Please help with how to aggregate files that may contain an inconsistent
list of variables. The files I want to use all contain temperature and
salinity time series, but some also have conductivity, attenuation or
other data. I'd like to include all the possible variables in a single
aggregation. Seems like if one file of 50 is missing attenuation, that
I have to exclude attenuation from the aggregation, and just operate on
the variables that are present in all 50.
Have any of you found a way to also include the other "possibly present
variables", or whether it's better to just make 1 joinExisting time
aggregation per variable. I heard that in FMRC aggregations there was
a way to specify a "protoDataset" (maybe not the right term) and it
fills in appropriately for any files with variables missing from the
prototype. I couldn't find a reference to this in the documentation,
but if it's possible, would this approach be appropriate for the
inconsistently present variables I'm trying to aggregate?
Or maybe someone has a good reason to supply several files (one file per
variable aggregated) instead of one file with all the possible variables
I'm interested in the pros and cons of each approach. Thanks for your help!
Ellyn T. Montgomery, Oceanographer and Data Manager
U.S. Geological Survey
Woods Hole Coastal and Marine Science Center
384 Woods Hole Road, Woods Hole, MA 02543-1598