Example on using `preprocess` with `mfdataset`

I wrote this little notebook today while trying to get some satellite data in form that was nice to work with: https://gist.github.com/dcherian/66269bc2b36c2bc427897590d08472d7

I think it would make a useful example for the docs.

A few questions:

1. Do you think it'd be a good addition to the examples?
2. Is this the recommended way of adding meaningful co-ordinates, expanding dims etc.? The main bit is this function:

def preprocess(ds):

        dsnew = ds.copy()
        dsnew['latitude'] = xr.DataArray(np.linspace(90, -90, 180),
                                         dims=['phony_dim_0'])
        dsnew['longitude'] = xr.DataArray(np.linspace(-180, 180, 360),
                                          dims=['phony_dim_1'])
        dsnew = (dsnew.rename({'l3m_data': 'sss',
                               'phony_dim_0': 'latitude',
                               'phony_dim_1': 'longitude'})
                 .set_coords(['latitude', 'longitude'])
                 .drop('palette'))

        dsnew['time'] = (pd.to_datetime(dsnew.attrs['time_coverage_start'])
                         + np.timedelta64(3, 'D') + np.timedelta64(12, 'h'))
        dsnew = dsnew.expand_dims('time').set_coords('time')

        return dsnew

Also open to other feedback...

Start by reviewing the notebook in the linked gist, especially the preprocess function and its use with mfdataset. Determine how it should be adapted into the xarray documentation examples, and consider the questions about coordinates, expanded dimensions, and recommended usage. Done means an accepted, maintainable documentation example with the relevant workflow explained.