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/5023#issuecomment-828683287,https://api.github.com/repos/pydata/xarray/issues/5023,828683287,MDEyOklzc3VlQ29tbWVudDgyODY4MzI4Nw==,7237617,2021-04-28T18:30:46Z,2021-04-28T18:30:46Z,NONE,"Thanks @dcherian 
```
>> ds = xr.open_mfdataset(NCs_urls, engine='netcdf4', 
                       parallel=True, 
                       concat_dim='XTIME',
                      )

ValueError: Could not find any dimension coordinates to use to order the datasets for concatenation
```

So it doesn't work, but perhaps that's not surprising give that 'XTIME' is a coordinate, but 'Time' is the dimension (one of WRF's quirks related to staggered grids and moving nests).  

```
>> print(ds.coords)

Coordinates:
    XLAT     (Time, south_north, west_east) float32 dask.array<chunksize=(8, 1035, 675), meta=np.ndarray>
    XLONG    (Time, south_north, west_east) float32 dask.array<chunksize=(8, 1035, 675), meta=np.ndarray>
    XTIME    (Time) datetime64[ns] dask.array<chunksize=(8,), meta=np.ndarray>
    XLAT_U   (Time, south_north, west_east_stag) float32 dask.array<chunksize=(8, 1035, 676), meta=np.ndarray>
    XLONG_U  (Time, south_north, west_east_stag) float32 dask.array<chunksize=(8, 1035, 676), meta=np.ndarray>
    XLAT_V   (Time, south_north_stag, west_east) float32 dask.array<chunksize=(8, 1036, 675), meta=np.ndarray>
    XLONG_V  (Time, south_north_stag, west_east) float32 dask.array<chunksize=(8, 1036, 675), meta=np.ndarray>
```

As such, I'm following the documentation to add a preprocessor `ds.swap_dims({'Time':'XTIME'})`, which works as expected.  

Thanks for everyone's help! Shall I close this? (as it was never actually an _issue_?


","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,829426650
https://github.com/pydata/xarray/issues/5023#issuecomment-812278389,https://api.github.com/repos/pydata/xarray/issues/5023,812278389,MDEyOklzc3VlQ29tbWVudDgxMjI3ODM4OQ==,7237617,2021-04-02T02:14:19Z,2021-04-02T02:14:19Z,NONE,"Thanks for the great suggestion @shoyer - your suggestion to loop through the netCDF files is working well in Dask using the following code:

```
import xarray as xr
import gcsfs
from tqdm.autonotebook import tqdm
xr.set_options(display_style=""html"");

fs = gcsfs.GCSFileSystem(project='ldeo-glaciology', mode='r',cache_timeout = 0)
NCs = fs.glob('gs://ldeo-glaciology/AMPS/WRF_24/domain_02/*.nc')
url = 'gs://' + NCs[0]
openfile = fs.open(url, mode='rb') 
ds = xr.open_dataset(openfile, engine='h5netcdf',chunks={'Time': -1})
for i in tqdm(range(1, 8)):
    url = 'gs://' + NCs[i]
    openfile = fs.open(url, mode='rb') 
    temp = xr.open_dataset(openfile, engine='h5netcdf',chunks={'Time': -1})
    ds = xr.concat([ds,temp],'Time')
```

However, I am still confused why `open_mfdataset` was not parsing the `Time` dimension - the concatenated DataSet using the looping method above appears to have a time dimension compatible with datetime64[ns].

```
>> ds.coords['XTIME'].compute()

xarray.DataArray'XTIME'Time: 8
array(['2019-01-01T03:00:00.000000000', '2019-01-01T06:00:00.000000000',
       '2019-01-01T09:00:00.000000000', '2019-01-01T12:00:00.000000000',
       '2019-01-01T15:00:00.000000000', '2019-01-01T18:00:00.000000000',
       '2019-01-01T21:00:00.000000000', '2019-01-02T00:00:00.000000000'],
      dtype='datetime64[ns]')
```

","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,829426650