diff --git a/weather_mv/loader_pipeline/ee.py b/weather_mv/loader_pipeline/ee.py
index 2ad914dd..ecaf5408 100644
--- a/weather_mv/loader_pipeline/ee.py
+++ b/weather_mv/loader_pipeline/ee.py
@@ -448,7 +448,6 @@ def convert_to_asset(self, queue: Queue, uri: str):
         with open_dataset(uri,
                           self.open_dataset_kwargs,
                           self.disable_grib_schema_normalization,
-                          band_names_dict=self.band_names_dict,
                           initialization_time_regex=self.initialization_time_regex,
                           forecast_time_regex=self.forecast_time_regex,
                           group_common_hypercubes=self.group_common_hypercubes) as ds_list:
@@ -459,15 +458,17 @@ def convert_to_asset(self, queue: Queue, uri: str):
                 attrs = ds.attrs
                 data = list(ds.values())
                 asset_name = get_ee_safe_name(uri)
-                channel_names = [da.name for da in data]
-                start_time, end_time, is_normalized = (attrs.get(key) for key in
-                                                       ('start_time', 'end_time', 'is_normalized'))
+                channel_names = [
+                    self.band_names_dict.get(da.name, da.name) if self.band_names_dict
+                    else da.name for da in data
+                ]
+
                 dtype, crs, transform = (attrs.pop(key) for key in ['dtype', 'crs', 'transform'])
-                attrs.update({'is_normalized': str(is_normalized)})  # EE properties does not support bool.
                 # Adding job_start_time to properites.
                 attrs["job_start_time"] = job_start_time
                 # Make attrs EE ingestable.
                 attrs = make_attrs_ee_compatible(attrs)
+                start_time, end_time = (attrs.get(key) for key in ('start_time', 'end_time'))
 
                 if self.group_common_hypercubes:
                     level, height = (attrs.pop(key) for key in ['level', 'height'])
diff --git a/weather_mv/loader_pipeline/sinks.py b/weather_mv/loader_pipeline/sinks.py
index 7f004ca5..52611a78 100644
--- a/weather_mv/loader_pipeline/sinks.py
+++ b/weather_mv/loader_pipeline/sinks.py
@@ -139,9 +139,14 @@ def rearrange_time_list(order_list: t.List, time_list: t.List) -> t.List:
     return datetime.datetime(*time_list)
 
 
-def _preprocess_tif(ds: xr.Dataset, filename: str, tif_metadata_for_start_time: str,
-                    tif_metadata_for_end_time: str, uri: str, band_names_dict: t.Dict,
-                    initialization_time_regex: str, forecast_time_regex: str) -> xr.Dataset:
+def _preprocess_tif(
+    ds: xr.Dataset,
+    tif_metadata_for_start_time: str,
+    tif_metadata_for_end_time: str,
+    uri: str,
+    initialization_time_regex: str,
+    forecast_time_regex: str
+) -> xr.Dataset:
     """Transforms (y, x) coordinates into (lat, long) and adds bands data in data variables.
 
     This also retrieves datetime from tif's metadata and stores it into dataset.
@@ -432,7 +437,6 @@ def open_dataset(uri: str,
                  disable_grib_schema_normalization: bool = False,
                  tif_metadata_for_start_time: t.Optional[str] = None,
                  tif_metadata_for_end_time: t.Optional[str] = None,
-                 band_names_dict: t.Optional[t.Dict] = None,
                  initialization_time_regex: t.Optional[str] = None,
                  forecast_time_regex: t.Optional[str] = None,
                  group_common_hypercubes: t.Optional[bool] = False,
@@ -482,11 +486,9 @@ def open_dataset(uri: str,
                     xr_dataset = xr_datasets.sel(time=slice(start_date, end_date))
                 if uri_extension in ['.tif', '.tiff']:
                     xr_dataset = _preprocess_tif(xr_dataset,
-                                                 local_path,
                                                  tif_metadata_for_start_time,
                                                  tif_metadata_for_end_time,
                                                  uri,
-                                                 band_names_dict,
                                                  initialization_time_regex,
                                                  forecast_time_regex)