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The Decadal Climate Prediction Project (DCPP) is a contributing MIP (Model Intercomparison Project) to the 6th Coupled Model Intercomparison Project (CMIP6 – Eyring et al., 2016), which is running as part of the World Climate Research Programme ((WCRP). DCPP addresses a range of scientific issues involving the ability of the climate system to be predicted on annual to decadal timescales, the skill that is currently and potentially available, the mechanisms involved in long timescale variability, and the production of forecasts of benefit to both science and society.
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The published datasets are the ones which took part on the C3S sectoral demonstrator service (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).
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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. |
MPI-ESM1-2-HR | The German Weather Service (Deutscher Wetterdienst, DWD) / Max Planck Institute for Meteorology (MPI-M) | The model used in climate research named MPI-ESM1.2-HR, released in 2017, includes the components:
The model was run in native nominal resolutions: aerosol: 100 km, atmos: 100 km, land: 100 km, landIce: none, ocean: 50 km, ocnBgchem: 50 km, seaIce: 50 km. |
MPI-ESM1-2-LR | The German Weather Service (Deutscher Wetterdienst, DWD) / Max Planck Institute for Meteorology (MPI-M) | The model used in climate research named MPI-ESM1.2-LR, released in 2017, includes the components:
The model was run in native nominal resolutions: aerosol: 250 km, atmos: 250 km, land: 250 km, landIce: none, ocean: 250 km, ocnBgchem: 250 km, seaIce: 250 km. https://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. |
Practical details of the published data
In the table below some practical details of the data is shown including the base year period covered and the number of ensemble members. Hindcast and forecast periods are not distinguished here as they are not mentioned in the CDS form neither. Please note that the ensemble members are not available individually, but they are concatenated into one file while the data is downloaded. Generally users are encouraged to use all members instead of selecting one members of the predictions.
| Forecast period | Ensemble members | |
|---|---|---|
| CMCC (Italy) | 1960-2020 | 10 |
| HadGEM3 (UK) | 1960-2020 | 10 |
| EC-EARTH (Europe) | 1960-2020 | 10 |
| MPI-ESM1-2-HR (Germany) | 1960-2018 | 10 |
| MPI-ESM1-2-LR (Germany) | 1960-2021 | 21 |
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 (16) simulations (ensemble members) for each start-date (called "Base year" in he CDS form).
The start-date ensemble is reflected in the DCPP data naming convention with the addition of a s<yyyy> start-date ensemble identifier ahead of the conventional CMIP6 ripf ensemble identifiers. For example, a simulation with a start year of 2014 will have the start-date ensemble identifier s2014, and a full ensemble identifier that follows the pattern s2014-r<W>i<X>p<Y>f<Z> where W, X, Y and Z are positive integers.
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