These data include all datasets published for 'CMIP6.CMIP.CMCC.CMCC-CM2-HR4.amip' 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 CMCC-CM2-HR4 climate model, released in 2016, includes the following components: aerosol: prescribed MACv2-SP, atmos: CAM4 (1deg; 288 x 192 longitude/latitude; 26 levels; top at ~2 hPa), land: CLM4.5 (SP mode), ocean: NEMO3.6 (ORCA0.25 1/4 deg from the Equator degrading at the poles; 1442 x 1051 longitude/latitude; 50 vertical levels; top grid cell 0-1 m), seaIce: CICE4.0. The model was run by the Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici, Lecce 73100, Italy (CMCC) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, land: 100 km, ocean: 25 km, seaIce: 25 km. Individuals using the data must abide by terms of use for CMIP6 data (https://pcmdi.llnl.gov/CMIP6/TermsOfUse). The original license restrictions on these datasets were recorded as global attributes in the data files, but these may have been subsequently updated.
Scoccimarro, Enrico; Bellucci, Alessio; Peano, Daniele (2023). CMCC CMCC-CM2-HR4 model output prepared for CMIP6 CMIP amip. World Data Center for Climate (WDCC) at DKRZ. https://www.wdc-climate.de/ui/entry?acronym=C6_4367380
[1] DOIScoccimarro, Enrico; Bellucci, Alessio; Peano, Daniele. (2021). CMCC CMCC-CM2-HR4 model output prepared for CMIP6 CMIP amip. doi:10.22033/ESGF/CMIP6.3735
Is referenced by
[1] DOIChen, Yan; Ji, Duoying; Moore, John C.; Hu, Jiangling; He, Yanyi. (2022). Observational Constraint on the Contribution of Surface Albedo Feedback to the Amplified Tibetan Plateau Surface Warming. doi:10.1029/2021jd036085
Is cited by
[1] DOIIntergovernmental Panel on Climate Change (IPCC). (2023). 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