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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 caron): Hi Jonathan: I think that this is the root of the disagreement/misunderstanding. Just as radar data is 2 dimensional (has 2 independent coordinates) but is "embedded" in 3D space (has 3 coordinates needed to represent its position on the earth), so too can time-series data be understood as a 1 dimensional subspace ("manifold") embedded in 4D space. But I dont think that proposal #104 allows that possibility. Regards, John Replying to [comment:55 jonathan]: > Dear John > > > Suppose that the data provider would prefer to represent her time- series data as having a single independent coordinate, ie is 1 dimensional? How would she do that under ticket #104? > > If the single timeseries is recorded like this: > > {{{ > dimensions: > station=1; > time=NNN; > variables: > float lat(station); > float lon(station); > float time(time); > float temp(station,time); > temp:coordinates="lat lon"; > }}} > > it would be interpreted as having two independent dimensions, one of space and one of time. The space dimension has size one and lat and lon both depend on it. Is that what you mean by 1D? It can't be truly 1D unless you omit the spatial information altogether. A timeseries discrete sampling geometry must have at least horizontal coordinates. > > If the single timeseries is recorded like this: > > {{{ > dimensions: > time=NNN; > variables: > float lat; > float lon; > float time(time); > float temp(time); > temp:coordinates="lat lon"; > }}} > > or like this: > > {{{ > dimensions: > lon=1; > lat=1; > time=NNN; > variables: > float lon(lon); > float lat(lat); > float time(time); > float temp(time,lat,lon); > }}} > > it would be interpreted as having three independent dimensions, of longitude, latitude and time, with the longitude and latitude both having size one. The main point of this ticket is that these last two representations are logically equivalent. > > So there are two logically distinct ways of representing a single timeseries. Which one you choose depends on whether you regard it as a single feature from a discrete sampling geometry (scattered points), or as the time-dependent data from a single point on a grid. > > Best wishes > > Jonathan -- Ticket URL: <https://cf-pcmdi.llnl.gov/trac/ticket/104#comment:56> 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.
