issue_comments: 879561954

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https://github.com/pydata/xarray/issues/5597#issuecomment-879561954 https://api.github.com/repos/pydata/xarray/issues/5597 879561954 MDEyOklzc3VlQ29tbWVudDg3OTU2MTk1NA== 1217238 2021-07-14T03:43:37Z 2021-07-14T03:44:00Z MEMBER

Thanks for sharing the subset netCDF file, that is very helpful for debugging indeed!

The weird thing is that the dtype picking logic seems to have a special case that, per the code comment, suggesting we want to be using float64 here: https://github.com/pydata/xarray/blob/eea76733770be03e78a0834803291659136bca31/xarray/coding/variables.py#L231-L238

But in fact, the dtype picking logic doesn't do that, because the dtype is already converted into float32, first. The culprit seems to be this line in CFMaskCoder, which promotes the dtype to float32 to fit a fill-value of NaN: https://github.com/pydata/xarray/blob/eea76733770be03e78a0834803291659136bca31/xarray/coding/variables.py#L202

To fix this, I think logic in _choose_float_dtype should be updated to look at encoding['dtype'] (if available) instead of dtype, in order to understand how the data was originally stored.

 
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