Loading a cube from netcdf with a wildcard produces MergeError

[am-thyst]

🐛 Bug Report

I have a collection of files containing the same diagnostics but different times (output from the UM). I can load all of the times into one cube using .pp files:

iris.load_cube("umnsaa_pa*.pp","surface_upward_latent_heat_flux")
<iris 'Cube' of surface_upward_latent_heat_flux / (W m-2) (time: 120; latitude: 550; longitude: 380)>

However, when importing the exact same data from netcdf, I get a MergeError:

iris.load_cube("umnsaa_pa*.nc","surface_upward_latent_heat_flux")


Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/miniconda3/envs/py310_env/lib/python3.10/site-packages/iris/cube.py", line 391, in merge_cube
    proto_cube.register(cube, error_on_mismatch=True)
  File "/home/miniconda3/envs/py310_env/lib/python3.10/site-packages/iris/_merge.py", line 1361, in register
    match = coord_payload.match_signature(
  File "/home/miniconda3/envs/py310_env/lib/python3.10/site-packages/iris/_merge.py", line 284, in match_signature
    raise iris.exceptions.MergeError(msgs)
iris.exceptions.MergeError: failed to merge into a single cube.
  Coordinates in cube.dim_coords differ: time.
  Coordinates in cube.aux_coords (non-scalar) differ: forecast_period.

I can fix this by using:

iris.load("umnsaa_pa*.nc","surface_upward_latent_heat_flux").concatenate()[0]
<iris 'Cube' of surface_upward_latent_heat_flux / (W m-2) (time: 120; latitude: 550; longitude: 380)>

How To Reproduce

Steps to reproduce the behaviour:

from iris.cube import Cube
from iris.coords import DimCoord
from cf_units import Unit
import numpy as np
import iris

times = np.array([418344,418345])

for x in [0,2]:
    T = times + x
    time = DimCoord(T, standard_name='time',
                    units=Unit('hours since 1970-01-01 00:00:00', calendar='gregorian'))
    
    latitude = DimCoord(np.linspace(-90, 90, 4),
                        standard_name='latitude',
                        units='degrees')
    longitude = DimCoord(np.linspace(45, 360, 8),
                         standard_name='longitude',
                         units='degrees')
    
    cube = Cube(np.zeros((2, 4, 8), np.float32),
                dim_coords_and_dims=[(time,0),(latitude, 1),
                                     (longitude, 2)])
    
    iris.save(cube,"cube_{0}.pp".format(x))
    iris.save(cube,"cube_{0}.nc".format(x))

iris.load_cube("cube_*.pp")
# should output a cube with all of the times
iris.load_cube("cube_*.nc")
# should output the error

Environment

• OS & Version: CentOS Linux, version 7 (core)
• Iris Version: 3.2.1