Dear John > If we use the time series featureType as example > > (from > http://cf-pcmdi.llnl.gov/documents/cf-conventions/1.6/cf-conventions.html#idp8307552) > > AFAIU, the orthogonal multidimensional representation would be: > > float humidity(station,time) > > not > > float humidity(lat, lon, time)
You are quite right, sorry. I was taking a step too far! The point is not only that the coordinates are size-1, but there is more than one of them. You are right that (lat,lon,time) can't be a timeseries discrete sampling geometry because it's got more than one spatial dimension. A timeseries DSG can have only one station (instance) dimension, and it is required to have both x and y coordinates. So these current rules mean that 2D field e.g. (lat,time) can't be a timeseries DSG. Like Mark, I saw the relevance of this to the discussion of scalar coordinates but I reached a different conclusion about it! At the moment, we are talking about the CF data model for version 1.5. DSGs were introduced in version 1.6. As a result of this discussion, it seems me that for a DSG (which is indicated by the presence of featureType), scalar coordinate variables have to be interpreted as auxiliary coordinate variables of an omitted size-one instance dimension. That is what is implied by section 9.2. It's different from the interpretation that is implied by section 5.7, which should exclude DSGs (and predates DSGs). I see no problem with having different interpretations for different purposes. Cheers Jonathan _______________________________________________ CF-metadata mailing list [email protected] http://mailman.cgd.ucar.edu/mailman/listinfo/cf-metadata
