html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/issues/827#issuecomment-211138272,https://api.github.com/repos/pydata/xarray/issues/827,211138272,MDEyOklzc3VlQ29tbWVudDIxMTEzODI3Mg==,1217238,2016-04-18T00:25:00Z,2016-04-18T00:25:00Z,MEMBER,"Ah, I finally figured out what's going on.

We use pandas to cleanup time units in an attempt to always write ISO-8601 compatible reference times. Unfortunately, pandas interprets dates like `'1-1-1'` or `'01-JAN-0001'` as January 1, 2001:

```
In [21]: pd.Timestamp('1-1-1 00:00:0.0')
Out[21]: Timestamp('2001-01-01 00:00:00')

In [25]: pd.Timestamp('01-JAN-0001 00:00:00')
Out[25]: Timestamp('2001-01-01 00:00:00')
```

One might argue this is a bug in pandas, but nonetheless that's what it does.

xarray can currently handle datetimes outside the range dates hangled by pandas (roughly 1700-2300), but only if pandas raises an OutOfBoundDatetime error.

Two fixes that we need for this:
- use netCDF4's reference time decoding (if available) _before_ trying to use pandas in [decode_cf_datetime](https://github.com/pydata/xarray/blob/master/xarray/conventions.py#L115). Note that it is important to only decode only the one reference time if possible using netCDF4, because it's a lot faster to parse dates with vectorized operations with pandas/numpy.
- stop using [_cleanup_netcdf_time_units](https://github.com/pydata/xarray/blob/master/xarray/conventions.py#L225), since apparently it can go wrong.

cc @jhamman who has some experience with these issues
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,148876551
https://github.com/pydata/xarray/issues/827#issuecomment-210926466,https://api.github.com/repos/pydata/xarray/issues/827,210926466,MDEyOklzc3VlQ29tbWVudDIxMDkyNjQ2Ng==,1217238,2016-04-17T00:09:06Z,2016-04-17T00:09:15Z,MEMBER,"When you're writing the data back to disk with [to_netcdf](http://xarray.pydata.org/en/stable/generated/xarray.Dataset.to_netcdf.html#xarray.Dataset.to_netcdf), try writing something like: `ds.to_netcdf('somefile.nc', encoding={'time': {'units': '01-JAN-0001 00:00:00'}})`.

But I'm a little surprised this doesn't work by default. Xarray does use '2001-01-01' as a default reference time, but if you pulled the data from an existing dataset (rather than creating the time variable directly yourself such as with numpy or pandas), then it should save the original units in `encoding` attribute of the `time` variable, which should then be used to save the units that it writes to the file. If `ds` is the name of the dataset you open from OpenDAP or save to netcdf, what does the value of `ds.time.encoding` look like?
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,148876551