The tropical Atlantic Ocean exhibits several modes of interannual variability such as the equatorial (or Atlantic Niño) mode, and meridional (or Atlantic dipole) mode. Nonlinear principal component analysis (NLPCA) is applied on detrended monthly Sea Surface Temperature Anomaly (SSTA) data from the tropical Atlantic Ocean (30°W-20°E, 26°S-22° N) for the period 1950 to 2005. The objective is to compare the modes extracted through this statistical analysis to those previously extracted through the more simple principal component analysis (PCA). It is shown that the first mode of NLPCA explains 38% of the total variance of SST compared to 36% by the first PCA while the second mode of NLPCA explains 22% of the total variance of SST compared to 16% by the second PCA. The first two NLPCA modes explain marginally more of the total data variance than the first two PCA modes. Our analysis confirms results from previous studies and, in addition, shows that the Atlantic El Niño structure is spatially more stable than the Atlantic dipole structure.