In an Empirical Orthogobal Function (EOF) decomposition the normalisation of the EOF maps and PC time series in arbitarry. Consider the definition

E(x,t) = ∑_{i=1^N Ei(x) pi(t)}

One can multiply the EOF E_i(x) by an arbitrary factor A as long as you divide the time series p_i(t) by the same factor A.

You can choose between four normalisation schemes.

• Spatial maximum one. This implies that all EOF plots will run from -1 to +1, which makes them easy to plot. The PC time series will have the units of the original field and smaller amplitudes for higher values of EOF number i.
• Spatial variance one. resembles the previous option, but makes the EOFs and PCs more comparable if there are few isolated areas with large amplitude in the EOF.
• Time series maximum one. Not very useful, included for symmtery. Time series variance one. This option implies that the EOF maps have the units of teh original field. They will have smaller amplitude for larger EOF number i.