With the aim of identifying the physical causes of variability of a given d
ynamic system, the geophysical community has made extensive use of the stat
istical component extraction techniques. We introduce here a recently devel
oped algorithm based on information theory: the Independent Component Analy
sis. This technique presents two major advantages over classical methods. F
irst, it aims at extracting statistically independent components where clas
sical techniques search for decorrelated components (i.e, a weaker constrai
nt). Secondly, the linear hypothesis for the mixture of components is not r
equired. This new method is presented in the context of geophysical time se
ries analysis. The ICA algorithm is applied to the study of the variability
of the tropical Sea Surface Temperature, with a particular emphasis on the
analysis of the links between El-Nino/Southern Oscillation and the Atlanti
c SST variability. ((C) Academie des sciences/Elsevier, Paris.).