`.chunk()` doesn't create chunks on 0 dim arrays

What happened?

.chunk's docstring states:

        """Coerce this array's data into a dask arrays with the given chunks.

        If this variable is a non-dask array, it will be converted to dask
        array. If it's a dask array, it will be rechunked to the given chunk
        sizes.

...but this doesn't happen for 0 dim arrays; example below.

For context, as part of #8245, I had a function that creates a template array. It created an empty DataArray, then expanded dims for each dimension. And it kept blowing up memory! ...until I realized that it was actually not a lazy array.

What did you expect to happen?

It may be that we can't have a 0-dim dask array — but then we should raise in this method, rather than return the wrong thing.

Minimal Complete Verifiable Example

[ins] In [1]: type(xr.DataArray().chunk().data)
Out[1]: numpy.ndarray

[ins] In [2]: type(xr.DataArray(1).chunk().data)
Out[2]: numpy.ndarray

[ins] In [3]: type(xr.DataArray([1]).chunk().data)
Out[3]: dask.array.core.Array

MVCE confirmation

• Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
• Complete example — the example is self-contained, including all data and the text of any traceback.
• Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result.
• New issue — a search of GitHub Issues suggests this is not a duplicate.

Relevant log output

No response

Anything else we need to know?

No response

Environment

Start at the DataArray .chunk() entry point and reproduce the three examples from the issue, comparing the resulting data types for zero-, one-, and higher-dimensional arrays. Determine whether zero-dimensional arrays should become lazy or raise an error, then add coverage demonstrating the chosen behavior and run the relevant test suite.