Hi, Unfortunately, I did not see your email until today, so I have not taken it into consideration when choosing how to handle probabilities for myself.
Like Roy, however, I believe that expressing probabilities as dimensions rather than attributes is the best approach for this. The problem with attributes is that if you have many variables and many probabilities or percentiles, you will get a huge amount of separate variables in your data set, and the relationship between them is not as easy to see as when (for example) all percentiles for air temperature are lumped into the same variable. If many users are like me, and use ncdump and ncview to look at the data, this will be a huge advantage. VG ----- Original Message ----- Fra: "Lorenzo Bigagli" <[email protected]> Til: [email protected], "vegard bones" <[email protected]> Kopi: "Nativi Stefano" <[email protected]> Sendt: 24. november 2011 18:07:07 Emne: [CF-metadata] standards for probabilities Dear Vegard, all, I take the opportunity to inform you that we are drafting a proposal for a netCDF convention on uncertainty (NetCDF-U). This work is partly developed in the framework of the FP7 UncertWeb project. We are going to present it next wednesday at the Open Geospatial Consortium TC Meeting in Bruxelles, to circulate it shortly after. We have tried to be convention-neutral, in particular making sure that netCDF-U fully integrates with the netCDF-CF Conventions, even using the same constructs when possible (e.g. the ancillary_variables attribute). Ideally, we think of datasets that would conform to both the conventions: :Conventions = "CF-1.5 UW-1.0" NetCDF-U is based on a generic mechanism for annotating netCDF variables according to the UncertML conceptual model. The first example in your use-case would read something like (note that CF attributes are unchanged): float precipitation_25(time, x, y) ; precipitation_25:standard_name = "precipitation_amount" ; precipitation_25:long_name = "precipitation_amount 25th percentile" ; precipitation_25:ref = " http://www.uncertml.org/statistics/percentile " ; precipitation_25:level = "25" ; The second, provided we have a variable "difference(Lat=100, Lon=100)" that contains the difference between the observed value and the forecast: float probability(Lat=100, Lon=100) ; probability:ref = " http://www.uncertml.org/statistics/probability " ; probability:gt = "-2.5" ; probability:lt = "2.5" ; I apologize if this is not clear enough, for the moment, and I hope it can be of prospective interest. Any comment is very appreciated. Best regards, Lorenzo Bigagli --- Dott. Lorenzo Bigagli Consiglio Nazionale delle Ricerche Istituto di Metodologie per l'Analisi Ambientale (CNR-IMAA) i: Area della Ricerca di Potenza, Contrada Santa Loja Zona Industriale, 85050 Tito Scalo (PZ), Italia t: +39 0971 427221 f: +39 0971 427222 m: [email protected] _______________________________________________ CF-metadata mailing list [email protected] http://mailman.cgd.ucar.edu/mailman/listinfo/cf-metadata
