@kmuehlbauer - I think I'm not understanding what you are suggesting because the zarr store is still not being read correctly when I switch the fill value to a different date:

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

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

<xarray.DataArray 'time' (time: 2)> array(['2023-01-02T00:00:00.000000000', '2023-01-02T00:00:00.000000000'], dtype='datetime64[ns]') Coordinates: * time (time) datetime64[ns] 2023-01-02 2023-01-02 {'chunks': (2,), 'preferred_chunks': {'time': 2}, 'compressor': Blosc(cname='lz4', clevel=5, shuffle=SHUFFLE, blocksize=0), 'filters': None, '_FillValue': -9.223372036854776e+18, 'units': 'days since 2023-01-02 00:00:00', 'calendar': 'proleptic_gregorian', 'dtype': dtype('float64')} ```