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Global climate projections are simulations of the climate system performed with general circulation models which represent physical processes in the atmosphere, ocean, cryosphere and land surface. These models may cover the entire globe or a specific region and globe and use information about the external influences on the system. Such simulations have been generated by multiple independent climate research centres in an effort coordinated by the World Climate Research Program (WCRP) and assessed by the Intergovernmental Panel on Climate Change (IPCC). These climate projections underpin the conclusions of the IPCC Assessment Reports that “Continued emission of greenhouse gases will cause further warming and long-lasting changes in all components of the climate system, increasing the likelihood of severe, pervasive and irreversible impacts for people and ecosystems”.
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Analysis of the CMIP data allows for improving
- an improved understanding of
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- the climate, including its variability and change,
- an improved understanding of the societal and environmental implications of climate change in terms of impacts, adaptation and vulnerability,
- informing the Intergovernmental Panel on Climate Change (IPCC) reports.
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- determining why similarly forced models to produce a range of responses,
- evaluating how realistic the different models are in simulating the recent past,
- examining climate predictability.
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The sixth phase of the Coupled Model Intercomparison Project (CMIP6) consists of 134 models from fifty-one modelling centers 53 modelling centres (Durack, 2020). CMIP6 data publication began in 2019 and the majority of the data publication will be completed by 2022. The scientific analyses from CMIP6 will be used extensively in the Intergovernmental Panel on Climate Change (IPCC) 6th Assessment Report (AR6), due for release in 2021/22 (IPCC, 2020).
CMIP6 will aim aims to address 3 main questions:
- How does the Earth system respond to forcing?
- What are the origins and consequences of systematic model biases?
- How can we assess future climate changes given internal climate variability, predictability, and uncertainties in scenarios ? (Eyring et al, 2016)?
There are some differences between the experimental design and organisation of CMIP6 and its predecessor CMIP5. It was decided that for CMIP6, a new and more federated structure would be used, consisting of the following three major elements:
- A handful of common experiments, the DECK (Diagnostic, Evaluation and Characterization of Klima) and CMIP historical simulations (1850 – near-present) that will maintain continuity and help document basic characteristics of models across different phases of CMIP;
- Common standards, coordination, infrastructure and documentation that will facilitate the distribution of model outputs and the characterization of the model ensemble;
- An ensemble of CMIP-Endorsed Model Intercomparison Projects (MIPs) that will be specific to a particular phase of CMIP (now CMIP6) and that will build on the DECK and CMIP historical simulations to address a large range of specific questions and fill the scientific gaps of the previous CMIP phases (World Climate Research Programme, 2020).
The CMIP6 data archive is distributed through the Earth System Grid Federation (ESGF) though many national centres have either a full or partial copy of the data. A quality-controlled subset of CMIP6 data are made available through the Climate Data Store (CDS) for the users of the Copernicus Climate Change Service (C3S).
Global climate projections in the CDS
The global climate projections in the Climate Data Store (CDS) are a quality-controlled subset of the wider CMIP6 data. These data represent only a small subset of CMIP6 archive. A set of 51 core variables from the CMIP6 archive were identified for the CDS. These variables are provided from 9 of the most popular CMIP6 experiments.
The CDS subset of CMIP6 data has been through a quality control procedure which ensures a high standard of dependability of the data. It may be for example, that similar data can be found in the main CMIP6 ESGF archive however these data come with very limited quality assurance and may have metadata errors or omissions.
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The SSP scenario experiments can be understood in terms of two pathways, a Shared Socioeconomic Pathway (SSP) and a Representative Concentration Pathway (RCP). The two pathways are represented by the three digits that make up the experiment’s name. The first digit represents the SSP storyline for the socio-economic mitigation and adaptation challenges that the experiment represents (Figure 1). The second and third digits represent the RCP climate forcing that the experiment follows. For example, experiment ssp245 follows SSP2, a storyline with intermediate mitigation and adaptation challenges, and RCP4.5 which leads to a radiative forcing of 4.5 Wm-2 by the year 2100.
Figure 1 - The socioeconomic “Challenge Space” to be spanned by the CMIP6 SSP experiments (O’Neil et al. 2014).
Experiments in the CDS
The CDS-CMIP6 subset consists of the following CMIP6 experiments:the CMIP6 experiments detailed in the table below.
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Models, grids and pressure levels
Models
The models included in the CDS-CMIP6 subset are detailed in the table below including a brief description of the model where this information is readily available, further details can be found on the Earth System Documentation site.
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Australian Community Climate and Earth System Simulator Climate Model Version 2 ACCESS-ESM1-5 CSIRO (Commonwealth Scientific and Industrial Research Organisation) | Australian Community Climate and Earth System Simulator Earth System Model Version 1.5 | AWI-CM-1-1-MR AWI (Alfred Wegener Institute) AWI-ESM-1-1-LR AWI (Alfred Wegener Institute) | BCC-CSM2-MR BCC (Beijing Climate Center) | BCC-ESM1 BCC (Beijing Climate Center) | CAMS-CSM1-0 CAMS (Chinese Academy of Meteorological Sciences) | CanESM5 CCCma | CanESM5-CanOE CCCma ( Canadian Centre for Climate Modelling and Analysis) | CAS-ESM2-0 CAS (Chinese Academy of Sciences) | CESM2 NCAR (National Center for Atmospheric Research) | The Community Earth System Model version 2 (CESM2) is a state-of-the-art coupled model that includes ocean, wave, land, land-ice, sea-ice, and river runoff models as well as both low-top and high-top full chemistry versions of atmopsheric models. The model also includes biogeochemistry. | CESM2-FV2 NCAR (National Center for Atmospheric Research) | CESM2-WACCM NCAR (National Center for Atmospheric Research) | CESM2-WACCM-FV2 NCAR (National Center for Atmospheric Research) | CIESM THU (Tsinghua University - Department of Earth System Science) | CMCC-CM2-SR5 CMCC (Centro Euro-Mediterraneo per I Cambiamenti Climatici) | CNRM-CM6-1 CNRM-CERFACS (National Center for Meteorological Research, Météo-France and CNRS laboratory, Climate Modeling and Global change) | ARPEGE-Climat Version 6.3 is the atmospheric component of the CNRM climate and Earth System models (CNRM-CM6-1 and CNRM-ESM2-1). It is based on the cycle 37 of the ARPEGE/IFS model (declared in 2010), developed under a collaboration between Météo-France and ECMWF. ARPEGE-Climat shares a large part of its physics and dynamics with its NWP counterpart ARPEGE used operationally at Météo-France. In comparison to ARPEGE-Climat Version 5.1 used for the CMIP5 exercise in CNRM-CM5.1, most of the atmospheric physics has been updated or revisited (Roehrig et al. 2019, Voldoire et al. 2019). For the surface, it is coupled to the SURFEX platform (Decharme et al. 2019). | CNRM-CM6-1-HR CNRM-CERFACS (National Center for Meteorological Research, Météo-France and CNRS laboratory, Climate Modeling and Global change) | CNRM-ESM2-1 CNRM-CERFACS (National Center for Meteorological Research, Météo-France and CNRS laboratory, Climate Modeling and Global change) | TACTIC (Tropospheric Aerosols for ClimaTe In CNRM) is an interactive tropospheric aerosol scheme, able to represent the main anthropogenic and natural aerosol types in the troposphere. Originally developed in the GEMS/MACC project (Morcrette et al., 2009), this scheme has been adapted to the ARPEGE/ALADIN-Climat models (Michou et al., 2015 and Nabat et al., 2015). Aerosols are included through sectional bins, separating desert dust (3 size bins), sea-salt (3 size bins), sulphate (1 bin, as well as 1 additional variable for sulfate precursors considered as SO2), organic matter (2 bins: hydrophobic and hydrophilic particles) and black carbon (2 bins: hydrophobic and hydrophilic particles) particles. All these 12 species are prognostic variables in the model, submitted to transport (semi-lagrangian advection, and convective transport), dry deposition, in-cloud and below-cloud scavenging. The interaction with shortwave and longwave radiation, is also taken into account through optical properties (extinction coefficient, single scattering albedo and asymmetry parameter) calculated using the Mie theory. Sulfate, organic matter and sea salt concentrations are used to determine the cloud droplet number concentration following Menon et al. (2002), thus representing the cloud-albedo effect (1st indirect aerosol effect). | E3SM-1-0 E3SM-Project LLNL (Energy Exascale Earth System Model, Lawrence Livermore National Laboratory) | E3SM-1-1 E3SM-Project RUBISCO (Energy Exascale Earth System Model, Reducing Uncertainty in Biogeochemical Interactions through Synthesis and COmputation) | E3SM 1.1 (Energy Exascale Earth System Model) | E3SM-1-1-ECA E3SM-Project (Energy Exascale Earth System Model) | E3SM 1.1 (Energy Exascale Earth System Model) with an experimental land BGC ECA configuration | EC-Earth3 EC-Earth-Consortium | The atmosphere-ocean general circulation model is described by Doescher-et-al-2020. The atmosphere is a modified version of IFS cycle 36r4, and includes the land-surface scheme H-TESSEL. The ocean and sea-ice model is NEMO-LIM3 version 3.6 with a few modifications. The OASIS3-MCT coupler version 3.0 is used to exchange fields between the atmosphere and ocean components. | EC-Earth3-LR EC-Earth-Consortium | The atmosphere-ocean general circulation model is described by Doescher-et-al-2020. The atmosphere is a modified version of IFS cycle 36r4, and includes the land-surface scheme H-TESSEL. The ocean and sea-ice model is NEMO-LIM3 version 3.6 with a few modifications. The OASIS3-MCT coupler version 3.0 is used to exchange fields between the atmosphere and ocean components. | EC-Earth3-Veg EC-Earth-Consortium | The atmosphere-ocean general circulation model is described by Doescher-et-al-2020. The atmosphere is a modified version of IFS cycle 36r4, and includes the land-surface scheme H-TESSEL. The ocean and sea-ice model is NEMO-LIM3 version 3.6 with a few modifications. The OASIS3-MCT coupler version 3.0 is used to exchange fields between the atmosphere and ocean components. | EC-Earth3-Veg-LR EC-Earth-Consortium | The atmosphere-ocean general circulation model is described by Doescher-et-al-2020. The atmosphere is a modified version of IFS cycle 36r4, and includes the land-surface scheme H-TESSEL. The ocean and sea-ice model is NEMO-LIM3 version 3.6 with a few modifications. The OASIS3-MCT coupler version 3.0 is used to exchange fields between the atmosphere and ocean components. | FGOALS-f3-L CAS (Chinese Academy of Sciences) | FGOALS-g3 CAS (Chinese Academy of Sciences) | FIO-ESM-2-0 FIO-QLNM (First Institute of Oceanography (FIO) and Qingdao National Laboratory for Marine Science and Technology (QNLM)) | GFDL-AM4 NOAA-GFDL (National Oceanic and Atmospheric Administration, Geophysical Fluid Dynamics Laboratory) | This is the Atmosphere and Land component (AM4.0.1) of GFDL coupled model CM4.0 for use in CMIP6. The Atmospheric component is identifical to the AM4.0 model documented in Zhao et. al (2018a, 2018b). The vegetation, land and glacier models differ from AM4.0 in the following aspects: 1) dynamical vegetation was used instead the static vegetation used in AM4.0. 2) glacier albedo is retuned. 3) other minor tuning in the land model. | GFDL-CM4 NOAA-GFDL (National Oceanic and Atmospheric Administration, Geophysical Fluid Dynamics Laboratory) | This is the GFDL physical coupled model CM4.0 for use in CMIP6. The model is documented in Held et al (2019) | GFDL-ESM4 NOAA-GFDL (National Oceanic and Atmospheric Administration, Geophysical Fluid Dynamics Laboratory) | GISS-E2-1-G NASA-GISS (National Oceanic and Atmospheric Administration, Goddard Institute for Space Studies) | GISS-E2-1-H NASA-GISS (National Oceanic and Atmospheric Administration, Goddard Institute for Space Studies) | GISS-E2-2-G NASA-GISS (National Oceanic and Atmospheric Administration, Goddard Institute for Space Studies) | HadGEM3-GC31-LL MOHC NERC (Met Office Hadley Centre, Natural Environmental Research Council) | Aerosol2: UKCA-GLOMAP-mode, atmos: MetUM-HadGEM3-GA7.1 (N96;192 x 144 longitude/latitude; 85 levels; top level 85km), atmosChem: none, land: JULES-HadGEM3-GL7.1, landIce: none, ocean: NEMO-HadGEM3-GO6.0 (ORCA1 tripolar primarily 1 deg latitude/longitude with meridional refinement down to 1/3 deg in tropics; 400 x 180 longitude/latitude; 75 levels; top grid cell 0-1m), ocnBgchem: none, seaIce: CICE-HadGEM3-GSI8 (ORCA1 tripolar primarily 1 deg; 360 x 180 longitude/latitude). | HadGEM3-GC31-MM MOHC (Met Office Hadley Centre) | IITM-ESM CCCR-IITM (Centre for Climate Change Research, Indian Institute of Tropical Meteorology) | INM-CM4-8 INM (Institute of Numerical Mathematics) | INM-CM5-0 INM (Institute of Numerical Mathematics) | IPSL-CM6A-LR IPSL (Institut Pierre‐Simon Laplace) | KACE-1-0-G NIMS-KMA (National Institute of Meteorological Sciences/Korea Met. Administration) | KIOST-ESM KIOST | MCM-UA-1-0 UA (University of Arizona - Department of Geosciences) | R30 spectral atmosphere coupled to MOM1 ocean using simple Manabe land model and simple Bryan sea ice model. | MIROC6 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)) | MIROC6 is a physical climate model mainly composed of three sub-models: atmosphere, land, and sea ice-ocean. The atmospheric model is based on the CCSR-NIES atmospheric general circulation model. The horizontal resolution is a T85 spectral truncation that is an approximately 1.4° grid interval for both latitude and longitude. The vertical grid coordinate is a hybrid σ-p coordinate. The model top is placed at 0.004 hPa, and there are 81 vertical levels. The Spectral Radiation-Transport Model for Aerosol Species (SPRINTARS) is used as an aerosol module for MIROC6 to predict the mass mixing ratios of the main tropospheric aerosols. By coupling the radiation and cloud-precipitation schemes, SPRINTARS calculates not only the aerosol transport processes but also the aerosol-radiation and aerosol-cloud interactions.The land surface model is based on Minimal Advanced Treatments of Surface Interaction and Runoff (MATSIRO), which includes a river routing model based on a kinematic wave flow equation and a lake module where one-dimensional thermal diffusion and mass conservation are considered. The horizontal resolution of the land surface model is the same as that of the atmopheric component. There are a three-layers snow and a six-layers soil down to a 14 m depth.The sea ice-ocean model is based on the CCSR Ocean Component model (COCO). The tripolar horizontal coordinate system is adopted, and the longitudinal grid spacing is 1° and the meridional grid spacing varies from about 0.5° near the equator to 1° in the mid-latitudes. There are 62 vertical levels in a hybrid σ-z coordinate system. A coupler system calculates heat and freshwater fluxes between the sub-models in order to ensure that all fluxes are conserved within machine precision and then exchanges the fluxes among the sub-models. No flux adjustments are used in MIROC6. | MIROC-ES2L 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)) | MIROC-AGCM is the atmospheric component of a climate model, the Model for Interdisciplinary Research on Climate version 6 (MIROC6). The MIROC-AGCM employs a spectral dynamical core, and standard physical parameterizations for cumulus convections, radiative transfer, cloud microphysics, turbulence, and gravity wave drag. It also has an aerosol module. The model is cooperatively developed by the Japanese modeling community including the Atmosphere and Ocean Research Institute, the University of Tokyo, the Japan Agency for Marine-Earth Science and Technology, and the National Institute for Environmental Studies. | MPI-ESM-1-2-HAM 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) | MPI-ESM1.2-HAM is the latest version of the Max Planck Institute for Meteorology Earth System Model (MPI-ESM1.2) coupled with the Hamburg Aerosol Module (HAM2.3), developed by the HAMMOZ consortium. The HAMMOZ consortium is composed of ETH Zurich, Max Planck Institut for Meteorology, Forschungszentrum Jülich, University of Oxford, the Finnish Meteorological Institute and the Leibniz Institute for Tropospheric Research, and managed by the Center for Climate Systems Modeling (C2SM) at ETH Zurich. | MPI-ESM1-2-HR MPI-M DWD DKRZ (Max Planck Institute for Meteorology (MPI-M), German Meteorological Service (DWD), German Climate Computing Center (DKRZ)) | MPI-ESM1-2-LR MPI-M AWI (Max Planck Institute for Meteorology (MPI-M), AWI (Alfred Wegener Institute)) | MRI-ESM2-0 MRI ( Meteorological Research Institute of the Korea Meteorological Administration) | NESM3 NUIST (Nanjing University of Information Science and Technology) | NorCPM1 NCC (Norwegian Climate Centre) | NorESM1-F NCC (Norwegian Climate Centre) | NorESM2-LM NCC (Norwegian Climate Centre) | NorESM2-MM NCC (Norwegian Climate Centre) | SAM0-UNICON SNU (Seoul National University) The atmospheric component of SEM0 is the Seoul National University Atmospheric Model Version 0 with a Unified Convection Scheme (SAM0-UNICON, Park et al. 2019, Park 2014a,b), which replaces CAM5's shallow and deep convection schemes and revises CAM5's cloud macrophysics scheme (Park et al. 2017). The other components of SEM0 (i.e., ocean, land, land-ice, sea-ice, and coupler) are identical to those of the Community Earth System Model version 1.2 (CESM1.2). | TaiESM1 AS-RCEC (Research Center for Environmental Changes) | UKESM1-0-LL 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)) | |
Grids
CMIP6 data is reported either on the model’s native grid or re-gridded to one or more target grids with data variables provided near the center of each grid cell (rather than at the boundaries). For CMIP6 there is a requirement to record both the native grid of the model and the grid of its output (archived in the CMIP6 repository) a “nominal_resolution”. The "nominal_resolution” enables users to identify which models are relatively high resolution and have data that might be challenging to download and store locally.
Pressure levels
For pressure level data the model output is available on the pressure levels according to the table below. Note that since the model output is standardised all models produce the data on the same pressure levels.
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1000., 925., 850., 700., 600., 500., 400., 300., 250., 200., 150., 100., 70., 50., 30., 20., 10., 5., 1.
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Grids
CMIP6 data is reported either on the model’s native grid or re-gridded to one or more target grids with data variables generally provided near the centre of each grid cell (rather than at the boundaries). For CMIP6 there is a requirement to record both the native grid of the model and the grid of its output (archived in the CMIP6 repository) as a “nominal_resolution”. The "nominal_resolution” enables users to identify which models are relatively high resolution and have data that might be challenging to download and store locally. Information about the grids can be found in the model table above, under 'Model Details' and within the NetCDF file metadata.
Pressure levels
For pressure level data the model output is available on the pressure levels according to the table below. Note that since the model output is standardised all models produce the data on the same pressure levels.
Frequency | Number of Levels | Pressure Levels (hPa) |
Daily | 8 | 1000., 850., 700., 500., 250., 100., 50., 10. |
Monthly | 19 | 1000., 925., 850., 700., 600., 500., 400., 300., 250., 200., 150., 100., 70., 50., 30., 20., 10., 5., 1. |
Ensembles
Each modelling centre typically run the same experiment using the same model with slightly different settings several times to confirm the robustness of results and inform sensitivity studies through the generation of statistical information. A model and its collection of runs is referred to as an ensemble. Within these ensembles, four different categories of sensitivity studies are done, and the resulting individual model runs are labelled by four integers indexing the experiments in each category
e.g. r<W>i<X>p<Y>f<Z>, where W, X, Y and Z are positive integers as defined below:
- The first category, labelled realization_index (referred to with letter r), performs experiments which differ only in random perturbations of the initial conditions of the experiment. Comparing different realizations allow estimation of the internal variability of the model climate.
- The second category, labelled initialization_index (referred to with letter i), refers to variation in initialisation parameters. Comparing differently initialised output provides an estimate of how sensitive the model is to initial conditions.
- The third category, labelled physics_index (referred to with letter p), refers to variations in the way in which sub-grid scale processes are represented. Comparing different simulations in this category provides an estimate of the structural uncertainty associated with choices in the model design.
- The fourth category labelled forcing_index (referred to with letter f) is used to distinguish runs of a single CMIP6 experiment, but with different forcings applied.
Parameter listings
Time-Independent parameters are marked with a *
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Ensembles
Each modelling centre typically run the same experiment using the same model several times to confirm the robustness of results and inform sensitivity studies through the generation of statistical information. A model and its collection of runs is referred to as an ensemble. Within these ensembles, four different categories of sensitivity studies are done, and the resulting individual model runs are labelled by four integers indexing the experiments in each category
e.g. r<W>i<X>p<Y>f<Z>, where W, X, Y and Z are positive integers as defined below:
- The first category, labelled realization_index (referred to with letter r), performs experiments which differ only in random perturbations of the initial conditions of the experiment. Comparing different realizations allow estimation of the internal variability of the model climate.
- The second category, labelled initialization_index (referred to with letter i), refers to variation in initialisation parameters. Comparing differently initialised output provides an estimate of how sensitive the model is to initial conditions.
- The third category, labelled physics_index (referred to with letter p), refers to variations in the way in which sub-grid scale processes are represented. Comparing different simulations in this category provides an estimate of the structural uncertainty associated with choices in the model design.
- The fourth category labelled forcing_index (referred to with letter f) is used to distinguish runs of a single CMIP6 experiment, but with different forcings applied.
Parameter listings
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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
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- variable_id: variable is a short variable name, e.g. “tas” for “temperature at the surface”.
- table_id: this refers to the MIP table being used. The MIP tables are used to organise the variables. For example, Amon refers to monthly atmospheric variables and Oday contains daily ocean data.
- source_id: this refers to the model used that produced the data.
- experiment_id: refers to the set of experiments being run for CMIP6. For example, PiControl, historical and 1pctCO2 (1 percent per year increase in CO2).
- variant_label: is a label constructed from 4 indices (ensemble identifiers) r<k>i<l>p<m>f<n>r<W>i<X>p<Y>f<Z>, where kW, lK, m Y and n Z are integers.
- grid_label: this describes the model grid used. For example, global mean data (gm), data reported on a model's native grid (gn) or regridded data reported on a grid other than the native grid and other than the preferred target grid (gr1).
- time_range: the temporal range is in the form YYYYMM[DDHH]-YYYY[MMDDHH], where Y is year, M is the month, D is day and H is hour. Note that day and hour are optional (indicated by the square brackets) and are only used if needed by the frequency of the data. For example, daily data from the 1st of January 1980 to the 31st of December 2010 would be written 19800101-20101231.
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The CMIP6 data Citation Service provides information for data users on how to cite CMIP6 data and on the data license. The long-term availability and long-term accessibility are granted by the use of DOIs for the landing page e.g . http://doi.org/10.22033/ESGF/CMIP6.1317.
Available CMIP6 data citations are discoverable in the ESGF or in the Citation Search at: http://bit.ly/CMIP6_Citation_Search.
Known issues
CDS users will be directed to the CMIP6 ES-DOC Errata Service for known issues with the wider CMIP6 data pool. Data that is provided to the CDS should not contain any errors or be listed in the Errata service, however this will still be a useful resource for CDS users as data they may be looking for but cannot access may have been withheld from the CDS for justifiable reasons.
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CDS users will now be able to apply subsetting operations to CMIP6 datasets. This mechanism (the "roocs" WPS framework) that runs at each of the partner sites: CEDA, DKRZ and IPSL. The WPS can receive requests for processing based on dataset identifiers, a temporal range, a bounding box and a range of vertical levels. Each request is converted to a job that is run asynchronously on the processing servers at the partner sites. NetCDF files are generated and the response contains download links to each of the files. Users of the CDS will be able to make subsetting selections using the web forms provided by the CDS catalogue web-interface. More advanced users will be able to define their own API requests in the CDS Toolbox that will call the WPS. Output files will be automatically retrieved so that users can access them directly within the CDS.
How to use the subsetting tool
Walkthrough and screenshots need to be provided by CDS team
References
Durack, P J. (2020) CMIP6_CVs. v6.2.53.5. Available at: https://github.com/WCRP-CMIP/CMIP6_CVs (Accessed: 26 October 2020).
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