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/784#issuecomment-192357422,https://api.github.com/repos/pydata/xarray/issues/784,192357422,MDEyOklzc3VlQ29tbWVudDE5MjM1NzQyMg==,4992424,2016-03-04T16:58:59Z,2016-03-04T16:58:59Z,NONE,"The `reindex_like()` approach works super well in my case. Since only my latitudes are screwed up (and they're spaced by a tad more than a degree), a low tolerance 1e-2-1e-3 worked perfectly. 
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,138443211
https://github.com/pydata/xarray/issues/784#issuecomment-192332830,https://api.github.com/repos/pydata/xarray/issues/784,192332830,MDEyOklzc3VlQ29tbWVudDE5MjMzMjgzMA==,4992424,2016-03-04T15:56:58Z,2016-03-04T15:56:58Z,NONE,"Hi @mathause, I actually just ran into a very similar problem to your second bullet point. I had some limited success by manually re-building the re-gridded dataset onto the CESM coordinate system, swapping out the not-exactly-but-actually-close-enough coordinates for the CESM reference data's coordinates. In my case, I was re-gridding with CDO, but even when I explicitly pull out the CESM grid definition it wouldn't match precisely.

Since there was a lot of boilerplate code to do this in xarray (although I had a lot of success defining a callback to pass in with open_dataset), it was far easier just to use NCO to copy the correct coordinate variables into the re-gridded data.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,138443211