I need to test for correlation of 4 sets of weather parameters between 2 sites. I am not interested in interactions between the parameters. Because no weather parameter is independent from other weather parameters, if I was simply trying to determine if each parameter differed between the 2 sites, I would use a MANOVA followed by multiple-comparisons t-tests, and correct for family-wise error using a Bonferroni method. But since I want to see if the parameters are correlated between the sites, I'm not sure what to do.
Is there an overarching test (like MANOVA) that should be applied prior to what amounts to multiple-comparison correlations? Or can I just do multiple Spearman's correlations and interpret from there?
EDIT: I suppose in the long run it doesn't really matter to me if the 2 parameters are statistically significantly correlated. What will matter is the strength of their correlations. That, from what I understand, is subjective (based on the field)...is this correct? In this respect, is there any multiple-comparison sort of thing I should be keeping in mind?