issues opening GFS archive

Thanks for this packages. I tried this today but couldn't open a file. I'm able to open it use `xr.open_dataset` and i'm not sure if intake-thredds wants the data to be in a certain format.

I'm reading in archive GFS forecast (https://rda.ucar.edu/datasets/ds084.1/#!description). Note you will have to get a log in to access it (https://stackoverflow.com/questions/66178846/read-in-authorized-opendap-url-using-xarray)

```
url = "https://rda.ucar.edu/thredds/dodsC/files/g/ds084.1/2020/20200201/gfs.0p25.2020020100.f000.grib2"
ds = xr.open_mfdataset([url])
```

vs

```
cat_url = "https://rda.ucar.edu/thredds/catalog/files/g/ds084.1/2020/20200201/catalog.xml"
catalog = intake.open_thredds_cat(cat_url, name="GFS-catalog")
file = list(catalog)[0]
source = catalog[file]
ds = source().to_dask()

---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
in
----> 1 ds = source().to_dask()
2 ds

~/miniconda/envs/main/lib/python3.8/site-packages/intake_xarray/base.py in to_dask(self)
67 def to_dask(self):
68 """Return xarray object where variables are dask arrays"""
---> 69 return self.read_chunked()
70
71 def close(self):

~/miniconda/envs/main/lib/python3.8/site-packages/intake_xarray/base.py in read_chunked(self)
42 def read_chunked(self):
43 """Return xarray object (which will have chunks)"""
---> 44 self._load_metadata()
45 return self._ds
46

~/miniconda/envs/main/lib/python3.8/site-packages/intake/source/base.py in _load_metadata(self)
234 """load metadata only if needed"""
235 if self._schema is None:
--> 236 self._schema = self._get_schema()
237 self.dtype = self._schema.dtype
238 self.shape = self._schema.shape

~/miniconda/envs/main/lib/python3.8/site-packages/intake_xarray/base.py in _get_schema(self)
16
17 if self._ds is None:
---> 18 self._open_dataset()
19
20 metadata = {

~/miniconda/envs/main/lib/python3.8/site-packages/intake_xarray/opendap.py in _open_dataset(self)
92 import xarray as xr
93 store = self._get_store()
---> 94 self._ds = xr.open_dataset(store, chunks=self.chunks, **self._kwargs)

~/miniconda/envs/main/lib/python3.8/site-packages/xarray/backends/api.py in open_dataset(filename_or_obj, group, decode_cf, mask_and_scale, decode_times, concat_characters, decode_coords, engine, chunks, lock, cache, drop_variables, backend_kwargs, use_cftime, decode_timedelta)
555
556 with close_on_error(store):
--> 557 ds = maybe_decode_store(store, chunks)
558
559 # Ensure source filename always stored in dataset object (GH issue #2550)

~/miniconda/envs/main/lib/python3.8/site-packages/xarray/backends/api.py in maybe_decode_store(store, chunks)
451
452 def maybe_decode_store(store, chunks):
--> 453 ds = conventions.decode_cf(
454 store,
455 mask_and_scale=mask_and_scale,

~/miniconda/envs/main/lib/python3.8/site-packages/xarray/conventions.py in decode_cf(obj, concat_characters, mask_and_scale, decode_times, decode_coords, drop_variables, use_cftime, decode_timedelta)
637 encoding = obj.encoding
638 elif isinstance(obj, AbstractDataStore):
--> 639 vars, attrs = obj.load()
640 extra_coords = set()
641 close = obj.close

~/miniconda/envs/main/lib/python3.8/site-packages/xarray/backends/common.py in load(self)
111 """
112 variables = FrozenDict(
--> 113 (_decode_variable_name(k), v) for k, v in self.get_variables().items()
114 )
115 attributes = FrozenDict(self.get_attrs())

~/miniconda/envs/main/lib/python3.8/site-packages/xarray/backends/pydap_.py in get_variables(self)
97
98 def get_variables(self):
---> 99 return FrozenDict(
100 (k, self.open_store_variable(self.ds[k])) for k in self.ds.keys()
101 )

~/miniconda/envs/main/lib/python3.8/site-packages/xarray/core/utils.py in FrozenDict(*args, **kwargs)
451
452 def FrozenDict(*args, **kwargs) -> Frozen:
--> 453 return Frozen(dict(*args, **kwargs))
454
455

~/miniconda/envs/main/lib/python3.8/site-packages/xarray/backends/pydap_.py in (.0)
98 def get_variables(self):
99 return FrozenDict(
--> 100 (k, self.open_store_variable(self.ds[k])) for k in self.ds.keys()
101 )
102

~/miniconda/envs/main/lib/python3.8/site-packages/xarray/backends/pydap_.py in open_store_variable(self, var)
94 def open_store_variable(self, var):
95 data = indexing.LazilyOuterIndexedArray(PydapArrayWrapper(var))
---> 96 return Variable(var.dimensions, data, _fix_attributes(var.attributes))
97
98 def get_variables(self):

~/miniconda/envs/main/lib/python3.8/site-packages/xarray/core/variable.py in __init__(self, dims, data, attrs, encoding, fastpath)
340 """
341 self._data = as_compatible_data(data, fastpath=fastpath)
--> 342 self._dims = self._parse_dimensions(dims)
343 self._attrs = None
344 self._encoding = None

~/miniconda/envs/main/lib/python3.8/site-packages/xarray/core/variable.py in _parse_dimensions(self, dims)
601 dims = tuple(dims)
602 if len(dims) != self.ndim:
--> 603 raise ValueError(
604 "dimensions %s must have the same length as the "
605 "number of data dimensions, ndim=%s" % (dims, self.ndim)

ValueError: dimensions ('height_above_ground_layer',) must have the same length as the number of data dimensions, ndim=2
```

Reproduce the failure using the catalog URL and source().to_dask(), then read the intake_xarray/opendap.py traceback path and xarray's pydap backend call that raises the dimension mismatch. Compare it with the working xr.open_mfdataset example; done means the catalog source can open this GFS archive without the ValueError.

Written by the indexing model from the issue text.