Model Intercomparison Project
| Attribute | Value |
|---|---|
| mip_abstract | The Decadal Climate Prediction Project (DCPP) is a coordinated multi-model investigation into decadal climate prediction, predictability, and variability that builds on the work of DCPP in CMIP6. In particular, DCPP addresses a range of scientific issues that are highly relevant to both science and society, including the ability to improve near-term climate predictions, the skill that is potentially available, and the mechanisms responsible for such long time-horizon predictability. In CMIP7, DCPP will build on recent improvements in models, data assimilation, and model initialization to provide an updated reference of decadal climate variability and prediction skill. Furthermore, DCPP will further coordinate testing of model resolution, as well as capitalize on interest on multi-annual predictions to expand the scope of coupled multi-model prediction as part of CMIP7. DCPP will contribute to CMIP7 as well as make key contributions to the World Climate Research Program’s lighthouse activity on Explaining and Predicting Earth System Change (EPESC) and the World Meteorological Organisation lead-centre activity on Annual-to-Decadal Climate Prediction (LC-ADCP). As in CMIP6, DCPP will likely consist of three components. Component A encompasses the production of an archive of retrospective forecasts to be used to assess and understand historical decadal prediction skill. In comparison with CMIP6, the highest priority retrospective predictions (or hindcasts) will be a core set (the DCPP-DECK) which focuses on a shorter verification window with fewer start dates, a minimal ensemble size, and multi-year forecast lead times. It is envisioned that such reduced requirements of the DCPP-DECK will encourage more groups to take part in DCPP in CMIP7. The DCPP-DECK will also allow DCPP to diversify into questions it has not currently addressed due to the expense of the experiment, including for example high-resolution initialized predictions and large ensembles of multi-year predictions. Component B organizes the ongoing production and dissemination of real-time multi-model decadal forecasts. Component C will involve more idealized simulations in order to better understand the mechanisms of internal or externally forced decadal climate variability. Modelling groups will be invited to participate in as many of the components of DCPP as interests them, although the DCPP-DECK will be the core requirement for Component A and Component B. |
| mip_long_name | Decadal Climate Prediction Project |
| mip_website | https://www.wcrp-climate.org/dcp-overview |
| name | DCPP |
| uid | 527f5c70-8c97-11ef-944e-41a8eb05f654 |