diff --git a/run_wrf_dh.py b/run_wrf_dh.py
index 315ca5ae5ea388753e5d227c06003e508ba4b8bc..bf57a4364743ce310b8da743b8ed51e0dff1228e 100644
--- a/run_wrf_dh.py
+++ b/run_wrf_dh.py
@@ -8,7 +8,7 @@ from mlair.workflows import DefaultWorkflow
 from mlair.helpers import remove_items
 from mlair.configuration.defaults import DEFAULT_PLOT_LIST
 
-from mlair.model_modules.model_class import IntelliO3TsArchitecture, MyLSTMModel, MyCNNModel, MyCNNModelSect, MyLuongAttentionLSTMModel
+from mlair.model_modules.model_class import IntelliO3TsArchitecture, MyLSTMModel, MyCNNModel, MyCNNModelSect, MyLuongAttentionLSTMModel, MyUnet
 
 import os
 
@@ -16,7 +16,6 @@ import os
 def load_stations():
     import json
     try:
-        filename = 'supplement/station_list_north_german_plain_rural.json'
         filename = 'supplement/WRF_coord_list_from_IntelliO3.json'
         with open(filename, 'r') as jfile:
             stations = json.load(jfile)
@@ -26,40 +25,24 @@ def load_stations():
 
 
 def main(parser_args):
-    plots = remove_items(DEFAULT_PLOT_LIST, "PlotConditionalQuantiles")
+    do_not_plot = ["PlotDataHistogram", "PlotAvailability"]
+    plots = remove_items(DEFAULT_PLOT_LIST, do_not_plot)
     workflow = DefaultWorkflow(  stations=load_stations(),
-        # stations=["DEBW087","DEBW013", "DEBW107",  "DEBW076"],
         lazy_preprocessing=False,
         train_model=False, create_new_model=True, network="UBA",
-        evaluate_bootstraps=False,  # plot_list=["PlotCompetitiveSkillScore"],
-#         competitors=["test_model", "test_model2"],
-#         competitor_path=os.path.join(os.getcwd(), "data", "comp_test"),
-        competitors=["baseline", "sector_baseline"],
-        competitor_path="/p/scratch/deepacf/kleinert1/IASS_proc_monthyl/competitors/o3",
+        evaluate_feature_importance=False,
+        feature_importance_bootstrap_type="group_of_variables",
+        feature_importance_create_new_bootstraps=False,
+        feature_importance_bootstrap_method="zero_mean",
+        plot_list=plots,
+        #competitors=["NN1s", "sector_baseline"],
+        #competitor_path="/p/scratch/deepacf/kleinert1/IASS_proc_monthyl/competitors/o3",
+        uncertainty_estimate_block_length="7d",
         train_min_length=1, val_min_length=1, test_min_length=1,
-        # data_handler=DataHandlerSingleStation,
-        # data_handler=DataHandlerSingleGridColumn,
-        epochs=100,
+        epochs=300,
         window_lead_time=4,
         window_history_size=6,
-#        stations=["coords__48_8479__10_0963", "coords__51_8376__14_1417",
-#                  "coords__50_7536__7_0827", "coords__51_4070__6_9656",
-#                  "coords__49_8421__7_8662", "coords__49_7410__7_1935",
-#                  "coords__51_1566__11_8182", "coords__51_4065__6_9660",
-#                  "coords__50_7333__7_1000", "coords__50_0000__8_0000",
-#                  "coords__48_7444__7_6000", "coords__51_0000__11_0000",
-#                  "coords__52_7555__8_1000", "coords__50_0000__2_0000",
-#                  "coords__51_7666__8_6000", "coords__50_0000__3_0000",
-#                  "coords__45_7777__9_1000", "coords__50_0000__4_0000",
-#                  ],
         data_handler=DataHandlerWRF,
-#        data_handler=DataHandlerMainSectWRF, #,
-        # data_path="/p/scratch/deepacf/kleinert1/IASS_proc_monthyl",
-        #data_path="/p/scratch/deepacf/kleinert1/IASS_proc",
-        #data_path="/p/project/deepacf/intelliaq/kleinert1/DATA/WRF_CHEM_soft_ln_small_test",
-        # data_path="/media/felix/INTENSO/WRF_CHEM/hourly/cdo_output_test/jan_test",
-        # data_path="/p/scratch/deepacf/intelliaq/kleinert1/IASS_proc_monthly/monthly2009",
-        # data_path="/p/scratch/deepacf/intelliaq/kleinert1/IASS_proc_monthly/monthly_count_test", 
         data_path = "/p/scratch/deepacf/intelliaq/kleinert1/IASS_proc_monthly/monthly2009_2010-03", 
         #data_path="/p/scratch/deepacf/intelliaq/kleinert1/IASS_proc_monthly/monthly_01-03",
         common_file_starter="wrfout_d01",
@@ -83,13 +66,15 @@ def main(parser_args):
             # 'CLDFRA': {"method": "min_max", "min": 0., "max": 1.},
         },
         # variables=['T2', 'o3', 'wdir10ll', 'wspd10ll', 'no', 'no2', 'co', 'PSFC', 'PBLH', 'CLDFRA'],
-        variables=['T2', 'o3', 'wdir10ll', 'wspd10ll', 'no', 'no2', 'co', 'PSFC', 'PBLH'],
+        variables=['T2', 'o3', 'wdir10ll', 'wspd10ll', 'no', 'no2', 'co', 'PSFC', 'PBLH', 'Q2'],
         target_var='o3',
+        target_var_unit="ppb",
+        vars_for_unit_conv={'o3': 'ppbv'},
         # statistics_per_var={'T2': None, 'o3': None, 'wdir10ll': None, 'wspd10ll': None,
         #                     'no': None, 'no2': None, 'co': None, 'PSFC': None, 'PBLH': None, 'CLDFRA': None, },
         statistics_per_var={'T2': "average_values", 'o3': "dma8eu", 'wdir10ll': "average_values",
                             'wspd10ll': "average_values", 'no': "dma8eu", 'no2': "dma8eu", 'co': "dma8eu",
-                            'PSFC': "average_values", 'PBLH': "average_values",
+                            'PSFC': "average_values", 'PBLH': "average_values", 'Q2': "average_values",
                             # 'CLDFRA': "average_values",
                             },
         # variables=['T2', 'Q2', 'PBLH', 'U10ll', 'V10ll', 'wdir10ll', 'wspd10ll'],
@@ -141,11 +126,8 @@ def main(parser_args):
         
         batch_size=64*2*2,
         interpolation_limit=0,
-        as_image_like_data_format=False,
-#         model=MyLSTMModel,
-          model=MyLuongAttentionLSTMModel,
-#         model=MyCNNModelSect,
-#        model=MyCNNModel,
+        as_image_like_data_format=True,
+        model=MyUnet,
 
         **parser_args.__dict__)
     workflow.run()