This database contains the monthly mean and montly long term mean fields from the NCEP/NCAR Reanalysis 1960-2000. Files contain the following data: airsfc.mon.mean.nc - surface air temperature land.nc - land/sea mask slp.mon.mean.nc - sea level pressure sst.mnmean.nc - sea surface temperature (see SST_README for more details) uwnd.mon.mean.nc - U (eastward) component of wind vwnd.mon.mean.nc - V (northward) component of wind shum.mon.mean.nc - specific humidity (this file does not contain all vertical levels, unlike the other 3-d variables) For all the above, files with 'ltm' instead of 'mean' contain the long-term monthly mean data. Data were downloaded on 25/11/2009 from the Earth System Reseach Laboratory (ESRL) Physical Sciences Division (PSD) website. (http://www.esrl.noaa.gov/psd/data/gridded/reanalysis/)

The Bushfire Attack Level Toolbox provides access to ArcGIS geoprocessing scripts that calculate the Bushfire Attack Level (BAL) as per Method 1 in AS-3959 (2009). BAL is a measure of the severity of a building's potential exposure to ember attack, radiant heat and direct flame contact in the event of a bushfire. It serves as a basis for establishing the requirements for construction to improve protection of building elements from attack by bushfire. The BAL Maps and Exposure report provide maps of three communities in Western Australia, with indicative BAL levels, and the aggregate inventory of assets and population exposed to the different levels of BAL.

The Australian Solar Energy Information System V3.0 has been developed as a collaborative project between Geoscience Australia and the Bureau of Meteorology. The product provides pre-competitive spatial information for investigations into suitable locations for solar energy infrastructure. The outcome of this project will be the production of new and improved solar resource data, to be used by solar researchers and the Australian solar power industry. it is aimed to facilitate broad analysis of both physical and socio-economic data parameters which will assist the solar industry to identify regions best suited for development of solar energy generation. It also has increased the quality and availability of national coverage solar exposure data, through the improved calibration and validation of satellite based solar exposure gridded data. The project is funded by the Australian Renewable Energy Agency. The ASEIS V3.0 has a solar database of resource mapping data which records and/or map the following Solar Exposure over a large temporal range, energy networks, infrastructure, water sources and other relevant data. ASEIS V3.0 has additional solar exposure data provided by the Bureau of Meteorology. - Australian Daily Gridded Solar Exposure Data now ranges from 1990 to 2013 - Australian Monthly Solar Exposure Gridded Data now ranges from 1990 to 2013 - Australian Hourly Solar Exposure Gridded Data now ranges from 1990 to 2012 ASEIS V3.0 also has a new electricity transmission reference dataset which allows for information to be assessed on any chosen region against the distance to the closest transmission powerline.

The Australian Solar Energy Information System V2.0 has been developed as a collaborative project between Geoscience Australia and the Bureau of Meteorology. The product provides pre-competitive spatial information for investigations into suitable locations for solar energy infrastructure. The outcome of this project will be the production of new and improved solar resource data, to be used by solar researchers and the Australian solar power industry. it is aimed to facilitate broad analysis of both physical and socio-economic data parameters which will assist the solar industry to identify regions best suited for development of solar energy generation. It also has increased the quality and availability of national coverage solar exposure data, through the improved calibration and validation of satellite based solar exposure gridded data. The project is funded by the Australian Renewable Energy Agency. The ASEIS V2.0 has a solar database of resource mapping data which records and/or map the following Solar Exposure over a large temporal range, energy networks, infrastructure, water sources and other relevant data. ASEIS V2.0 has additional solar exposure data provided by the Bureau of Meteorology. - Australian Daily Gridded Solar Exposure Data now ranges from 1990 to 2012 - Australian Monthly Solar Exposure Gridded Data now ranges from 1990 to 2011 ASEIS V2.0 also has a new electricity transmission reference dataset which allows for information to be assessed on any chosen region the distance and bearing angle to the closest transmission powerline.

Results from the first pass application of the tomography technique using low accuracy sensors is presented and limitations of the sensors and technique discussed. BUll. Seismol. Soc. AM.

Following the drilling of a shallow CO2 reservoir at the Qinghai research site, west of Haidong, China, it was discovered that CO2 was continuously leaking from the wellbore due to well-failure. The site has become a useful facility in China for studying CO2 leakage and monitoring technologies for application to geological storage sites of CO2. During an eight day period in 2014, soil gas and soil flux surveys were conducted to characterise the distribution, magnitude and likely source of the leaking CO2. Two different sampling patterns were utilised during soil flux surveys. A regular sampling grid was used to spatially map out the two high flux zones which were located 20-50 m away from the wellhead. An irregular sampling grid with higher sampling density in the high flux zones, allowed for more accurate mapping of the leak distribution and estimation of total field emission rate using cubic interpolation. The total CO2 emission rate for the site was estimated at 649-1015 kgCO2/d and there appeared to be some degree of spatial correlation between observed CO2 fluxes and elevated surface H2O fluxes. Sixteen soil gas wells were installed across the field to test the real-time application of Romanak et al.'s (2012) process-based approach for soil gas measurements (using ratios of major soil gas components to identify the CO2 source) using a portable multi-gas analyser. Results clearly identified CO2 as being derived from one exogenous source, and are consistent with gas samples collected for laboratory analysis. Carbon-13 isotopes in the centre of each leak zone (-0.21 and -0.22 ) indicate the underlying CO2 is likely sourced from the thermal decomposition of marine carbonates. Surface soil mineralisation (predominantly calcite) is used to infer prior distribution of the CO2 hotspots and as a consequence highlighted plume migration of 20 m in 11 years. Detachment of the plume from the wellbore at the Qinghai research site markedly increases the area that needs surveying at sufficient density to detect a leak. This challenges the role of soil flux and soil gas in a CCS monitoring and verification program for leak detection, whereas these techniques may best be applied for characterising source and emission rate of a CO2 leak.

Tropical cyclones are the most common disaster in the Pacific, and among the most destructive. In December 2012, Cyclone Evan caused over US$200 million damage in Samoa, nearly 30 percent of Samoan GDP. Niue suffered losses of US$85 million following Cyclone Heta in 2004-over five times its GDP. As recently as January 2014, Cyclone Ian caused significant damage throughout Tonga, resulting in the first payout of the Pacific Catastrophe Risk Insurance Pilot system operated by the World Bank (2014). According to the Intergovernmental Panel on Climate Change (IPCC), intense tropical cyclone activity in the Pacific basin will likely increase in the future (IPCC 2013). But such general statements about global tropical cyclone activity provide little guidance on how impacts may change locally or even regionally, and thus do little to help communities and nations prepare appropriate adaptation measures. This study assesses climate change in terms of impact on the human population and its assets, expressed in terms of financial loss. An impact focus is relevant to adaptation because changes in hazard do not necessarily result in a proportional change in impact. This is because impacts are driven by exposure and vulnerability as well as by hazard. For example, a small shift in hazard in a densely populated area may have more significant consequences than a bigger change in an unpopulated area. Analogously, a dense population that has a low vulnerability to a particular hazard might not need to adapt significantly to a change in hazard. Even in regions with high tropical cyclone risk and correspondingly stringent building codes, such as the state of Florida, a modest 1 percent increase in wind speeds can result in a 5 percent to 10 percent increase in loss to residential property. Quantifying the change impact thus supports evidence-based decision making on adaptation to future climate risk.

Natural hazard data supports the nation to respond effectively to emergencies, reduce the threat natural hazards pose to Australia¿s national interests and address issues relating to community safety, urban development, building design, climate change and insurance. A baseline understanding of hazards, impacts and risk can help to enhance community resilience to extreme events and a changing environment. Probabilistic hazard and risk information provides planners and designers opportunity to investigate the cost and benefit of policy options to mitigate natural hazard impacts. Modelled disaster scenario information can enable disaggregation of probabilistic hazard to identify the most probable event contributing to hazard. Tropical cyclone return period wind hazard maps developed using the Tropical Cyclone Risk Model. The hazard maps are derived from a catalogue of synthetic tropical cyclone events representing 10,000 years of activity. Annual maxima are evaluated from the catalogue and used to fit a generalised extreme value distribution at each grid point. Wind multipliers are factors that transform regional wind speed to local wind speed, mathematically describing the influences of terrain, shielding and topographic effects. Local wind speeds are critical to wind-related activities that include hazard and risk assessment. The complete dataset is comprised of: - Stochastic tracks, wind fields and impact data; - Probabilistic wind speed data (hazard); - Site-exposure wind multipliers.

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No abstract available