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  • almost-equal grids · 2 ✖

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id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
192357422 https://github.com/pydata/xarray/issues/784#issuecomment-192357422 https://api.github.com/repos/pydata/xarray/issues/784 MDEyOklzc3VlQ29tbWVudDE5MjM1NzQyMg== darothen 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. 

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   almost-equal grids 138443211
192332830 https://github.com/pydata/xarray/issues/784#issuecomment-192332830 https://api.github.com/repos/pydata/xarray/issues/784 MDEyOklzc3VlQ29tbWVudDE5MjMzMjgzMA== darothen 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.

 
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   almost-equal grids 138443211

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