Dear Martin > what is the difference between a mean value and an observation count? > You may add the 25th percentile to this list as well. As far as I can tell, > the cell_methods attribute should be best suited for all of these and I don't > see a need to work with standard_name modifiers
Though this has not been thoroughly debated, I think the reasons why there are these two different mechanisms are that the two functions are distinguished like this: * cell_methods represents subgrid variation. They always imply that the data variable formerly had a higher dimensionality or a higher resolution, and they refer to one or more dimensions of the data on which the reduction or collapse was done. The relationships indicated by standard_name modifiers do not refer to particular dimensions of the data. * The operations cell_methods records are done on the data in the variable itself. Ancillary variables, described by standard_name modifiers, are extra information about the data in the variable. This cannot be inferred from the data; they are metadata, really, not a statistical reduction of data. However, I agree there's a similarity. In particular, both of them were motivated by a desire to avoid proliferation of standard_names because of the need to describe very common operations that could be applied to anything, and both of them could modify the units. Best wishes Jonathan _______________________________________________ CF-metadata mailing list [email protected] http://mailman.cgd.ucar.edu/mailman/listinfo/cf-metadata
