Hi again, I check a little bit more the behavior of Zarr and Dask and I found that the problem only occurs when the lock option in the 'dask.store' method is set as None or False, below you can find an example: ```py

import numpy as np import zarr import dask.array as da

Writing an small zarr array with 42.2 as the value

z1 = zarr.open('data/example.zarr', mode='w', shape=(152), chunks=(30), dtype='f4') z1[:] = 42.2

resizing the array

z2 = zarr.open('data/example.zarr', mode='a') z2.resize(308)

New data to append

append_data = da.from_array(np.array([50.3] * 156), chunks=(30))

If you pass to the lock parameters None or False you will get the PermissonError or some 0s in the final result

so I think this is the problem when Xarray writes to Zarr with Dask, (I saw in the code that by default use lock = None)

If you put lock = True all the problems disappear.

da.store(append_data, z2, regions=[tuple([slice(152, 308)])], lock=None)

the result can contain many 0s or throw an error

print(z2[:]) ```

Hope this help to fix the bug.