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/3627#issuecomment-566077467,https://api.github.com/repos/pydata/xarray/issues/3627,566077467,MDEyOklzc3VlQ29tbWVudDU2NjA3NzQ2Nw==,6628425,2019-12-16T14:11:43Z,2019-12-16T14:11:43Z,MEMBER,"Hmm...I can't seem to reproduce the issue.  Are you sure you are using the latest release of xarray?
```
In [1]: import gcsfs; import xarray as xr

In [2]: gcs = gcsfs.GCSFileSystem(token='anon')

In [3]: mapper = gcs.get_mapper('gs://cmip6/CMIP/NCAR/CESM2/historical/r1i1p1f1/
   ...: Amon/tas/gn/')

In [4]: ds = xr.open_zarr(mapper, consolidated=True)

In [5]: ds.sel(time=slice('1975', '2005'))
Out[5]:
<xarray.Dataset>
Dimensions:    (lat: 192, lon: 288, nbnd: 2, time: 372)
Coordinates:
  * lat        (lat) float64 -90.0 -89.06 -88.12 -87.17 ... 88.12 89.06 90.0
    lat_bnds   (lat, nbnd) float32 dask.array<chunksize=(192, 2), meta=np.ndarray>
  * lon        (lon) float64 0.0 1.25 2.5 3.75 5.0 ... 355.0 356.2 357.5 358.8
    lon_bnds   (lon, nbnd) float32 dask.array<chunksize=(288, 2), meta=np.ndarray>
  * time       (time) object 1975-01-15 12:00:00 ... 2005-12-15 12:00:00
    time_bnds  (time, nbnd) object dask.array<chunksize=(372, 2), meta=np.ndarray>
Dimensions without coordinates: nbnd
Data variables:
    tas        (time, lat, lon) float32 dask.array<chunksize=(300, 192, 288), meta=np.ndarray>
Attributes:
    Conventions:            CF-1.7 CMIP-6.2
    activity_id:            CMIP
    branch_method:          standard
    branch_time_in_child:   674885.0
    branch_time_in_parent:  219000.0
    case_id:                15
    cesm_casename:          b.e21.BHIST.f09_g17.CMIP6-historical.001
    contact:                cesm_cmip6@ucar.edu
    creation_date:          2019-01-16T23:34:05Z
    data_specs_version:     01.00.29
    experiment:             all-forcing simulation of the recent past
    experiment_id:          historical
    external_variables:     areacella
    forcing_index:          1
    frequency:              mon
    further_info_url:       https://furtherinfo.es-doc.org/CMIP6.NCAR.CESM2.h...
    grid:                   native 0.9x1.25 finite volume grid (192x288 latxlon)
    grid_label:             gn
    initialization_index:   1
    institution:            National Center for Atmospheric Research, Climate...
    institution_id:         NCAR
    license:                CMIP6 model data produced by <The National Center...
    mip_era:                CMIP6
    model_doi_url:          https://doi.org/10.5065/D67H1H0V
    nominal_resolution:     100 km
    parent_activity_id:     CMIP
    parent_experiment_id:   piControl
    parent_mip_era:         CMIP6
    parent_source_id:       CESM2
    parent_time_units:      days since 0001-01-01 00:00:00
    parent_variant_label:   r1i1p1f1
    physics_index:          1
    product:                model-output
    realization_index:      1
    realm:                  atmos
    source:                 CESM2 (2017): atmosphere: CAM6 (0.9x1.25 finite v...
    source_id:              CESM2
    source_type:            AOGCM BGC
    sub_experiment:         none
    sub_experiment_id:      none
    table_id:               Amon
    tracking_id:            hdl:21.14100/d9a7225a-49c3-4470-b7ab-a8180926f839
    variable_id:            tas
    variant_info:           CMIP6 20th century experiments (1850-2014) with C...
    variant_label:          r1i1p1f1
    status:                 2019-10-25;created;by nhn2@columbia.edu
```

#### Output of ``xr.show_versions()``
<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.7.3 | packaged by conda-forge | (default, Jul  1 2019, 14:38:56)
[Clang 4.0.1 (tags/RELEASE_401/final)]
python-bits: 64
OS: Darwin
OS-release: 19.0.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8
libhdf5: 1.10.5
libnetcdf: None

xarray: 0.14.1
pandas: 0.25.0
numpy: 1.17.0
scipy: 1.3.1
netCDF4: None
pydap: installed
h5netcdf: 0.7.4
h5py: 2.9.0
Nio: None
zarr: 2.3.2
cftime: 1.0.4.2
nc_time_axis: None
PseudoNetCDF: None
rasterio: 1.0.25
cfgrib: 0.9.7.1
iris: None
bottleneck: 1.2.1
dask: 2.9.0+2.gd0daa5bc
distributed: 2.9.0
matplotlib: 3.1.1
cartopy: None
seaborn: 0.9.0
numbagg: installed
setuptools: 42.0.2.post20191201
pip: 19.2.2
conda: None
pytest: 5.0.1
IPython: 7.10.1
sphinx: None

</details>","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,538380868
https://github.com/pydata/xarray/issues/3627#issuecomment-566070938,https://api.github.com/repos/pydata/xarray/issues/3627,566070938,MDEyOklzc3VlQ29tbWVudDU2NjA3MDkzOA==,6628425,2019-12-16T13:54:27Z,2019-12-16T13:54:27Z,MEMBER,Could you add a few more details to your example above so that I can try reproducing the issue?  I think example values of `df_mon_tas` and `experiment_ids` would be all I need.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,538380868
https://github.com/pydata/xarray/issues/3627#issuecomment-566061443,https://api.github.com/repos/pydata/xarray/issues/3627,566061443,MDEyOklzc3VlQ29tbWVudDU2NjA2MTQ0Mw==,6628425,2019-12-16T13:30:08Z,2019-12-16T13:30:08Z,MEMBER,"Ah yes, there were some changes in the latest version of cftime that we needed to accommodate in xarray (see https://github.com/pydata/xarray/pull/3430).  Try upgrading xarray to version 0.14.1 and I think you should be good:

```
$ conda upgrade -c conda-forge xarray
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,538380868
https://github.com/pydata/xarray/issues/3627#issuecomment-566051958,https://api.github.com/repos/pydata/xarray/issues/3627,566051958,MDEyOklzc3VlQ29tbWVudDU2NjA1MTk1OA==,6628425,2019-12-16T13:03:49Z,2019-12-16T13:05:35Z,MEMBER,"Hi @mikebyrne6 -- it looks like `cftime` is not installed on your system.  Could you try installing that and trying again?  Time-indexing functionality for non-standard calendars through a `CFTimeIndex` is only supported through that.

```
$ conda install -c conda-forge cftime
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,538380868