Dear Seth > Attached below are the 93 unique values for surface types from > these 3 models. If it looks like we could hash out the details > and extend the existing area_types list could be extended to > cover this list in fairly short order, then I think we can say > that the current system will be sufficient. If it's a bigger > job than that, then I don't think it's adequate.
I don't suppose we could do this quickly, as I expect you anticipate. The reason why it would take time is because we would have to establish whether any of these terms actually meant the same thing. So this raises the question of what the intended use of the metadata is. There could be two aims: * describe the contents of each dataset by itself. * indicate which quantities in one dataset are to be regarded as comparable with quantities in another dataset. The first aim is easier. It can be met by defining an attribute which is allowed to contain some values from a vocabulary, which could be a vocabulary external to CF. Provided the values in the vocabulary are self-explanatory, the data is self-describing. However, if there are several datasets using different vocabularies, as you describe, this approach doesn't address the second aim, which is the one that is usually more difficult. It's the second aim which is particularly important to CF; that's what standard names are for. It can't be done without understanding what all the terms in each vocabulary mean, and that takes effort! Of course, we could allow area_type to have non-standardised contents, or use a different attribute for this purpose. That postpones the effort until the time when you want to do it, so it serves the purpose of data archival more than data intercomparison, I suppose. Best wishes Jonathan _______________________________________________ CF-metadata mailing list [email protected] http://mailman.cgd.ucar.edu/mailman/listinfo/cf-metadata
