diff --git a/src/modelskill/comparison/_comparison.py b/src/modelskill/comparison/_comparison.py
index aed4cc27e..72a664bf4 100644
--- a/src/modelskill/comparison/_comparison.py
+++ b/src/modelskill/comparison/_comparison.py
@@ -907,17 +907,25 @@ def sel(
                 k: v.sel(time=slice(start, end)) for k, v in raw_mod_data.items()
             }  # type: ignore
         if time is not None:
-            d = d.sel(time=time)
+            try:
+                d = d.sel(time=time)
+            except KeyError:
+                d = d.isel(time=slice(0, 0))  # No data for this time, return empty
+            else:
+                if "time" not in d.dims:
+                    # Exact timestamp match returns 0-dimensional dataset; expand back to 1D
+                    d = d.expand_dims("time")
             raw_mod = {}
             # Nearest time selection for raw_mod_data,
             # as it may not have the same time points as the matched data
             if isinstance(time, slice):
                 raw_mod_data = {k: v.sel(time=time) for k, v in raw_mod_data.items()}  # type: ignore
             else:
-                for k, v in raw_mod_data.items():
-                    time_vals = v.time.values
-                    idx = np.abs(time_vals - np.datetime64(time)).argmin()
-                    raw_mod[k] = v.sel(time=time_vals[idx])
+                if len(d.time) > 0:
+                    for k, v in raw_mod_data.items():
+                        time_vals = v.time.values
+                        idx = np.abs(time_vals - np.datetime64(time)).argmin()
+                        raw_mod[k] = v.sel(time=time_vals[idx])
                 raw_mod_data = raw_mod
         if area is not None:
             if _area_is_bbox(area):
diff --git a/tests/test_comparercollection.py b/tests/test_comparercollection.py
index f884ff7f4..6365d3195 100644
--- a/tests/test_comparercollection.py
+++ b/tests/test_comparercollection.py
@@ -140,16 +140,21 @@ def test_cc_sel_model_last(cc):
     assert cc2.mod_names == ["m3"]
 
 
-# TODO: FAILS
-# def test_cc_sel_time_single(cc):
-#     cc1 = cc.sel(time="2019-01-03")
-#     assert cc1.n_comparers == 2
-#     assert cc1.n_models == 3
-#     assert cc1.n_points == 6
-#     assert cc1.start == pd.Timestamp("2019-01-03")
-#     assert cc1.end == pd.Timestamp("2019-01-05")
-#     assert cc1.obs_names == ["fake point obs", "fake track obs"]
-#     assert cc1.mod_names == ["m1", "m2", "m3"]
+def test_cc_sel_time_string(cc):
+    """Selecting a date string where both comparers have data should include both."""
+    # pc has data from 2019-01-01, tc starts from 2019-01-03 - both have data on Jan 3
+    cc1 = cc.sel(time="2019-01-03")
+    assert len(cc1) == 2
+    assert cc1.obs_names == ["fake point obs", "fake track obs"]
+
+
+def test_cc_sel_time_string_no_overlap(cc):
+    """Selecting a date string where one comparer has no data should exclude that comparer."""
+    # pc has data from 2019-01-01, tc starts from 2019-01-03
+    # Selecting 2019-01-01 should return only pc
+    cc1 = cc.sel(time="2019-01-01")
+    assert len(cc1) == 1
+    assert cc1.obs_names == ["fake point obs"]
 
 
 def test_cc_sel_time(cc):