use to_netcdf() : save value to netcdf file

Here is a value:

<xarray.DataArray 'height_interp' (Time: 24, south_north: 282, west_east: 540)>

array([[[146.38087, 146.36438, ..., 150.47563, 150.22495],
[146.31306, 146.33267, ..., 150.4368 , 150.4107 ],
...,
[144.736 , 144.68318, ..., 147.91237, 147.94415],
[146.47084, 144.24289, ..., 147.98172, 148.00264]],
[[146.63193, 146.64368, ..., 150.74966, 150.60242],
[146.59207, 146.61151, ..., 150.64212, 150.65385],
...,
[145.27626, 145.13568, ..., 147.51866, 147.48692],
[145.96034, 144.85298, ..., 147.57097, 147.56674]],
...,
[[146.64447, 146.59451, ..., 149.74435, 149.65564],
[146.64937, 146.62129, ..., 149.73277, 149.69064],
...,
[145.3436 , 145.35204, ..., 144.83829, 144.81752],
[145.42519, 145.33458, ..., 144.85371, 144.82965]],
...,
[[146.03555, 146.10979, ..., 149.63452, 149.66908],
[146.15005, 146.14072, ..., 149.64066, 149.6417 ],
...,
[145.02827, 144.96996, ..., 145.09335, 145.08134],
[144.8737 , 144.95973, ..., 145.12323, 145.0956 ]]], dtype=float32)
Coordinates:
XLONG (south_north, west_east) float32 79.74786 79.82733 ... 134.49786
XLAT (south_north, west_east) float32 14.181648 14.207611 ... 39.589397

• Time (Time) datetime64[ns] 2013-06-01 ... 2013-06-01T23:00:00
  datetime (Time) datetime64[ns] 2013-06-01 ... 2013-06-01T23:00:00
  level int64 850
  Dimensions without coordinates: south_north, west_east
  Attributes:
  FieldType: 104
  units: dm
  stagger:
  coordinates: XLONG XLAT
  projection: LambertConformal(stand_lon=105.81999969482422, moad_cen_l...
  missing_value: 9.969209968386869e+36
  _FillValue: 9.969209968386869e+36
  vert_units: hPa

hgt_850.to_netcdf("hgt_850.nc")

TypeError Traceback (most recent call last)
in
----> 1 hgt_850.to_netcdf("hgt_850.nc")

~/soft/anaconda2/envs/py3/lib/python3.6/site-packages/xarray/core/dataarray.py in to_netcdf(self, *args, **kwargs)
1759 dataset = self.to_dataset()
1760
-> 1761 return dataset.to_netcdf(*args, **kwargs)
1762
1763 def to_dict(self, data=True):

~/soft/anaconda2/envs/py3/lib/python3.6/site-packages/xarray/core/dataset.py in to_netcdf(self, path, mode, format, group, engine, encoding, unlimited_dims, compute)
1321 engine=engine, encoding=encoding,
1322 unlimited_dims=unlimited_dims,
-> 1323 compute=compute)
1324
1325 def to_zarr(self, store=None, mode='w-', synchronizer=None, group=None,

~/soft/anaconda2/envs/py3/lib/python3.6/site-packages/xarray/backends/api.py in to_netcdf(dataset, path_or_file, mode, format, group, engine, encoding, unlimited_dims, compute, multifile)
769 # validate Dataset keys, DataArray names, and attr keys/values
770 _validate_dataset_names(dataset)
--> 771 _validate_attrs(dataset)
772
773 try:

~/soft/anaconda2/envs/py3/lib/python3.6/site-packages/xarray/backends/api.py in _validate_attrs(dataset)
167 for variable in dataset.variables.values():
168 for k, v in variable.attrs.items():
--> 169 check_attr(k, v)
170
171

~/soft/anaconda2/envs/py3/lib/python3.6/site-packages/xarray/backends/api.py in check_attr(name, value)
158 'a string, an ndarray or a list/tuple of '
159 'numbers/strings for serialization to netCDF '
--> 160 'files'.format(value))
161
162 # Check attrs on the dataset itself

TypeError: Invalid value for attr: LambertConformal(stand_lon=105.81999969482422, moad_cen_lat=30.45999526977539, truelat1=30.0, truelat2=60.0, pole_lat=90.0, pole_lon=0.0) must be a number, a string, an ndarray or a list/tuple of numbers/strings for serialization to netCDF files

The failure path is DataArray.to_netcdf(), Dataset.to_netcdf(), and xarray/backends/api.py::_validate_attrs; start there and inspect handling of the LambertConformal attribute. Reproduce with the shown DataArray and consider the work done when hgt_850.to_netcdf("hgt_850.nc") completes and writes a readable NetCDF file.