<p>Geoscience Australia in collaboration with the CO2CRC hosted three controlled subsurface release experiments of CO2 during 2012 to 2013 at an agricultural research station managed by CSIRO Plant Industry Canberra. The facility was designed to simulate surface emissions of CO2 and other greenhouse gases from the soil into the atmosphere, and has deployed a range of near-surface monitoring techniques in the pursuit of improving detection and quantification methods and technologies. This product, which encompasses 4 geodatabases, a metadata report and a data dictionary, presents all the data collected during the experiments from over 10 research organisations, and is made to use with GIS software. The intention of this data release is make the data available for comparison with measurements taken at other controlled release experiments, CO2 storage projects and natural analogues. This will hopefully facilitate the further development of greenhouse gas monitoring technologies, methods and monitoring strategies and increase our understanding of the migration behaviour and impact of near surface CO2 leakage. <p>The contents of each geodatabase/experiment is summarised below: <p>Release 1 (Feb-May 2012): <p>- Soil microbial data <p>- Soil chemistry <p>- Free air CO2 concentration <p>- Eddy covariance <p>- Groundwater chemistry <p>- Soil gas <p>- Krypton tracers <p>- EM31 <p>- Soil flux <p>Release 2 (Oct-Dec 2012): <p>- Groundwater chemistry <p>- EM31 <p>- EM38 <p>- Soil gas <p>- Soil flux <p>- Airborne hyperspectral <p>- Ground hyperspectral <p>Release 3 (Oct-Dec 2013): <p>- Mobile CO2 surveys <p>- Groundwater depth <p>- Eddy covariance <p>- Plant physiology and chemistry <p>- EM31 <p>- EM38 <p>- Soil gas <p>- Soil flux <p>- Airborne hyperspectral <p>All Releases: <p>- Aerial images <p>- Groundwater depths <p>- Meteorological data <p>Bibliographic reference: <p>Feitz, A.J., Schroder, I.F., Jenkins, C.J., Schacht, U., Zegelin, S., Berko, H., McGrath, A., Noble, R., Palu, T.J., George, S., Heath, C., Zhang, H., Sirault, X. and Jimenez-Berni, J. 2016. Ginninderra Controlled CO2 Release Facility Dataset 2012-2013. eCat 90078, Geoscience Australia and CO2CRC, Canberra. https://pid.geoscience.gov.au/dataset/ga/90078. <p>Digital Object Identifier: http://dx.doi.org/10.4225/25/5823c37333f9d

Fugitive methane emissions, in particular relating to coal seam gas (CSG),has become an emerging issue in Australia over the last few years. There has been significant controversy in US regarding the magnitude of fugitive emissions during production from unconventional gas wells, with large differences in emissions reported between studies using different measurement approaches. . Preliminary research into a small number of Australia's unconventional fields suggest the average fugitive emissions per well are lower than that found in the US. The primary challenge is that the techniques for quantifying methane leakages are still at an early stage of development. Current methods for the small to medium scale use chamber based approaches or vehicles installed with fixed sampling lines and high precisions gas analysers. These technologies are promising, but generally have not been ground truthed in field conditions against known emission rates to estimate effectiveness. They also have limited application in environments where vehicle access is not possible. The Ginniderra facility is being upgraded to support a methane controlled release experiment in 2015. This will enable testing of and verifying methods and technologies for measuring and quantifying methane emissions. To address the absence of suitable techniques for emmission measurement at medium scales, several BOREAL lasers will be deployed which work at scales of 20-1000 m. It is also envisaged airborne techniques utilising laser and hyperspectral will be deployed, along with tomography work utilising multiple concurrent concentration measurements.

The Bushfire Attack Level Toolbox provides access to ArcGIS geoprocessing scripts that calculate the Bushfire Attack Level (BAL) as per Method 1 in AS3959-2009. BAL is a measure of the severity of a building's potential exposure to ember attack, radiant head and direct flame contact. It is defined in AS3959-2009 to serve as a basis for establishing the requirements for construction to improve protection of building elements from attack by bushfire. In the BAL Toolbox, the calculation method (as defined in AS3959-2009) is adapted to be applied spatially. Input information required are a digital elevation model and classified vegetation data. The BAL Toolbox allows users to calculate BAL for small regions, without the need for large computational resources or for executing code in command-line environments. This will provide stakeholders with the ability to efficiently generate rigorous and robust maps of Bushfire Attack Level that adhere to the national standard, compared to products generated by manual techniques. The BAL Toolbox code is written in Python, utilising the ArcGIS "arcpy" module to enable easy reading/writing of raster data and to provide methods for a graphical user interface in the standard ArcGIS tool style. The BAL Toolbox User Guide provides users an overview of the Toolbox, instructions on installation, any customisations execution and evaluation of results.

The local wind multiplier data for Tongatapu is used to generate local wind speeds over the island of Tongatapu, Tonga.

To provide the solar power industry with a data resource to allow them to assess the economic potential of a site for a solar power plant. Specifically under the Solar Flagship program.

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.

This dataset contains various code and outputs developed in demonstrating potential methods of generating 3-D topographic (and possibly other) multipliers for use in wind risk modelling activities. The 'wrf' folder contains output and configuration settings Chris Thomas developed in 2010 to test the feasibility of using WRF locally to derive topographic multipliers.

Not available

A metadata report for the atmospheric monitoring station installed in Arcturus, south of Emerald in central Queensland. The station was installed for baseline atmospheric monitoring to contribute to emission modelling spanning 2010-2014. The station included compositional gas analysers, supporting meteorological sensors and an eddy covariance flux tower. The metadata covered in the report include: the major variables measured by each instrument, the data duration and frequency, data accuracy, calibration and corrections, the location the data is stored, and the primary contact for the data.

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