timeseries_cubes_month = [<iris 'Cube' of air_temperature / (K) (time: 14; air_pressure: 2; latitude: 3; longitude: 2)>, <iris 'Cube' of air_te... 3; longitude: 2)>, <iris 'Cube' of air_temperature / (K) (time: 14; air_pressure: 2; latitude: 3; longitude: 2)>, ...]

    @pytest.mark.functional
    # @pytest.mark.xfail('ValueError')
    def test_multimodel_no_time_dimension(timeseries_cubes_month):
        """Test statistic without time dimension using monthly data."""
        span = 'full'
        cubes = timeseries_cubes_month
        cubes = [cube[0] for cube in cubes]
        # ValueError: Cannot guess bounds for a coordinate of length 1.
>       multimodel_test(cubes, span=span, statistic='mean')

tests/functional/test_multimodel.py:227:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
tests/functional/test_multimodel.py:125: in multimodel_test
    output = multi_model_statistics(cubes, span=span, statistics=statistics)
esmvalcore/preprocessor/_multimodel.py:439: in multi_model_statistics
    statistic_cube = _assemble_full_data(cubes, statistic)
esmvalcore/preprocessor/_multimodel.py:323: in _assemble_full_data
    time_axis = [float(fl) for fl in _monthly_t(cubes)]
esmvalcore/preprocessor/_multimodel.py:277: in _monthly_t
    days = {day for cube in cubes for day in _datetime_to_int_days(cube)}
esmvalcore/preprocessor/_multimodel.py:277: in <setcomp>
    days = {day for cube in cubes for day in _datetime_to_int_days(cube)}
esmvalcore/preprocessor/_multimodel.py:206: in _datetime_to_int_days
    cube = _align_yearly_axes(cube)
esmvalcore/preprocessor/_multimodel.py:231: in _align_yearly_axes
    return regrid_time(cube, 'yr')
esmvalcore/preprocessor/_time.py:602: in regrid_time
    cube.coord('time').guess_bounds()
../../miniconda3/envs/esmvaltool/lib/python3.8/site-packages/iris/coords.py:1564: in guess_bounds
    self.bounds = self._guess_bounds(bound_position)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

self = DimCoord(array([49456.]), standard_name='time', units=Unit('days since 1850-1-1 00:00:00', calendar='365_day'), long_name='time', var_name='time', attributes={'_ChunkSizes': 1})
bound_position = 0.5

    def _guess_bounds(self, bound_position=0.5):
        """
        Return bounds for this coordinate based on its points.

        Kwargs:

        * bound_position:
            The desired position of the bounds relative to the position
            of the points.

        Returns:
            A numpy array of shape (len(self.points), 2).

        .. note::

            This method only works for coordinates with ``coord.ndim == 1``.

        .. note::

            If `iris.FUTURE.clip_latitudes` is True, then this method
            will clip the coordinate bounds to the range [-90, 90] when:

            - it is a `latitude` or `grid_latitude` coordinate,
            - the units are degrees,
            - all the points are in the range [-90, 90].

        .. deprecated:: 2.0.0

            The `iris.FUTURE.clip_latitudes` option is now deprecated
            and is set to True by default. Please remove code which
            relies on coordinate bounds being outside the range
            [-90, 90].

        """
        # XXX Consider moving into DimCoord
        # ensure we have monotonic points
        if not self.is_monotonic():
            raise ValueError("Need monotonic points to generate bounds for %s"
                             % self.name())

        if self.ndim != 1:
            raise iris.exceptions.CoordinateMultiDimError(self)

        if self.shape[0] < 2:
>           raise ValueError('Cannot guess bounds for a coordinate of length '
                             '1.')
E           ValueError: Cannot guess bounds for a coordinate of length 1.