[gradsusr] handling non-world coordinates

[Jeff Duda]

Hello,
I have some netCDF files that I created using my own FORTRAN code.  I wish
to display some arrays in those files that have some non-world-coordinate
dimensions.  For example, my data contain probabilities of precipitation
from three different ensembles using five different precipitation
accumulation thresholds.  Therefore, I have two non-world-coordinate
dimensions.  I see in the documentation how to handle one (see below):

*If your data file contains a variable that also varies in a
non-world-coordinate dimension (e.g. histogram interval, spectral band,
ensemble number) then you can put a non-negative integer in the list of
varying dimensions that will become the array index of the extra dimension.
For example: *



* VAR=>hist0   0   0,y,x   First historgram interval for VAR VAR=>hist1
   0   1,y,x   Second historgram interval for VAR VAR=>hist2   0   2,y,x
   Third histogram interval for VAR *

*Another option in this example would be to fill the unused Z axis with the
histogram intervals: *



* zdef 3 linear 1 1 ... VAR=>hist   3   z,y,x   VAR Histogram*

*In this case, it would appear to GrADS that variable 'hist' varies in Z,
but the user would have to remember that the Z levels correspond to
histogram intervals. The latter technique makes it easier to slice through
the data, but is not the most accurate representation. And if you don't
have an unsued world-coordinate axis available, then you still have a way
to access your data.*
However, I am unsure of how to handle two.  Let alone, if you have no
"free" world coordinates, how do you reference these other dimensions when
displaying the grids in Grads?

Here is an ncdump of one of my files:

netcdf \0527_neighborhood_PoP_007200 {
dimensions:
        X = 803 ;
        Y = 603 ;
        threshold = 5 ;
        ensemble = 3 ;
variables:
        float forecast_PoP(ensemble, threshold, Y, X) ;
        float observed_PoP(threshold, Y, X) ;
}

Jeff Duda
-- 
Jeff Duda
Graduate research assistant
University of Oklahoma School of Meteorology
Center for Analysis and Prediction of Storms
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