diff --git a/src/model_modules/linear_model.py b/src/model_modules/linear_model.py
index 17a9b2326ab6ba1829ee4f65f0161de887e70778..d8c455b551ef748e90ae601c91931a8092a82b38 100644
--- a/src/model_modules/linear_model.py
+++ b/src/model_modules/linear_model.py
@@ -32,7 +32,7 @@ class OrdinaryLeastSquaredModel:
 
     def predict(self, data):
         data = sm.add_constant(self.reshape_xarray_to_numpy(data))
-        return self.model.predict(data)
+        return np.atleast_2d(self.model.predict(data))
 
     @staticmethod
     def reshape_xarray_to_numpy(data):
diff --git a/src/plotting/postprocessing_plotting.py b/src/plotting/postprocessing_plotting.py
index cd49ddd56b0a4642b0a9a7f280d0a6b83681398c..ece1ad97fb0be754c97997fb63d711e351d1095f 100644
--- a/src/plotting/postprocessing_plotting.py
+++ b/src/plotting/postprocessing_plotting.py
@@ -63,7 +63,8 @@ class PlotMonthlySummary(RunEnvironment):
             data = xr.open_dataarray(file_name)
 
             data_cnn = data.sel(type="CNN").squeeze()
-            data_cnn.coords["ahead"].values = [f"{days}d" for days in data_cnn.coords["ahead"].values]
+            if len(data_cnn.shape) > 1:
+                data_cnn.coords["ahead"].values = [f"{days}d" for days in data_cnn.coords["ahead"].values]
 
             data_orig = data.sel(type="orig", ahead=1).squeeze()
             data_orig.coords["ahead"] = "orig"
diff --git a/src/run_modules/experiment_setup.py b/src/run_modules/experiment_setup.py
index 9ecc421bc1ef6790d0de8343066c15332728ecc9..d2410de06c8726ad1aef3626a56876c3202bf334 100644
--- a/src/run_modules/experiment_setup.py
+++ b/src/run_modules/experiment_setup.py
@@ -33,13 +33,13 @@ class ExperimentSetup(RunEnvironment):
                  window_lead_time=None, dimensions=None, interpolate_dim=None, interpolate_method=None,
                  limit_nan_fill=None, train_start=None, train_end=None, val_start=None, val_end=None, test_start=None,
                  test_end=None, use_all_stations_on_all_data_sets=True, trainable=False, fraction_of_train=None,
-                 experiment_path=None, plot_path=None, forecast_path=None, overwrite_local_data=None):
+                 experiment_path=None, plot_path=None, forecast_path=None, overwrite_local_data=None, sampling="daily"):
 
         # create run framework
         super().__init__()
 
         # experiment setup
-        self._set_param("data_path", helpers.prepare_host())
+        self._set_param("data_path", helpers.prepare_host(sampling=sampling))
         self._set_param("trainable", trainable, default=False)
         self._set_param("fraction_of_training", fraction_of_train, default=0.8)
 
@@ -72,6 +72,7 @@ class ExperimentSetup(RunEnvironment):
         self._set_param("end", end, default="2017-12-31", scope="general")
         self._set_param("window_history_size", window_history_size, default=13)
         self._set_param("overwrite_local_data", overwrite_local_data, default=False, scope="general.preprocessing")
+        self._set_param("sampling", sampling)
 
         # target
         self._set_param("target_var", target_var, default="o3")
diff --git a/src/run_modules/post_processing.py b/src/run_modules/post_processing.py
index e6f271ce3cc6cf2548ff5b06ba40e2fd509f8c8d..93cb27dcdc7ad10137dd663c35ca43c401254872 100644
--- a/src/run_modules/post_processing.py
+++ b/src/run_modules/post_processing.py
@@ -140,7 +140,9 @@ class PostProcessing(RunEnvironment):
     def _create_ols_forecast(self, input_data, ols_prediction, mean, std, transformation_method):
         tmp_ols = self.ols_model.predict(input_data)
         tmp_ols = statistics.apply_inverse_transformation(tmp_ols, mean, std, transformation_method)
-        ols_prediction.values = np.swapaxes(np.expand_dims(tmp_ols, axis=1), 2, 0)
+        tmp_ols = np.expand_dims(tmp_ols, axis=1)
+        target_shape = ols_prediction.values.shape
+        ols_prediction.values = np.swapaxes(tmp_ols, 2, 0) if target_shape != tmp_ols.shape else tmp_ols
         return ols_prediction
 
     def _create_persistence_forecast(self, input_data, persistence_prediction, mean, std, transformation_method):
diff --git a/src/run_modules/pre_processing.py b/src/run_modules/pre_processing.py
index 2a4632d515a36a77b01a09a539da4f51ecd3e07a..c5b1c53fc007a887f5219066185b5a02f352ee7c 100644
--- a/src/run_modules/pre_processing.py
+++ b/src/run_modules/pre_processing.py
@@ -13,7 +13,7 @@ from src.join import EmptyQueryResult
 
 DEFAULT_ARGS_LIST = ["data_path", "network", "stations", "variables", "interpolate_dim", "target_dim", "target_var"]
 DEFAULT_KWARGS_LIST = ["limit_nan_fill", "window_history_size", "window_lead_time", "statistics_per_var",
-                       "station_type", "overwrite_local_data", "start", "end"]
+                       "station_type", "overwrite_local_data", "start", "end", "sampling"]
 
 
 class PreProcessing(RunEnvironment):