diff --git a/tests/test_spatial_avg.py b/tests/test_spatial_avg.py
index 32ae9419..f4c9a252 100644
--- a/tests/test_spatial_avg.py
+++ b/tests/test_spatial_avg.py
@@ -396,7 +396,7 @@ class TestGetWeights:
     def setup(self):
         self.ds = generate_dataset(cf_compliant=True, has_bounds=True)
 
-    def test_returns_area_weights_for_region_within_lat_and_lon(self):
+    def test_area_weights_for_region_within_lat_and_lon(self):
         result = self.ds.spatial._get_weights(
             axis=["lat", "lon"], lat_bounds=(-5, 5), lon_bounds=(-170, -120)
         )
@@ -415,7 +415,7 @@ def test_returns_area_weights_for_region_within_lat_and_lon(self):
 
         xr.testing.assert_allclose(result, expected)
 
-    def test_returns_area_weights_for_region_within_lat(self):
+    def test_area_weights_for_region_within_lat(self):
         result = self.ds.spatial._get_weights(
             axis=["lat", "lon"], lat_bounds=(-5, 5), lon_bounds=None
         )
@@ -434,7 +434,7 @@ def test_returns_area_weights_for_region_within_lat(self):
 
         xr.testing.assert_allclose(result, expected)
 
-    def test_returns_area_weights_for_region_within_lon(self):
+    def test_area_weights_for_region_within_lon(self):
         expected = xr.DataArray(
             data=np.array(
                 [
@@ -459,37 +459,68 @@ class TestGetLongitudeWeights:
     def setup(self):
         self.ds = generate_dataset(cf_compliant=True, has_bounds=True)
 
-    def test_returns_area_weights_for_region_within_lon(self):
-        expected = xr.DataArray(
-            data=np.array([0.0, 0.0, 50.0, 0.0]),
-            coords={"lon": self.ds.lon},
-            dims=["lon"],
-        )
+    def test_returns_weights_for_region_in_lon(self):
         # Longitude axes orientation swaps from (-180, 180) to (0, 360).
         result = self.ds.spatial._get_longitude_weights(
             domain_bounds=self.ds.lon_bnds.copy(),
             region_bounds=np.array([-170.0, -120.0]),
         )
+        expected = xr.DataArray(
+            data=np.array([0.0, 0.0, 50.0, 0.0]),
+            coords={"lon": self.ds.lon},
+            dims=["lon"],
+        )
 
         xr.testing.assert_allclose(result, expected)
 
-    def test_returns_area_weights_for_region_within_lon_including_prime_meridian_cell(
-        self,
-    ):
+    def test_weights_for_region_in_lon_domain_with_both_spanning_p_meridian(self):
         ds = self.ds.copy()
+        # Domain spans prime meridian.
         ds.lon_bnds.data[:] = np.array([[359, 1], [1, 90], [90, 180], [180, 359]])
 
+        result = ds.spatial._get_longitude_weights(
+            domain_bounds=ds.lon_bnds,
+            # Region spans prime meridian.
+            region_bounds=np.array([359, 1]),
+        )
         expected = xr.DataArray(
-            data=np.array([0.0, 0.0, 0.0, 50.0]),
-            coords={"lon": self.ds.lon},
+            data=np.array([2.0, 0.0, 0.0, 0.0]),
+            coords={"lon": ds.lon},
             dims=["lon"],
-        )
+          
+        xr.testing.assert_allclose(result, expected)
+
+    def test_weights_for_region_in_lon_domain_with_domain_spanning_p_meridian(self):
+        ds = self.ds.copy()
+        # Domain spans prime meridian.
+        ds.lon_bnds.data[:] = np.array([[359, 1], [1, 90], [90, 180], [180, 359]])
 
         # Longitude axes orientation swaps from (-180, 180) to (0, 360).
-        result = self.ds.spatial._get_longitude_weights(
-            domain_bounds=self.ds.lon_bnds,
+        result = ds.spatial._get_longitude_weights(
+            domain_bounds=ds.lon_bnds,
             region_bounds=np.array([-170.0, -120.0]),
         )
+        expected = xr.DataArray(
+            data=np.array([0.0, 0.0, 0.0, 50.0]),
+            coords={"lon": ds.lon},
+            dims=["lon"],
+        )
+
+        xr.testing.assert_allclose(result, expected)
+
+    def test_weights_for_region_in_lon_domain_with_region_spanning_p_meridian(self):
+        ds = self.ds.copy()
+
+        result = ds.spatial._get_longitude_weights(
+            domain_bounds=ds.lon_bnds,
+            # Region spans prime meridian.
+            region_bounds=np.array([359, 1]),
+        )
+        expected = xr.DataArray(
+            data=np.array([1.875, 0.0625, 0.0, 0.0625]),
+            coords={"lon": ds.lon},
+            dims=["lon"],
+        )
 
         xr.testing.assert_allclose(result, expected)
 
@@ -528,7 +559,7 @@ class TestGetLatitudeWeights:
     def setup(self):
         self.ds = generate_dataset(cf_compliant=True, has_bounds=True)
 
-    def test_returns_area_weights_for_region_within_lat(self):
+    def test_weights_for_region_within_lat(self):
         expected = xr.DataArray(
             data=np.array([0.0, 0.087156, 0.087156, 0.0]),
             coords={"lat": self.ds.lat},
diff --git a/xcdat/spatial_avg.py b/xcdat/spatial_avg.py
index 2c8f3ea8..1fa29968 100644
--- a/xcdat/spatial_avg.py
+++ b/xcdat/spatial_avg.py
@@ -369,11 +369,12 @@ def _get_longitude_weights(
 
         1. Align the axis orientations of the domain and region bounds to
            (0, 360) to ensure compatibility in the proceeding steps.
-        2. Handle grid cells that cross the prime meridian (e.g., [-1, 1])
-           by recreating the axis with two additional grid cells ([0, 1] and
-           [359, 360]) to ensure alignment with the (0, 360) axis orientation.
-           The prime meridian grid cell is returned as a variable to handle
-           the length of weights in a proceeding step.
+        2. Handle grid cells that cross the prime meridian (e.g., [-1, 1]) by
+           breaking such grid cells into two (e.g., [0, 1] and [359, 360]) to
+           ensure alignment with the (0, 360) axis orientation. This results in
+           a bounds axis of length(nlon)+1. The index of the grid cell that
+           crosses the prime meridian is returned in order to reduce the length
+           of weights to nlon.
         3. Scale the domain down to a region (if selected).
         4. Calculate weights using the domain bounds.
         5. If the prime meridian grid cell exists, use this cell's index to