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What are global climate projections?

Global climat climate projections are simulations of the climate system performed with general circulation models which represent physical processes in the atmosphere, ocean, cryosphere and land surface. These models may cover the entire globe or a specific region and globe and use information about the external influences on the system. Such simulations have been generated by multiple independent climate research centres in an effort coordinated by the World Climate Research Program (WCRP) and assessed by the Intergovernmental Panel on Climate Change (IPCC). These climate projections underpin the conclusions of the IPCC Assessment Reports that “Continued emission of greenhouse gases will cause further warming and long-lasting changes in all components of the climate system, increasing the likelihood of severe, pervasive and irreversible impacts for people and ecosystems”.

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Analysis of the CMIP data allows for improving

an improved understanding of

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the climate, including its variability and change,
an improved understanding of the societal and environmental implications of climate change in terms of impacts, adaptation and vulnerability,
informing the Intergovernmental Panel on Climate Change (IPCC) reports.

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determining why similarly forced models to produce a range of responses,
evaluating how realistic the different models are in simulating the recent past,
examining climate predictability.

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The sixth phase of the Coupled Model Intercomparison Project (CMIP6) consists of 134 models from fifty-one modelling centers 53 modelling centres (Durack, 2020). CMIP6 data publication began in 2019 and the majority of the data publication will be completed by 2022. The scientific analyses from CMIP6 will be used extensively in the Intergovernmental Panel on Climate Change (IPCC) 6th Assessment Report (AR6), due for release in 2021/22 (IPCC, 2020).

CMIP6 will aim aims to address 3 main questions:

How does the Earth system respond to forcing?
What are the origins and consequences of systematic model biases?
How can we assess future climate changes given internal climate variability, predictability, and uncertainties in scenarios ? (Eyring et al, 2016)?

There are some differences between the experimental design and organisation of CMIP6 and its predecessor CMIP5. It was decided that for CMIP6, a new and more federated structure would be used, consisting of the following three major elements:

A handful of common experiments, the DECK (Diagnostic, Evaluation and Characterization of Klima) and CMIP historical simulations (1850 – near-present) that will maintain continuity and help document basic characteristics of models across different phases of CMIP;
Common standards, coordination, infrastructure and documentation that will facilitate the distribution of model outputs and the characterization of the model ensemble;
An ensemble of CMIP-Endorsed Model Intercomparison Projects (MIPs) that will be specific to a particular phase of CMIP (now CMIP6) and that will build on the DECK and CMIP historical simulations to address a large range of specific questions and fill the scientific gaps of the previous CMIP phases (World Climate Research Programme, 2020).

The CMIP6 data archive is distributed through the Earth System Grid Federation (ESGF) though many national centres have either a full or partial copy of the data. A quality-controlled subset of CMIP6 data are made available through the Climate Data Store (CDS) for the users of the Copernicus Climate Change Service (C3S).

Global climate projections in the CDS

The global climate projections in the Climate Data Store (CDS) are a quality-controlled subset of the wider CMIP6 data. These data represent only a small subset of CMIP6 archive. A set of 51 core variables from the CMIP6 archive were identified for the CDS. These variables are provided from 9 of the most popular CMIP6 experiments.

The CDS subset of CMIP6 data have has been through a quality control procedure which ensures a high standard of dependability of the data. It may be for example, that similar data can be found in the main CMIP6 ESGF archive however these data come with very limited quality assurance and may have metadata errors or omissions.

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The SSP scenario experiments can be understood in terms of two pathways, a Shared Socioeconomic Pathway (SSP) and a Representative Concentration Pathway (RCP). The two pathways are represented by the three digits that make up the experiment’s name. The first digit represents the SSP storyline for the socio-economic mitigation and adaptation challenges that the experiment represents (Figure 1). The second and third digits represent the RCP climate forcing that the experiment follows. For example, experiment ssp245 follows SSP2, a storyline with intermediate mitigation and adaptation challenges, and RCP4.5 which leads to a radiative forcing of 4.5 Wm^-2by the year 2100.

Image AddedImage Removed

Figure 1 - The socioeconomic “Challenge Space” to be spanned by the CMIP6 SSP experiments (O’Neil et al. 2014).

Experiments in the CDS

The CDS-CMIP6 subset consists of the following CMIP6 experiments:CMIP6 experiments detailed in the table below.

Expand

title	Click here to expand... CMIP6 experiments included in the CDS

Experiment name

Extended Description

historical

The historical experiment is a simulation of the recent past from 1850 to 2014, it is performed with a coupled atmosphere-ocean general circulation model (AOGCM). In the historical simulations the model is forced with changing conditions (consistent with observations) which include atmospheric composition, land use and solar forcing. The initial conditions for the historical simulation are taken from the pre-industrial control simulation (piControl) at a point where the remaining length of the piControl is sufficient to extend beyond the period of the historical simulation to the end of any future "scenario" simulations run by the same model. The historical simulation is used to evaluate model performance against present climate and observed climate change.

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ssp585

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SSP5-8.5

SSP5-8.5 is a scenario experiment extending into the near future from 2015 to 2100, it is performed with a coupled atmosphere-ocean general circulation model (AOGCM). The forcing for the CMIP6 SSP experiments is derived from shared socioeconomic pathways (SSPs), a set of emission scenarios driven by different socioeconomic assumptions, paired with representative concentration pathways (RCPs), global forcing pathways which lead to specific end of century radiative forcing targets.

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SSP5-8.5 is based on SSP5 in which climate change mitigation challenges dominate and RCP8.5, a future pathway with a radiative forcing of 8.5 W/m2 in the year 2100. The ssp585 scenario represents the high end of plausible future forcing pathways.

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SSP5-8.5 is comparable to the CMIP5 experiment RCP8.5.

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ssp370

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SSP3-7.0

SSP3-7.0 is a scenario experiment extending into the near future from 2015 to 2100, it is performed with a coupled atmosphere-ocean general circulation model (AOGCM). The forcing for the CMIP6 SSP experiments is derived from shared socioeconomic pathways (SSPs), a set of emission scenarios driven by different socioeconomic assumptions, paired with representative concentration pathways (RCPs), global forcing pathways which lead to specific end of century radiative forcing targets. SSP3-7.

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0 is based on SSP3 in which climate change mitigation and adaptation challenges are high and RCP7.0, a future pathway with a radiative forcing of 7.0 W/m2 in the year 2100. The

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SSP3-7.0 scenario represents the medium to high end of plausible future forcing pathways.

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SSP3-7.0 fills a gap in the CMIP5 forcing pathways that is particularly important because it represents a forcing level common to several (unmitigated) SSP baseline pathways.

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ssp245

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SSP2-4.5

SSP2-4.5 is a scenario experiment extending into the near future from 2015 to 2100, it is performed with a coupled atmosphere-ocean general circulation model (AOGCM). The forcing for the CMIP6 SSP experiments is derived from shared socioeconomic pathways (SSPs), a set of emission scenarios driven by different socioeconomic assumptions, paired with representative concentration pathways (RCPs), global forcing pathways which lead to specific end of century radiative forcing targets.

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SSP2-4.5 is based on SSP2 with intermediate climate change mitigation and adaptation challenges and RCP4.5, a future pathway with a radiative forcing of 4.5 W/m2 in the year 2100. The ssp245 scenario represents the medium part of plausible future forcing pathways. SSP2-4.

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5 is comparable to the CMIP5 experiment RCP4.5.

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ssp126

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SSP1-2.6

SSP1-2.6 is a scenario experiment extending into the near future from 2015 to 2100, it is performed with a coupled atmosphere-ocean general circulation model (AOGCM). The forcing for the CMIP6 SSP experiments is derived from shared socioeconomic pathways (SSPs), a set of emission scenarios driven by different socioeconomic assumptions, paired with representative concentration pathways (RCPs), global forcing pathways which lead to specific end of century radiative forcing targets.

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SSP1-2.6 is based on SSP1 with low climate change mitigation and adaptation challenges and RCP2.6, a future pathway with a radiative forcing of 2.6 W/m2 in the year 2100. The

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SSP1-2.6 scenario represents the low end of plausible future forcing pathways.

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SSP1-2.6 depicts a "best case" future from a sustainability perspective.

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ssp460

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SSP4-6.0

SSP4-6.0 is a scenario experiment extending into the near future from 2015 to 2100, it is performed with a coupled atmosphere-ocean general circulation model (AOGCM). The forcing for the CMIP6 SSP experiments is derived from shared socioeconomic pathways (SSPs), a set of emission scenarios driven by different socioeconomic assumptions, paired with representative concentration pathways (RCPs), global forcing pathways which lead to specific end of century radiative forcing targets. SSP4-6.

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0 is based on SSP4 in which climate change adaptation challenges dominate and RCP6.0, a future pathway with a radiative forcing of 6.0 W/m2 in the year 2100. The

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SSP4-6.0 scenario fills in the range of medium plausible future forcing pathways.

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SSP4-6.0 defines the low end of the forcing range for unmitigated SSP baseline scenarios.

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ssp434

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SSP4-3.4

SSP4-3.4 is a scenario experiment extending into the near future from 2015 to 2100, it is performed with a coupled atmosphere-ocean general circulation model (AOGCM). The forcing for the CMIP6 SSP experiments is derived from shared socioeconomic pathways (SSPs), a set of emission scenarios driven by different socioeconomic assumptions, paired with representative concentration pathways (RCPs), global forcing pathways which lead to specific end of century radiative forcing targets.

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SSP4-3.4 is based on SSP4 in which climate change adaptation challenges dominate and RCP3.4, a future pathway with a radiative forcing of 3.4 W/m2 in the year 2100. The

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SSP4-3.4 scenario fills a gap at the low end of the range of plausible future forcing pathways.

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SSP4-3.4 is of interest to mitigation policy since mitigation costs differ substantially between forcing levels of 4.5 W/m2 and 2.6 W/m2.

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SSP5-

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3.4OS

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SSP5-

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3.4OS is a scenario experiment with simulations beginning in the mid-21st century running from 2040 to 2100, it is performed with a coupled atmosphere-ocean general circulation model (AOGCM). The forcing for the CMIP6 SSP experiments is derived from shared socioeconomic pathways (SSPs), a set of emission scenarios driven by different socioeconomic assumptions, paired with representative concentration pathways (RCPs), global forcing pathways which lead to specific end of century radiative forcing targets.

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SSP5-

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3.4OS is based on SSP5 in which climate change mitigation challenges dominate and RCP3.4-over, a future pathway with a peak and decline in forcing towards an eventual radiative forcing of 3.4 W/m2 in the year 2100. The

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SSP5-

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3.4OS scenario branches from

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SSP5-8.5 in the year 2040 whereupon it applies substantially negative net emissions.

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SSP5-

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3.4OS explores the climate science and policy implications of a peak and decline in forcing during the 21st century.

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SSP5-3.4OS fills a gap in existing climate simulations by investigating the implications of a substantial overshoot in radiative forcing relative to a longer-term target.

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ssp119

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SSP1-1.9

SSP1-1.9 is a scenario experiment extending into the near future from 2015 to 2100, it is performed with a coupled atmosphere-ocean general circulation model (AOGCM). The forcing for the CMIP6 SSP experiments is derived from shared socioeconomic pathways (SSPs), a set of emission scenarios driven by different socioeconomic assumptions, paired with representative concentration pathways (RCPs), global forcing pathways which lead to specific end of century radiative forcing targets. SSP1-1.

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9 is based on SSP1 with low climate change mitigation and adaptation challenges and RCP1.9, a future pathway with a radiative forcing of 1.9 W/m2 in the year 2100. The

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SSP1-1.9 scenario fills a gap at the very low end of the range of plausible future forcing pathways.

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SSP1-1.9 forcing will be substantially below

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SSP1-2.6 in 2100. There is policy interest in low-forcing scenarios that would inform a possible goal of limiting global mean warming to 1.5°C above pre-industrial levels based on the Paris COP21 agreement.

Models, grids and pressure levels

Models

The models included in the CDS-CMIP6 subset are detailed in the table below including a brief description of the model where this information is readily available, further details can be found on the Earth System Documentation site.

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Expand

title	Click here to expand...Global climate models included in the CDS

Model Name	Modelling Centre	Model Details
ACCESS-CM2 (released in 2019)	CSIRO-ARCCSS (Commonwealth Scientific and Industrial Research Organisation,

Aspendale, Victoria 3195, Australia,

Australian Research Council Centre of Excellence for Climate System Science)

Australian Community Climate and Earth System Simulator Climate Model Version 2

Grids

CMIP6 data is reported either on the model’s native grid or re-gridded to one or more target grids with data variables provided near the center of each grid cell (rather than at the boundaries). For CMIP6 there is a requirement to record both the native grid of the model and the grid of its output (archived in the CMIP6 repository) a “nominal_resolution”. The "nominal_resolution” enables users to identify which models are relatively high resolution and have data that might be challenging to download and store locally.

Pressure levels

For pressure level data the model output is available on the pressure levels according to the table below. Note that since the model output is standardised all models produce the data on the same pressure levels.

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Frequency

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Number of Levels

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Pressure Levels (hPa)

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Daily

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8

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1000., 850., 700., 500., 250., 100., 50., 10.

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Monthly

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19

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1000., 925., 850., 700., 600., 500., 400., 300., 250., 200., 150., 100., 70., 50., 30., 20., 10., 5., 1.

The model includes the components: aerosol: UKCA-GLOMAP-mode, atmos: MetUM-HadGEM3-GA7.1 (N96; 192 x 144 longitude/latitude; 85 levels; top-level 85 km), land: CABLE2.5, ocean: ACCESS-OM2 (GFDL-MOM5, tripolar primarily 1deg; 360 x 300 longitude/latitude; 50 levels; top grid cell 0-10 m), seaIce: CICE5.1.2 (same grid as ocean). The model was run in native nominal resolutions: aerosol: 250 km, atmosphere: 250 km, land: 250 km, ocean: 100 km, seaIce: 100 km.
ACCESS-ESM1-5 (released in 2019)	CSIRO (Commonwealth Scientific and Industrial Research Organisation)	The model includes the components: aerosol: CLASSIC (v1.0), atmos: HadGAM2 (r1.1, N96; 192 x 145 longitude/latitude; 38 levels; top level 39255 m), land: CABLE2.4, ocean: ACCESS-OM2 (MOM5, tripolar primarily 1deg; 360 x 300 longitude/latitude; 50 levels; top grid cell 0-10 m), ocnBgchem: WOMBAT (same grid as ocean), seaIce: CICE4.1 (same grid as ocean). The model was run in native nominal resolutions: aerosol: 250 km, atmosphere: 250 km, land: 250 km, ocean: 100 km, ocean biogeochemistry: 100 km, seaIce: 100 km.
AWI-CM-1-1-MR (released in 2018)	AWI (Alfred Wegener Institute)	The model includes the components: atmos: ECHAM6.3.04p1 (T127L95 native atmosphere T127 gaussian grid; 384 x 192 longitude/latitude; 95 levels; top level 80 km), land: JSBACH 3.20, ocean: FESOM 1.4 (unstructured grid in the horizontal with 830305 wet nodes; 46 levels; top grid cell 0-5 m), seaIce: FESOM 1.4. The model was run in native nominal resolutions: atmos: 100 km, land: 100 km, ocean: 25 km, seaIce: 25 km.
AWI-ESM-1-1-LR (released in 2018)	AWI (Alfred Wegener Institute)	The model includes the components: atmos: ECHAM6.3.04p1 (T63L47 native atmosphere T63 gaussian grid; 192 x 96 longitude/latitude; 47 levels; top-level 80 km), land: JSBACH 3.20 with dynamic vegetation, ocean: FESOM 1.4 (unstructured grid in the horizontal with 126859 wet nodes; 46 levels; top grid cell 0-5 m), seaIce: FESOM 1.4. AWI-ESM 1.1 LR is an extension of the AWI-CM for earth system modelling. The model was run in native nominal resolutions: atmos: 250 km, land: 250 km, ocean: 50 km, seaIce: 50 km.
BCC-CSM2-MR (released in 2017)	BCC (Beijing Climate Center)	The model includes the components: atmos: BCC_AGCM3_MR (T106; 320 x 160 longitude/latitude; 46 levels; top level 1.46 hPa), land: BCC_AVIM2, ocean: MOM4 (1/3 deg 10S-10N, 1/3-1 deg 10-30 N/S, and 1 deg in high latitudes; 360 x 232 longitude/latitude; 40 levels; top grid cell 0-10 m), seaIce: SIS2. The model was run in native nominal resolutions: atmosphere: 100 km, land: 100 km, ocean: 50 km, seaIce: 50 km.
BCC-ESM1 (released in 2017)	BCC (Beijing Climate Center)	The model includes the components: atmos: BCC_AGCM3_LR (T42; 128 x 64 longitude/latitude; 26 levels; top level 2.19 hPa), atmosChem: BCC-AGCM3-Chem, land: BCC_AVIM2, ocean: MOM4 (1/3 deg 10S-10N, 1/3-1 deg 10-30 N/S, and 1 deg in high latitudes; 360 x 232 longitude/latitude; 40 levels; top grid cell 0-10 m), seaIce: SIS2. The model was run in native nominal resolutions: atmosphere: 250 km, atmospheric chemistry: 250 km, land: 250 km, ocean: 50 km, seaIce: 50 km.
CAMS-CSM1-0 (released in 2016)	CAMS (Chinese Academy of Meteorological Sciences)	The model includes the components: atmos: ECHAM5_CAMS (T106; 320 x 160 longitude/latitude; 31 levels; top level 10 mb), land: CoLM 1.0, ocean: MOM4 (tripolar; 360 x 200 longitude/latitude, primarily 1deg latitude/longitude, down to 1/3deg within 30deg of the equatorial tropics; 50 levels; top grid cell 0-10 m), seaIce: SIS 1.0. The model was run in native nominal resolutions: atmosphere: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km.
CanESM5 (released in 2019)	CCCMA (Canadian Centre for Climate Modelling and Analysis)	The model includes the 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 in native nominal resolutions: aerosol: 500 km, atmosphere: 500 km, atmospheric chemistry: 500 km, land: 500 km, landIce: 500 km, ocean: 100 km, ocean biogeochemistry: 100 km, seaIce: 100 km.
CanESM5-CanOE (released in 2019)	CCCMA (Canadian Centre for Climate Modelling and Analysis)	CanESM5-CanOE is identical to CanESM5, except that CMOC (Canadian Model of Ocean Carbon) was replaced with CanOE (Canadian Ocean Ecosystem model). The model was run 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.
CAS-ESM2-0 (released in 2019)	CAS (Chinese Academy of Sciences)	The model includes the components: aerosol: IAP AACM, atmos: IAP AGCM 5.0 (Finite difference dynamical core; 256 x 128 longitude/latitude; 35 levels; top level 2.2 hPa), atmosChem: IAP AACM, land: CoLM, ocean: LICOM2.0 (LICOM2.0, primarily 1deg; 362 x 196 longitude/latitude; 30 levels; top grid cell 0-10 m), ocnBgchem: IAP OBGCM, seaIce: CICE4. The model was run in native nominal resolutions: aerosol: 100 km, atmosphere: 100 km, atmospheric chemistry: 100 km, land: 100 km, ocean: 100 km, ocean biogeochemistry: 100 km, seaIce: 100 km.
CESM2	NCAR (National Center for Atmospheric Research)	The model includes the components: aerosol: MAM4 (same grid as atmos), atmos: CAM6 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb), atmosChem: MAM4 (same grid as atmos), land: CLM5 (same grid as atmos), landIce: CISM2.1, ocean: POP2 (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m), ocnBgchem: MARBL (same grid as ocean), seaIce: CICE5.1 (same grid as ocean). The model was run in native nominal resolutions: aerosol: 100 km, atmos: 100 km, atmosChem: 100 km, land: 100 km, landIce: 5 km, ocean: 100 km, ocnBgchem: 100 km, seaIce: 100 km.
CESM2-FV2 (released in 2019)	NCAR (National Center for Atmospheric Research)	The model includes the components: aerosol: MAM4 (same grid as atmos), atmos: CAM6 (1.9x2.5 finite volume grid; 144 x 96 longitude/latitude; 32 levels; top level 2.25 mb), atmosChem: MAM4 (same grid as atmos), land: CLM5 (same grid as atmos), landIce: CISM2.1, ocean: POP2 (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m), ocnBgchem: MARBL (same grid as ocean), seaIce: CICE5.1 (same grid as ocean). The model was run in native nominal resolutions: aerosol: 250 km, atmosphere: 250 km, atmospheric chemistry: 250 km, land: 250 km, landIce: 5 km, ocean: 100 km, ocean biogeochemistry: 100 km, seaIce: 100 km.
CESM2-WACCM (released in 2018)	NCAR (National Center for Atmospheric Research)	The model includes the components: aerosol: MAM4 (same grid as atmos), atmos: WACCM6 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 70 levels; top level 4.5e-06 mb), atmosChem: MAM4 (same grid as atmos), land: CLM5 (same grid as atmos), landIce: CISM2.1, ocean: POP2 (320 x 384 longitude/latitude; 60 levels; top grid cell 0-10 m), ocnBgchem: MARBL (same grid as ocean), seaIce: CICE5.1 (same grid as ocean). The model was run in native nominal resolutions: aerosol: 100 km, atmosphere: 100 km, atmospheric chemistry: 100 km, land: 100 km, landIce: 5 km, ocean: 100 km, ocean biogeochemistry: 100 km, seaIce: 100 km.
CESM2-WACCM-FV2 (released in 2019)	NCAR (National Center for Atmospheric Research)	The model includes the components: aerosol: MAM4 (same grid as atmos), atmos: WACCM6 (1.9x2.5 finite volume grid; 144 x 96 longitude/latitude; 70 levels; top level 4.5e-06 mb), atmosChem: MAM4 (same grid as atmos), land: CLM5 (same grid as atmos), landIce: CISM2.1, ocean: POP2 (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m), ocnBgchem: MARBL (same grid as ocean), seaIce: CICE5.1 (same grid as ocean). The model was run in native nominal resolutions: aerosol: 250 km, atmosphere: 250 km, atmospheric chemistry: 250 km, land: 250 km, landIce: 5 km, ocean: 100 km, ocean biogeochemistry: 100 km, seaIce: 100 km.
CIESM (released in 2017)	THU (Tsinghua University - Department of Earth System Science)	The model includes the components: aerosol: MAM4, atmos: CIESM-AM (FV/FD; 288 x 192 longitude/latitude; 30 levels; top level 2.255 hPa), atmosChem: trop_mam4, land: CIESM-LM (modified CLM4.5), ocean: CIESM-OM (FD, SCCGrid Displaced Pole; 720 x 560 longitude/latitude; 46 levels; top grid cell 0-6 m), seaIce: CICE4. The model was run in native nominal resolutions: aerosol: 100 km, atmosphere: 100 km, atmospheric chemistry: 100 km, land: 100 km, ocean: 50 km, seaIce: 50 km.
CMCC-CM2-SR5 (released in 2016)	CMCC (Centro Euro-Mediterraneo per I Cambiamenti Climatici)	The model includes the components: aerosol: MAM3, atmos: CAM5.3 (1deg; 288 x 192 longitude/latitude; 30 levels; top at ~2 hPa), land: CLM4.5 (BGC mode), ocean: NEMO3.6 (ORCA1 tripolar primarly 1 deg lat/lon with meridional refinement down to 1/3 degree in the tropics; 362 x 292 longitude/latitude; 50 vertical levels; top grid cell 0-1 m), seaIce: CICE4.0. The model was run in native nominal resolutions: aerosol: 100 km, atmosphere: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km.
CNRM-CM6-1 (released in 2017)	CNRM-CERFACS (National Center for Meteorological Research, Météo-France and CNRS laboratory, Climate Modeling and Global change)	The model includes the components: aerosol: prescribed monthly fields computed by TACTIC_v2 scheme, atmos: Arpege 6.3 (T127; Gaussian Reduced with 24572 grid points in total distributed over 128 latitude circles (with 256 grid points per latitude circle between 30degN and 30degS reducing to 20 grid points per latitude circle at 88.9degN and 88.9degS); 91 levels; top-level 78.4 km), atmosChem: OZL_v2, land: Surfex 8.0c, ocean: Nemo 3.6 (eORCA1, tripolar primarily 1deg; 362 x 294 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: Gelato 6.1. The model was run in native nominal resolutions: aerosol: 250 km, atmos: 250 km, atmosChem: 250 km, land: 250 km, ocean: 100 km, seaIce: 100 km.
CNRM-CM6-1-HR (released in 2017)	CNRM-CERFACS (National Center for Meteorological Research, Météo-France and CNRS laboratory, Climate Modeling and Global change)	The model includes the 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 in native nominal resolutions: aerosol: 100 km, atmosphere: 100 km, atmospheric chemistry: 100 km, land: 100 km, ocean: 25 km, seaIce: 25 km.
CNRM-ESM2-1 (released in 2017)	CNRM-CERFACS (National Center for Meteorological Research, Météo-France and CNRS laboratory, Climate Modeling and Global change)	The model includes the components: aerosol: TACTIC_v2, atmos: Arpege 6.3 (T127; Gaussian Reduced with 24572 grid points in total distributed over 128 latitude circles (with 256 grid points per latitude circle between 30degN and 30degS reducing to 20 grid points per latitude circle at 88.9degN and 88.9degS); 91 levels; top-level 78.4 km), atmosChem: REPROBUS-C_v2, land: Surfex 8.0c, ocean: Nemo 3.6 (eORCA1, tripolar primarily 1deg; 362 x 294 longitude/latitude; 75 levels; top grid cell 0-1 m), ocnBgchem: Pisces 2.s, seaIce: Gelato 6.1. The model was run in native nominal resolutions: aerosol: 250 km, atmos: 250 km, atmosChem: 250 km, land: 250 km, ocean: 100 km, ocnBgchem: 100 km, seaIce: 100 km.
E3SM-1-0 (released in 2018)	E3SM-Project LLNL (Energy Exascale Earth System Model, Lawrence Livermore National Laboratory)	The model includes the components: aerosol: MAM4 with resuspension, marine organics, and secondary organics (same grid as atmos), atmos: EAM (v1.0, 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 (v1.0, cubed sphere spectral-element grid; 5400 elements with p=3; 1 deg average grid spacing; 90 x 90 x 6 longitude/latitude/cubeface; satellite phenology mode), MOSART (v1.0, 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), seaIce: MPAS-Seaice (v6.0, same grid as ocean). The model was run in native nominal resolutions: aerosol: 100 km, atmosphere: 100 km, atmospheric chemistry: 100 km, land: 100 km, ocean: 50 km, seaIce: 50 km.
E3SM-1-1 (released in 2019)	E3SM-Project RUBISCO (Energy Exascale Earth System Model, Reducing Uncertainty in Biogeochemical Interactions through Synthesis and COmputation)	The model includes the 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 grid as atmos; active biogeochemistry using the Converging Trophic Cascade plant and soil carbon and nutrient mechanisms to represent carbon, nitrogen and phosphorus cycles), 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 in native nominal resolutions: aerosol: 100 km, atmosphere: 100 km, atmospheric chemistry: 100 km, land: 100 km, ocean: 50 km, ocean biogeochemistry: 50 km, seaIce: 50 km.
E3SM-1-1-ECA (released in 2019)	E3SM-Project (Energy Exascale Earth System Model)	The model includes the 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 in native nominal resolutions: aerosol: 100 km, atmosphere: 100 km, atmospheric chemistry: 100 km, land: 100 km, ocean: 50 km, ocean biogeochemistry: 50 km, seaIce: 50 km.
EC-Earth3 (released in 2019)	EC-Earth-Consortium	The model includes the components: atmos: IFS cy36r4 (TL255, linearly reduced Gaussian grid equivalent to 512 x 256 longitude/latitude; 91 levels; top-level 0.01 hPa), land: HTESSEL (land surface scheme built-in IFS), ocean: NEMO3.6 (ORCA1 tripolar primarily 1 deg with meridional refinement down to 1/3 degree in the tropics; 362 x 292 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: LIM3. The model was run in native nominal resolutions: atmos: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km.
EC-Earth3-LR (released in 2019)	EC-Earth-Consortium	The model includes the components: atmos: IFS cy36r4 (TL159, linearly reduced Gaussian grid equivalent to 320 x 160 longitude/latitude; 62 levels; top-level 5 hPa), land: HTESSEL (land surface scheme built-in IFS), ocean: NEMO3.6 (ORCA1 tripolar primarily 1 degree with meridional refinement down to 1/3 degree in the tropics; 362 x 292 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: LIM3. The model was run in native nominal resolutions: atmos: 250 km, land: 250 km, ocean: 100 km, seaIce: 100 km.
EC-Earth3-Veg (released in 2019)	EC-Earth-Consortium	The model includes the components: atmos: IFS cy36r4 (TL255, linearly reduced Gaussian grid equivalent to 512 x 256 longitude/latitude; 91 levels; top-level 0.01 hPa), land: HTESSEL (land surface scheme built-in IFS) and LPJ-GUESS v4, ocean: NEMO3.6 (ORCA1 tripolar primarily 1 degree with meridional refinement down to 1/3 degree in the tropics; 362 x 292 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: LIM3. The model was run in native nominal resolutions: atmos: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km.
EC-Earth3-Veg-LR (released in 2019)	EC-Earth-Consortium	The model includes the components: atmos: IFS cy36r4 (TL159, linearly reduced Gaussian grid equivalent to 320 x 160 longitude/latitude; 62 levels; top-level 5 hPa), land: HTESSEL (land surface scheme built-in IFS) and LPJ-GUESS v4, ocean: NEMO3.6 (ORCA1 tripolar primarily 1 degree with meridional refinement down to 1/3 degree in the tropics; 362 x 292 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: LIM3. The model was run in native nominal resolutions: atmos: 250 km, land: 250 km, ocean: 100 km, seaIce: 100 km.
FGOALS-f3-L (released in 2017)	CAS (Chinese Academy of Sciences)	The model includes the components: atmos: FAMIL2.2 (Cubed-sphere, c96; 360 x 180 longitude/latitude; 32 levels; top level 2.16 hPa), land: CLM4.0, ocean: LICOM3.0 (LICOM3.0, tripolar primarily 1deg; 360 x 218 longitude/latitude; 30 levels; top grid cell 0-10 m), seaIce: CICE4.0. The model was run in native nominal resolutions: atmosphere: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km.
FGOALS-g3 (released in 2017)	CAS (Chinese Academy of Sciences)	The model includes the components: atmos: GAMIL3 (180 x 80 longitude/latitude; 26 levels; top level 2.19hPa), land: CAS-LSM, ocean: LICOM3.0 (LICOM3.0, tripolar primarily 1deg; 360 x 218 longitude/latitude; 30 levels; top grid cell 0-10 m), seaIce: CICE4.0. The model was run in native nominal resolutions: atmosphere: 250 km, land: 250 km, ocean: 100 km, seaIce: 100 km.
FIO-ESM-2-0 (released in 2018)	FIO-QLNM (First Institute of Oceanography (FIO) and Qingdao National Laboratory for Marine Science and Technology (QNLM))	The model includes the components: aerosol: Prescribed monthly fields, atmos: CAM4 (0.9x1.25 finite volume grid; 192 x 288 longitude/latitude; 26 levels; top level ~2 hPa), land: CLM4.0 (same grid at atmos), ocean: POP2-W (POP2 coupled with MASNUM surface wave model, Displaced Pole; 320 x 384 longitude/latitude; 60 levels; top grid cell 0-10 m), seaIce: CICE4.0 (same grid as ocean). The model was run in native nominal resolutions: aerosol: 100 km, atmosphere: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km.
GFDL-AM4 (released in 2018)	NOAA-GFDL (National Oceanic and Atmospheric Administration, Geophysical Fluid Dynamics Laboratory)	The model includes the components: aerosol: interactive, atmos: GFDL-AM4.0 (Cubed-sphere (c96) - 1 degree nominal horizontal resolution; 360 x 180 longitude/latitude; 33 levels; top level 1 hPa), atmosChem: fast chemistry, aerosol only, land: GFDL-LM4.0, landIce: GFDL-LM4.0. The model was run in native nominal resolutions: aerosol: 100 km, atmos: 100 km, atmosChem: 100 km, land: 100 km, landIce: 100 km.
GFDL-CM4 (released in 2018)	NOAA-GFDL (National Oceanic and Atmospheric Administration, Geophysical Fluid Dynamics Laboratory)	The model includes the components: aerosol: interactive, atmos: GFDL-AM4.0.1 (Cubed-sphere (c96) - 1 degree nominal horizontal resolution; 360 x 180 longitude/latitude; 33 levels; top level 1 hPa), atmosChem: fast chemistry, aerosol only, land: GFDL-LM4.0.1 (1 degree nominal horizontal resolution; 360 x 180 longitude/latitude; 20 levels; bottom level 10m); land-Veg:unnamed (dynamic vegetation, dynamic land use); land-Hydro:unnamed (soil water and ice, multi-layer snow, rivers and lakes), landIce: GFDL-LM4.0.1, ocean: GFDL-OM4p25 (GFDL-MOM6, tripolar - nominal 0.25 deg; 1440 x 1080 longitude/latitude; 75 levels; top grid cell 0-2 m), ocnBgchem: GFDL-BLINGv2, seaIce: GFDL-SIM4p25 (GFDL-SIS2.0, tripolar - nominal 0.25 deg; 1440 x 1080 longitude/latitude; 5 layers; 5 thickness categories). The model was run in native nominal resolutions: aerosol: 100 km, atmos: 100 km, atmosChem: 100 km, land: 100 km, landIce: 100 km, ocean: 25 km, ocnBgchem: 25 km, seaIce: 25 km.
GFDL-ESM4 (released in 2018)	NOAA-GFDL (National Oceanic and Atmospheric Administration, Geophysical Fluid Dynamics Laboratory)	The model includes the components: aerosol: interactive, atmos: GFDL-AM4.1 (Cubed-sphere (c96) - 1 degree nominal horizontal resolution; 360 x 180 longitude/latitude; 49 levels; top level 1 Pa), atmosChem: GFDL-ATMCHEM4.1 (full atmospheric chemistry), land: GFDL-LM4.1, landIce: GFDL-LM4.1, ocean: GFDL-OM4p5 (GFDL-MOM6, tripolar - nominal 0.5 deg; 720 x 576 longitude/latitude; 75 levels; top grid cell 0-2 m), ocnBgchem: GFDL-COBALTv2, seaIce: GFDL-SIM4p5 (GFDL-SIS2.0, tripolar - nominal 0.5 deg; 720 x 576 longitude/latitude; 5 layers; 5 thickness categories). The model was run in native nominal resolutions: aerosol: 100 km, atmosphere: 100 km, atmospheric chemistry: 100 km, land: 100 km, landIce: 100 km, ocean: 50 km, ocean biogeochemistry: 50 km, seaIce: 50 km.
GISS-E2-1-G (released in 2019)	NASA-GISS (National Oceanic and Atmospheric Administration, Goddard Institute for Space Studies)	The model includes the components: aerosol: Varies with physics-version (p==1 none, p==3 OMA, p==4 TOMAS, p==5 MATRIX), atmos: GISS-E2.1 (2.5x2 degree; 144 x 90 longitude/latitude; 40 levels; top level 0.1 hPa), atmosChem: Varies with physics-version (p==1 Non-interactive, p>1 GPUCCINI), land: GISS LSM, ocean: GISS Ocean (GO1, 1 degree; 360 x 180 longitude/latitude; 40 levels; top grid cell 0-10 m), seaIce: GISS SI. The model was run in native nominal resolutions: aerosol: 250 km, atmosphere: 250 km, atmospheric chemistry: 250 km, land: 250 km, ocean: 100 km, seaIce: 250 km.
GISS-E2-1-H (released in 2019)	NASA-GISS (National Oceanic and Atmospheric Administration, Goddard Institute for Space Studies)	The model includes the components: aerosol: Varies with physics-version (p==1 none, p==3 OMA, p==4 TOMAS, p==5 MATRIX), atmos: GISS-E2.1 (2.5x2 degree; 144 x 90 longitude/latitude; 40 levels; top level 0.1 hPa), atmosChem: Varies with physics-version (p==1 Non-interactive, p>1 GPUCCINI), land: GISS LSM, ocean: HYCOM Ocean (~1 degree tripolar grid; 360 x 180 longitude/latitude; 32 levels; top grid cell 0-10 m), seaIce: GISS SI. The model was run in native nominal resolutions: aerosol: 250 km, atmosphere: 250 km, atmospheric chemistry: 250 km, land: 250 km, ocean: 100 km, seaIce: 250 km.
GISS-E2-2-G (released in 2019)	NASA-GISS (National Oceanic and Atmospheric Administration, Goddard Institute for Space Studies)	The model includes the components: aerosol: varies with physics-version (p==1 none, p==3 OMA, p==4 TOMAS, p==5 MATRIX), atmos: GISS-E2.2 (High-top, 2 x 2.5 degrees; 144 x 90 longitude/latitude; 102 levels; top level 0.002 hPa), atmosChem: varies with physics-version (p==1 Non-interactive, p>1 GPUCCINI), land: GISS LSM, landIce: Fixed, ocean: GISS Ocean (GO1, 1 degree; 360 x 180 longitude/latitude; 40 levels; top grid cell 0-10m), seaIce: GISS SI. The model was run in native nominal resolutions: aerosol: 250 km, atmosphere: 250 km, atmospheric chemistry: 250 km, land: 250 km, landIce: 250 km, ocean: 100 km, seaIce: 100 km.
HadGEM3-GC31-LL (released in 2016)	MOHC NERC (Met Office Hadley Centre, Natural Environmental Research Council)	The model includes the components: aerosol: UKCA-GLOMAP-mode, atmos: MetUM-HadGEM3-GA7.1 (N96; 192 x 144 longitude/latitude; 85 levels; top level 85 km), land: JULES-HadGEM3-GL7.1, ocean: NEMO-HadGEM3-GO6.0 (eORCA1 tripolar primarily 1 deg with meridional refinement down to 1/3 degree in the tropics; 360 x 330 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: CICE-HadGEM3-GSI8 (eORCA1 tripolar primarily 1 deg; 360 x 330 longitude/latitude). The model was run in native nominal resolutions: aerosol: 100 km, atmosphere: 100 km, land: 100 km, ocean: 25 km, seaIce: 25 km.
HadGEM3-GC31-MM (released in 2016)	MOHC (Met Office Hadley Centre)	The model includes the components: aerosol: UKCA-GLOMAP-mode, atmos: MetUM-HadGEM3-GA7.1 (N216; 432 x 324 longitude/latitude; 85 levels; top level 85 km), land: JULES-HadGEM3-GL7.1, ocean: NEMO-HadGEM3-GO6.0 (eORCA025 tripolar primarily 0.25 deg; 1440 x 1205 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: CICE-HadGEM3-GSI8 (eORCA025 tripolar primarily 0.25 deg; 1440 x 1205 longitude/latitude). The model was run in native nominal resolutions: aerosol: 100 km, atmosphere: 100 km, land: 100 km, ocean: 25 km, seaIce: 25 km.
IITM-ESM (released in 2015)	CCCR-IITM (Centre for Climate Change Research, Indian Institute of Tropical Meteorology)	The model includes the components: aerosol: prescribed MAC-v2, atmos: IITM-GFSv1 (T62L64, Linearly Reduced Gaussian Grid; 192 x 94 longitude/latitude; 64 levels; top level 0.2 mb), land: NOAH LSMv2.7.1, ocean: MOM4p1 (tripolar, primarily 1deg; 360 x 200 longitude/latitude; 50 levels; top grid cell 0-10 m), ocnBgchem: TOPAZv2.0, seaIce: SISv1.0. The model was run in native nominal resolutions: aerosol: 250 km, atmosphere: 250 km, land: 250 km, ocean: 100 km, ocean biogeochemistry: 100 km, seaIce: 100 km.
INM-CM4-8 (released in 2016)	INM (Institute of Numerical Mathematics)	The model includes the components: aerosol: INM-AER1, atmos: INM-AM4-8 (2x1.5; 180 x 120 longitude/latitude; 21 levels; top level sigma = 0.01), land: INM-LND1, ocean: INM-OM5 (North Pole shifted to 60N, 90E; 360 x 318 longitude/latitude; 40 levels; sigma vertical coordinate), seaIce: INM-ICE1. The model was run in native nominal resolutions: aerosol: 100 km, atmosphere: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km.
INM-CM5-0 (released in 2016)	INM (Institute of Numerical Mathematics)	The model includes the components: aerosol: INM-AER1, atmos: INM-AM5-0 (2x1.5; 180 x 120 longitude/latitude; 73 levels; top level sigma = 0.0002), land: INM-LND1, ocean: INM-OM5 (North Pole shifted to 60N, 90E. 0.5x0.25; 720 x 720 longitude/latitude; 40 levels; vertical sigma coordinate), seaIce: INM-ICE1. The model was run in native nominal resolutions: aerosol: 100 km, atmosphere: 100 km, land: 100 km, ocean: 50 km, seaIce: 50 km.
IPSL-CM6A-LR (released in 2017)	IPSL (Institut Pierre‐Simon Laplace)	The model includes the components: atmos: LMDZ (NPv6, N96; 144 x 143 longitude/latitude; 79 levels; top level 80000 m), land: ORCHIDEE (v2.0, Water/Carbon/Energy mode), ocean: NEMO-OPA (eORCA1.3, tripolar primarily 1deg; 362 x 332 longitude/latitude; 75 levels; top grid cell 0-2 m), ocnBgchem: NEMO-PISCES, seaIce: NEMO-LIM3. The model was run in native nominal resolutions: atmosphere: 250 km, land: 250 km, ocean: 100 km, ocean biogeochemistry: 100 km, seaIce: 100 km.
KACE-1-0-G (released in 2018)	NIMS-KMA (National Institute of Meteorological Sciences/Korea Met. Administration)	The model includes the components: aerosol: UKCA-GLOMAP-mode, atmos: MetUM-HadGEM3-GA7.1 (N96; 192 x 144 longitude/latitude; 85 levels; top level 85 km), land: JULES-HadGEM3-GL7.1, ocean: MOM4p1 (tripolar primarily 1deg; 360 x 200 longitude/latitude; 50 levels; top grid cell 0-10 m), seaIce: CICE-HadGEM3-GSI8 (tripolar primarily 1deg; 360 x 200 longitude/latitude). The model was run in native nominal resolutions: aerosol: 250 km, atmos: 250 km, land: 250 km, ocean: 100 km, seaIce: 100 km.
KIOST-ESM (released in 2018)	KIOST (Korea Institute of Ocean Science and Technology)	The model includes the components: atmos: GFDL-AM2.0 (cubed sphere (C48); 192 x 96 longitude/latitude; 32 vertical levels; top level 2 hPa), atmosChem: Simple carbon aerosol model (emission type), land: NCAR-CLM4, landIce: NCAR-CLM4, ocean: GFDL-MOM5.0 (tripolar - nominal 1.0 deg; 360 x 200 longitude/latitude; 52 levels; top grid cell 0-2 m; NK mixed layer scheme), ocnBgchem: TOPAZ2, seaIce: GFDL-SIS. The model was run in native nominal resolutions: atmosphere: 250 km, atmospheric chemistry: 250 km, land: 250 km, landIce: 250 km, ocean: 100 km, ocean biogeochemistry: 100 km, seaIce: 100 km.
MCM-UA-1-0 (released in 1991)	UA (University of Arizona - Department of Geosciences)	The model includes the components: aerosol: Modifies surface albedoes (Haywood et al. 1997, doi: 10.1175/1520-0442(1997)010<1562:GCMCOT>2.0.CO;2), atmos: R30L14 (3.75 X 2.5 degree (long-lat) configuration; 96 x 80 longitude/latitude; 14 levels; top level 0.015 sigma, 15 mb), land: Standard Manabe bucket hydrology scheme (Manabe 1969, doi: 10.1175/1520-0493(1969)097<0739:CATOC>2.3.CO;2), landIce: Specified location - invariant in time, has high albedo and latent heat capacity, ocean: MOM1.0 (MOM1, 1.875 X 2.5 deg; 192 x 80 longitude/latitude; 18 levels; top grid cell 0-40 m), seaIce: Thermodynamic ice model (free drift dynamics). The model was run in native nominal resolutions: aerosol: 250 km, atmos: 250 km, land: 250 km, landIce: 250 km, ocean: 250 km, seaIce: 250 km.
MIROC6 (released in 2017)	MIROC (Atmosphere and Ocean Research Institute (AORI), Centre for Climate System Research - National Institute for Environmental Studies (CCSR-NIES) and Atmosphere and Ocean Research Institute (AORI))	The model includes the components: aerosol: SPRINTARS6.0, atmos: CCSR AGCM (T85; 256 x 128 longitude/latitude; 81 levels; top level 0.004 hPa), land: MATSIRO6.0, ocean: COCO4.9 (tripolar primarily 1deg; 360 x 256 longitude/latitude; 63 levels; top grid cell 0-2 m), seaIce: COCO4.9. The model was run in native nominal resolutions: aerosol: 250 km, atmos: 250 km, land: 250 km, ocean: 100 km, seaIce: 100 km.
MIROC-ES2L (released in 2018)	MIROC (Atmosphere and Ocean Research Institute (AORI), Centre for Climate System Research - National Institute for Environmental Studies (CCSR-NIES) and Atmosphere and Ocean Research Institute (AORI))	The model includes the components: aerosol: SPRINTARS6.0, atmos: CCSR AGCM (T42; 128 x 64 longitude/latitude; 40 levels; top level 3 hPa), land: MATSIRO6.0+VISIT-e ver.1.0, ocean: COCO4.9 (tripolar primarily 1deg; 360 x 256 longitude/latitude; 63 levels; top grid cell 0-2 m), ocnBgchem: OECO ver.2.0; NPZD-type with C/N/P/Fe/O cycles, seaIce: COCO4.9. The model was run in native nominal resolutions: aerosol: 500 km, atmos: 500 km, land: 500 km, ocean: 100 km, ocnBgchem: 100 km, seaIce: 100 km.
MPI-ESM-1-2-HAM (released in 2017)	HAMMOZ-Consortium (Swiss Federal Institute of Technology Zurich (ETH-Zurich), Max Planck Institute for Meteorology (MPI-M), Forschungszentrum Jülich, University of Oxford, Finnish Meteorological Institute (FMI), Leibniz Institute for Tropospheric Research (IfT) and Center for Climate Systems Modeling (C2SM) at ETH Zurich)	The model includes the components: aerosol: HAM2.3, atmos: ECHAM6.3 (spectral T63; 192 x 96 longitude/latitude; 47 levels; top level 0.01 hPa), atmosChem: sulfur chemistry (unnamed), land: JSBACH 3.20, ocean: MPIOM1.63 (bipolar GR1.5, approximately 1.5deg; 256 x 220 longitude/latitude; 40 levels; top grid cell 0-12 m), ocnBgchem: HAMOCC6, seaIce: unnamed (thermodynamic (Semtner zero-layer) dynamic (Hibler 79) sea ice model). The model was run in native nominal resolutions: aerosol: 250 km, atmos: 250 km, atmosChem: 250 km, land: 250 km, ocean: 250 km, ocnBgchem: 250 km, seaIce: 250 km.
MPI-ESM1-2-HR (released in 2017)	MPI-M DWD DKRZ (Max Planck Institute for Meteorology (MPI-M), German Meteorological Service (DWD), German Climate Computing Center (DKRZ))	The model includes the components: aerosol: none, prescribed MACv2-SP, atmos: ECHAM6.3 (spectral T127; 384 x 192 longitude/latitude; 95 levels; top level 0.01 hPa), land: JSBACH3.20, landIce: none/prescribed, ocean: MPIOM1.63 (tripolar TP04, approximately 0.4deg; 802 x 404 longitude/latitude; 40 levels; top grid cell 0-12 m), ocnBgchem: HAMOCC6, seaIce: unnamed (thermodynamic (Semtner zero-layer) dynamic (Hibler 79) sea ice model). The model was run in native nominal resolutions: aerosol: 100 km, atmosphere: 100 km, land: 100 km, landIce: none, ocean: 50 km, ocean biogeochemistry: 50 km, seaIce: 50 km.
MPI-ESM1-2-LR (released in 2017)	MPI-M AWI (Max Planck Institute for Meteorology (MPI-M), AWI (Alfred Wegener Institute))	The model includes the components: aerosol: none, prescribed MACv2-SP, atmos: ECHAM6.3 (spectral T63; 192 x 96 longitude/latitude; 47 levels; top level 0.01 hPa), land: JSBACH3.20, landIce: none/prescribed, ocean: MPIOM1.63 (bipolar GR1.5, approximately 1.5deg; 256 x 220 longitude/latitude; 40 levels; top grid cell 0-12 m), ocnBgchem: HAMOCC6, seaIce: unnamed (thermodynamic (Semtner zero-layer) dynamic (Hibler 79) sea ice model). The model was run in native nominal resolutions: aerosol: 250 km, atmosphere: 250 km, land: 250 km, landIce: none, ocean: 250 km, ocean biogeochemistry: 250 km, seaIce: 250 km.
MRI-ESM2-0 (released in 2017)	MRI (Meteorological Research Institute, Japan)	The model includes the components: aerosol: MASINGAR mk2r4 (TL95; 192 x 96 longitude/latitude; 80 levels; top level 0.01 hPa), atmos: MRI-AGCM3.5 (TL159; 320 x 160 longitude/latitude; 80 levels; top level 0.01 hPa), atmosChem: MRI-CCM2.1 (T42; 128 x 64 longitude/latitude; 80 levels; top level 0.01 hPa), land: HAL 1.0, ocean: MRI.COM4.4 (tripolar primarily 0.5 deg latitude/1 deg longitude with meridional refinement down to 0.3 deg within 10 degrees north and south of the equator; 360 x 364 longitude/latitude; 61 levels; top grid cell 0-2 m), ocnBgchem: MRI.COM4.4, seaIce: MRI.COM4.4. The model was run in native nominal resolutions: aerosol: 250 km, atmosphere: 100 km, atmospheric chemistry: 250 km, land: 100 km, ocean: 100 km, ocean biogeochemistry: 100 km, seaIce: 100 km.
NESM3 (released in 2016)	NUIST (Nanjing University of Information Science and Technology)	The model includes the components: atmos: ECHAM v6.3 (T63; 192 x 96 longitude/latitude; 47 levels; top level 1 Pa), land: JSBACH v3.1, ocean: NEMO v3.4 (NEMO v3.4, tripolar primarily 1deg; 384 x 362 longitude/latitude; 46 levels; top grid cell 0-6 m), seaIce: CICE4.1. The model was run in native nominal resolutions: atmosphere: 250 km, land: 2.5 km, ocean: 100 km, seaIce: 100 km.
NorCPM1 (released in 2019)	NCC (Norwegian Climate Centre)	The model includes the components: aerosol: OsloAero4.1 (same grid as atmos), atmos: CAM-OSLO4.1 (2 degree resolution; 144 x 96 longitude/latitude; 26 levels; top level ~2 hPa), atmosChem: OsloChemSimp4.1 (same grid as atmos), land: CLM4 (same grid as atmos), ocean: MICOM1.1 (1 degree resolution; 320 x 384 longitude/latitude; 53 levels; top grid cell 0-2.5 m [native model uses hybrid density and generic upper-layer coordinate interpolated to z-level for contributed data]), ocnBgchem: HAMOCC5.1 (same grid as ocean), seaIce: CICE4 (same grid as ocean). The model was run in native nominal resolutions: aerosol: 250 km, atmosphere: 250 km, atmospheric chemistry: 250 km, land: 250 km, ocean: 100 km, ocean biogeochemistry: 100 km, seaIce: 100 km.
NorESM1-F (released in 2018)	NCC (Norwegian Climate Centre)	The model includes the components: atmos: CAM4 (2 degree resolution; 144 x 96; 32 levels; top level 3 mb), land: CLM4, landIce: CISM, ocean: MICOM (1 degree resolution; 360 x 384; 70 levels; top grid cell minimum 0-2.5 m [native model uses hybrid density and generic upper-layer coordinate interpolated to z-level for contributed data]), ocnBgchem: HAMOCC5.1, seaIce: CICE4. The model was run in native nominal resolutions: atmosphere: 250 km, land: 250 km, landIce: 250 km, ocean: 100 km, ocean biogeochemistry: 100 km, seaIce: 100 km.
NorESM2-LM (released in 2017)	NCC (Norwegian Climate Centre)	The model includes the components: aerosol: OsloAero, atmos: CAM-OSLO (2 degree resolution; 144 x 96; 32 levels; top level 3 mb), atmosChem: OsloChemSimp, land: CLM, landIce: CISM, ocean: MICOM (1 degree resolution; 360 x 384; 70 levels; top grid cell minimum 0-2.5 m [native model uses hybrid density and generic upper-layer coordinate interpolated to z-level for contributed data]), ocnBgchem: HAMOCC, seaIce: CICE. The model was run in native nominal resolutions: aerosol: 250 km, atmospheric: 250 km, atmospheric chemistry: 250 km, land: 250 km, landIce: 250 km, ocean: 100 km, ocean biogeochemistry: 100 km, seaIce: 100 km.
NorESM2-MM (released in 2017)	NCC (Norwegian Climate Centre)	The model includes the components: aerosol: OsloAero, atmos: CAM-OSLO (1 degree resolution; 288 x 192; 32 levels; top level 3 mb), atmosChem: OsloChemSimp, land: CLM, landIce: CISM, ocean: MICOM (1 degree resolution; 360 x 384; 70 levels; top grid cell minimum 0-2.5 m [native model uses hybrid density and generic upper-layer coordinate interpolated to z-level for contributed data]), ocnBgchem: HAMOCC, seaIce: CICE. The model was run in native nominal resolutions: aerosol: 100 km, atmosphere: 100 km, atmospheric chemistry: 100 km, land: 100 km, landIce: 100 km, ocean: 100 km, ocean biogeochemistry: 100 km, seaIce: 100 km.
SAM0-UNICON (released in 2017)	SNU (Seoul National University)	The model includes the components: aerosol: MAM3, atmos: CAM5.3 with UNICON (1deg; 288 x 192 longitude/latitude; 30 levels; top level ~2 hPa), land: CLM4.0, ocean: POP2 (Displaced Pole; 320 x 384 longitude/latitude; 60 levels; top grid cell 0-10 m), seaIce: CICE4.0. The model was run in native nominal resolutions: aerosol: 100 km, atmos: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km.
TaiESM1 (released in 2018)	AS-RCEC (Research Center for Environmental Changes)	The model includes the components: aerosol: SNAP (same grid as atmos), atmos: TaiAM1 (0.9x1.25 degree; 288 x 192 longitude/latitude; 30 levels; top level ~2 hPa), atmosChem: SNAP (same grid as atmos), land: CLM4.0 (same grid as atmos), ocean: POP2 (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m), seaIce: CICE4. The model was run in native nominal resolutions: aerosol: 100 km, atmosphere: 100 km, atmospheric chemistry: 100 km, land: 100 km, ocean: 100 km, seaIce: 50 km.
UKESM1-0-LL (released in 2018)	MOHC, NERC, NIMS-KMA, NIWA (Met Office Hadley Centre, Natural Environmental Research Council, National Institute of Meteorological Science / Korean Meteorological Administration (NIMS-KMA), National Institute of Weather and Atmospheric Research (NIWA))	The model includes the components: aerosol: UKCA-GLOMAP-mode, atmos: MetUM-HadGEM3-GA7.1 (N96; 192 x 144 longitude/latitude; 85 levels; top level 85 km), atmosChem: UKCA-StratTrop, land: JULES-ES-1.0, ocean: NEMO-HadGEM3-GO6.0 (eORCA1 tripolar primarily 1 deg with meridional refinement down to 1/3 degree in the tropics; 360 x 330 longitude/latitude; 75 levels; top grid cell 0-1 m), ocnBgchem: MEDUSA2, seaIce: CICE-HadGEM3-GSI8 (eORCA1 tripolar primarily 1 deg; 360 x 330 longitude/latitude). The model was run in native nominal resolutions: aerosol: 250 km, atmosphere: 250 km, atmospheric chemistry: 250 km, land: 250 km, ocean: 100 km, ocean biogeochemistry: 100 km, seaIce: 100 km.

Grids

CMIP6 data is reported either on the model’s native grid or re-gridded to one or more target grids with data variables generally provided near the centre of each grid cell (rather than at the boundaries). For CMIP6 there is a requirement to record both the native grid of the model and the grid of its output (archived in the CMIP6 repository) as a “nominal_resolution”. The "nominal_resolution” enables users to identify which models are relatively high resolution and have data that might be challenging to download and store locally. Information about the grids can be found in the model table above, under 'Model Details' and within the NetCDF file metadata.

Pressure levels

For pressure level data the model output is available on the pressure levels according to the table below. Note that since the model output is standardised all models produce the data on the same pressure levels.

Frequency	Number of Levels	Pressure Levels (hPa)
Daily	8	1000., 850., 700., 500., 250., 100., 50., 10.
Monthly	19	1000., 925., 850., 700., 600., 500., 400., 300., 250., 200., 150., 100., 70., 50., 30., 20., 10., 5., 1.

Ensembles

Each modelling centre typically run the same experiment using the same model with slightly different settings several times to confirm the robustness of results and inform sensitivity studies through the generation of statistical information. A model and its collection of runs is referred to as an ensemble. Within these ensembles, four different categories of sensitivity studies are done, and the resulting individual model runs are labelled by four integers indexing the experiments in each category

e.g. r<W>i<X>p<Y>f<Z>, where W, X, Y and Z are positive integers as defined below:

The first category, labelled realization_index (referred to with letter r), performs experiments which differ only in random perturbations of the initial conditions of the experiment. Comparing different realizations allow estimation of the internal variability of the model climate.
The second category, labelled initialization_index (referred to with letter i), refers to variation in initialisation parameters. Comparing differently initialised output provides an estimate of how sensitive the model is to initial conditions.
The third category, labelled physics_index (referred to with letter p), refers to variations in the way in which sub-grid scale processes are represented. Comparing different simulations in this category provides an estimate of the structural uncertainty associated with choices in the model design.
The fourth category labelled forcing_index (referred to with letter f) is used to distinguish runs of a single CMIP6 experiment, but with different forcings applied.

Parameter listings

Time-Independent parameters are marked with a *

Expand

title	List of parameters

CDS parameter name for CMIP5	ESGF variable id	Long name to be used in CMIP6	Units
2m temperature	tas	Near-Surface Air Temperature	Kelvin
Maximum 2m temperature in the last 24 hours	tasmax	Daily Maximum Near-Surface Air Temperature	Kelvin
Minimum 2m temperature in the last 24 hours	tasmin	Daily Minimum Near-Surface Air Temperature	Kelvin
Maximum 10m wind speed in the last 24 hours	sfcwindmax	Daily Maximum Near-Surface Wind Speed	m s^-1
Skin temperature	ts	Surface Temperature	Kelvin
Mean sea level pressure	psl	Sea Level Pressure	Pa
Surface pressure	ps	Surface Air Pressure	Pa
10m u component of wind	uas	Eastward Near-Surface Wind	m s^-1
10m v component of wind	vas	Northward Near-Surface Wind	m s^-1
10m wind speed	sfcWind	Near-Surface Wind Speed	m s^-1
2m relative humidity	hurs	Near-Surface Relative Humidity	1
2m specific humidity	huss	Near-Surface Specific Humidity	1
Mean precipitation flux	pr	Precipitation	kg m^-2s^-1
Snowfall	prsn	Snowfall Flux	kg m^-2s^-1
Evaporation	evspsbl	Evaporation Including Sublimation and Transpiration	kg m^-2s^-1
Atmosphere water vapor content	prw	Atmosphere Water Vapor Content	kg m^-2
Eastward turbulent surface stress	tauu	Surface Downward Eastward Wind Stress	Pa
Northward turbulent surface stress	tauv	Surface Downward Northward Wind Stress	Pa
Surface latent heat flux	hfls	Surface Upward Latent Heat Flux	W m^-2
Surface sensible heat flux	hfss	Surface Upward Sensible Heat Flux	W m^-2
Surface thermal radiation downwards	rlds	Surface Downwelling Longwave Radiation	W m^-2
Surface upwelling longwave radiation	rlus	Surface Upwelling Longwave Radiation	W m^-2
Surface solar radiation downwards	rsds	Surface Downwelling Shortwave Radiation	W m^-2
Surface upwelling shortwave radiation	rsus	Surface Upwelling Shortwave Radiation	W m^-2
TOA incident solar radiation	rsdt	TOA Incident Shortwave Radiation	W m^-2
TOA outgoing shortwave radiation	rsut	TOA Outgoing Shortwave Radiation	W m^-2
TOA outgoing longwave radiation	rlut	TOA Outgoing Longwave Radiation	W m^-2
TOA outgoing clear-sky shortwave radiation	rsutcs	TOA Outgoing Shortwave Flux Assuming Clear Sky	W m^-2
TOA outgoing clear-sky longwave radiation	rlutcs	TOA Outgoing Longwave Flux Assuming Clear Sky	W m^-2
Total cloud cover	clt	Total Cloud Cover Percentage	1
Air temperature	ta	Air Temperature	K
U-component of wind	ua	Eastward Wind	m s^-1
V-component of wind	va	Northward Wind	m s^-1
Relative humidity	hur	Relative Humidity	1
Specific humidity	hus	Specific Humidity	1
Geopotential height	zg	Geopotential Height	m
Surface snow amount	snw	Surface Snow Amount	kg m^-2
Snow depth	snd	Snow Depth	m
Surface runoff	mrros	Surface Runoff Flux	kg m^-2s^-1
Runoff	mrro	Total Runoff	kg m^-2s^-1
Soil moisture content	mrsos	Moisture in Upper Portion of Soil Column	kg m^-2
Sea-ice area percentage	siconc	Sea-Ice Area Percentage (Ocean Grid)	1
Sea ice thickness	sithick	Sea Ice Thickness	m
Sea ice plus snow amount	simass	Sea-Ice Mass per Area	kg m^-2
Sea ice surface temperature	sitemptop	Surface Temperature of Sea Ice	K
Sea surface temperature	tos	Sea Surface Temperature	K
Sea surface salinity	sos	Sea Surface Salinity	PSU
Sea surface height above geoid	zos	Sea Surface Height Above Geoid	m
Grid-cell area for ocean variables	areacello	Grid-Cell Area for Ocean Variables*	m²
Sea area percentage	sftof	Sea Area Percentage*	%
Grid-cell area for atmospheric grid variables	areacella	Grid-Cell Area for Atmospheric Grid Variables*	m²
Capacity of soil to store water (field capacity)	mrsofc	Capacity of Soil to Store Water (Field Capacity)*	kg m^-2
Percentage of grid cell occupied by land (including lakes)	sftlf	Percentage of the Grid Cell Occupied by Land (Including Lakes)*	%
Land ice area percentage	sftgif	Land Ice Area Percentage*	1
Orography	orog	Surface Altitude*	m

Ensembles

Each modelling centre typically run the same experiment using the same model several times to confirm the robustness of results and inform sensitivity studies through the generation of statistical information. A model and its collection of runs is referred to as an ensemble. Within these ensembles, four different categories of sensitivity studies are done, and the resulting individual model runs are labelled by four integers indexing the experiments in each category

e.g. r<W>i<X>p<Y>f<Z>, where W, X, Y and Z are positive integers as defined below:

The first category, labelled realization_index (referred to with letter r), performs experiments which differ only in random perturbations of the initial conditions of the experiment. Comparing different realizations allow estimation of the internal variability of the model climate.
The second category, labelled initialization_index (referred to with letter i), refers to variation in initialisation parameters. Comparing differently initialised output provides an estimate of how sensitive the model is to initial conditions.
The third category, labelled physics_index (referred to with letter p), refers to variations in the way in which sub-grid scale processes are represented. Comparing different simulations in this category provides an estimate of the structural uncertainty associated with choices in the model design.
The fourth category labelled forcing_index (referred to with letter f) is used to distinguish runs of a single CMIP6 experiment, but with different forcings applied.

Parameter listings

Expand

title	Table 1

Kelvin

CDS parameter name	ESGF variable id	Units
*this needs to be provided by C3S CDS team	tas	Kelvin
	tasmax	Kelvin
	tasmin

Data Format

The CDS subset of CMIP6 data are provided as NetCDF files. NetCDF (Network Common Data Form) is a file format that is freely available and commonly used in the climate modelling community. See more details: What are NetCDF files and how can I read them

...

variable_id: variable is a short variable name, e.g. “tas” for “temperature at the surface”.
table_id: this refers to the MIP table being used. The MIP tables are used to organise the variables. For example, Amon refers to monthly atmospheric variables and Oday contains daily ocean data.
source_id: this refers to the model used that produced the data.
experiment_id: refers to the set of experiments being run for CMIP6. For example, PiControl, historical and 1pctCO2 (1 percent per year increase in CO2).
variant_label: is a label constructed from 4 indices (ensemble identifiers) r<k>i<l>p<m>f<n>r<W>i<X>p<Y>f<Z>, where kW, lK, m Y and n Z are integers.
grid_label: this describes the model grid used. For example, global mean data (gm), data reported on a model's native grid (gn) or regridded data reported on a grid other than the native grid and other than the preferred target grid (gr1).
time_range: the temporal range is in the form YYYYMM[DDHH]-YYYY[MMDDHH], where Y is year, M is the month, D is day and H is hour. Note that day and hour are optional (indicated by the square brackets) and are only used if needed by the frequency of the data. For example, daily data from the 1st of January 1980 to the 31st of December 2010 would be written 19800101-20101231.

...

The CMIP6 data Citation Service provides information for data users on how to cite CMIP6 data and on the data license. The long-term availability and long-term accessibility are granted by the use of DOIs for the landing page e.g . http://doi.org/10.22033/ESGF/CMIP6.1317.

Available CMIP6 data citations are discoverable in the ESGF or in the Citation Search at: http://bit.ly/CMIP6_Citation_Search.

Known issues

CDS users will be directed to the CMIP6 ES-DOC Errata Service for known issues with the wider CMIP6 data pool. Data that is provided to the CDS should not contain any errors or be listed in the Errata service, however this will still be a useful resource for CDS users as data they may be looking for but cannot access may have been withheld from the CDS for justifiable reasons.

...

CDS users will now be able to apply subsetting operations to CMIP6 datasets. This mechanism (the "roocs" WPS framework) that runs at each of the partner sites: CEDA, DKRZ and IPSL. The WPS can receive requests for processing based on dataset identifiers, a temporal range, a bounding box and a range of vertical levels. Each request is converted to a job that is run asynchronously on the processing servers at the partner sites. NetCDF files are generated and the response contains download links to each of the files. Users of the CDS will be able to make subsetting selections using the web forms provided by the CDS catalogue web-interface. More advanced users will be able to define their own API requests in the CDS Toolbox that will call the WPS. Output files will be automatically retrieved so that users can access them directly within the CDS.

How to use the subsetting tool

Walkthrough and screenshots need to be provided by CDS team

References

Durack, P J. (2020) CMIP6_CVs. v6.2.53.5. Available at: https://github.com/WCRP-CMIP/CMIP6_CVs (Accessed: 26 October 2020).

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Key

What are global climate projections?

Global climate projections in the CDS

Experiments in the CDS

Models, grids and pressure levels

Models

Grids

Grids

Pressure levels

Ensembles

Parameter listings

Parameter listings

Data Format

Known issues

References