developed the AUSGEIOD09 model. In this presentation, we will briefly overview the AUSPOS2 system including the improved modelling and analysis strategies employed. Then, we will present test results for AUSPOS2 using 1, 2, 6, 12, 24 hours of data from 232 IGS2008 core stations as well stations from the Asia Pacific Reference Frame (APREF) network within mainland Australia using the IGS final, rapid and ultra rapid products, respectively. Preliminary tests using 24 hours data show that coordinate differences between AUSPOS solutions and APREF weekly solutions are within a millimetres level for all three components.

Volcanoes are one of nature's most powerful and destructive forces experienced on Earth. Lava flows, explosions of ash, molten rock and huge eruption clouds are pictures we relate to of volcanoes destructive power. But why do volcanoes erupt? This booklet identifies different types of volcanoes, and the dangers associated when volcanic materials are ejected in an eruption. It explains the importance of why we should study volcanoes and the effects these eruptions have on the atmosphere and climate. It also identifies where volcanoes are located in Australia. Student activities are included.

This abstract is to be submitted to the Australian Society of Exploration Geophysicists for consideration as a poster to be delivered at the 22nd ASEG conference and exhibition in February 2012.

The Geoscience Australia (GA) building located in Symonston, ACT utilises one of the largest GSHP systems in the southern hemisphere. It is based on a series of 210 geothermal heat pumps throughout the general office area of the building, which carry water through loops of pipe buried in 352 bore holes each 100 metres deep and 20cm in diameter. The system is one of the largest and longest operating of its type in Australia, providing an opportunity to examine the long term performance of a GSHP system. A 10-year building review conducted in 2007 estimated that the system had saved about $400,000 in electricity costs. When comparing energy performance in the annual 'Energy Use in the Australian Government Operations' reports, the GA building has maintained energy performance and targets that might normally be expected of a general office administration building. This is significant given the requirements to provide additional fresh air to laboratories and 24/7 temperature control to special storage areas. The energy savings can be attributed to the GSHP system and other energy efficient design principles used in the building.

These datasets contain both fundamental and also final outputs in the form of files, rasters and vectors. These datasets are utilised to provide a measure of Tasmanian severe wind risk for both current climate and two climate change scenarios. To provide a measure of Tasmanian severe wind risk for both current climate and two climate change scenarios, this study has developed: (1) an understanding of severe wind hazard for two climate change scenarios (at 2060 & 2100) separately considering thunderstorm downbursts and synoptic winds and then combining the elements to construct hazard with regards to likelihood and intensity for the region. The outputs of general circulation climate models were forced by two increasing greenhouse gas trajectories (A2 & B1 scenarios) to give representative wind hazard for the respective possible future greenhouse gas concentrations scenarios. (2) an understanding of how residential building exposure may change for the case study regions (2060 & 2100) utilising the Australian Bureau of Statistics population projections (A, B & C series) and the National Exposure Information System (NEXIS) to project current trends in occupancy statistics. (3) a preliminary understanding of annualised loss due to wind exposure for urban areas within 42 Tasmanian regions (considering 10 year to 2000 year return period hazard). Regions have been ranked on the severity of loss, and key contributing factors driving the risk in these high wind risk regions are considered.