| description abstract | The interaction between tropical Atlantic variability and El Niño?Southern Oscillation (ENSO) is investigated using three ensembles of atmospheric general circulation model integrations. The integrations are forced by specifying observed sea surface temperature (SST) variability over a forcing domain. The forcing domain is the global ocean for the first ensemble, limited to the tropical ocean for the second ensemble, and further limited to the tropical Atlantic region for the third ensemble. The ensemble integrations show that extratropical SST anomalies have little impact on tropical variability, but the effect of ENSO is pervasive in the Tropics. Consistent with previous studies, the most significant influence of ENSO is found during the boreal spring season and is associated with an anomalous Walker circulation. Two important aspects of ENSO?s influence on tropical Atlantic variability are noted. First, the ENSO signal contributes significantly to the ?dipole? correlation structure between tropical Atlantic SST and rainfall in the Nordeste Brazil region. In the absence of the ENSO signal, the correlations are dominated by SST variability in the southern tropical Atlantic, resulting in less of a dipole structure. Second, the remote influence of ENSO also contributes to positive correlations between SST anomalies and downward surface heat flux in the tropical Atlantic during the boreal spring season. However, even when ENSO forcing is absent, the model integrations provide evidence for a positive surface heat flux feedback in the deep Tropics, which is analyzed in a companion study by Chang et al. The analysis of model simulations shows that interannual atmospheric variability in the tropical Pacific?Atlantic system is dominated by the interaction between two distinct sources of tropical heating: (i) an equatorial heat source in the eastern Pacific associated with ENSO and (ii) an off-equatorial heat source associated with SST anomalies near the Caribbean. Modeling this Caribbean heat source accurately could be very important for seasonal forecasting in the Central American?Caribbean region. | |
