After downloading MODIS L2 Ocean Color data from https://oceandata.sci.gsfc.nasa.gov/MODIS-Aqua/L2/ or just via the L1 and L2 browser https://oceancolor.gsfc.nasa.gov/cgi/browse.pl it seems like xarray can't open these files properly. The attributes are there but no data, dimensions, or coordinates.The netCDF4 module works and I've just been using that to create xarray datasets, but it feels clunky.

MCVE Code Sample

This can be reproduced by this code and a workable example is on colab here: https://colab.research.google.com/drive/1sLh98c06I99kRGEFYuzIUD9nqgTvasdo

```python import numpy as np import matplotlib.pyplot as plt %matplotlib inline

data can be downloaded from https://oceandata.sci.gsfc.nasa.gov/ob/getfile/A2020113184000.L2_LAC_OC.nc

fn = 'A2020113184000.L2_LAC_OC.nc'

import xarray as xr xds = xr.open_dataset(fn)

when you view the contents of the xds there is no data

print(xds)

netcdf4 works fine

from netCDF4 import Dataset dataset = Dataset(fn)

gd=dataset.groups['geophysical_data'] nav=dataset.groups['navigation_data'] lons = nav.variables["longitude"][:] lats = nav.variables["latitude"][:]

flags= gd.variables["l2_flags"][:]

this has the data we want

print(gd.variables.keys())

we can create the correct xds with the data from netcdf4

chl_xds = xr.Dataset({'chlor_a':(('x', 'y'),gd.variables['chlor_a'][:].data)}, coords = {'latitude': (('x', 'y'), lats), 'longitude': (('x', 'y'), lons)}, attrs={'variable':'Chlorophyll-a'})

then merge back into the xarray dataset with all the attributes, though I'm not 100% sure I'm doing this correctly

xds['chlor_a'] = chl_xds.chlor_a

replace nodata areas with nan

xds = xds.where(xds['chlor_a'] != -32767.0)

just to visualize the data to verify

from matplotlib import colors xds.chlor_a.plot(vmin=0, vmax=1)

```

Expected Output

I would expect xarray to be able to open this level two data from the netCDF file.

Problem Description

This workaround using netCDF4 seems clunky and I would have imagined xarray could open this data that I would imagine many folks use. I'm happy to try to help resolve this issue if there is a set way to add some details that will help xarray use MODIS L2 data without issue.

Versions

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

INSTALLED VERSIONS ------------------ commit: None python: 3.6.9 (default, Nov 7 2019, 10:44:02) [GCC 8.3.0] python-bits: 64 OS: Linux OS-release: 4.19.104+ machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_US.UTF-8 LOCALE: en_US.UTF-8 libhdf5: 1.10.4 libnetcdf: 4.6.3 xarray: 0.15.1 pandas: 1.0.3 numpy: 1.18.2 scipy: 1.4.1 netCDF4: 1.5.3 pydap: None h5netcdf: None h5py: 2.10.0 Nio: None zarr: None cftime: 1.1.2 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: 3.2.1 cartopy: None seaborn: 0.10.0 numbagg: None setuptools: 46.1.3 pip: 19.3.1 conda: None pytest: 3.6.4 IPython: 5.5.0 sphinx: 1.8.5