E(x,t) = ∑i=1N
Ei(x) pi(t)
The EOFs and PCs are chosen such that for small N the
difference with the full field is as small as possible.
In this field you can choose how many EOFS (and PCs) you want to have
computed, and how the difference should be evaluated.
More EOFs only take slightly more time to compute, so feel free to
give a large number.
The EOF decomposition can be defined in two ways. The first is to
minimise the difference in absolute units, for instance in mb or mm/dy. The
second is to minimse the fraction of the variability at each point
that is explained by the EOF decomposition. The first method
emphasises the areas in which the variability is large, the second one
treats all areas equally.
The option "normalize each yearly period to s.d. of that period"
normalises the input values by the standard deviation of those values. This
is done per yearly period. For example, for monthly data, the standard deviation
is calculated across all data points for January, and then every January value is divided
by this value. The same process is applied for all months. For daily data, each day of the year
is divided by the standard deviation for that day across all years in the dataset.
Note: This is entirely separate from the second Normalize option, carried out on the processed EOF maps and PC time series.
See here.