diff --git a/modules/Visualization/R/plot_extreme_probs.R b/modules/Visualization/R/plot_extreme_probs.R
index bf561020857245b75c396db3e0258e4603a52a42..d0d38e5db3c25005c511e3f978982f8ef21ba447 100644
--- a/modules/Visualization/R/plot_extreme_probs.R
+++ b/modules/Visualization/R/plot_extreme_probs.R
@@ -231,7 +231,7 @@ plot_extreme_probs <- function(recipe, fcst,
             }
             # Plots
             ## TODO: Should not be forecast ensemble mean...
-            output_configuration <- output_conf$multipanel$forecast_ensemble_mean
+            output_configuration <- output_conf$multipanel$extreme_probabilities
             base_args <- list(fun = "VizEquiMap",
                               plot_dims = c('longitude', 'latitude'),
                               var = i_var_fcst, lon = longitude,
@@ -279,7 +279,7 @@ plot_extreme_probs <- function(recipe, fcst,
                                 col_inf = cols_1[1],
                                 col_sup = cols_2[length(cols_2)])
             }
-            output_configuration <- output_conf[[projection]]$forecast_ensemble_mean
+            output_configuration <- output_conf[[projection]]$extreme_probabilities
             base_args[names(output_configuration)] <- output_configuration
             # Loop over forecast times
             for (i in 1:length(time_labels)) {  
diff --git a/modules/Visualization/R/plot_forecast_map.R b/modules/Visualization/R/plot_forecast_map.R
index 28b9dead16eba04ba8b6846a6a8ad95a16b3a703..d41e5646b6dfad6f4fb1bc0663f3af1c6be40dd1 100644
--- a/modules/Visualization/R/plot_forecast_map.R
+++ b/modules/Visualization/R/plot_forecast_map.R
@@ -191,7 +191,7 @@ plot_forecast_map <- function(recipe, fcst, mask = NULL, dots = NULL,
                              "\n", "Forecast Ensemble ", method, "/ ", "Init.: ", i_syear)
         }
         # Plots
-        output_configuration <- output_conf$multipanel$forecast_ensemble_mean
+        output_configuration <- output_conf$multipanel$forecast_map
         base_args <- list(fun = "VizEquiMap",
                           plot_dims = c('longitude', 'latitude'),
                           var = i_var_fcst, lon = longitude,
@@ -235,7 +235,7 @@ plot_forecast_map <- function(recipe, fcst, mask = NULL, dots = NULL,
                             style = 'point', brks = brks, cols = cols,
                             dots_size = 0.2, dots_shape = 47)
         }
-        output_configuration <- output_conf[[projection]]$forecast_ensemble_mean
+        output_configuration <- output_conf[[projection]]$forecast_map
         base_args[names(output_configuration)] <- output_configuration
         # Loop over forecast times
         for (i in 1:length(time_labels)) {  
diff --git a/modules/Visualization/output_size.yml b/modules/Visualization/output_size.yml
index 6526591678216e4bc4bbcc50ccc0eb6fc75289f1..bbec8dac9f8207be9befb8d473df4ed68280c422 100644
--- a/modules/Visualization/output_size.yml
+++ b/modules/Visualization/output_size.yml
@@ -7,7 +7,7 @@
 # region:
 #   <name_of_region>: (name of the region you will specify in the recipe)
 #     <projection>: (cylindrical_equidistant, robinson, stereographic, lambert_europe)
-#       <plot_type>: (can be skill_metrics, forecast_ensemble_mean or most_likely_terciles)
+#       <plot_type>: (can be skill_metrics, forecast_map, most_likely_terciles or extreme_probabilities)
 #         parameter1: value
 #         parameter2: value
 #         ...
@@ -31,7 +31,7 @@ region: #units inches
         dot_symbol: 4
         font.main: 1
         colNA: "white"
-      forecast_ensemble_mean:
+      forecast_map:
         width: 8.5
         height: 8.5
         axes_label_scale: 0.8
@@ -47,14 +47,27 @@ region: #units inches
         dot_size: 2
         plot_margin: !expr c(0, 4.1, 4.1, 2.1)
         colNA: "white"
+      extreme_probabilities:
+        width: 8.5
+        height: 8.5
+        axes_label_scale: 0.8
+        bar_label_scale: 1.2
+        bar_extra_margin: !expr c(2,1,0.5,1)
+        dot_symbol: 4
+        dot_size: 1.7
+        font.main: 1
+        colNA: "white"
     multipanel:
-      forecast_ensemble_mean: 
+      forecast_map: 
+        width: 8.5
+        height: 8.5
+      extreme_probabilities: 
         width: 8.5
         height: 8.5
     robinson:
       skill_metrics: {width: 8, height: 5}
       colNA: "white"
-  NA-EU: #Norht Atlantic European region
+  NA-EU: #North Atlantic European region
   Iberia: #latmin: 34, latmax: 46, lonmin: -10, lonmax: 5
     cylindrical_equidistant:
       skill_metrics:
@@ -69,7 +82,7 @@ region: #units inches
         dot_symbol: 4
         font.main: 1
         colNA: "white"
-      forecast_ensemble_mean:
+      forecast_map:
         width: 8
         height: 7.5
         intylat: 2
@@ -90,8 +103,20 @@ region: #units inches
         plot_margin: !expr c(2, 5, 7.5, 5) 
         bar_extra_margin: !expr c(2.5, 1, 0.5, 1) # colorbar proportions
         colNA: "white"
+      extreme_probabilities:
+        width: 8
+        height: 7.5
+        intylat: 2
+        intxlon: 2
+        axes_label_scale: 0.8
+        bar_label_scale: 1.2
+        bar_extra_margin: !expr c(2, 1, 0.5, 1)
+        dot_symbol: 4
+        dot_size: 1.7
+        font.main: 1
+        colNA: "white"
     multipanel:
-      forecast_ensemble_mean: 
+      forecast_map: 
         width: 8.5
         height: 9.5
         title_margin_scale: 4
@@ -99,6 +124,10 @@ region: #units inches
         width: 8.5
         height: 9.5
         title_margin_scale: 4
+      extreme_probabilities: 
+        width: 8.5
+        height: 9.5
+        title_margin_scale: 4
     robinson:
       skill_metrics: {width: 8, height: 5}
       colNA: "white"