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
1499473190,I_kwDOAMm_X85ZYCUm,7385,Unexpected NaNs in broadcast,221526,open,0,,,4,2022-12-16T02:42:44Z,2023-03-14T20:43:00Z,,CONTRIBUTOR,,,,"### What happened?

When running the `broadcast` in the sample code, I end up with `nan` in the output when there are not any in the original source array. While I know the construction is really odd (this came from user-submitted code), I'm shocked that it resulted in `nan`s the resulting broadcasted data and honestly assumed MetPy's code was doing something dumb for quite awhile. I would have expected (regardless of the nature of the coordinates) that the result for `broad_a` be `[[1, 2], [1, 2]]`.

### What did you expect to happen?

_No response_

### Minimal Complete Verifiable Example

```Python
levs = np.array([100000, 85000])
a = xr.Dataset({'a': (('lev',), [1, 2])}, coords={'lev': levs}).to_array()
b = xr.Dataset({'b': (('lev',), [3, 4])}, coords={'lev': levs}).to_array()

broad_a, broad_b = xr.broadcast(a, b)
print(broad_a)
```


### 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 (variable: 2, lev: 2)>
array([[ 1.,  2.],
       [nan, nan]])
Coordinates:
  * lev       (lev) int64 100000 85000
  * variable  (variable) object 'a' 'b'
```


### Anything else we need to know?

_No response_

### Environment

<details>
INSTALLED VERSIONS
------------------
commit: None
python: 3.10.8 | packaged by conda-forge | (main, Nov 22 2022, 08:31:57) [Clang 14.0.6 ]
python-bits: 64
OS: Darwin
OS-release: 21.6.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: ('en_US', 'UTF-8')
libhdf5: 1.12.2
libnetcdf: 4.8.1

xarray: 2022.12.0
pandas: 1.5.2
numpy: 1.23.5
scipy: 1.9.3
netCDF4: 1.6.2
pydap: None
h5netcdf: None
h5py: None
Nio: None
zarr: 2.13.3
cftime: 1.6.2
nc_time_axis: None
PseudoNetCDF: None
rasterio: None
cfgrib: 0.9.10.3
iris: None
bottleneck: 1.3.5
dask: 2022.6.1
distributed: 2022.6.1
matplotlib: 3.6.2
cartopy: 0.21.0
seaborn: None
numbagg: None
fsspec: 2022.11.0
cupy: None
pint: 0.20.1
sparse: None
flox: None
numpy_groupies: None
setuptools: 65.5.1
pip: 22.3.1
conda: None
pytest: 7.2.0
mypy: 0.991
IPython: 8.7.0
sphinx: 5.3.0
</details>
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