How to know to which PC (Principal Component) a sample belongs in EOF/PCA
I recommend you read Monahan et al. (1990) for a thorough explanation of Empirical Orthogonal Functions. I suggest you pay attention to the way the principal components are extracted. Ultimately, there is no guarantee that a sample belongs to a specific component. What you are working with is eigenvalues/eigenvectors and thus a specific data point can have influences from multiple components. The EOF provides a time series of eigenvalues for each component. The larger the eigenvalue for that component at a specific time, the more that component explains the data point.

If what you need is to assign a data point to a component, I would recommend a cluster analysis instead. For instance Smith &amp; Aretxabaleta (2007) present an improved methodology to separate regimes that outperforms the EOF analysis in an ENSO-influenced dataset.