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/2962#issuecomment-492625308,https://api.github.com/repos/pydata/xarray/issues/2962,492625308,MDEyOklzc3VlQ29tbWVudDQ5MjYyNTMwOA==,10050469,2019-05-15T12:01:42Z,2019-05-15T12:01:42Z,MEMBER,Thanks! If you want you can also accept the stackoverflow answer for later reference,"{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,444367776
https://github.com/pydata/xarray/issues/2962#issuecomment-492623485,https://api.github.com/repos/pydata/xarray/issues/2962,492623485,MDEyOklzc3VlQ29tbWVudDQ5MjYyMzQ4NQ==,10050469,2019-05-15T11:55:17Z,2019-05-15T11:55:17Z,MEMBER,"> But I can't figure out what was the code doing without create this new one ""common dimension""

It is doing what is called ""orthogonal indexing"", but with interpolation. The resulting shape of the output is then (2, 2, 2) in your case, but could be any (t, y, x) as given by the size of each dimension indexer. 

Maybe this helps a little: http://xarray.pydata.org/en/stable/indexing.html#vectorized-indexing","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,444367776
https://github.com/pydata/xarray/issues/2962#issuecomment-492612763,https://api.github.com/repos/pydata/xarray/issues/2962,492612763,MDEyOklzc3VlQ29tbWVudDQ5MjYxMjc2Mw==,10050469,2019-05-15T11:17:05Z,2019-05-15T11:17:05Z,MEMBER,"Yes, it is possible. It is a bit ""less intuitive"" at first sight, but powerful and documented here: http://xarray.pydata.org/en/stable/interpolation.html#advanced-interpolation

The call you need to make is:

```python
blah.interp(longitude=('z', lon), latitude=('z', lat))
```","{""total_count"": 2, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 1, ""eyes"": 0}",,444367776