Weather radar data provided by the Bureau of Meteorology for initial investigation into thunderstorm tracking and analysis applications

The CO2CRC has been leading the international development and application of atmospheric techniques for CO2 leak detection and quantification for CCS. CSIRO's atmospheric monitoring program at the CO2CRC Otway Project demonstrated world's leading practice for atmospheric monitoring at geological storage sites. The GA-CO2CRC Ginninderra controlled release facility has enabled development and testing of a new atmospheric tomography approach for accurately quantifying CO2 emissions using atmospheric techniques. A scaled-up version of the technique using an array of more cost effective (but less accurate) sensors was applied at a larger scale at the Otway Stage 2B controlled release. Additional techniques have been developed including data filtering to optimize the detection of emitted gases against the ecosystem background and Bayesian inverse modeling to locate and quantify a source. GA and CSIRO operate a joint baseline atmospheric station in the Bowen Basin and have been independently investigating the sensitivity of CO2 leak detection through coupling of measurements taken in a sub-tropical environment with simulated leakage events. An outcome from this body of work is the importance of good quality, calibrated measurements, a long baseline record and the development and application of techniques using atmospheric models for quantifying gaseous emissions from the ground to the atmosphere. These same measurement requirements and quantification techniques have direct application to fugitive methane emissions from open cut coal mines, coal seam gas, tight gas, and conventional gas emissions. Application is easier for methane: the background signal is lower, sensors are available at affordable cost, and the emissions are measureable now. The Bowen Basin site, for example, is detecting fugitive methane emitted from open cut coal mining activities tens of kilometres away. An example of the sensitivity of atmospheric techniques for the detection of fugitive emissions from a simulated methane source will be presented.

Lagrangian stochastic (LS) forward modelling of CO2 plumes from above-surface release experiments conducted at the GA-CO2CRC Ginninderra GHG controlled release facility demonstrated that small surface leaks are likely to disperse rapidly and unlikely to be detected at heights greater 4 m; this was verified using a rotorcraft to map out the plume. The CO2 sensing rotorcraft unmanned aerial vehicle (RUAV) developed at the Australian National University, Canberra, is equipped with a CO2 sensor (3 ppm accuracy and 2 s response time), a GPS, lidar and a communication module. It was developed to detect, locate and quantify CO2 gas leaks. The choice of a rotorcraft UAV allows slower flight speeds compared to speeds of a fixed-wing UAV; and the electric powered motor enables flight times of 12 min. During the experiments, gaseous CO2 (100 kg per day) was released from a small diffuse source located in the middle of the paddock of the controlled release facility, and the RUAV, flying repeatedly over the CO2 source at a few metres height, recorded CO2 concentrations up to 85 ppm above background. Meteorological parameters measured continuously at the site were input in the LS model. Mapped out horizontal and vertical CO2 concentrations established the need to be close to the ground in order to detect CO2 leakage using aerial techniques. Using the rotorcraft as a mobile sensor could be an expedient mechanism to detect plumes over large areas, and would be important for early detection of CO2 leaks arising from CO2 geological storage activities.

Global solar exposure is the total amount of solar energy falling on a horizontal surface. The hourly global solar exposure is the total solar energy for one hour. Typical values for hourly global exposure range up to 4 MJ/m2 (megajoules per square metre). The values are usually highest in the middle of the day and around summer, with localised variations caused mainly by variations in atmospheric conditions, primarily cloudiness. See metadata statement for more information.

Source The data was sourced from CSIRO (Victoria) in 2012 by Bob Cechet. It is not known specifically which division of CSIRO, although it is likely to have been the Marine and Atmospheric Research Division (Aspendale), nor the contact details of the person who provided the data to Bob. The data was originally produced by CSIRO for their input into the South-East Queensland Climate Adaptation Research Initiative (SEQCARI). Reference, from an email of 16 March 2012 sent from Bob Cechet to Chris Thomas (Appendix 1 of the README doc stored at the parent folder level with the data), is made to 'download NCEP AVN/GFS files' or to source them from the CSIRO archive. Content The data is compressed into 'tar' files. The name content is separated by a dot where the first section is the climatic variable as outlined in the table format below: Name Translation rain 24 hr accumulated precipitation rh1_3PM Relative humidity at 3pm local time tmax Maximum temperature tmin Minimum temperature tscr_3PM Screen temperature (2 m above ground) at 3pm local time u10_3PM 10-metre above ground eastward wind speed at 3pm local time v10_3PM 10-metre above ground northward wind speed at 3pm local time The second part of the name is the General Circulation Model (GCM) applied: Name Translation gfdlcm21 GFDL CM2.1 miroc3_2_medres MIROC 3.2 (medres) mpi_echam5 MPI ECHAM5 ncep NCEP The third, and final, part of the tarball name is the year range that the results relate to: 1961-2000, 1971-2000, 2001-2040 and 2041-2099 Data format and extent Inside each of the tarball files is a collection of NetCDF files covering each simulation that constitutes the year range (12 simulations for each year). A similar naming protocol is used for the NetCDF files with a two digit extension added to the year for each of the simulations for that year (e.g 01-12). The spatial coverage of the NetCDF files is shown in the bounding box extents as shown below. Max X: -9.92459297180176 Min X: -50.0749073028564 Max Y: 155.149784088135 Min Y: 134.924812316895 The cell size is 0.15 degrees by 0.15 degrees (approximately 17 km square at the equator) The data is stored relative to the WGS 1984 Geographic Coordinate System. The GCMs were forced with the Intergovernmental Panel on Climate Change (IPCC) A2 emission scenario as described in the IPCC Special Report on Emissions Scenarios (SRES) inputs for the future climate. The GCM results were then downscaled from a 2 degree cell resolution by CSIRO using their Cubic Conformal Atmospheric Model (CCAM) to the 0.15 degree cell resolution. Use This data was used within the Rockhampton Project to identify the future climate changes based on the IPCC A2 SRES emissions scenario. The relative difference of the current climate GCM results to the future climate results was applied to the results of higher resolution current climate natural hazard modelling. Refer to GeoCat # 75085 for the details relating to the report and the 59 attached ANZLIC metadata entries for data outputs.

We have developed an autonomous CO2 monitoring station, based around the Vaisala GMP343 sensor. The station is powered by a solar panel and incorporates a data logger and a directional antenna for line-of-sight wireless communication with a base station. The base station communicates via the Telstra mobile phone data network. The concept of atmospheric tomography was tested at the Ginninderra site and proved very successful as a method of locating and quantifying a spatially small release of CO2. In this case the sensors were separated from the source by 40 m. The opportunity to test the method over a larger distance arose during the controlled release of Buttress gas during the stage 2B experiment at the Otway site. Gas was released at 8 tpd during daylight hours, and an approximate ring of 8 monitoring stations was deployed around the release point; the ring was about 800 m in diameter. Gas was released on 12 occasions, chosen to match wind directions that would carry the plume in the direction of one of the sensors. The dataset was too limited to carry out the full-scale Bayesian inversion that was demonstrated in the Ginninderra test (which lasted two months) but a simple inversion was possible. This located the source of the release correctly to within 20 m. The test demonstrated that inexpensive sensors could achieve enough stability and sensitivity to work (in this particular application) at the few ppm level. Moreover quite simple dispersion models could be used to predict plume geometry up to 500 m from the release. Overall the experiment indicates the basis of an inexpensive method for remotely monitoring areas of around a km2 for spatially small leakages.

To determine the magnitude of severe wind gust hazard due to thunderstorm downbursts using regional climate model output and analysis of observed data (including radar reflectivity and proximity soundings).

Modelling tropical cyclone Yasi using TCRM

The world's first satellite-derived mineral maps of a continent, namely Australia, are now publicly available as digital, web-accessible products. The value of this spatially comprehensive mineral information is readily being captured by explorers at terrane to prospect scales. However, potentially even greater benefits can ensue for environmental applications, especially for the Earth's extensive drylands which generate nearly 50% of the world's agricultural production but are most at risk to climate change and poor land management. Here we show how these satellite mineral maps can be used to: characterise soil types; define the extent of deserts; fingerprint sources of dust; measure the REDOX of iron minerals as a potential marine input; and monitor the process of desertification. We propose a 'Mineral Desertification Index' that can be applied to all Earth's drylands where the agriculturally productive clay mineral component is being lost by erosion. Mineral information is fundamental to understanding geology and is important for resource applications1. Minerals are also a fundamental component of soils2 as well as dust eroded from the land surface, which can potentially impact on human health3, the marine environment4 and climate5. Importantly, minerals are well exposed in the world's 'drylands', which account for nearly 50% of Earth's land area6. Here, vegetation cover is sparse to non-existent as a result of low rainfall (P) and high evaporation (E) rates (P/E<0.65). However, drylands support 50% of the world's livestock production and almost half of all cultivated systems6. In Australia, drylands cover 85% of the continent and account for 50% of its beef, 80% of its sheep and 93% of its grain production7. Like other parts of the world, Australia is facing serious desertification of its drylands6. Wind, overgrazing and overstocking are major factors in the desertification process8. That is, the agriculturally productive clay-size fraction of soils (often includes organic carbon) is lost largely through wind erosion, which is acerbated by the loss of any vegetative groundcover (typically dry plant materials). Once clay (and carbon) loss begins, then the related break down of the soil structure and loss of its water holding capacity increases the rate of the degeneration process with the final end products being either exposed rock or quartz sands that often concentrate in deserts.

Global solar exposure is the total amount of solar energy falling on a horizontal surface. The daily global solar exposure is the total solar energy for a day. Typical values for daily global exposure range from 1 to 35 MJ/m2 (megajoules per square metre). For mid-latitudes, the values are usually highest in clear sun conditions during the summer, and lowest during winter or very cloudy days. The monthly means are derived from the daily global solar exposure. See metadata statement for more information.