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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 from 1960-2019 and performed with a coupled atmosphere-ocean general circulation model (AOGCM). The exact start dates begin in the November of the year preceding Prior to the year 2020 the models running these simulations are forced with historical conditions that are consistent with observations, these conditions include atmospheric composition, land use, volcanic aerosols and solar forcing. For simulations that extend beyond 2020 (e.g. 2015-2025) the models are forced with future conditions from the ssp245 scenario for the period from 2020 to the end of the simulation. There are 10 ensemble members for each start date and simulations run for 10 years. DCPP hindcasts can be used to assess and understand the historical decadal prediction skill of climate models. |
dcppB-forecast | forecast initialized from observations | dcppB-forecast is a set of quasi-real-time decadal forecasts that are initialised every year from 2019 in real time and ongoing. The forecasts are performed with the same coupled atmosphere-ocean general circulation model (AOGCM), which was used to generate the hindcast data. The exact start dates begin in the November of the year preceding the forecast period to allow for DJF (December, January, February) seasonal averages to be calculated. The models running these simulations are initialised using observed data, thereafter they are forced with future conditions from the ssp245 scenario that include atmospheric composition, land use, and solar forcing. There are 10 ensemble members for each start date and simulations run for 10 years. DCPP forecasts form a basis for potential operational forecast production. |
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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: atmos: IFS cy36r4 (TL255, linearly reduced Gaussian grid equivalent to 512 x 256 longitude/latitude; 91 levels; top level 0.01 hPa), land: HTESSEL (land surface scheme built in IFS), ocean: NEMO3.6 (ORCA1 tripolar primarily 1 deg with meridional refinement down to 1/3 degree in the tropics; 362 x 292 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: LIM3. 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: aerosol: MAM3, atmos: CAM5.3 (1deg; 288 x 192 longitude/latitude; 30 levels; top at ~2 hPa), land: CLM4.5 (BGC mode), ocean: NEMO3.6 (ORCA1 tripolar primarly 1 deg lat/lon with meridional refinement down to 1/3 degree in the tropics; 362 x 292 longitude/latitude; 50 vertical levels; top grid cell 0-1 m), seaIce: CICE4.0. 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: aerosol: none, prescribed MACv2-SP, atmos: ECHAM6.3 (spectral T127; 384 x 192 longitude/latitude; 95 levels; top level 0.01 hPa), land: JSBACH3.20, landIce: none/prescribed, ocean: MPIOM1.63 (tripolar TP04, approximately 0.4deg; 802 x 404 longitude/latitude; 40 levels; top grid cell 0-12 m), ocnBgchem: HAMOCC6, seaIce: unnamed (thermodynamic (Semtner zero-layer) dynamic (Hibler 79) sea ice model). 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. |
XX | The German Weather Service (Deutscher Wetterdienst, DWD) / Max Planck Institute for Meteorology (MPI-M) | XX |
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: aerosol: UKCA-GLOMAP-mode, atmos: MetUM-HadGEM3-GA7.1 (N216; 432 x 324 longitude/latitude; 85 levels; top level 85 km), land: JULES-HadGEM3-GL7.1, ocean: NEMO-HadGEM3-GO6.0 (eORCA025 tripolar primarily 0.25 deg; 1440 x 1205 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: CICE-HadGEM3-GSI8 (eORCA025 tripolar primarily 0.25 deg; 1440 x 1205 longitude/latitude). 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
For the The DCPP dataset experiments in the CDS each model runs , are a suite of overlapping simulations that are initialised annually every year throughout the experiment's duration. Each model has run the same experiment using the same model with slightly different settings 10 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:
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duration of the start-date range specified by the experiment. The exact start-dates begin in the November of the year preceding the forecast period to allow for DJF (December, January, February) seasonal averages to be calculated. There are 10 ensemble members for each start-date.
The start-date ensemble is reflected in the DCPP data with an additional 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<d>i<d>p<d>f<d> where d are positive integers
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Parameter listings
Data for the dcppA-hindcast experiment 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.
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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 5 indices (ensemble identifiers) s<yyyy>-r<W>i<X>p<Y>f<Z>, where yyyy is the start year and W, K, Y and Z are positive 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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