diff --git a/mlair/plotting/postprocessing_plotting.py b/mlair/plotting/postprocessing_plotting.py
index 8ecf5ec7f9aef53bb42f312fd68bb0b7a305288d..66679a22bcf0d6a2da4702bf6d41e0fb61b6f62a 100644
--- a/mlair/plotting/postprocessing_plotting.py
+++ b/mlair/plotting/postprocessing_plotting.py
@@ -854,6 +854,7 @@ class PlotFeatureImportanceSkillScore(AbstractPlotClass):  # pragma: no cover
             except NotImplementedError:
                 pass
         _, sampling_letter = self._get_sampling(sampling, 1)
+        sampling_letter = {"d": "D", "h": "H"}.get(sampling_letter, sampling_letter)
         self._labels = [sampling_letter + str(i) for i in data.coords[self._ahead_dim].values]
         if station_dim not in data.dims:
             data = data.expand_dims(station_dim)
@@ -1138,7 +1139,8 @@ class PlotTimeSeries:  # pragma: no cover
         color = sns.color_palette("Blues_d", self._window_lead_time).as_hex()
         for ahead in data.coords[self._ahead_dim].values:
             plot_data = data.sel({"type": self._model_name, self._ahead_dim: ahead}).drop(["type", self._ahead_dim]).squeeze().shift(index=ahead)
-            label = f"{self._sampling}{ahead}"
+            sampling_letter = {"d": "D", "h": "H"}.get(self._sampling, self._sampling)
+            label = f"{sampling_letter}{ahead}"
             ax.plot(plot_data, color=color[ahead - 1], label=label)
 
     def _plot_obs(self, ax, data):
@@ -1264,6 +1266,7 @@ class PlotSampleUncertaintyFromBootstrap(AbstractPlotClass):  # pragma: no cover
             return  # nothing to do
         n_boots = self._n_boots
         error_label = self.error_measure if self.error_unit is None else f"{self.error_measure} (in {self.error_unit})"
+        sampling_letter = {"d": "D", "h": "H"}.get(self.sampling, self.sampling)
         if agg_type == "single":
             fig, ax = plt.subplots()
             if self.ahead_dim in data_table.index.names:
@@ -1291,7 +1294,7 @@ class PlotSampleUncertaintyFromBootstrap(AbstractPlotClass):  # pragma: no cover
             g.map(sns.kdeplot, 0)
             g.add_legend(title="")
             fig = plt.gcf()
-            _labels = [self.sampling + str(i) for i in data_table.index.levels[1].values]
+            _labels = [sampling_letter + str(i) for i in data_table.index.levels[1].values]
             for axi, title in zip(g.axes.flatten(), _labels):
                 axi.set_title(title)
             for axi in g.axes.flatten():
@@ -1324,6 +1327,7 @@ class PlotSampleUncertaintyFromBootstrap(AbstractPlotClass):  # pragma: no cover
         size = len(np.unique(data_table.columns))
         asteriks = self.get_asteriks_from_mann_whitney_u_result if apply_u_test is True else None
         color_palette = sns.color_palette("Blues_d", self._factor).as_hex()
+        sampling_letter = {"d": "D", "h": "H"}.get(self.sampling, self.sampling)
         if orientation == "v":
             figsize, width = (size, 5), 0.4
         elif orientation == "h":
@@ -1348,7 +1352,7 @@ class PlotSampleUncertaintyFromBootstrap(AbstractPlotClass):  # pragma: no cover
                         flierprops={"marker": "o", "markerfacecolor": "black", "markeredgecolor": "none", "markersize": 3},
                         boxprops={'edgecolor': 'k'}, width=.8, orient=orientation, **xy, hue=self.ahead_dim)
 
-            _labels = [self.sampling + str(i) for i in data_table.index.levels[1].values]
+            _labels = [sampling_letter + str(i) for i in data_table.index.levels[1].values]
             handles, _ = ax.get_legend_handles_labels()
             ax.legend(handles, _labels)
         else:
@@ -1362,7 +1366,7 @@ class PlotSampleUncertaintyFromBootstrap(AbstractPlotClass):  # pragma: no cover
                    flierprops={"marker": "o", "markerfacecolor": "black", "markeredgecolor": "none", "markersize": 3},
                    boxprops={'facecolor': 'none', 'edgecolor': 'k'}, width=width, orient=orientation)
 
-            _labels = [self.sampling + str(i) for i in data_table.index.levels[1].values]
+            _labels = [sampling_letter + str(i) for i in data_table.index.levels[1].values]
             for axi, title in zip(ax.axes.flatten(), _labels):
                 axi.set_title(title)
                 plt.setp(axi.lines, color='k')
@@ -1631,6 +1635,7 @@ class PlotSeasonalMSEStack(AbstractPlotClass):
 
     def _plot(self, dim, split_ahead=True, sampling="daily", orientation="vertical"):
         _, sampling_letter = self._get_sampling(sampling, 1)
+        sampling_letter = {"d": "D", "h": "H"}.get(sampling_letter, sampling_letter)
         if split_ahead is False:
             self.plot_name = self.plot_name_orig + "_total_" + orientation
             data = self._data.mean(dim)
@@ -1763,7 +1768,8 @@ class PlotErrorsOnMap(AbstractPlotClass):
         cbar_label = f"{error_long_name} (in {error_units})" if error_units is not None else error_long_name
         plt.colorbar(cb, label=cbar_label)
         self._adjust_extent(ax)
-        title = model_type if ahead is None else f"{model_type} ({self.sampling}{ahead})"
+        sampling_letter = {"d": "D", "h": "H"}.get(self.sampling, self.sampling)
+        title = model_type if ahead is None else f"{model_type} ({sampling_letter}{ahead})"
         plt.title(title)
         plt.tight_layout()