diff --git a/modules/Loading/R/get_timeidx.R b/modules/Loading/R/get_forecast_times.R
similarity index 87%
rename from modules/Loading/R/get_timeidx.R
rename to modules/Loading/R/get_forecast_times.R
index 2796b2021d3ce341508a6ec11ab4799cb2a53188..621c7d2778596255a3dc7b5f883dcddf20fbccd3 100644
--- a/modules/Loading/R/get_timeidx.R
+++ b/modules/Loading/R/get_forecast_times.R
@@ -2,17 +2,19 @@
 #'to the start dates, min. and max. leadtimes and 
 #'time frequency.
 # 
+#'The leadtimes are returned as dates in POSIXct format,
+#'so that they can be read by Start().
 #'The leadtimes are defined by months
-#'Ex. 20201101 with leadtimes 1-4 corresponds to 
-#'the forecasting times covering November to february
 #'
 #'@param sdates vector containind the start dates
 #'@param ltmin first leadtime
 #'@param ltmax last leadtime
 #'@param time_freq time frequency ("monthly_mean" or "daily_mean" or "daily")
+#'@param ncores number of cores to use for parallel computation
 
-get_timeidx <- function(sdates, ltmin, ltmax, 
-                        time_freq="monthly_mean") {
+get_forecast_times <- function(sdates, ltmin, ltmax, 
+                               time_freq="monthly_mean",
+                               ncores = 1) {
 
   if (time_freq %in% c("daily_mean", "daily")) {
 
@@ -55,7 +57,7 @@ get_timeidx <- function(sdates, ltmin, ltmax,
                    output_dims = c("time"),
                    idx_min = ltmin - 1,
                    idx_max = ltmax - 1,
-                   ncores = recipe$Analysis$ncores
+                   ncores = ncores
                    )[[1]]
     indxs_dims <- dim(indxs)
     indxs <- as.POSIXct(indxs, origin = "1970-01-01", tz = "UTC")
diff --git a/modules/Loading/R/load_decadal.R b/modules/Loading/R/load_decadal.R
index c55688e01dc480bd6440fae78d4fc15ebea87b2d..cdb3d339ab1c4abe05727ba92baf6cb4a82f9119 100644
--- a/modules/Loading/R/load_decadal.R
+++ b/modules/Loading/R/load_decadal.R
@@ -3,7 +3,7 @@ source("modules/Loading/R/get_regrid_params.R")
 source("modules/Loading/R/helper_loading_decadal.R")
 source("modules/Loading/R/dates2load.R")
 source("modules/Loading/R/check_latlon.R")
-source("modules/Loading/R/get_timeidx.R")
+source("modules/Loading/R/get_forecast_times.R")
 source("modules/Loading/R/compare_exp_obs_grids.R")
 
 #====================================================================
diff --git a/modules/Loading/R/load_seasonal.R b/modules/Loading/R/load_seasonal.R
index 1e6c9367be006160210168efb9d524ccacccd874..1824b7d5b9408bca1be3b2374e702ca6a3cf55ba 100644
--- a/modules/Loading/R/load_seasonal.R
+++ b/modules/Loading/R/load_seasonal.R
@@ -1,7 +1,7 @@
 # Load required libraries/funs
 source("modules/Loading/R/get_regrid_params.R")
 source("modules/Loading/R/dates2load.R")
-source("modules/Loading/R/get_timeidx.R")
+source("modules/Loading/R/get_forecast_times.R")
 source("modules/Loading/R/check_latlon.R")
 source("modules/Loading/R/compare_exp_obs_grids.R")
 
@@ -27,16 +27,16 @@ load_seasonal <- function(recipe) {
   sdates <- dates2load(recipe, recipe$Run$logger)
   
   idxs <- NULL
-  idxs$hcst <- get_timeidx(sdates$hcst,
-                           recipe$Analysis$Time$ftime_min,
-                           recipe$Analysis$Time$ftime_max,
-                           time_freq=store.freq)
+  idxs$hcst <- get_forecast_times(sdates$hcst,
+                                  recipe$Analysis$Time$ftime_min,
+                                  recipe$Analysis$Time$ftime_max,
+                                  time_freq=store.freq)
 
   if (!(is.null(sdates$fcst))) {
-    idxs$fcst <- get_timeidx(sdates$fcst,
-                             recipe$Analysis$Time$ftime_min,
-                             recipe$Analysis$Time$ftime_max,
-                             time_freq=store.freq)
+    idxs$fcst <- get_forecast_times(sdates$fcst,
+                                    recipe$Analysis$Time$ftime_min,
+                                    recipe$Analysis$Time$ftime_max,
+                                    time_freq=store.freq)
   }
 
   # get datasets dict:
diff --git a/modules/Loading/R/load_subseasonal.R b/modules/Loading/R/load_subseasonal.R
index da316a61b8a447fc8ad6e4ba4a2160e17ef15fba..dba21ee1e868fab210e4158377b31c32a216ba2d 100644
--- a/modules/Loading/R/load_subseasonal.R
+++ b/modules/Loading/R/load_subseasonal.R
@@ -33,7 +33,7 @@ load_subseasonal <- function(recipe) {
   ##fcst.name <- recipe$Analysis$Datasets$System[[sys]]$name
   
   # get datasets dict:
-  archive <-get_archive(recipe) # read_yaml("conf/archive_subseasonal.yml")[[recipe$Run$filesystem]]
+  archive <- get_archive(recipe) # read_yaml("conf/archive_subseasonal.yml")[[recipe$Run$filesystem]]
   exp_descrip <- archive$System[[exp.name]]
   
   freq.hcst <- unlist(exp_descrip[[store.freq]][variable[1]])
diff --git a/modules/Loading/R/load_tas_tos.R b/modules/Loading/R/load_tas_tos.R
index d035f05d04a89afbf6f950a98559227d7293ff9f..c19b79923bdc5a676b5b071bcfbd8cb095bb5a25 100644
--- a/modules/Loading/R/load_tas_tos.R
+++ b/modules/Loading/R/load_tas_tos.R
@@ -1,7 +1,7 @@
 # Load required libraries/funs
 source("modules/Loading/R/get_regrid_params.R")
 source("modules/Loading/R/dates2load.R")
-source("modules/Loading/R/get_timeidx.R")
+source("modules/Loading/R/get_forecast_times.R")
 source("modules/Loading/R/check_latlon.R")
 source('modules/Loading/R/mask_tas_tos.R')
 source("modules/Loading/R/compare_exp_obs_grids.R")
@@ -37,16 +37,16 @@ load_tas_tos <- function(recipe) {
   sdates <- dates2load(recipe, recipe$Run$logger)
   
   idxs <- NULL
-  idxs$hcst <- get_timeidx(sdates$hcst,
-                           recipe$Analysis$Time$ftime_min,
-                           recipe$Analysis$Time$ftime_max,
-                           time_freq = store.freq)
+  idxs$hcst <- get_forecast_times(sdates$hcst,
+                                  recipe$Analysis$Time$ftime_min,
+                                  recipe$Analysis$Time$ftime_max,
+                                  time_freq = store.freq)
   
   if (!(is.null(sdates$fcst))) {
-    idxs$fcst <- get_timeidx(sdates$fcst,
-                             recipe$Analysis$Time$ftime_min,
-                             recipe$Analysis$Time$ftime_max,
-                             time_freq = store.freq)
+    idxs$fcst <- get_forecast_times(sdates$fcst,
+                                    recipe$Analysis$Time$ftime_min,
+                                    recipe$Analysis$Time$ftime_max,
+                                    time_freq = store.freq)
   }
   
   # get esarchive datasets dict:
diff --git a/tests/testthat/test-utils-get_forecast_times.R b/tests/testthat/test-utils-get_forecast_times.R
new file mode 100644
index 0000000000000000000000000000000000000000..89e6dbc6dc6eb4994c1fb43ee2dc2bfbccbc7590
--- /dev/null
+++ b/tests/testthat/test-utils-get_forecast_times.R
@@ -0,0 +1,113 @@
+context("get_forecast_times.R")
+
+source("tools/libs.R")
+source("modules/Loading/R/get_forecast_times.R")
+source("modules/Loading/R/dates2load.R")
+###########################################
+
+sdates <- list()
+sdates$fcst <- "20250501"
+dim(sdates$fcst) <- c(sday = 1, sweek = 1, syear = 1)
+sdates$hcst <- paste0(1993:2016, "0501")
+dim(sdates$hcst) <- c(sday = 1, sweek = 1, syear = length(1993:2016))
+
+test_that("1. Seasonal daily, 6 months", {
+  ltmin <- 1
+  ltmax <- 6
+  time_freq <- "daily_mean"
+
+  idxs <- list()
+  idxs$hcst <- get_forecast_times(sdates = sdates$hcst,
+                                  ltmin = ltmin,
+                                  ltmax = ltmax,
+                                  time_freq = time_freq)
+
+  idxs$fcst <- get_forecast_times(sdates = sdates$fcst,
+                                  ltmin = ltmin,
+                                  ltmax = ltmax,
+                                  time_freq = time_freq)
+  # Results
+  expect_equal(
+    dim(idxs$hcst),
+    c(file_date = 24, time = 184)
+  )
+  expect_equal(
+    as.character(idxs$hcst[1]),
+    "1993-05-01 12:01:00"
+  )
+  expect_equal(
+    as.character(idxs$hcst[24, 2]),
+    "2016-05-02 12:01:00"
+  )
+  expect_equal(
+    as.character(idxs$hcst[4, 91]),
+    "1996-07-30 12:01:00"
+  )
+  expect_equal(
+    dim(idxs$fcst),
+    c(file_date = 1, time = 184)
+  )
+  expect_equal(
+    as.character(idxs$fcst[1]),
+    "2025-05-01 12:01:00"
+  )
+  expect_equal(
+    as.character(idxs$fcst[1, 2]),
+    "2025-05-02 12:01:00"
+  )
+  expect_equal(
+    as.character(idxs$fcst[1, 91]),
+    "2025-07-30 12:01:00"
+  )
+})
+
+
+sdates <- list()
+sdates$fcst <- "20231201"
+dim(sdates$fcst) <- c(sday = 1, sweek = 1, syear = 1)
+sdates$hcst <- paste0(1993:1996, "1201")
+dim(sdates$hcst) <- c(sday = 1, sweek = 1, syear = length(1993:1996))
+
+test_that("2. Seasonal monthly, 2 months, end of year", {
+  ltmin <- 1
+  ltmax <- 2
+  time_freq <- "monthly_mean"
+
+  idxs <- list()
+  idxs$hcst <- get_forecast_times(sdates = sdates$hcst,
+                                  ltmin = ltmin,
+                                  ltmax = ltmax,
+                                  time_freq = time_freq)
+
+  idxs$fcst <- get_forecast_times(sdates = sdates$fcst,
+                                  ltmin = ltmin,
+                                  ltmax = ltmax,
+                                  time_freq = time_freq)
+  # Results
+  expect_equal(
+    dim(idxs$hcst),
+    c(time = 2, file_date = 4)
+  )
+  expect_equal(
+    as.character(idxs$hcst[1, ]),
+    c("1993-12-16 12:01:00", "1994-12-16 12:01:00",
+      "1995-12-16 12:01:00", "1996-12-16 12:01:00")
+  )
+  expect_equal(
+    as.character(idxs$hcst[2, ]),
+    c("1994-01-16 12:01:00", "1995-01-16 12:01:00",
+      "1996-01-16 12:01:00", "1997-01-16 12:01:00")
+  )
+  expect_equal(
+    dim(idxs$fcst),
+    c(time = 2, file_date = 1)
+  )
+  expect_equal(
+    as.character(idxs$fcst[1, ]),
+    "2023-12-16 12:01:00"
+  )
+  expect_equal(
+    as.character(idxs$fcst[2, ]),
+    "2024-01-16 12:01:00"
+  )
+})