ORIGINAL

This catalogue entry provides daily and monthly global climate model data from Decadal Climate Predictions Project (DCPP) experiments, part of the sixth phase of the Coupled Model Intercomparison Project (CMIP6). The decadal data in the Climate Data Store (CDS) are a targeted, quality-controlled subset of the full DCPP.

CMIP6-DCPP data addresses the ability of the climate system to be predicted on annual, multi-annual and decadal timescales. The information generated by the DCPP can provide a basis for socially relevant operational climate predictions on annual to decadal timescales. The use of these data is mostly aimed at:

• assessing historical decadal prediction skill;
• exploring the potential for operational forecast production.

The term "experiments" in the context of DCPP refers to two categories of simulations:

• hindcast experiments which cover the recent past from 1960 and are constrained by climate observations.
• forecast experiments that are initialised with observations from 2019 onwards and are constrained by conditions of the ssp245 illustrative climate scenario.

For DCPP experiments, each model is used to produce overlapping simulations that are initialised annually throughout the experiment.

This catalogue entry provides two-dimensional data, along with an option to apply spatial and/or temporal subsetting to data requests. This feature of the global climate projection dataset relies on compute processes run simultaneously in the ESGF nodes, where the data are originally located.

The data are produced by the participating institutes of the sectoral decadal demonstrator service conducted by C3S.

UPDATED

This catalogue entry provides daily and monthly global climate model data from Decadal Climate Predictions Project (DCPP) experiments, part of the sixth phase of the Coupled Model Intercomparison Project (CMIP6). The decadal data in the Climate Data Store (CDS) are a quality-controlled subset of the full DCPP.

CMIP6-DCPP data addresses the ability of the climate system to be predicted on annual, multi-annual and decadal timescales. The information generated by the DCPP can provide a basis for socially relevant operational climate predictions on annual to decadal timescales. The use of these data is mostly aimed at:

• assessing historical decadal prediction skill (hindcasts);
• exploring the potential for operational forecast production (forecasts).

The term "experiments" in the context of DCPP refers to two categories of simulations:

• hindcast experiments which cover the recent past from 1960 and are constrained by climate observations.
• forecast experiments that are initialised with observations from 2019 onwards and are constrained by conditions of the ssp245 illustrative climate scenario.

For DCPP experiments, each model is used to produce ensemble of simulations that are initialised annually. The ensemble members provide uncertainty information and they are concatenated into one data file for each model.

This catalogue entry provides daily and monthly near surface air temperature, precipitation, sea level pressure, daily minimum/maximum near surface air temperature and 500 hPa geopotential height data. The data is accompanied with an option to apply spatial and/or temporal subsetting to data requests.

The data have been produced by the institutes participating in the sectoral decadal demonstrator service developed by

The Climate Model Intercomparison Project (CMIP)

The Climate Model Intercomparison Project (CMIP) was established in 1995 by the World Climate Research Program (WCRP) to provide climate scientists with a database of coupled Global Circulation Model (GCM) simulations.

The CMIP process involves institutions (such as national meteorological centres or research institutes) from around the world running their climate models with an agreed set of input parameters. The modelling centres produce a set of standardised output, when combined these produce a multi-model dataset that can be shared internationally between modelling centres and the results compared. 

Analysis of the CMIP data allows for improving understanding of

• the climate, including its variability and change, 
• the societal and environmental implications of climate change in terms of impacts, adaptation and vulnerability,
• informing the Intergovernmental Panel on Climate Change (IPCC) reports. 

...

• determining why similarly forced models to produce a range of responses,
• evaluating how realistic the different models are in simulating the recent past,
• examining climate predictability.

CMIP5

The fifth phase of Coupled Model Intercomparison Project (CMIP5, 2008-2012) involved 24 modelling centres running their climate models under the prescribed conditions to produce the multi-model dataset designed to advance our knowledge of climate (Taylor et al. 2012). The scientific analyses from CMIP5 were used extensively in the Intergovernmental Panel on Climate Change (IPCC) 5th Assessment Report (IPCC AR5), published in September 2013. 

...

the Copernicus Climate Change Service (C3S)

...

To obtain full details of the whole CMIP5 data archive please refer to the full documentation at the Program for Climate Model Diagnosis & Intercomparison (PCMDI). An introductory factsheet for an overview of an IPCC subset also provides a useful guide to the CMIP5 data. 

in 2021. This demonstrator provided decadal prediction products tailored to specific users from the agriculture, energy, infrastructure and insurance sectors. 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/sectoral-applications-decadal-predictions Any application - similar to or different from these examples - needs to consider and apply the required data processing with care. 

ALTERNATIVE LAST PARAGRAPH OF THE OVERVIEW WITHOUT LINK:

The data have been produced by the institutes participating in the sectoral decadal demonstrator service developed by the Copernicus Climate Change Service (C3S) in 2021. This demonstrator provided decadal prediction products tailored to specific users from the agriculture, energy, infrastructure and insurance sectors. The data were used in these demonstrators following processing procedures necessary to extract valid information (e.g., bias adjustment). Any application - similar to or different from these examples - needs to consider and apply the required data processing with care.

CHANGES IN THE OVERVIEW TABLES

• Include "Update frequency" in the data description table, we can mention there: "no updates planned".
• "Vertical coverage" to "vertical resolution" (to be checked)
• "Vertical coverage": near surface and 500 hPa depending on the variable 
• Tooltip updates:
  • Model: "Consult the Documentation section to learn more about these models"
  • Base year: "The start year of the forecast"

CHANGES IN TITLE AND LINK

Proposed modified link: projections-CMIP6-decadal-protoype

Proposed modified title: CMIP6 predictions underpinning the C3S decadal prediction prototypes

CMIP6

...