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
2115049090,I_kwDOAMm_X85-ERaC,8694,Error while saving an altered dataset to NetCDF when loaded from a file,12544636,open,0,,,4,2024-02-02T14:18:03Z,2024-02-07T13:38:40Z,,NONE,,,,"### What happened?

When attempting to save an altered Xarray dataset to a NetCDF file using the `to_netcdf` method, an error occurs if the original dataset is loaded from a file. Specifically, this error does not occur when the dataset is created directly but only when it is loaded from a file.

### What did you expect to happen?

The altered Xarray dataset is saved as a NetCDF file using the `to_netcdf` method.

### Minimal Complete Verifiable Example

```Python
import xarray as xr


ds = xr.Dataset(
    data_vars=dict(
        win_1=(""attempt"", [True, False, True, False, False, True]),
        win_2=(""attempt"", [False, True, False, True, False, False]),
    ),
    coords=dict(
        attempt=[1, 2, 3, 4, 5, 6],
        player_1=(""attempt"", [""paper"", ""paper"", ""scissors"", ""scissors"", ""paper"", ""paper""]),
        player_2=(""attempt"", [""rock"", ""scissors"", ""paper"", ""rock"", ""paper"", ""rock""]),
    )
)
ds.to_netcdf(""dataset.nc"")

ds_from_file = xr.load_dataset(""dataset.nc"")

ds_altered = ds_from_file.where(ds_from_file[""player_1""] == ""paper"", drop=True)
ds_altered.to_netcdf(""dataset_altered.nc"")
```


### 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.
- [X] Recent environment — the issue occurs with the latest version of xarray and its dependencies.

### Relevant log output

```Python
Traceback (most recent call last):
  File ""example.py"", line 20, in <module>
    ds_altered.to_netcdf(""dataset_altered.nc"")
  File "".../python3.9/site-packages/xarray/core/dataset.py"", line 2303, in to_netcdf
    return to_netcdf(  # type: ignore  # mypy cannot resolve the overloads:(
  File "".../python3.9/site-packages/xarray/backends/api.py"", line 1315, in to_netcdf
    dump_to_store(
  File "".../python3.9/site-packages/xarray/backends/api.py"", line 1362, in dump_to_store
    store.store(variables, attrs, check_encoding, writer, unlimited_dims=unlimited_dims)
  File "".../python3.9/site-packages/xarray/backends/common.py"", line 356, in store
    self.set_variables(
  File "".../python3.9/site-packages/xarray/backends/common.py"", line 398, in set_variables
    writer.add(source, target)
  File "".../python3.9/site-packages/xarray/backends/common.py"", line 243, in add
    target[...] = source
  File "".../python3.9/site-packages/xarray/backends/scipy_.py"", line 78, in __setitem__
    data[key] = value
  File "".../python3.9/site-packages/scipy/io/_netcdf.py"", line 1019, in __setitem__
    self.data[index] = data
ValueError: could not broadcast input array from shape (4,5) into shape (4,8)
```


### Anything else we need to know?

**Findings:**

The issue is related to the encoding information of the dataset becoming invalid after filtering data with the `where` method. The `to_netcdf` method takes the available encoding information instead of considering the actual shape of the data.

In the provided examples, the maximum length of strings stored in ""player_1"" and ""player_2"" is originally set to 8 characters. However, after filtering with the `where` method, the maximum length of the string becomes 5 in ""player_1"" and remains 8 in ""player_2."". But the encoding information of the variables still shows a length of 8, particularly the attribute `char_dim_name`.

**Workaround:**

A workaround to resolve this issue is to call the `drop_encoding` method on the dataset before saving it with `to_netcdf`. This action ensures that the encoding information is not available, and the `to_netcdf` method is forced to take the actual shapes of the data, preventing the broadcasting error.

### Environment

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.9.14 (main, Aug 24 2023, 14:01:46) 
[GCC 11.4.0]
python-bits: 64
OS: Linux
OS-release: 6.3.1-060301-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: ('en_US', 'UTF-8')
libhdf5: None
libnetcdf: None

xarray: 2024.1.1
pandas: 2.2.0
numpy: 1.26.3
scipy: 1.12.0
netCDF4: None
pydap: None
h5netcdf: None
h5py: None
Nio: None
zarr: None
cftime: None
nc_time_axis: None
iris: None
bottleneck: None
dask: None
distributed: None
matplotlib: None
cartopy: None
seaborn: None
numbagg: None
fsspec: None
cupy: None
pint: None
sparse: None
flox: None
numpy_groupies: None
setuptools: 69.0.3
pip: 23.3.2
conda: None
pytest: None
mypy: None
IPython: None
sphinx: None

</details>
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