[QUESTION] compare_zonal_mean not reading in Xarray.Dataset files? about gcpy HOT 1 CLOSED

gcpy.open_mfdataset is a wrapper around xarray function open_mfdataset which reads in netcdf variables as dask arrays. See http://xarray.pydata.org/en/stable/dask.html for more information on using dask arrays in xarray.

For example, I used open_mfdataset to read in several files and my resulting data looks like this:

<xarray.Dataset>
Dimensions: (lat: 288, lev: 72, lon: 48)
Coordinates:

• lon (lon) float64 1.0 2.0 3.0 4.0 5.0 ... 45.0 46.0 47.0 48.0
• lat (lat) float64 1.0 2.0 3.0 4.0 5.0 ... 285.0 286.0 287.0 288.0
• lev (lev) float64 1.0 2.0 3.0 4.0 5.0 ... 69.0 70.0 71.0 72.0
  Data variables:
  Jval_O3O3P (lev, lat, lon) float32 dask.array<shape=(72, 288, 48), chunksize=(72, 288, 48)>
  Jval_O3O1D (lev, lat, lon) float32 dask.array<shape=(72, 288, 48), chunksize=(72, 288, 48)>
  Jval_O2 (lev, lat, lon) float32 dask.array<shape=(72, 288, 48), chunksize=(72, 288, 48)>
  Jval_INPN (lev, lat, lon) float32 dask.array<shape=(72, 288, 48), chunksize=(72, 288, 48)>
  Jval_MRP (lev, lat, lon) float32 dask.array<shape=(72, 288, 48), chunksize=(72, 288, 48)>

This will cause problems when regridding since xesmf expects numpy array or xarray DataArray. When you ran your code for compare_single_level you likely did not regrid and so did not run into this problem. However, when you pass the same cubed-sphere data to compare_zonal_mean it will automatically be regridded to calculate zonal mean.

To avoid this problem you can convert your dask arrays to numpy arrays or xarray DataArrays prior to passing the data to the plotting functions. For example, np.array(ds_ref['varname'].data). You can also create an issue for xesmf to expand the handling to include dask arrays.

from gcpy.