xarray.DataArray.where always returns array of float64 regardless of input dtype

MCVE Code Sample

import numpy as np
import xarray as xr

a = xr.DataArray(np.arange(25).reshape(5, 5), dims=('x', 'y'))
print(a.dtype)
'int32'
a_sub = a.where(a.x + a.y < 4)
a_sub.dtype
'float64'

Expected Output

a_sub should be an xarray of dtype int32

Problem Description

The documentation (http://xarray.pydata.org/en/stable/generated/xarray.DataArray.where.html)
states that return type should be the same type as caller. However, the return type is always float64

Output of xr.show_versions()

INSTALLED VERSIONS

commit: None
python: 3.7.1 | packaged by conda-forge | (default, Mar 13 2019, 13:32:59) [MSC v.1900 64 bit (AMD64)]
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 45 Stepping 7, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None
libhdf5: 1.10.4
libnetcdf: 4.6.2

xarray: 0.13.0
pandas: 0.25.1
numpy: 1.17.2
scipy: 1.3.1
netCDF4: 1.4.2
pydap: None
h5netcdf: None
h5py: 2.9.0
Nio: None
zarr: None
cftime: 1.0.3.4
nc_time_axis: None
PseudoNetCDF: None
rasterio: 1.0.22
cfgrib: None
iris: None
bottleneck: None
dask: 2.5.2
distributed: None
matplotlib: 3.1.1
cartopy: 0.17.0
seaborn: 0.9.0
numbagg: None
setuptools: 41.4.0
pip: 19.2.3
conda: None
pytest: None
IPython: 7.8.0
sphinx: None

Reproduce the MCVE against the current xarray.DataArray.where entry point and trace how the condition and missing values determine the result dtype. Done means an integer DataArray retains int32 where the expected output permits it, with regression coverage for the reported case.