The decadal predictions are performed in both retrospective (hindcast) and forecast mode. Specifically, the full set of prediction experiments consists of 3-members ensembles of 30-years simulations, starting at 5-years intervals from 1960 to 2005, using CMIP5 historical radiative forcing conditions (including green-house gases, aerosols and solar irradiance variability) for the 1960-2005 period, followed by RCP4.5 scenario settings for the 2005-2035 period. The ocean initial state is provided by ocean syntheses  differing by assimilation methodologies and assimilated data, but obtained with the same ocean model. The use of alternative ocean reanalyses yields the required perturbation of the full three-dimensional ocean state aimed at generating the ensemble members spread. A full-value initialization technique is adopted.

The dynamical model used to perform the decadal prediction experiments is the global coupled general circulation model developed at the Centro Euro-Mediterraneo per i Cambiamenti Climatici CMCC-CM (Scoccimarro et al., 2011).

To large extent, predictive skill of the system appears to be mainly driven by trends in the radiative forcing. However, after removing the trend, residual skill over specific regions of the ocean emerge in the near-term. Specifically, natural fluctuations in the North Atlantic sea-surface temperature (SST) associated with large-scale multi-decadal variability modes appear to be predictable in the 2-5 years range, consistent with significant predictive skill found in the Atlantic meridional overturning circulation over a similar time range. Forecast skill dependency on ocean initialization is analysed, revealing a strong impact of details of ocean data assimilation products on the system predictive skill. This points to the need of reducing the large uncertainties, which currently affect global ocean syntheses, in the perspective of providing reliable near-term climate predictions.

CMCC’s decadal simulations data are available through the CMCC/ESGF Data node

Further detail about the decadal prediction activity and information about the data availability can be obtained by contacting Alessio Bellucci.

  • Bellucci, A., S. Gualdi, S. Masina, A. Storto, E. Scoccimarro, C. Cagnazzo, P. Fogli, E. Manzini, and A. Navarra, 2011: Decadal Climate Predictions with a coupled OAGCM initialized with oceanic reanalyses. Climate Dynamics, Volume 40, Issue 5-6, 1483-1497, DOI: 10.1007/s00382-012-1468-z.
  • Bellucci, A., R. Haarsma, S. Gualdi, P. Athanasiadis and Co-Workers, 2014: An assessment of a multi-model ensemble of decadal climate predictions. Climate Dynamics, DOI: 10.1007/s00382-014-2164-y