CMIP6 ScenarioMIP CNRM-CERFACS CNRM-CM6-1-HR ssp585 r1i1p1f2 Amon pr gr v20191202

Voldoire, Aurore

Dataset
Summary
[ Derived from parent entry - See data hierarchy tab ]

These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.ScenarioMIP.CNRM-CERFACS.CNRM-CM6-1-HR.ssp585' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The CNRM-CM6-1-HR climate model, released in 2017, includes the following components: aerosol: prescribed monthly fields computed by TACTIC_v2 scheme, atmos: Arpege 6.3 (T359; Gaussian Reduced with 181724 grid points in total distributed over 360 latitude circles (with 720 grid points per latitude circle between 32.2degN and 32.2degS reducing to 18 grid points per latitude circle at 89.6degN and 89.6degS); 91 levels; top level 78.4 km), atmosChem: OZL_v2, land: Surfex 8.0c, ocean: Nemo 3.6 (eORCA025, tripolar primarily 1/4deg; 1442 x 1050 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: Gelato 6.1. The model was run by the CNRM (Centre National de Recherches Meteorologiques, Toulouse 31057, France), CERFACS (Centre Europeen de Recherche et de Formation Avancee en Calcul Scientifique, Toulouse 31057, France) (CNRM-CERFACS) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, atmosChem: 100 km, land: 100 km, ocean: 25 km, seaIce: 25 km.
Project
IPCC-AR6_CMIP6 (Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets)
Location(s)
global
Spatial Coverage
Longitude 0 to 360 Latitude -90 to 90
Temporal Coverage
2015-01-16 to 2100-12-16 (gregorian)
Use constraints
Creative Commons Attribution 4.0 International (CC BY 4.0) (https://creativecommons.org/licenses/by/4.0/)
Data Catalog
World Data Center for Climate
Access constraints
registered users
Size
735.44 MiB (771165991 Byte)
Format
NetCDF
Status
completely archived
Creation Date
Future Review Date
2032-12-02
Download Permission
Please login to check permission and download options
Cite as
[ Derived from parent entry - See data hierarchy tab ]
Voldoire, Aurore (2023). IPCC DDC: CNRM-CERFACS CNRM-CM6-1-HR model output prepared for CMIP6 ScenarioMIP ssp585. World Data Center for Climate (WDCC) at DKRZ. https://doi.org/10.26050/WDCC/AR6.C6SPCECC2s585

BibTeX RIS
VariableCodeAggregationUnit
precipitation_fluxCF
pr (IPCC_DDC_AR6: 780)
monkg m-2 s-1

Is referenced by

[1] DOI IPCC Data Distribution Centre. (2025). CMIP6 input data usage information for IPCC WGI AR6 figure 10.19. doi:10.5281/zenodo.14986314
[2] DOI IPCC Data Distribution Centre. (2025). CMIP6 input data usage information for IPCC WGI AR6 figure 4.32. doi:10.5281/zenodo.14986437
[3] DOI IPCC Data Distribution Centre. (2025). CMIP6 input data usage information for IPCC WGI AR6 figure 4.42. doi:10.5281/zenodo.14986441
[4] DOI IPCC Data Distribution Centre. (2025). CMIP6 input data usage information for IPCC WGI AR6 figure 8.13. doi:10.5281/zenodo.14986453
[5] DOI IPCC Data Distribution Centre. (2025). CMIP6 input data usage information for IPCC WGI AR6 figure 8.16. doi:10.5281/zenodo.14986462

Is source of

[1] IPCC. (2023). Cross-Chapter Box 11.1, Figure 3 | Illustration of the AR6 global warming level (GWL) sampling approach to derive the timing and the response at a given GWL for the case of Coupled Model Intercomparison Project Phase 6 (CMIP6) data. In IPCC, 2023: Chapter 11. https://www.ipcc.ch/report/ar6/wg1/figures/chapter-11/ccbox-11-1-figure-3
[2] IPCC. (2023). Figure 8.13 | Zonal and annual-mean projected long-term changes in the atmospheric water budget. In IPCC, 2023: Chapter 8. https://www.ipcc.ch/report/ar6/wg1/figures/chapter-8/figure-8-13
[3] IPCC. (2023). Figure 8.16 | Rate of change in components of water cycle mean and variability across increasing global warming levels. In IPCC, 2023: Chapter 8. https://www.ipcc.ch/report/ar6/wg1/figures/chapter-8/figure-8-16
[4] IPCC. (2023). Table 8.1 | Global and global land annual mean water cycle projections in the mid-term (2041–2060) and long term (2081–2100) relative to present day (1995–2014), showing present day mean and 90% confidence range across CMIP6 models (historical experiment) and projected mean changes and the 90% confidence range across the same set of models and a range of Shared Socio-economic Pathway scenarios. In IPCC, 2023: Chapter 8. https://www.ipcc.ch/report/ar6/wg1/chapter/chapter-8/#8.4.1.1
[5] IPCC. (2023). Table 8.2 | Monsoon mean water cycle projections in the mid-term (2041–2060) and long term (2081–2100) relative to present day (1995–2014), showing present-day mean and 90% confidence range across CMIP6 models (historical experiment) and projected mean changes and the 90% confidence range across the same set of models and a range of Shared Socio-economic Pathway scenarios. All statistics are in units of mm day–1. In IPCC, 2023: Chapter 8. https://www.ipcc.ch/report/ar6/wg1/chapter/chapter-8/#8.4.2.4
[6] IPCC. (2023). FAQ 11.1, Figure 1 | How will changes in climate extremes compare with changes in climate averages? | Global maps of future changes in surface temperature (top panels) and precipitation (bottom panels) for long-term average (left) and extreme conditions (right). In IPCC, 2023: Chapter 11. https://www.ipcc.ch/report/ar6/wg1/figures/chapter-11/faq-11-1-figure-1
[7] IPCC. (2023). Box 8.2 Figure 1 | Projected long-term changes in precipitation seasonality. . https://www.ipcc.ch/report/ar6/wg1/figures/chapter-8/box-8-2-figure-1
[8] IPCC. (2023). Figure 10.15 | Future emergence of anthropogenic signal at regional scale. In IPCC, 2023: Chapter 10. https://www.ipcc.ch/report/ar6/wg1/figures/chapter-10/figure-10-15
[9] IPCC. (2023). Figure 10.19 | Changes in the Indian summer monsoon in the historical and future periods. In IPCC, 2023: Chapter 10. https://www.ipcc.ch/report/ar6/wg1/figures/chapter-10/figure-10-19
[10] IPCC. (2023). Figure 4.33 | Area fraction of significant precipitation change at 1.5°C, 2°C, 3°C, and 4°C of global warming. In IPCC, 2023: Chapter 4. https://www.ipcc.ch/report/ar6/wg1/figures/chapter-4/figure-4-33
[11] IPCC. (2023). Figure 4.14 | Time series of global land monsoon precipitation and Northern Hemisphere summer monsoon (NHSM) circulation index anomalies. In IPCC, 2023: Chapter 4. https://www.ipcc.ch/report/ar6/wg1/figures/chapter-4/figure-4-14
[12] IPCC. (2023). Figure 4.32 | Projected spatial patterns of change in annual average precipitation (expressed as a percentage change) at different levels of global warming. In IPCC, 2023: Chapter 4. https://www.ipcc.ch/report/ar6/wg1/figures/chapter-4/figure-4-32
[13] IPCC. (2023). Figure 4.42 | High-warming storylines for changes in annual mean precipitation. In IPCC, 2023: Chapter 4. https://www.ipcc.ch/report/ar6/wg1/figures/chapter-4/figure-4-42
[14] IPCC. (2023). Figure 10.14 | Robustness and scalability of anthropogenic signals at regional scale. In IPCC, 2023: Chapter 10. https://www.ipcc.ch/report/ar6/wg1/figures/chapter-10/figure-10-14
[15] IPCC. (2023). Figure 4.10 | Changes in amplitude of ENSO Variability. In IPCC, 2023: Chapter 4. https://www.ipcc.ch/report/ar6/wg1/figures/chapter-4/figure-4-10
[16] DOI Jury, M.; Turner, A. (2023). Chapter 10 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 10.19 (v20220622). doi:10.5285/e79aab21bf644e61bf5dacd02199daa3
[17] DOI Fischer, E. (2023). Chapter 4 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 4.42 (v20230213). doi:10.5285/e5e7afe5355a439e8d63be47ee7467c8
[18] DOI Fischer, E. (2023). Chapter 4 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 4.32 v20230531. doi:10.5285/0192ae3037794e0eb93b022c5140f399
[19] DOI Sénési, S. (2023). Chapter 8 of the Working Group I Contribution to the IPCC Sixth Assessment Report - Input data for Figure 8.16 (v20220718). doi:10.5285/92dc7ae089d84a43a28099ae49633383
[20] DOI Sénési, S. (2023). Chapter 8 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 8.13 (v20220718). doi:10.5285/6ed1539e8fe84caea089a0d6a7ffcdbd
[21] IPCC. (2023). Code for Figure 8.13 of the Working Group I Contribution to the IPCC Sixth Assessment Report. https://github.com/IPCC-WG1/Chapter-8
[22] IPCC. (2023). Code for Figure 8.16 of the Working Group I Contribution to the IPCC Sixth Assessment Report. https://github.com/IPCC-WG1/Chapter-8
[23] IPCC. (2023). Code for Box8.2 Figure 1 of the Working Group I Contribution to the IPCC Sixth Assessment Report. https://github.com/IPCC-WG1/Chapter-8
[24] IPCC. (2023). Code for Figure 10.19 of the Working Group I Contribution to the IPCC Sixth Assessment Report. https://github.com/IPCC-WG1/Chapter-10_Fig19
[25] IPCC. (2023). Code for Figure FAQ11.1.1 of the Working Group I Contribution to the IPCC Sixth Assessment Report. https://github.com/IPCC-WG1/Chapter-11/blob/main/code/FAQ_11.1_Figure_1_mean_vs_extreme.ipynb
[26] DOI Sénési, Stéphane. (2021). IPCC WGI AR6 Chapter 8. doi:10.5281/zenodo.5217343
[27] DOI Sénési, Stéphane. (2021). IPCC WGI AR6 Chapter 8. doi:10.5281/zenodo.5217343
[28] DOI Jury, M.W.; Turner, A. (2022). IPCC AR6 WGI - Figure 10.19. doi:10.5281/zenodo.6787528
[29] DOI Sénési, Stéphane. (2021). IPCC WGI AR6 Chapter 8. doi:10.5281/zenodo.5217343
[30] DOI Hauser, Mathias. (2023). IPCC AR6 WGI - Chapter 11. doi:10.5281/zenodo.7692016

Parent

CMIP6 ScenarioMIP CNRM-CERFACS CNRM-CM6-1-HR ssp585
Details
[Entry acronym: C6SPCECC2s585r1112Amprld91202] [Entry id: 3925961]