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
1451961530,I_kwDOAMm_X85Wiyy6,7292,`dtype` of `zarr` array unexpectedly changes when `fill_value` is specified,8552,open,0,,,2,2022-11-16T17:03:19Z,2022-12-01T12:46:16Z,,NONE,,,,"### What happened?

Opening a `zarr` group which contains an array of integer `dtype` with a `fill_value` results in an `xarray` dataset in which the array has floating-point dtype.

### What did you expect to happen?

An `xarray` dataset in which the array has the original integer `dtype`.

### Minimal Complete Verifiable Example

```Python
import zarr
import xarray

#Create zarr with integer dtype and fill_value
grp = zarr.open_group(""test.zarr"")
arr = grp.create(shape=(10,), name=""array"", dtype=""int8"", fill_value=-1)
arr.attrs['_ARRAY_DIMENSIONS'] = ['dim1']

#Open in xarray to see that the dtype is now float32
ds = xarray.open_zarr(""test.zarr"", consolidated=False)
ds['array'].dtype
```


### 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

_No response_

### Anything else we need to know?

This is a result of https://github.com/pydata/xarray/issues/5475 where xarray's `_FillValue` has a different meaning to zarr's `fill_value`.

The change of dtype happens at https://github.com/pydata/xarray/blob/3c98ec7d96cc4b46664850cc7a40af2bc184fea0/xarray/coding/variables.py#L204 where xarray is trying to find a dtype where `fill_value` can represent ""missing"" data, wheras in `zarr`, `fill_value` can be any data value as its intent is to fill in missing _chunks_ not represent missing _data_.

I'm not sure how best to fix this - maybe if the zarr fill value is clearly a non-missing value for the dtype then xarray should act as if it doesn't have a fill value? Happy to work on a PR if that seems to be a valid approach, although others may have thought on if that is a breaking change for some folks.

### Environment

<details>
INSTALLED VERSIONS
------------------
commit: None
python: 3.10.4 (main, Jun 29 2022, 12:14:53) [GCC 11.2.0]
python-bits: 64
OS: Linux
OS-release: 5.15.0-47-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_GB.UTF-8
LOCALE: ('en_GB', 'UTF-8')
libhdf5: None
libnetcdf: None

xarray: 2022.11.0
pandas: 1.3.5
numpy: 1.21.6
scipy: 1.9.3
netCDF4: None
pydap: None
h5netcdf: None
h5py: None
Nio: None
zarr: 2.13.3
cftime: None
nc_time_axis: None
PseudoNetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: None
dask: 2022.01.0
distributed: 2022.01.0
matplotlib: None
cartopy: None
seaborn: None
numbagg: None
fsspec: 2022.10.0
cupy: None
pint: None
sparse: None
flox: None
numpy_groupies: None
setuptools: 59.6.0
pip: 22.0.2
conda: None
pytest: None
IPython: None
sphinx: None


</details>
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