diff --git a/tobac/utils/internal/xarray_utils.py b/tobac/utils/internal/xarray_utils.py
index e7a649a1..3f0cfe70 100644
--- a/tobac/utils/internal/xarray_utils.py
+++ b/tobac/utils/internal/xarray_utils.py
@@ -37,8 +37,10 @@ def find_axis_from_dim_coord(
         Returns ValueError if there are more than one matching dimension name or
         if the dimension/coordinate isn't found.
     """
-
-    dim_axis = find_axis_from_dim(in_da, dim_coord_name)
+    try:
+        dim_axis = find_axis_from_dim(in_da, dim_coord_name)
+    except ValueError:
+        dim_axis = None
 
     try:
         coord_axes = find_axis_from_coord(in_da, dim_coord_name)
@@ -96,7 +98,7 @@ def find_axis_from_dim(in_da: xr.DataArray, dim_name: str) -> Union[int, None]:
             "More than one matching dimension. Need to specify which axis number or rename "
             "your dimensions."
         )
-    return None
+    raise ValueError("Dimension not found. ")
 
 
 def find_axis_from_coord(in_da: xr.DataArray, coord_name: str) -> tuple[int]:
@@ -135,18 +137,18 @@ def find_axis_from_coord(in_da: xr.DataArray, coord_name: str) -> tuple[int]:
 
     if len(all_matching_coords) > 1:
         raise ValueError("Too many matching coords")
-    return tuple()
+    raise ValueError("No matching coords")
 
 
 def find_vertical_coord_name(
-    variable_cube: xr.DataArray,
+    variable_da: xr.DataArray,
     vertical_coord: Union[str, None] = None,
 ) -> str:
     """Function to find the vertical coordinate in the iris cube
 
     Parameters
     ----------
-    variable_cube: xarray.DataArray
+    variable_da: xarray.DataArray
         Input variable cube, containing a vertical coordinate.
     vertical_coord: str
         Vertical coordinate name. If None, this function tries to auto-detect.
@@ -162,7 +164,7 @@ def find_vertical_coord_name(
         Raised if the vertical coordinate isn't found in the cube.
     """
 
-    list_coord_names = variable_cube.coords
+    list_coord_names = variable_da.coords
 
     if vertical_coord is None or vertical_coord == "auto":
         # find the intersection
@@ -347,14 +349,20 @@ def add_coordinates_to_features(
     hdim2_name_original = variable_da.dims[hdim2_axis]
 
     # generate random names for the new coordinates that are based on i, j, k values
-    hdim1_name_new = "".join(
-        random.choice(string.ascii_uppercase + string.ascii_lowercase + string.digits)
-        for _ in range(16)
-    )
-    hdim2_name_new = "".join(
-        random.choice(string.ascii_uppercase + string.ascii_lowercase + string.digits)
-        for _ in range(16)
-    )
+    hdim1_name_new = "__temp_hdim1_name"
+    hdim2_name_new = "__temp_hdim2_name"
+    vdim_name_new = "__temp_vdim_name"
+
+    if (
+        hdim1_name_new in variable_da.dims
+        or hdim2_name_new in variable_da.dims
+        or vdim_name_new in variable_da.dims
+    ):
+        raise ValueError(
+            "Cannot have dimensions named {0}, {1}, or {2}".format(
+                hdim1_name_new, hdim2_name_new, vdim_name_new
+            )
+        )
 
     dim_new_names = {
         hdim1_name_original: hdim1_name_new,
@@ -367,12 +375,6 @@ def add_coordinates_to_features(
 
     if is_3d:
         vdim_name_original = variable_da.dims[vertical_axis]
-        vdim_name_new = "".join(
-            random.choice(
-                string.ascii_uppercase + string.ascii_lowercase + string.digits
-            )
-            for _ in range(16)
-        )
         dim_interp_coords[vdim_name_new] = xr.DataArray(
             return_feat_df["vdim"].values, dims="features"
         )
@@ -383,9 +385,9 @@ def add_coordinates_to_features(
     # dataset
     renamed_dim_da = variable_da.swap_dims(dim_new_names)
     interpolated_df = renamed_dim_da.interp(coords=dim_interp_coords)
-    interpolated_df = interpolated_df.drop([hdim1_name_new, hdim2_name_new])
-    if is_3d:
-        interpolated_df = interpolated_df.drop([vdim_name_new])
+    interpolated_df = interpolated_df.drop_vars(
+        [hdim1_name_new, hdim2_name_new, vdim_name_new], errors="ignore"
+    )
     return_feat_df[time_dim_name] = variable_da[time_dim_name].values[
         return_feat_df["frame"]
     ]