diff --git a/modules/Saving/Saving.R b/modules/Saving/Saving.R
index 7d0520c239faaffeddcd4fe479b6c2a3fbe771cd..fc9fe4eebd0d51f1b33a9a397a566d424215d99c 100644
--- a/modules/Saving/Saving.R
+++ b/modules/Saving/Saving.R
@@ -44,8 +44,8 @@ Saving <- function(recipe, data,
 
   # Separate ensemble correlation from the rest of the metrics, as it has one
   # extra dimension "ensemble" and must be saved to a different file
-  if ("corr" %in% names(skill_metrics)) {
-    corr_metric_names <- grep("^corr", names(skill_metrics))
+  if ("corr_individual_members" %in% names(skill_metrics)) {
+    corr_metric_names <- grep("^corr_individual_members", names(skill_metrics))
     corr_metrics <- skill_metrics[corr_metric_names]
     skill_metrics <- skill_metrics[-corr_metric_names]
     if (length(skill_metrics) == 0) {
diff --git a/modules/Skill/Skill.R b/modules/Skill/Skill.R
index fd27ba75d46dd19710d0506345e4e32a4c9439e8..2b3fb1de0c4b234db1da9b7f00a02bb2eb2c956f 100644
--- a/modules/Skill/Skill.R
+++ b/modules/Skill/Skill.R
@@ -77,7 +77,7 @@ Skill <- function(recipe, data, agg = 'global') {
       Fair <- F
     }
     # Whether to compute correlation for the ensemble mean or for each member
-    if (metric == 'corr') {
+    if (metric == 'corr_individual_members') {
       memb <- T
     } else if (metric == 'enscorr') {
       memb <- F
@@ -208,7 +208,7 @@ Skill <- function(recipe, data, agg = 'global') {
       skill_metrics[[ metric ]] <- skill$biasSS
       skill_metrics[[ paste0(metric, "_significance") ]] <- skill$sign
     # Ensemble mean correlation
-    } else if (metric %in% c('enscorr', 'corr')) {
+    } else if (metric %in% c('enscorr', 'corr_individual_members')) {
       ## TODO: Return significance
       ## TODO: Implement option for Kendall and Spearman methods?
       skill <- s2dv::Corr(data$hcst$data, data$obs$data, 
@@ -315,7 +315,7 @@ Skill <- function(recipe, data, agg = 'global') {
                                   "/outputs/Skill/")
   # Separate 'corr' from the rest of the metrics because of extra 'ensemble' dim
   if (recipe$Analysis$Workflow$Skill$save == 'all') {
-    corr_metric_names <- grep("^corr", names(skill_metrics))
+    corr_metric_names <- grep("^corr_individual_members", names(skill_metrics))
     if (length(corr_metric_names) == 0) {
       save_metrics(recipe = recipe, skill = skill_metrics,
                    data_cube = data$hcst, agg = agg)
diff --git a/tests/recipes/recipe-decadal_monthly_3.yml b/tests/recipes/recipe-decadal_monthly_3.yml
index fc42cd2d85261399547a90d124d32439344d4b8d..f7ab5fc1a565092d042a9535ed6c72020072f026 100644
--- a/tests/recipes/recipe-decadal_monthly_3.yml
+++ b/tests/recipes/recipe-decadal_monthly_3.yml
@@ -37,7 +37,7 @@ Analysis:
       method: 'evmos'
       save: 'none'
     Skill:
-      metric: BSS10 Corr
+      metric: BSS10 Corr_Individual_Members
       save: 'none'
     Probabilities:
       percentiles: [[1/3, 2/3]]
diff --git a/tests/recipes/recipe-seasonal_downscaling.yml b/tests/recipes/recipe-seasonal_downscaling.yml
index 1a2a3110cf2414b5c2d3052b0c8be4a1b39a3a35..dc41adc2800030da41a69503bcc0747e94112dce 100644
--- a/tests/recipes/recipe-seasonal_downscaling.yml
+++ b/tests/recipes/recipe-seasonal_downscaling.yml
@@ -29,7 +29,7 @@ Analysis:
       cross_validation: 
       save: 'none'
     Calibration:
-      method: 'none'
+      method: 'raw'
       save: 'none'
     Skill:
       metric: BSS10 CRPSS RPSS mean_bias
@@ -44,7 +44,7 @@ Analysis:
       log_reg_method:
       nanalogs: 3
       target_grid: /esarchive/recon/ecmwf/era5/daily_mean/tas_f1h/tas_199301.nc
-      save: 'none'
+      save: 'all'
   Output_format: S2S4E
 Run:
   Loglevel: INFO
diff --git a/tests/recipes/recipe-seasonal_monthly_1.yml b/tests/recipes/recipe-seasonal_monthly_1.yml
index 0edf4795764bf101cd3bd67de17e66065fc8602a..99acb16cb8dc6d61dc0f388678db297c936ee98d 100644
--- a/tests/recipes/recipe-seasonal_monthly_1.yml
+++ b/tests/recipes/recipe-seasonal_monthly_1.yml
@@ -36,7 +36,7 @@ Analysis:
       method: mse_min
       save: 'all'
     Skill:
-      metric: RPSS CRPSS EnsCorr Corr Enscorr_specs
+      metric: RPSS CRPSS EnsCorr Corr_individual_members Enscorr_specs
       save: 'all'
     Probabilities:
       percentiles: [[1/3, 2/3], [1/10, 9/10]]
diff --git a/tests/testthat/test-decadal_monthly_3.R b/tests/testthat/test-decadal_monthly_3.R
index d1b42fd5c763b5f35863afca1695aee3fbbd13ee..3cdc826aa4231a2a3dc51a68a1cc4068451b732a 100644
--- a/tests/testthat/test-decadal_monthly_3.R
+++ b/tests/testthat/test-decadal_monthly_3.R
@@ -133,7 +133,8 @@ TRUE
 )
 expect_equal(
 names(skill_metrics),
-c("bss10", "bss10_significance", "corr", "corr_significance")
+c("bss10", "bss10_significance",
+  "corr_individual_members", "corr_individual_members_significance")
 )
 expect_equal(
 class(skill_metrics[[1]]),
@@ -157,7 +158,7 @@ any(as.vector(skill_metrics$bss10_significance)),
 FALSE
 )
 expect_equal(
-as.vector(skill_metrics$corr[2, , , 1, 2]),
+as.vector(skill_metrics$corr_individual_members[2, , , 1, 2]),
 c(-0.2015265, 0.4635463, -0.1019575),
 tolerance = 0.0001
 )
diff --git a/tests/testthat/test-seasonal_monthly.R b/tests/testthat/test-seasonal_monthly.R
index d112acf9a9187bb073de5c1c84778f4d5f74ae8a..d9b7b3c3857f4d79df127f4be135c25c0b77818c 100644
--- a/tests/testthat/test-seasonal_monthly.R
+++ b/tests/testthat/test-seasonal_monthly.R
@@ -185,7 +185,8 @@ TRUE
 expect_equal(
 names(skill_metrics),
 c("rpss", "rpss_significance", "crpss", "crpss_significance", "enscorr",
-  "enscorr_significance", "corr", "corr_significance", "enscorr_specs")
+  "enscorr_significance", "corr_individual_members", "corr_individual_members_significance",
+  "enscorr_specs")
 )
 expect_equal(
 class(skill_metrics$rpss),