diff --git a/mlair/data_handler/data_handler_mixed_sampling.py b/mlair/data_handler/data_handler_mixed_sampling.py
index 23996c80c532d0cdb778f1d231d41c7d24527e6f..d19bbadbf156b4d79d0bcef0c227b536ab7fecff 100644
--- a/mlair/data_handler/data_handler_mixed_sampling.py
+++ b/mlair/data_handler/data_handler_mixed_sampling.py
@@ -176,9 +176,9 @@ class DataHandlerMixedSamplingSeparationOfScalesSingleStation(DataHandlerMixedSa
             data_filter = data.sel({"filter": filter_name})
             for w in range(start, end):
                 res_filter.append(data_filter.shift({dim: -w * delta}))
-            res_filter = xr.concat(res_filter, dim=window_array)
+            res_filter = xr.concat(res_filter, dim=window_array).chunk()
             res.append(res_filter)
-        res = xr.concat(res, dim="filter").chunk()
+        res = xr.concat(res, dim="filter")
         return res
 
     def estimate_filter_width(self):
diff --git a/mlair/plotting/postprocessing_plotting.py b/mlair/plotting/postprocessing_plotting.py
index c8682374e0d4c0d724d83a5e36977543ac3a50f8..63b31d33f89188be21c994b26b48f1062dde9134 100644
--- a/mlair/plotting/postprocessing_plotting.py
+++ b/mlair/plotting/postprocessing_plotting.py
@@ -72,6 +72,9 @@ class AbstractPlotClass:
 
     def __init__(self, plot_folder, plot_name, resolution=500):
         """Set up plot folder and name, and plot resolution (default 500dpi)."""
+        plot_folder = os.path.abspath(plot_folder)
+        if not os.path.exists(plot_folder):
+            os.makedirs(plot_folder)
         self.plot_folder = plot_folder
         self.plot_name = plot_name
         self.resolution = resolution
@@ -82,7 +85,7 @@ class AbstractPlotClass:
 
     def _save(self, **kwargs):
         """Store plot locally. Name of and path to plot need to be set on initialisation."""
-        plot_name = os.path.join(os.path.abspath(self.plot_folder), f"{self.plot_name}.pdf")
+        plot_name = os.path.join(self.plot_folder, f"{self.plot_name}.pdf")
         logging.debug(f"... save plot to {plot_name}")
         plt.savefig(plot_name, dpi=self.resolution, **kwargs)
         plt.close('all')
@@ -995,10 +998,31 @@ class PlotAvailability(AbstractPlotClass):
         return lgd
 
 
+@TimeTrackingWrapper
+class PlotSeparationOfScales(AbstractPlotClass):
+
+    def __init__(self, collection: DataCollection, plot_folder: str = "."):
+        """Initialise."""
+        # create standard Gantt plot for all stations (currently in single pdf file with single page)
+        plot_folder = os.path.join(plot_folder, "separation_of_scales")
+        super().__init__(plot_folder, "separation_of_scales")
+        self._plot(collection)
+
+    def _plot(self, collection: DataCollection):
+        orig_plot_name = self.plot_name
+        for dh in collection:
+            data = dh.get_X(as_numpy=False)[0]
+            station = dh.id_class.station[0]
+            data = data.sel(Stations=station)
+            # plt.subplots()
+            data.plot(x="datetime", y="window", col="filter", row="variables")
+            self.plot_name = f"{orig_plot_name}_{station}"
+            self._save()
+
+
 if __name__ == "__main__":
     stations = ['DEBW107', 'DEBY081', 'DEBW013', 'DEBW076', 'DEBW087']
     path = "../../testrun_network/forecasts"
     plt_path = "../../"
 
     con_quan_cls = PlotConditionalQuantiles(stations, path, plt_path)
-
diff --git a/mlair/run_modules/post_processing.py b/mlair/run_modules/post_processing.py
index 571d3a07d15873af1c1ccedc59e0cc462e07820f..b32df1a650ff4af077090923e2a60eb6198693e9 100644
--- a/mlair/run_modules/post_processing.py
+++ b/mlair/run_modules/post_processing.py
@@ -19,7 +19,8 @@ from mlair.helpers import TimeTracking, statistics, extract_value
 from mlair.model_modules.linear_model import OrdinaryLeastSquaredModel
 from mlair.model_modules.model_class import AbstractModelClass
 from mlair.plotting.postprocessing_plotting import PlotMonthlySummary, PlotStationMap, PlotClimatologicalSkillScore, \
-    PlotCompetitiveSkillScore, PlotTimeSeries, PlotBootstrapSkillScore, PlotAvailability, PlotConditionalQuantiles
+    PlotCompetitiveSkillScore, PlotTimeSeries, PlotBootstrapSkillScore, PlotAvailability, PlotConditionalQuantiles, \
+    PlotSeparationOfScales
 from mlair.run_modules.run_environment import RunEnvironment
 
 
@@ -262,6 +263,8 @@ class PostProcessing(RunEnvironment):
         plot_list = self.data_store.get("plot_list", "postprocessing")
         time_dimension = self.data_store.get("time_dim")
 
+        PlotSeparationOfScales(self.test_data, plot_folder=self.plot_path)
+
         if self.bootstrap_skill_scores is not None and "PlotBootstrapSkillScore" in plot_list:
             PlotBootstrapSkillScore(self.bootstrap_skill_scores, plot_folder=self.plot_path, model_setup="CNN")