qIn brief, EOF analysis uses a set of orthogonal functions (EOFs) to represent a time series
in the following way:
q
q
q
qZ(x,y,t) is the original time series as a function of time (t) and space (x, y).
q EOF(x,
y) show the spatial structures (x, y) of the major factors that can account for the
temporal variations of Z.
q PC(t)
is the principal component that tells you how the amplitude of each EOF varies with
time.