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
741806260,MDU6SXNzdWU3NDE4MDYyNjA=,4579,Invisible differences between arrays using IntervalIndex,500246,open,0,,,2,2020-11-12T17:54:55Z,2022-10-03T15:09:25Z,,CONTRIBUTOR,,,,"<!-- Please include a self-contained copy-pastable example that generates the issue if possible.

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**What happened**:

I have two `DataArray`s that each have a coordinate constructed with `pandas.interval_range`.  In one case I pass the `interval_range` directly, in the other case I call `.to_numpy()` first.  The two `DataArray`s look identical but aren't.  This can lead to hard-to-find bugs, because behaviour is not identical: the former supports indexing whereas the latter doesn't.

**What you expected to happen**:

I expect two arrays that appear identical to behave identically.  If they don't behave identically then there should be some way to tell the difference (apart from `equals`, which tells me they are different but not how).

**Minimal Complete Verifiable Example**:

```python
import xarray
import pandas

da1 = xarray.DataArray([0, 1, 2], dims=(""x"",), coords={""x"":
    pandas.interval_range(0, 2, 3)})
da2 = xarray.DataArray([0, 1, 2], dims=(""x"",), coords={""x"":
    pandas.interval_range(0, 2, 3).to_numpy()})

print(repr(da1) == repr(da2))
print(repr(da1.x) == repr(da2.x))
print(da1.x.dtype == da2.x.dtype)

# identical?  No:
print(da1.equals(da2))
print(da1.x.equals(da2.x))

# in particular:
da1.sel(x=1)  # works
da2.sel(x=1)  # fails
```

Results in:

```
True
True
True
False
False
Traceback (most recent call last):
  File ""/data/gholl/miniconda3/envs/py38/lib/python3.8/site-packages/pandas/core/indexes/base.py"", line 2895, in get_loc
    return self._engine.get_loc(casted_key)
  File ""pandas/_libs/index.pyx"", line 70, in pandas._libs.index.IndexEngine.get_loc
  File ""pandas/_libs/index.pyx"", line 101, in pandas._libs.index.IndexEngine.get_loc
  File ""pandas/_libs/hashtable_class_helper.pxi"", line 1675, in pandas._libs.hashtable.PyObjectHashTable.get_item
  File ""pandas/_libs/hashtable_class_helper.pxi"", line 1683, in pandas._libs.hashtable.PyObjectHashTable.get_item
KeyError: 1

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File ""mwe105.py"", line 19, in <module>
    da2.sel(x=1)  # fails
  File ""/data/gholl/miniconda3/envs/py38/lib/python3.8/site-packages/xarray/core/dataarray.py"", line 1143, in sel
    ds = self._to_temp_dataset().sel(
  File ""/data/gholl/miniconda3/envs/py38/lib/python3.8/site-packages/xarray/core/dataset.py"", line 2105, in sel
    pos_indexers, new_indexes = remap_label_indexers(
  File ""/data/gholl/miniconda3/envs/py38/lib/python3.8/site-packages/xarray/core/coordinates.py"", line 397, in remap_label_indexers
    pos_indexers, new_indexes = indexing.remap_label_indexers(
  File ""/data/gholl/miniconda3/envs/py38/lib/python3.8/site-packages/xarray/core/indexing.py"", line 275, in remap_label_indexers
    idxr, new_idx = convert_label_indexer(index, label, dim, method, tolerance)
  File ""/data/gholl/miniconda3/envs/py38/lib/python3.8/site-packages/xarray/core/indexing.py"", line 196, in convert_label_indexer
    indexer = index.get_loc(label_value, method=method, tolerance=tolerance)
  File ""/data/gholl/miniconda3/envs/py38/lib/python3.8/site-packages/pandas/core/indexes/base.py"", line 2897, in get_loc
    raise KeyError(key) from err
KeyError: 1
```

**Additional context**

I suppose this happens because under the hood xarray does something clever to support pandas-style indexing even though the coordinate variable appears like a numpy array with an object dtype, and that this cleverness is lost if the object is already converted to a numpy array.  But there is, as far as I can see, no way to tell the difference once the objects have been created.

**Environment**:

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

INSTALLED VERSIONS
------------------
commit: None
python: 3.8.6 | packaged by conda-forge | (default, Oct  7 2020, 19:08:05)
[GCC 7.5.0]
python-bits: 64
OS: Linux
OS-release: 4.12.14-lp150.12.82-default
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_GB.UTF-8
LOCALE: en_GB.UTF-8
libhdf5: 1.10.6
libnetcdf: 4.7.4

xarray: 0.16.1
pandas: 1.1.4
numpy: 1.19.4
scipy: 1.5.3
netCDF4: 1.5.4
pydap: None
h5netcdf: 0.8.1
h5py: 3.1.0
Nio: None
zarr: 2.5.0
cftime: 1.2.1
nc_time_axis: None
PseudoNetCDF: None
rasterio: 1.1.7
cfgrib: None
iris: None
bottleneck: None
dask: 2.30.0
distributed: 2.30.1
matplotlib: 3.3.2
cartopy: 0.18.0
seaborn: None
numbagg: None
pint: None
setuptools: 49.6.0.post20201009
pip: 20.2.4
conda: installed
pytest: 6.1.2
IPython: 7.19.0
sphinx: 3.3.0

</details>
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