BUG: Series inconsistent with overflow errors in Timedelta calcs
- [x] I have checked that this issue has not already been reported.

- [x] I have confirmed this bug exists on the latest version of pandas.

- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.

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**Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug.

#### Code Sample, a copy-pastable example

```python

>>> x = pd.Series([pd.Timedelta(100000, "days"), pd.Timedelta(100000, "days")])

# Results in ValueError
>>> x.sum()

# Results in OverflowError
>>> pd.Timedelta(100000, "days")*2

# Results in OverflowError
>>> x + x

# Permits overflow
>>> x*2
0   -13504 days +00:25:26.290448384
1   -13504 days +00:25:26.290448384
dtype: timedelta64[ns]
```

#### Problem description

It would seem that pandas.Series calcs with Timedeltas are inconsistent in raising overflow errors, or not.
The exact error is also inconsistent (OverflowError vs ValueError).

#### Expected Output

Ideally `x*2` in above example raises an error, and all overflow related errors are of type OverflowError.

#### Output of ``pd.show_versions()``
INSTALLED VERSIONS
------------------
commit           : 5f648bf1706dd75a9ca0d29f26eadfbb595fe52b
python           : 3.7.5.final.0
python-bits      : 64
OS               : Windows
OS-release       : 10
Version          : 10.0.19041
machine          : AMD64
processor        : Intel64 Family 6 Model 158 Stepping 10, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : None.None

pandas           : 1.3.2
numpy            : 1.21.2
pytz             : 2021.1
dateutil         : 2.8.2
pip              : 19.2.3
setuptools       : 41.2.0
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
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : None
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pyxlsb           : None
s3fs             : None
scipy            : None
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : None

</details>
