id,node_id,number,title,user,state,locked,assignee,milestone,comments,created_at,updated_at,closed_at,author_association,active_lock_reason,draft,pull_request,body,reactions,performed_via_github_app,state_reason,repo,type
1060646604,I_kwDOAMm_X84_OC7M,6015,TypeError: '_ElementwiseFunctionArray' object does not support item assignment,25624127,open,0,,,0,2021-11-22T22:19:24Z,2021-11-22T23:38:17Z,,CONTRIBUTOR,,,,"<!-- Please include a self-contained copy-pastable example that generates the issue if possible.

Please be concise with code posted. See guidelines below on how to provide a good bug report:

- Craft Minimal Bug Reports: http://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports
- Minimal Complete Verifiable Examples: https://stackoverflow.com/help/mcve

Bug reports that follow these guidelines are easier to diagnose, and so are often handled much more quickly.
-->

**What happened**:
I am attempting to mask specific `time_bnds` coordinate points using `loc`, but am receiving `TypeError: '_ElementwiseFunctionArray' object does not support item assignment`. 

This happens when calling `ds = xr.open_dataset(""path/to/file"", decode_times=False)`, followed by `ds = xr.decode_cf(ds, decode_times=True`).

**What you expected to happen**:

The `time_bnds` coordinate points selected using `.loc` should mask.

**Minimal Complete Verifiable Example**:

```python
import numpy as np
import xarray as xr

file_path = ""./input/ts_Amon_ACCESS1-0_historical_r1i1p1_185001-200512.nc""

# This works fine
ds = xr.open_dataset(file_path, decode_times=True)
ds[""time_bnds""].loc[dict(time=""1850-01"")] = np.nan

# This breaks
ds2 = xr.open_dataset(file_path, decode_times=False)
ds2 = xr.decode_cf(ds2, decode_times=True)
ds2[""time_bnds""].loc[dict(time=""1850-01"")] = np.nan

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
~/Documents/Repositories/XCDAT/xcdat/qa/PR47 temporal avg/bugs/qa_seasonal_bug.py in <module>
      13 ds2 = xr.open_dataset(file_path, decode_times=False)
      14 ds2 = xr.decode_cf(ds2, decode_times=True)
----> 15 ds2[""time_bnds""].loc[dict(time=""1850-01"")] = np.nan

/opt/miniconda3/envs/xcdat_dev/lib/python3.9/site-packages/xarray/core/dataarray.py in __setitem__(self, key, value)
    212 
    213         pos_indexers, _ = remap_label_indexers(self.data_array, key)
--> 214         self.data_array[pos_indexers] = value
    215 
    216 

/opt/miniconda3/envs/xcdat_dev/lib/python3.9/site-packages/xarray/core/dataarray.py in __setitem__(self, key, value)
    765                 for k, v in self._item_key_to_dict(key).items()
    766             }
--> 767             self.variable[key] = value
    768 
    769     def __delitem__(self, key: Any) -> None:

/opt/miniconda3/envs/xcdat_dev/lib/python3.9/site-packages/xarray/core/variable.py in __setitem__(self, key, value)
    852 
    853         indexable = as_indexable(self._data)
--> 854         indexable[index_tuple] = value
    855 
    856     @property

/opt/miniconda3/envs/xcdat_dev/lib/python3.9/site-packages/xarray/core/indexing.py in __setitem__(self, key, value)
    435             )
    436         full_key = self._updated_key(key)
--> 437         self.array[full_key] = value
    438 
    439     def __repr__(self):

TypeError: '_ElementwiseFunctionArray' object does not support item assignment


```

**Anything else we need to know?**:

The workaround is to perform `.load()` after `xr.decode_cf()`
```python
# This works
ds3 = xr.open_dataset(file_path, decode_times=False)
ds3 = xr.decode_cf(ds3, decode_times=True)
ds3.load()
ds3[""time_bnds""].loc[dict(time=""1850-01"")] = np.nan
```

**Environment**:

<details><summary>Output of <tt>xr.show_versions()</tt></summary>

<!-- Paste the output here xr.show_versions() here -->

INSTALLED VERSIONS
------------------
commit: None
python: 3.9.7 | packaged by conda-forge | (default, Sep 29 2021, 20:33:18) 
[Clang 11.1.0 ]
python-bits: 64
OS: Darwin
OS-release: 19.6.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: None
LOCALE: (None, 'UTF-8')
libhdf5: 1.12.1
libnetcdf: 4.8.1

xarray: 0.19.0
pandas: 1.3.3
numpy: 1.21.2
scipy: None
netCDF4: 1.5.7
pydap: None
h5netcdf: None
h5py: None
Nio: None
zarr: None
cftime: 1.5.1
nc_time_axis: None
PseudoNetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: 1.3.2
dask: 2021.09.1
distributed: 2021.09.1
matplotlib: None
cartopy: None
seaborn: None
numbagg: None
pint: None
setuptools: 58.2.0
pip: 21.2.4
conda: None
pytest: 6.2.5
IPython: 7.28.0
sphinx: 4.2.0

</details>
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6015/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue