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    The project brought together a group of Australian researchers and managers with a broad range of expertise to identify current and emerging economies (‘drivers’) affecting regional agricultural landscapes and to suggest beneficial transformational changes for successful adaptation. A key challenge in these landscapes is altering how we use the land for ongoing, viable production while increasing native biodiversity. The group:<ul style="list-style-type: disc;"> <li>identified the major historical influences on Australian land use and the current social and economic drivers that are likely to increase in the future</li> <li>assessed the condition of five agro-climatic regions (adapted from Williams et al., 2002 and Hobbs and McIntyre, 2005) using a Delphi method. A small (4-person) expert panel scored the impact of historical and future scenarios on ten sustainability indicators (biodiversity, water, soil, social capital, built capital, food/fibre, carbon, energy, minerals and cultural). Five regions were chosen: Southern Mediterranean, Northern tropical, Central arid, North-east subtropical, and South-east temperate. This was an iterative process whereby scores were revisited until internal consistency between regions, scenarios, and indicators was achieved</li> <li>made projections of regional condition under the four global Representative Concentration Pathways (RCPs) based on van Vuuren et al. (2011)</li> <li>developed recommendations about land use and management, institutional and policy arrangements and social processes that will assist adaptation towards a values-rich vision of Australia in 2100.</li></ul>

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    Heatwaves are defined as unusually high temperature events that occur for at least three consecutive days with major impacts to human health, economy, agriculture and ecosystems. This dataset provides time-series of heatwave characteristics such as peak temperature, number of events, frequency and duration from 1950 to 2016 in Australia. The analysis were based on daily minimum and maximum temperature obtained from the Australian Water Availability Project (AWAP). The data is available as spatial time-series (5km grid-cell) and aggregated time-series for all Local Government Areas in Australia.

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    Dynamically downscaled high-resolution (~10 km spatial resolution) climate change projection data for Queensland. Downscaling was completed using CSIRO Conformal Cubic Atmospheric Model (CCAM) for two RCPs (RCP4.5 and RCP8.5) from 11 CMIP5 global coarse resolution models for period 1980-2099. The Queensland Future Climate Dashboard (www.longpaddock.qld.gov.au/qld-future-climate/ ) provides easy access to climate projection for Queensland. The dashboard allows users to explore, visualize and download the latest high-resolution climate modelling data for specific regions, catchments, disaster areas, local government areas and grid squares. Underlying data is provided via TERN for easy access for each of 11 downscaled models. The Queensland Future Climate Dataset provides high resolution data for over 30 different metrics grouped in six climate themes: (i) Mean Climate; (ii) Heatwaves; (iii) Extreme Temperature Indices; (iv) Extreme Precipitation Indices; (v) Droughts; and (vi) Floods. In addition selected variables at daily and monthly intervals are also available.