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#104: Clarify the interpretation of scalar coordinate variables -----------------------------+---------------------------------------------- Reporter: jonathan | Owner: [email protected] Type: enhancement | Status: new Priority: medium | Milestone: Component: cf-conventions | Version: Resolution: | Keywords: -----------------------------+---------------------------------------------- Comment (by jonathan): Dear Mark That's a matter of interpretation. There is a choice to be made with this dataset. One possibility is to regard it the timeseries for a single point from a 4D dataset (time,vertical,lat,lon), in which case it is natural to regard the spatial coordinates as independent and with size one. That's how I represented it above. Alternatively, you could regard it as a single timeseries from a set of timeseries at scattered points. In that case, the spatial coordinates are not independent; there is one independent coordinate for location and another for time. For several timeseries, you would have for instance (this is like Example H.2 in the CF document) {{{ dimensions: time = 39238923; location=10; variables: float data(time,location); data:coordinates = "lat lon heightAboveGround heightAboveMsl"; float lat(location); float lon(location); float heightAboveGround(location) ; float heightAboveMsl(location); float time(time); }}} If you regard the single-location timeseries as a special case of the above, with `location=1`, then according to this ticket you cannot drop the "location" dimension of the size-one coordinates. You have to keep it in order to show that they are related and do not vary independently of one another. These are different points of view. Given the means of production of the data (e.g. was it selected from a GCM, or is it a single observational location), one of them is probably more natural than the other. The data- writer can choose, but it's easy for the analyst to convert one to the other if necessary, since the data are all the same, it's only a matter of size-one dimensions being included or not. The effect of this ticket is to give an unambiguous interpretation to the dataset, thus: * numeric scalar coordinate is equivalent to size-one (Unidata, COARDS, dimension) coordinate, and is an independent variable. * numeric size-one (CF) auxiliary coordinate is a dependent variable. I think this is nice and simple. I am getting a sense of deja vu, though. Best wishes Jonathan -- Ticket URL: <https://cf-pcmdi.llnl.gov/trac/ticket/104#comment:51> CF Metadata <http://cf-pcmdi.llnl.gov/> CF Metadata This message came from the CF Trac system. To unsubscribe, without unsubscribing to the regular cf-metadata list, send a message to "[email protected]" with "unsubscribe cf-metadata" in the body of your message.
