Synoptic Weather-Map Classification: Correlation Versus Sums-of-Squares

A sums-of-squares similarity measure (S), attributed to Kirchhofer, has been characterized by a number of synoptic climatologists as superior to correlation for quantifying the similarity between two gridded weather maps. The sums-of-squares metric and product-moment correlation, however, are virtually identical so S cannot be regarded as better. It is also suggested that correlation, in any form, is not generally a satisfactory measure of the similarity between weather maps of comparable units.