From Queensland Government
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Consistent Climate Scenarios

Created 04/05/2025

Updated 04/05/2025

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Consistent Climate Scenarios (CCS) data are daily climate projections data for Australian locations for years centred on 2030 and 2050. The data have been developed by adjusting SILO historical climate data according to AR4 based climate projections for 2030 and 2050. Since mid-2012, CCS data have been freely provided to registered users through a portal on the Queensland Government's Long Paddock website. CCS data are unique, in that they: - maintain 'weather-like' properties for a range of climate variables (rainfall, evaporation, minimum and maximum temperature, solar radiation and vapour pressure deficit), - are available for more than 4500 climate stations across Australia, or for individual grid points on a 0.05 degree (approximately 5 km) grid across Australia and - are provided in 'ready to use' formats, suitable for input to biophysical models (such as GRASP and APSIM). The development of the CCS Data was funded by the Commonwealth Department of Agriculture, Fisheries and Forestry (DAFF) through its Australia's Farming Future Climate Change Research Program. While the CCS web portal currently provides AR4 based projections data, AR5 based projections data may be included at a future date.

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Additional Info

Field Value
Title Consistent Climate Scenarios
Language English
Licence cc-by-4
Landing Page https://devweb.dga.links.com.au/data/dataset/5b6cb17c-6706-416b-a951-e8dfcf6901ee
Remote Last Updated 20/06/2022
Contact Point
Environment, Tourism, Science and Innovation
opendata@des.qld.gov.au
Reference Period 27/05/2015
Geospatial Coverage {"type": "Polygon", "coordinates": [[ [96.0,-45.0],[96.0,-9.0], [168.0,-9.0], [168.0,-45.0], [96.0,-45.0]]]}
Data Portal data.gov.au

Data Source

This dataset was originally found on Queensland Government "Consistent Climate Scenarios". Please visit the source to access the original metadata of the dataset:
https://data.qld.gov.au/dataset/consistent-climate-scenarios

Original dataset
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No duplicate datasets found.