Support alignment/broadcasting with unlabeled dimensions of size 1

Sometimes, it's convenient to include placeholder dimensions of size 1, which allows for removing any ambiguity related to the order of output dimensions.

Currently, this is not supported with xarray:

>>> xr.DataArray([1], dims='x') + xr.DataArray([1, 2, 3], dims='x')
ValueError: arguments without labels along dimension 'x' cannot be aligned because they have different dimension sizes: {1, 3}

>>> xr.Variable(('x',), [1]) + xr.Variable(('x',), [1, 2, 3])
ValueError: operands cannot be broadcast together with mismatched lengths for dimension 'x': (1, 3)

However, these operations aren't really ambiguous. With size 1 dimensions, we could logically do broadcasting like NumPy arrays, e.g.,

>>> np.array([1]) + np.array([1, 2, 3])
array([2, 3, 4])

This would be particularly convenient if we add keepdims=True to xarray operations (#2170).

Start by reproducing the DataArray and Variable examples in the issue and tracing xarray's alignment and broadcasting behavior for unlabeled dimensions. Done means size-1 dimensions broadcast like NumPy arrays without changing the labeled-dimension behavior, with tests covering both examples.