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822987300,MDU6SXNzdWU4MjI5ODczMDA=,5001,.min() doesn't work on np.datetime64 with a chunked Dataset,49512274,open,0,,,2,2021-03-05T11:12:19Z,2022-05-01T16:11:48Z,,NONE,,,,"<!-- Please include a self-contained copy-pastable example that generates the issue if possible.

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Hi all,

if a xr.Dataset is chunked, i cannot do ds.time.min(), i get an error : `ufunc 'add' cannot use operands with types dtype('<M8[ns]') and dtype('<M8[ns]')`. I don't know if it is expected ? 
Moreover, `ds2.time.mean()` works

Thanks

**What happened**:

raised an `UFuncTypeError: ufunc 'add' cannot use operands with types dtype('<M8[ns]') and dtype('<M8[ns]')`


**What you expected to happen**:

compute the min & max on a chunked datetime64 xarray.DataArray


**Minimal Complete Verifiable Example**:

```python
import xarray as xr
import numpy as np

obs=200
t0 = np.datetime64(""2010-01-01T00:00:00"")
tn = t0 + np.timedelta64(123*4, ""D"")

ds2 = xr.Dataset(
    {
        ""time"": ([""obs""], np.arange(t0, tn, (tn-t0)/obs)),
    },
    coords={
        ""obs"": ([""obs""], np.arange(obs)),
    },
).chunk({""obs"": 100})

ds2.time.min()
```

**Anything else we need to know?**:

ds2.time.mean() works, max & min raise Exception


**Environment**:

<details><summary>Output of <tt>xr.show_versions()</tt></summary>

<!-- Paste the output here xr.show_versions() here -->

INSTALLED VERSIONS
------------------
commit: None
python: 3.7.9 (default, Aug 31 2020, 12:42:55) 
[GCC 7.3.0]
python-bits: 64
OS: Linux
OS-release: 4.15.0-133-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: fr_FR.UTF-8
LOCALE: fr_FR.UTF-8
libhdf5: 1.12.0
libnetcdf: 4.7.4

xarray: 0.16.2
pandas: 1.2.1
numpy: 1.19.5
scipy: 1.6.0
netCDF4: 1.5.5.1
pydap: None
h5netcdf: None
h5py: None
Nio: None
zarr: 2.6.1
cftime: 1.3.1
nc_time_axis: None
PseudoNetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: None
dask: 2021.01.1
distributed: 2021.01.1
matplotlib: 3.3.4
cartopy: None
seaborn: None
numbagg: None
pint: 0.16.1
setuptools: 52.0.0.post20210125
pip: 20.3.3
conda: None
pytest: 6.2.2
IPython: 7.20.0
sphinx: 3.5.0


</details>
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