issue_comments: 1078904879

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https://github.com/pydata/xarray/issues/6412#issuecomment-1078904879 https://api.github.com/repos/pydata/xarray/issues/6412 1078904879 IC_kwDOAMm_X85ATsgv 6628425 2022-03-25T10:59:49Z 2022-03-25T10:59:49Z MEMBER

This is a common point of confusion, but is in fact expected. Xarray intentionally converts any np.datetime64 type to np.datetime64[ns]. The primary motivation is compatibility with pandas, which xarray relies on for time indexing and other time-related operations through things like pandas.DatetimeIndex or the pandas.Series.dt accessor (see, e.g., discussion in https://github.com/pydata/xarray/issues/789).

May I ask what your reason is for requiring a lower-precision datetime type? In xarray we have tried to provide alternatives (e.g. through cftime) for use-cases like longer date ranges.

 
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