We perform a systematic study of the predict- ability of surface air temperature and precipitation in Southeastern South America (SESA) using ensembles of AGCM simulations, focusing on the role of the South Atlantic and its interaction with the El Nin˜ o-Southern Oscillation (ENSO). It is found that the interannual pre- dictability of climate over SESA is strongly tied to ENSO showing high predictability during the seasons and periods when there is ENSO influence. The most robust ENSO signal during the whole period of study (1949–2006) is during spring when warm events tend to increase the pre- cipitation over Southeastern South America. Moreover, the predictability shows large inter-decadal changes: for the period 1949–1977, the surface temperature shows high predictability during late fall and early winter. On the other hand, for the period 1978–2006, the temperature shows (low) predictability only during winter, while the precipi- tation shows not only high predictability in spring but also in fall. Furthermore, it is found that the Atlantic does not directly affect the climate over SESA. However, the experiments where air–sea coupling is allowed in the south Atlantic suggest that this ocean can act as a moderator of the ENSO influence. During warm ENSO events the ocean off Brazil and Uruguay tends to warm up through changes in the atmospheric heat fluxes, altering the atmospheric anomalies and the predictability of climate over SESA. The main effect of the air–sea coupling is to strengthen the surface temperature anomalies over SESA; changes in precipitation are more subtle. We further found that the thermodynamic coupling can increase or decrease the predictability. For example, the air–sea coupling signifi- cantly increases the skill of the model in simulating the surface air temperature anomalies for most seasons during period 1949–1977, but tends to decrease the skill in late fall during period 1978–2006. This decrease in skill during late fall in 1978–2006 is found to be due to a wrong simulation of the remote ENSO signal that is further intensified by the local air–sea coupling in the south Atlantic. Thus, our results suggest that climate models used for seasonal pre- diction should simulate correctly not only the remote ENSO signal, but also the local air–sea thermodynamic coupling.