Table of Contents

Introduction

What are global climate projections?

Global climate projections are climate model simulations which 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 conclusion of the IPCC 5th Assessment Report (published in 2013) 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”. 

The Climate Model Intercomparison Project (CMIP)

The Climate Model Intercomparison Project (CMIP) was established in 1995 by the World Climate Research Program (WCRP) to provide climate scientists with a database of coupled Global Circulation Model (GCM) simulations.

The CMIP process involves institutions (such as national meteorological centres or research institutes) from around the world running their climate models with an agreed set of input parameters. The modelling centres produce a set of standardised output, when combined these produce a multi-model dataset that can be shared internationally between modelling centres and the results compared. 

Analysis of the CMIP data allows for improving understanding of

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


Comparison of different climate models allows for 

  • 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.

CMIP5

The fifth phase of Coupled Model Intercomparison Project (CMIP5, 2008-2012) involved 24 modelling centres running their climate models under the prescribed conditions to produce the multi-model dataset designed to advance our knowledge of climate (Taylor et al. 2012). The scientific analyses from CMIP5 were used extensively in the Intergovernmental Panel on Climate Change (IPCC) 5th Assessment Report (IPCC AR5), published in September 2013. 

The CMIP5 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 for their scientists to utilise. A quality-controlled subset of CMIP5 data are made available through the Climate Data Store (CDS) for the users of the Copernicus Climate Change Service (C3S).

To obtain full details of the whole CMIP5 data archive please refer to the full documentation at the Program for Climate Model Diagnosis & Intercomparison (PCMDI). An introductory factsheet for an overview of an IPCC subset also provides a useful guide to the CMIP5 data. 

CMIP6

The sixth phase of the Coupled Model Intercomparison Project (CMIP6) is in progress. Approximately 40 modelling centres are participating in this phase of CMIP. During the period 2019-2020 modelling centres are standardising and releasing their data to be distributed internationally through the Earth System Grid Federation (ESGF). It is expected that the Climate Data Store (CDS) will begin making CMIP6 data available from 2021. 

Global climate projections in the CDS

The global climate projections in the Climate Data Store (CDS) are a quality-controlled subset of the wider CMIP5 data. These data represent only a small subset of CMIP5 archive. A set of 50 core variables from the CMIP5 archive were identified for the CDS. These are the most used of the CMIP5 data. These variables are provided from seven of the most popular CMIP5 experiments.  

The CDS subset of CMIP5 data have been through a metadata quality control procedure which ensures a high standard of reliability of the data. It may be for example that similar data can be found in the main CMIP5 archive however these data come with no quality assurance and may have metadata errors or omissions. The quality-control process means that the CDS subset of CMIP5 data is further reduced to exclude data that have metadata errors or inconsistencies. It is important to note that passing of the quality control should not be confused with validity: for example, it will be possible for a file to have fully compliant metadata but contain gross errors in the data that have not been noted. In other words, it means that the quality control is purely technical and does not contain any scientific evaluation (for instance consistency check).

Experiments

The CDS-CMIP5 subset consists of the following CMIP5 experiments

  • amip: An atmosphere-only configuration of the model as in the Atmospheric Model Intercomparison Project (AMIP, a pre-cursor to CMIP). Models impose sea surface temperatures (SSTs) & sea ice (from observations over 1979 to at least 2008), but with other conditions including CO2 concentrations and aerosols prescribed in the same way as the ‘historical’ experiment.
  • historical: Models impose changing conditions (consistent with observations from 1850-2005), which may include: atmospheric composition due to both anthropogenic and volcanic influences, solar forcing, emissions or concentrations of short-lived species and natural and anthropogenic aerosols or their precursors, as well as land use.
  • piControl (Pre-industrial Control): Models impose non-evolving, pre-industrial conditions, which may include prescribed atmospheric concentrations or non-evolving emissions of gases, aerosols or their precursors, as well as unperturbed land use.
    • The piControl experiment is often run for a long number of years (500 or more) this allows for the models to reach an equilibrium state however this means that model data from this experiment only have a time element where the year is a modelling year not a representative year. Therefore to avoid confusion this experimental data is currently only available through the CDS API and will not be visible through the data download menu.
  • Scenario experiments RCP2.6, RCP4.5, RCP6.0, RCP8.5: Future projections (2006-2100) forced by RCP2.6, 4.5, 6.0, and 8.5. RCPs (representative concentration pathways) approximately result in radiative forcings of 2.6, 4.5, 6.0 and 8.5 W m-2 at the year 2100 respectively, relative to pre-industrial conditions.

Models, grids and pressure levels

Models 

The models included in the CDS-CMIP5 subset are detailed in the table below, these include most of the models from the main CMIP5 archive. However a small number of models were not included as the data from the models have a research-only restriction on their use, all data in the CDS are released without restriction, therefore, the MIROC and MRI models from Japan are not included. 

The following table contains a list of the global climate models in use in the CDS and a brief description of the model where this information is readily available, further details can be found on the Earth System Documentation site.

Model name

Modelling centre

Model details

ACCESS1-0

CSIRO (Commonwealth Scientific and Industrial Research Organisation, Australia), and BOM (Bureau of Meteorology, Australia)

ACCESS1-0 2011. Atmosphere: AGCM v1.0 (N96 grid-point, 1.875 degrees EW x approx 1.25 degree NS, 38 levels); ocean: NOAA/GFDL MOM4p1 (nominal 1.0 degree EW x 1.0 degrees NS, tripolar north of 65N, equatorial refinement to 1/3 degree from 10S to 10 N, cosine dependent NS south of 25S, 50 levels); sea ice: CICE4.1 (nominal 1.0 degree EW x 1.0 degrees NS, tripolar north of 65N, equatorial refinement to 1/3 degree from 10S to 10 N, cosine dependent NS south of 25S); land: MOSES2 (1.875 degree EW x 1.25 degree NS, 4 levels;

ACCESS1.3

CSIRO (Commonwealth Scientific and Industrial Research Organisation, Australia), and BOM (Bureau of Meteorology, Australia)

ACCESS1-3 2011. Atmosphere: AGCM v1.0 (N96 grid-point, 1.875 degrees EW x approx 1.25 degree NS, 38 levels); ocean: NOAA/GFDL MOM4p1 (nominal 1.0 degree EW x 1.0 degrees NS, tripolar north of 65N, equatorial refinement to 1/3 degree from 10S to 10 N, cosine dependent NS south of 25S, 50 levels); sea ice: CICE4.1 (nominal 1.0 degree EW x 1.0 degrees NS, tripolar north of 65N, equatorial refinement to 1/3 degree from 10S to 10 N, cosine dependent NS south of 25S); land: CABLE1.0 (1.875 degree EW x 1.25 degree NS, 6 levels;

bcc-csm1-1

Beijing Climate Center(BCC),China Meteorological Administration,China

bcc-csm1-1:atmosphere: BCC_AGCM2.1 (T42L26); land: BCC_AVIM1.0;ocean: MOM4_L40 (tripolar, 1 lon x (1-1/3) lat, L40);sea ice: SIS (tripolar,1 lon x (1-1/3) lat);

bcc-csm1-1-m

Beijing Climate Center(BCC),China Meteorological Administration,China

bcc-csm1-1-m:atmosphere: BCC_AGCM2.2 (T106L26); land: BCC_AVIM1.1;ocean: MOM4_L40v2 (tripolar, 1 lon x (1-1/3) lat, L40);sea ice: SIS (tripolar,1 lon x (1-1/3) lat);

BNU-ESM

GCESS,BNU,Beijing,China

BNU-ESM;

CanAM4

CCCma (Canadian Centre for Climate Modelling and Analysis, Victoria, BC, Canada)

CanAM4 2010 atmosphere: CanAM4 (AGCM15i, T63L35) land: CLASS2.7 (Note: Adjusted Land Cover and soil albedo relative to that used in CanESM2 and CanCM4);

CanCM4

CCCma (Canadian Centre for Climate Modelling and Analysis, Victoria, BC, Canada)

CanCM4 2010 atmosphere: CanAM4 (AGCM15i, T63L35) ocean: CanOM4 (OGCM4.0, 256x192L40) sea ice: CanSIM1 (Cavitating Fluid, T63 Gaussian Grid) land: CLASS2.7;

CanESM2

CCCma (Canadian Centre for Climate Modelling and Analysis, Victoria, BC, Canada)

CanESM2 2010 atmosphere: CanAM4 (AGCM15i, T63L35) ocean: CanOM4 (OGCM4.0, 256x192L40) and CMOC1.2 sea ice: CanSIM1 (Cavitating Fluid, T63 Gaussian Grid) land: CLASS2.7 and CTEM1;

CCSM4

NCAR (National Center for Atmospheric Research) Boulder, CO, USA

CCSM4 (repository tag: ccsm4_0_beta49 compset: BRCP26CN);

CESM1-BGC

NSF/DOE NCAR (National Center for Atmospheric Research) Boulder, CO, USA

CESM1-BGC;

CESM1-CAM5

NSF/DOE NCAR (National Center for Atmospheric Research) Boulder, CO, USA

CESM1-CAM5;

CESM1-FASTCHEM

NSF/DOE NCAR (National Center for Atmospheric Research) Boulder, CO, USA

CESM1-FASTCHEM;

CESM1-WACCM

NSF/DOE NCAR (National Center for Atmospheric Research) Boulder, CO, USA

CESM1-WACCM;

CMCC-CESM

CMCC - Centro Euro-Mediterraneo per i Cambiamenti Climatici, Bologna, Italy

CMCC-CESM;

CMCC-CM

CMCC - Centro Euro-Mediterraneo per i Cambiamenti

CMCC-CM;

CMCC-CMS

CMCC - Centro Euro-Mediterraneo per i Cambiamenti Climatici, Bologna, Italy

CMCC-CMS;

CNRM-CM5

CNRM (Centre National de Recherches Meteorologiques, Meteo-France, Toulouse,France) and CERFACS (Centre Europeen de Recherches et de Formation Avancee en Calcul Scientifique, Toulouse, France)

CNRM-CM5 2010 Atmosphere: ARPEGE-Climat (V5.2.1, TL127L31); Ocean: NEMO (nemo3.3.v10.6.6P, ORCA1degL42); Sea Ice: GELATO (V5.30); River Routing: TRIP (v1); Land: SURFEX (v5.1.c); Coupler : OASIS 3;

CNRM-CM5-2

CNRM (Centre National de Recherches Meteorologiques, Meteo-France, Toulouse, France) and CERFACS (Centre Europeen de Recherches et de Formation Avancee en Calcul Scientifique, Toulouse, France)

CNRM-CM5-2 2010 Atmosphere: ARPEGE-Climat (V5.2.3i, TL127L31); Ocean: NEMO (nemo3.2.v11.3, ORCA1degL42); Sea Ice: GELATO (V5.47f); River Routing: TRIP (v1); Land: SURFEX (v5.1.c); Coupler : OASIS 3;

CSIRO-Mk3-6-0

Australian Commonwealth Scientific and Industrial Research Organization (CSIRO) Marine and Atmospheric Research (Melbourne, Australia) in collaboration with the Queensland Climate Change Centre of Excellence (QCCCE) (Brisbane, Australia)

CSIRO-Mk3-6-0 2010 atmosphere: AGCM v7.3.8 (T63 spectral, 1.875 degrees EW x approx. 1.875 degrees NS, 18 levels); ocean: GFDL MOM2.2 (1.875 degrees EW x approx. 0.9375 degrees NS, 31 levels);

EC-EARTH

EC-EARTH (European Earth System Model)

EC-EARTH 2.3 (2011); atmosphere: IFS (cy31R1+modifications, T159L62); ocean: NEMO (version2+modifications, ORCA1-42lev); sea ice: LIM2; land: HTessel;

FGOALS_g2

IAP (Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China) and THU (Tsinghua University)

FGOALS_g2 2011 atmosphere: GAMIL (gamil2, 128x60L26); ocean: LICOM (licom2, 360x196L30); ice: CICE (cice4_lasg, 360x196L4); land: CLM (clm3, 128x60);

FGOALS-s2; IAP(Institute of Atmospheric Physics),CAS(Chinese Academy of Sciences),Beijing,China

FGOALS-s2 SAMIL 2-4-7


FIO-ESM

FIO(The First Institution of Oceanography,SOA,Qingdao,China)

FIO-ESM

GFDL-CM2p1

NOAA GFDL(201 Forrestal Rd, Princeton, NJ, 08540)

GFDL-CM2p1 2010 ocean: MOM4 (MOM4p1_x1_Z50_cCM2M,Tripolar360x200L50); atmosphere: AM2 (AM2p14,M45L24); sea ice: SIS (SISp2,Tripolar360x200L50); land: LM2 (LM2,M45);

GFDL-CM3

NOAA GFDL(201 Forrestal Rd, Princeton, NJ, 08540)

GFDL-CM3 2010 atmosphere: AM3 (AM3p9,C48L48); sea ice: SIS (SISp2,Tripolar360x200); land: LM3 (LM3p7_cCM3,C48); ocean: MOM4 (MOM4p1_x1_Z50_cCM3,Tripolar360x200L50);

GFDL-ESM2G

NOAA GFDL(201 Forrestal Rd, Princeton, NJ, 08540)

GFDL-ESM2G 2010 ocean: TOPAZ (TOPAZ1p2,Tripolar360x210L63); atmosphere: AM2 (AM2p14,M45L24); sea ice: SIS (SISp2,Tripolar360x210L63); land: LM3 (LM3p7_cESM,M45);

GFDL-ESM2M

NOAA GFDL(201 Forrestal Rd, Princeton, NJ, 08540)

GFDL-ESM2M 2010 ocean: MOM4 (MOM4p1_x1_Z50_cCM2M,Tripolar360x200L50); atmosphere: AM2 (AM2p14,M45L24); sea ice: SIS (SISp2,Tripolar360x200L50); land: LM3 (LM3p7_cESM,M45) Computing resources were provided by the Climate Simulation Laboratory at the NCAR Computational and Information Systems Laboratory (CISL),\n,;

GFDL-HIRAM-C180

NOAA GFDL(201 Forrestal Rd, Princeton, NJ, 08540)

GFDL-HIRAM-C180 2010 atmosphere: HIRAM (HIRAMp1,C180L32); land: LM3 (LM3p7_cHIRAM,C180);

GFDL-HIRAM-C360

NOAA GFDL(201 Forrestal Rd, Princeton, NJ, 08540)

GFDL-HIRAM-C360 2010 atmosphere: HIRAM (HIRAMp1,C360L32); land: LM3 (LM3p7_cHIRAM,C360);

GISS-E2-H

NASA/GISS (Goddard Institute for Space Studies) New York, NY

GISS-E2-H-Eh135f9b Atmosphere: GISS-E2; Ocean: H;

GISS-E2-H-CC

NASA/GISS (Goddard Institute for Space Studies) New York, NY

GISS-E2-H-CC-E4arobio_h8P Atmosphere: GISS-E2; Ocean: H;

GISS-E2-R

NASA/GISS (Goddard Institute for Space Studies) New York, NY

GISS-E2-R-E135OCNf9aF40 Atmosphere: GISS-E2;

GISS-E2-R-CC

NASA/GISS (Goddard Institute for Space Studies) New York, NY

GISS-E2-R-CC-E4arobio_g8RCP45 Atmosphere: GISS-E2; Ocean: R;

HadCM3

Met Office Hadley Centre, Fitzroy Road, Exeter, Devon, EX1 3PB, UK, (http://www.metoffice.gov.uk)

HadCM3 - Hadley Centre Coupled Model Version 3 (2000) atmosphere: HadAM3 (N48L19); ocean: HadOM (lat: 1.25 lon: 1.25 L20); land-surface/vegetation: MOSES1;;

HadGEM2-A

Met Office Hadley Centre, Fitzroy Road, Exeter, Devon, EX1 3PB, UK, (http://www.metoffice.gov.uk)

HadGEM2-A (2009) atmosphere: HadGAM2 (N96L38); land-surface/vegetation: MOSES2;

HadGEM2-CC

Met Office Hadley Centre, Fitzroy Road, Exeter, Devon, EX1 3PB, UK, (http://www.metoffice.gov.uk)

HadGEM2-CC (2011) atmosphere: HadGAM2(N96L60); ocean: HadGOM2 (lat: 1.0-0.3 lon: 1.0 L40); land-surface/vegetation: MOSES2 and TRIFFID; ocean biogeochemistry: diat-HadOCC;

HadGEM2-ES

Met Office Hadley Centre, Fitzroy Road, Exeter, Devon, EX1 3PB, UK, (http://www.metoffice.gov.uk)

HadGEM2-ES (2009) atmosphere: HadGAM2 (N96L38); ocean: HadGOM2 (lat: 1.0-0.3 lon: 1.0 L40); land-surface/vegetation: MOSES2 and TRIFFID; tropospheric chemistry: UKCA; ocean biogeochemistry: diat-HadOCC;

inmcm4

INM (Institute for Numerical Mathematics, Moscow, Russia)

inmcm4 (2009);

IPSL-CM5A-LR

IPSL (Institut Pierre Simon Laplace, Paris, France)

IPSL-CM5A-LR (2010) : atmos : LMDZ4 (LMDZ4_v5, 96x95x39); ocean : ORCA2 (NEMOV2_3, 2x2L31); seaIce : LIM2 (NEMOV2_3); ocnBgchem : PISCES (NEMOV2_3); land : ORCHIDEE (orchidee_1_9_4_AR5);

IPSL-CM5A-MR

IPSL (Institut Pierre Simon Laplace, Paris, France)

IPSL-CM5A-MR (2010) : atmos : LMDZ4 (LMDZ4_v5, 144x143x39); ocean : ORCA2 (NEMOV2_3, 2x2L31); seaIce : LIM2 (NEMOV2_3); ocnBgchem : PISCES (NEMOV2_3); land : ORCHIDEE (orchidee_1_9_4_AR5);

IPSL-CM5B-LR

IPSL (Institut Pierre Simon Laplace, Paris, France)

IPSL-CM5B-LR (2011) : atmos : LMDZ5 (LMDZ5_NPv3.1, 96x95x39); ocean : ORCA2 (NEMOV2_3, 2x2L31); seaIce : LIM2 (NEMOV2_3); ocnBgchem : PISCES (NEMOV2_3); land : ORCHIDEE (orchidee_1_9_4_AR5);

MPI-ESM-LR

Max Planck Institute for Meteorology

MPI-ESM-LR 2011; URL: https://gmd.copernicus.org/articles/12/3241/2019/; atmosphere: ECHAM6 (REV: 4418), T63L47; land: JSBACH (REV: 4418);;

MPI-ESM-MR

Max Planck Institute for Meteorology

MPI-ESM-MR 2011; URL: https://gmd.copernicus.org/articles/12/3241/2019/; atmosphere: ECHAM6 (REV: 4968), T63L47; land: JSBACH (REV: 4968);;

MPI-ESM-P

Max Planck Institute for Meteorology

MPI-ESM-P 2011; URL: https://gmd.copernicus.org/articles/12/3241/2019/; atmosphere: ECHAM6 (REV: 5051), T63L47; land: JSBACH (REV: 5051); ocean: MPIOM (REV: 5051), GR15L40; sea ice: 5051; marine bgc: HAMOCC (REV: 5051);;

NorESM1-M

Norwegian Climate Centre

NorESM1-M 2011 atmosphere: CAM-Oslo (CAM4-Oslo-noresm-ver1_cmip5-r112, f19L26); ocean: MICOM (MICOM-noresm-ver1_cmip5-r112, gx1v6L53); sea ice: CICE (CICE4-noresm-ver1_cmip5-r112); land: CLM (CLM4-noresm-ver1_cmip5-r112);

NorESM1-ME

Norwegian Climate Centre

NorESM1-ME 2011 atmosphere: CAM-Oslo (CAM4-Oslo-noresm-ver1_cmip5-r139, f19L26); ocean: MICOM (MICOM-noresm-ver1_cmip5-r139, gx1v6L53); ocean biogeochemistry: HAMOCC (HAMOCC-noresm-ver1_cmip5-r139, gx1v6L53); sea ice: CICE (CICE4-noresm-ver1_cmip5-r139); land: CLM (CLM4-noresm-ver1_cmip5-r139);

Pressure levels

For pressure level data the model output is available on the pressure levels according to the table below. Note that not all models provide the same pressure levels. 


Frequency

Number of Levels 

Pressure Levels (hPa)

Daily

8

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

Monthly

17

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

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, three different categories of sensitivity studies are done, and the resulting individual model runs are labelled by three integers indexing the experiments in each category. 

  • The first category, labelled “realization”, 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 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”, 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. 

Each member of an ensemble is identified by a triad of integers associated with the letters r, i and p which index the “realization”, “initialization” and “physics” variations respectively. For instance, the member "r1i1p1" and the member "r1i1p2" for the same model and experiment indicate that the corresponding simulations differ since the physical parameters of the model for the second member were changed relative to the first member. 

It is very important to distinguish between variations in experiment specifications, which are globally coordinated across all the models contributing to CMIP5, and the variations which are adopted by each modelling team to assess the robustness of their own results. The “p” index refers to the latter, with the result that values have different meanings for different models, but in all cases these variations must be within the constraints imposed by the specifications of the experiment. 

For the scenario experiments, the ensemble member identifier is preserved from the historical experiment providing the initial conditions, so RCP 4.5 ensemble member “r1i1p2” is a continuation of historical ensemble member “r1i1p2”.

Parameter listings

Table 1: CMIP5 data on pressure levels

count

name

units

Variable name in CDS

Daily data

Monthly data

1

Air temperatureK
temperature
xx

2

Geopotential heightm
geopotential_height
xx
3Relative humidity%
relative_humidity

x
4Specific humidity%
specific_humidity

x

5

U-component of windm s-1
u_component_of_wind
xx
6V-component of windm s-1
v_component_of_wind

x

Table 2: CMIP5 data on single levels

count

name

units

Variable name in CDSDaily dataMonthly data
110m u component of windm s-1
10m_wind_speed
xx
210m v component of windm s-1
10m_v_component_of_wind

x
310m wind_speedm s-1
10m_wind_speed

x
42m temperatureK
2m_temperature
xx
5Daily near surface relative humidity%
daily_near_surface_relative_humidity
x
6Eastward turbulent surface stressN s m-2
eastward_turbulent_surface_stress

x
7Evaporationkg m-2 s-1
evaporation

x
8Maximum 2m temperature in the last 24 hoursK
maximum_2m_temperature_in_the_last_24_hours
xx
9Mean precipitation fluxkg m-2 s-1
mean_precipitation_flux

x
10Mean sea level pressurePa
mean_sea_level_pressure

x
11Minimum 2m temperature in the last 24 hoursK
minimum_2m_temperature_in_the_last_24_hours

x
12Near surface relative humidity%
near_surface_relative_humidity
xx
13Near surface specific humidityDimensionless
near_surface_specific_humidity

x
14Northward turbulent surface stressN s m-2
northward_turbulent_surface_stress

x
15Runoffkg m-2 s-1
runoff

x
16Sea ice fractionDimensionless
sea_ice_fraction

x
17Sea ice plus snow amountkg m-2
sea_ice_plus_snow_amount

x
18Sea ice surface temperatureK
sea_ice_surface_temperature

x
19Sea ice thicknessm
sea_ice_thickness

x
20Sea surface height above geoidm
sea_surface_height_above_geoid

x
21Sea surface salinity
sea_surface_salinity

x
22Sea surface temperatureK
sea_surface_temperature

x
23Skin temperatureK
skin_temperature

x
24Snow depth over sea iceK
snow_depth_over_sea_ice

x
25Snowfallkg m-2 s-1
snowfall
xx
26Soil moisture contentkg m-2
soil_moisture_content

x
27Surface latent heat fluxW m-2
surface_latent_heat_flux

x
28Surface pressurePa
surface_pressure

x
29Surface sensible heat fluxW m-2
surface_sensible_heat_flux

x
30Surface snow amountkg m-2
surface_snow_amount

x
31Surface solar radiation downwardsW m-2
surface_solar_radiation_downwards
xx
32Surface thermal radiation downwardsW m-2
surface_thermal_radiation_downwards

x
33Surface upwelling longwave radiationW m-2
surface_upwelling_longwave_radiation

x
34Surface upwelling shortwave radiationW m-2
surface_upwelling_shortwave_radiation

x
35TOA incident solar radiationW m-2toa_incident_solar_radiation
x
36TOA outgoing clear-sky longwave radiationW m-2
toa_outgoing_clear_sky_longwave_radiation

x
37TOA outgoing clear-sky shortwave radiationW m-2
toa_outgoing_clear_sky_short_wave_radiation

x
38TOA outgoing longwave radiationW m-2
toa_outgoing_longwave_radiation

x
39TOA outgoing shortwave radiationW m-2
toa_outgoing_shortwave_radiation

x
40Total cloud coverDimensionless
total_cloud_cove

x

Data Format

The CDS subset of CMIP5 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 CMIP5 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
    • 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

The metadata provided in NetCDF files adhere to the Climate and Forecast (CF) conventions (v1.4 for CMIP5 data). The rules within the CF-conventions ensure consistency across data files, for example ensuring that the naming of variables is consistent and that the use of variable units is consistent.

File naming conventions

When you download a CMIP5 file from the CDS it will have a naming convention that is as follows:

<variable>_<cmor_table>_<model>_<experiment>_<ensemble_member>_<temporal_range>.nc

Where

  • variable is a short variable name, e.g. “tas” for ”temperature at the surface”
  • cmor_table is a reference to the realm (an earth system component such as atmosphere or ocean) and frequency of the variable, e.g. “Amon” indicates that a variable is present in the atmosphere realm at a monthly frequency (link to list of these)
  • model is the name of the model that produced the data
  • ensemble member is the ensemble identifier in the form “r<X>i<Y>p<Z>”, X, Y and Z are integers
  • 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.

Please note that the CIMP5 filenames in the CDS do not contain a version tag as opposed to the file names used for the corresponding data in the ESGF nodes, where you have the versioning information. In the CDS we serve the latest version of the CMIP5 data which is now complete (no new version expected). To find the version number of this latest version published in the CDS, see the metadata of the netcdf file. This contains a track identity of the file and an http address for each file from where the version number information may be checked.

Quality control of the CDS-CMIP5 subset

The CDS subset of the CMIP5 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-CMIP5 subset or if possible the error is corrected and a note made in the history attribute of the file. The quality control of the CDS CMIP5 subset checks for metadata errors or inconsistencies against the Climate and Forecast (CF) Conventions and a set of CMIP5 specific file naming and file global metadata conventions. 

Various software tools have been used to check the metadata of the CDS CMIP5 data:

  • The Centre for Environmental Data Analysis (CEDA) compliance checking tool CEDA-CC is used to check that: 
    • the file name adheres to the CMIP5 file naming convention, 
    • the global attributes of the NetCDF file are consistent with filename,
    • there are no omissions of required CMIP5 metadata.
  • The CF-Checker Climate and Forecast (CF) conventions checker ensures that any metadata that is provided is consistent with the CF conventions
  • A time-axis-checker is used to check the temporal dimension of the data:
    • for individual files the time dimension of the data is checked to ensure it is valid and is consistent with the temporal information in the filename, 
    • where more than one file is required to generate a time-series of data, the files have been checked to ensure there are no temporal gaps or overlaps between the files.

The data within the files were not individually checked however where it was known that a variable from a given model had a gross error, e.g in the sign convention of a flux, then these data were also omitted from the CDS-CMIP5 subset. 

It is important to note that passing of these quality control tests should not be confused with validity: for example, it will be possible for a file to be fully CF compliant and have fully compliant CMIP5 metadata but contain gross errors in the data that have not been noted. 

For a detailed description of all the quality control of the data please see the accompanying documentation  

Known issues

  • Please note that not all the combinations of models and variables exist. This feature is inherited from the ESGF system, where the main target is to publish as much as possible data and even publish incomplete datasets, which might be of use. This allows to have more data available with the price that not everything is fully complete. 

This document has been produced in the context of the Copernicus Climate Change Service (C3S).

The activities leading to these results have been contracted by the European Centre for Medium-Range Weather Forecasts, operator of C3S on behalf of the European Union (Delegation Agreement signed on 11/11/2014 and Contribution Agreement signed on 22/07/2021). All information in this document is provided "as is" and no guarantee or warranty is given that the information is fit for any particular purpose.

The users thereof use the information at their sole risk and liability. For the avoidance of all doubt , the European Commission and the European Centre for Medium - Range Weather Forecasts have no liability in respect of this document, which is merely representing the author's view.