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.

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.

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.

Queensland Fire and Emergency Services are leading the development of consistent risk information relating to the potential impacts of disasters across Queensland. The stated aim is to ensure all local, district and state government stakeholders have access to the same information to guide risk-based planning in the preparation for natural disasters. This extends to future projections natural hazard activity, including tropical cyclones (TC), in the Queensland region. To achieve this last objective, Queensland’s Department of Environment and Science (DES) have undertaken a program of regional climate simulations, with a view to informing long-term planning decisions. When it comes to TCs – a major cause of disasters in Queensland – many of the stakeholders want to answer the question: “How many severe tropical cyclones will the future hold for us?”, or similar questions around the likelihood of TC occurrence. To answer this, DES and Geoscience Australia are interrogating the regional climate simulations to extract Tropical Cyclone-Like Vortices (TCLVs). The behaviour of these TCLVs is then analysed to understand changes in frequency, intensity and spatial distribution. The TCLVs – with some additional bias corrections - can also be used as input to stochastic models that can provide probabilistic wind hazard information across the entire state of Queensland. In this paper we demonstrate the challenges of extracting TCLVs from regional climate models and the bias corrections required to make useful projections of TC activity into the future. Abstract presented at the 2020 Australian Meteorological and Oceanographic Society 2020 National Conference (http://amos-2020.w.amos.currinda.com/)

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.

Hourly direct normal solar exposure is the total amount of direct beam solar energy falling over one hour on a surface whose orientation is maintained perpendicular to the solar beam. Typical values for hourly direct normal exposure range up to around 3 MJ/m2 (megajoules per square metre). The values are usually highest in clear skies and decrease rapidly with increasing cloudiness, and also decrease to a lesser extent with increasing haziness and decreasing solar elevation. 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 the winter or very cloudy days. See LINEAGE below for more information.

Wind multipliers are factors that transform regional wind speeds to local wind speeds considering local effects of land cover and topographic influences. It includes terrain, shielding, topographic and direction multipliers. Except for the direction multiplier whose value can be defined specifically by the Australian wind loading standard AS/NZS 1170.2, terrain, shielding and topographic multipliers are calculated using this software package based on the adaptations of formulae outlined in the AS/NZS 1170.2. This package is an upgraded version of wind multiplier computation software (<a href="https://pid.geoscience.gov.au/dataset/ga/82481">eCat 82481</a>) used to produce wind terrain, shielding and topographic multipliers for national coverage using an input of Land Cover Classification Scheme (LCCS) level 4 version 1.0.0 ( 2015) and 1-second SRTM level 2 derived digital elevation models (DEM-S) version 1.0. In order to improve the classification resolution in the built environment, the LCCS layer is overlaid with both mesh block and settlement types. The output is based on tiles with dimensions about 1 by 1 decimal degree in netCDF format. It includes terrain, shielding and topographic multiplier respectively. Each multiplier further contains 8 directions. The upgraded package is stored in Geoscience Australia public-facing repository and can be accessed via https://github.com/GeoscienceAustralia/Wind_Multipliers

<div>An automatic algorithm for classifying wind gust events has been developed at Geoscience Australia, utilizing 1-minute weather observations from Automatic Weather Stations (AWS). This algorithm employs a comprehensive dataset of wind, temperature, dew point, and pressure measurements within a two-hour timeframe centred on the peak wind gust.&nbsp;&nbsp;</div><div> The classification methodology effectively segregates wind gust events into convective and non-convective categories. Initial development entails a subset of stations, employing visual classification verified by contemporaneous observer reports and weather radar data, to create a robust training dataset. The algorithm, based on the analysis of almost 1000 visually-classified events, demonstrates the capability to classify over 150,000 events in a matter of minutes.&nbsp;</div><div> Utilizing wind gust events from past 20 years via our algorithm, the spatial distribution, diurnal cycle and seasonal variation are investigated across Australia. Moreover, a comparative analysis of spatial and temporal disparities, along with radar characteristics, has been conducted for convective and non-convective gust events. Finally, the extreme values of wind gust events, including the 1% annual exceedance probability wind speed (using the Generalized Pareto Distribution) across Australia is shown in this presentation. &nbsp;</div> Presented at the 30th Conference of the Australian Meteorological and Oceanographic Society (AMOS) 2024

<div>The Severe Wind Hazard Assessment for Queensland arose as a project to better understand the potential impacts of tropical cyclones (TCs) on population centres and elements of critical infrastructure in Queensland. The rationale for the project was reinforced by lessons from Severe Tropical Cyclone (STC) Debbie, the direct and indirect impacts of which affected a significant area of Queensland, stretching from Bowen to the City of Gold Coast and Northern New South Wales between 28 March and 7 April 2017, resulting in 14 mostly flood associated deaths, and more than A$3.5 billion in direct losses. The intent of the project is to explore and assess a range of scenarios that extend beyond the contemporary recollection of severe events in order to challenge decision making for rarer but higher-consequence events. The scenarios described in the report can be used to improve planning for severe tropical cyclone (TC) events and their impacts. This includes developing a better understanding of how the capabilities of emergency services and supporting elements may be impacted in actual events.&nbsp;</div><div><br></div><div>Scenarios were selected from the catalogue of synthetic events (i.e. events that did not actually occur but whose occurrence was as probable as those that did occur) generated for the 2018 Tropical Cyclone Hazard Assessment (TCHA; Arthur, 2018), in consultation with Queensland Fire and Emergency Services (QFES) and those local governments involved within the project. Two TC events were modelled for each location for this project – a Category 3 and a Category 5 TC -with ‘favourable’ tracks for impact analysis. In all scenarios, consideration was given to regional historical analogues for the selected synthetic tracks to better relate the scenario outputs to known or “lived” events. These categories were chosen as they represent events with a moderate and very low likelihood with respect to intensity, based on historical observations. This also accounts for the future climate of less TCs but more intense occurrences, highlighting the different impacts arising from different events. It is important to emphasise and understand that each individual TC event will be different and lead to different impacts.&nbsp;</div><div><br></div>

Using the new release of the local wind multipliers software (V.3.1) (<a href="https://pid.geoscience.gov.au/dataset/ga/145699">eCat 145699</a>) and an appropriate source of classified terrain data, local wind multipliers on a national scale for the whole continent of Australia at (approximately) 25-metre resolution were calculated. This product is a necessary component for calculating local wind speeds from scenarios and guiding impact assessment of severe wind hazards for both federal and state-wide Emergency Services in Australia.