Sea surface temperature patterns in the Tropical Atlantic: Principal component analysis and nonlinear principal component analysis

摘要

The tropical Atlantic Ocean exhibits several modes of interannual variability such as the equatorial (or Atlantic Nino) 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 degrees W - 20 degrees E, 26 degrees S - 22 degrees N) for the period 1950 to 2005. The objective is to compare the modes extracted through this statistical analysis to those previously extracted through simpler principal component analysis (PCA). It is shown that the first NLPCA mode explains 38% of the total SST variance compared to 36% by the first PCA while the second NLPCA mode explains 22% of the total SST variance compared to 16% by the second PCA. The first two NLPCA modes marginally explain 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 Nino structure is spatially more stable than the Atlantic dipole structure.