issue_comments: 1432943981

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https://github.com/pydata/xarray/issues/7039#issuecomment-1432943981 https://api.github.com/repos/pydata/xarray/issues/7039 1432943981 IC_kwDOAMm_X85VaP1t 60435591 2023-02-16T11:29:45Z 2023-02-16T11:29:45Z CONTRIBUTOR

I have also encountered an issue with reading of ERA5 data with open_mfdatset, writing it to_netcdf() and reading it again (https://github.com/Deltares/dfm_tools/issues/239). I was actually looking for a place to land this, and found your issue.

My expectation is that this is because the ERA5 data is saved as ints, but all files have different offsets/scalingfactors. Upon opening it with open_mfdataset(), the data is converted to floats and to the offset/scalingfactor of the first file. This is fine, but the issue occurs I think (and what you also mention) since {'dtype': 'int16'} is in the encoding. The file is written as ints and this seems to mess up the data. (all a theory)

A workaround is to remove the dtype from the encoding for all variables in the file (or update to float32), but that seems cumbersome. 

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