EOF input averaging

Computing Empirical Orthogobal Functions (EOFs) can take a lot of
computer time. First the covariance matrix is estimated, this takes
The computation can therefore be sped up by computing the EOFs on a
coarser grid than the orginal data, reducing *N _{x}*. If
one averages over two grid boxes in longitude and two in latitude,

If an EOF computation takes too long, please kill it (using the link provided on the next page) and retry with larger numbers in these fields.

There are more efficient algorithms to compute he EOFs, but as far as I know these do not work when there is missing data. I plan to implement a faster method for fields without missing data in the future.

Percentage valid points

The covariance between two grid points is only considered valid when
percentage of the time series both have valid data. Enter a smaller
number to get more valid data in the EOFs, but the quality of these
data will be lower. A higher number gives fewer but higher-quality
data points. At very low values the EOF procedure will fail, as the
estimate of the covariance matrix is no longer positive-definite.