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| title | Click here to expand... CMIP6 experiments included in the CDS |
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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. |
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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, 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.
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| title | Click here to expand... CMIP6 models with model detail discrepancies |
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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) | | CESM2-WACCM | atmos: WACCM6 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 70 levels; top level 4.5e-06 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) |
| 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)
| 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)
| GISS-E2-1-H | Released in 2019 |
| MCM-UA-1-0 |
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Grids
CMIP6 data is reported 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 grid approximate resolution of its the final output data (archived in the CMIP6 repository, and available via the CDS) as a “nominal_resolution”. The This "nominal_resolution” enables users to identify which models are have relatively high resolution and have data that might be challenging to download and store locallyoutput. Information about the grids can be found in the model table above, under 'Model Details', and within the NetCDF file metadata.
Pressure levels
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 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 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
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- 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 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.
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| CDS parameter name for CMIP6 | Time resolution available | ESGF variable id | CDS parameter name for CMIP5 | Units | | Near-surface air temperature | monthly, daily | tas | 2m temperature | Kelvin | | Daily maximum near-surface air temperature | monthly, daily | tasmax | Maximum 2m temperature in the last 24 hours | Kelvin | | Daily minimum near-surface air temperature | monthly, daily | tasmin | Minimum 2m temperature in the last 24 hours | Kelvin | | Surface temperature | monthly | ts | Skin temperature | Kelvin | | Sea level pressure | monthly, daily | psl | Mean sea level pressure | Pa | | Surface air pressure | monthly | ps | Surface pressure | Pa | | Eastward near-surface wind | monthly | uas | 10m u component of wind | m s-1 | | Northward near-surface wind | monthly | vas | 10m v component of wind | m s-1 | | Near-surface wind speed | monthly, daily | sfcWind | 10m wind speed | m s-1 | | Near-surface relative humidity | monthly | hurs | 2m relative humidity | 1 | | Near-surface specific humidity | monthly, daily | huss | 2m specific humidity | 1 | | Precipitation | monthly, daily | pr | Mean precipitation flux | kg m-2s-1 | | Snowfall flux | monthly | prsn | Snowfall | kg m-2 s-1 | | Evaporation Including sublimation and transpiration | monthly | evspsbl | Evaporation | kg m-2 s-1 | | Surface downward eastward wind stress | monthly | tauu | Eastward turbulent surface stress | Pa | | Surface downward northward wind stress | monthly | tauv | Northward turbulent surface stress | Pa | | Surface upward latent heat flux | monthly | hfls | Surface latent heat flux | W m-2 | | Surface upward sensible heat flux | monthly | hfss | Surface sensible heat flux | W m-2 | | Surface downwelling longwave radiation | monthly | rlds | Surface thermal radiation downwards | W m-2 | | Surface upwelling longwave radiation | monthly | rlus | Surface upwelling longwave radiation | W m-2 | | Surface downwelling shortwave radiation | monthly | rsds | Surface solar radiation downwards | W m-2 | | Surface upwelling shortwave radiation | monthly | rsus | Surface upwelling shortwave radiation | W m-2 | | TOA incident shortwave radiation | monthly | rsdt | TOA incident solar radiation | W m-2 | | TOA outgoing shortwave radiation | monthly | rsut | TOA outgoing shortwave radiation | W m-2 | | TOA outgoing longwave radiation | monthly | rlut | TOA outgoing longwave radiation | W m-2 | | Total cloud cover percentage | monthly | clt | Total cloud cover | % | | Air temperature | monthly | ta | Air temperature | K | | Eastward wind | monthly | ua | U-component of wind | m s-1 | | Northward wind | monthly | va | V-component of wind | m s-1 | | Relative humidity | monthly | hur | Relative humidity | 1 | | Specific humidity | monthly | hus | Specific humidity | 1 | | Geopotential height | monthly | zg | Geopotential height | m | | Surface snow amount | monthly | snw | Surface snow amount | kg m-2 | | Snow depth | monthly | snd | Snow depth | m | | Total runoff | monthly | mrro | Runoff | kg m-2 s-1 | | Moisture in upper portion of soil column | monthly | mrsos | Soil moisture content | kg m-2 | | Sea-Ice area percentage (ocean grid) | monthly | siconc | Sea-ice area percentage | 1 | | Sea Ice thickness | monthly | sithick | Sea ice thickness | m | | Sea-Ice mass per area | monthly | simass | Sea ice plus snow amount | kg m-2 | | Surface temperature of sea Ice | monthly | sitemptop | Sea ice surface temperature | K | | Sea surface temperature | monthly | tos | Sea surface temperature | K | | Sea surface salinity | monthly | sos | Sea surface salinity | PSU | | Sea surface height above geoid | monthly | zos | Sea surface height above geoid | m | | Grid-cell area for ocean variables | - | areacello | NOT AVAILABLE | m2 | | Sea floor depth below geoid | - | deptho | NOT AVAILABLE | m | | Sea area percentage | - | sftof | NOT AVAILABLE | % | | Grid-cell area for atmospheric grid variables | - | areacella | NOT AVAILABLE | m2 | | Capacity of soil to store water (field capacity) | - | mrsofc | NOT AVAILABLE | kg m-2 | | Percentage of the grid cell occupied by land (including lakes) | - | sftlf | NOT AVAILABLE | % | | Land ice area percentage | - | sftgif | NOT AVAILABLE | 1 | | Surface altitude | - | orog | NOT AVAILABLE | m |
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- 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, 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.
- 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.
- 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.
- Errata: The dataset was checked to ensure that no outstanding Errata record existed at the time of publication.
- 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.
- 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.
- Exists at all partner sites: It is asserted that each dataset exists at all three partner sites CEDA, DKRZ and IPSL.
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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
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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)
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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
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EC-Earth3-Veg | - no historical data on the CDS (other than fixed fields)
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MIROC-ES2H | - only historical data available
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EC-Earth3-Veg-LR | - missing historical data for some variables
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NORESM2-LM | - missing historical data for some variables
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GISS-E2-1-G | - missing historical data for some variables
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Subsetting and downloading data
CDS users will now be able to apply temporal and spatial 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.
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