rioxarray (or xarray) converts spatial_ref coordinate to variable after reprojecting and saving with to_netcdf?

Question

I have a "dataarray" which I am trying to reproject it using rioxarray. However after reprojection when I use xarray.to_netcdf, the saved file is a dataset where the "spatial_ref" coordinate converted to a variable. I am not sure if that is xarray or rioxarray.reprojection causes this behavior. Here are some codes that show the issue:

import xarray as xr 
import rioxarray
from pyproj import CRS 

lst = xr.open_dataset("lst.nc") # File which carries the original CRS
luc = xr.open_rasterio("luc.tif") # File with the desired projection system
file_to_reproject = xr.open_dataarray("myfile.nc") # File to reproject

cc_lst = CRS.from_cf(lst.crs.attrs) # Get the CRS 
cc_luc = luc.rio.crs

file_to_reproject = file_to_reproject.rio.write_crs(cc_lst) # write crs 
file_reprojected= file_to_reproject.rio.reproject(cc_luc) #reproject the file

print(file_reprojected)
<xarray.DataArray (season: 4, y: 4343, x: 4172)>
array([[[nan, nan, nan, ..., nan, nan, nan],
        [nan, nan, nan, ..., nan, nan, nan]]])
Coordinates:
  * x            (x) float64 -3.382e+06 -3.381e+06 ... 4.817e+05 4.826e+05
  * y            (y) float64 5.361e+06 5.36e+06 ... 1.338e+06 1.337e+06
  * season       (season) object 'DJF' 'JJA' 'MAM' 'SON'
    spatial_ref  int64 0

# however after saving the file and reloading it I get a dataset where 
# spatial_ref turned into variable 
file_reprojected.to_netcdf("file_reprojected.nc")
ds= xr.open_dataset("file_reprojected.nc")

>>> print(ds)
<xarray.Dataset>
Dimensions:                        (season: 4, x: 4172, y: 4343)
Coordinates:
  * x                              (x) float64 -3.382e+06 ... 4.826e+05
  * y                              (y) float64 5.361e+06 5.36e+06 ... 1.337e+06
  * season                         (season) object 'DJF' 'JJA' 'MAM' 'SON'
Data variables:
    spatial_ref                    int64 ...
    __xarray_dataarray_variable__  (season, y, x) float64 ...

# Here is the content of spatial_ref
>>> print(ds["spatial_ref"])
<xarray.DataArray 'spatial_ref' ()>
array(0)
Attributes: (12/19)
    crs_wkt:                        PROJCS["unknown",GEOGCS["unknown",DATUM["...
    semi_major_axis:                6378137.0
    semi_minor_axis:                6356752.314140356
    inverse_flattening:             298.257222101
    reference_ellipsoid_name:       GRS 1980
    longitude_of_prime_meridian:    0.0
    ...                             ...

As you can see after reprojecting the dataarray and saving it the file turns into dataset with spatial_ref as a new variable.

I am just interested in georeferenced dataarray. How can I fix this?

Edit1

I think it might have something with this ( here ) issue

Edit2

I forgot to mention when I import the reprojected file is has no crs:

ds= xr.open_dataset("file_reprojected.nc")
ds.rio.crs # Retruns nothing 

Answer 1

The issue was I did not set decode_coords="all" when I used xarray.open_dataarray. With the following everything looks ok:

file_to_reproject = xr.open_dataarray("myfile.nc",decode_coords="all")