CAS FGOALS-f3-L Model Datasets for CMIP6 DCPP Experiment

The outputs of the Chinese Academy of Sciences (CAS) Flexible Global Ocean-Atmosphere-Land System (FGOALS-f3-L) model for the decadal climate prediction project (DCPP) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) are described in this paper. The FGOALS-f3-L was initialized through the upgraded, weakly coupled data assimilation scheme, referred to as EnOI-IAU, which assimilates observational anomalies of sea surface temperature (SST) and upper-level (0-1000-m) ocean temperature and salinity profiles into the coupled model. Then, nine ensemble members of 10-year hindcast/forecast experiments were conducted for each initial year over the period of 1960-2021, based on initial conditions produced by three initialization experiments. The hindcast and forecast experiments follow the experiment designs of the Component-A and Component-B of the DCPP, respectively. The decadal prediction output datasets contain a total of 44 monthly mean atmospheric and oceanic variables. The preliminary evaluation indicates that the hindcast experiments show significant predictive skill for the interannual variations of SST in the north Pacific and multi-year variations of SST in the subtropical Pacific and the southern Indian Ocean.

Automated summary

This paper describes the outputs of the Chinese Academy of Sciences (CAS) Flexible Global Ocean-Atmosphere-Land System (FGOALS-f3-L) model for the decadal climate prediction project (DCPP) of the Coupled Model Intercomparison Project Phase 6 (CMIP6). The FGOALS-f3-L model was initialized using a weakly coupled data assimilation scheme, assimilating observational anomalies of sea surface temperature and upper-level ocean temperature and salinity profiles. Nine ensemble members of 10-year hindcast/forecast experiments were conducted for each initial year, showing significant predictive skill for interannual and multi-year variations of SST in specific regions.