text: import iris
  import harmonise
  from cube_funcs import get_dates
  
  # specify path to file that matches the resolution you wish to regrid to
  # 1.0 degree resolution target
  path = ('/nfs/a68/gyjcab/datasets/lapse_data_harmonised/Jan_2018/mon_1.0deg/')
  one_deg_cube = path+'tas_airs_mon_1.0deg_2003_2016.nc'
  
  # 0.25 degree resolution target
  path = ('/nfs/a68/gyjcab/datasets/lapse_data_harmonised/Jan_2018/mon_0.25deg/')
  pt25_cube = path+'sal_clara_mon_0.25deg_1982_2015_direct_from_netcdf.nc'
  
  # specify target cube
  regrid_cube = one_deg_cube
  
  # read in ERA5 data
  path = '/nfs/a68/gyjcab/datasets/ERA5/'
  cube = iris.load_cube(path + 'era5_surface_solar_radiation.nc')
  print(cube)
  
  # Convert units to W/m2 by dividing by seconds in day
  dates = get_dates(cube)
  for t in range(len(dates)):
      date = dates[t]
      seconds_in_day = 60*60*24
      temp_data = cube.data[t, :, :] / seconds_in_day
      cube.data[t, :, :] = temp_data
  
  # convert cube data units
  cube.units = 'W/m2'
  
  # call harmonise.cube2netcdf function to regrid and save as new cube
  harmonise.cube2netcdf(cube, 'rdn', startyr=1979, nyear=41,
                        #remove_cell_methods=True,
                        product='era5_test', regrid=True, latlon_bounds=True,
                        #time_bounds=False,
                        regrid_cube=regrid_cube)
  
  