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Changes between Version 7 and Version 8 of PDAF_eofcovar

v7	v8
34	34	The multivariate normalization computes for each field in the state vector its standard deviation and then normalizes the field variability for the EOF computation so that it is one. Then the singular value decomposition is computed. Finally the fields are re-scaled to their original values. To use the multivariate normalization one has to define the number of different fields in a state vector (`nfields`), the dimension of all fields (`dim_fields`) and the offset of each field from the start of the state vector (`offsets`). The intention of the multivariate normalization is to ensure that all fields have comparable variability and are hence equally represented by all EOFs. Without the normalization a field with particularly small variability might be essentially absent from the leading EOFs.
35	35
36		The use of the EOF decompositon to generate a covariance matrix with PDAF_eofcovar is exemplified in the Lorenz-96 model example (see ~~testsuite/src/lorenz96/tools/generate_covar.F90~~).
	36	The use of the EOF decompositon to generate a covariance matrix with PDAF_eofcovar is exemplified in the Lorenz-96 model example (see models/lorenz96/tools/generate_covar.F90 (from PDAF 1.15; before it was located in testsuite/src/lorenz96/tools/generate_covar.F90)).
37	37
38	38	=== Mean state computation and subtraction (remove_mstate) ===