Application-ready quantile-delta-change (QDC) scaled CMIP6 climate projections for Australia (time-slices, 5km grid)

This collection consists of application-ready climate projections based on observations, adjusted through a quantile-delta-change method to incorporate projected climate changes from CMIP6 Global Climate Models.\n\nThe collection consists of daily projections of precipitation, mean downwelling shortwave radiation, maximum and minimum near-surface temperature, maximum, mean and minimum near-surface relative humidity, and mean near-surface wind speed for 9 CMIP6 models. Two 30-year windows of projections are available (2035-2064 and 2070-2099) for four shared socio-economic pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5). Data is available with two sources of historic climate observations for Australia: AGCD (for precipitation and temperature only) and BARRA-R2. The BARRA-R2 baseline data has been interpolated to the same resolution as AGCD (~5km).\n\nIn addition, historical baseline data for 1985-2014 from AGCD and BARRA-R2 used for the quantile-delta-change adjustment are also available in the collection.\n\nMore in-depth information on the dataset can be found in the technical report: https://doi.org/10.25919/03by-9y62\n\nThis collection is not updated frequently.\nLineage: Daily data from 9 CMIP6 models (ACCESS-CM2, ACCESS-ESM1-5, CESM2, CMCC-ESM2, CNRM-ESM2-1, EC-Earth3, MPI-ESM1-2-HR, NorESM2-MM, UKESM1-0-LL) are used to calculate climate changes between a 1985-2014 baseline period and the two future projection periods for each SSP. The projected changes are then applied to 1985-2014 baseline data from AGCD and BARRA-R2 to produce the application-ready datasets. The quantile-delta-change method is used, which applies different climate changes to different parts (quantiles) of the distribution of daily data.\n\nThis process is done using python software available at https://github.com/AusClimateService/qq-workflows/tree/main/qdc-cmip6.\n\nMore in-depth information on the method can be found in the technical report: https://doi.org/10.25919/03by-9y62\n\nThe application-ready projections have also been subject to a quality-control and assurance check utilising a python script (https://github.com/climate-innovation-hub/qdc-cmip6-qaqc) to ensure full data coverage and compliance with metadata standards, with the process documented in the QAQC report: https://doi.org/10.25919%2F4n26-fh08