What happened?

when I try and save the dataset with an attribute as a list of strings it fails.

See example code

```python

import xarray as xr import pandas as pd import numpy as np

ds = xr.Dataset()

temp = 15 + 8 * np.random.randn(2, 2, 3)

precip = 10 * np.random.rand(2, 2, 3)

lon = [[-99.83, -99.32], [-99.79, -99.23]]

lat = [[42.25, 42.21], [42.63, 42.59]]

ds["temperature"] = (("x", "y", "time"), temp)

ds["temperature_double"] = (("x", "y", "time"), temp * 2)

ds["precipitation"] = (("x", "y", "time"), precip)

ds.coords["lat"] = (("x", "y"), lat)

ds.coords["lon"] = (("x", "y"), lon)

ds.coords["time"] = pd.date_range("2014-09-06", periods=3)

ds.coords["reference_time"] = pd.Timestamp("2014-09-05")

ds.attrs['test'] = [1,2,3] ds.to_netcdf('test.nc')

no error

ds.attrs['test'] = ['1','2','3'] ds.to_netcdf('test.nc') ```

```bash File "C:\Users\xxxx\Anaconda3\envs\base1\lib\site-packages\scipy\io_netcdf.py", line 555, in _write_att_values nc_type = REVERSE[values.dtype.char, values.dtype.itemsize]

KeyError: ('U', 4) ```

What did you expect to happen?

No response

Minimal Complete Verifiable Example

No response

MVCE confirmation

• [ ] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
• [ ] Complete example — the example is self-contained, including all data and the text of any traceback.
• [ ] Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result.
• [ ] New issue — a search of GitHub Issues suggests this is not a duplicate.

Relevant log output

No response

Anything else we need to know?

No response

Environment

xr.show_versions() INSTALLED VERSIONS ------------------ commit: None python: 3.10.9 | packaged by conda-forge | (main, Jan 11 2023, 15:15:40) [MSC v.1916 64 bit (AMD64)] python-bits: 64 OS: Windows OS-release: 10 machine: AMD64 processor: Intel64 Family 6 Model 165 Stepping 2, GenuineIntel byteorder: little LC_ALL: None LANG: en LOCALE: ('English_United States', '1252') libhdf5: 1.10.6 libnetcdf: None xarray: 2022.11.0 pandas: 1.5.2 numpy: 1.21.5 scipy: 1.9.3 netCDF4: None pydap: None h5netcdf: None h5py: 3.7.0 Nio: None zarr: None cftime: None nc_time_axis: None PseudoNetCDF: None rasterio: None cfgrib: None iris: None bottleneck: 1.3.5 dask: 2022.05.0 distributed: 2022.5.0 matplotlib: 3.6.2 cartopy: None seaborn: 0.12.2 numbagg: None fsspec: 2022.11.0 cupy: None pint: 0.20.1 sparse: None flox: None numpy_groupies: None setuptools: 65.6.3 pip: 22.3.1 conda: None pytest: 7.1.2 IPython: 7.31.1 sphinx: 5.0.2