Following the CMIP6 Decadal Climate Prediction Project (DCPP) protocol (Boer et al., 2017) decadal prediction experiments consist of 10-member ensembles of 5-year hindcasts, starting every second year from 1960 to the present, using historical radiative forcing conditions (including green-house gases, aerosols and solar irradiance variability), followed by SSP2-4.5 scenario settings for the future. The ocean-sea ice initial state is provided by an ensemble of ocean synthesis differing for assimilation methodologies, assimilated data, and atmospheric forcing fluxes (Yang et al., 2016). The alternative ocean states are combined with two different analyses of the land-surface, providing an estimate for the uncertainty of the land surface state. Initial conditions for the atmosphere are obtained from the ERA40/Era-Interim reanalyses. The use of alternative ocean-sea ice syntheses and land analyses to constrain the initial state of the climate system yields the required perturbation of the full three-dimensional ocean/sea ice/land 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 CMCC-CM2-SR5 global coupled general circulation model (Cherchi et al., 2019).
The decadal prediction system is currently under development and no decadal hindcasts are available yet. Expected by early summer 2019.
References:
- Boer, G. J., Smith, D. M., Cassou, C., Doblas-Reyes, F., Danabasoglu, G., Kirtman, B., Kushnir, Y., Kimoto, M., Meehl, G. A., Msadek, R., Mueller, W. A., Taylor, K. E., Zwiers, F., Rixen, M., Ruprich-Robert, Y., and Eade, R., 2016. The Decadal Climate Prediction Project (DCPP) contribution to CMIP6, Geosci. Model Dev., 9, 3751-3777, https://doi.org/10.5194/gmd-9-3751-2016
- Cherchi, A., Fogli, P. G., Lovato, T., Peano, D., Iovino, D., Gualdi, S., et al. (2019). Global mean climate and main patterns of variability in the CMCC-CM2 coupled model. Journal of Advances in Modeling Earth Systems, 11. https://doi.org/ 10.1029/2018MS001369
- Yang, C., S. Masina, and A. Storto (2016). Historical ocean reanalyses (1900-2010) using different data assimilation strategies: Historical Ocean Reanalyses, 2016, Quarterly Journal of the Royal Meteorological Society, doi: 10.1002/qj.2936