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The sixth phase of the Coupled Model Intercomparison Project (CMIP6) consists of 134 models from 53 modelling modelling centres (Durack, 2020). CMIP6 data publication began in 2019 and the majority of the data publication will be was completed by in 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).

...

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. These data can be used to assess plausible future changes in the variables provided, under a range of socio-economic pathways.

The CDS subset of CMIP6 data has been through a quality control procedure which ensures a high standard of dependability of the data. It may be for example, that similar Additional 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.

...

Expand
titleClick 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.

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

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

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. 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. SSP2-4.5 is comparable to the CMIP5 experiment RCP4.5.

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. 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 SSP1-2.6 scenario represents the low end of plausible future forcing pathways. SSP1-2.6 depicts a "best case" future from a sustainability perspective.

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. SSP4-6.0 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 SSP4-6.0 scenario fills in the range of medium plausible future forcing pathways. SSP4-6.0 defines the low end of the forcing range for unmitigated SSP baseline scenarios.

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

SSP5-3.4OS

SSP5-3.4OS 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. SSP5-3.4OS 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 SSP5-3.4OS scenario branches from SSP5-8.5 in the year 2040 whereupon it applies substantially negative net emissions. SSP5-3.4OS explores the climate science and policy implications of a peak and decline in forcing during the 21st century. 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.

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. SSP1-1.9 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 SSP1-1.9 scenario fills a gap at the very low end of the range of plausible future forcing pathways. SSP1-1.9 forcing will be substantially below 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, calendars, 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 (ES-DOC) or WDC-climate pages. Sometimes there are differences between the model details reported in the CMIP6 metadata and the source documentation, the models with such discrepancies are marked here with an asterix and further details are provided in a second table below. The grid IDs reported in the final column are explained further under the 'grids' section.


CAS (Chinese Academy of Sciences
Expand
titleClick here to expand...Global climate models included in the CDS


Model Name

Modelling Centre

Model Details 

ACCESS-CM2 (released in 2019)

Grids on the CDS ('gn', 'gr' or 'gr1')

ACCESS-CM2 (released in 2019)

CSIRO-ARCCSS (Commonwealth Scientific and Industrial Research Organisation, Australian Research Council Centre of Excellence for Climate System Science)

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.

'gn'

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.'gn'

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.

'gn'

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.'gn'

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.'gn'

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.'gn'

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.'gn'

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.'gn'

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)

'gn'

CESM2

NCAR (National Center for Atmospheric Research)The model includes the components: aerosol:
IAP AACM
MAM4 (same grid as atmos), atmos:
IAP AGCM 5.0 (Finite difference dynamical core; 256 x 128
CAM6 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude;
35
32 levels; top level 2.
2 hPa
25 mb), atmosChem:
IAP AACM
MAM4 (same grid as atmos), land:
CoLM, ocean: LICOM2.0 (LICOM2.0, primarily 1deg; 362 x 196
CLM5 (same grid as atmos), landIce: CISM2.1, ocean: POP2 (320x384 longitude/latitude;
30
60 levels; top grid cell 0-10 m), ocnBgchem:
IAP OBGCM
MARBL (same grid as ocean), seaIce:
CICE4.
CICE5.1 (same grid as ocean). The model was run in native nominal resolutions: aerosol: 100 km,
atmosphere
atmos: 100 km,
atmospheric chemistry
atmosChem: 100 km, land: 100 km, landIce: 5 km, ocean: 100 km,
ocean biogeochemistry
ocnBgchem: 100 km, seaIce: 100 km.'gn'

CESM2-FV2 (released in 2019)

NCAR (National Center for Atmospheric Research)

The model includes the components:

 

aerosol: MAM4 (same grid as atmos), atmos: CAM6 (

0

1.

9x1

9x2.

25

5 finite volume grid;

288

144 x

192

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:

100

250 km,

atmos

atmosphere:

100

250 km,

atmosChem

atmospheric chemistry:

100

250 km, land:

100

250 km, landIce: 5 km, ocean: 100 km,

ocnBgchem

ocean biogeochemistry: 100 km, seaIce: 100 km.

'gn'

CESM2-

FV2 

WACCM (released in

2019

2018)*

NCAR (National Center for Atmospheric Research)The model includes the components: aerosol: MAM4 (same grid as atmos), atmos:
CAM6
WACCM6 (
1
0.
9x2
9x1.
5
25 finite volume grid;
144
288 x
96
192 longitude/latitude;
32
70 levels; top level
2
4.
25
5e-06 mb), atmosChem: MAM4 (same grid as atmos), land: CLM5 (same grid as atmos), landIce: CISM2.1, ocean: POP2 (
320x384
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:
250
100 km, atmosphere:
250
100 km, atmospheric chemistry:
250
100 km, land:
250
100 km, landIce: 5 km, ocean: 100 km, ocean biogeochemistry: 100 km, seaIce: 100 km.'gn'

CESM2-

WACCM 

WACCM-FV2 (released in

2018

2019)*

NCAR (National Center for Atmospheric Research)The model includes the components: aerosol: MAM4 (same grid as atmos), atmos: WACCM6 (
0
1.
9x1
9x2.
25
5 finite volume grid;
288
144 x
192
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 (
320 x 384
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
250 km, atmosphere:
100
250 km, atmospheric chemistry:
100
250 km, land:
100
250 km, landIce: 5 km, ocean: 100 km, ocean biogeochemistry: 100 km, seaIce: 100 km.
CESM2-WACCM-FV2 
'gn'

CIESM (released in

2019

2017)*

NCAR (National Center for Atmospheric Research
THU (Tsinghua University - Department of Earth System Science)The model includes the components: aerosol: MAM4
(same grid as atmos)
, atmos:
WACCM6 (1.9x2.5 finite volume grid; 144 x 96
CIESM-AM (FV/FD; 288 x 192 longitude/latitude;
70
30 levels; top level
4.5e-06 mb
2.255 hPa), atmosChem:
MAM4 (same grid as atmos)
trop_mam4, land:
CLM5 (same grid as atmos), landIce: CISM2.1
CIESM-LM (modified CLM4.5), ocean:
POP2 (320x384 longitude
CIESM-OM (FD, SCCGrid Displaced Pole; 720 x 560 longitude/latitude;
60
46 levels; top grid cell 0-
10 m), ocnBgchem: MARBL (same grid as ocean
6 m), seaIce:
CICE5.1 (same grid as ocean).
CICE4. The model was run in native nominal resolutions: aerosol:
250
100 km, atmosphere:
250
100 km, atmospheric chemistry:
250
100 km, land:
250 km, landIce: 5 km, ocean:
100 km, ocean
biogeochemistry
:
100
50 km, seaIce:
100
50 km.
'gn', 'gr'

CMCC-CM2-HR4

CIESM 

(released in

2017

2016)

THU
CMCC (
Tsinghua University - Department of Earth System Science
Centro Euro-Mediterraneo per I Cambiamenti Climatici)The model includes the components: aerosol:
MAM4
prescribed MACv2-SP, atmos:
CIESM-AM (FV/FD
CAM4 (1deg; 288 x 192 longitude/latitude;
30
26 levels; top
level 2.255
at ~2 hPa),
atmosChem: trop_mam4,
land:
CIESM-LM (modified
CLM4.5 (SP mode), ocean:
CIESM-OM (FD, SCCGrid Displaced Pole; 720 x 560
NEMO3.6 (ORCA0.25 1/4 deg from the Equator degrading at the poles; 1442 x 1051 longitude/latitude;
46
50 vertical levels; top grid cell 0-
6
1 m), seaIce: CICE4.0.
The model was run in native nominal resolutions: aerosol: 100 km,
atmosphere
atmos: 100 km,
atmospheric chemistry: 100 km,
land: 100 km, ocean:
50
25 km, seaIce:
50
25 km.'gn'

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  
'gn'

CMCC-ESM2 (released in 2017)

CNRM-CERFACS (National Center for Meteorological Research, Météo-France and CNRS laboratory, Climate Modeling and Global change
CMCC (Centro Euro-Mediterraneo per I Cambiamenti Climatici)The model includes the components:
 aerosol: prescribed monthly fields computed by TACTIC_v2 scheme
MAM3, atmos:
Arpege 6
CAM5.3 (
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
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), ocnBgchem: BFM5.2, seaIce:
Gelato 6
CICE4.
1
0.
 
The model was run in native nominal resolutions: aerosol:
250
100 km, atmos:
250
100 km,
atmosChem
land:
250
100 km,
land
ocean:
250
100 km,
ocean
ocnBgchem: 100 km, seaIce: 100 km.'gn'

CNRM-CM6-

1-HR 

1  (released in 2017)

CNRM-
CERFACS 
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
T127; Gaussian Reduced with
181724
24572 grid points in total distributed over
360
128 latitude circles (with
720
256 grid points per latitude circle between
32.2degN and 32.2degS reducing to 18
30degN and 30degS reducing to 20 grid points per latitude circle at
89
88.
6degN
9degN and
89
88.
6degS
9degS); 91 levels; top-level 78.4 km), atmosChem: OZL_v2, land: Surfex 8.0c, ocean: Nemo 3.6 (
eORCA025
eORCA1, tripolar primarily
1/4deg
1deg;
1442
362 x
1050
294 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: Gelato 6.1. The model was run in native nominal resolutions: aerosol:
100
250 km,
atmosphere
atmos:
100
250 km,
atmospheric chemistry
atmosChem:
100
250 km, land:
100
250 km, ocean:
25
100 km, seaIce:
25
100 km.
'gn', gr', 'gr1'

CNRM-

ESM2

CM6-1-

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 (
T127
T359; Gaussian Reduced with
24572
181724 grid points in total distributed over
128
360 latitude circles (with
256
720 grid points per latitude circle between
30degN and 30degS
32.2degN and 32.2degS reducing to
20
18 grid points per latitude circle at
88
89.
9degN
6degN and
88
89.
9degS
6degS); 91 levels; top-level 78.4 km), atmosChem:
REPROBUS-C
OZL_v2, land: Surfex 8.0c, ocean: Nemo 3.6 (
eORCA1
eORCA025, tripolar primarily
1deg
1/4deg;
362
1442 x
294
1050 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
100 km,
atmos
atmosphere:
250
100 km,
atmosChem
atmospheric chemistry:
250
100 km, land:
250
100 km, ocean:
100 km, ocnBgchem: 100
25 km, seaIce:
100
25 km.
E3SM-1-0 
'gn', 'gr'

CNRM-ESM2-1 (released in

2018

2017)

E3SM
CNRM-
Project LLNL (Energy Exascale Earth System Model, Lawrence Livermore National Laboratory
CERFACS (National Center for Meteorological Research, Météo-France and CNRS laboratory, Climate Modeling and Global change)The model includes the components: aerosol:
MAM4 with resuspension, marine organics, and secondary organics (same grid as atmos)
TACTIC_v2, 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). 
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:
100
250 km,
atmosphere
atmos:
100
250 km,
atmospheric chemistry
atmosChem:
100
250 km, land: 250 km, ocean: 100 km,
ocean
ocnBgchem:
50
100 km, seaIce:
50
100 km.'gn', gr', 'gr1'

E3SM-1-

1 

0 (released in

2019

2018)

E3SM-
Project RUBISCO 
Project LLNL (Energy Exascale Earth System Model, 
Reducing Uncertainty in Biogeochemical Interactions through Synthesis and COmputation
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.
1
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.
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
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.
1
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),
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.'gr'

E3SM-1-

1-ECA 

1 (released in 2019)

E3SM-
Project  
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
Equilibrium Chemistry Approximation to represent
Converging Trophic Cascade plant and soil carbon and nutrient mechanisms
especially
to represent carbon, nitrogen and phosphorus
limitation
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.
'gr'

E3SM-1-1-ECA 

EC-Earth3 

(released in 2019)

EC
E3SM-
Earth-Consortium
Project  (Energy Exascale Earth System Model)The model includes the components:
 atmos: IFS cy36r4 (TL255, linearly reduced Gaussian grid equivalent to 512 x 256 longitude/latitude; 91
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.
01
1 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
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-
1 m
10 m), ocnBgchem: BEC (Biogeochemical Elemental Cycling model, NPZD-type with C/N/P/Fe/Si/O; same grid as ocean), seaIce:
LIM3. 
MPAS-Seaice (v6.0; same grid as ocean). The model was run
 
in native nominal resolutions:
atmos
aerosol: 100 km,
land
atmosphere: 100 km,
ocean
atmospheric chemistry: 100 km,
seaIce
land: 100 km
.
, ocean: 50 km, ocean biogeochemistry: 50 km, seaIce: 50 km.'gr'

EC-Earth3 

EC-Earth3-LR  

(released in 2019)

EC-Earth-ConsortiumThe model includes the components: atmos: IFS cy36r4 (
TL159
TL255, linearly reduced Gaussian grid equivalent to
320
512 x
160
256 longitude/latitude;
62
91 levels; top-level
5
0.01 hPa), land: HTESSEL (land surface scheme built-in IFS), ocean: NEMO3.6 (ORCA1 tripolar primarily 1
degree
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
run in native nominal resolutions: atmos:
250
100 km, land:
250
100 km, ocean: 100 km, seaIce: 100 km.'gn', 'gr'

EC-Earth3-

Veg 

AerChem (released in 2019)

EC-Earth-ConsortiumThe model includes the components
: 
: aerosol: M5 (3 x 2 degrees; 120 x 90 longitude/latitude; 34 levels; top level: 0.1 hPa), atmos: IFS cy36r4 (TL255, linearly reduced Gaussian grid equivalent to 512 x 256 longitude/latitude; 91 levels; top
-
level 0.01 hPa), atmosChem: TM5 (3 x 2 degrees; 120 x 90 longitude/latitude; 34 levels; top level: 0.1 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.
 
'gn', 'gr'
The model was run in native nominal resolutions: atmos: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km.

EC-Earth3-

Veg-LR 

CC  (released in 2019)

EC-Earth-Consortium

The model includes the components: atmos: IFS cy36r4 (

TL159

TL255, linearly reduced Gaussian grid equivalent to

320 x 160

512 x 256 longitude/latitude; 91 levels; top level 0.01 hPa), atmosChem: TM5 (3 x 2 degrees; 120 x 90 longitude/latitude;

62

34 levels; top

-

level

5

: 0.1 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), ocnBgchem: PISCES v2, seaIce: LIM3.

 

The model was run in native nominal resolutions: atmos: 100 km, atmosChem: 250 km, land:

250

100 km, ocean: 100 km, ocnBgchem: 100 km, seaIce: 100 km.

FGOALS-f3-L 

'gn', 'gr'

EC-Earth3-Veg (released in

2017

2019)

CAS (Chinese Academy of Sciences)
EC-Earth-ConsortiumThe model includes the components: atmos:
FAMIL2.2 (Cubed-sphere, c96; 360 x 180
IFS cy36r4 (TL255, linearly reduced Gaussian grid equivalent to 512 x 256 longitude/latitude;
32
91 levels; top-level
2
0.
16
01 hPa), land:
CLM4.0
HTESSEL (land surface scheme built-in IFS) and LPJ-GUESS v4, ocean:
LICOM3
NEMO3.
0 (LICOM3.0, tripolar primarily 1deg; 360 x 218
6 (ORCA1 tripolar primarily 1 degree with meridional refinement down to 1/3 degree in the tropics; 362 x 292 longitude/latitude;
30
75 levels; top grid cell 0-
10
1 m), seaIce:
CICE4
LIM3.
0.
 The model was
run
run in native nominal resolutions:
atmosphere
atmos: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km.
FGOALS-g3 
'gn', 'gr'

EC-Earth3-Veg-LR (released in

2017

2019)

CAS (Chinese Academy of Sciences)
EC-Earth-ConsortiumThe model includes the components: atmos:
GAMIL3 (180 x 80
IFS cy36r4 (TL159, linearly reduced Gaussian grid equivalent to 320 x 160 longitude/latitude;
26
62 levels; top-level
2.19hPa
5 hPa), land:
CAS-LSM
HTESSEL (land surface scheme built-in IFS) and LPJ-GUESS v4, ocean:
LICOM3
NEMO3.
0 (LICOM3.0, tripolar primarily 1deg; 360 x 218
6 (ORCA1 tripolar primarily 1 degree with meridional refinement down to 1/3 degree in the tropics; 362 x 292 longitude/latitude;
30
75 levels; top grid cell 0-
10
1 m), seaIce:
CICE4
LIM3.
0.
 The model was run in native nominal resolutions:
atmosphere
atmos: 250 km, land: 250 km, ocean: 100 km, seaIce: 100 km.
FIO-ESM-2-0 
'gn', 'gr'

FGOALS-f3-L (released in

2018

2017)

FIO-QLNM (First Institute of Oceanography (FIO) and Qingdao National Laboratory for Marine Science and Technology (QNLM))
CAS (Chinese Academy of Sciences)The model includes the components
: aerosol
:
Prescribed monthly fields,
atmos:
CAM4 (0.9x1.25 finite volume grid; 192 x 288
FAMIL2.2 (Cubed-sphere, c96; 360 x 180 longitude/latitude;
26
32 levels; top level
~2
2.16 hPa), land: CLM4.0
(same grid at atmos)
, ocean:
POP2-W (POP2 coupled with MASNUM surface wave model, Displaced Pole; 320 x 384
LICOM3.0 (LICOM3.0, tripolar primarily 1deg; 360 x 218 longitude/latitude;
60
30 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
'gn', 'gr'

FGOALS-g3 (released in

2018

2017)*

NOAA-GFDL (National Oceanic and Atmospheric Administration, Geophysical Fluid Dynamics Laboratory
CAS (Chinese Academy of Sciences)The model includes the components:
 aerosol: interactive,
atmos:
GFDL-AM4.0 (Cubed-sphere (c96) - 1 degree nominal horizontal resolution; 360 x 180
GAMIL3 (180 x 80 longitude/latitude;
33
26 levels; top level
1 hPa
2.19hPa),
atmosChem: fast chemistry, aerosol only,
land:
GFDL
CAS-
LM4.0
LSM,
landIce
ocean:
GFDL-LM4
LICOM3.0
. The model was
(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:
aerosol
atmosphere:
100
250 km,
atmos
land:
100
250 km,
atmosChem
ocean: 100 km,
land
seaIce: 100 km
, landIce: 100 km.
.'gn'

FIO-ESM-2-0 

GFDL-CM4

(released in 2018)

NOAA-GFDL (National Oceanic and Atmospheric Administration, Geophysical Fluid Dynamics Laboratory
FIO-QLNM (First Institute of Oceanography (FIO) and Qingdao National Laboratory for Marine Science and Technology (QNLM))The model includes the components:
 
aerosol:
interactive
Prescribed monthly fields, atmos:
GFDL-AM4.0.1 (Cubed-sphere (c96) - 1 degree nominal horizontal resolution; 360 x 180
CAM4 (0.9x1.25 finite volume grid; 192 x 288 longitude/latitude;
33
26 levels; top level
1
~2 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
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-
2
10 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). 
CICE4.0 (same grid as ocean). The model was run in native nominal resolutions: aerosol: 100 km,
atmos
atmosphere: 100 km,
atmosChem: 100 km,
land: 100 km,
landIce
ocean: 100
km, ocean: 25
km,
ocnBgchem: 25 km,
seaIce:
25
100 km.'gn'

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.'gr', 'gr1'

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.'gn'

GISS-E2-1-

H 

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 
'gn', 'gr'

HadGEM3-GC31-LL (released in

2019

2016)

NASA-GISS  (National Oceanic and Atmospheric Administration, Goddard Institute for Space Studies
MOHC NERC (Met Office Hadley Centre, Natural Environmental Research Council)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
UKCA-GLOMAP-mode, atmos: MetUM-HadGEM3-GA7.1 (N96; 192 x 144 longitude/latitude;
102
85 levels; top level
0.002 hPa
85 km),
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
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-
10m
1 m), seaIce:
GISS SI
CICE-HadGEM3-GSI8 (eORCA1 tripolar primarily 1 deg; 360 x 330 longitude/latitude). The model was run in native nominal resolutions: aerosol:
250
100 km, atmosphere:
250
100 km,
atmospheric chemistry
land:
250
100 km,
land: 250 km, landIce: 250 km,
ocean:
100
25 km, seaIce:
100
25 km.'gn', 'gr'

HadGEM3-GC31-

LL

MM (released in 2016)

MOHC NERC
MOHC (Met Office Hadley Centre
, Natural Environmental Research Council
)The model includes the components:
 
aerosol: UKCA-GLOMAP-mode, atmos: MetUM-HadGEM3-GA7.1 (
N96
N216;
192
432 x
144
324 longitude/latitude; 85 levels; top level 85 km), land: JULES-HadGEM3-GL7.1, ocean: NEMO-HadGEM3-GO6.0 (
eORCA1
eORCA025 tripolar primarily
1 deg with meridional refinement down to 1/3 degree in the tropics; 360 x 330
0.25 deg; 1440 x 1205 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: CICE-HadGEM3-GSI8 (
eORCA1
eORCA025 tripolar primarily
1
0.25 deg;
360
1440 x
330
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.
HadGEM3-GC31-MM 
'gn', 'gr'

IITM-ESM  (released in

2016

2015)

MOHC (Met Office Hadley Centre
CCCR-IITM (Centre for Climate Change Research, Indian Institute of Tropical Meteorology)The model includes the components: aerosol:
UKCA-GLOMAP-mode
prescribed MAC-v2, atmos:
MetUM-HadGEM3-GA7.1 (N216; 432 x 324
IITM-GFSv1 (T62L64, Linearly Reduced Gaussian Grid; 192 x 94 longitude/latitude;
85
64 levels; top level
85 km
0.2 mb), land:
JULES-HadGEM3-GL7
NOAH LSMv2.7.1, ocean:
NEMO-HadGEM3-GO6.0 (eORCA025 tripolar primarily 0.25 deg; 1440 x 1205
MOM4p1 (tripolar, primarily 1deg; 360 x 200 longitude/latitude;
75
50 levels; top grid cell 0-
1
10 m),
seaIce: CICE-HadGEM3-GSI8 (eORCA025 tripolar primarily 0.25 deg; 1440 x 1205 longitude/latitude).
ocnBgchem: TOPAZv2.0, seaIce: SISv1.0. The model was run in native nominal resolutions: aerosol:
100
250 km, atmosphere:
100
250 km, land: 250 km, ocean: 100 km, ocean biogeochemistry:
25
100 km, seaIce:
25
100 km.
IITM-ESM  
'gn'

INM-CM4-8 (released in

2015

2016)

CCCR-IITM (Centre for Climate Change Research, Indian Institute of Tropical Meteorology
INM (Institute of Numerical Mathematics)The model includes the components: aerosol:
prescribed MAC
INM-
v2
AER1, atmos:
IITM
INM-AM4-
GFSv1 (T62L64, Linearly Reduced Gaussian Grid; 192 x 94
8 (2x1.5; 180 x 120 longitude/latitude;
64
21 levels; top level sigma = 0.
2 mb
01), land:
NOAH LSMv2.7.1
INM-LND1, ocean:
MOM4p1 (tripolar, primarily 1deg
INM-OM5 (North Pole shifted to 60N, 90E; 360 x
200
318 longitude/latitude;
50
40 levels;
top grid cell 0-10 m), ocnBgchem: TOPAZv2.0
sigma vertical coordinate), seaIce:
SISv1.0
INM-ICE1. The model was run in native nominal resolutions: aerosol:
250
100 km, atmosphere:
250
100 km, land
: 250 km, ocean
: 100 km, ocean
biogeochemistry
: 100 km, seaIce: 100 km.'gr1'

INM-

CM4

CM5-

8

0 (released in 2016)

INM
INM (Institute of Numerical Mathematics)The model includes the components: aerosol: INM-AER1, atmos: INM-
AM4
AM5-
8
0 (2x1.5; 180 x 120 longitude/latitude;
21
73 levels; top level sigma = 0.
01
0002), land: INM-LND1, ocean: INM-OM5 (North Pole shifted to 60N, 90E
; 360 x 318
. 0.5x0.25; 720 x 720 longitude/latitude; 40 levels; vertical 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
50 km, seaIce:
100
50 km.
INM-CM5-0
'gr1'

IPSL-CM5A2-INCA (released in

2016

2019)

INM (Institute of Numerical Mathematics
IPSL (Institut Pierre‐Simon Laplace)The model includes the components: aerosol:
INM-AER1
INCA v6 NMHC-AER-S, atmos:
INM-AM5-0 (2x1.5; 180 x 120
LMDZ (APv5; 96 x 96 longitude/latitude;
73
39 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
80000 m), atmosChem: INCA v6 NMHC-AER-S, land: ORCHIDEE (IPSLCM5A2.1, Water/Carbon/Energy mode), ocean: NEMO-OPA (v3.6, ORCA2 tripolar primarily 2deg; 182 x 149 longitude/latitude; 31 levels; top grid cell 0-10 m), ocnBgchem: NEMO-PISCES, seaIce: NEMO-LIM2. The model was run in native nominal resolutions::
aerosol: 100
500 km, atmos: 500 km,
atmosphere
atmosChem:
100
500 km, land:
100
500 km, ocean: 250 km, ocnBgchem:
50
250 km, seaIce:
50 km.
250 km'gn', 'gr'

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-
'gn', 'gr'

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.'gr'

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.'gr1'

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, https://doi.org/10.1175/1520-0442(1997)010<2963:SFVOTN>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: https://doi.org/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.'gn', 'gr'

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.'gn'

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.
'gn', 'gr1'

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.'gn'

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.'gn'

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.'gn'

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.'gn', 'gr'

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.'gn'

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.'gn'
NorESM1

NorESM2-

F

LM (released in

2018

2017)

NCC
NCC (Norwegian Climate Centre)The model includes the components: aerosol: OsloAero, atmos:
CAM4
CAM-OSLO (2 degree resolution; 144 x 96; 32 levels; top level 3 mb), atmosChem: OsloChemSimp, land:
CLM4
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:
HAMOCC5.1
HAMOCC, seaIce:
CICE4
CICE. The model was
run in
run in native nominal resolutions
: atmosphere
: 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.'gn'

NorESM2-

LM

MM (released in 2017)

NCC (Norwegian Climate Centre)The model includes the components: aerosol: OsloAero, atmos: CAM-OSLO (
2
1 degree resolution;
144
288 x
96
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
run in native nominal resolutions: aerosol:
250
100 km,
atmospheric
atmosphere:
250
100 km, atmospheric chemistry:
250
100 km, land:
250
100 km, landIce:
250
100 km, ocean: 100 km, ocean biogeochemistry: 100 km, seaIce: 100 km.
NorESM2-MM
'gn'

SAM0-UNICON (released in 2017)

NCC (Norwegian Climate Centre

SNU (Seoul National University)

The model includes the components: aerosol:
OsloAero
MAM3, atmos:
CAM-OSLO (1 degree resolution
CAM5.3 with UNICON (1deg; 288 x 192 longitude/latitude;
32
30 levels; top level
3 mb
~2 hPa),
atmosChem: OsloChemSimp,
land:
CLM, landIce: CISM,
CLM4.0, ocean:
MICOM (1 degree resolution; 360 x 384; 70
POP2 (Displaced Pole; 320 x 384 longitude/latitude; 60 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
10 m), seaIce:
CICE
CICE4.0. The model was run in native nominal resolutions: aerosol: 100 km,
atmosphere
atmos: 100 km,
atmospheric chemistry: 100 km,
land
: 100 km, landIce
: 100 km, ocean: 100 km,
ocean biogeochemistry: 100 km,
seaIce: 100 km.
'gn'

TaiESM1

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)

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.'gn'

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.

'gn', 'gr'



Expand
titleClick here to expand... CMIP6 models with model detail discrepancies

CMIP6 models where there is a discrepancy between some model details reported in the available documentation and the metadata:

Model Name

Model details (WDC-Climate CMIP6 documentation)

Model details (CMIP6 data files metadata) 

CESM2-WACCM

atmos: WACCM6 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 70 levels; top level 4.5e-06 mb)

atmosphere: CAM6 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 70 levels; top level 4.5e-6 mb)

CESM2-WACCM-FV2 

atmos: WACCM6 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 70 levels; top level 4.5e-06 mb)

atmosphere: CAM6 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 70 levels; top level 4.5e-6 mb)

CIESM 

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)

aerosol: prescribed MACv2-SP

atmos: CIESM-AM1.0 (Modified CAM5; 1 degree spectral element; 48602 cells; 30 levels; top level 2.255 hPa)

atmosChem: none

land: CIESM-LM1.0 (Modified CLM4.0)

ocean: CIESM-OM1.0 (Modified POP2; 320 x 384 longitude/latitude; 60 levels; top grid cell 0-10 m)

FGOALS-g3 

atmos: GAMIL3 (180 x 80 longitude/latitude; 26 levels; top level 2.19hPa), 

land: CAS-LSM

atmos: GAMIL2 (180 x 90 longitude/latitude; 26 levels; top level 2.19hPa)

land: CLM4.0

GISS-E2-1-H

Released in 2019

Released in 2016

MCM-UA-1-0


No model details in metadata


Grids

CMIP6 data is available 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). This re-gridding is normally done for models which use native grids other than regular lat-lon grids (e.g. cubed sphere or gaussian), in these cases the output has been re-gridded to a regular lat-lon grid by the modelling centers. For CMIP6 there is a requirement to record both the native grid of the model, and the approximate resolution of the final output data (archived in the CMIP6 repository, and available via the CDS) as a “nominal_resolution”.  This "nominal_resolution” enables users to identify which models have relatively high resolution output. Information about the grids can be found in the model table above, under 'Model Details', and within the NetCDF file metadata.

The column 'Grids on the CDS ('gn', 'gr' or 'gr1')' lists which grid IDs are associated with the data from that model available on the CDS. These labels reflect whether a given set of model data (variable) uploaded to ESGF is on the 

  • native grid of the model component ('gn'),
  • regridded to the regular target grid specified for the particular variable ('gr'),
  • or another target grid ('gr1').

The output from some models has multiple different grid IDs associated with it, due to different model components (atmosphere, land, ocean, cryosphere etc.) being treated differently. This does not necessarily mean the data itself is on a different grid, for example the atmospheric variables maybe on a regular native grid ('gn'), and the ocean variables with an irregular native grid may have been regridded to the atmosphere grid (hence are labelled 'gr'), so they are on the same grid in spite of the fact that their grid ID is different. On the other hand, if a model is only listed as having output on the native grid ('gn'), this does not guarantee that all the data (variable) is on the same grid, as the native grid for different model components can be different.

Note: some data (i.e. variables) have been submitted to ESGF on multiple grids, in these cases only one grid is made available on the CDS (this is decided on a case-by-case basis).

Calendars

Climate models sometime use different calendars, for example Hadley Centre models in CMIP6 use a 360 day calendar, where every month has exactly 30 days. Some models use a fixed 365-day calendar, and others include leap-years. These variations can result in different length time-dimensions if daily data is downloaded, depending on the time period and models selected, or even failed data requests. Users need to be careful, when using the CDS user interface download form or API, to avoid selecting days which may not be available in the calendar of the given model (for example requests referring to day 31 for the Hadley Centre models would fail, because they have a 360 day calendar).The CDS form for CMIP6 currently assumes a standard calendar, so allows the selection of such missing days, and conversely may not allow selection of all days from models with non-standard calendars (but this data can be retrieved using the API). 

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

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

...

  • 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 *

  • 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 dash in the time resolution column. Please note that some parameters defined at pressure levels, such as 1000 hPa temperature, may contain missing data where they are not defined (so the fields look incomplete over terrain) or are filled with interpolated values (different modelling centres may have different approaches). This happens when the pressure level falls below the orography.


Expand
titleList of parameters


wind geoid
CDS parameter name for CMIP6Time resolution available

 ESGF variable id

CDS parameter name for CMIP5

 Units

Near-surface air temperaturemonthly, daily

 tas

2m temperature

Kelvin

Daily maximum near-surface air temperaturemonthly, daily

 tasmax

Maximum 2m temperature in the last 24 hours

Kelvin

Daily minimum near-surface air temperaturemonthly, daily

 tasmin

Minimum 2m temperature in the last 24 hours 

Kelvin

Surface temperaturemonthlytsSkin temperatureKelvin
Sea level pressuremonthly, dailypslMean sea level pressurePa
Surface air pressuremonthlypsSurface pressurePa
Eastward near-surface windmonthlyuas10m u component of windm s-1
Northward near-surface windmonthlyvas10m v component of windm s-1
Near-surface wind speedmonthly, dailysfcWind10m wind speedm s-1
Near-surface relative humiditymonthlyhurs2m relative humidity1
Near-surface specific humiditymonthly, dailyhuss2m specific humidity1
Precipitationmonthly, dailyprMean precipitation fluxkg m-2s-1
Snowfall fluxmonthlyprsnSnowfall

kg m-2 s-1

Evaporation Including sublimation and transpirationmonthlyevspsblEvaporation

kg m-2 s-1

Surface downward eastward wind stressmonthlytauuEastward turbulent surface stressPa
Surface downward northward wind stressmonthlytauvNorthward turbulent surface stressPa
Surface upward latent heat fluxmonthlyhflsSurface latent heat fluxW m-2
Surface upward sensible heat fluxmonthlyhfssSurface sensible heat fluxW m-2 
Surface downwelling longwave radiationmonthlyrldsSurface thermal radiation downwardsW m-2
Surface upwelling longwave radiationmonthlyrlus

Surface upwelling longwave radiation

W m-2
Surface downwelling shortwave radiationmonthlyrsds

Surface solar radiation downwards

W m-2
Surface upwelling shortwave radiationmonthlyrsus

Surface upwelling shortwave radiation

W m-2
TOA incident shortwave radiationmonthlyrsdt

TOA incident solar radiation

W m-2
TOA outgoing shortwave radiationmonthlyrsutTOA outgoing shortwave radiationW m-2
TOA outgoing longwave radiationmonthlyrlutTOA outgoing longwave radiationW m-2
Total cloud cover percentagemonthlycltTotal cloud cover%
Air temperaturemonthlytaAir temperatureK
Eastward windmonthlyuaU-component of windm s-1
Northward windmonthlyvaV-component of windm s-1
Relative humiditymonthlyhurRelative humidity1
Specific humiditymonthlyhusSpecific humidity 1
Geopotential heightmonthlyzgGeopotential heightm
Surface snow amountmonthlysnwSurface snow amountkg m-2
Snow depthmonthlysndSnow depthm
Total runoffmonthlymrroRunoffkg m-2 s-1
Moisture in upper portion of soil columnmonthlymrsosSoil moisture contentkg m-2
Sea-Ice area percentage (ocean grid)monthlysiconcSea-ice area percentage1
Sea Ice thicknessmonthlysithickSea ice thicknessm
Sea-Ice mass per areamonthlysimassSea ice plus snow amountkg m-2
Surface temperature of sea IcemonthlysitemptopSea ice surface temperatureK
Sea surface temperaturemonthlytosSea surface temperatureK
Sea surface salinitymonthlysosSea surface salinityPSU
Sea surface height above geoidmonthlyzosSea surface height above m
Grid-cell area for ocean variables*areacelloNOT AVAILABLEm2
Sea floor depth below geoid*depthoNOT AVAILABLEm
Sea area percentage*sftofNOT AVAILABLE%
Grid-cell area for atmospheric grid variables*areacellaNOT AVAILABLEm2
Capacity of soil to store water (field capacity)*mrsofcNOT AVAILABLEkg m-2
Percentage of the grid cell occupied by land (including lakes)*sftlfNOT AVAILABLE%
Land ice area percentage*sftgifNOT AVAILABLE1
Surface altitude*orogNOT AVAILABLEm

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

 A CMIP6 NetCDF file in the CDS contains:

  • Global metadata: these fields can describe many different aspects of the file such as
    • when the file was created
    • the name of the institution and model used to generate the file
    • Information on the horizontal grid and regridding procedure
    • links to peer-reviewed papers and technical documentation describing the climate model,
    • links to supporting documentation on the climate model used to generate the file,
    • software used in post-processing.
  • variable dimensions: such as time, latitude, longitude and height
  • variable data: the gridded data
  • variable metadata: e.g. the variable units, averaging period (if relevant) and additional descriptive data

File naming conventions

When you download a CMIP6 file from the CDS it will have a naming convention that is as follows:

<variable_id>_<table_id>_<source_id>_<experiment_id>_<variant_label>_<grid_label>_<time_range>.nc

 Where:

  • 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<W>i<X>p<Y>f<Z>, where W, K, Y and 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.

Quality control of the CDS-CMIP6 subset

The CDS subset of the CMIP6 data have been through a set of quality control checks before being made available through the CDS. The objective of the quality control process is to ensure that all files in the CDS meet a minimum standard. Data files were required to pass all stages of the quality control process before being made available through the CDS. Data files that fail the quality control process are excluded from the CDS-CMIP6 subset, data providers are contacted and if they are able to release a new version of the data with the error corrected then providing this data passes all remaining QC steps may be available for inclusion in the next CMIP6 data release.

 The main aim of the quality control procedure is to check for metadata and gross data errors in the CMIP6 files and datasets. A brief description of each of the QC checks is provided here:

  1. CF-Checks: The CF-checker tool checks that each NetCDF4 file in a given dataset is compliant with the Climate and Forecast (CF) conventions, compliance ensures that the files are interoperable across a range of software tools.
  2. PrePARE: The PrePARE software tool is provided by PCMDI (Program for Climate Model Diagnosis and Intercomparison) to verify that CMIP6 files conform to the CMIP6 data protocol. All CMIP6 data should meet this required standard however this check is included to ensure that all data supplied to the CDS have passed this QC test.
  3. nctime: The nctime checker checks the temporal axis of the NetCDF files. For each NetCDF file the temporal element of the file is compared with the time axis data within the file to ensure consistency. For a time-series of data comprised of several NetCDF files nctime ensures that the entire timeseries is complete, that there are no temporal gaps or overlaps in either the filename or in the time axes within the files.
  4. Errata: The dataset is checked to ensure that no outstanding Errata record exists.
  5. Data Ranges: A set of tests on the extreme values of the variables are performed, this is used to ensure that the values of the variables fall into physically realistic ranges.
  6. Handle record consistency checks: This check ensures that the version of the dataset used is the most recently published dataset by the modelling centre, it also checks for any inconsistency in the ESGF publication and excludes any datasets that may have an inconsistent ESGF publication metadata.
  7. Exists at all partner sites: It is asserted that each dataset exists at all three partner sites CEDA, DKRZ and IPSL.

It is important to note that passing these quality control tests should not be confused with validity: for example, it will be possible for a file to pass all QC steps but contain errors in the data that have not been identified by either data providers or data users.

 In cases where the quality control picks up errors that are related to minor technical details of the conventions, or behavior that is in line with expectations for climate model output despite being unexpected in a physical system, the data will be published with details of the errors referenced in the documentation. An example of the 2nd type of error is given by negative salinity values which occur in one model as a result of rapid release of fresh water from melting sea-ice. These negative values are part of the noise associated with the numerical simulation and reflect what is happening in the numerical model.

Citation, license and PID information

In general the CMIP6 data Citation Service provides information for users on how to cite CMIP6 data and also information on the data licenses.

The users can decide on what level they want to refer to the CMIP6 datasets. 

The highest level is the one provided by the CDS with the use of the following DOI: 10.24381/cds.c866074c (available also at the right-hand-side of the entry). The users can refer to any data with this DOI, which are available in the CMIP6 catalogue entry in the CDS.

The CMIP6 citation Search is at http://bit.ly/CMIP6_Citation_Search. Citations for CDS CMIP6 data available in the CDS are discoverable in the ESGF on model and experiment levels (please note that these linked files are csv files, which can be looked at after downloading them). 

The CMIP6 datasets are also labelled by the so called Persistent Identifiers (PIDs). PIDs are assigned to each version of every file and dataset. These are unique identifiers of the data and they are available in the header of the netcdf datafiles. The PIDs are also provided on dataset and file levels (please note that these files are csv files, which can be looked at after downloading them).

Known issues

...

geoidm
Grid-cell area for ocean variables-areacelloNOT AVAILABLEm2
Sea floor depth below geoid-depthoNOT AVAILABLEm
Sea area percentage-sftofNOT AVAILABLE%
Grid-cell area for atmospheric grid variables-areacellaNOT AVAILABLEm2
Capacity of soil to store water (field capacity)-mrsofcNOT AVAILABLEkg m-2
Percentage of the grid cell occupied by land (including lakes)-sftlfNOT AVAILABLE%
Land ice area percentage-sftgifNOT AVAILABLE1
Surface altitude-orogNOT AVAILABLEm


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

 A CMIP6 NetCDF file in the CDS contains:

  • Global metadata: these fields can describe many different aspects of the file such as
    • when the file was created
    • the name of the institution and model used to generate the file
    • Information on the horizontal grid and regridding procedure
    • links to peer-reviewed papers and technical documentation describing the climate model,
    • links to supporting documentation on the climate model used to generate the file,
    • software used in post-processing.
  • variable dimensions: such as time, latitude, longitude and height
  • variable data: the gridded data
  • variable metadata: e.g. the variable units, averaging period (if relevant) and additional descriptive data

File naming conventions

When you download a CMIP6 file from the CDS it will have a naming convention that is as follows:

<variable_id>_<table_id>_<source_id>_<experiment_id>_<variant_label>_<grid_label>_<time_range>.nc

 Where:

  • 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<W>i<X>p<Y>f<Z>, where W, K, Y and 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.

Quality control of the CDS-CMIP6 subset

The CDS subset of the CMIP6 data have been through a set of quality control checks before being made available through the CDS. The objective of the quality control process is to ensure that all files in the CDS meet a minimum standard. Data files were required to pass all stages of the quality control process before being made available through the CDS. Data files that fail the quality control process are excluded from the CDS-CMIP6 subset, data providers are contacted and if they are able to release a new version of the data with the error corrected then providing this data passes all remaining QC steps may be available for inclusion in the next CMIP6 data release.

 The main aim of the quality control procedure is to check for metadata and gross data errors in the CMIP6 files and datasets. A brief description of each of the QC checks is provided here:

  1. CF-Checks: The CF-checker tool checks that each NetCDF4 file in a given dataset is compliant with the Climate and Forecast (CF) conventions, compliance ensures that the files are interoperable across a range of software tools. When CF-checker 1.7 is run on the current data some remaining issues are highlighted, particularly for lat, lon and time bounds.
  2. PrePARE: The PrePARE software tool is provided by PCMDI (Program for Climate Model Diagnosis and Intercomparison) to verify that CMIP6 files conform to the CMIP6 data protocol. All CMIP6 data should meet this required standard however this check is included to ensure that all data supplied to the CDS have passed this QC test.
  3. nctime: The nctime checker checks the temporal axis of the NetCDF files. For each NetCDF file the temporal element of the file is compared with the time axis data within the file to ensure consistency. For a time-series of data comprised of several NetCDF files nctime ensures that the entire timeseries is complete, that there are no temporal gaps or overlaps in either the filename or in the time axes within the files.
  4. Errata: The dataset was checked to ensure that no outstanding Errata record existed at the time of publication.
  5. Data Ranges: A set of tests on the extreme values of the variables are performed, this is used to ensure that the values of the variables fall into physically realistic ranges.
  6. Handle record consistency checks: This check ensures that the version of the dataset used is the most recently published dataset by the modelling centre, it also checks for any inconsistency in the ESGF publication and excludes any datasets that may have inconsistent high-level metadata.
  7. Exists at all partner sites: It is asserted that each dataset exists at all three partner sites CEDA, DKRZ and IPSL.

It is important to note that passing these quality control tests should not be confused with validity: for example, it will be possible for a file to pass all QC steps but contain errors in the data that have not been identified by either data providers or data users.

 In cases where the quality control picks up errors that are related to minor technical details of the conventions, or behavior that is in line with expectations for climate model output despite being unexpected in a physical system, the data will be published with details of the errors referenced in the documentation. An example of the 2nd type of error is given by negative salinity values which occur in one model as a result of rapid release of fresh water from melting sea-ice. These negative values are part of the noise associated with the numerical simulation and reflect what is happening in the numerical model.

Citation, license and PID information

In general the CMIP6 data Citation Service provides information for users on how to cite CMIP6 data and also information on the data licenses.

The users can decide on what level they want to refer to the CMIP6 datasets. 

The highest level is the one provided by the CDS with the use of the following DOI: 10.24381/cds.c866074c (available also at the right-hand-side of the entry). The users can refer to any data with this DOI, which are available in the CMIP6 catalogue entry in the CDS.

The CMIP6 citation Search is at http://bit.ly/CMIP6_Citation_Search. Citations for CDS CMIP6 data available in the CDS are discoverable in the ESGF on model and experiment levels (please note that these linked files are csv files, which can be looked at after downloading them). 

The CMIP6 datasets are also labelled by the so called Persistent Identifiers (PIDs). PIDs are assigned to each version of every file and dataset. These are unique identifiers of the data and they are available in the header of the netcdf datafiles. The PIDs are also provided on dataset and file levels (please note that these files are csv files, which can be looked at after downloading them).

Known issues

CDS users are directed to the CMIP6 ES-DOC Errata Service for known issues with the wider CMIP6 data pool. Data that is provided to the CDS either should not contain any errors, or minor errors should be listed in the Errata Service. Additionally, the Errata Service is also a useful resource for CDS users as data may have been withheld from the CDS for justifiable reasons.

Some models currently have either missing historical or scenario data for some variables, which is in the process of being resolved. Some details are given in the table below:

Model

Missing variable data details

MPI-ESM-1-2-HAM

    • no historical data on the CDS (other than fixed fields)

EC-Earth3

    • no historical data on the CDS (other than fixed fields)
    • SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP3-8.5 - only fixed fields

EC-Earth3-Veg

    • no historical data on the CDS (other than fixed fields)

MIROC-ES2H

    • only historical data available

EC-Earth3-Veg-LR

    • missing historical data for some variables

NORESM2-LM

    • missing historical data for some variables

GISS-E2-1-G

    • missing historical data for some variables


Subsetting and downloading data

...

When CMIP6 data is downloaded from the Climate Data Store, information about any additional processing applied to the data (such as temporal or spatial subsetting) is included in both PNG and JSON form. These provenance files will be zipped up with the retrieved data and named provenance.png and provenance.json, which describe the software used and the methods applied to the data following the W3C PROV standard. For more information about how to interpret these files, please see https://rook-wps.readthedocs.io/en/latest/prov.html.

Additional resources

A training resource in python is available via a Jupyter Notebook on the C3S data tutorials page here: https://ecmwf-projects.github.io/copernicus-training-c3s/projections-cmip6.html

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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