diff --git a/doc/whats-new.rst b/doc/whats-new.rst
index 24a8042ee66..4729b74640f 100644
--- a/doc/whats-new.rst
+++ b/doc/whats-new.rst
@@ -52,7 +52,7 @@ Bug fixes
 
 - Variables which are chunked using dask in larger (but aligned) chunks than the target zarr chunk size
   can now be stored using `to_zarr()` (:pull:`6258`) By `Tobias Kölling <https://github.com/d70-t>`_.
-- Multi-file datasets containing encoded :py:class:`cftime.datetime` objects can be read in parallel again (:issue:`6226`, :pull:`6249`).  By `Martin Bergemann <https://github.com/antarcticrainforest>`_.
+- Multi-file datasets containing encoded :py:class:`cftime.datetime` objects can be read in parallel again (:issue:`6226`, :pull:`6249`, :pull:`6305`).  By `Martin Bergemann <https://github.com/antarcticrainforest>`_ and `Stan West <https://github.com/stanwest>`_.
 
 Documentation
 ~~~~~~~~~~~~~
diff --git a/xarray/tests/test_distributed.py b/xarray/tests/test_distributed.py
index b97032014c4..773733b7b89 100644
--- a/xarray/tests/test_distributed.py
+++ b/xarray/tests/test_distributed.py
@@ -1,8 +1,6 @@
 """ isort:skip_file """
-import os
 import pickle
 import numpy as np
-import tempfile
 
 import pytest
 from packaging.version import Version
@@ -113,19 +111,18 @@ def test_dask_distributed_netcdf_roundtrip(
 
 @requires_cftime
 @requires_netCDF4
-def test_open_mfdataset_can_open_files_with_cftime_index():
+def test_open_mfdataset_can_open_files_with_cftime_index(tmp_path):
     T = xr.cftime_range("20010101", "20010501", calendar="360_day")
     Lon = np.arange(100)
     data = np.random.random((T.size, Lon.size))
     da = xr.DataArray(data, coords={"time": T, "Lon": Lon}, name="test")
+    file_path = tmp_path / "test.nc"
+    da.to_netcdf(file_path)
     with cluster() as (s, [a, b]):
         with Client(s["address"]):
-            with tempfile.TemporaryDirectory() as td:
-                data_file = os.path.join(td, "test.nc")
-                da.to_netcdf(data_file)
-                for parallel in (False, True):
-                    with xr.open_mfdataset(data_file, parallel=parallel) as tf:
-                        assert_identical(tf["test"], da)
+            for parallel in (False, True):
+                with xr.open_mfdataset(file_path, parallel=parallel) as tf:
+                    assert_identical(tf["test"], da)
 
 
 @pytest.mark.parametrize("engine,nc_format", ENGINES_AND_FORMATS)