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CSIRO Dawn to 2100 SRESA2 huss - GCM Specific Humidity datasets and trends 1850 to 2100 using the SRESA2 Scenario

Created 24/06/2017

Updated 24/06/2017

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The CSIRO Dawn-2100 archive contains datasets for atmospheric, land and oceanographic variables for the approximate period 1850 - 2100 (dependent on model). These have been created through the concatenation of 20th century (20C3M) and other scenario (currently SRESA1B or SRESA2) data from a number of the 25 differant global climate models (GCM) from various countries. The SRESA2_huss dataset contains the Specific Humidity variable for various GCM's and runs (multiple runs being averaged to a single file if existing) under the scenario SRESA2 emissions 2001 to 2100. These variables have also been further analysed to give monthly, seasonal and annual trend data, calculated from a monthly timeseries referenced to the area-weighted mean global warming values. 8 GCM models are available with data for variables being in 12 month, annual and 4 seasons(DJF, MAM,JJA,SON) format with 20 files totaling 2.94 GB as Netcdf files. Available for internal use and analysis by CSIRO staff on the HPSC cherax.

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Title CSIRO Dawn to 2100 SRESA2 huss - GCM Specific Humidity datasets and trends 1850 to 2100 using the SRESA2 Scenario
Language English
Licence Other
Landing Page https://devweb.dga.links.com.au/data/dataset/77710ef2-dccc-4484-8ce4-486e290b1a7c
Contact Point
CSIRO Oceans and Atmosphere - Information and Data Centre
data-requests-hf@csiro.au
Geospatial Coverage {"type": "Polygon", "coordinates": [[[-180.0, -90.0], [180.0, -90.0], [180.0, 90.0], [-180.0, 90.0], [-180.0, -90.0]]]}
Data Portal data.gov.au

Data Source

This dataset was originally found on data.gov.au "CSIRO Dawn to 2100 SRESA2 huss - GCM Specific Humidity datasets and trends 1850 to 2100 using the SRESA2 Scenario". Please visit the source to access the original metadata of the dataset:
https://devweb.dga.links.com.au/data/dataset/csiro-dawn-to-2100-sresa2-huss-gcm-specific-humidity-datasets-and-trends-1850-to-2100-using-the

Original dataset
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No duplicate datasets found.