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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:

 This representation:

 {{{
 variables:
   float lat;
   float lon;
   float time(time);
   float temp(time);
     temp:coordinates="lat lon";
 }}}

 would be interpreted as having three independent dimensions. But thats
 incorrect, or at least should be optional. It should be possible to
 interpret this as having only one independent coordinate, ie "1D". But
 theres no way to represent that in proposal #104.

 The more general issue is that the number of dimensions and the number of
 coordinates have different meanings. Interpreting a scalar coordinate as a
 dimension 1 coordinate (meaning independent) complicates things without
 any gain that i can see. Better is to let it be understood as a dependent
 variable, and if you want to indicate that its an independent coordinate,
 then you have to make it a coordinate variable, ie give it a dimension of
 length 1, and add that dimension to the data.

 OTOH, theres nothing special about a scalar coordinate, and should not be
 handled in a special way in the data model. Its just an auxiliary
 coordinate, period. By the current definition of coordinate and auxiliary
 coordinate, its clearly an auxiliary coordinate.

 What this discussion has helped clarify for me is that coordinate
 variables are independent, and auxiliary coordinates are dependent
 variables. I think thats a really valuable advance in the data model.

 Things are complicated a bit by the DSG representations that introduce, eg
 a station dimension, that allows one to factor out the station info from
 the observation. Since all we have in the classic model are
 multidimensional arrays, one has to use dimensions for lots of things, not
 just to indicate the domain dimensionality. I guess we should look hard at
 the DSG representation to see what it says about the assertion that
 "coordinate variables are independent, and auxiliary coordinates are
 dependent variables".

 regards,
 John

-- 
Ticket URL: <https://cf-pcmdi.llnl.gov/trac/ticket/104#comment:58>
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