Interpreting variability in global SST data using independent component analysis and principal component analysis.

The article presents an analysis and interpretation of global sea surface temperature (SST) data using independent component analysis (ICA) and principal component analysis (PCA). It states that PCA represents multivariates and expands the variance explicated by components. It compares the capacity of PCA, the Varimax rotation and ICA in demonstrating climate unpredictability in SST anomaly (SSTA) data distributed worldwide.