```python xr_ds.to_zarr(location_new_fill,encoding=encoding)

xr_read = xr.open_zarr(location) print("******") print("Read back out of the zarr store with xarray") print(xr_read["time"]) print(xr_read["time"].encoding) ```

@christine-e-smit Is this just a remnant of copy&paste? The above code writes to location_new_fill, but reads from location.

Here is my code and output for comparison (using latest zarr/xarray):

```python

Create a numpy array of type np.datetime64 with one fill value and one date

time_fill_value = np.datetime64("1900-01-01") time = np.array([np.datetime64("NaT"), '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 1900-01-01") print(xr_ds["time"])

Save the dataset to zarr

location_new_fill = "from_xarray_new_fill.zarr" encoding = { "time":{"_FillValue":time_fill_value,"dtype":np.int64} } xr_ds.to_zarr(location_new_fill, encoding=encoding)

xr_read = xr.open_zarr(location_new_fill) print("******") print("Read back out of the zarr store with xarray") print(xr_read["time"]) print(xr_read["time"].encoding) ```

```python

---

Created with fill value 1900-01-01 <xarray.DataArray 'time' (time: 2)> array([ 'NaT', '2023-01-02T00:00:00.000000000'], dtype='datetime64[ns]') Coordinates: * time (time) datetime64[ns] NaT 2023-01-02

---

Read back out of the zarr store with xarray <xarray.DataArray 'time' (time: 2)> array([ 'NaT', '2023-01-02T00:00:00.000000000'], dtype='datetime64[ns]') Coordinates: * time (time) datetime64[ns] NaT 2023-01-02 {'chunks': (2,), 'preferred_chunks': {'time': 2}, 'compressor': Blosc(cname='lz4', clevel=5, shuffle=SHUFFLE, blocksize=0), 'filters': None, '_FillValue': -25567, 'units': 'days since 2023-01-02 00:00:00', 'calendar': 'proleptic_gregorian', 'dtype': dtype('int64')} ```

This doesn't look correct either. At least the decoded _FillValue or the units are wrong. So -25567 is 1900-01-01 when referenced to of unix-epoch (Question: Is zarr time based on unix epoch?). When read back via zarr only this would decode into:

python <xarray.DataArray 'time' (time: 2)> array(['1953-01-02T00:00:00.000000000', '2023-01-02T00:00:00.000000000'], dtype='datetime64[ns]')

I totally agree with @christine-e-smit, this is all very confusing. As said at the beginning, I have little knowledge of zarr. I'm currently digging into cf encoding/decoding which made me jump on here.

AFAICT, it looks like already the encoding has a problem, at least the data on disk is already not what we expect. It seems that somehow the xarray cf_encoding/decoding is not well aligned with the zarr writing/reading of datetimes.