`where` grows new dimensions for unrelated variables

In the example below, the dimensionality for data variable y grows from (b) to (b, a) after calling the dataset where method. This behaviour does not appear to be documented. Is it a bug?

    In [46]: ds = xarray.Dataset({"x": (("a", "b"), arange(25).reshape(5,5)+100), "y": ("b", arange(5)-100)}, {"a": arange(5), "b": arange(5)*2, "c": (("a",), list("ABCDE"))})
    
    In [47]: print(ds)
    <xarray.Dataset>
    Dimensions:  (a: 5, b: 5)
    Coordinates:
      * b        (b) int64 0 2 4 6 8
        c        (a) <U1 'A' 'B' 'C' 'D' 'E'
      * a        (a) int64 0 1 2 3 4
    Data variables:
        x        (a, b) int64 100 101 102 103 104 105 106 107 108 109 110 111 ...
        y        (b) int64 -100 -99 -98 -97 -96
    
    In [69]: ds.where((ds.c>='A') & (ds.c<='C'))
    Out[69]: 
    <xarray.Dataset>
    Dimensions:  (a: 5, b: 5)
    Coordinates:
      * b        (b) int64 0 2 4 6 8
        c        (a) <U1 'A' 'B' 'C' 'D' 'E'
      * a        (a) int64 0 1 2 3 4
    Data variables:
        x        (a, b) float64 100.0 101.0 102.0 103.0 104.0 105.0 106.0 107.0 ...
        y        (b, a) float64 -100.0 -100.0 -100.0 nan nan -99.0 -99.0 -99.0 ...

Start by reproducing the documented Dataset.where example with xarray, checking how the data variable y changes from (b) to (b, a). Read the Dataset.where entry point and existing tests for where behavior, if available. Done means determining whether the dimensionality change is intended and adding or updating coverage and documentation accordingly.