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/1064#issuecomment-359839979,https://api.github.com/repos/pydata/xarray/issues/1064,359839979,MDEyOklzc3VlQ29tbWVudDM1OTgzOTk3OQ==,1997005,2018-01-23T16:07:44Z,2018-01-23T16:07:44Z,CONTRIBUTOR,"FYI, `merged.time.encoding = {}` before calling `to_netcdf` seems to avoid the RuntimeWarning.","{""total_count"": 2, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 1, ""rocket"": 0, ""eyes"": 0}",,185709414
https://github.com/pydata/xarray/issues/1064#issuecomment-358570582,https://api.github.com/repos/pydata/xarray/issues/1064,358570582,MDEyOklzc3VlQ29tbWVudDM1ODU3MDU4Mg==,1997005,2018-01-18T08:16:06Z,2018-01-18T08:16:06Z,CONTRIBUTOR,"There you go !

```python
import numpy
import pandas
import tempfile
import warnings
import xarray


array1 = xarray.DataArray(
    numpy.random.rand(5),
    dims=['time'],
    coords={'time': pandas.to_datetime(['2018-01-01', '2018-01-01 00:01', '2018-01-01 00:02', '2018-01-01 00:03', '2018-01-01 00:04'])},
    name='foo'
)

array2 = xarray.DataArray(
    numpy.random.rand(5),
    dims=['time'],
    coords={'time': pandas.to_datetime(['2018-01-01 00:05', '2018-01-01 00:05:10', '2018-01-01 00:05:20', '2018-01-01 00:05:30', '2018-01-01 00:05:40'])},
    name='foo'
)

with tempfile.NamedTemporaryFile() as tmp:
    # save first array
    array1.to_netcdf(tmp.name)
    # reload it
    array1_reloaded = xarray.open_dataarray(tmp.name)

    # the time encoding stores minutes as int, so seconds won't be allowed at next call of to_netcdf
    assert array1_reloaded.time.encoding['dtype'] == numpy.int64
    assert array1_reloaded.time.encoding['units'] == 'minutes since 2018-01-01 00:00:00'

    merged = xarray.merge([array1_reloaded, array2])
    array1_reloaded.close()

    with warnings.catch_warnings():
        warnings.filterwarnings('error', category=RuntimeWarning)
        merged.to_netcdf(tmp.name)
```
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,185709414
https://github.com/pydata/xarray/issues/1064#issuecomment-358324488,https://api.github.com/repos/pydata/xarray/issues/1064,358324488,MDEyOklzc3VlQ29tbWVudDM1ODMyNDQ4OA==,1997005,2018-01-17T14:41:14Z,2018-01-17T14:41:14Z,CONTRIBUTOR,"I faced this issue when switching from a ``concat`` to a ``merge``.

The first merged dataset had a time dimension which ``encoding`` says ``{'calendar': 'proleptic_gregorian', 'dtype': dtype('int64'), 'units': 'minutes since 2017-08-20 00:00:00'}``, which meant that the data from the second merged dataset could not be stored with a finer resolution than minutes.

If I try to store values like '2017-08-20 00:00:30', I get the warning `xarray\conventions.py:1092: RuntimeWarning: saving variable time with floating point data as an integer dtype without any _FillValue to use for NaNs`.

Maybe it is similar in your case: netcdf stored the data as 'hours since XXXX', so you lose the minutes.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,185709414