Abstract
The collaboration between the Coordinated Regional Climate Downscaling Experiment (CORDEX) and the Earth System Grid Federation (ESGF) provides open access to an unprecedented ensemble of regional climate model (RCM) simulations, across the 14 CORDEX continental-scale domains, with global coverage. These simulations have been used as a new line of evidence to assess regional climate projections in the latest contribution of the Working Group I (WGI) to the IPCC Sixth Assessment Report (AR6), particularly in the regional chapters and the Atlas. Here, we present the work done in the framework of the Copernicus Climate Change Service (C3S) to assemble a consistent worldwide CORDEX grand ensemble, aligned with the deadlines and activities of IPCC AR6. This work addressed the uneven and heterogeneous availability of CORDEX ESGF data by supporting publication in CORDEX domains with few archived simulations and performing quality control. It also addressed the lack of comprehensive documentation by compiling information from all contributing regional models, allowing for an informed use of data. In addition to presenting the worldwide CORDEX dataset, we assess here its consistency for precipitation and temperature by comparing climate change signals in regions with overlapping CORDEX domains, obtaining overall coincident regional climate change signals. The C3S CORDEX dataset has been used for the assessment of regional climate change in the IPCC AR6 (and for the interactive Atlas) and is available through the Copernicus Climate Data Store (CDS).
Original language | English |
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Pages (from-to) | E2804-E2826 |
Journal | Bulletin of the American Meteorological Society |
Volume | 103 |
Issue number | 12 |
DOIs | |
State | Published - 2022 |
Funding
This work has been funded by the Copernicus Climate Change Service, implemented by ECMWF on behalf of the European Commission. JF and ASC acknowledge project CORDyS (PID2020-116595RB-I00) funded by MCIN/AEI/10.13039/501100011033. JMG and MI acknowledge project ATLAS (PID2019-111481RB-I00) funded by MCIN/AEI/10.13039/501100011033. ASC and EC acknowledge Project IS-ENES3 which is funded by the European Union's Horizon 2020 research and innovation programme under Grant Agreement 824084. JM acknowledges the support from the Spanish Agencia Estatal de Investigación through the Unidad de Excelencia María de Maeztu with Reference MDM-2017-0765. MED acknowledges the Partnership for advanced computing in Europe (PRACE) for awarding access to Piz Daint at ETH Zürich/Swiss National Supercomputing Centre (Switzerland), as well as the Federal Office for Meteorology and Climatology MeteoSwiss, the Swiss National Supercomputing Centre (CSCS), and ETH Zürich for their contributions to the development of the GPU-accelerated version of COSMO, COSMO-crCLIM. Acknowledgments. This work has been funded by the Copernicus Climate Change Service, implemented by ECMWF on behalf of the European Commission. JF and ASC acknowledge project CORDyS (PID2020-116595RB-I00) funded by MCIN/AEI/10.13039/501100011033. JMG and MI acknowledge project ATLAS (PID2019-111481RB-I00) funded by MCIN/AEI/10.13039/501100011033. ASC and EC acknowledge Project IS-ENES3 which is funded by the European Union’s Horizon 2020 research and innovation programme under Grant Agreement 824084. JM acknowledges the support from the Spanish Agencia Estatal de Investigación through the Unidad de Excelencia María de Maeztu with Reference MDM-2017-0765. MED acknowledges the Partnership for advanced computing in Europe (PRACE) for awarding access to Piz Daint at ETH Zürich/Swiss National Supercomputing Centre (Switzerland), as well as the Federal Office for Meteorology and Climatology MeteoSwiss, the Swiss National Supercomputing Centre (CSCS), and ETH Zürich for their contributions to the development of the GPU-accelerated version of COSMO, COSMO-crCLIM.
Keywords
- Climate change
- Climate services
- Data quality control
- Downscaling
- Ensembles
- Regional models