id,node_id,number,title,user,state,locked,assignee,milestone,comments,created_at,updated_at,closed_at,author_association,active_lock_reason,draft,pull_request,body,reactions,performed_via_github_app,state_reason,repo,type
784042442,MDU6SXNzdWU3ODQwNDI0NDI=,4796,Use apply_ufunc for unary funcs,19226431,open,0,,,3,2021-01-12T08:56:03Z,2022-04-18T16:31:02Z,,CONTRIBUTOR,,,,"<!-- Please include a self-contained copy-pastable example that generates the issue if possible.

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- Minimal Complete Verifiable Examples: https://stackoverflow.com/help/mcve

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-->

DataArray.clip() of a chunked array returns an assertion error as soon as the argument takes an chunked array. With non-chunked arrays every thing works as intended. 

```python
x = xr.DataArray(np.random.uniform(size=[100, 100])).chunk(10)
x.clip(max=x)
```

**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 | packaged by conda-forge | (default, Dec  9 2020, 21:08:20) 
[GCC 9.3.0]
python-bits: 64
OS: Linux
OS-release: 5.4.0-60-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8
libhdf5: 1.10.4
libnetcdf: 4.6.3

xarray: 0.16.2
pandas: 1.2.0
numpy: 1.19.5
scipy: 1.5.0
netCDF4: 1.5.3
pydap: None
h5netcdf: 0.7.4
h5py: 2.10.0
Nio: None
zarr: 2.3.2
cftime: 1.0.4.2
nc_time_axis: None
PseudoNetCDF: None
rasterio: 1.1.0
cfgrib: None
iris: None
bottleneck: 1.2.1
dask: 2020.12.0
distributed: 2020.12.0
matplotlib: 3.1.3
cartopy: 0.18.0
seaborn: 0.11.0
numbagg: None
pint: None
setuptools: 49.2.1.post20200807
pip: 20.2.1
conda: 4.8.3
pytest: 6.0.1
IPython: 7.11.1
sphinx: 3.1.2

</details>
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830040696,MDU6SXNzdWU4MzAwNDA2OTY=,5024,xr.DataArray.sum() converts string objects into unicode,19226431,open,0,,,0,2021-03-12T11:47:06Z,2022-04-09T01:40:09Z,,CONTRIBUTOR,,,,"<!-- Please include a self-contained copy-pastable example that generates the issue if possible.

Please be concise with code posted. See guidelines below on how to provide a good bug report:

- Craft Minimal Bug Reports: http://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports
- Minimal Complete Verifiable Examples: https://stackoverflow.com/help/mcve

Bug reports that follow these guidelines are easier to diagnose, and so are often handled much more quickly.
-->

**What happened**:

When summing over all axes of a DataArray with strings of dtype `object`, the result is a one-size `unicode` DataArray. 

**What you expected to happen**:

I expected the summation would preserve the dtype, meaning the one-size DataArray would be of dtype `object`

**Minimal Complete Verifiable Example**:


```
ds = xr.DataArray('a', [range(3), range(3)]).astype(object)
ds.sum()
```

Output
```
  <xarray.DataArray ()>
    array('aaaaaaaaa', dtype='<U9')
```

On the other hand, when summing over one dimension only, the dtype is preserved
```
ds.sum('dim_0')
```

Output:
```
   <xarray.DataArray (dim_1: 3)>
    array(['aaa', 'aaa', 'aaa'], dtype=object)
    Coordinates:
      * dim_1    (dim_1) int64 0 1 2
```
 
**Anything else we need to know?**:

The problem becomes relevant as soon as dask is used in the workflow. Dask expects the aggregated DataArray to be of dtype `object` which will likely lead to errors in the operations to follow. 

Probably the behavior comes from creating a new DataArray after the reduction with `np.sum()` (which itself leads results in a pure python string).   

**Environment**:

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

<!-- Paste the output here xr.show_versions() here -->
INSTALLED VERSIONS
------------------
commit: None
python: 3.8.5 (default, Sep  4 2020, 07:30:14) 
[GCC 7.3.0]
python-bits: 64
OS: Linux
OS-release: 5.4.0-66-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8
libhdf5: 1.10.6
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: 0.7.4
h5py: 3.1.0
Nio: None
zarr: 2.3.2
cftime: 1.3.1
nc_time_axis: None
PseudoNetCDF: None
rasterio: 1.2.0
cfgrib: None
iris: None
bottleneck: 1.3.2
dask: 2021.01.1
distributed: 2021.01.1
matplotlib: 3.3.3
cartopy: 0.18.0
seaborn: 0.11.1
numbagg: None
pint: None
setuptools: 52.0.0.post20210125
pip: 21.0
conda: 4.9.2
pytest: 6.2.2
IPython: 7.19.0
sphinx: 3.4.3

</details>
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