Dear all,
perhaps I am not aware of the previous discussions on this issue, but reading through the comments about the "count" modifier, I am wondering whether the concept of standard_name modifiers is a good solution. Once again, I am presently biased towards observational data (ozone time series from stations), and I can think of a couple of use cases here. A typical thing to do with obs. data is to create a monthly means file from hourly observations. Then we would be interested in the mean value, the standard deviation, the number of valid(!) data points and potentially other parameters (percentiles, mean of daytime values, mean of nighttime values, etc.). Is it practical to include all this in pre-defined standard_name modifiers? Or wouldn't it make more sense to define some sort of "operator" attribute which describes what has been done to the data? In order to be traceable, one would of course have to define the allowed operations, but ultimately it may become possible to even define more complex formulae wh
ich could then describe operations such as differences between a model realisation and an ensemble, a normalized mean bias between model and observations, a root mean square error, etc.
For "CF checking" I do see a point though that actually advocates the present approach: if I am not mistaken, the the standard_name attribute is the only attribute that defines which units a variable should have, so the CF checker needs to parse only standard_name to find out if the given units are allowed. With a new "operator" attribute one would need to parse another attribute (and first check if it exists).
Best regards,
Martin
= Dr. Martin G. Schultz, IEK-8, Forschungszentrum J?lich =
= D-52425 J?lich, Germany =
= ph: +49 (0)2461 61 2831, fax: +49 (0)2461 61 8131 =
= email: m.schultz at fz-juelich.de =
= web:
http://www.fz-juelich.de/icg/icg-2/m_schultz =
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Received on Thu Feb 24 2011 - 08:23:17 GMT
