diff --git a/esmvaltool/cmorizers/data/cmor_config/ESACCI-SOILMOISTURE.yml b/esmvaltool/cmorizers/data/cmor_config/ESACCI-SOILMOISTURE.yml
index 0b17a06e94..651fed0932 100644
--- a/esmvaltool/cmorizers/data/cmor_config/ESACCI-SOILMOISTURE.yml
+++ b/esmvaltool/cmorizers/data/cmor_config/ESACCI-SOILMOISTURE.yml
@@ -5,16 +5,35 @@ attributes:
   modeling_realm: sat
   institution: 'TU Wien (AUT); VanderSat B.V. (NL); Planet Labs (NL); CESBIO (FR), EODC Gmbh (AUT)'
   reference: 'esacci-soilmoisture'
+  comment: ''
+
+  # COMBINED Attributes
   source: 'ftp://anon-ftp.ceda.ac.uk/neodc/esacci/soil_moisture/data/'
   title: 'ESA CCI Soil Moisture'
   version: 'L3S-SSMV-COMBINED-v08.1'
-  comment: ''
+
+  # GAPFILLED Attributes
+  version 'L3S-SSMV-COMBINED_GAPFILLED-fv09.1'
+  source: 'https://researchdata.tuwien.ac.at/records/s5j4q-rpd32'
+  title: 'ESA CCI Soil Moisture'
+
 variables:
+#   sm:
+#     mip: Eday
+#     raw: sm
+#     filename: ESACCI-SOILMOISTURE-L3S-SSMV-COMBINED-{year}????000000-fv08.1.nc
+#   smStderr:
+#     mip: Eday
+#     raw: sm_uncertainty
+#    filename: ESACCI-SOILMOISTURE-L3S-SSMV-COMBINED-{year}????000000-fv08.1.nc
+
   sm:
     mip: Eday
     raw: sm
-    filename: ESACCI-SOILMOISTURE-L3S-SSMV-COMBINED-{year}????000000-fv08.1.nc
+    gapfilled: True
+    filename: ESACCI-SOILMOISTURE-L3S-SSMV-COMBINED_GAPFILLED-{year}????000000-fv09.1.nc
   smStderr:
     mip: Eday
     raw: sm_uncertainty
-    filename: ESACCI-SOILMOISTURE-L3S-SSMV-COMBINED-{year}????000000-fv08.1.nc
+    gapfilled: True
+    filename: ESACCI-SOILMOISTURE-L3S-SSMV-COMBINED_GAPFILLED-{year}????000000-fv09.1.nc
diff --git a/esmvaltool/cmorizers/data/formatters/datasets/esacci_soilmoisture.py b/esmvaltool/cmorizers/data/formatters/datasets/esacci_soilmoisture.py
index 0676c5c85f..abec237523 100644
--- a/esmvaltool/cmorizers/data/formatters/datasets/esacci_soilmoisture.py
+++ b/esmvaltool/cmorizers/data/formatters/datasets/esacci_soilmoisture.py
@@ -57,6 +57,16 @@ def fix_coords(cube):
     cube: iris.cube.Cube
         data cube with fixed coordinates.
     """
+    # This makes fix_dim_coordnames work with GAPFILLED
+    try:
+        cube.coord("lat").standard_name = "latitude"
+    except iris.exceptions.CoordinateNotFoundError:
+        pass
+    try:
+        cube.coord("lon").standard_name = "longitude"
+    except iris.exceptions.CoordinateNotFoundError:
+        pass
+
     # First fix any completely missing coord var names
     fix_dim_coordnames(cube)
 
@@ -86,14 +96,18 @@ def fix_coords(cube):
     return cube
 
 
-def extract_variable(raw_info):
-    """Extract variables."""
+def extract_variable(raw_info, is_gapfilled):
+    """Extract variables.
+    is_gapfilled is True or False to determine if the StdErr is going to
+    load as an ancillary variable or a seperate cube.
+    """
     rawvar = raw_info["name"]
     constraint = iris.Constraint(name=rawvar)
-    if rawvar == "sm_uncertainty":
+    if rawvar == "sm_uncertainty" and not is_gapfilled:
         sm_cube = iris.load_cube(
             raw_info["file"], iris.NameConstraint(var_name="sm")
         )
+
         ancillary_var = sm_cube.ancillary_variable(
             "Volumetric Soil Moisture Uncertainty"
         )
@@ -102,6 +116,7 @@ def extract_variable(raw_info):
         cube = iris.load_cube(raw_info["file"], constraint)
 
     # Remove dysfunctional ancillary data without standard names
+
     for ancillary_variable in cube.ancillary_variables():
         cube.remove_ancillary_variable(ancillary_variable)
 
@@ -126,6 +141,7 @@ def cmorization(in_dir, out_dir, cfg, cfg_user, start_date, end_date):
         var_info = cfg["cmor_table"].get_variable(vals["mip"], var_name)
         glob_attrs["mip"] = vals["mip"]
         raw_info = {"name": vals["raw"]}
+        is_gapfilled = vals["gapfilled"]
         inpfile_pattern = os.path.join(in_dir, vals["filename"])
         logger.info(
             "CMORizing var %s from file type %s", var_name, inpfile_pattern
@@ -136,7 +152,7 @@ def cmorization(in_dir, out_dir, cfg, cfg_user, start_date, end_date):
             inpfiles = sorted(glob.glob(year_inpfile_pattern))
             for inpfile in inpfiles:
                 raw_info["file"] = inpfile
-                cube = extract_variable(raw_info)
+                cube = extract_variable(raw_info, is_gapfilled)
                 all_data_cubes.append(cube)
         final_cube = concatenate(all_data_cubes)
         fix_var_metadata(final_cube, var_info)