Application-ready quantile-delta-change (QDC) scaled CMIP6 climate projections for Australia (time slices, 11km 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 based on BARRA-R2 historic climate variability for Australia. This dataset is on the original 11km BARRA-R2 resolution.\n\nIn addition, historical baseline data for 1985-2014 from 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 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

本数据集集合包含基于观测数据构建的可直接应用的气候预估产品，该产品通过分位数-增量变化法（quantile-delta-change）进行校正，融合了第六次耦合模式比较计划（Coupled Model Intercomparison Project Phase 6, CMIP6）全球气候模式的预估气候变化信号。

该数据集集合包含9个CMIP6模式的逐日预估数据，涵盖降水量、平均下行短波辐射、近地面最高与最低气温、近地面相对湿度的最大、平均及最小值，以及近地面平均风速。针对4种共享社会经济路径（Shared Socioeconomic Pathways, SSP）：SSP1-2.6、SSP2-4.5、SSP3-7.0及SSP5-8.5，提供两个30年预估时段的结果：2035-2064年与2070-2099年。数据基于澳大利亚区域高分辨率大气再分析数据集第二版（Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia version 2, BARRA-R2）的历史气候变率场，且保留了其原始的11公里分辨率。

此外，数据集集合中还提供了用于分位数-增量变化法校正的1985-2014年BARRA-R2历史基准期数据。

更多关于本数据集的详细信息可参阅技术报告：https://doi.org/10.25919/03by-9y62

本数据集集合更新频率较低。

数据溯源流程如下：选取9个CMIP6模式（ACCESS-CM2、ACCESS-ESM1-5、CESM2、CMCC-ESM2、CNRM-ESM2-1、EC-Earth3、MPI-ESM1-2-HR、NorESM2-MM、UKESM1-0-LL）的逐日数据，计算1985-2014年基准期与两个未来预估时段间，各共享社会经济路径对应的气候变化信号；随后将该预估变化信号应用于BARRA-R2的1985-2014年基准期数据，生成可直接应用的数据集。本次校正采用分位数-增量变化法，该方法可针对逐日数据分布的不同分位区间应用差异化的气候变化校正信号。

本处理流程通过公开的Python软件实现，代码仓库地址为：https://github.com/AusClimateService/qq-workflows/tree/main/qdc-cmip6。

更多关于该方法的详细信息可参阅前述技术报告：https://doi.org/10.25919/03by-9y62。

可直接应用的预估产品还通过Python脚本（代码仓库地址：https://github.com/climate-innovation-hub/qdc-cmip6-qaqc）完成了质量控制与质量保证校验，以确保数据覆盖完整且符合元数据标准，相关流程记录于质量控制报告：https://doi.org/10.25919%2F4n26-fh08。