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I am trying to access the SubX CFSv2 temperature forecasts used in this project in order to do some slightly different preprocessing and am running into an error with the netCDF4 back-end of xarray.
import xarray as xa
x = xa.open_dataset(
"https://iridl.ldeo.columbia.edu/SOURCES/.Models/.SubX/.NCEP/.CFSv2/.forecast/.tas/dods",
decode_times=False,
)
x['tas'][0, :, :, :, :].data
causes the following error
File src/netCDF4/_netCDF4.pyx:4406, in netCDF4._netCDF4.Variable.__getitem__()
File src/netCDF4/_netCDF4.pyx:5348, in netCDF4._netCDF4.Variable._get()
IndexError: index exceeds dimension bounds
This also occurs when simply trying to access the data as x['tas'].data
Is this a good way to go about this? It seems the scripts here are running into the issue mentioned in #18
Thanks!
The text was updated successfully, but these errors were encountered:
@btickell you actually got further along with downloading data from that link than I did. I tried your code on my computer and have the same issues with you. It's a very large file which may have some part in the issue??? The data I downloaded for GEOS (with the script in #18) were daily data, but I had to figure out which days were actually the initialized days because all the other files were filled with np.nan. It appears that you have the entire time series because with GMAO GEOS-5, there were only 1239 initialized days. Your current script has creates 6456 days (which may be unrealistic for CFSv2).
I am trying to access the SubX CFSv2 temperature forecasts used in this project in order to do some slightly different preprocessing and am running into an error with the netCDF4 back-end of xarray.
causes the following error
This also occurs when simply trying to access the data as
x['tas'].data
Is this a good way to go about this? It seems the scripts here are running into the issue mentioned in #18
Thanks!
The text was updated successfully, but these errors were encountered: