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
1685803922,I_kwDOAMm_X85ke1OS,7790,Fill values in time arrays (numpy.datetime64) are lost in zarr,14983768,closed,0,,,25,2023-04-26T22:03:06Z,2023-09-17T08:15:28Z,2023-09-17T08:15:28Z,NONE,,,,"### What happened?

I have a time array of type numpy.datetime64 with fill values. When I save the dateset I created with xarray to zarr and then read that zarr store back out again with xarray, the fill values are lost.

### What did you expect to happen?

I expected my fill values to still be in my time array when I read it back out of the zarr store.

### Minimal Complete Verifiable Example

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


# Create a numpy array of type np.datetime64 with one fill value and one date
time_fill_value = np.datetime64(""NaT"")
time = np.array([time_fill_value,'2023-01-02'],dtype='M8[ns]')

# Create a dataset with this one array
xr_time_array = xr.DataArray(data=time,dims=['time'],name='time')
xr_ds = xr.Dataset(dict(time=xr_time_array))

print(""******************"")
print(""Created with fill value (NaT)"")
print(xr_ds[""time""])

# Save the dataset to zarr
location = ""from_xarray.zarr""
encoding = {
    ""time"":{""_FillValue"":time_fill_value}
}
xr_ds.to_zarr(location,encoding=encoding)

xr_read = xr.open_zarr(location)
print(""******************"")
print(""No fill value"")
print(xr_read[""time""])
```


### 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?

When I look in the .zmetadata file generated for this zarr store, I see that the time array as been converted to float and there is a units attribute:

```json
{
    ""metadata"": {
        "".zattrs"": {},
        "".zgroup"": {
            ""zarr_format"": 2
        },
        ""time/.zarray"": {
            ""chunks"": [
                2
            ],
            ""compressor"": {
                ""blocksize"": 0,
                ""clevel"": 5,
                ""cname"": ""lz4"",
                ""id"": ""blosc"",
                ""shuffle"": 1
            },
            ""dtype"": ""<f8"",
            ""fill_value"": -9.223372036854776e+18,
            ""filters"": null,
            ""order"": ""C"",
            ""shape"": [
                2
            ],
            ""zarr_format"": 2
        },
        ""time/.zattrs"": {
            ""_ARRAY_DIMENSIONS"": [
                ""time""
            ],
            ""calendar"": ""proleptic_gregorian"",
            ""units"": ""days since 2023-01-02 00:00:00""
        }
    },
    ""zarr_consolidated_format"": 1
}
```

If I open the data using zarr, the actual values in the time array look fine, given the transformation:
```python
z = zarr.open(location,'r')

print(f'Fill value: {z[""time""].fill_value}')
print(f'Data values: {z[""time""][:]}')
```
Output:
```
Fill value: -9.223372036854776e+18
Data values: [-9.22337204e+18  0.00000000e+00]
```

### Environment

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.11.3 | packaged by conda-forge | (main, Apr  6 2023, 08:58:31) [Clang 14.0.6 ]
python-bits: 64
OS: Darwin
OS-release: 22.4.0
machine: arm64
processor: arm
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: ('en_US', 'UTF-8')
libhdf5: None
libnetcdf: None

xarray: 2023.4.2
pandas: 2.0.1
numpy: 1.24.3
scipy: None
netCDF4: None
pydap: None
h5netcdf: None
h5py: None
Nio: None
zarr: 2.14.2
cftime: None
nc_time_axis: None
PseudoNetCDF: 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: 67.7.2
pip: 23.1.2
conda: None
pytest: None
mypy: None
IPython: 8.12.0
sphinx: None
</details>
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