This message came from the CF Trac system.  Do not reply.  Instead, enter your 
comments in the CF Trac system at https://cf-pcmdi.llnl.gov/trac/.

#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

 > 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:55>
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.

Reply via email to