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The Decadal Climate Prediction Project (Boer et al., 2016) addresses the ability of the climate system to be predicted on annual, multi-annual and decadal timescales. The information generated by the DCPP and archived on the Earth System Grid Federation (ESGF) nodes and that is made accessible in the CDS can provide a basis for socially relevant operational climate predictions on annual to decadal timescales.
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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). The DCPP 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 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.
The CMIP6 data archive is distributed through the ESGF though many national centres have either a full or partial copy of the data. 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). 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 (see details at https://climate.copernicus.eu/sectoral-applications-decadal-predictions)
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The CDS provides data access for 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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Experiment Name | Experiment Long Name | Extended Description |
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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 | forecast initialized 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. The forecasts are performed with the same coupled atmosphere-ocean general circulation model (AOGCM), which was used to generate the hindcast data. The The hindcasts begin in November to allow for DJF (December, January, February) seasonal averages to be calculated. There There are 10 forecasts for each start date and forecasts run for 10 years. The models running these forecasts 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. DCPP forecast experiments form a basis for potential operational decadal forecast production. |
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