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/2233#issuecomment-1066784566,https://api.github.com/repos/pydata/xarray/issues/2233,1066784566,IC_kwDOAMm_X84_ldc2,5797727,2022-03-14T13:27:00Z,2022-03-14T13:30:24Z,NONE,"Hi

For now, I found a workaround loading and renaming the problematic coordinates with `netCDF4.Dataset()`.
Soon I will post this and other solutions for this model output in [iuryt/FVCOMpy](https://github.com/iuryt/FVCOMpy).

For now, you could try:
```
import xarray as xr
from netCDF4 import Dataset

# define year and month to be read
year = 2019
month = 5
# we could use this to run a loop through the years/months we need


# list problematic coordinates
drop_variables = ['siglay','siglev']

# base url for openDAP server
url = """".join([""http://www.smast.umassd.edu:8080/thredds/dodsC/models/fvcom/"",
        f""NECOFS/Archive/NECOFS_GOM/{year}/gom4_{year}{month:02d}.nc?""])

# lazy load of the data
ds = xr.open_dataset(url,drop_variables=drop_variables,decode_times=False)

# load data with netCDF4
nc = Dataset(url)
# load the problematic coordinates
coords = {name:nc[name] for name in drop_variables}
# function to extract ncattrs from `Dataset()`
get_attrs = lambda name: {attr:coords[name].getncattr(attr) for attr in coords[name].ncattrs()}
# function to convert from `Dataset()` to `xr.DataArray()`
nc2xr = lambda name: xr.DataArray(coords[name],attrs=get_attrs(name),name=f'{name}_coord',dims=(f'{name}','node'))
# merge `xr.DataArray()` objects
coords = xr.merge([nc2xr(name) for name in coords.keys()])
# reassign to the main `xr.Dataset()`
ds = ds.assign_coords(coords)
```

Leaving it here in case someone fall into the same problem.","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,332471780