CMIP6 CMIP E3SM-Project E3SM-1-1-ECA piControl r1i1p1f1 Omon tos gr v20201203

Bader, David C. et al.

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.CMIP.E3SM-Project.E3SM-1-1-ECA.piControl' 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 E3SM 1.1 (Energy Exascale Earth System Model) with an experimental land BGC ECA configuration climate model, released in 2019, includes the following components: aerosol: MAM4 with resuspension, marine organics, and secondary organics (same grid as atmos), atmos: EAM (v1.1, cubed sphere spectral-element grid; 5400 elements with p=3; 1 deg average grid spacing; 90 x 90 x 6 longitude/latitude/cubeface; 72 levels; top level 0.1 hPa), atmosChem: Troposphere specified oxidants for aerosols. Stratosphere linearized interactive ozone (LINOZ v2) (same grid as atmos), land: ELM (v1.1, same as atmos; active biogeochemistry using the Equilibrium Chemistry Approximation to represent plant and soil carbon and nutrient mechanisms especially carbon, nitrogen and phosphorus limitation), MOSART (v1.1, 0.5 degree latitude/longitude grid), ocean: MPAS-Ocean (v6.0, oEC60to30 unstructured SVTs mesh with 235160 cells and 714274 edges, variable resolution 60 km to 30 km; 60 levels; top grid cell 0-10 m), ocnBgchem: BEC (Biogeochemical Elemental Cycling model, NPZD-type with C/N/P/Fe/Si/O; same grid as ocean), seaIce: MPAS-Seaice (v6.0; same grid as ocean). The model was run by the LLNL (Lawrence Livermore National Laboratory, Livermore, CA 94550, USA); ANL (Argonne National Laboratory, Argonne, IL 60439, USA); BNL (Brookhaven National Laboratory, Upton, NY 11973, USA); LANL (Los Alamos National Laboratory, Los Alamos, NM 87545, USA); LBNL (Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA); ORNL (Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA); PNNL (Pacific Northwest National Laboratory, Richland, WA 99352, USA); SNL (Sandia National Laboratories, Albuquerque, NM 87185, USA). Mailing address: LLNL Climate Program, c/o David C. Bader, Principal Investigator, L-103, 7000 East Avenue, Livermore, CA 94550, USA (E3SM-Project) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, atmosChem: 100 km, land: 100 km, ocean: 50 km, ocnBgchem: 50 km, seaIce: 50 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.
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
1850-01-16 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
440.08 MiB (461458403 Byte)
Format
NetCDF
Status
completely archived
Creation Date
Future Review Date
2032-12-03
Download Permission
Please login to check permission and download options
Cite as
[ Derived from parent entry - See data hierarchy tab ]
Bader, David C.; Leung, Ruby; Taylor, Mark; McCoy, Renata B. (2023). IPCC DDC: E3SM-Project E3SM1.1ECA model output prepared for CMIP6 CMIP piControl. World Data Center for Climate (WDCC) at DKRZ. https://doi.org/10.26050/WDCC/AR6.C6CMEPE1pc

BibTeX RIS
VariableCodeAggregationUnit
sea_surface_temperatureCF
tos (IPCC_DDC_AR6: 1158)
mondegC

Is source of

[1] IPCC. (2023). Figure 3.39 | Model evaluation of the Pacific Decadal Variability (PDV). In IPCC, 2023: Chapter 3. https://www.ipcc.ch/report/ar6/wg1/figures/chapter-3/figure-3-39
[2] IPCC. (2023). Figure 3.40 | Model evaluation of Atlantic Multi-decadal Variability (AMV). In IPCC, 2023: Chapter 3. https://www.ipcc.ch/report/ar6/wg1/figures/chapter-3/figure-3-40
[3] DOI Phillips, A.; Kosaka, Y.; Cassou, C.; Kazeroni, R. (2023). Chapter 3 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 3.40 (v20220614). doi:10.5285/12f0d7db5ed747d2940210e52211ed6a
[4] DOI Phillips, A.; Kosaka, Y.; Cassou, C.; Kazeroni, R. (2023). Chapter 3 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 3.39 (v20220614). doi:10.5285/02006a22c33b42039d96be53d332930a
[5] IPCC. (2023). Code for Figure 3.39 of the Working Group I Contribution to the IPCC Sixth Assessment Report. https://github.com/IPCC-WG1/Chapter-3_Fig39
[6] IPCC. (2023). Code for Figure 3.40 of the Working Group I Contribution to the IPCC Sixth Assessment Report. https://github.com/IPCC-WG1/Chapter-3_Fig40
[7] DOI Phillips, A.; Kosaka, Y.; Cassou, C.; Karmouche, S.; Bock, L.; Kazeroni, R. (2022). IPCC AR6 WGI - Figure 3.39. doi:10.5281/zenodo.6783258
[8] DOI Phillips, A.; Kosaka, Y.; Cassou, C.; Karmouche, S.; Bock, L.; Kazeroni, R. (2022). IPCC AR6 WGI - Figure 3.40. doi:10.5281/zenodo.6783260

Parent

CMIP6 CMIP E3SM-Project E3SM-1-1-ECA piControl
Details
[Entry acronym: C6CMEPE1pcr111Omtosld01203] [Entry id: 3911131]