I have a question regarding coordinate variables:
I am working with time-series data representing hydrological conditions at
fixed locations in a stream network. The values are generated by a model at
regular time intervals, and I believe that the data will fit well into the
timeSeries feature type described in the “Discrete Sampling Geometries” chapter
of the CF conventions. For example, we would put all the discharge values into
a single 2D array:
double flow(time, location)
The dimension “location” here is the “instance dimension” described in the
convention.
I would like to use an integer variable named “location” as a coordinate
variable to go along with the location dimension. I think this would provide a
handy way for post-processing programs to locate a time series in our model
result files. The Best Practices guidance on the Unidata website, though, says
that coordinate variables “must be strictly monotonic” and the order of the IDs
in my location variable is arbitrary. All of the location values are unique,
but the location numbers are essentially numerical labels – location 1524 is
distinct from location 2817, but neither is greater than the other in a way
that means anything to the model. Location IDs do not consistently increase or
decrease traveling downstream, for example.
So, is the guidance that coordinate variable should strictly increase or
decrease relevant to my case? I’ve built some sample files and examined them
using Panoply, and in Python using xarray. I haven’t seen any problems with
using non-monotonic integer “ID numbers” as coordinate variables, but that
“must” in the guidance troubles me. If my locations are identified by arbitrary
numbers, do I run the risk of scrambling the links between my time series and
their identifiers?
Thanks
Tom Evans
[cid:[email protected]]<http://www.niwa.co.nz>
Dr Tom Evans
Software Developer
T +64-7-859-1832
National Institute of Water & Atmospheric Research Ltd (NIWA)
Gate 10 Silverdale Road, Hillcrest, Hamilton
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