Wavelet Analysis provides a new orthogonal basis set which is localized in both physical space and Fourier transform space. Empirical Orthogonal Functions (EOFs), on the other hand, provide a global representation of data sets. Here we investigate the various ways in which one can combine these basis sets for optimal representation of data. EOFs represent the global large scale information and wavelet analysis are used to supplement this large scale information with local fine scale information. Here we begin to explore the application of these two basis sets for outputs from an Ocean General Circulation Model and we explore various applications, including data assimilation.
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