id,node_id,number,title,user,state,locked,assignee,milestone,comments,created_at,updated_at,closed_at,author_association,active_lock_reason,draft,pull_request,body,reactions,performed_via_github_app,state_reason,repo,type
1169750048,I_kwDOAMm_X85FuPgg,6360,Multidimensional `interpolate_na()`,5797727,open,0,,,4,2022-03-15T14:27:46Z,2023-09-28T11:51:20Z,,NONE,,,,"### Is your feature request related to a problem?

I think that having a way to run a multidimensional interpolation for filling missing values would be awesome.

The code snippet below create a data and show the problem I am having now. If the data has some orientation, we couldn't simply interpolate dimensions separately.


```python
import xarray as xr
import numpy as np

n = 30
x = xr.DataArray(np.linspace(0,2*np.pi,n),dims=['x'])
y = xr.DataArray(np.linspace(0,2*np.pi,n),dims=['y'])
z = (np.sin(x)*xr.ones_like(y))

mask = xr.DataArray(np.random.randint(0,1+1,(n,n)).astype('bool'),dims=['x','y'])

kw = dict(add_colorbar=False)

fig,ax = plt.subplots(1,3,figsize=(11,3))
z.plot(ax=ax[0],**kw)
z.where(mask).plot(ax=ax[1],**kw)
z.where(mask).interpolate_na('x').plot(ax=ax[2],**kw)
```

![image](https://user-images.githubusercontent.com/5797727/158399309-437aaf06-9cbf-41dc-8668-5ac6b13016b6.png)



I tried to use advanced interpolation for that, but it doesn't look like the best solution.

```python
zs = z.where(mask).stack(k=['x','y'])
zs = zs.where(np.isnan(zs),drop=True)
xi,yi = zs.k.x.drop('k'),zs.k.y.drop('k')
zi = z.interp(x=xi,y=yi)

fig,ax = plt.subplots()
z.where(mask).plot(ax=ax,**kw)
ax.scatter(xi,yi,c=zi,**kw,linewidth=1,edgecolor='k')
```
returns 

![image](https://user-images.githubusercontent.com/5797727/158399255-4fcce6fa-c12d-4745-a99a-0a2b27506573.png)


### Describe the solution you'd like

Simply `z.interpolate_na(['x','y'])`

### Describe alternatives you've considered

I could extract the data to `numpy` and interpolate using `scipy.interpolate.griddata`, but this is not the way `xarray` should work.

### Additional context

_No response_","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6360/reactions"", ""total_count"": 11, ""+1"": 9, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 2}",,,13221727,issue
786347954,MDU6SXNzdWU3ODYzNDc5NTQ=,4814,Error while loading an HDF file,5797727,closed,0,,,2,2021-01-14T21:19:34Z,2023-08-14T08:42:46Z,2021-01-22T19:30:48Z,NONE,,,,"<!-- Please include a self-contained copy-pastable example that generates the issue if possible.

Please be concise with code posted. See guidelines below on how to provide a good bug report:

- Craft Minimal Bug Reports: http://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports
- Minimal Complete Verifiable Examples: https://stackoverflow.com/help/mcve

Bug reports that follow these guidelines are easier to diagnose, and so are often handled much more quickly.
-->

**What happened**:

I am trying to read a HDF file from MODIS satellite product.
Source of the file: https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/61/MOD06_L2/2015/012/MOD06_L2.A2015012.1510.061.2017318235218.hdf

and

`xr.open_dataset('MOD06_L2.A2015012.1510.061.2017318235218.hdf')`

returns

<details><summary>Error log</summary>
<p>

```

---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
~/.local/lib/python3.6/site-packages/xarray/backends/file_manager.py in _acquire_with_cache_info(self, needs_lock)
    198             try:
--> 199                 file = self._cache[self._key]
    200             except KeyError:

~/.local/lib/python3.6/site-packages/xarray/backends/lru_cache.py in __getitem__(self, key)
     52         with self._lock:
---> 53             value = self._cache[key]
     54             self._cache.move_to_end(key)

KeyError: [<class 'netCDF4._netCDF4.Dataset'>, ('/project/umd_amit_tandon/iury/data/coldpools/modis/MOD06_L2/2015/001/MOD06_L2.A2015001.0000.061.2017318203346.hdf',), 'r', (('clobber', True), ('diskless', False), ('format', 'NETCDF4'), ('persist', False))]

During handling of the above exception, another exception occurred:

OSError                                   Traceback (most recent call last)
<ipython-input-3-3a318c45af2b> in <module>()
----> 1 xr.open_dataset(fnames[0])

~/.local/lib/python3.6/site-packages/xarray/backends/api.py in open_dataset(filename_or_obj, group, decode_cf, mask_and_scale, decode_times, autoclose, concat_characters, decode_coords, engine, chunks, lock, cache, drop_variables, backend_kwargs, use_cftime, decode_timedelta)
    507         if engine == ""netcdf4"":
    508             store = backends.NetCDF4DataStore.open(
--> 509                 filename_or_obj, group=group, lock=lock, **backend_kwargs
    510             )
    511         elif engine == ""scipy"":

~/.local/lib/python3.6/site-packages/xarray/backends/netCDF4_.py in open(cls, filename, mode, format, group, clobber, diskless, persist, lock, lock_maker, autoclose)
    356             netCDF4.Dataset, filename, mode=mode, kwargs=kwargs
    357         )
--> 358         return cls(manager, group=group, mode=mode, lock=lock, autoclose=autoclose)
    359 
    360     def _acquire(self, needs_lock=True):

~/.local/lib/python3.6/site-packages/xarray/backends/netCDF4_.py in __init__(self, manager, group, mode, lock, autoclose)
    312         self._group = group
    313         self._mode = mode
--> 314         self.format = self.ds.data_model
    315         self._filename = self.ds.filepath()
    316         self.is_remote = is_remote_uri(self._filename)

~/.local/lib/python3.6/site-packages/xarray/backends/netCDF4_.py in ds(self)
    365     @property
    366     def ds(self):
--> 367         return self._acquire()
    368 
    369     def open_store_variable(self, name, var):

~/.local/lib/python3.6/site-packages/xarray/backends/netCDF4_.py in _acquire(self, needs_lock)
    359 
    360     def _acquire(self, needs_lock=True):
--> 361         with self._manager.acquire_context(needs_lock) as root:
    362             ds = _nc4_require_group(root, self._group, self._mode)
    363         return ds

/opt/conda/lib/python3.6/contextlib.py in __enter__(self)
     79     def __enter__(self):
     80         try:
---> 81             return next(self.gen)
     82         except StopIteration:
     83             raise RuntimeError(""generator didn't yield"") from None

~/.local/lib/python3.6/site-packages/xarray/backends/file_manager.py in acquire_context(self, needs_lock)
    185     def acquire_context(self, needs_lock=True):
    186         """"""Context manager for acquiring a file.""""""
--> 187         file, cached = self._acquire_with_cache_info(needs_lock)
    188         try:
    189             yield file

~/.local/lib/python3.6/site-packages/xarray/backends/file_manager.py in _acquire_with_cache_info(self, needs_lock)
    203                     kwargs = kwargs.copy()
    204                     kwargs[""mode""] = self._mode
--> 205                 file = self._opener(*self._args, **kwargs)
    206                 if self._mode == ""w"":
    207                     # ensure file doesn't get overriden when opened again

netCDF4/_netCDF4.pyx in netCDF4._netCDF4.Dataset.__init__()

netCDF4/_netCDF4.pyx in netCDF4._netCDF4._ensure_nc_success()

OSError: [Errno -51] NetCDF: Unknown file format: b'/project/umd_amit_tandon/iury/data/coldpools/modis/MOD06_L2/2015/001/MOD06_L2.A2015001.0000.061.2017318203346.hdf'


```

</p>
</details> 

**What you expected to happen**:

Read the HDF file normally.

**Minimal Complete Verifiable Example**:

Just

`xr.open_dataset('MOD06_L2.A2015012.1510.061.2017318235218.hdf')`

**Anything else we need to know?**:

**Environment**:

<details><summary>Output of <tt>xr.show_versions()</tt></summary>

INSTALLED VERSIONS
------------------
commit: None
python: 3.6.4 |Anaconda, Inc.| (default, Jan 16 2018, 18:10:19) 
[GCC 7.2.0]
python-bits: 64
OS: Linux
OS-release: 2.6.32-754.35.1.el6.x86_64
machine: x86_64
processor: 
byteorder: little
LC_ALL: C.UTF-8
LANG: C.UTF-8
LOCALE: en_US.UTF-8
libhdf5: 1.10.5
libnetcdf: 4.6.3

xarray: 0.16.1
pandas: 1.1.4
numpy: 1.16.4
scipy: 1.2.0
netCDF4: 1.5.4
pydap: None
h5netcdf: 0.8.1
h5py: 2.7.1
Nio: None
zarr: None
cftime: 1.2.1
nc_time_axis: None
PseudoNetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: 1.2.1
dask: 0.16.1
distributed: 1.20.2
matplotlib: 3.2.2
cartopy: None
seaborn: 0.8.1
numbagg: None
pint: None
setuptools: 38.4.0
pip: 20.2.4
conda: 4.4.10
pytest: 3.3.2
IPython: 6.2.1
sphinx: 1.6.6


</details>
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4814/reactions"", ""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue
1592154849,I_kwDOAMm_X85e5lrh,7542,`OSError: [Errno -70] NetCDF: DAP server error` when `parallel=True` on a cluster,5797727,open,0,,,1,2023-02-20T16:27:11Z,2023-03-20T17:53:39Z,,NONE,,,,"### What is your issue?

Hi,

I am trying to access MERRA-2 dataset using `opendap` links on `xarray`.
The code below is based on a [tutorial](https://daac.gsfc.nasa.gov/information/howto?title=How%20to%20Access%20MERRA-2%20Data%20using%20OPeNDAP%20with%20Python3%20and%20Calculate%20Daily%2FWeekly%2FMonthly%20Statistics%20from%20Hourly%20Data%20) that [@betolink](https://discourse.pangeo.io/u/betolink) sent me as an example.

The code runs well if `parallel=False`, but returns `OSError: [Errno -70] NetCDF: DAP server error` if I set `parallel=True`, no matter if I create the cluster or not.

[@betolink](https://discourse.pangeo.io/u/betolink) suspected that the workers doesn’t know the authentication and suggested me to do something like mentioned in [@rsignell](https://discourse.pangeo.io/u/rsignell) [issue](https://github.com/nebari-dev/nebari/discussions/331).

Which would involve adding `client.register_worker_plugin(UploadFile('~/.netrc'))` after creating the client. I also tested that but returned the same error. In the code below I had to replace `~/.netrc` for the full path because it was returning file not found error.

It is important to say that `parallel=True` works fine on my local computer using Ubuntu by WSL.

Has anyone faced this problem before or has any guesses on how to solve this issue?

```python
# ----------------------------------
# Import Python modules
# ----------------------------------

import warnings

warnings.filterwarnings(""ignore"")

import xarray as xr
import matplotlib.pyplot as plt
from calendar import monthrange

create_cluster = True
parallel = True
upload_file = True

if create_cluster:
    # --------------------------------------
    # Creating 50 workers with 1core and 2Gb each
    # --------------------------------------
    import os
    from dask_jobqueue import SLURMCluster
    from dask.distributed import Client
    from dask.distributed import WorkerPlugin

    class UploadFile(WorkerPlugin):
        """"""A WorkerPlugin to upload a local file to workers.
        Parameters
        ----------
        filepath: str
            A path to the file to upload
        Examples
        --------
        >>> client.register_worker_plugin(UploadFile("".env""))
        """"""
        def __init__(self, filepath):
            """"""
            Initialize the plugin by reading in the data from the given file.
            """"""

            self.filename = os.path.basename(filepath)
            self.dirname = os.path.dirname(filepath)
            with open(filepath, ""rb"") as f:
                self.data = f.read()

        async def setup(self, worker):
            if not os.path.exists(self.dirname):
                os.mkdir(self.dirname)
            os.chdir(self.dirname)
            with open(self.filename, ""wb+"") as f:
                f.write(self.data)
            return os.listdir()
    
    cluster = SLURMCluster(cores=1, memory=""40GB"")
    cluster.scale(jobs=10)

    client = Client(cluster)  # Connect this local process to remote workers
    if upload_file:
        client.register_worker_plugin(UploadFile('/home/isimoesdesousa/.netrc'))


# ---------------------------------
# Read data
# ---------------------------------
# MERRA-2 collection (hourly)
collection_shortname = 'M2T1NXAER'
collection_longname  = 'tavg1_2d_aer_Nx'
collection_number = 'MERRA2_400'  
MERRA2_version = '5.12.4'
year = 2020
    
# Open dataset
# Read selected days in the same month and year
month = 1  # January
day_beg = 1
day_end = 31
    
# Note that collection_number is MERRA2_401 in a few cases, refer to ""Records of MERRA-2 Data Reprocessing and Service Changes""
if year == 2020 and month == 9:
    collection_number = 'MERRA2_401'
            
# OPeNDAP URL 

url = 'https://goldsmr4.gesdisc.eosdis.nasa.gov/opendap/MERRA2/{}.{}/{}/{:0>2d}'.format(collection_shortname, MERRA2_version, year, month)
files_month = ['{}/{}.{}.{}{:0>2d}{:0>2d}.nc4'.format(url,collection_number, collection_longname, year, month, days) for days in range(day_beg,day_end+1,1)]
# Get the number of files
len_files_month=len(files_month)

# Print
print(""{} files to be opened:"".format(len_files_month))
print(""files_month"", files_month)

# Read dataset URLs
ds = xr.open_mfdataset(files_month, parallel=parallel)
   
# View metadata (function like ncdump -c)
ds
```

As this deals with HPCs, I also posted on pangeo forum
https://discourse.pangeo.io/t/access-ges-disc-nasa-dataset-using-xarray-and-dask-on-a-cluster/3195/1","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/7542/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue
1521002414,I_kwDOAMm_X85aqKeu,7422,`plot.scatter` only works for declared arguments,5797727,closed,0,,,2,2023-01-05T16:15:28Z,2023-01-05T22:39:23Z,2023-01-05T22:39:23Z,NONE,,,,"### What happened?


```python
ds.plot.scatter(""x"",""y"")
```

returns:

```python
---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
File /autofs/nas1/home/isimoesdesousa/programs/mambaforge/envs/coringa/lib/python3.9/site-packages/xarray/core/dataset.py:1340, in Dataset._construct_dataarray(self, name)
   1339 try:
-> 1340     variable = self._variables[name]
   1341 except KeyError:

KeyError: None

During handling of the above exception, another exception occurred:

KeyError                                  Traceback (most recent call last)
Cell In[60], line 1
----> 1 ds.plot.scatter(""x"",""y"")

File /autofs/nas1/home/isimoesdesousa/programs/mambaforge/envs/coringa/lib/python3.9/site-packages/xarray/plot/accessor.py:1071, in DatasetPlotAccessor.scatter(self, *args, **kwargs)
   1069 @functools.wraps(dataset_plot.scatter)
   1070 def scatter(self, *args, **kwargs) -> PathCollection | FacetGrid[DataArray]:
-> 1071     return dataset_plot.scatter(self._ds, *args, **kwargs)

File /autofs/nas1/home/isimoesdesousa/programs/mambaforge/envs/coringa/lib/python3.9/site-packages/xarray/plot/dataset_plot.py:914, in scatter(ds, x, y, z, hue, hue_style, markersize, linewidth, figsize, size, aspect, ax, row, col, col_wrap, xincrease, yincrease, add_legend, add_colorbar, add_labels, add_title, subplot_kws, xscale, yscale, xticks, yticks, xlim, ylim, cmap, vmin, vmax, norm, extend, levels, *args, **kwargs)
    912 del locals_[""ds""]
    913 locals_.update(locals_.pop(""kwargs"", {}))
--> 914 da = _temp_dataarray(ds, y, locals_)
    916 return da.plot.scatter(*locals_.pop(""args"", ()), **locals_)

File /autofs/nas1/home/isimoesdesousa/programs/mambaforge/envs/coringa/lib/python3.9/site-packages/xarray/plot/dataset_plot.py:740, in _temp_dataarray(ds, y, locals_)
    736         coords[key] = ds[key]
    738 # The dataarray has to include all the dims. Broadcast to that shape
    739 # and add the additional coords:
--> 740 _y = ds[y].broadcast_like(ds)
    742 return DataArray(_y, coords=coords)

File /autofs/nas1/home/isimoesdesousa/programs/mambaforge/envs/coringa/lib/python3.9/site-packages/xarray/core/dataset.py:1431, in Dataset.__getitem__(self, key)
   1429     return self.isel(**key)
   1430 if utils.hashable(key):
-> 1431     return self._construct_dataarray(key)
   1432 if utils.iterable_of_hashable(key):
   1433     return self._copy_listed(key)

File /autofs/nas1/home/isimoesdesousa/programs/mambaforge/envs/coringa/lib/python3.9/site-packages/xarray/core/dataset.py:1342, in Dataset._construct_dataarray(self, name)
   1340     variable = self._variables[name]
   1341 except KeyError:
-> 1342     _, name, variable = _get_virtual_variable(self._variables, name, self.dims)
   1344 needed_dims = set(variable.dims)
   1346 coords: dict[Hashable, Variable] = {}

File /autofs/nas1/home/isimoesdesousa/programs/mambaforge/envs/coringa/lib/python3.9/site-packages/xarray/core/dataset.py:174, in _get_virtual_variable(variables, key, dim_sizes)
    171     return key, key, variable
    173 if not isinstance(key, str):
--> 174     raise KeyError(key)
    176 split_key = key.split(""."", 1)
    177 if len(split_key) != 2:

KeyError: None
```

### What did you expect to happen?

To plot the figure:

![image](https://user-images.githubusercontent.com/5797727/210827438-d784828d-2496-427e-8485-9471d3ee5e6c.png)


### Minimal Complete Verifiable Example

```Python
import pandas as pd

n = 1000
df = pd.DataFrame()
df[""x""] = np.random.randn(n)
df[""y""] = np.random.randn(n)
ds = df.to_xarray()

#this works
ds.plot.scatter(x=""x"",y=""y"")

#this doesn't work
ds.plot.scatter(""x"",""y"")
```


### MVCE confirmation

- [x] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
- [X] Complete example — the example is self-contained, including all data and the text of any traceback.
- [X] Verifiable example — the example copy & pastes into an IPython prompt or [Binder notebook](https://mybinder.org/v2/gh/pydata/xarray/main?urlpath=lab/tree/doc/examples/blank_template.ipynb), returning the result.
- [X] New issue — a search of GitHub Issues suggests this is not a duplicate.

### Relevant log output

_No response_

### Anything else we need to know?

_No response_

### Environment

<details>
NSTALLED VERSIONS
------------------
commit: None
python: 3.9.15 | packaged by conda-forge | (main, Nov 22 2022, 15:55:03) 
[GCC 10.4.0]
python-bits: 64
OS: Linux
OS-release: 5.15.0-50-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: ('en_US', 'UTF-8')
libhdf5: 1.12.2
libnetcdf: 4.8.1

xarray: 2022.12.0
pandas: 1.5.2
numpy: 1.24.0
scipy: 1.9.3
netCDF4: 1.6.2
pydap: None
h5netcdf: None
h5py: None
Nio: None
zarr: None
cftime: 1.6.2
nc_time_axis: None
PseudoNetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: 1.3.5
dask: 2022.12.1
distributed: 2022.12.1
matplotlib: 3.6.2
cartopy: None
seaborn: None
numbagg: None
fsspec: 2022.11.0
cupy: None
pint: None
sparse: None
flox: None
numpy_groupies: None
setuptools: 65.6.3
pip: 22.3.1
conda: None
pytest: None
mypy: None
IPython: 8.7.0
sphinx: None


</details>
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/7422/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue
1340669247,I_kwDOAMm_X85P6P0_,6922,Support for matplotlib mosaic using variable names,5797727,open,0,,,1,2022-08-16T17:31:23Z,2022-08-17T05:35:39Z,,NONE,,,,"### Is your feature request related to a problem?

This is not related to any problem, but I think it would be nice to have a support for giving a `matplotlib` `mosaic` with the keys for the variables you want to plot for different panels and `xarray` parse that into the figure.

### Describe the solution you'd like

Something like

```python
import matplotlib.pyplot as plt
import xarray as xr
import numpy as np

n = 200
t = np.linspace(0,3*2*np.pi,n)
ds = xr.Dataset({letter:((""s"",""t""),np.sin(t)+0.5*np.random.randn(3,n)) for letter in ""A B C D E"".split()})
ds = ds.assign_coords(t=t,s=range(3))

mosaic = [
    [""A"",""A"",""B"",""B"",""C"",""C""],
    [""X"",""D"",""D"",""E"",""E"",""X""],
]

kw = dict(x=""t"",hue=""s"",add_legend=False)
ds.plot.line(mosaic=mosaic,empty_sentinel=""X"",**kw)



```
![image](https://user-images.githubusercontent.com/5797727/184942015-edaa11fe-8823-4de3-bf88-397d788a629a.png)
### Describe alternatives you've considered

I have a code snippet that generate similar results but with more code.

```python
import matplotlib.pyplot as plt
import xarray as xr
import numpy as np

n = 200
t = np.linspace(0,3*2*np.pi,n)
ds = xr.Dataset({letter:((""s"",""t""),np.sin(t)+0.5*np.random.randn(3,n)) for letter in ""A B C D E"".split()})
ds = ds.assign_coords(t=t,s=range(3))


mosaic = [
    [""A"",""A"",""B"",""B"",""C"",""C""],
    [""X"",""D"",""D"",""E"",""E"",""X""],
]

kw = dict(x=""t"",hue=""s"",add_legend=False)
fig = plt.figure(constrained_layout=True,figsize=(8,4))
ax = fig.subplot_mosaic(mosaic,empty_sentinel=""X"")
for key in ds:
    ds[key].plot.line(ax=ax[key],**kw)
```

![image](https://user-images.githubusercontent.com/5797727/184942015-edaa11fe-8823-4de3-bf88-397d788a629a.png)


### Additional context

_No response_","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6922/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue
905452377,MDU6SXNzdWU5MDU0NTIzNzc=,5395,"ValueError: unrecognized engine zarr must be one of: ['netcdf4', 'scipy', 'store']",5797727,closed,0,,,6,2021-05-28T13:53:38Z,2021-12-07T19:44:04Z,2021-05-28T15:09:30Z,NONE,,,,"<!-- Please include a self-contained copy-pastable example that generates the issue if possible.

Please be concise with code posted. See guidelines below on how to provide a good bug report:

- Craft Minimal Bug Reports: http://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports
- Minimal Complete Verifiable Examples: https://stackoverflow.com/help/mcve

Bug reports that follow these guidelines are easier to diagnose, and so are often handled much more quickly.
-->

Hi,

I am trying to load MUR data from AWS on Google Colab just as Chelle did for her Pangeo tutorial.
https://github.com/pangeo-gallery/osm2020tutorial/blob/master/AWS-notebooks/aws_mur_sst_tutorial_long.ipynb

**What happened**:

```python
---------------------------------------------------------------------------

ValueError                                Traceback (most recent call last)

<ipython-input-15-363886c4b27b> in <module>()
      1 import xarray as xr
      2 
----> 3 ds = xr.open_zarr('https://mur-sst.s3.us-west-2.amazonaws.com/zarr-v1',consolidated=True)

2 frames

/usr/local/lib/python3.7/dist-packages/xarray/backends/plugins.py in get_backend(engine)
    133         if engine not in engines:
    134             raise ValueError(
--> 135                 f""unrecognized engine {engine} must be one of: {list(engines)}""
    136             )
    137         backend = engines[engine]

ValueError: unrecognized engine zarr must be one of: ['netcdf4', 'scipy', 'store']
```

**What you expected to happen**:

Load Zarr data from S3.

**Minimal Complete Verifiable Example**:

```python
import xarray as xr
ds = xr.open_zarr('https://mur-sst.s3.us-west-2.amazonaws.com/zarr-v1',consolidated=True)
```

**Anything else we need to know?**:

I am using Google Colab.

**Environment**:

<details><summary>Output of <tt>xr.show_versions()</tt></summary>

INSTALLED VERSIONS
------------------
commit: None
python: 3.7.10 (default, May  3 2021, 02:48:31) 
[GCC 7.5.0]
python-bits: 64
OS: Linux
OS-release: 5.4.109+
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: ('en_US', 'UTF-8')
libhdf5: 1.12.0
libnetcdf: 4.7.4

xarray: 0.18.2
pandas: 1.1.5
numpy: 1.19.5
scipy: 1.4.1
netCDF4: 1.5.6
pydap: None
h5netcdf: None
h5py: 3.1.0
Nio: None
zarr: 2.8.3
cftime: 1.5.0
nc_time_axis: None
PseudoNetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: 1.3.2
dask: 2.12.0
distributed: 1.25.3
matplotlib: 3.2.2
cartopy: None
seaborn: 0.11.1
numbagg: None
pint: None
setuptools: 56.1.0
pip: 19.3.1
conda: None
pytest: 3.6.4
IPython: 5.5.0
sphinx: 1.8.5


</details>
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/5395/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue
782848816,MDU6SXNzdWU3ODI4NDg4MTY=,4787,Pass `locator` argument to matplotlib when calling `plot.contourf`,5797727,open,0,,,3,2021-01-10T16:04:26Z,2021-01-11T17:41:52Z,,NONE,,,,"<!-- Please do a quick search of existing issues to make sure that this has not been asked before. -->

**Is your feature request related to a problem? Please describe.**
Everytime I have to do a `contourf` I need to call it from `matplotlib` directly because `locator` argument is not passed from `xarray.plot.contourf` to `matplotlib`.

**Describe the solution you'd like**
Being `ds` a `xarray.DataArray`, I want to have the behaviour described here when passing `locator =  ticker.LogLocator()` to `ds.plot.contourf`.

**Describe alternatives you've considered**
I usually have to do `plt.contourf(ds.dim_0,ds.dim_1,ds.values,locator =  ticker.LogLocator())`.
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4787/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue