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
1474785646,I_kwDOAMm_X85X53Fu,7354,'open_mfdataset' zarr zip timestamp issue,34686298,open,0,,,5,2022-12-04T12:45:12Z,2022-12-16T00:29:54Z,,NONE,,,,"### What happened?

We have been collecting Satellite data and we save each image as one `{time}.zarr.zip` file. 
We then collate the images using `xr.open_mfdataset` and same them to `large.zarr.zip` file.
When loading this file the timestamps are all the same. 

This bug did not appear in `2022.3.0` but it did in `2022.6.0`

I tried to keep this as minimum as possible, but its a bit of a long example. Hopefully the comments help.

Sorry if this has already been reported, but I could not find it in the `issue` list

### What did you expect to happen?

Expected the time stamps to reflect the data that went in

### Minimal Complete Verifiable Example

```Python
import pandas as pd
import xarray as xr
import numpy as np
from datetime import datetime, timedelta
import zarr
import os
import glob

# ids and times
path = ""tmp.zarr.zip""
ids = np.array(range(0, 10))
times = [datetime(2022, 9, 1) + timedelta(minutes=60 * i) for i in range(0, 10)]


# make 10 random zipp files
for time in times:
    dataset = xr.DataArray(
        np.random.uniform(size=(1, len(ids))),
        coords=((""time"", [time]), (""id"", ids)),
        name=""data"",
    ).to_dataset(name=""data"")

    file_name = f""tmp_dir/{time.isoformat()}.zarr.zip""

    if os.path.exists(file_name):
        os.remove(file_name)
    with zarr.ZipStore(file_name) as store:
        dataset.to_zarr(store)

# load them all together
files = list(glob.glob(f""tmp_dir/*.zarr.zip""))
dataset = xr.open_mfdataset(files, engine=""zarr"").sortby(""time"")

# this is fine!
assert pd.to_datetime(dataset.time.values[0]) == times[0]
assert pd.to_datetime(dataset.time.values[1]) == times[1]

# save to file
if os.path.exists(path):
    os.remove(path)
with zarr.ZipStore(path) as store:
    dataset.to_zarr(store)

# read the file
dataset_read = xr.open_dataset(path, engine=""zarr"")
print(dataset_read)

# this casues an error
assert pd.to_datetime(dataset_read.time.values[0]) == times[0]
assert pd.to_datetime(dataset_read.time.values[1]) == times[1]
```


### 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

```Python
/Users/peterdudfield/Documents/Github/nwp/venv/lib/python3.8/site-packages/xarray/core/dataset.py:2060: SerializationWarning: saving variable None with floating point data as an integer dtype without any _FillValue to use for NaNs
  return to_zarr(  # type: ignore
<xarray.Dataset>
Dimensions:  (time: 10, id: 10)
Coordinates:
  * id       (id) int64 0 1 2 3 4 5 6 7 8 9
  * time     (time) datetime64[ns] 2022-09-01 2022-09-01 ... 2022-09-01
Data variables:
    data     (time, id) float64 ...
Traceback (most recent call last):
  File ""/Users/peterdudfield/Documents/Github/nwp/venv/lib/python3.8/site-packages/IPython/core/interactiveshell.py"", line 3251, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File ""<ipython-input-16-45f86e8a5977>"", line 36, in <module>
    assert pd.to_datetime(dataset_read.time.values[1]) == times[1]
AssertionError
```


### Anything else we need to know?

_No response_

### Environment

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.8.2 (default, Jun  8 2021, 11:59:35) 
[Clang 12.0.5 (clang-1205.0.22.11)]
python-bits: 64
OS: Darwin
OS-release: 20.4.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: None
LOCALE: ('en_GB', 'UTF-8')
libhdf5: 1.12.1
libnetcdf: 4.7.4
xarray: 2022.6.0
pandas: 1.4.2
numpy: 1.22.0
scipy: 1.7.3
netCDF4: 1.5.8
pydap: None
h5netcdf: 0.13.1
h5py: 3.6.0
Nio: None
zarr: 2.10.3
cftime: 1.6.0
nc_time_axis: None
PseudoNetCDF: None
rasterio: 1.2.10
cfgrib: 0.9.9.1
iris: None
bottleneck: 1.3.4
dask: 2022.01.0
distributed: None
matplotlib: 3.5.1
cartopy: None
seaborn: None
numbagg: None
fsspec: 2022.11.0
cupy: None
pint: None
sparse: None
flox: None
numpy_groupies: None
setuptools: 57.0.0
pip: 21.1.2
conda: None
pytest: 6.2.5
IPython: 8.0.1
sphinx: None


</details>
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