Inconsitent treatment of datetime64 data between DataArray and Dask array

What is your issue?

When processing datetime as the data of a DataArray, Xarray could lead to different results depending on whether the data is a numpy.array or a Dask.array.Array:

import dask.array
import numpy as np
import xarray as xr

data = np.array("2016-01-01").astype("datetime64[s]")

da1 = xr.DataArray(data)
da2 = xr.DataArray(dask.array.from_array(data))

assert da1.equals(da2)

assert da1.astype("datetime64[M]").dtype == '<M8[s]'
assert da2.astype("datetime64[M]").dtype == '<M8[M]'

assert da1.astype("datetime64[M]").astype(int).data == 1451606400
assert da2.astype("datetime64[M]").astype(int).compute().data == 552

Environment info:

• xarray 2025.7.1
• dask 2025.7.0

Issue opened after @spencerkclark comment in #10220

Start by running the Python reproducer in the issue with NumPy-backed and Dask-backed DataArray objects, then trace the astype calls involved in datetime64 conversion. Compare the resulting dtypes and integer values, and add a regression test wherever the relevant behavior is covered. Done means both paths have an agreed, consistent result.