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
Received on Wed Jun 05 2013 - 07:08:25 BST
