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
1238838588,I_kwDOAMm_X85J1y08,6617,Multi-dimensional extrapolation doesn't work,40182387,closed,0,,,2,2022-05-17T15:45:08Z,2022-06-01T06:41:26Z,2022-06-01T06:41:26Z,CONTRIBUTOR,,,,"### What happened?

I am trying to interpolate and _extrapolate_ a two dimensional DataArray. Passing the `kwargs=dict(fill_value=None)` argument to `DataArray.interp` still returns `nan` values.

The MCVE is taken from the [documentation guide](https://docs.xarray.dev/en/stable/user-guide/interpolation.html) on interpolation. (Note that the documentation also shows `nan` values.)

### What did you expect to happen?

I expected the routine to extrapolate the data when ""out-of-bounds"" coordinates were provided.

### Minimal Complete Verifiable Example

```Python
import xarray as xr
import numpy as np

# multi-dimensional extrapolation
da = xr.DataArray(
     np.sin(0.3 * np.arange(12).reshape(4, 3)),
    [(""time"", np.arange(4)), (""space"", [0.1, 0.2, 0.3])],
)
interped_da = da.interp(time=4, space=np.linspace(-0.1, 0.5, 10), kwargs={""fill_value"": None})
print(interped_da)
```


### MVCE confirmation

- [X] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
- [X] Complete example — the example is self-contained, including all data and the text of any traceback.
- [X] Verifiable example — the example copy & pastes into an IPython prompt or [Binder notebook](https://mybinder.org/v2/gh/pydata/xarray/main?urlpath=lab/tree/doc/examples/blank_template.ipynb), returning the result.
- [X] New issue — a search of GitHub Issues suggests this is not a duplicate.

### Relevant log output

```Python
<xarray.DataArray (space: 10)>
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan])
Coordinates:
    time     int64 4
  * space    (space) float64 -0.1 -0.03333 0.03333 0.1 ... 0.3 0.3667 0.4333 0.5
```


### Anything else we need to know?

This is my first issue, I hope I didn't forget something! Thank you for the amazing package!

### Environment

<details>

```
INSTALLED VERSIONS
------------------
commit: None
python: 3.9.12 | packaged by conda-forge | (main, Mar 24 2022, 23:22:55) 
[GCC 10.3.0]
python-bits: 64
OS: Linux
OS-release: 5.3.18-150300.59.63-default
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: ('en_US', 'UTF-8')
libhdf5: 1.10.6
libnetcdf: None

xarray: 2022.3.0
pandas: 1.4.2
numpy: 1.21.5
scipy: 1.7.3
netCDF4: None
pydap: None
h5netcdf: None
h5py: 3.6.0
Nio: None
zarr: None
cftime: None
nc_time_axis: None
PseudoNetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: 1.3.4
dask: 2022.05.0
distributed: 2022.5.0
matplotlib: 3.5.2
cartopy: None
seaborn: None
numbagg: None
fsspec: 2022.3.0
cupy: None
pint: None
sparse: None
setuptools: 62.2.0
pip: 22.1
conda: None
pytest: None
IPython: 8.3.0
sphinx: 4.5.0
```

</details>
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