diff --git a/modules/Visualization/R/plot_extreme_probs.R b/modules/Visualization/R/plot_extreme_probs.R
index 7397898246957832d52ed89f1d019f0dcc94340d..5669efd85017d8ecde94449260c7417f28298397 100644
--- a/modules/Visualization/R/plot_extreme_probs.R
+++ b/modules/Visualization/R/plot_extreme_probs.R
@@ -208,7 +208,13 @@ plot_extreme_probs <- function(recipe, fcst,
                                               indices = var,
                                               drop = 'selected')
             dim_dots <- dim(var_dots)
-            var_dots <- as.numeric(var_dots >= 0)
+            if (recipe$Analysis$Workflow$Visualization$dots_on_points == "significant") {
+              var_dots <- as.numeric(var_dots <= 0)
+              dots_caption <- "Dots indicate negative RPSS"
+            } else { # "non-significant"
+              var_dots <- as.numeric(var_dots > 0)
+              dots_caption <- "Dots indicate positive RPSS"
+            }
             dim(var_dots) <- dim_dots
           } else {
             var_dots <- NULL
@@ -284,7 +290,7 @@ plot_extreme_probs <- function(recipe, fcst,
               fun <- VizEquiMap
               base_args <- list(data = NULL, dots = NULL, mask = NULL,
                                 lon = longitude, lat = latitude,
-                                dot_symbol = 20, title_scale = 0.6,
+                                dot_symbol = 4, title_scale = 0.6,
                                 font.main = 2, margin_scale = c(1, 5, 5, 5),
                                 filled.continents = F, brks = brks, cols = cols,
                                 bar_label_digits = 4, bar_label_scale = 1.5,
@@ -306,7 +312,7 @@ plot_extreme_probs <- function(recipe, fcst,
                                 lon_dim = 'longitude', lat_dim = 'latitude',
                                 target_proj = target_proj, drawleg = 'bar',
                                 style = 'point', brks = brks, cols = cols,
-                                dot_size = 0.2, dot_symbol = 47,
+                                dot_size = 0.2, dot_symbol = 4,
                                 col_inf = cols_1[1],
                                 col_sup = cols_2[length(cols_2)])
             }
@@ -361,7 +367,7 @@ plot_extreme_probs <- function(recipe, fcst,
                        "Reference: ", recipe$Analysis$Datasets$Reference,
                        " [", recipe$Analysis$Time$hcst_start, " - ",
                        recipe$Analysis$Time$hcst_end, "]",
-                       "\n", " ")
+                       "\n", if (!is.null(dots)) dots_caption else " ")
               # Modify base arguments
               base_args[[1]] <- i_var_fcst[i, , ]
               if (is.null(attributes(fcst$attrs$time_bounds))) {
diff --git a/modules/Visualization/R/plot_forecast_map.R b/modules/Visualization/R/plot_forecast_map.R
index e86800c10d783510dc6324c74840df3492983443..7ba2e88201bf8cad332bcdf1be7a6786390315ce 100644
--- a/modules/Visualization/R/plot_forecast_map.R
+++ b/modules/Visualization/R/plot_forecast_map.R
@@ -159,7 +159,13 @@ plot_forecast_map <- function(recipe, fcst, mask = NULL, dots = NULL,
                                           indices = var,
                                           drop = 'selected')
         dim_dots <- dim(var_dots)
-        var_dots <- as.numeric(var_dots <= 0)
+        if (recipe$Analysis$Workflow$Visualization$dots_on_points == "significant") {
+          var_dots <- as.numeric(var_dots <= 0)
+          dots_caption <- "Dots indicate negative RPSS"
+        } else { # "non-significant"
+          var_dots <- as.numeric(var_dots > 0)
+          dots_caption <- "Dots indicate positive RPSS"
+        }
         dim(var_dots) <- dim_dots
       } else {
         var_dots <- NULL
@@ -231,7 +237,7 @@ plot_forecast_map <- function(recipe, fcst, mask = NULL, dots = NULL,
           fun <- VizEquiMap
           base_args <- list(data = NULL, dots = NULL, mask = NULL,
                             lon = longitude, lat = latitude,
-                            dot_symbol = 20, title_scale = 0.7,
+                            dot_symbol = 4, title_scale = 0.7,
                             font.main = 2, margin_scale = c(3, 5, 5, 5),
                             bar_extra_margin = rep(0.9, 4),
                             filled.continents = F, brks = brks, cols = cols,
@@ -251,7 +257,7 @@ plot_forecast_map <- function(recipe, fcst, mask = NULL, dots = NULL,
                             lon_dim = 'longitude', lat_dim = 'latitude',
                             target_proj = target_proj, drawleg = 'bar',
                             style = 'point', brks = brks, cols = cols,
-                            dot_size = 0.2, dot_symbol = 47)
+                            dot_size = 0.2, dot_symbol = 4)
         }
         output_configuration <- output_conf[[projection]]$forecast_map
         base_args[names(output_configuration)] <- output_configuration
@@ -303,7 +309,8 @@ plot_forecast_map <- function(recipe, fcst, mask = NULL, dots = NULL,
                                                   "%d-%m-%Y"), "\n",
                    forecast_time_caption, "\n",
                    "Reference: ", recipe$Analysis$Datasets$Reference, "\n",
-                   "Units: ", units)
+                   "Units: ", units, "\n",
+                   if (!is.null(dots)) dots_caption else " ")
           # Modify base arguments
           base_args[[1]] <- i_var_fcst[i, , ]
           if (is.null(attributes(fcst$attrs$time_bounds))) {
diff --git a/modules/Visualization/R/plot_metrics.R b/modules/Visualization/R/plot_metrics.R
index 6392609cb00cce0a3afe46f6da13ecab479d4492..43b012ddb6405ba84eb2cdbe30717f17193c3496 100644
--- a/modules/Visualization/R/plot_metrics.R
+++ b/modules/Visualization/R/plot_metrics.R
@@ -302,7 +302,7 @@ plot_metrics <- function(recipe, data_cube, metrics,
                             data = asplit(metric, MARGIN = 1),
                             lon = longitude, lat = latitude,
                             special_args = metric_significance,
-                            dot_symbol = 20, toptitle = toptitle,
+                            dot_symbol = 4, toptitle = toptitle,
                             title_scale = 0.6, titles = titles,
                             filled.continents = FALSE, brks = brks,
                             cols = cols, col_inf = col_inf, col_sup = col_sup,
@@ -338,7 +338,7 @@ plot_metrics <- function(recipe, data_cube, metrics,
             fun <- VizEquiMap
             base_args <- list(data = NULL, dots = NULL,
                               lon = longitude, lat = latitude,
-                              dot_symbol = 20, dot_size = 1,
+                              dot_symbol = 4, dot_size = 1,
                               title_scale = 0.6,
                               filled.continents = F, brks = brks, cols = cols, 
                               col_inf = col_inf, col_sup = col_sup, 
@@ -363,7 +363,7 @@ plot_metrics <- function(recipe, data_cube, metrics,
                               target_proj = target_proj, drawleg = 'bar',
                               style = 'point', dots = NULL, brks = brks, 
                               cols = cols, col_inf = col_inf, col_sup = col_sup,
-                              units = units, dot_size = 0.2, dot_symbol = 47)
+                              units = units, dot_size = 0.2, dot_symbol = 4)
           }
           output_configuration <- output_conf[[projection]]$skill_metrics
           base_args[names(output_configuration)] <- output_configuration
@@ -482,11 +482,23 @@ plot_metrics <- function(recipe, data_cube, metrics,
               } else {
                 if (significance == 'dots') {
                   if (projection != 'cylindrical_equidistant') {
-                    base_args[[10]] <- metric_significance[[i]][[1]]
+                    if (recipe$Analysis$Workflow$Visualization$dots_on_points == "significant") {
+                      base_args[[10]] <- metric_significance[[i]][[1]]
+                      dots_caption <- paste0("Dots indicate statistical significance", "\n")
+                    } else { # "non-significant"
+                      base_args[[10]] <- 1 - base_args[[10]]
+                      dots_caption <- paste0("Dots indicate statistical non-significance", "\n")
+                    }
                   } else {
                     # The position of arguments in base_args requires this cond
                     # so VizEquiMap plots dots when requested
-                    base_args[[2]] <- metric_significance[[i]][[1]]
+                    if (recipe$Analysis$Workflow$Visualization$dots_on_points == "significant") {
+                      base_args[[2]] <- metric_significance[[i]][[1]]
+                      dots_caption <- paste0("Dots indicate statistical significance", "\n")
+                    } else {
+                      base_args[[2]] <- 1 - base_args[[2]]
+                      dots_caption <- paste0("Dots indicate statistical non-significance", "\n")
+                    }
                   }
                   sign_file_label <- '_dots'
                 } else if (significance == 'mask') {
@@ -494,7 +506,7 @@ plot_metrics <- function(recipe, data_cube, metrics,
                   sign_file_label <- '_mask'
                 }
               }
-              significance_caption <- "\n alpha = 0.05"
+              significance_caption <- "alpha = 0.05"
             } else {
               significance_caption <- NULL
               sign_file_label <- NULL
@@ -503,7 +515,8 @@ plot_metrics <- function(recipe, data_cube, metrics,
             base_args[['caption']] <- 
               paste0("Nominal start date: ", nominal_startdate_caption, "\n",
                      forecast_time_caption, "\n",
-                     "Reference: ", recipe$Analysis$Datasets$Reference,
+                     "Reference: ", recipe$Analysis$Datasets$Reference,  "\n",
+                     if (significance == 'dots') dots_caption,
                      significance_caption)
             
             fileout <- paste0(outfile, "_ft", forecast_time,
diff --git a/modules/Visualization/R/plot_most_likely_terciles_map.R b/modules/Visualization/R/plot_most_likely_terciles_map.R
index 3f8a41b813169d3da66f1415690e160832e38237..14406085fe924b61dcb3d19b8d3ba819c4b5ce50 100644
--- a/modules/Visualization/R/plot_most_likely_terciles_map.R
+++ b/modules/Visualization/R/plot_most_likely_terciles_map.R
@@ -159,10 +159,17 @@ plot_most_likely_terciles <- function(recipe,
                                             indices = var,
                                             drop = 'selected')
           dim_dots <- dim(var_dots)
-          var_dots <- as.numeric(var_dots <= 0)
+          if (recipe$Analysis$Workflow$Visualization$dots_on_points == "significant") {
+            var_dots <- as.numeric(var_dots <= 0)
+            dots_caption <- "Dots indicate negative RPSS"
+          } else { # "non-significant"
+            var_dots <- as.numeric(var_dots > 0)
+            dots_caption <- "Dots indicate positive RPSS"
+          }
           dim(var_dots) <- dim_dots
       } else {
         var_dots <- NULL
+        dots_caption <- NULL
       }
 
       # Plot title labels look different depending on horizon and aggregation
@@ -350,6 +357,12 @@ plot_most_likely_terciles <- function(recipe,
             tmp$bar_titles <- NULL
             tmp$nmap <- NULL
             tmp$var_limits <- NULL
+            if (i_bar == 1) {
+              if (!is.null(dots_caption)) {
+                mtext(dots_caption, side = 1, line = 12, at = NA, adj = 0,
+                      cex = 0.9, col = "black")
+              }
+            }
             if (length(cb_info$brks[[i_bar]]) > 2) {
               # plot colorbar as normal
               do.call(ColorBar, tmp)
diff --git a/modules/Visualization/Visualization.R b/modules/Visualization/Visualization.R
index 8c50be4585a4cb943918a2839284caec716d6486..6fab018e518b5a12e2d4f23473c0f444c24b7988 100644
--- a/modules/Visualization/Visualization.R
+++ b/modules/Visualization/Visualization.R
@@ -25,7 +25,7 @@ Visualization <- function(recipe,
                           skill_metrics = NULL,
                           statistics = NULL,
                           probabilities = NULL,
-                          significance = F,
+                          significance = FALSE,
                           output_conf = NULL,
                           logo = NULL) {
   # Try to produce and save several basic plots.
@@ -85,6 +85,11 @@ Visualization <- function(recipe,
     recipe$Analysis$Workflow$Visualization$multi_panel <- FALSE
   }
   
+  # Set default dotting of non-significant grid points if not specified
+  if (is.null(recipe$Analysis$Workflow$Visualization$dots_on_points)) {
+    recipe$Analysis$Workflow$Visualization$dots_on_points <- "non-significant"
+  }
+  
   # Warning if significance parameter not included in function call
   if (!missing(significance) && !is.null(recipe$Analysis$Workflow$Visualization$significance)) {
     if (significance != recipe$Analysis$Workflow$Visualization$significance) {
@@ -144,7 +149,7 @@ Visualization <- function(recipe,
     }
   }
 
-  # Plot forecast ensemble mean
+  # Plot forecast map
   if ("forecast_map" %in% plots) {
     if (!is.null(data$fcst)) {
       if (is.null(recipe$Analysis$Workflow$Visualization$mask_ens)) {
@@ -174,11 +179,11 @@ Visualization <- function(recipe,
             c('both', TRUE)) {
           if (is.null(skill_metrics)) {
             error(recipe$Run$logger,
-                  paste0("For the forecast ensemble mean  plot, skill_metrics ",
+                  paste0("For the forecast map plot, skill_metrics ",
                          "needs to be provided to be masked."))
           } else if (!('enscorr' %in% names(skill_metrics))) {
             error(recipe$Run$logger,
-                  paste0("For the forecast ensemble mean plot, enscor metric ",
+                  paste0("For the forecast map plot, enscor metric ",
                          "needs to be provided to be masked."))
           } else {
             plot_forecast_map(recipe, data$fcst,
@@ -193,11 +198,11 @@ Visualization <- function(recipe,
         if (recipe$Analysis$Workflow$Visualization$dots %in% c('both', TRUE)) {
           if (is.null(skill_metrics)) {
             error(recipe$Run$logger,
-                  paste0("For the forecast ensemble mean plot, skill_metrics ",
+                  paste0("For the forecast map plot, skill_metrics ",
                          "needs to be provided for the dots."))
           } else if (!('enscorr' %in% names(skill_metrics))) {
             error(recipe$Run$logger,
-                  paste0("For the forecast ensemble mean plot, enscor metric ",
+                  paste0("For the forecast map plot, enscor metric ",
                          "needs to be provided for the dots."))
           } else {
             plot_forecast_map(recipe, data$fcst,
@@ -211,7 +216,7 @@ Visualization <- function(recipe,
       } ## End loop over methods
     } else {
       error(recipe$Run$logger,
-            paste0("The forecast ensemble mean plot has been requested, but ",
+            paste0("The forecast map plot has been requested, but ",
                    "there is no fcst element in 'data'."))
     }
   }
diff --git a/recipe_template.yml b/recipe_template.yml
index 8df187122fcf4673e66ee75175fecb6e86dde55e..c948cb847ece016b1e9d715a0285f64dbdb7d3b6 100644
--- a/recipe_template.yml
+++ b/recipe_template.yml
@@ -148,8 +148,9 @@ Analysis:
       multi_panel: yes # Multi-panel plot or single-panel plots. Default is 'no/false'. (Optional, bool)
       projection: 'cylindrical_equidistant' # Options: 'cylindrical_equidistant', 'robinson', 'lambert_europe'. Default is cylindrical equidistant. (Optional, str)
       significance: 'dots' # Type of mask for statistical significance. Options are 'dots', and yes/no. 'dots'. 'mask' and 'both' options are not available for projections other than cylindrical_equidistant.
-      mask_terciles: no # Whether to dot or mask the non-significant points by rpss in the most likely tercile plot. yes/true, no/false or 'both'. Default is no/false. (Optional, str)
-      dots_terciles: yes # Whether to dot the non-significant by rpss in the most likely tercile plot. yes/true, no/false or 'both'. Default is no/false. (Optional, str)
+      mask_terciles: no # Whether to mask the non-significant points by rpss in the most likely tercile plot. yes/true, no/false or 'both'. Default is no/false. (Optional, str)
+      dots_terciles: yes # Whether to dot the non-significant points by rpss in the most likely tercile plot. yes/true, no/false or 'both'. Default is no/false. (Optional, str)
+      dots_on_points: "non-significant" # Which grid points to dot, if dots are requested. Either "significant" or "non-significant".
       mask_ens: no # Whether to mask the non-significant points by rpss in the forecast ensemble mean plot. yes/true, no/false or 'both'. Default is no/false. (Optional, str)
       shapefile: # path to a shapefile (*.shp) to include in the plots. Only available for the cylindrical equidistant projection. (Optional, str)
       logo: tools/BSC_logo_95.jpg # path to a logo (*.png or *.jpg/jpeg) to include in the plots. (Optional, str)