diff --git a/examples/aus_test.py b/examples/aus_test.py
deleted file mode 100644
index 7b51b42..0000000
--- a/examples/aus_test.py
+++ /dev/null
@@ -1,62 +0,0 @@
-import os
-import numpy as np
-import pandas as pd
-from tqdm import tqdm
-from hydrodataset import Camels
-
-directory = 'basin_flow'
-if not os.path.exists(directory):
-    os.makedirs(directory)
-
-camels_aus_path = "/ftproot/camels/camels_aus/"
-camels_aus_v2_path="/home/estelle/data/waterism/datasets-origin/camels/camels_aus_v2/"
-
-aus_region = "AUS"
-aus_v2_region = "AUS_v2"
-# ------------------------------ AUS --------------------------------
-camels_aus = Camels(camels_aus_path, download=False, region=aus_region)
-camels_aus_v2=Camels(camels_aus_v2_path, download=False, region=aus_v2_region)
-gage_ids = camels_aus.read_object_ids()
-
-# Return -> np.array: forcing data
-hydro_info = camels_aus.read_relevant_cols(
-    gage_ids[:],
-    ["2015-01-01", "2022-02-15"],
-    ["et_morton_point_SILO", "precipitation_SILO", "et_morton_actual_SILO"]
-)
-
-gages_to_nan = ['403213A', '224213A', '224214A', '227225A']
-
-# 1 Megaliters Per Day = 0.011574074074074 Cubic Meters Per Second
-# ML_to_m3_per_s = 0.011574074074074
-
-t_info = pd.date_range(start="2015-01-01", end="2022-02-14", freq='D')
-formatted_time = t_info.strftime('%Y-%m-%d %H:%M:%S')
-
-for i, gage_id in enumerate(gage_ids):
-    hydro_data = hydro_info[i]
-
-    if gage_id in gages_to_nan:
-        streamflow_data_m3_per_s = np.nan * np.ones_like(hydro_data[:, 0])
-    else:
-        # Return -> np.array: streamflow data, 3-dim [station, time, streamflow(ML/d)]
-        streamflow_info = camels_aus_v2.read_target_cols(
-            gage_ids[i:i+1],
-            ["2015-01-01", "2022-02-15"],
-            target_cols=["streamflow_MLd"],
-        )
-        streamflow_data_m3_per_s = (streamflow_info[0,:,0]/35.314666721489)
-
-    pet = hydro_data[:, 0]
-    prcp = hydro_data[:, 1]
-    flow = streamflow_data_m3_per_s
-    et = hydro_data[:, 2]
-    node1_flow = np.nan * np.ones_like(flow)  # NA for node1_flow
-    merged_row = np.column_stack([formatted_time, pet, prcp, flow, et, node1_flow])
-    # tiem pet(mm/day) prcp(mm/day) flow(m^3/s) et(mm/day) node1_flow(m^3/s)
-    columns = ["time", "pet(mm/day)", "prcp(mm/day)", "flow(m^3/s)", "et(mm/day)", "node1_flow(m^3/s)"]
-    df = pd.DataFrame(merged_row, columns=columns)
-    filename = f'basin_{gage_id}.csv'
-    file_path = os.path.join(directory, filename)
-    df.to_csv(file_path, index=False)
-
diff --git a/examples/aus_v2_test.py b/examples/aus_v2_test.py
deleted file mode 100644
index 6b0f720..0000000
--- a/examples/aus_v2_test.py
+++ /dev/null
@@ -1,41 +0,0 @@
-import os
-import numpy as np
-
-from hydrodataset import Camels
-
-camels_aus_v2_path="/home/estelle/data/waterism/datasets-origin/camels/camels_aus_v2/"
-
-aus_v2_region = "AUS_v2"
-
-# ---------------------------- AUS-V2 -------------------------------
-camels_aus_v2=Camels(camels_aus_v2_path, download=False, region=aus_v2_region)
-
-gage_ids = camels_aus_v2.read_object_ids()
-
-p_mean_info=camels_aus_v2.read_mean_prcp(
-    gage_ids[:5],unit="mm/h"
-)
-print(p_mean_info)
-
-attrs = camels_aus_v2.read_constant_cols(
-    gage_ids[:5], var_lst=["catchment_area", "geol_sec", "metamorph"]
-)
-print(attrs)
-forcings = camels_aus_v2.read_relevant_cols(
-    gage_ids[:5],
-    ["1990-01-01", "2010-01-01"],
-    var_lst=["precipitation_AGCD", "et_morton_actual_SILO", "tmin_SILO"],
-)
-print(forcings.shape)
-flows = camels_aus_v2.read_target_cols(
-    gage_ids[:5],
-    ["2015-01-01", "2022-01-01"],
-    target_cols=["streamflow_MLd", "streamflow_mmd"],
-)
-print(flows)
-streamflow_types = camels_aus_v2.get_target_cols()
-print(streamflow_types)
-focing_types = camels_aus_v2.get_relevant_cols()
-print(focing_types)
-attr_types = camels_aus_v2.get_constant_cols()
-print(attr_types)
\ No newline at end of file
diff --git a/examples/scripts.py b/examples/scripts.py
index ba96649..72b17ba 100644
--- a/examples/scripts.py
+++ b/examples/scripts.py
@@ -1,7 +1,7 @@
 """
 Author: Wenyu Ouyang
 Date: 2022-09-06 23:42:46
-LastEditTime: 2024-09-14 13:27:17
+LastEditTime: 2024-11-11 16:44:31
 LastEditors: Wenyu Ouyang
 Description: examples for using hydrodataset
 FilePath: \hydrodataset\examples\scripts.py
@@ -18,7 +18,7 @@
 camels_cl_path = os.path.join("camels", "camels_cl")
 camels_gb_path = os.path.join("camels", "camels_gb")
 camels_us_path = os.path.join("camels", "camels_us")
-camels_aus_v2_path=os.path.join("camels","camels_aus_v2")
+camels_aus_v2_path = os.path.join("camels", "camels_aus_v2")
 
 aus_v2_region = "AUS_v2"
 aus_region = "AUS"
@@ -174,7 +174,7 @@
 )
 
 # # ---------------------------- AUS-V2 -------------------------------
-camels_aus_v2=Camels(camels_aus_v2_path, download=False, region=aus_v2_region)
+camels_aus_v2 = Camels(camels_aus_v2_path, download=False, region=aus_v2_region)
 gage_ids = camels_aus_v2.read_object_ids()
 assert gage_ids.size == 561
 attrs = camels_aus_v2.read_constant_cols(
diff --git a/hydrodataset/camels.py b/hydrodataset/camels.py
index 6cdd1c8..bc2d697 100644
--- a/hydrodataset/camels.py
+++ b/hydrodataset/camels.py
@@ -1,7 +1,7 @@
 """
 Author: Wenyu Ouyang
 Date: 2022-01-05 18:01:11
-LastEditTime: 2024-09-10 19:15:33
+LastEditTime: 2024-11-11 17:26:42
 LastEditors: Wenyu Ouyang
 Description: Read Camels Series ("AUStralia", "BRazil", "ChiLe", "GreatBritain", "UnitedStates") datasets
 FilePath: \hydrodataset\hydrodataset\camels.py
@@ -595,7 +595,9 @@ def get_relevant_cols(self) -> np.ndarray:
                 if root == self.data_source_description["CAMELS_FORCING_DIR"]:
                     continue
                 forcing_types.extend(
-                    file[:-4] for file in files if file not in ["ClimaticIndices.csv", "desktop.ini"]
+                    file[:-4]
+                    for file in files
+                    if file not in ["ClimaticIndices.csv", "desktop.ini"]
                 )
             return np.array(forcing_types)
         elif self.region == "BR":
@@ -1295,7 +1297,9 @@ def read_relevant_cols(
                 chosen_data = forcing_data[gage_id_lst].values[ind1, :]
                 x[:, ind2, k] = chosen_data.T
         elif self.region == "AUS_v2":
-            for k in tqdm(range(len(var_lst)), desc="Read forcing data of CAMELS-AUS-V2"):
+            for k in tqdm(
+                range(len(var_lst)), desc="Read forcing data of CAMELS-AUS-V2"
+            ):
                 if "precipitation_" in var_lst[k]:
                     forcing_dir = os.path.join(
                         self.data_source_description["CAMELS_FORCING_DIR"],
@@ -1559,13 +1563,37 @@ def read_area(self, gage_id_lst) -> np.ndarray:
         else:
             raise NotImplementedError(CAMELS_NO_DATASET_ERROR_LOG)
 
-    def read_mean_prcp(self, gage_id_lst, unit="mm/d") -> np.ndarray:
+    def read_mean_prcp(self, gage_id_lst, unit="mm/d") -> xr.Dataset:
+        """Read mean precipitation data
+
+        Parameters
+        ----------
+        gage_id_lst : list
+            station ids
+        unit : str, optional
+            the unit of mean_prcp, by default "mm/d"
+
+        Returns
+        -------
+        xr.Dataset
+            TODO: now only support CAMELS-US
+
+        Raises
+        ------
+        NotImplementedError
+            some regions are not supported
+        ValueError
+            unit must be one of ['mm/d', 'mm/day', 'mm/h', 'mm/hour', 'mm/3h', 'mm/3hour', 'mm/8d', 'mm/8day']
+        """
         if self.region in ["US", "AUS", "AUS_v2", "BR", "GB"]:
             if self.region == "US":
                 data = self.read_attr_xrdataset(gage_id_lst, ["p_mean"])
-            data = self.read_constant_cols(
-                gage_id_lst, ["p_mean"], is_return_dict=False,
-            )
+            else:
+                data = self.read_constant_cols(
+                    gage_id_lst,
+                    ["p_mean"],
+                    is_return_dict=False,
+                )
         elif self.region == "CL":
             # there are different p_mean values for different forcings, here we chose p_mean_cr2met now
             data = self.read_constant_cols(
@@ -1579,9 +1607,11 @@ def read_mean_prcp(self, gage_id_lst, unit="mm/d") -> np.ndarray:
             converted_data = data / 24
         elif unit in ["mm/3h", "mm/3hour"]:
             converted_data = data / 8
+        elif unit in ["mm/8d", "mm/8day"]:
+            converted_data = data * 8
         else:
             raise ValueError(
-                "unit must be one of ['mm/d', 'mm/day', 'mm/h', 'mm/hour', 'mm/3h', 'mm/3hour']"
+                "unit must be one of ['mm/d', 'mm/day', 'mm/h', 'mm/hour', 'mm/3h', 'mm/3hour', 'mm/8d', 'mm/8day']"
             )
         return converted_data
 
@@ -1897,4 +1927,4 @@ def read_attr_xrdataset(self, gage_id_lst=None, var_lst=None, **kwargs):
 
     @property
     def streamflow_unit(self):
-        return "foot^3/s"
\ No newline at end of file
+        return "foot^3/s"
diff --git a/tests/test_camels.py b/tests/test_camels.py
index 957a476..f1ccd40 100644
--- a/tests/test_camels.py
+++ b/tests/test_camels.py
@@ -1,7 +1,7 @@
 """
 Author: Wenyu Ouyang
 Date: 2022-09-05 23:20:24
-LastEditTime: 2024-11-04 20:15:11
+LastEditTime: 2024-11-11 17:29:13
 LastEditors: Wenyu Ouyang
 Description: Tests for `hydrodataset` package
 FilePath: \hydrodataset\tests\test_camels.py
@@ -16,6 +16,7 @@
 from hydrodataset import Camels
 import numpy as np
 import pandas as pd
+import xarray as xr
 from unittest.mock import patch, MagicMock
 
 
@@ -76,6 +77,7 @@ def test_read_mean_prcp():
     gage_ids = camels.read_object_ids()
     mean_prcp = camels.read_mean_prcp(gage_ids[:5])
     print(mean_prcp)
+    assert isinstance(mean_prcp, xr.Dataset)
 
 
 def test_read_target_cols_us():
@@ -281,16 +283,6 @@ def test_read_camels_us_model_output_data_no_data():
         assert np.all(np.isnan(result))
 
 
-def test_read_mean_prcp_us():
-    camels = Camels()
-    camels.region = "US"
-    camels.read_attr_xrdataset = MagicMock(return_value=np.array([1.0, 2.0, 3.0]))
-
-    gage_id_lst = ["01013500", "01013501", "01013502"]
-    result = camels.read_mean_prcp(gage_id_lst)
-    assert np.array_equal(result, np.array([1.0, 2.0, 3.0]))
-
-
 def test_read_mean_prcp_aus():
     camels = Camels()
     camels.region = "AUS"