Impact of atmosphere and sub‐surface ocean data on decadal climate prediction

Abstract

We present a set of idealised model experiments that investigate the impact of assimilating different amounts of ocean and atmosphere data on decadal climate prediction skill. Assimilating monthly average sub‐surface temperature and salinity data successfully initialises the meridional overturning circulation and produces skillful predictions of global ocean heat content. However, when sea surface temperature data is assimilated alone the predictions have much less skill, particularly in the extra‐tropics. The upper 2000m temperature and salinity observations currently provided by the Argo array of floats are therefore potentially well suited to initialising decadal climate predictions. We note however that we do not attempt to simulate the actual distribution of Argo floats. Assimilating data beneath 2000m always reduces the RMSE, with the most significant improvements in the Southern Ocean. Furthermore, assimilating six hourly atmospheric observations significantly improves the forecast skill within the first year, but has little impact thereafter.