Dear all I think Philip's posting points out that this disagreement is partly caused by a confusion. I agree with his distinction of two cases.
Perhaps in Ken's use case, the standard deviation describes the spread of a number of measurements that are regarded as samples from a population. The difference between the samples is random error, not a dependence on time or space that is of interest to the user of the dataset. This also sounds like what Nan means by, "We collect in situ data, and I know that MANY of our instruments output the mean of several measurements, few do single spot samples." If the instrument itself does not output the individual measurements, the variation among them as a function of time or space is obviously of no geophysical interest. I agree that this standard deviation is a kind of measurement property. As Ken says, the standard error is usually calculated as the sample standard deviation divided by the square root of the number in the sample. However I appreciate that you might wish to report the standard deviation instead of the standard error. To do this, I agree that we would need a new standard_name modifier, which I suggest should be sample_standard_deviation to avoids its being confused with any other kind of standard deviation. Perhaps that is the answer I should have given to Ken's first question, instead of asking whether it was a temporal or a spatial standard deviation. In fact it is neither. Going on to the wider question, I agree with Ken that a mean is just as much a statistical operation as a standard deviation. Only a point measurement (which is also one of the cell_methods of Appendix E) is the "true" geophysical quantity. All the other methods are statistical ways of representing variation of that quantity within the cell. It probably doesn't seem surprising to regard a mean as the "same" quantity, nor the mode and median perhaps, but maybe you begin to feel uncomfortable when moving on to the maximum and minimum, the range (absolute difference between max and min, which is going to be added as a cell_method in the next version of CF, https://cf-pcmdi.llnl.gov/trac/ticket/65), and finally the standard deviation and the variance, the last of which has different units. All these methods belong to the same family, and it seems to me it would be arbitrary and therefore unsatisfactory to choose a certain level of surprise or discomfort in order to decide when it was no longer the "same" geophysical quantity. The only solution, I think, is for everyone to learn that the standard name is only a *part* of the description of the attribute, as John says. John asked whether the difference between cell_methods and standard_name modifiers could be clearly stated. My understanding is that standard_name modifiers denote ancillary variables (they were introduced to CF at the same time), whose purpose is to provide metadata about the individual values of another data variable (start of section 3.4), while cell methods indicate the statistical methods whereby the data values represent variation within cells. This is a difference, but it might not be sufficiently obvious to require them to be different features in CF. The sample standard deviation *could* be represented by cell_methods, if we introduced a notional axis of sample, to index the samples, and then collapsed it to size one, like we do for a time-mean or a zonal mean. The sample standard deviation would then be described in cell_methods as "sample: standard_deviation". Likewise, the number of observations could be regarded as a cell_method that counted the size of its (sample) axis. If we do not wish to maintain the difference, we could simplify the standard by abolishing standard_name modifiers and creating some new cell_methods, some of which might be of a different kind from before because they wouldn't refer to a particular axis. Cheers Jonathan _______________________________________________ CF-metadata mailing list [email protected] http://mailman.cgd.ucar.edu/mailman/listinfo/cf-metadata
