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/4552#issuecomment-720059537,https://api.github.com/repos/pydata/xarray/issues/4552,720059537,MDEyOklzc3VlQ29tbWVudDcyMDA1OTUzNw==,10194086,2020-11-01T09:28:17Z,2020-11-01T09:28:17Z,MEMBER,I am closing this. Feel free to reopen if you think there more we can do.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,732567105
https://github.com/pydata/xarray/issues/4552#issuecomment-719575453,https://api.github.com/repos/pydata/xarray/issues/4552,719575453,MDEyOklzc3VlQ29tbWVudDcxOTU3NTQ1Mw==,10194086,2020-10-30T14:11:38Z,2020-10-30T14:11:38Z,MEMBER,"I don't really see through. The 

```python-traceback
UFuncTypeError: ufunc 'multiply' did not contain a loop with signature matching types (dtype('<U6'), dtype('<U6')) -> dtype('<U6')
```
error hints at a dtype problem. The `B01:scale_factor = ""0.0001""` has `dtype=<U6` so maybe it fails trying to apply the `scale_factor`. The other error
```python traceback
RuntimeError: NetCDF: Attempting netcdf-4 operation on netcdf-3 file
```
sounds like a netCDF3 file is pretending to be a netCDF4 file. Also `file HLS.S30.T13SDD.2020004.v1.4.hdf` tells me it's a `hdf4` file. I thought netCDF4 files have to be hdf5 (but I am not sure).

To summarize
1. the file is maybe not meant to be opened as a netCDF but with a hdf library
2. the file may have an issue, either with the metadata or in the way the file is saved
3. if 2. and 3. are not the case, there _may_ be a bug in the netCDF4 library (because you also get the error using netCDF4 without xarray) So I am tagging this as upstream issue.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,732567105
https://github.com/pydata/xarray/issues/4552#issuecomment-719083836,https://api.github.com/repos/pydata/xarray/issues/4552,719083836,MDEyOklzc3VlQ29tbWVudDcxOTA4MzgzNg==,4762214,2020-10-29T23:37:54Z,2020-10-29T23:46:40Z,NONE,"thanks for your reply, @mathause !

`xr.open_dataset(f, decode_cf=False)` returns the following traceback with xarray 0.16.1, but providing that keyword in version 0.14.1 seems to have loaded the data but at the cost of some metadata like nodata and coordinates on the axes. But maybe that data isn't structured such that is easily decoded?

```
---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
<ipython-input-34-e087a0866e6e> in <module>
      1 # ds = xr.open_dataset(f.replace('.hdf', '.h4'))
----> 2 ds = xr.open_dataset(f, decode_cf=False)
      3 ds['B01'].values

C:\software\Anaconda3\envs\x-python\lib\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)
    543 
    544     with close_on_error(store):
--> 545         ds = maybe_decode_store(store)
    546 
    547     # Ensure source filename always stored in dataset object (GH issue #2550)

C:\software\Anaconda3\envs\x-python\lib\site-packages\xarray\backends\api.py in maybe_decode_store(store, lock)
    457             drop_variables=drop_variables,
    458             use_cftime=use_cftime,
--> 459             decode_timedelta=decode_timedelta,
    460         )
    461 

C:\software\Anaconda3\envs\x-python\lib\site-packages\xarray\conventions.py in decode_cf(obj, concat_characters, mask_and_scale, decode_times, decode_coords, drop_variables, use_cftime, decode_timedelta)
    580         encoding = obj.encoding
    581     elif isinstance(obj, AbstractDataStore):
--> 582         vars, attrs = obj.load()
    583         extra_coords = set()
    584         file_obj = obj

C:\software\Anaconda3\envs\x-python\lib\site-packages\xarray\backends\common.py in load(self)
    110         """"""
    111         variables = FrozenDict(
--> 112             (_decode_variable_name(k), v) for k, v in self.get_variables().items()
    113         )
    114         attributes = FrozenDict(self.get_attrs())

C:\software\Anaconda3\envs\x-python\lib\site-packages\xarray\backends\netCDF4_.py in get_variables(self)
    398     def get_variables(self):
    399         dsvars = FrozenDict(
--> 400             (k, self.open_store_variable(k, v)) for k, v in self.ds.variables.items()
    401         )
    402         return dsvars

C:\software\Anaconda3\envs\x-python\lib\site-packages\xarray\core\utils.py in FrozenDict(*args, **kwargs)
    440 
    441 def FrozenDict(*args, **kwargs) -> Frozen:
--> 442     return Frozen(dict(*args, **kwargs))
    443 
    444 

C:\software\Anaconda3\envs\x-python\lib\site-packages\xarray\backends\netCDF4_.py in <genexpr>(.0)
    398     def get_variables(self):
    399         dsvars = FrozenDict(
--> 400             (k, self.open_store_variable(k, v)) for k, v in self.ds.variables.items()
    401         )
    402         return dsvars

C:\software\Anaconda3\envs\x-python\lib\site-packages\xarray\backends\netCDF4_.py in open_store_variable(self, name, var)
    374         # netCDF4 specific encoding; save _FillValue for later
    375         encoding = {}
--> 376         filters = var.filters()
    377         if filters is not None:
    378             encoding.update(filters)

netCDF4\_netCDF4.pyx in netCDF4._netCDF4.Variable.filters()

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

RuntimeError: NetCDF: Attempting netcdf-4 operation on netcdf-3 file
```
`ncdump -k HLS.S30.T13SDD.2020004.v1.4.hdf` returns `netCDF-4`

`ncdump -h HLS.S30.T13SDD.2020004.v1.4.hdf` returns

```
netcdf HLS.S30.T13SDD.2020004.v1.4 {
dimensions:
        YDim_Grid = 3660 ;
        XDim_Grid = 3660 ;
variables:
        short B01(YDim_Grid, XDim_Grid) ;
                B01:long_name = ""Coastal_Aerosol"" ;
                B01:_FillValue = ""-1000"" ;
                B01:scale_factor = ""0.0001"" ;
                B01:add_offset = ""0.0"" ;
        short B02(YDim_Grid, XDim_Grid) ;
                B02:long_name = ""Blue"" ;
                B02:_FillValue = ""-1000"" ;
                B02:scale_factor = ""0.0001"" ;
                B02:add_offset = ""0.0"" ;
        short B03(YDim_Grid, XDim_Grid) ;
                B03:long_name = ""Green"" ;
                B03:_FillValue = ""-1000"" ;
                B03:scale_factor = ""0.0001"" ;
                B03:add_offset = ""0.0"" ;
        short B04(YDim_Grid, XDim_Grid) ;
                B04:long_name = ""Red"" ;
                B04:_FillValue = ""-1000"" ;
                B04:scale_factor = ""0.0001"" ;
                B04:add_offset = ""0.0"" ;
        short B05(YDim_Grid, XDim_Grid) ;
                B05:long_name = ""Red_Edge1"" ;
                B05:_FillValue = ""-1000"" ;
                B05:scale_factor = ""0.0001"" ;
                B05:add_offset = ""0.0"" ;
        short B06(YDim_Grid, XDim_Grid) ;
                B06:long_name = ""Red_Edge2"" ;
                B06:_FillValue = ""-1000"" ;
                B06:scale_factor = ""0.0001"" ;
                B06:add_offset = ""0.0"" ;
        short B07(YDim_Grid, XDim_Grid) ;
                B07:long_name = ""Red_Edge3"" ;
                B07:_FillValue = ""-1000"" ;
                B07:scale_factor = ""0.0001"" ;
                B07:add_offset = ""0.0"" ;
        short B08(YDim_Grid, XDim_Grid) ;
                B08:long_name = ""NIR_Broad"" ;
                B08:_FillValue = ""-1000"" ;
                B08:scale_factor = ""0.0001"" ;
                B08:add_offset = ""0.0"" ;
        short B8A(YDim_Grid, XDim_Grid) ;
                B8A:long_name = ""NIR_Narrow"" ;
                B8A:_FillValue = ""-1000"" ;
                B8A:scale_factor = ""0.0001"" ;
                B8A:add_offset = ""0.0"" ;
        short B09(YDim_Grid, XDim_Grid) ;
                B09:long_name = ""Water_Vapor"" ;
                B09:_FillValue = ""-1000"" ;
                B09:scale_factor = ""0.0001"" ;
                B09:add_offset = ""0.0"" ;
        short B10(YDim_Grid, XDim_Grid) ;
                B10:long_name = ""Cirrus"" ;
                B10:_FillValue = ""-1000"" ;
                B10:scale_factor = ""0.0001"" ;
                B10:add_offset = ""0.0"" ;
        short B11(YDim_Grid, XDim_Grid) ;
                B11:long_name = ""SWIR1"" ;
                B11:_FillValue = ""-1000"" ;
                B11:scale_factor = ""0.0001"" ;
                B11:add_offset = ""0.0"" ;
        short B12(YDim_Grid, XDim_Grid) ;
                B12:long_name = ""SWIR2"" ;
                B12:_FillValue = ""-1000"" ;
                B12:scale_factor = ""0.0001"" ;
                B12:add_offset = ""0.0"" ;
        ubyte QA(YDim_Grid, XDim_Grid) ;
                QA:_FillValue = 255UB ;
                QA:QA\ description = ""Bits are listed from the MSB (bit 7) to the LSB (bit 0): \n7-6    aerosol:\n       00 - climatology\n       01 - low\n       10 - average\n       11 - high\n5      water\n4      snow/ice\n3      cloud shadow\n2      adjacent to cloud\n1      cloud\n0      cirrus\n"" ;

// global attributes:
                :PRODUCT_URI = ""S2A_MSIL1C_20200104T174731_N0208_R098_T13SDD_20200104T211121.SAFE"" ;
                :L1C_IMAGE_QUALITY = ""NONE"" ;
                :SPACECRAFT_NAME = ""Sentinel-2A"" ;
                :TILE_ID = ""S2A_OPER_MSI_L1C_TL_MTI__20200104T211121_A023690_T13SDD_N02.08"" ;
                :DATASTRIP_ID = ""S2A_OPER_MSI_L1C_DS_MTI__20200104T211121_S20200104T175119_N02.08"" ;
                :PROCESSING_BASELINE = ""02.08"" ;
                :SENSING_TIME = ""2020-01-04T17:53:07.422642Z"" ;
                :L1_PROCESSING_TIME = ""2020-01-04T21:56:59.9799Z"" ;
                :HORIZONTAL_CS_NAME = ""WGS84 / UTM zone 13N"" ;
                :HORIZONTAL_CS_CODE = ""EPSG:32613"" ;
                :NROWS = ""3660"" ;
                :NCOLS = ""3660"" ;
                :SPATIAL_RESOLUTION = ""30"" ;
                :ULX = 399960. ;
                :ULY = 4400040. ;
                :MEAN_SUN_ZENITH_ANGLE\(B01\) = 64.3317331872464 ;
                :MEAN_SUN_AZIMUTH_ANGLE\(B01\) = 161.102367370935 ;
                :MEAN_VIEW_ZENITH_ANGLE\(B01\) = 9.9000815211444 ;
                :MEAN_VIEW_AZIMUTH_ANGLE\(B01\) = 103.57344530063 ;
                :spatial_coverage = 46s ;
                :cloud_coverage = 100s ;
                :ACCODE = ""LaSRCS2AV3.5.5"" ;
                :arop_s2_refimg = ""NONE"" ;
                :arop_ncp = 0 ;
                :arop_rmse\(meters\) = 0. ;
                :arop_ave_xshift\(meters\) = 0. ;
                :arop_ave_yshift\(meters\) = 0. ;
                :HLS_PROCESSING_TIME = ""2020-01-11T07:00:37Z"" ;
                :NBAR_Solar_Zenith = 43.5498278763703 ;
                :AngleBand = 0UB, 1UB, 2UB, 3UB, 4UB, 5UB, 6UB, 7UB, 8UB, 9UB, 10UB, 11UB, 12UB ;
                :MSI\ band\ 01\ bandpass\ adjustment\ slope\ and\ offset = ""0.995900, -0.000200"" ;
                :MSI\ band\ 02\ bandpass\ adjustment\ slope\ and\ offset = ""0.977800, -0.004000"" ;
                :MSI\ band\ 03\ bandpass\ adjustment\ slope\ and\ offset = ""1.005300, -0.000900"" ;
                :MSI\ band\ 04\ bandpass\ adjustment\ slope\ and\ offset = ""0.976500, 0.000900"" ;
                :MSI\ band\ 8a\ bandpass\ adjustment\ slope\ and\ offset = ""0.998300, -0.000100"" ;
                :MSI\ band\ 11\ bandpass\ adjustment\ slope\ and\ offset = ""0.998700, -0.001100"" ;
                :MSI\ band\ 12\ bandpass\ adjustment\ slope\ and\ offset = ""1.003000, -0.001200"" ;
                :StructMetadata.0 = ""GROUP=SwathStructure\nEND_GROUP=SwathStructure\nGROUP=GridStructure\n\tGROUP=GRID_1\n\t\tGridName=\""Grid\""\n\t\tXDim=3660\n\t\tYDim=3660\n\t\tPixelSize=(30.0,30.0)\n\t\tUpperLeftPointMtrs=(399960.000000,4400040.000000)\n\t\tLowerRightMtrs=(509760.000000,4290240.000000)\n\t\tProjection=GCTP_UTM\n\t\tZoneCode=13\n\t\tSphereCode=12\n\t\tDatum=WGS84\n\t\tGridOrigin=HDFE_GD_UL\n\t\tGROUP=Dimension\n\t\t\tOBJECT=Dimension_1\n\t\t\t\tDimensionName=\""YDim_Grid\""\n\t\t\t\tSize=3660\n\t\t\tEND_OBJECT=Dimension_1\n\t\t\tOBJECT=Dimension_2\n\t\t\t\tDimensionName=\""XDim_Grid\""\n\t\t\t\tSize=3660\n\t\t\tEND_OBJECT=Dimension_2\n\t\tEND_GROUP=Dimension\n\t\tGROUP=DimensionMap\n\t\tEND_GROUP=DimensionMap\n\t\tGROUP=IndexDimensionMap\n\t\tEND_GROUP=IndexDimensionMap\n\t\tGROUP=DataField\n\t\t\tOBJECT=DataField_1\n\t\t\t\tDataFieldName=\""B01\""\n\t\t\t\tDataType=DFNT_INT16\n\t\t\t\tDimList=(\""YDim_Grid\"",\""XDim_Grid\"")\n\t\t\tEND_OBJECT=DataField_1\n\t\t\tOBJECT=DataField_2\n\t\t\t\tDataFieldName=\""B02\""\n\t\t\t\tDataType=DFNT_INT16\n\t\t\t\tDimList=(\""YDim_Grid\"",\""XDim_Grid\"")\n\t\t\tEND_OBJECT=DataField_2\n\t\t\tOBJECT=DataField_3\n\t\t\t\tDataFieldName=\""B03\""\n\t\t\t\tDataType=DFNT_INT16\n\t\t\t\tDimList=(\""YDim_Grid\"",\""XDim_Grid\"")\n\t\t\tEND_OBJECT=DataField_3\n\t\t\tOBJECT=DataField_4\n\t\t\t\tDataFieldName=\""B04\""\n\t\t\t\tDataType=DFNT_INT16\n\t\t\t\tDimList=(\""YDim_Grid\"",\""XDim_Grid\"")\n\t\t\tEND_OBJECT=DataField_4\n\t\t\tOBJECT=DataField_5\n\t\t\t\tDataFieldName=\""B05\""\n\t\t\t\tDataType=DFNT_INT16\n\t\t\t\tDimList=(\""YDim_Grid\"",\""XDim_Grid\"")\n\t\t\tEND_OBJECT=DataField_5\n\t\t\tOBJECT=DataField_6\n\t\t\t\tDataFieldName=\""B06\""\n\t\t\t\tDataType=DFNT_INT16\n\t\t\t\tDimList=(\""YDim_Grid\"",\""XDim_Grid\"")\n\t\t\tEND_OBJECT=DataField_6\n\t\t\tOBJECT=DataField_7\n\t\t\t\tDataFieldName=\""B07\""\n\t\t\t\tDataType=DFNT_INT16\n\t\t\t\tDimList=(\""YDim_Grid\"",\""XDim_Grid\"")\n\t\t\tEND_OBJECT=DataField_7\n\t\t\tOBJECT=DataField_8\n\t\t\t\tDataFieldName=\""B08\""\n\t\t\t\tDataType=DFNT_INT16\n\t\t\t\tDimList=(\""YDim_Grid\"",\""XDim_Grid\"")\n\t\t\tEND_OBJECT=DataField_8\n\t\t\tOBJECT=DataField_9\n\t\t\t\tDataFieldName=\""B8A\""\n\t\t\t\tDataType=DFNT_INT16\n\t\t\t\tDimList=(\""YDim_Grid\"",\""XDim_Grid\"")\n\t\t\tEND_OBJECT=DataField_9\n\t\t\tOBJECT=DataField_10\n\t\t\t\tDataFieldName=\""B09\""\n\t\t\t\tDataType=DFNT_INT16\n\t\t\t\tDimList=(\""YDim_Grid\"",\""XDim_Grid\"")\n\t\t\tEND_OBJECT=DataField_10\n\t\t\tOBJECT=DataField_11\n\t\t\t\tDataFieldName=\""B10\""\n\t\t\t\tDataType=DFNT_INT16\n\t\t\t\tDimList=(\""YDim_Grid\"",\""XDim_Grid\"")\n\t\t\tEND_OBJECT=DataField_11\n\t\t\tOBJECT=DataField_12\n\t\t\t\tDataFieldName=\""B11\""\n\t\t\t\tDataType=DFNT_INT16\n\t\t\t\tDimList=(\""YDim_Grid\"",\""XDim_Grid\"")\n\t\t\tEND_OBJECT=DataField_12\n\t\t\tOBJECT=DataField_13\n\t\t\t\tDataFieldName=\""B12\""\n\t\t\t\tDataType=DFNT_INT16\n\t\t\t\tDimList=(\""YDim_Grid\"",\""XDim_Grid\"")\n\t\t\tEND_OBJECT=DataField_13\n\t\t\tOBJECT=DataField_14\n\t\t\t\tDataFieldName=\""QA\""\n\t\t\t\tDataType=DFNT_UINT8\n\t\t\t\tDimList=(\""YDim_Grid\"",\""XDim_Grid\"")\n\t\t\tEND_OBJECT=DataField_14\n\t\tEND_GROUP=DataField\n\t\tGROUP=MergedFields\n\t\tEND_GROUP=MergedFields\n\tEND_GROUP=GRID_1\nEND_GROUP=GridStructure\nGROUP=PointStructure\nEND_GROUP=PointStructure\nEND\n"" ;
}
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,732567105
https://github.com/pydata/xarray/issues/4552#issuecomment-719072356,https://api.github.com/repos/pydata/xarray/issues/4552,719072356,MDEyOklzc3VlQ29tbWVudDcxOTA3MjM1Ng==,10194086,2020-10-29T23:03:30Z,2020-10-29T23:03:30Z,MEMBER,"Could you try `xr.open_dataset(f, decode_cf=False)`. It could also be helpful to know the output of `ncdump - k <file>` and `ncdump -h <file>`","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,732567105
https://github.com/pydata/xarray/issues/4552#issuecomment-719053278,https://api.github.com/repos/pydata/xarray/issues/4552,719053278,MDEyOklzc3VlQ29tbWVudDcxOTA1MzI3OA==,4762214,2020-10-29T22:11:16Z,2020-10-29T22:11:16Z,NONE,"I have also tried a clean install in a fresh conda environment with python 3.7, and receive this traceback now upon calling `xr.open_dataset(f)`, which previously at least was able to read the metadata. output of `xr.show_versions()` below that.

```
---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
<ipython-input-16-de78b6c36cbe> in <module>
      1 # ds = xr.open_dataset(f.replace('.hdf', '.h4'))
----> 2 ds = xr.open_dataset(f)
      3 ds['B01'].values

C:\software\Anaconda3\envs\x-python\lib\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)
    543 
    544     with close_on_error(store):
--> 545         ds = maybe_decode_store(store)
    546 
    547     # Ensure source filename always stored in dataset object (GH issue #2550)

C:\software\Anaconda3\envs\x-python\lib\site-packages\xarray\backends\api.py in maybe_decode_store(store, lock)
    457             drop_variables=drop_variables,
    458             use_cftime=use_cftime,
--> 459             decode_timedelta=decode_timedelta,
    460         )
    461 

C:\software\Anaconda3\envs\x-python\lib\site-packages\xarray\conventions.py in decode_cf(obj, concat_characters, mask_and_scale, decode_times, decode_coords, drop_variables, use_cftime, decode_timedelta)
    580         encoding = obj.encoding
    581     elif isinstance(obj, AbstractDataStore):
--> 582         vars, attrs = obj.load()
    583         extra_coords = set()
    584         file_obj = obj

C:\software\Anaconda3\envs\x-python\lib\site-packages\xarray\backends\common.py in load(self)
    110         """"""
    111         variables = FrozenDict(
--> 112             (_decode_variable_name(k), v) for k, v in self.get_variables().items()
    113         )
    114         attributes = FrozenDict(self.get_attrs())

C:\software\Anaconda3\envs\x-python\lib\site-packages\xarray\backends\netCDF4_.py in get_variables(self)
    398     def get_variables(self):
    399         dsvars = FrozenDict(
--> 400             (k, self.open_store_variable(k, v)) for k, v in self.ds.variables.items()
    401         )
    402         return dsvars

C:\software\Anaconda3\envs\x-python\lib\site-packages\xarray\core\utils.py in FrozenDict(*args, **kwargs)
    440 
    441 def FrozenDict(*args, **kwargs) -> Frozen:
--> 442     return Frozen(dict(*args, **kwargs))
    443 
    444 

C:\software\Anaconda3\envs\x-python\lib\site-packages\xarray\backends\netCDF4_.py in <genexpr>(.0)
    398     def get_variables(self):
    399         dsvars = FrozenDict(
--> 400             (k, self.open_store_variable(k, v)) for k, v in self.ds.variables.items()
    401         )
    402         return dsvars

C:\software\Anaconda3\envs\x-python\lib\site-packages\xarray\backends\netCDF4_.py in open_store_variable(self, name, var)
    374         # netCDF4 specific encoding; save _FillValue for later
    375         encoding = {}
--> 376         filters = var.filters()
    377         if filters is not None:
    378             encoding.update(filters)

netCDF4\_netCDF4.pyx in netCDF4._netCDF4.Variable.filters()

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

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

`xr.show_versions()`:

INSTALLED VERSIONS
------------------
commit: None
python: 3.7.8 | packaged by conda-forge | (default, Jul 31 2020, 01:53:57) [MSC v.1916 64 bit (AMD64)]
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 158 Stepping 9, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None
libhdf5: 1.10.6
libnetcdf: 4.7.4

xarray: 0.16.1
pandas: 1.1.3
numpy: 1.19.2
scipy: 1.5.2
netCDF4: 1.5.4
pydap: None
h5netcdf: None
h5py: None
Nio: None
zarr: None
cftime: 1.2.1
nc_time_axis: None
PseudoNetCDF: None
rasterio: 1.1.7
cfgrib: None
iris: None
bottleneck: None
dask: None
distributed: None
matplotlib: 3.3.2
cartopy: None
seaborn: 0.11.0
numbagg: None
pint: None
setuptools: 49.6.0.post20201009
pip: 20.2.4
conda: None
pytest: None
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