This paper shows the application of the empirical orthogonal unctions/principal component transformation on global sea surface height and temperature data from 1996 and 1997. A nonlinear correlation analysis of the transformed data is proposed and performed by applying the alternating conditional expectations algorithm. New canonical variates are found that indicate that the highest correlation between ocean temperature and height is associated with the build-up of the El Niño during the last half of 1997.
|Title of host publication||Proceedings of MultiTemp2001 Workshop, Trento, Italy|
|Publication status||Published - 2001|
|Event||Analysis of Multi-Temporal Remote Sensing Images - MultiTemp2001, Trento, Italy|
Duration: 1 Jan 2001 → …
|Conference||Analysis of Multi-Temporal Remote Sensing Images|
|City||MultiTemp2001, Trento, Italy|
|Period||01/01/2001 → …|