diff --git a/mlair/plotting/postprocessing_plotting.py b/mlair/plotting/postprocessing_plotting.py
index 581af2a009133c0e994ba3e33b105b5125f129dd..578a71b4cc1c9a68c55aeabcba141ba9a59eb1af 100644
--- a/mlair/plotting/postprocessing_plotting.py
+++ b/mlair/plotting/postprocessing_plotting.py
@@ -723,9 +723,15 @@ class PlotBootstrapSkillScore(AbstractPlotClass):
     (score_only=True, default). Y-axis is adjusted following the data and not hard coded. The plot is saved under
     plot_folder path with name skill_score_clim_{extra_name_tag}{model_setup}.pdf and resolution of 500dpi.
 
+    By passing a list `separate_vars` containing variable names, a second plot is created showing the `separate_vars`
+    and the remaining variables side by side with different scaling.
+
     .. image:: ../../../../../_source/_plots/skill_score_bootstrap.png
         :width: 400
 
+    .. image:: ../../../../../_source/_plots/skill_score_bootstrap_separated.png
+        :width: 400
+
     """
 
     def __init__(self, data: Dict, plot_folder: str = ".", model_setup: str = "", separate_vars: List = None):
@@ -1071,8 +1077,10 @@ class PlotAvailability(AbstractPlotClass):
         # create standard Gantt plot for all stations (currently in single pdf file with single page)
         super().__init__(plot_folder, "data_availability")
         self.dim = time_dimension
-        self.linewidth = None
         self.sampling = self._get_sampling(sampling)
+        self.linewidth = None
+        if self.sampling == 'h':
+            self.linewidth = 0.001
         plot_dict = self._prepare_data(generators)
         lgd = self._plot(plot_dict)
         self._save(bbox_extra_artists=(lgd,), bbox_inches="tight")
@@ -1087,13 +1095,6 @@ class PlotAvailability(AbstractPlotClass):
         lgd = self._plot(plot_dict_summary)
         self._save(bbox_extra_artists=(lgd,), bbox_inches="tight")
 
-    def _get_sampling(self, sampling):
-        if sampling == "daily":
-            return "D"
-        elif sampling == "hourly":
-            self.linewidth = 0.001
-            return "h"
-
     def _prepare_data(self, generators: Dict[str, DataCollection]):
         plt_dict = {}
         for subset, data_collection in generators.items():
@@ -1195,19 +1196,27 @@ class PlotAvailabilityHistogram(AbstractPlotClass):
     2) data_availability_histogram_cumulative: number of samples (xaxis) vs. number of stations having at least number
        of samples (yaxis)
 
+       .. image:: ../../../../../_source/_plots/data_availability_histogram_hist.png
+        :width: 400
+
+        .. image:: ../../../../../_source/_plots/data_availability_histogram_hist_cum.png
+        :width: 400
+
     """
 
-    def __init__(self, generators: Dict[str, DataCollection], plot_folder: str = ".", sampling="daily",
-                 subset_dim: str = 'DataSet', temporal_dim: str = 'datetime', history_dim: str = 'window',
-                 station_dim: str = 'Stations', target_dim='variables'):
+    def __init__(self, generators: Dict[str, DataCollection], plot_folder: str = ".",
+                 subset_dim: str = 'DataSet', history_dim: str = 'window',
+                 station_dim: str = 'Stations',):
 
         super().__init__(plot_folder, "data_availability_histogram")
-        self.freq = self._get_sampling(sampling)
+
         self.subset_dim = subset_dim
-        self.temporal_dim = temporal_dim
         self.history_dim = history_dim
         self.station_dim = station_dim
-        self.target_dim = target_dim
+
+        self.freq = None
+        self.temporal_dim = None
+        self.target_dim = None
         self._prepare_data(generators)
 
         for plt_type in self.allowed_plot_types:
@@ -1217,6 +1226,11 @@ class PlotAvailabilityHistogram(AbstractPlotClass):
             self._save()
             self.plot_name = plot_name_tmp
 
+    def _set_dims_from_datahandler(self, data_handler):
+        self.temporal_dim = data_handler.id_class.time_dim
+        self.target_dim = data_handler.id_class.target_dim
+        self.freq = self._get_sampling(data_handler.id_class.sampling)
+
     @property
     def allowed_plot_types(self):
         plot_types = ['hist', 'hist_cum']
@@ -1234,6 +1248,7 @@ class PlotAvailabilityHistogram(AbstractPlotClass):
         for subset, generator in generators.items():
             avail_list = []
             for station in generator:
+                self._set_dims_from_datahandler(data_handler=station)
                 station_data_x = station.get_X(as_numpy=False)[0]
                 station_data_x = station_data_x.loc[{self.history_dim: 0,  # select recent window frame
                                                      self.target_dim: station_data_x[self.target_dim].values[0]}]