diff --git a/imap_processing/ancillary/ancillary_dataset_combiner.py b/imap_processing/ancillary/ancillary_dataset_combiner.py
index 01819a9d12..104255f876 100644
--- a/imap_processing/ancillary/ancillary_dataset_combiner.py
+++ b/imap_processing/ancillary/ancillary_dataset_combiner.py
@@ -338,7 +338,7 @@ def __init__(
     ):
         super().__init__(ancillary_input, expected_end_date)
 
-    def convert_file_to_dataset(self, filepath: str | Path) -> xr.Dataset:
+    def convert_file_to_dataset(self, filepath: str | Path) -> xr.Dataset:  # noqa: PLR0911
         """
         Convert GLOWS ancillary .dat files to xarray datasets.
 
@@ -364,6 +364,19 @@ def convert_file_to_dataset(self, filepath: str | Path) -> xr.Dataset:
         if "excluded-regions" in filename:
             # Handle excluded regions (2 columns: longitude, latitude)
             data = np.loadtxt(filepath, comments="#")
+            if data.size == 0:
+                return xr.Dataset(
+                    {
+                        "ecliptic_longitude_deg": (
+                            ["region"],
+                            np.array([], dtype=float),
+                        ),
+                        "ecliptic_latitude_deg": (
+                            ["region"],
+                            np.array([], dtype=float),
+                        ),
+                    }
+                )
             return xr.Dataset(
                 {
                     "ecliptic_longitude_deg": (["region"], data[:, 0]),
@@ -412,6 +425,19 @@ def convert_file_to_dataset(self, filepath: str | Path) -> xr.Dataset:
                 }
             )
 
+        elif "l2-calibration" in filename:
+            # Handle calibration file (timestamp + cps_per_R float value)
+            with open(filepath) as f:
+                lines = [line.strip() for line in f if not line.startswith("#")]
+            identifiers = [line.split(" ", 1)[0] for line in lines]
+            values = [float(line.split(" ", 1)[1]) for line in lines]
+            return xr.Dataset(
+                {
+                    "start_time_utc": (["time_block"], identifiers),
+                    "cps_per_r": (["time_block"], values),
+                }
+            )
+
         elif filename.endswith(".json"):
             # Handle pipeline settings JSON file using the generic read_json method
             return self.convert_json_to_dataset(filepath)
diff --git a/imap_processing/tests/ancillary/test_ancillary_dataset_combiner.py b/imap_processing/tests/ancillary/test_ancillary_dataset_combiner.py
index fb45059fab..f7d3f0020e 100644
--- a/imap_processing/tests/ancillary/test_ancillary_dataset_combiner.py
+++ b/imap_processing/tests/ancillary/test_ancillary_dataset_combiner.py
@@ -236,6 +236,19 @@ def test_glows_excluded_regions_combiner(glows_ancillary_filepath):
     assert dataset["ecliptic_latitude_deg"].dims == ("region",)
 
 
+def test_glows_excluded_regions_combiner_empty_file(tmp_path):
+    file_path = tmp_path / "imap_glows_l1b-map-of-excluded-regions_20251112_v001.dat"
+    file_path.write_text("# header only\n")
+
+    combiner = GlowsAncillaryCombiner([], "20251115")
+    dataset = combiner.convert_file_to_dataset(file_path)
+
+    assert "ecliptic_longitude_deg" in dataset.data_vars
+    assert "ecliptic_latitude_deg" in dataset.data_vars
+    assert len(dataset["ecliptic_longitude_deg"]) == 0
+    assert len(dataset["ecliptic_latitude_deg"]) == 0
+
+
 def test_glows_uv_sources_combiner(glows_ancillary_filepath):
     file_path = (
         glows_ancillary_filepath / "imap_glows_map-of-uv-sources_20250923_v002.dat"
@@ -300,6 +313,21 @@ def test_glows_exclusions_by_instr_team_combiner(glows_ancillary_filepath):
         assert combiner.timestamped_data[0].version == "v002"
 
 
+def test_glows_l2_calibration_combiner(tmp_path):
+    file_path = tmp_path / "imap_glows_l2-calibration_20251112_v001.dat"
+    file_path.write_text(
+        "# header\n2025-11-13T18:12:48 1.020\n2025-11-14T09:58:04 0.849\n"
+    )
+
+    combiner = GlowsAncillaryCombiner([], "20251115")
+    dataset = combiner.convert_file_to_dataset(file_path)
+
+    assert "start_time_utc" in dataset.data_vars
+    assert "cps_per_r" in dataset.data_vars
+    assert len(dataset["cps_per_r"]) == 2
+    assert dataset["cps_per_r"].values[0] == pytest.approx(1.020)
+
+
 def test_ancillary_combiner_empty_input():
     """Test AncillaryCombiner with empty input list."""
     combiner = AncillaryCombiner([], "20251031")