diff --git a/mlair/run_modules/post_processing.py b/mlair/run_modules/post_processing.py
index cb3f938602164e624aaa6f7d43c0ad83c32e15c2..95120868d009bf111e333ce68c9c1405b0b96587 100644
--- a/mlair/run_modules/post_processing.py
+++ b/mlair/run_modules/post_processing.py
@@ -271,6 +271,7 @@ class PostProcessing(RunEnvironment):
     def store_crps_reports(df, report_path, subset, station=False):
         if station is True:
             file_name = f"crps_stations_{subset}.%s"
+            df = df.transpose()
         else:
             file_name = f"crps_summary_{subset}.%s"
         column_format = tables.create_column_format_for_tex(df)
diff --git a/run_bnn.py b/run_bnn.py
index 3baa8b15ffac73d63b0bc6b78e8539d159d63cff..d2e94b6f4cc454a14e01489cf6d540c68d5f5250 100644
--- a/run_bnn.py
+++ b/run_bnn.py
@@ -33,6 +33,16 @@ def main(parser_args):
     stats_per_var = {'o3': 'dma8eu', 'relhum': 'average_values', 'temp': 'maximum', 'u': 'average_values',
      'v': 'average_values', 'no': 'dma8eu', 'no2': 'dma8eu', 'cloudcover': 'average_values',
      'pblheight': 'maximum'}
+    transformation = {'o3': {'method': 'standardise'},
+                      'relhum': {'method': 'min_max'},
+                      'temp': {'method': 'standardise'},
+                      'u': {'method': 'standardise'},
+                      'v': {'method': 'standardise'},
+                      'no': {'method': 'standardise'},
+                      'no2': {'method': 'standardise'},
+                      'cloudcover': {'method': 'min_max'},
+                      'pblheight': {'method': 'standardise'}
+                      }
     workflow = DefaultWorkflow(  # stations=load_stations(),
         #stations=["DEBW087","DEBW013", "DEBW107",  "DEBW076"],
         stations=load_stations(2),
@@ -42,6 +52,7 @@ def main(parser_args):
         epochs=200,
         batch_size=512, #1024,
         permute_data_on_training=True,
+        transformation=transformation,
         train_model=False, create_new_model=True, network="UBA",
         evaluate_feature_importance=False,  # plot_list=["PlotCompetitiveSkillScore"],
         competitors=["IntelliO3-ts"],#["test_model", "test_model2"],