...
The CMIP6 data archive is distributed through the ESGF. A quality-controlled subset of CMIP6 global climate projection data are made available through the Climate Data Store (CDS) for the users of the Copernicus Climate Change Service (C3S). Dedicated ESGF data nodes are used for C3S in France (at IPSL) and in Germany (DKRZ). Similarly, the decadal climate prediction project (DCPP) data in the Climate Data Store (CDS) are a targeted, quality-controlled subset of the DCPP commissioned by C3S.
The published datasets are the ones which took part on the C3S sectoral demonstrator service. This demonstrator provided decadal prediction products tailored to specific users from the agriculture, energy, infrastructure and insurance sectors (see details at https://climate.copernicus.eu/sectoral-applications-decadal-predictions)
Decadal Climate Prediction Project Data in the CDS
DCPP Experiments
The CDS provides data access to two DCPP experiments: dcppA-hindcast which consists of retrospective decadal forecasts that can be used to assess historical decadal prediction skill, and dcppB-forecast which are experimental quasi-real-time decadal forecasts that form a basis for potential operational forecast production. For these DCPP experiments, each model performs multiple overlapping simulations that are initialised annually throughout the experiment. The dcppA-hindcast and dcppB-forecast experiments are further described in the table below. The DCPP experiment descriptions presented here are based on information harvested from Earth System Documentation (ES-DOC).
. The data were used in these demonstrators following processing procedures necessary to extract valid information (e.g., bias adjustment); details on this processing are available in the technical appendix at https://climate.copernicus.eu/sites/default/files/2021-09/Technical_appendix_2020.pdf. Any application - similar to or different from these examples - needs to consider and apply the required data processing with care.
Decadal Climate Prediction Project Data in the CDS
DCPP Experiments
The CDS provides data access to two DCPP experiments: dcppA-hindcast which consists of retrospective decadal forecasts that can be used to assess historical decadal prediction skill, and dcppB-forecast which are experimental quasi-real-time decadal forecasts that form a basis for potential operational forecast production. For these DCPP experiments, each model performs multiple overlapping simulations that are initialised annually throughout the experiment. The dcppA-hindcast and dcppB-forecast experiments are further described in the table below. The DCPP experiment descriptions presented here are based on information harvested from Earth System Documentation (ES-DOC).
Experiment Name | Experiment Long Name | Extended Description |
|---|---|---|
dcppA-hindcast | hindcasts initialized from observations with historical forcing | dcppA-hindcast is a set of retrospective decadal forecasts (known as hindcasts) that are initialised every year mostly from 1960-2019 and performed with a |
Experiment Name | Experiment Long Name | Extended Description |
dcppA-hindcast | hindcasts initialized from observations with historical forcing | dcppA-hindcast is a set of retrospective decadal forecasts (known as hindcasts) that are initialised every year mostly from 1960-2019 and performed with a coupled atmosphere-ocean general circulation model (AOGCM). The hindcasts begin in November to allow for DJF (December, January, February) seasonal averages to be calculated. There are 10 hindcasts for each start date and hindcasts run for 10 years. The models running these hindcasts are initialised using observed data. Prior to the year 2020, the models are forced with historical conditions that are consistent with observations, these conditions include atmospheric composition, land use, volcanic aerosols and solar forcing. When hindcasts extend beyond 2020, the models are forced with future conditions from the ssp245 scenario from 2020 until the end of the simulation. DCPP hindcast experiments can be used to assess and understand the historical decadal prediction skill of climate models. |
dcppB-forecast | forecasts initialised from observations with ssp245 scenario forcing | dcppB-forecast is a set of quasi-real-time decadal forecasts that are initialised every year from 2019 in real time and ongoing (although only the data used in the secotoral demonstrator service is available from the CDS). The forecasts are performed with the same coupled atmosphere-ocean general circulation model (AOGCM), which was used to generate the hindcast data. The forecasts . The hindcasts begin in November to allow for DJF (December, January, February) seasonal averages to be calculated. There are 10 forecasts hindcasts for each start date and forecasts hindcasts run for 10 years. The models running these forecasts hindcasts are initialised using observed data. Prior to the year 2020, the models are forced with historical conditions that are consistent with observations, these conditions include atmospheric composition, land use, volcanic aerosols and solar forcing. When forecasts hindcasts extend beyond 2020, the models are forced with future conditions from the ssp245 scenario from 2020 until the end of the simulation. DCPP forecast experiments form a basis for potential operational decadal forecast production. |
Models
Data for the dcppA-hindcast and dcppB-forecast experiments published in the CDS are generated from simulations run by the models described in the table below. The model descriptions presented here are harvested from the dataset DOI pages held at the World Data Centre for Climate (WDCC), further model details can be found on the ES-DOC. The EC-Earth3, MPI-ESM1-2-HR, MPI-ESM1-2-LR and HadGEM3-GC31-MM models were configured with 360-day years (where every month has 30 days), whereas the CMCC-CM2-SR5 model was configured with a 365 day year (with an irregular number of days in each month).
hindcast experiments can be used to assess and understand the historical decadal prediction skill of climate models. | ||
dcppB-forecast | forecasts initialised from observations with ssp245 scenario forcing | dcppB-forecast is a set of quasi-real-time decadal forecasts that are initialised every year from 2019 in real time and ongoing (although only the data used in the secotoral demonstrator service is available from the CDS). The forecasts are performed with the same coupled atmosphere-ocean general circulation model (AOGCM), which was used to generate the hindcast data. The forecasts begin in November to allow DJF (December, January, February) seasonal averages to be calculated. There are 10 forecasts for each start date and forecasts run for 10 years. The models running these forecasts are initialised using observed data. Prior to the year 2020, the models are forced with historical conditions that are consistent with observations, these conditions include atmospheric composition, land use, volcanic aerosols and solar forcing. When forecasts extend beyond 2020, the models are forced with future conditions from the ssp245 scenario from 2020 until the end of the simulation. DCPP forecast experiments form a basis for potential operational decadal forecast production. |
Models
Data for the dcppA-hindcast and dcppB-forecast experiments published in the CDS are generated from simulations run by the models described in the table below. The model descriptions presented here are harvested from the dataset DOI pages held at the World Data Centre for Climate (WDCC), further model details can be found on the ES-DOC. The EC-Earth3, MPI-ESM1-2-HR, MPI-ESM1-2-LR and HadGEM3-GC31-MM models were configured with 360-day years (where every month has 30 days), whereas the CMCC-CM2-SR5 model was configured with a 365 day year (with an irregular number of days in each month).
Model | Centre | Description | ||
|---|---|---|---|---|
EC-Earth3 | EC Earth Consortium | The model used in climate research named EC Earth 3.3, released in 2019, includes the components:
| ||
Model | Centre | Description | ||
EC-Earth3 | EC Earth Consortium | The model used in climate research named EC Earth 3.3, released in 2019, includes the components:
The model was run in native nominal resolutions: atmos: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km. | ||
CMCC-CM2-SR5 | The Euro-Mediterranean Center on Climate Change (Centro Euro-Mediterraneo per I Cambiamenti Climatici, CMCC) | The model used in climate research named CMCC-CM2-SR5, released in 2016, includes the components:
The model was run in native nominal resolutions: aerosol: 100 km, atmos: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km. | ||
MPICMCC-ESM1CM2-2-HRSR5 | The German Weather Service (Deutscher Wetterdienst, DWD) / Max Planck Institute for Meteorology (MPI-M)Euro-Mediterranean Center on Climate Change (Centro Euro-Mediterraneo per I Cambiamenti Climatici, CMCC) | The model used in climate research named MPICMCC-ESM1.2CM2-HRSR5, released in 20172016, includes the components:
The model was run in native nominal resolutions: aerosol: 100 km, atmos: 100 km, land: 100 km, landIce: none, ocean: 50 ocean: 100 km, ocnBgchem: 50 km, seaIce: 50 100 km. | ||
MPI-ESM1-2-LRHR | The German Weather Service (Deutscher Wetterdienst, DWD) / Max Planck Institute for Meteorology (MPI-M) | The model used in climate research named MPI-ESM1.2-LRHR, released in 2017, includes the components:
The model was run in native nominal resolutions: aerosol: 250 100 km, atmos: 250 100 km, land: 250 100 km, landIce: none, ocean: 250 50 km, ocnBgchem: 250 50 km, seaIce: 250 50 km. https://www.wdc-climate.de/ui/cmip6?input=CMIP6.DCPP.MPI-M.MPI-ESM1-2-LR | HadGEM3-GC31-MM | |
MPI-ESM1-2-LR | The German Weather Service (Deutscher Wetterdienst, DWD) / Max Planck Institute for Meteorology (MPI-MMet Office Hadley Centre (MOHC) | The model used in climate research named HadGEM3MPI-GC3ESM1.12-N216ORCA025LR, released in 20162017, includes the components:
The model was run in native nominal resolutions: aerosol: 100 250 km, atmos: 100 250 km, land: 100 250 km, landIce: none, ocean: 250 km, ocnBgchem: 25 250 km, seaIce: 25 250 km. https://doi.org/10.22033/ESGF/CMIP6.456 |
Start-Date Ensembles
The DCPP experiments published in the CDS, are a suite of overlapping simulations that are initialised every year throughout the duration of the start-date range specified by the experiment. The simulations begin in November to allow for DJF (December, January, February) seasonal averages to be calculated. There are 10 simulations (ensemble members) for each start-date (called "Base year" in the CDS form), except for the MPI-ESM1-2-LR model which has 16 ensemble members.
The start-date ensemble is reflected in the DCPP data naming convention with the addition of a s<yyyy> start-date ensemble identifier. Please note that the conventional CMIP6 ripf ensemble identifiers are omitted for this particular dataset since all the ensemble members are concatenated into one file.
See some more more details in the File naming conventions and In-file metadata modifications sections below.
Practical details of the published data
In the table below some practical details of the data is shown including the base year (or start year) period covered and the number of ensemble members. For each start year there are (at least) 10 years of corresponding hindcast or forecast data available. Hindcast and forecast start years are not distinguished in the CDS form. Please note that the ensemble members are not available individually, but they are concatenated into one file while the data is downloaded, and generally users are encouraged to use all members instead of selecting one member of the predictions.
...
www.wdc-climate.de/ui/cmip6?input=CMIP6.DCPP.MPI-M.MPI-ESM1-2-LR | ||
HadGEM3-GC31-MM | Met Office Hadley Centre (MOHC) | The model used in climate research named HadGEM3-GC3.1-N216ORCA025, released in 2016, includes the components:
The model was run in native nominal resolutions: aerosol: 100 km, atmos: 100 km, land: 100 km, ocean: 25 km, seaIce: 25 km. |
Start-Date Ensembles
The DCPP experiments published in the CDS, are a suite of overlapping simulations that are initialised every year throughout the duration of the start-date range specified by the experiment. The simulations begin in November to allow for DJF (December, January, February) seasonal averages to be calculated. There are 10 simulations (ensemble members) for each start-date (called "Base year" in the CDS form), except for the MPI-ESM1-2-LR model which has 16 ensemble members.
The start-date ensemble is reflected in the DCPP data naming convention with the addition of a s<yyyy> start-date ensemble identifier. Please note that the conventional CMIP6 ripf ensemble identifiers are omitted for this particular dataset since all the ensemble members are concatenated into one file.
See some more more details in the File naming conventions and In-file metadata modifications sections below.
Practical details of the published data
In the table below some practical details of the data is shown including the base year (or start year) period covered and the number of ensemble members. For each start year there are (at least) 10 years of corresponding hindcast or forecast data available. Hindcast and forecast start years are not distinguished in the CDS form. Please note that the ensemble members are not available individually, but they are concatenated into one file while the data is downloaded, and generally users are encouraged to use all members instead of selecting one member of the predictions.
| Hindcast start years* | Forecast start years* | Ensemble members | Nominal resolution | Monthly variables | Daily variables | |
|---|---|---|---|---|---|---|
| CMCC (Italy) | 1960 -2018 | 2019 - 2020 | 10 | 100 km | Near surface air temperature, precipitation, sea level pressure | --- |
| EC-EARTH (Europe) | 1960 - 2018 | 2019 - 2020 | 10 | 100 km | Near surface air temperature, precipitation, sea level pressure | 500 hPa geopotential height, daily maximum near surface air temperature, daily minimum near surface air temperature, near surface air temperature, precipitation, sea level pressure |
| HadGEM3 (UK) | 1960 - 2018 | 2019 - 2020 | 10 | 100 km | Near surface air temperature, precipitation, sea level pressure | 500 hPa geopotential height, daily minimum near surface air temperature, precipitation |
| MPI-ESM1-2-HR (Germany) | 1960 - 2018 | --- | 10 | 100 km | Near surface air temperature, precipitation, sea level pressure | 500 hPa geopotential height, daily maximum near surface air temperature, daily minimum near surface air temperature, precipitation |
| MPI-ESM1-2-LR (Germany) | 1960 - 2018 | 2019 - 2021 | 16 | 250 km | Near surface air temperature, precipitation, sea level pressure | Daily maximum near surface air temperature, daily minimum near surface air temperature |
*Note: Since hindcast and forecast data begins in November, the actual period the data covers includes only November and December for each start year, however the last year includes November and December. For example, for the 1960 start year, 1960 includes November and December and 1961 - 1970 have full coverage.
Parameter listings
Data for the dcppA-hindcast experiments and the dcppB-forecast experiments will include parameters at monthly and daily resolution as described in the tables below. The parameter descriptions presented here are harvested from the CMIP6 Data Request via the CLIPC variable browser.
*Note: Since hindcast and forecast data begins in November, the actual period the data covers includes only November and December for each start year, however the last year includes November and December. For example, for the 1960 start year, 1960 includes November and December and 1961 - 1970 have full coverage.
Parameter listings
Data for the dcppA-hindcast experiments and the dcppB-forecast experiments will include parameters at monthly and daily resolution as described in the tables below. The parameter descriptions presented here are harvested from the CMIP6 Data Request via the CLIPC variable browser.
Monthly Parameters
...
ESGF variable id
...
units
...
Standard name (CF)
...
Long name
...
Description
...
tas
...
K
...
air_temperature
...
Near-Surface Air Temperature
...
Temperature of air at 2m above the surface of land, sea or inland waters. 2m temperature is calculated by interpolating between the lowest model level and the Earth's surface, taking account of the atmospheric conditions.
...
pr
...
kg m-2 s-1
...
precipitation_flux
...
Precipitation
...
The sum of liquid and frozen water, comprising rain and snow, that falls to the Earth's surface. It is the sum of large-scale precipitation and convective precipitation. This parameter does not include fog, dew or the precipitation that evaporates in the atmosphere before it lands at the surface of the Earth. This variable represents amount of water per unit area and time.
...
psl
...
Pa
...
air_pressure_at_sea_level
...
Sea Level Pressure
...
The pressure (force per unit area) of the atmosphere at the surface of the Earth, adjusted to the height of sea level. It is a measure of the weight that all the air in a column vertically above a point on the Earth's surface would have, if the point were located at sea level. It is calculated over all surfaces - land, sea and inland water.
Daily Parameters
...
ESGF variable id
...
units
...
Standard name (CF)
...
Long name
...
Description
...
tasmin
...
K
...
air_temperature
...
Daily Minimum Near-Surface Air Temperature
...
Daily minimum temperature of air at 2m above the surface of land, sea or inland waters.
...
tasmax
...
K
...
air_temperature
...
Daily Maximum Near-Surface Air Temperature
...
Daily maximum temperature of air at 2m above the surface of land, sea or inland waters.
...
pr
...
kg m-2 s-1
...
precipitation_flux
...
Precipitation
...
The sum of liquid and frozen water, comprising rain and snow, that falls to the Earth's surface. It is the sum of large-scale precipitation and convective precipitation. This parameter does not include fog, dew or the precipitation that evaporates in the atmosphere before it lands at the surface of the Earth. This variable represents amount of water per unit area and time.
...
zg500
...
m
...
geopotential_height
...
Geopotential Height at 500hPa
...
Gravitational potential energy per unit mass normalised by the standard gravity at 500hPa at the same latitude.
INSTEAD, NEW TABLE PROPOSED
| CDS parameter name | ESGF variable id | units | Standard name (CF) | Long name | Description |
|---|---|---|---|---|---|
| 500 hPa geopotential height | zg500 | m | geopotential_height | Geopotential Height at 500hPa | Gravitational potential energy per unit mass normalised by the standard gravity at 500hPa at the same latitude. |
| Daily maximum near-surface air temperature | tasmax | K | air_temperature | Daily Maximum Near-Surface Air Temperature | Daily maximum temperature of air at 2m above the surface of land, sea or inland waters. |
| Daily minimum near-surface air temperature | tasmin | K | air_temperature | Daily Minimum Near-Surface Air Temperature | Daily minimum temperature of air at 2m above the surface of land, sea or inland waters. |
| Near-surface air temperature | tas | K | air_temperature | Near-Surface Air Temperature | Temperature of air at 2m above the surface of land, sea or inland waters. 2m temperature is calculated by interpolating between the lowest model level and the Earth's surface, taking account of the atmospheric conditions. |
| Precipitation | pr | kg m-2 s-1 | precipitation_flux | Precipitation | The sum of liquid and frozen water, comprising rain and snow, that falls to the Earth's surface. It is the sum of large-scale precipitation and convective precipitation. This parameter does not include fog, dew or the precipitation that evaporates in the atmosphere before it lands at the surface of the Earth. This variable represents amount of water per unit area and time. |
| Sea level pressure | psl | Pa | air_pressure_at_sea_level | Sea Level Pressure | The pressure (force per unit area) of the atmosphere at the surface of the Earth, adjusted to the height of sea level. It is a measure of the weight that all the air in a column vertically above a point on the Earth's surface would have, if the point were located at sea level. It is calculated over all surfaces - land, sea and inland water. |
...
World Climate Research Programme (2020) CMIP Phase 6 (CMIP6): Overview CMIP6 Experimental Design and Organization. Available at: https://www.wcrp-climate.org/wgcm-cmip/wgcm-cmip6 (Accessed: 2 November 2020).
| Info | ||
|---|---|---|
| ||
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 agreementAgreement 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. |
Related articles
| Content by Label | ||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|
...