Series (but not DataFrame) combine_first() loses timezone information
#### Code Sample, a copy-pastable example if possible

```python
dts1 = pd.date_range('20150101','20150105',tz='UTC')  
df1 = pd.DataFrame({'DATE':dts1})                     
dts2 = pd.date_range('20150103','20150105',tz='UTC')  
df2 = pd.DataFrame({'DATE':dts2})                     
df = df1.combine_first(df2)                           
df.DATE[0].tz # returns<UTC>, 10567 fixed

ser = df1['DATE'].combine_first(df2['DATE'])
ser[0].tz  # returns None, should be <UTC> as above

```
#### Problem description

Calling `Series.combine_first` on two tz-localized datetime Series returns a non-localized Series.

#10567 handled the case when running `DataFrame.combine_first` on DataFrames with datetime tz columns. Oddly, this does not work for Series. This behavior is the same under at least both 0.19.2 and latest master so it appears it may never have been fixed with #10567.

#### Output of ``pd.show_versions()``

<details>
INSTALLED VERSIONS
------------------
commit: 576d5c6b76e039a411a7cc4c0de29813e2de0149
python: 3.6.5.final.0
python-bits: 64
OS: Windows
OS-release: 7
machine: AMD64
processor: Intel64 Family 6 Model 62 Stepping 4, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.24.0.dev0+103.g576d5c6b7
pytest: 3.6.0
pip: 10.0.1
setuptools: 39.2.0
Cython: 0.28.3
numpy: 1.14.2
scipy: 1.0.0
pyarrow: 0.8.0
xarray: 0.10.6
IPython: 6.4.0
sphinx: 1.7.5
patsy: 0.5.0
dateutil: 2.7.3
pytz: 2018.4
blosc: None
bottleneck: 1.2.1
tables: 3.4.3
numexpr: 2.6.4
feather: 0.4.0
matplotlib: 2.2.2
openpyxl: 2.5.3
xlrd: 1.1.0
xlwt: 1.3.0
xlsxwriter: 1.0.5
lxml: 4.1.1
bs4: 4.6.0
html5lib: 1.0.1
sqlalchemy: 1.2.8
pymysql: 0.8.1
psycopg2: None
jinja2: 2.10
s3fs: 0.1.5
fastparquet: 0.1.5
pandas_gbq: None
pandas_datareader: None
</details>
