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
1050082137,I_kwDOAMm_X84-lvtZ,5969,"`to_zarr(append_dim=""time"")` appends incorrect datetimes",460756,closed,0,,,3,2021-11-10T17:00:53Z,2024-05-03T17:09:31Z,2024-05-03T17:09:30Z,NONE,,,,"### Description

If you create a Zarr with a single timestep and then append to the `time` dimension of that Zarr in subsequent writes then the appended timestamps are likely to be wrong.  This only seems to happen if the `time` dimension is `datetime64`.

### Minimal Complete Verifiable Example

Create a really simple `Dataset`:

```python
times = pd.date_range(""2000-01-01 00:35"", periods=8, freq=""6H"")
da = xr.DataArray(coords=[times], dims=[""time""])
ds = da.to_dataset(name=""foo"")
```

Write just the first timestep to a new Zarr store:

```python
ZARR_PATH = ""test.zarr""
ds.isel(time=[0]).to_zarr(ZARR_PATH, mode=""w"")
```

So far, so good!

Now things get weird... let's append the remainder of `ds` to the Zarr store:

```python
ds.isel(time=slice(1, None)).to_zarr(ZARR_PATH, append_dim=""time"")
```

This throws a warning, which is probably relevant:

```
/home/jack/miniconda3/envs/nowcasting_dataset/lib/python3.9/site-packages/xarray/core/dataset.py:2037: 
SerializationWarning: saving variable None with floating point data as an integer dtype
 without any _FillValue to use for NaNs
  return to_zarr(
```

### What happened

Let's load the Zarr and print the contents on the `time` coord:

```python
ds_loaded = xr.open_dataset(ZARR_PATH, engine=""zarr"")
print(ds_loaded.time)
```
```
<xarray.DataArray 'time' (time: 8)>
array(['2000-01-01T00:35', '2000-01-01T00:35',
       '2000-01-01T00:35', '2000-01-02T00:35',
       '2000-01-02T00:35', '2000-01-02T00:35',
       '2000-01-03T00:35', '2000-01-03T00:35'],
      dtype='datetime64[ns]')
Coordinates:
  * time     (time) datetime64[ns] 2000-01-01T00:35:00 ... 2000-01-03T00:35:00
```

(I've removed the seconds and milliseconds to make it a bit easier to read)

The first and fifth time coords (2000-01-01T00:35 and 2000-01-02T00:35) are correct.  None of the others are correct!

The encoding is not appropriate (see #3942)... notice that the `units` is `days since...`, which clearly can't represent sub-day resolution:

```python
print(ds_loaded.time.encoding)
```
```
{'chunks': (1,),
 'preferred_chunks': {'time': 1},
 'compressor': Blosc(cname='lz4', clevel=5, shuffle=SHUFFLE, blocksize=0),
 'filters': None,
 'units': 'days since 2000-01-01 00:35:00',
 'calendar': 'proleptic_gregorian',
 'dtype': dtype('int64')}
```

### What you expected to happen

The correct `time` coords are:
```python
print(ds.time)
```
```
<xarray.DataArray 'time' (time: 8)>
array(['2000-01-01T00:35', '2000-01-01T06:35',
       '2000-01-01T12:35', '2000-01-01T18:35',
       '2000-01-02T00:35', '2000-01-02T06:35',
       '2000-01-02T12:35', '2000-01-02T18:35'],
      dtype='datetime64[ns]')
Coordinates:
  * time     (time) datetime64[ns] 2000-01-01T00:35:00 ... 2000-01-02T18:35:00
```

### Anything else we need to know?

There are three workarounds that I'm aware of:

1)  When first creating the Zarr, write two or more timesteps into the Zarr.  Then you can append any number of timesteps to the Zarr and everything works fine.
2) Convert the `time` coords to Unix epoch, represented as ints.
3) Manually set the encoding before the first write (as suggested in https://github.com/pydata/xarray/issues/3942#issuecomment-610444090).  For example:

```python
ds.isel(time=[0]).to_zarr(
    ZARR_PATH, 
    mode=""w"",
    encoding={
        'time': {
            'units': 'seconds since 1970-01-01'
        }
    }
)
```

### Related issues

It's possible that the root cause of this issue is #3942.

And I think #3379 is another symptom of this issue.

### Environment

<details><summary>Output of <tt>xr.show_versions()</tt></summary>

INSTALLED VERSIONS
------------------
commit: None
python: 3.9.7 | packaged by conda-forge | (default, Sep 29 2021, 19:20:46) 
[GCC 9.4.0]
python-bits: 64
OS: Linux
OS-release: 5.13.0-21-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_GB.UTF-8
LOCALE: ('en_GB', 'UTF-8')
libhdf5: 1.12.1
libnetcdf: 4.8.1

xarray: 0.20.1
pandas: 1.3.4
numpy: 1.21.4
scipy: 1.7.2
netCDF4: 1.5.8
pydap: None
h5netcdf: 0.11.0
h5py: 3.4.0
Nio: None
zarr: 2.10.1
cftime: 1.5.1.1
nc_time_axis: None
PseudoNetCDF: None
rasterio: 1.2.8
cfgrib: 0.9.9.1
iris: None
bottleneck: 1.3.2
dask: 2021.10.0
distributed: None
matplotlib: 3.4.3
cartopy: None
seaborn: None
numbagg: None
fsspec: 2021.11.0
cupy: None
pint: None
sparse: None
setuptools: 58.5.3
pip: 21.3.1
conda: None
pytest: 6.2.5
IPython: 7.29.0
sphinx: None

</details>
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