# Regridding of unstructured data (climate model)

**URL:** <https://discourse.pangeo.io/t/regridding-of-unstructured-data-climate-model/2300>\
**Category:** CMIP6 Hackathon\
**Created:** [March 10, 2022, 7:05pm UTC](https://discourse.pangeo.io/t/regridding-of-unstructured-data-climate-model/2300 "2022-03-10T19:05:38Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![Ahmed](https://avatars.discourse-cdn.com/v4/letter/a/8c91f0/32.png) [@Ahmed](https://discourse.pangeo.io/u/Ahmed)\
**Post date:** [March 10, 2022, 7:05pm UTC](https://discourse.pangeo.io/t/regridding-of-unstructured-data-climate-model/2300/1 "2022-03-10T19:05:38Z")

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I work with climate models from CMIP6 and I have to interpolate/re-grid them. The problem is that the data are unstructured in the shape of: msftmz(time, basin, latitude, level). I was able to interpolate the level (depth) using CDO, however for the latitude this way is not possible. I have also tried to work with scipy and CDK.Tree from scipy but it also did not work.

I have a specific model (target), which has regular latitude values, and I need to find a way to make all other models (sources) have the same latitude values. Could someone help me with an idea/advice on how I can accomplish this complicated regridding task?

Thanks!  
The screenshot contains information about one of the models.

 ![Screenshot 2022-03-11 152522](https://canada1.discourse-cdn.com/flex030/uploads/pangeo/original/2X/6/6608e92e0d5ccf54545746f6aebe9ece8130e517.png)

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**Author:** ![aaronspring](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.pangeo.io/aaronspring/32/188_2.png) [@aaronspring](https://discourse.pangeo.io/u/aaronspring)\
**Post date:** [March 10, 2022, 8:17pm UTC](https://discourse.pangeo.io/t/regridding-of-unstructured-data-climate-model/2300/2 "2022-03-10T20:17:30Z")

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I tried xesmf on unstructured output, see [unstructured grids · Issue #115 · pangeo-data/xESMF · GitHub](https://github.com/pangeo-data/xESMF/issues/115) however the spatial dimension were ncells