html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/issues/531#issuecomment-131214583,https://api.github.com/repos/pydata/xarray/issues/531,131214583,MDEyOklzc3VlQ29tbWVudDEzMTIxNDU4Mw==,4992424,2015-08-14T19:26:18Z,2015-08-14T19:26:18Z,NONE,"Hi @jsbj,

The fancy indexing notation you're trying to use only works when xray successfully decodes the time dimension. As discussed in the documentation [here](http://xray.readthedocs.org/en/stable/time-series.html#creating-datetime64-data), this only works when the year of record falls between 1678 and 2262. Since you have years 2262-2300 in your dataset, this is a feature - xray is failing gracefully.

There are a few current open discussions on this behavior, which is an issue higher up the python chain with numpy:
1. [time decoding error with ""days since""](https://github.com/xray/xray/issues/521)
2. [Fix datetime decoding when time units are 'days since 0000-01-01 00:00:00'](https://github.com/xray/xray/pull/522)
3. [ocefpaf - Loading non-standard dates with cf_units](https://ocefpaf.github.io/python4oceanographers/blog/2015/08/10/cf_units_and_time/)
4. [numpy - Non-standard Calendar Support](https://github.com/numpy/numpy/issues/6207)

For now, a very simple hack would be to re-compute your time units so that they're re-based, say, with units 'days since 1700-01-01 00:00:00'. That way all of them would fit within the permissible range to use the decoding routine built into xray. You could simply pass the **decode_cf=False** flag when you open the dataset, modify the non-decoded time array and units, then run **xray.decode_cf()** on the modified dataset.
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