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In common_analysis.make_analysis() the code defaults to using wfdei.regrid_wfdei():
############################################################################ Get a function for deriving RWR output grid info.###########################################################################iffile_sftlfisNone:
regrid_model=wfdei.regrid_wfdeielse:
defregrid_model(res):
grid=read_grid(file_sftlf)
land= [[i] foriinrange(grid.nl)]
returngrid, land
which is ultimately called as the hard-wired regrid_model(1). That means the user has to do more work to get the code to calculate RWR on the native input grid of the data (e.g., 0.5 deg for observations) than to calculate it on a 1 deg coarsened version of one particular native grid (WFDEI). It seems like this behaviour is the wrong way around for general use.
The text was updated successfully, but these errors were encountered:
In
common_analysis.make_analysis()
the code defaults to usingwfdei.regrid_wfdei()
:which is ultimately called as the hard-wired
regrid_model(1)
. That means the user has to do more work to get the code to calculate RWR on the native input grid of the data (e.g., 0.5 deg for observations) than to calculate it on a 1 deg coarsened version of one particular native grid (WFDEI). It seems like this behaviour is the wrong way around for general use.The text was updated successfully, but these errors were encountered: