Cannot map Timestamp.isocalendar on tz-aware timestamp series, gives ValueError: MultiIndex has no single backing array
### Problem description

While:

    pd.to_datetime(dates).map(pd.Timestamp.isocalendar)

works as expected,

    pd.to_datetime(dates, utc=True).map(pd.Timestamp.isocalendar)

(i.e. just adding `utc=True`)

or any variation of it using `map` fails with the below error. Only a list comprehension works, so it doesn't seem possible to vectorize the operation. The error message is also confusing.

### Example code

```python
import pandas as pd

pd.show_versions()

dates = pd.Series(pd.date_range(start='20180101', end='20180102', periods=2))
print(dates)
print(pd.to_datetime(dates).map(pd.Timestamp.isocalendar))
print([x.isocalendar() for x in pd.to_datetime(dates, utc=True)])

# Error here
print(pd.to_datetime(dates, utc=True).map(lambda x:x.isocalendar()))
```

Try it here: https://repl.it/repls/RawClosedPorts

Output:

```
0   2018-01-01
1   2018-01-02
dtype: datetime64[ns]
0    (2018, 1, 1)
1    (2018, 1, 2)
dtype: object
[(2018, 1, 1), (2018, 1, 2)]
Traceback (most recent call last):
  File "main.py", line 9, in <module>
    print(pd.to_datetime(dates, utc=True).map(lambda x:x.isocalendar()))
  File "/home/runner/.local/share/virtualenvs/python3/lib/python3.7/site-packages/pandas/core/series.py", line 3821, in map
    new_values = super()._map_values(arg, na_action=na_action)
  File "/home/runner/.local/share/virtualenvs/python3/lib/python3.7/site-packages/pandas/core/base.py", line 1300, in _map_values
    new_values = map_f(values, mapper)
  File "/home/runner/.local/share/virtualenvs/python3/lib/python3.7/site-packages/pandas/core/base.py", line 1287, in <lambda>
    map_f = lambda values, f: values.map(f)
  File "/home/runner/.local/share/virtualenvs/python3/lib/python3.7/site-packages/pandas/core/arrays/datetimelike.py", line 722, in map
    return Index(self).map(mapper).array
  File "/home/runner/.local/share/virtualenvs/python3/lib/python3.7/site-packages/pandas/core/indexes/multi.py", line 633, in array
    raise ValueError(msg)
ValueError: MultiIndex has no single backing array. Use 'MultiIndex.to_numpy()' to get a NumPy array of tuples.
```

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

<details>

```
INSTALLED VERSIONS
------------------
commit           : None
python           : 3.7.4.final.0
python-bits      : 64
OS               : Linux
OS-release       : 4.15.0-1036-gcp
machine          : x86_64
processor        :
byteorder        : little
LC_ALL           : None
LANG             : C.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 0.25.0
numpy            : 1.17.0
pytz             : 2019.2
dateutil         : 2.8.0
pip              : 19.0.3
setuptools       : 40.8.0
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : None
IPython          : None
pandas_datareader: None
bs4              : None
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : None
matplotlib       : 3.1.1
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
s3fs             : None
scipy            : 1.3.0
sqlalchemy       : None
tables           : None
xarray           : None
xlrd             : None
xlwt             : None
xlsxwriter       : None
```
</details>
