CMIP6 ScenarioMIP CCCma CanESM5 ssp585

doi:10.26050/WDCC/AR6.C6SPCCCEs585

Swart, Neil Cameron et al.

Dataset GroupDOI
Summary
These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.ScenarioMIP.CCCma.CanESM5.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 CanESM5 climate model, released in 2019, includes the following components: aerosol: interactive, atmos: CanAM5 (T63L49 native atmosphere, T63 Linear Gaussian Grid; 128 x 64 longitude/latitude; 49 levels; top level 1 hPa), atmosChem: specified oxidants for aerosols, land: CLASS3.6/CTEM1.2, landIce: specified ice sheets, ocean: NEMO3.4.1 (ORCA1 tripolar grid, 1 deg with refinement to 1/3 deg within 20 degrees of the equator; 361 x 290 longitude/latitude; 45 vertical levels; top grid cell 0-6.19 m), ocnBgchem: Canadian Model of Ocean Carbon (CMOC); NPZD ecosystem with OMIP prescribed carbonate chemistry, seaIce: LIM2. The model was run by the Canadian Centre for Climate Modelling and Analysis, Environment and Climate Change Canada, Victoria, BC V8P 5C2, Canada (CCCma) in native nominal resolutions: aerosol: 500 km, atmos: 500 km, atmosChem: 500 km, land: 500 km, landIce: 500 km, ocean: 100 km, ocnBgchem: 100 km, seaIce: 100 km.
Project
IPCC-AR6_CMIP6 (Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets)
Contact
Neil Cameron Swart (
 neil.swart@nullcanada.ca
0000-0002-8200-6187)
Location(s)
global
Spatial Coverage
Longitude 0 to 360 Latitude -90 to 90
Temporal Coverage
2015-01-01 to 2300-12-31 (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
Size
247.56 GiB (265819777503 Byte)
Format
NetCDF
Status
completely archived
Creation Date
Future Review Date
2032-04-29
Cite as
Swart, Neil Cameron; Cole, Jason N.S.; Kharin, Viatcheslav V.; Lazare, Mike; Scinocca, John F.; Gillett, Nathan P.; Anstey, James; Arora, Vivek; Christian, James R.; Jiao, Yanjun; Lee, Warren G.; Majaess, Fouad; Saenko, Oleg A.; Seiler, Christian; Seinen, Clint; Shao, Andrew; Solheim, Larry; von Salzen, Knut; Yang, Duo; Winter, Barbara; Sigmond, Michael (2023). IPCC DDC: CCCma CanESM5 model output prepared for CMIP6 ScenarioMIP ssp585. World Data Center for Climate (WDCC) at DKRZ. https://doi.org/10.26050/WDCC/AR6.C6SPCCCEs585

BibTeX RIS
Description
assessed by IPCC WGI AR6 authors
Method
IPCC Assessment
Method Description
The data was part of a formal IPCC assessment conducted by the IPCC authors.
Method Url
Description
All TQA checks were passed for CMIP6 ScenarioMIP CCCma CanESM5 ssp585.
Method
CMIP6-TQA Checks
Method Description
Checks performed by WDCC. CMIP6-TQA metrics are documented: https://redmine.dkrz.de/projects/cmip6-lta-and-data-citation/wiki/Quality_Checks
Method Url
Result Date
2023-06-13
Contact typePersonORCIDOrganization
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Cites

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[6] DOI Gutiérrez, J.M.; Jones, R.G.; Narisma, G.T.; Alves, L.M.; Amjad, M.; Gorodetskaya, I.V.; Grose, M.; Klutse, N.A.B.; Krakovska, S.; Li, J.; Martínez-Castro, D.; Mearns, L.O.; Mernild, S.H.; Ngo-Duc, T.; van den Hurk, B.; Yoon, J.-H. (2023). Atlas. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change[Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. doi:10.1017/9781009157896.021
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Is part of

[1] DOI Swart, Neil Cameron; Cole, Jason N.S.; Kharin, Viatcheslav V.; Lazare, Mike; Scinocca, John F.; Gillett, Nathan P.; Anstey, James; Arora, Vivek; Christian, James R.; Jiao, Yanjun; Lee, Warren G.; Majaess, Fouad; Saenko, Oleg A.; Seiler, Christian; Seinen, Clint; Shao, Andrew; Solheim, Larry; von Salzen, Knut; Yang, Duo; Winter, Barbara; Sigmond, Michael. (2019). CCCma CanESM5 model output prepared for CMIP6 ScenarioMIP ssp585. doi:10.22033/ESGF/CMIP6.3696
[2] DOI Swart, Neil Cameron; Cole, Jason N.S.; Kharin, Viatcheslav V.; Lazare, Mike; Scinocca, John F.; Gillett, Nathan P.; Anstey, James; Arora, Vivek; Christian, James R.; Jiao, Yanjun; Lee, Warren G.; Majaess, Fouad; Saenko, Oleg A.; Seiler, Christian; Seinen, Clint; Shao, Andrew; Solheim, Larry; von Salzen, Knut; Yang, Duo; Winter, Barbara; Sigmond, Michael. (2023). IPCC DDC: CCCma CanESM5 model output prepared for CMIP6 ScenarioMIP. doi:10.26050/WDCC/AR6.C6SPCCCE

Is referenced by

[1] DOI Cai, Wenju; Yang, Kai; Wu, Lixin; Huang, Gang; Santoso, Agus; Ng, Benjamin; Wang, Guojian; Yamagata, Toshio. (2020). Opposite response of strong and moderate positive Indian Ocean Dipole to global warming. doi:10.1038/s41558-020-00943-1
[2] DOI Koven, Charles D.; Arora, Vivek K.; Cadule, Patricia; Fisher, Rosie A.; Jones, Chris D.; Lawrence, David M.; Lewis, Jared; Lindsay, Keith; Mathesius, Sabine; Meinshausen, Malte; Mills, Michael; Nicholls, Zebedee; Sanderson, Benjamin M.; Séférian, Roland; Swart, Neil C.; Wieder, William R.; Zickfeld, Kirsten. (2022). Multi-century dynamics of the climate and carbon cycle under both high and net negative emissions scenarios. doi:10.5194/esd-13-885-2022
[3] DOI Wang, Shizhu; Wang, Qiang; Wang, Muyin; Lohmann, Gerrit; Qiao, Fangli. (2022). Arctic Ocean Freshwater in CMIP6 Coupled Models. doi:10.1029/2022ef002878
[4] DOI Langan, Joseph A.; Bell, Richard J.; Collie, Jeremy S. (2022). Taking stock: Is recovery of a depleted population possible in a changing climate?. doi:10.1111/fog.12599
[5] DOI Dahlke, Flemming T.; Wohlrab, Sylke; Butzin, Martin; Pörtner, Hans-Otto. (2020). Thermal bottlenecks in the life cycle define climate vulnerability of fish. doi:10.1126/science.aaz3658
[6] DOI Weijer, W.; Cheng, W.; Garuba, O. A.; Hu, A.; Nadiga, B. T. (2020). CMIP6 Models Predict Significant 21st Century Decline of the Atlantic Meridional Overturning Circulation. doi:10.1029/2019gl086075
[7] DOI Akinsanola, Akintomide Afolayan; Ogunjobi, Kehinde O; Abolude, Akintayo T; Salack, Seyni. (2021). Projected changes in wind speed and wind energy potential over West Africa in CMIP6 models. doi:10.1088/1748-9326/abed7a
[8] DOI Sung, Jang Hyun; Seo, Seung Beom; Ryu, Young. (2022). Deep Learning-Based Projection of Occurrence Frequency of Forest Fires under SSP Scenario: Exploring the Link between Drought Characteristics and Forest Fires. doi:10.3390/su14095494

Is related to

[1] DOI Thompson, Marten; Braverman, Amy; Chatterjee, Snigdhansu. (2022). A dependent multimodel approach to climate prediction with Gaussian processes. doi:10.1017/eds.2022.24

Parent

CMIP6 ScenarioMIP CCCma CanESM5
Details

Attached Datasets ( 943 )

Details for selected entry
[Entry acronym: C6SPCCCEs585] [Entry id: 3917451]