KeyError pulling from Nasa server with Pydap

What happened:
I'm trying to pull data from this NASA server: https://hydro1.gesdisc.eosdis.nasa.gov/dods/NLDAS_FORA0125_H.002?. Through pydap, I can create a DataSet representing the data, but when I try to get the data I get this error:

---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
~/my-conda-envs/nwm/lib/python3.7/site-packages/pydap/model.py in _getitem_string(self, key)
    403         try:
--> 404             return self._dict[quote(key)]
    405         except KeyError:

KeyError: 'tmp2m%2Etmp2m'

During handling of the above exception, another exception occurred:

IndexError                                Traceback (most recent call last)
<ipython-input-17-3efbb8f7b71f> in <module>
----> 1 ds['tmp2m'].isel(time=0).values

~/my-conda-envs/nwm/lib/python3.7/site-packages/xarray/core/dataarray.py in values(self)
    632     def values(self) -> np.ndarray:
    633         """The array's data as a numpy.ndarray"""
--> 634         return self.variable.values
    635 
    636     @values.setter

~/my-conda-envs/nwm/lib/python3.7/site-packages/xarray/core/variable.py in values(self)
    552     def values(self):
    553         """The variable's data as a numpy.ndarray"""
--> 554         return _as_array_or_item(self._data)
    555 
    556     @values.setter

~/my-conda-envs/nwm/lib/python3.7/site-packages/xarray/core/variable.py in _as_array_or_item(data)
    285         data = data.get()
    286     else:
--> 287         data = np.asarray(data)
    288     if data.ndim == 0:
    289         if data.dtype.kind == "M":

~/my-conda-envs/nwm/lib/python3.7/site-packages/numpy/core/_asarray.py in asarray(a, dtype, order, like)
    100         return _asarray_with_like(a, dtype=dtype, order=order, like=like)
    101 
--> 102     return array(a, dtype, copy=False, order=order)
    103 
    104 

~/my-conda-envs/nwm/lib/python3.7/site-packages/xarray/core/indexing.py in __array__(self, dtype)
    691 
    692     def __array__(self, dtype=None):
--> 693         self._ensure_cached()
    694         return np.asarray(self.array, dtype=dtype)
    695 

~/my-conda-envs/nwm/lib/python3.7/site-packages/xarray/core/indexing.py in _ensure_cached(self)
    688     def _ensure_cached(self):
    689         if not isinstance(self.array, NumpyIndexingAdapter):
--> 690             self.array = NumpyIndexingAdapter(np.asarray(self.array))
    691 
    692     def __array__(self, dtype=None):

~/my-conda-envs/nwm/lib/python3.7/site-packages/numpy/core/_asarray.py in asarray(a, dtype, order, like)
    100         return _asarray_with_like(a, dtype=dtype, order=order, like=like)
    101 
--> 102     return array(a, dtype, copy=False, order=order)
    103 
    104 

~/my-conda-envs/nwm/lib/python3.7/site-packages/xarray/core/indexing.py in __array__(self, dtype)
    661 
    662     def __array__(self, dtype=None):
--> 663         return np.asarray(self.array, dtype=dtype)
    664 
    665     def __getitem__(self, key):

~/my-conda-envs/nwm/lib/python3.7/site-packages/numpy/core/_asarray.py in asarray(a, dtype, order, like)
    100         return _asarray_with_like(a, dtype=dtype, order=order, like=like)
    101 
--> 102     return array(a, dtype, copy=False, order=order)
    103 
    104 

~/my-conda-envs/nwm/lib/python3.7/site-packages/xarray/core/indexing.py in __array__(self, dtype)
    566     def __array__(self, dtype=None):
    567         array = as_indexable(self.array)
--> 568         return np.asarray(array[self.key], dtype=None)
    569 
    570     def transpose(self, order):

~/my-conda-envs/nwm/lib/python3.7/site-packages/xarray/conventions.py in __getitem__(self, key)
     60 
     61     def __getitem__(self, key):
---> 62         return np.asarray(self.array[key], dtype=self.dtype)
     63 
     64 

~/my-conda-envs/nwm/lib/python3.7/site-packages/numpy/core/_asarray.py in asarray(a, dtype, order, like)
    100         return _asarray_with_like(a, dtype=dtype, order=order, like=like)
    101 
--> 102     return array(a, dtype, copy=False, order=order)
    103 
    104 

~/my-conda-envs/nwm/lib/python3.7/site-packages/xarray/coding/variables.py in __array__(self, dtype)
     68 
     69     def __array__(self, dtype=None):
---> 70         return self.func(self.array)
     71 
     72     def __repr__(self):

~/my-conda-envs/nwm/lib/python3.7/site-packages/xarray/coding/variables.py in _apply_mask(data, encoded_fill_values, decoded_fill_value, dtype)
    136 ) -> np.ndarray:
    137     """Mask all matching values in a NumPy arrays."""
--> 138     data = np.asarray(data, dtype=dtype)
    139     condition = False
    140     for fv in encoded_fill_values:

~/my-conda-envs/nwm/lib/python3.7/site-packages/numpy/core/_asarray.py in asarray(a, dtype, order, like)
    100         return _asarray_with_like(a, dtype=dtype, order=order, like=like)
    101 
--> 102     return array(a, dtype, copy=False, order=order)
    103 
    104 

~/my-conda-envs/nwm/lib/python3.7/site-packages/xarray/core/indexing.py in __array__(self, dtype)
    566     def __array__(self, dtype=None):
    567         array = as_indexable(self.array)
--> 568         return np.asarray(array[self.key], dtype=None)
    569 
    570     def transpose(self, order):

~/my-conda-envs/nwm/lib/python3.7/site-packages/xarray/backends/pydap_.py in __getitem__(self, key)
     36     def __getitem__(self, key):
     37         return indexing.explicit_indexing_adapter(
---> 38             key, self.shape, indexing.IndexingSupport.BASIC, self._getitem
     39         )
     40 

~/my-conda-envs/nwm/lib/python3.7/site-packages/xarray/core/indexing.py in explicit_indexing_adapter(key, shape, indexing_support, raw_indexing_method)
    851     """
    852     raw_key, numpy_indices = decompose_indexer(key, shape, indexing_support)
--> 853     result = raw_indexing_method(raw_key.tuple)
    854     if numpy_indices.tuple:
    855         # index the loaded np.ndarray

~/my-conda-envs/nwm/lib/python3.7/site-packages/xarray/backends/pydap_.py in _getitem(self, key)
     43         # downloading coordinate data twice
     44         array = getattr(self.array, "array", self.array)
---> 45         result = robust_getitem(array, key, catch=ValueError)
     46         # in some cases, pydap doesn't squeeze axes automatically like numpy
     47         axis = tuple(n for n, k in enumerate(key) if isinstance(k, integer_types))

~/my-conda-envs/nwm/lib/python3.7/site-packages/xarray/backends/common.py in robust_getitem(array, key, catch, max_retries, initial_delay)
     51     for n in range(max_retries + 1):
     52         try:
---> 53             return array[key]
     54         except catch:
     55             if n == max_retries:

~/my-conda-envs/nwm/lib/python3.7/site-packages/pydap/model.py in __getitem__(self, index)
    318     def __getitem__(self, index):
    319         out = copy.copy(self)
--> 320         out.data = self._get_data_index(index)
    321         return out
    322 

~/my-conda-envs/nwm/lib/python3.7/site-packages/pydap/model.py in _get_data_index(self, index)
    347             return np.vectorize(decode_np_strings)(self._data[index])
    348         else:
--> 349             return self._data[index]
    350 
    351     def _get_data(self):

~/my-conda-envs/nwm/lib/python3.7/site-packages/pydap/handlers/dap.py in __getitem__(self, index)
    147         dataset = build_dataset(dds)
    148         dataset.data = unpack_data(BytesReader(data), dataset)
--> 149         return dataset[self.id].data
    150 
    151     def __len__(self):

~/my-conda-envs/nwm/lib/python3.7/site-packages/pydap/model.py in __getitem__(self, key)
    423     def __getitem__(self, key):
    424         if isinstance(key, string_types):
--> 425             return self._getitem_string(key)
    426         elif (isinstance(key, tuple) and
    427               all(isinstance(name, string_types)

~/my-conda-envs/nwm/lib/python3.7/site-packages/pydap/model.py in _getitem_string(self, key)
    407             if len(splitted) > 1:
    408                 try:
--> 409                     return self[splitted[0]]['.'.join(splitted[1:])]
    410                 except KeyError:
    411                     return self['.'.join(splitted[1:])]

~/my-conda-envs/nwm/lib/python3.7/site-packages/pydap/model.py in __getitem__(self, index)
    318     def __getitem__(self, index):
    319         out = copy.copy(self)
--> 320         out.data = self._get_data_index(index)
    321         return out
    322 

~/my-conda-envs/nwm/lib/python3.7/site-packages/pydap/model.py in _get_data_index(self, index)
    347             return np.vectorize(decode_np_strings)(self._data[index])
    348         else:
--> 349             return self._data[index]
    350 
    351     def _get_data(self):

IndexError: only integers, slices (`:`), ellipsis (`...`), numpy.newaxis (`None`) and integer or boolean arrays are valid indices

What you expected to happen:

I should be able to select the data w/o error.

Minimal Complete Verifiable Example:

(a nasa username and password are required):

from pydap.client import open_url
from pydap.cas.urs import setup_session
import xarray as xr

base_url = "https://hydro1.gesdisc.eosdis.nasa.gov/dods/NLDAS_FORA0125_H.002?"

session = setup_session("USER", "PASSWORD", check_url=base_url)

store = xr.backends.PydapDataStore.open(base_url, session=session)

ds = xr.open_dataset(store)

ds['tmp2m'].isel(time=0, lat=0, lon=0).values

Anything else we need to know?:

Environment:

Start with xarray/backends/pydap_.py and the PydapDataStore.open entry point, then reproduce the provided ds['tmp2m'].isel(time=0, lat=0, lon=0).values example against the NASA URL. Trace the request into the pydap model.py calls shown in the traceback; done means selecting and loading the variable completes without the reported KeyError or IndexError.