Iris: read data from daily data files into a single, merged cube

iris_read_daily_data.py

import datetime

import iris
import cf_units


TIME_UNITS = 'hours since 1970-01-01 00:00:00'


def read_file_as_cube(filename, prefix):
    # get date from filename
    date = datetime.datetime.strptime(filename, prefix + '%Y%m%d')
    
    # set the `cube` and `hour` variables from reading the file
    # just an example below, REPLACE BY YOUR CODE
    lon = iris.coords.DimCoord([70, 80], standard_name='longitude')
    lat = iris.coords.DimCoord([5, 10, 15], standard_name='latitude')
    cube = iris.cube.Cube([[0, 1, 2], [2, 3, 4]],
                          dim_coords_and_dims=((lon, 0), (lat, 1)))
    hour = 12
    
    # create time scalar coordinate and add to the cube
    hour = datetime.time(hour=hour)
    dt = datetime.datetime.combine(date, hour)
    dt_num = cf_units.date2num(dt, TIME_UNITS, cf_units.CALENDAR_STANDARD)
    time_coord = iris.coords.AuxCoord(dt_num, standard_name='time',
                                      units=TIME_UNITS)
    cube.add_aux_coord(time_coord)
    
    return cube


filenames = ['HCOOHiasi_20090727', 'HCOOHiasi_20090728', 'HCOOHiasi_20090729']

cubes = iris.cube.CubeList([read_file_as_cube(fn, 'HCOOHiasi_')
                            for fn in filenames])

merged_cube = cubes.merge_cube()