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
859065068,MDU6SXNzdWU4NTkwNjUwNjg=,5164,Xarray unable to read file that netCDF4 can,31640292,open,0,,,5,2021-04-15T16:45:24Z,2023-09-16T15:59:34Z,,CONTRIBUTOR,,,,"<!-- 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 reading files from https://www-air.larc.nasa.gov/pub/NDACC/PUBLIC/stations/mauna.loa.hi/hdf/lidar/.

When passed to `xr.open_dataset`, the following error occurs

```python
---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
<ipython-input-36-895975874f7f> in <module>
----> 1 xr.open_dataset(
      2     ""/users/bmward/groundbased_lidar.temperature_nasa.jpl002_glass.1.1_mauna.loa.hi_20200103t050130z_20200103t072420z_001.h4"",
      3     engine=""netcdf4"",
      4 )

~/.conda/envs/bg-dev/lib/python3.9/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)

~/.conda/envs/bg-dev/lib/python3.9/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,

~/.conda/envs/bg-dev/lib/python3.9/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

~/.conda/envs/bg-dev/lib/python3.9/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())

~/.conda/envs/bg-dev/lib/python3.9/site-packages/xarray/backends/netCDF4_.py in get_variables(self)
    417 
    418     def get_variables(self):
--> 419         dsvars = FrozenDict(
    420             (k, self.open_store_variable(k, v)) for k, v in self.ds.variables.items()
    421         )

~/.conda/envs/bg-dev/lib/python3.9/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 

~/.conda/envs/bg-dev/lib/python3.9/site-packages/xarray/backends/netCDF4_.py in <genexpr>(.0)
    418     def get_variables(self):
    419         dsvars = FrozenDict(
--> 420             (k, self.open_store_variable(k, v)) for k, v in self.ds.variables.items()
    421         )
    422         return dsvars

~/.conda/envs/bg-dev/lib/python3.9/site-packages/xarray/backends/netCDF4_.py in open_store_variable(self, name, var)
    394         # netCDF4 specific encoding; save _FillValue for later
    395         encoding = {}
--> 396         filters = var.filters()
    397         if filters is not None:
    398             encoding.update(filters)

src/netCDF4/_netCDF4.pyx in netCDF4._netCDF4.Variable.filters()

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

RuntimeError: NetCDF: Attempting netcdf-4 operation on netcdf-3 file
```

However, 
```python
import netCDF4
netCDF4.Dataset(
    ""/users/bmward/groundbased_lidar.temperature_nasa.jpl002_glass.1.1_mauna.loa.hi_20200103t050130z_20200103t072420z_001.hdf"",
)
```
Does not produce any errors

**What you expected to happen**:

I expect that xarray be able to load the file

**Minimal Complete Verifiable Example**:

```python
import xarray
xr.open_dataset(
    ""groundbased_lidar.temperature_nasa.jpl002_glass.1.1_mauna.loa.hi_20200103t050130z_20200103t072420z_001.hdf"",
    engine=""netcdf4"",
)
```

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

Changing the engine to `h5netcdf` produces a different error, but still fails.

Setting `decode_cf=False` has no effect.

**Environment**:

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


INSTALLED VERSIONS
------------------
commit: None
python: 3.9.1 | packaged by conda-forge | (default, Jan 26 2021, 01:34:10) 
[GCC 9.3.0]
python-bits: 64
OS: Linux
OS-release: 3.10.0-1160.11.1.el7.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None
libhdf5: 1.10.6
libnetcdf: 4.7.4

xarray: 0.17.0
pandas: 1.2.3
numpy: 1.20.1
scipy: 1.6.2
netCDF4: 1.5.6
pydap: None
h5netcdf: 0.10.0
h5py: 3.1.0
Nio: None
zarr: None
cftime: 1.4.1
nc_time_axis: None
PseudoNetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: None
dask: 2021.03.1
distributed: 2021.03.1
matplotlib: 3.3.4
cartopy: 0.18.0
seaborn: None
numbagg: None
pint: 0.17
setuptools: 49.6.0.post20210108
pip: 21.0.1
conda: None
pytest: None
IPython: 7.22.0
sphinx: 3.5.3



</details>
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816016031,MDU6SXNzdWU4MTYwMTYwMzE=,4955,set_index does not respect keep_attrs,31640292,closed,0,,,2,2021-02-25T02:22:05Z,2022-03-17T17:11:41Z,2022-03-17T17:11:41Z,CONTRIBUTOR,,,,"
**What happened**: set_index removes attributes from a coordinate, even with `xr.set_options(keep_attrs=True)`

**What you expected to happen**: The attributes to be preserved through the coordinate renaming

**Minimal Complete Verifiable Example**:

```python
import xarray as xr
xr.set_options(keep_attrs=True)
x = xr.DataArray([1,2], dims=['x'])
x.coords['x'] = (['x'],[2,3], {""name"":""coord_1""})
x.coords['a'] = (['x'],[0,1], {""name"":""coord 2""})
x.set_index(x='a').x.attrs # should be {""name"":""coord 2""}, is {}
```

**Environment**:

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

INSTALLED VERSIONS
------------------
commit: None
python: 3.8.5 | packaged by conda-forge | (default, Sep 24 2020, 16:55:52) 
[GCC 7.5.0]
python-bits: 64
OS: Linux
OS-release: 3.10.0-1160.11.1.el7.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en.UTF-8
LOCALE: None.None
libhdf5: 1.10.6
libnetcdf: 4.7.4

xarray: 0.16.2
pandas: 1.2.0
numpy: 1.19.1
scipy: 1.6.0
netCDF4: 1.5.5.1
pydap: None
h5netcdf: 0.8.1
h5py: 3.1.0
Nio: None
zarr: None
cftime: 1.3.1
nc_time_axis: 1.2.0
PseudoNetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: 1.3.2
dask: 2021.01.0
distributed: 2021.01.0
matplotlib: 3.3.3
cartopy: 0.18.0
seaborn: 0.11.1
numbagg: None
pint: 0.16.1
setuptools: 49.6.0.post20210108
pip: 20.2.3
conda: None
pytest: None
IPython: 7.18.1
sphinx: 3.4.3


</details>
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4955/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue
741200389,MDU6SXNzdWU3NDEyMDAzODk=,4575,FacetGrid.set_title should allow more extensive formatting,31640292,open,0,,,2,2020-11-12T01:41:32Z,2021-07-04T01:26:35Z,,CONTRIBUTOR,,,,"**Is your feature request related to a problem? Please describe.**
I've been using facetgrids fairly extensively with data that is a numpy.float32. 

Using set_title does not lead to properly formatted results, as this dtype does not match isinstance(x, (float, np.float_)), so it is cast directly to a string leading to labels that are often incredibly unreadable.

**Describe the solution you'd like**
Do not use the format_item in the facetgrid.set_titles function for non-datetime values, but instead allow arguments of the form ""{value:0.4f}"" etc

**Describe alternatives you've considered**
The alternative is that format_item should be loser on it's isinstance checks, in particular allowing other precisions of float to be formatted. Ideally, both of these could be implemented in tandem
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4575/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue
915168227,MDU6SXNzdWU5MTUxNjgyMjc=,5453,"Notion of ""distance"" or ""scale"" for indexes and selection",31640292,open,0,,,0,2021-06-08T15:19:52Z,2021-06-08T15:27:58Z,,CONTRIBUTOR,,,,"**Is your feature request related to a problem? Please describe.**

I've been using xarray with atmospheric data given on pressure levels. This data is best thought of in log(pressure) for computation, but it is stored and displayed as standard numbers. I would love if there was some way to have `data.sel(lev=4, method='nearest')` return the nearest data in log-space without having to have my index stored in the log space. 

E.g, currently
```python
>>> a = xr.DataArray(['a', 'b', 'c'], dims='lev', coords=[('lev', [0.1, 10, 100])])
>>> a.sel(lev=2, method='nearest')
<xarray.DataArray ()>
array('a', dtype='<U1')
Coordinates:
    lev      float64 0.1
```
but in the scientific sense underlying this data, the closer point was actually 'b' at 10, not 'a' at 0.1.

In general, one can imagine situations where the opposite is true (storing data in log-space for numerical accuracy, but wanting a concept of 'nearest' which is the standard linear sense), or a desire for arbitrary scaling.

**Describe the solution you'd like**
The simplest solution I can imagine is to provide a preprocessor argument to the sel function which operates over numpy values and is used before the call to `get_loc`. 

e.g.
```python
>>> a.sel(lev=2, method='nearest', pre=np.log)
<xarray.DataArray ()>
array('b', dtype='<U1')
Coordinates:
    lev      float64 10.0
```

I believe this can be implemented by wrapping both index and label_value here with a call to the preprocess function (assuming the argument is only desired alongside the 'method' kwarg): https://github.com/pydata/xarray/blob/9daf9b13648c9a02bddee3640b80fe95ea1fff61/xarray/core/indexes.py#L224-L226

**Describe alternatives you've considered**
I'm not sure how this would relate to the ongoing work on #1603, but one solution is to include a concept of the underlying number line within the index api. The end result is similar to the proposed implementation, but it would be stored with the index rather than passed to the `sel` method each time. This may keep the `sel` api simpler if this feature was only available for a special ScaledIndex class or something like that.

One version of this could also be used to set reasonable defaults when plotting, e.g. if a coordinate has a log numberline then it could set the x/yscale to 'log' by default when plotting over that coordinate. 

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