Hi Ken,
As hoped, Jonathan, has already responded. I'm off on a tangent here ...
I want here to comment on a *wee* (and admittedly debatable) side
metadata issue -- the proper use of the "long_name" attribute. The
long_name is typically used as the source of a title string for plots
and listings. My view is that a long name such as "Objectively Analyzed
Mean", which names a statistic, but does not name the underlying
parameter, creates a bit of a documentation risk. No doubt the global
'title' attribute is expected to fill in the missing context -- stating
in this example that this is a Sea Surface Temperature data set. That
is probably sufficient for most basic plotting situations. But when one
wants to offer automated products, like computed differences between
fields (as LAS does), it can become impractical to carry along the title
string of each dataset used in a calculation. The number of
annotations needed just grows and grows. As Jonathan's answer has
implied, annotations about cell_methods are also required.
I guess I am lobbying a viewpoint that the long_name attached to each
variable should represent a best effort to have each variable
self-document who she is. Thus "Objectively Analyzed Mean SST" would
be preferable to "Objectively Analyzed Mean". Does this seem reasonable?
- Steve
=======================
On 3/22/2013 10:29 AM, Kenneth S. Casey - NOAA Federal wrote:
> Hi Everyone,
>
> At US NODC we are trying to sort out how to best document a gridded
> dataset that contains a number of variables. For example, we have a
> sea water temperature gridded dataset, and it contains 6 variables:
>
> objectively analyzed mean
> statistical mean
> number of observations
> standard deviation
> standard error of the mean
> 'grid points'
>
> We are currently documenting, for example, the objective analyzed
> mean temperature variable in this netCDF file like this:
>
> float t_an(time, depth, lat, lon) ;
> t_an:standard_name = "sea_water_temperature" ;
> t_an:long_name = "Objectively Analyzed Mean" ;
> t_an:comment = "Objectively analyzed climatologies are
> the objectively interpolated mean fields for an oceanographic variable
> at standard depth levels for the World Ocean." ;
> t_an:cell_methods = "area:mean depth:mean time:mean" ;
> t_an:grid_mapping = "crs" ;
> t_an:units = "degrees_celsius" ;
> t_an:FillValue = 9.96921e+36f ;
>
> That makes reasonable sense to an application client because the
> variable contains a temperature value, so the standard_name makes
> sense. Also, cell methods here represent how the data in the cells
> are compiled. They do not directly describe the "thing" in those
> cells but what kinds of procedures where used (in this case, the grid
> cell, with time, lat, lon, and depth dimensions, is a computed by
> calculating mean). We think this is the correct way to
> represent this particular variable.
>
> But what we should do for the statistical variables is less clear. We
> can use standard name modifiers to provide reasonable standard names,
> but only four are defined currently:
>
> http://cf-pcmdi.llnl.gov/documents/cf-conventions/1.6/apc.html
>
> detection_minimum, number_of_observations, standard_error, and status_flag
>
> How would we handle the variables like standard deviation? Right now,
> we could not provide a standard name with a modifier, so we'd have to
> rely on long_name and comment attributes which is not very
> satisfactory. We wouldn't want to use
>
> t_standard_deviation:standard_name =
> "sea_water_temperature" ;
>
> because the values in the variable are not sea water temperature, they
> are the standard deviation of sea water temperature. Is the solution
> to propose some new standard name modifiers, or are we missing
> something? This issue seems like it should be a fairly common problem.
>
> Thanks,
> Ken
>
>
>
> Kenneth S. Casey, Ph.D.
> Technical Director
> NOAA National Oceanographic Data Center
> 1315 East-West Highway
> Silver Spring MD 20910
> 301-713-3272 x133
> http://www.nodc.noaa.gov <http://www.nodc.noaa.gov/>
>
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Received on Fri Mar 22 2013 - 12:22:38 GMT
