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/521#issuecomment-129198927,https://api.github.com/repos/pydata/xarray/issues/521,129198927,MDEyOklzc3VlQ29tbWVudDEyOTE5ODkyNw==,2443309,2015-08-09T15:29:52Z,2015-08-09T15:29:52Z,MEMBER,"> Perhaps the long term fix is to implement non-standard calendars within numpy itself.

I agree, although that sounds like quite an undertaking.  Maybe raise an issue over at numpy and ask if they would be interested in a multi-calendar api? If numpy could make it work, then I'm sure pandas could as well.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,99836561
https://github.com/pydata/xarray/issues/521#issuecomment-129102650,https://api.github.com/repos/pydata/xarray/issues/521,129102650,MDEyOklzc3VlQ29tbWVudDEyOTEwMjY1MA==,2443309,2015-08-09T04:03:34Z,2015-08-09T04:03:34Z,MEMBER,"We _try_ to cast all the time variables to a pandas time index.  This gives xray the ability to use many of the fast and fancy timeseries tools that pandas has.  One consequence of that is that non-standard calendars, such as the ""noleap"" calendar must have dates inside the valid range of the standard calendars (1678 and 2226). 

Does that make since? Ideally, numpy and pandas would support custom calendars but they don't so, at this point, we're bound to there limits.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,99836561
https://github.com/pydata/xarray/issues/521#issuecomment-129059364,https://api.github.com/repos/pydata/xarray/issues/521,129059364,MDEyOklzc3VlQ29tbWVudDEyOTA1OTM2NA==,2443309,2015-08-08T22:43:05Z,2015-08-08T22:43:05Z,MEMBER,"@rabernat - 

Yes - this is all coming from the `netCDF4.netcdftime` module.

The work around with xray is to use `ds = xray.open_dataset(filename, decode_times=False)` then to fix up the time variable ""manually"". You can use `xray.decode_cf()` or simply assign a new pandas time index to your time variable.

As an aside, I also work with CESM output and this is a common problem with its netCDF output.
","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,99836561