@CONFERENCE\{IMM2002-0173,
    author       = "A. A. Nielsen and K. B. Hilger and O. B. Andersen and P. Knudsen",
    title        = "A Bivariate Extension to Traditional Empirical Orthogonal Function Analysis",
    year         = "2002",
    pages        = "179-185",
    booktitle    = "Analysis of Multi-Temporal Remote Sensing Images (MultiTemp2001, Trento, Italy)",
    volume       = "",
    series       = "Series in Remote Sensing",
    editor       = "Lorenzo Bruzzone and Paul Smits",
    publisher    = "World Scientific",
    organization = "",
    address      = "Richard Petersens Plads, Building 321",
    url          = "http://www2.compute.dtu.dk/pubdb/pubs/173-full.html",
    abstract     = "This paper describes the application of canonical correlations analysis to the joint analysis of global monthly mean values of 1996-1997 sea surface temperature (SST) and height (SSH) data. The {SST} data are considered as one set and the {SSH} data as another set of multivariate observations, both with 24 variables. This type of analysis can be considered as an extension of traditional empirical orthogonal function (EOF) analysis which provides a marginal analysis of one variable over time. The motivation for using a bivariate extention stems from the fact that the two fields are interrelated as for example an increase in the {SST} will lead to an increase in the {SSH}. The analysis clearly shows the build-up of one of the largest El Niņo events on record. Also the analysis indicates a phase lag of approximately one month between the {SST} and {SSH} fields."
}