How to Compute the EOFs by SVD?

[ecastro]

Considering I have a matrix $\mathbf{A}$ which has a size of $M \times N$, how can I compute the Empirical Orthogonal Functions (EOFs) by Singular Value Decomposition (SVD)?

According to SVD, the matrix $\mathbf{A}$ is

$\mathbf{A} = \mathbf{U} \mathbf{\Sigma} \mathbf{V}^{T}$

where a superscript of $T$ denotes a transpose. Now, which are the EOFs in this equation, are they the rows of $\mathbf{V}^{T}$ or its columns (the rows of $\mathbf{V}$)?

Thank you in advance.

 

[akeleti8]

Hi there. The EOFs are the columns of V^T.

This site helps me to figure this out https://pmc.ucsc.edu/~dmk/notes/EOFs/EOFs.html. Goodnight from your atemporal interested in orthostatics guy.

Mod note: deleted broken link