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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 John We agree about the 2D radar data (two independent dimensions) and the trajectory (one independent dimension). Table 9.1 defines a timeseries as "a series of data points at the same spatial location with monotonically increasing times". A collection of timeseries in a discrete sampling geometry has data(i,o) and mandatory coordinates x(i) y(i) t(i,o), where i is the instance dimension and o the element dimension i.e. {{{ float lat(stations); float lon(stations); float time(time); float temp(stations,time); temp:coordinates="lat lon"; }}} in the orthogonal representation, like example H.2. In this representation, `time` is a 1D coordinate variable, because it's the same for all the stations, so it does not have the instance dimension. If there is only one station, you can keep the size-one instance dimension `stations=1`, or you can omit it (last para of sect 9.2): {{{ float lat; float lon; float time(time); float temp(time); temp:coordinates="lat lon"; }}} like example H.4. According to this ticket, the interpretations are different. If you keep the size-one dimension, you are making explicit that lat and lon are related: they are two coordinates which share a single dimension of the domain. If you drop the size-one dimension, lat and lon are independent dimensions. That means the single timeseries is equivalent to {{{ float lat(lat); float lon(lon); float time(time); float temp(time,lat,lon); }}} with `lat=1` and `lon=1`. That is, it's regarded as having been extracted from a 2D array of timeseries. Physically, this is a perfectly fine interpretation; that might indeed be how the single timeseries was obtained. Therefore I think that the two interpretations are physically distinct, and this ticket recognises them as distinct. However, it is clearly not difficult to convert between them, as the data is completely unaffected; they only differ through the presence and absence of size-one dimensions. However, this kind of data: {{{ float lat(time); float lon(time); float time(time); float temp(time); temp:coordinates="lat lon"; }}} is not a timeseries feature, according to Table 9.1. It's a trajectory. In a timeseries, the x and y coordinates do not vary with the element dimension (`time` in this case). Best wishes Jonathan -- Ticket URL: <https://cf-pcmdi.llnl.gov/trac/ticket/104#comment:53> 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.
