diff --git a/.gitignore b/.gitignore
index 752f5cf97a2e597b4d8863bf8cfd55046423eb0f..8fec461d052296bfd1779cceec4e33b7b8893afa 100644
--- a/.gitignore
+++ b/.gitignore
@@ -2,3 +2,5 @@ out-logs/
 *.swp
 *.swo
 /modules/Calibration/test_victoria.R
+modules/Loading/testing_recipes/recipe_decadal_calendartest.yml
+modules/Loading/testing_recipes/recipe_decadal_daily_calendartest.yml
diff --git a/conf/archive.yml b/conf/archive.yml
index 492cde285ae9427ccf438dbe6d8557fe4189fc1e..ac65cb6d80e254e0ead46f63ea53b99c9fe110c0 100644
--- a/conf/archive.yml
+++ b/conf/archive.yml
@@ -14,6 +14,7 @@ archive:
             nmember:
               fcst: 51
               hcst: 25
+            calendar: "proleptic_gregorian"
             reference_grid: "/esarchive/exp/ecmwf/system5c3s/monthly_mean/tas_f6h/tas_20180501.nc"
         system7c3s:
             src: "exp/meteofrance/system7c3s/"
@@ -23,6 +24,7 @@ archive:
             nmember:
               fcst: 51
               hcst: 25
+            calendar: "proleptic_gregorian"
             reference_grid: "conf/grid_description/griddes_system7c3s.txt"
         system21_m1:
             src: "exp/dwd/system21_m1/"
@@ -32,6 +34,7 @@ archive:
             nmember:
               fcst: 50
               hcst: 30
+            calendar: "proleptic_gregorian"
             reference_grid: "conf/grid_description/griddes_system21_m1.txt"
         system35c3s:
             src: "exp/cmcc/system35c3s/"
@@ -41,6 +44,7 @@ archive:
             nmember:
               fcst: 50
               hcst: 40
+            calendar: "proleptic_gregorian"
             reference_grid: "conf/grid_description/griddes_system35c3s.txt"
         system2c3s:
             src: "exp/jma/system2c3s/"
@@ -49,6 +53,7 @@ archive:
             nmember:
               fcst: 10
               hcst: 10
+            calendar: "proleptic_gregorian"
             reference_grid: "conf/grid_description/griddes_system2c3s.txt"
         eccc1:
             src: "exp/eccc/eccc1/"
@@ -57,6 +62,7 @@ archive:
             nmember:
               fcst: 10
               hcst: 10
+            calendar: "proleptic_gregorian"
             reference_grid: "conf/grid_description/griddes_eccc1.txt"
         glosea6_system600-c3s:
             src: "exp/ukmo/glosea6_system600-c3s/"
@@ -65,6 +71,7 @@ archive:
             nmember:
               fcst: 62
               hcst: 28
+            calendar: "proleptic_gregorian"
             reference_grid: "conf/grid_description/griddes_ukmo600.txt"
 
         ncep-cfsv2:
@@ -74,6 +81,7 @@ archive:
             nmember:
               fcst: 20
               hcst: 20
+            calendar: "gregorian"
             reference_grid: "conf/grid_description/griddes_ncep-cfsv2.txt"
     Reference:
         era5: 
@@ -90,6 +98,7 @@ archive:
                            "sfcWind":"_f1h-r1440x721cds/",
                            "tasmax":"_f1h-r1440x721cds/",
                            "tasmin":"_f1h-r1440x721cds/"}
+            calendar: "standard"
             reference_grid: "/esarchive/recon/ecmwf/era5/monthly_mean/tas_f1h-r1440x721cds/tas_201805.nc"
         era5land:
             src: "recon/ecmwf/era5land/"
@@ -98,11 +107,13 @@ archive:
             monthly_mean: {"tas":"_f1h/","tasmin":"_f24h/",
                            "tasmax":"_f24h/", "prlr":"_f1h/",
                            "sfcWind":"_f1h/", "rsds":"_f1h/"}
+            calendar: "proleptic_gregorian"
             reference_grid: "/esarchive/recon/ecmwf/era5land/daily_mean/tas_f1h/tas_201805.nc"
         uerra: 
             src: "recon/ecmwf/uerra_mescan/"
             daily_mean: {"tas":"_f6h/"}
             monthly_mean: {"tas":"_f6h/"}
+            calendar: "proleptic_gregorian"
             reference_grid: "/esarchive/recon/ecmwf/uerra_mescan/daily_mean/tas_f6h/tas_201805.nc"
 
 
diff --git a/conf/archive_decadal.yml b/conf/archive_decadal.yml
index 03e4142546529ab455bb7d1841e2ddc843514f9d..61e3f2b8eb5d781be670d619e2113c9e5619d229 100644
--- a/conf/archive_decadal.yml
+++ b/conf/archive_decadal.yml
@@ -14,7 +14,7 @@ archive:
         daily_mean:
           grid: {"clt":"gr", "hurs":"gr", "hursmin":"gr", "pr":"gr", "psl":"gr", "rsds":"gr", "sfcWind":"gr", "sfcWindmax":"gr", "tas":"gr", "tasmax":"gr", "tasmin":"gr"}
           version: {"clt":"v20190713", "hurs":"v20190713", "hursmin":"v20190713", "pr":"v20190713", "psl":"v20190713", "rsds":"v20190713", "sfcWind":"v20190713", "sfcWindmax":"v20190713", "tas":"v20190713", "tasmax":"v20190713", "tasmin":"v20190713"}
-          calendar: "proleptic_gregorian"
+        calendar: "proleptic_gregorian"
         member: r1i1p1f1,r2i1p1f1,r3i1p1f1,r4i1p1f1,r5i1p1f1,r6i1p1f1,r7i1p1f1,r8i1p1f1,r9i1p1f1,r10i1p1f1
         initial_month: 11
         reference_grid: "/esarchive/exp/ecearth/a1ua/cmorfiles/DCPP/EC-Earth-Consortium/EC-Earth3/dcppA-hindcast/r1i1p1f1/Amon/tas/gr/v20190713/tas_Amon_EC-Earth3_dcppA-hindcast_s1960-r1i1p1f1_gr_196011-196110.nc" #'r512x256'
@@ -33,7 +33,7 @@ archive:
         daily_mean:
           grid: {"pr":"gr", "tas":"gr", "tasmax":"gr", "tasmin":"gr"}
           version:  {"pr":"v20200508", "tas":"v20200731", "tasmax":"v20200730", "tasmin":"v20200730"}
-          calendar: "proleptic_gregorian"
+        calendar: "proleptic_gregorian"
         #NOTE:There are many members but not all of them are available on ESGF (only r6-10 available). Then, we might have some variables for the rest of the members (r1-5 and r11-15), but not for all the variables. That's why i'm only using r6-10
         member: r6i2p1f1,r7i2p1f1,r8i2p1f1,r9i2p1f1,r10i2p1f1
         initial_month: 11
@@ -70,7 +70,7 @@ archive:
         daily_mean:
           grid: {"tas":"gr", "pr":"gr", "psl":"gr"}
           version: {"tas":"v20210910", "pr":"v20210910", "psl":"v20210910"}
-          calendar: "proleptic_gregorian"
+        calendar: "proleptic_gregorian"
         member: r1i4p1f1,r2i4p1f1,r3i4p1f1,r4i4p1f1,r5i4p1f1,r6i4p1f1,r7i4p1f1,r8i4p1f1,r9i4p1f1,r10i4p1f1
         initial_month: 11
         reference_grid: "/esarchive/exp/ecearth/a3w5/original_files/cmorfiles/DCPP/EC-Earth-Consortium/EC-Earth3/dcppA-hindcast/r1i4p1f1/Amon/tas/gr/v20210910/tas_Amon_EC-Earth3_dcppA-hindcast_s1960-r1i4p1f1_gr_196011-196110.nc" 
@@ -89,7 +89,7 @@ archive:
         daily_mean:
           grid: {"tas":"gn"}
           version: {"tasmin":"v20200101", "tasmax":"v20200101", "pr":"v20200417"}
-          calendar: "360-day"
+        calendar: "360-day"
         member: r1i1p1f2,r2i1p1f2,r3i1p1f2,r4i1p1f2,r5i1p1f2,r6i1p1f2,r7i1p1f2,r8i1p1f2,r9i1p1f2,r10i1p1f2
         initial_month: 11
         reference_grid: "/esarchive/exp/CMIP6/dcppA-hindcast/dcppA-hindcast/HadGEM3-GC31-MM/DCPP/MOHC/HadGEM3-GC31-MM/dcppA-hindcast/r1i1p1f2/Amon/tas/gr/v20200316/tas_Amon_HadGEM3_dcppA-hindcast_s2018-r1i1p1f2_gr_201811-202903.nc" #'r432x324'
@@ -108,7 +108,7 @@ archive:
         daily_mean:
           grid: {"pr":"gn", "sfcWind":"gn", "tas":"gn", "tasmax":"gn", "tasmin":"gn", "uas":"gn", "vas":"gn"} 
           version: {"pr":"v20200114", "sfcWind":"v20200101", "tas":"v20200408", "tasmax":"v20200114", "tasmin":"v20200114", "uas":"v20200114", "vas":"v20200114"}
-          calendar: "365_day"
+        calendar: "365_day"
         member: r1i1p1f1,r2i1p1f1,r3i1p1f1,r4i1p1f1,r5i1p1f1,r6i1p1f1,r7i1p1f1,r8i1p1f1
         initial_month: 1 
         reference_grid: "/esarchive/exp/CMIP6/dcppA-hindcast/BCC-CSM2-MR/DCPP/BCC/BCC-CSM2-MR/dcppA-hindcast/r8i1p1f1/Amon/tas/gn/v20200101/tas_Amon_BCC-CSM2-MR_dcppA-hindcast_s2008-r8i1p1f1_gn_200801-201712.nc"
@@ -127,7 +127,7 @@ archive:
         daily_mean:
           grid: {"pr":"gn", "tas":"gn", "tasmax":"gn", "tasmin":"gn"}
           version: {"pr":"v20190429", "tas":"v20190429", "tasmax":"v20190429", "tasmin":"v20190429"}
-          calendar: "365_day"
+        calendar: "365_day"
         member: r1i1p2f1,r2i1p2f1,r3i1p2f1,r4i1p2f1,r5i1p2f1,r6i1p2f1,r7i1p2f1,r8i1p2f1, r9i1p2f1, r10i1p2f1, r11i1p2f1,r12i1p2f1,r13i1p2f1,r14i1p2f1,r15i1p2f1,r16i1p2f1,r17i1p2f1,r18i1p2f1, r19i1p2f1, r20i1p2f1,r21i1p2f1,r22i1p2f1,r23i1p2f1,r24i1p2f1,r25i1p2f1,r26i1p2f1,r27i1p2f1,r28i1p2f1, r29i1p2f1, r30i1p2f1, r31i1p2f1,r32i1p2f1,r33i1p2f1,r34i1p2f1,r35i1p2f1,r36i1p2f1,r37i1p2f1,r38i1p2f1, r39i1p2f1, r40i1p2f1
         initial_month: 1 #next year Jan
         reference_grid: "/esarchive/exp/canesm5/cmip6-dcppA-hindcast_i1p2/original_files/cmorfiles/DCPP/CCCma/CanESM5/dcppA-hindcast/r1i1p2f1/Amon/tas/gn/v20190429/tas_Amon_CanESM5_dcppA-hindcast_s2008-r1i1p2f1_gn_200901-201812.nc"
@@ -145,7 +145,7 @@ archive:
         daily_mean:
           grid:
           version:
-          calendar:
+        calendar: "365_day"
         member: r1i1p1f1,r2i1p1f1,r3i1p1f1,r4i1p1f1,r5i1p1f1,r6i1p1f1,r7i1p1f1,r8i1p1f1, r9i1p1f1, r10i1p1f1, r11i1p1f1,r12i1p1f1,r13i1p1f1,r14i1p1f1,r15i1p1f1,r16i1p1f1,r17i1p1f1,r18i1p1f1, r19i1p1f1, r20i1p1f1,r21i1p1f1,r22i1p1f1,r23i1p1f1,r24i1p1f1,r25i1p1f1,r26i1p1f1,r27i1p1f1,r28i1p1f1, r29i1p1f1, r30i1p1f1, r31i1p1f1,r32i1p1f1,r33i1p1f1,r34i1p1f1,r35i1p1f1,r36i1p1f1,r37i1p1f1,r38i1p1f1, r39i1p1f1, r40i1p1f1
         initial_month: 11
         reference_grid: "/esarchive/exp/ncar/cesm-dple-dcppA-hindcast/cmorfiles/DCPP/NCAR/CESM1-1-CAM5-CMIP5/dcppA-hindcast/r1i1p1f1/Amon/tas/gn/v20200101/tas_Amon_CESM1-1-CAM5-CMIP5_dcppA-hindcast_s2008-r1i1p1f1_gn_200811-201812.nc" 
@@ -163,7 +163,7 @@ archive:
         daily_mean:
           grid: {"pr":"gn", "tasmax":"gn", "tasmin":"gn"}
           version: {"pr":"v20210909", "tasmax":"v20210909", "tasmin":"v20210909"}
-          calendar: "365_day"
+        calendar: "365_day"
         member: r1i1p1f1,r2i1p1f1,r3i1p1f1,r4i1p1f1,r5i1p1f1,r6i1p1f1,r7i1p1f1,r8i1p1f1,r9i1p1f1,r10i1p1f1
         initial_month: 11
         reference_grid: "/esarchive/exp/CMIP6/dcppA-hindcast/CMCC-CM2-SR5/DCPP/CMCC/CMCC-CM2-SR5/dcppA-hindcast/r1i1p1f1/Amon/tas/gn/v20210312/tas_Amon_CMCC-CM2-SR5_dcppA-hindcast_s2008-r1i1p1f1_gn_200811-201812.nc"
@@ -182,7 +182,7 @@ archive:
         daily_mean:
           grid:
           version:
-          calendar:
+        calendar: "365_day"
         member: r1i1p1f1,r2i1p1f1,r3i1p1f1
         initial_month: 11
         reference_grid: "/esarchive/exp/CMIP6/dcppA-hindcast/FGOALS-f3-L/DCPP/CAS/FGOALS-f3-L/dcppA-hindcast/r1i1p1f1/Amon/tas/gr/v20220212/tas_Amon_FGOALS-f3-L_dcppA-hindcast_s1960-r1i1p1f1_gr_196011-197012.nc"
@@ -199,7 +199,7 @@ archive:
         daily_mean:
           grid: {"pr":"gr", "tas":"gr", "tasmax":"gr", "tasmin":"gr"}
           version: {"pr":"v20200108", "tas":"v20200504", "tasmax":"v20200504", "tasmin":"v20200504"}
-          calendar: "gregorian"
+        calendar: "gregorian"
         member: r1i1p1f1,r2i1p1f1,r3i1p1f1,r4i1p1f1,r5i1p1f1,r6i1p1f1,r7i1p1f1,r8i1p1f1,r9i1p1f1,r10i1p1f1
         initial_month: 1
         reference_grid: "/esarchive/exp/CMIP6/dcppA-hindcast/IPSL-CM6A-LR/DCPP/IPSL/IPSL-CM6A-LR/dcppA-hindcast/r1i1p1f1/Amon/tas/gr/v20200504/tas_Amon_IPSL-CM6A-LR_dcppA-hindcast_s2008-r1i1p1f1_gr_200901-201812.nc"
@@ -216,7 +216,7 @@ archive:
         daily_mean:
           grid: {"pr":"gn", "tas":"gn", "tasmax":"gn", "tasmin":"gn"}
           version: {"pr":"v20191217", "tas":"v20200416", "tasmax":"v20200416", "tasmin":"v20200416"}
-          calendar: "standard"
+        calendar: "standard"
         member: r1i1p1f1,r2i1p1f1,r3i1p1f1,r4i1p1f1,r5i1p1f1,r6i1p1f1,r7i1p1f1,r8i1p1f1,r9i1p1f1,r10i1p1f1
         initial_month: 11
         reference_grid: "/esarchive/exp/CMIP6/dcppA-hindcast/MIROC6/DCPP/MIROC/MIROC6/dcppA-hindcast/r1i1p1f1/Amon/tas/gn/v20200417/tas_Amon_MIROC6_dcppA-hindcast_s2008-r1i1p1f1_gn_200811-201812.nc"
@@ -233,7 +233,7 @@ archive:
         daily_mean:
           grid: {"pr":"gn", "tas":"gn", "tasmax":"gn", "tasmin":"gn"}
           version: {"pr":"v20210128", "tas":"v20200320", "tasmax":"v20200101", "tasmin":"v20200101"}
-          calendar: "standard"
+        calendar: "standard"
         member: r1i1p1f1,r2i1p1f1,r3i1p1f1,r4i1p1f1,r5i1p1f1,r6i1p1f1,r7i1p1f1,r8i1p1f1,r9i1p1f1,r10i1p1f1
         initial_month: 11
         reference_grid: "/esarchive/exp/CMIP6/dcppA-hindcast/MPI-ESM1-2-HR/DCPP/MPI-M/MPI-ESM1-2-HR/dcppA-hindcast/r1i1p1f1/Amon/tas/gn/v20200320/tas_Amon_MPI-ESM1-2-HR_dcppA-hindcast_s2008-r1i1p1f1_gn_200811-201812.nc"
@@ -250,7 +250,7 @@ archive:
         daily_mean:
           grid:
           version:
-          calendar:
+        calendar: "proleptic_gregorian"
         member: r1i1p1f1,r2i1p1f1,r3i1p1f1,r4i1p1f1,r5i1p1f1,r6i1p1f1,r7i1p1f1,r8i1p1f1,r9i1p1f1,r10i1p1f1,r11i1p1f1,r12i1p1f1,r13i1p1f1,r14i1p1f1,r15i1p1f1,r16i1p1f1
         initial_month: 11
         reference_grid: "/esarchive/exp/CMIP6/dcppA-hindcast/MPI-ESM1-2-LR/DCPP/MPI-M/MPI-ESM1-2-LR/dcppA-hindcast/r1i1p1f1/Amon/tas/gn/v20200101/tas_Amon_MPI-ESM1-2-LR_dcppA-hindcast_s2008-r1i1p1f1_gn_200811-201812.nc"
@@ -267,7 +267,7 @@ archive:
         daily_mean:
           grid: {"pr":"gn", "tasmax":"gn", "tasmin":"gn"}
           version: {"pr":"v20210122", "tasmax":"v20210122", "tasmin":"v20210122"}
-          calendar: "proleptic_gregorian"
+        calendar: "proleptic_gregorian"
         member: r1i1p1f1,r2i1p1f1,r3i1p1f1,r4i1p1f1,r5i1p1f1,r6i1p1f1,r7i1p1f1,r8i1p1f1,r9i1p1f1,r10i1p1f1
         initial_month: 11
         reference_grid: "/esarchive/exp/CMIP6/dcppA-hindcast/MRI-ESM2-0/DCPP/MRI/MRI-ESM2-0/dcppA-hindcast/r1i1p1f1/Amon/tas/gn/v20200101/tas_Amon_MRI-ESM2-0_dcppA-hindcast_s2008-r1i1p1f1_gn_200811-201312.nc"
@@ -285,7 +285,7 @@ archive:
         daily_mean:
           grid: {"pr":"gn", "tas":"gn", "tasmax":"gn", "tasmin":"gn"}
           version: {"pr":"v20191005", "tas":"v20200320", "tasmax":"v20191005", "tasmin":"v20191005"}
-          calendar: "noleap"
+        calendar: "noleap"
         member: r1i1p1f1,r2i1p1f1,r3i1p1f1,r4i1p1f1,r5i1p1f1,r6i1p1f1,r7i1p1f1,r8i1p1f1,r9i1p1f1,r10i1p1f1
         initial_month: 10
         reference_grid: "/esarchive/exp/CMIP6/dcppA-hindcast/NorCPM1/DCPP/NCC/NorCPM1/dcppA-hindcast/r1i1p1f1/Amon/tas/gn/v20200320/tas_Amon_NorCPM1_dcppA-hindcast_s2008-r1i1p1f1_gn_200810-201812.nc"
@@ -302,7 +302,7 @@ archive:
         daily_mean:
           grid: {"pr":"gn", "tas":"gn", "tasmax":"gn", "tasmin":"gn"}
           version: {"pr":"v20191005", "tas":"v20200101", "tasmax":"v20191005", "tasmin":"v20191005"}
-          calendar: "noleap"
+        calendar: "noleap"
         member: r1i2p1f1,r2i2p1f1,r3i2p1f1,r4i2p1f1,r5i2p1f1,r6i2p1f1,r7i2p1f1,r8i2p1f1,r9i2p1f1,r10i2p1f1
         initial_month: 10
         reference_grid: "/esarchive/exp/CMIP6/dcppA-hindcast/NorCPM1/DCPP/NCC/NorCPM1/dcppA-hindcast/r1i2p1f1/Amon/pr/gn/v20200101/pr_Amon_NorCPM1_dcppA-hindcast_s2008-r1i2p1f1_gn_200810-201812.nc"
@@ -315,8 +315,8 @@ archive:
         src: "obs/noaa/ghcn_v4/"
         monthly_mean: {"tas":"", "tasanomaly":""}
         daily_mean:
+        calendar: "gregorian"
         reference_grid: "/esarchive/obs/noaa/ghcn_v4/monthly_mean/tasanomaly/tasanomaly_201811.nc"
-
 # ----
       ERA5:
         src: "recon/ecmwf/era5/"
@@ -324,7 +324,7 @@ archive:
         daily_mean: {"tas":"_f1h-r1440x721cds/", "rsds":"_f1h-r1440x721cds/",
                      "prlr":"_f1h-r1440x721cds/", "sfcWind":"_f1h-r1440x721cds/",
                      "tos":"_f1h-r1440x721cds"}
-        calendar: "proleptic_gregorian"
+        calendar: "gregorian"
         reference_grid: "/esarchive/recon/ecmwf/era5/monthly_mean/tas_f1h-r1440x721cds/tas_201805.nc"
 
 # ----
@@ -344,6 +344,7 @@ archive:
         src: "obs/noaa-nasa/ghcnersstgiss/"
         monthly_mean: {"tasanomaly":""}
         daily_mean:
+        calendar: "standard"
         reference_grid: "/esarchive/obs/noaa-nasa/ghcnersstgiss/monthly_mean/tasanomaly_200811.nc"
 
 # ----
@@ -351,6 +352,7 @@ archive:
         src: "obs/ukmo/hadcrut_v4.6/"
         monthly_mean: {"tasanomaly":""}
         daily_mean:
+        calendar: "standard"
         reference_grid: "/esarchive/obs/ukmo/hadcrut_v4.6/monthly_mean/tasanomaly/tasanomaly_200811.nc"
 
 # ----
@@ -358,5 +360,6 @@ archive:
         src: "obs/ukmo/hadslp_v2/"
         monthly_mean: {"psl":""}
         daily_mean:
+        calendar: "proleptic_gregorian"
         reference_grid: "/esarchive/obs/ukmo/hadslp_v2/monthly_mean/psl_200811.nc"
 
diff --git a/modules/Loading/Loading.R b/modules/Loading/Loading.R
index 8f0c4626db0cb59456b9591d271547758875e8d5..aaf4d91692445ceec16baf5c8af19ec5d3e1057b 100644
--- a/modules/Loading/Loading.R
+++ b/modules/Loading/Loading.R
@@ -289,9 +289,9 @@ load_datasets <- function(recipe_file) {
   dim(obs) <- default_dims
  
   # Convert obs to s2dv_cube
-
-  # Check for consistency between hcst and obs grid
   obs <- as.s2dv_cube(obs)
+  
+  # Check for consistency between hcst and obs grid
   if (!(recipe$Analysis$Regrid$type == 'none')) {
     if (!identical(as.vector(hcst$lat), as.vector(obs$lat))) {
       stop("hcst and obs don't share the same latitude.")
@@ -301,6 +301,8 @@ load_datasets <- function(recipe_file) {
     }
   }
 
+  
+
   # Print a summary of the loaded data for the user, for each object
   data_summary(hcst, store.freq)
   data_summary(obs, store.freq)
diff --git a/modules/Loading/Loading_decadal.R b/modules/Loading/Loading_decadal.R
index f188c198810478f136f9e9652c165b04fb50903b..7f99ac68b130a9fa2cd1073a645feac4872531ab 100644
--- a/modules/Loading/Loading_decadal.R
+++ b/modules/Loading/Loading_decadal.R
@@ -54,7 +54,7 @@ load_datasets <- function(recipe_file) {
                                    ftimemax = as.numeric(recipe$Analysis$Time$ftime_max),
                                    initial_month = archive$System[[exp.name]]$initial_month,
                                    sdates = sdates_hcst,
-                                   calendar = archive$System[[exp.name]][[store.freq]]$calendar)
+                                   calendar = archive$System[[exp.name]]$calendar)
   }
 
 #NOTE: May be used in the future
diff --git a/modules/Saving/Saving.R b/modules/Saving/Saving.R
index 03288a8e053d01ff72557cf90e114c5de3c088c7..a301a1e6eb8b7c1d96427d7a92404343efd8b562 100644
--- a/modules/Saving/Saving.R
+++ b/modules/Saving/Saving.R
@@ -2,18 +2,29 @@
 
 source("modules/Saving/paths2save.R")
 
-save_data <- function(recipe, data, 
+save_data <- function(recipe, archive, data,
 		      calibrated_data = NULL,
 		      skill_metrics = NULL,
-		      probabilities = NULL,
-                      archive = NULL) {
+		      probabilities = NULL) {
   # Wrapper for the saving functions.
   # recipe: The auto-s2s recipe
+  # archive: The auto-s2s archive
   # data: output of load_datasets()
   # calibrated_data: output of calibrate_datasets()
   # skill_metrics: output of compute_skill_metrics()
   # probabilities: output of compute_probabilities()
 
+  if (is.null(recipe)) {
+    stop("The 'recipe' parameter is mandatory.")
+  }
+  if (is.null(archive)) {
+    stop("The 'archive' parameter is mandatory.")
+  }
+  if (is.null(data)) {
+    stop("The 'data' parameter is mandatory. It should be the output of",
+	 "load_datasets().")
+  }
+
   dict <- read_yaml("conf/variable-dictionary.yml")
 
   # Create output directory
@@ -75,10 +86,10 @@ get_global_attributes <- function(recipe) {
   return(attrs)
 }
 
-get_times <- function(store.freq, fcst.horizon, leadtimes, sdate) {
+get_times <- function(store.freq, fcst.horizon, leadtimes, sdate, calendar) {
   # Generates time dimensions and the corresponding metadata.
   ## TODO: Add calendar
-  ## TODO: Subseasonal and decadal
+  ## TODO: Subseasonal
 
   switch(fcst.horizon,
          "seasonal" = {time <- leadtimes; ref <- 'hours since '; 
@@ -90,7 +101,8 @@ get_times <- function(store.freq, fcst.horizon, leadtimes, sdate) {
 
   dim(time) <- length(time)
   sdate <- as.Date(sdate, format = '%Y%m%d') # reformatting
-  metadata <- list(time = list(units = paste0(ref, sdate, 'T00:00:00')))
+  metadata <- list(time = list(units = paste0(ref, sdate, 'T00:00:00'),
+			       calendar = calendar))
   attr(time, 'variables') <- metadata
   names(dim(time)) <- 'time'
   
@@ -145,10 +157,16 @@ save_forecast <- function(data_cube,
   global_attributes <- get_global_attributes(recipe)
   fcst.horizon <- tolower(recipe$Analysis$Horizon)
   store.freq <- recipe$Analysis$Variables$freq
-
+  calendar <- archive$System[[global_attributes$system]]$calendar
+#  if (fcst.horizon == "seasonal") {
+#    calendar <- attr(data_cube$Variable, "variable")$dim$time$calendar
+#  } else {
+#    calendar <- attr(data_cube$Variable, "variable")$dim[[3]]$calendar
+#  }
   
   # Generate vector containing leadtimes
-  dates <- ClimProjDiags::Subset(as.Date(data_cube$Dates$start), 'syear', 1)
+  dates <- as.PCICt(ClimProjDiags::Subset(data_cube$Dates$start, 'syear', 1),
+		    cal = calendar)
   if (fcst.horizon == 'decadal') {
     # Method 1: Use the first date as init_date. But it may be better to use the real initialized date (ask users)
 #    init_date <- as.Date(data_cube$Dates$start[1], format = '%Y%m%d')
@@ -156,25 +174,27 @@ save_forecast <- function(data_cube,
     init_month <- archive$System[[recipe$Analysis$Datasets$System$name]]$initial_month
     if (type == 'hcst') {
 #PROBLEM for fcst!!!!!!!!!!!!
-      init_date <- as.Date(paste0(recipe$Analysis$Time$hcst_start, '-', 
-                                  sprintf('%02d', init_month), '-01'))
+      init_date <- as.PCICt(paste0(recipe$Analysis$Time$hcst_start, '-', 
+                                   sprintf('%02d', init_month), '-01'),
+			    cal = calendar)
     } else if (type == 'fcst') {
-      init_date <- as.Date(paste0(recipe$Analysis$Time$fcst_year[1], '-',
-                                  sprintf('%02d', init_month), '-01'))
+      init_date <- as.PCICt(paste0(recipe$Analysis$Time$fcst_year[1], '-',
+                                   sprintf('%02d', init_month), '-01'),
+			    cal = calendar)
     }
   } else {
     if (type == 'hcst') {
-      init_date <- as.Date(paste0(recipe$Analysis$Time$hcst_start,
-                           recipe$Analysis$Time$sdate),
-	                   format = '%Y%m%d')
+      init_date <- as.PCICt(paste0(recipe$Analysis$Time$hcst_start,
+                            recipe$Analysis$Time$sdate),
+	                    format = '%Y%m%d', cal = calendar)
     } else if (type == 'fcst') {
-      init_date <- as.Date(paste0(recipe$Analysis$Time$fcst_year,
-                           recipe$Analysis$Time$sdate),
-			   format = '%Y%m%d')
+      init_date <- as.PCICt(paste0(recipe$Analysis$Time$fcst_year,
+                            recipe$Analysis$Time$sdate),
+			    format = '%Y%m%d', cal = calendar)
     }
   }
-  # Get time difference in months
-  leadtimes <- interval(init_date, dates) %/% hours(1)
+  # Get time difference in hours
+  leadtimes <- as.numeric(dates - init_date)/3600
 
   syears <- seq(1:dim(data_cube$data)['syear'][[1]])
   syears_val <- lubridate::year(data_cube$Dates$start[1, 1, , 1]) # expect dim = [sday = 1, sweek = 1, syear, time]
@@ -201,6 +221,7 @@ save_forecast <- function(data_cube,
     } else {
       dims <- c(lalo, 'ensemble', 'time')
       var.expname <- variable
+      var.sdname <- var.sdname
       var.units <- attr(data_cube$Variable, 'variable')$units
     }
   
@@ -211,7 +232,6 @@ save_forecast <- function(data_cube,
     attr(fcst[[1]], 'variables') <- metadata
     names(dim(fcst[[1]])) <- dims
     # Add global attributes
-    global_attributes <- get_global_attributes(recipe)
     attr(fcst[[1]], 'global_attrs') <- global_attributes
     
     # Select start date
@@ -220,6 +240,7 @@ save_forecast <- function(data_cube,
 #      fcst.sdate <- format(as.Date(data_cube$Dates$start[i]), '%Y%m%d')
 
       # init_date is like "1990-11-01"
+      init_date <- as.POSIXct(init_date)
       fcst.sdate <- init_date + lubridate::years(syears_val[i] - lubridate::year(init_date))
       fcst.sdate <- format(fcst.sdate, '%Y%m%d')
 
@@ -228,7 +249,7 @@ save_forecast <- function(data_cube,
     }
 
     # Get time dimension values and metadata
-    times <- get_times(store.freq, fcst.horizon, leadtimes, fcst.sdate)
+    times <- get_times(store.freq, fcst.horizon, leadtimes, fcst.sdate, calendar)
     time <- times$time
 
     # Generate name of output file
@@ -274,25 +295,28 @@ save_observations <- function(data_cube,
   global_attributes <- get_global_attributes(recipe)
   fcst.horizon <- tolower(recipe$Analysis$Horizon)
   store.freq <- recipe$Analysis$Variables$freq
+  calendar <- archive$Reference[[global_attributes$reference]]$calendar
   
   # Generate vector containing leadtimes
   ## TODO: Move to a separate function?
-  dates <- ClimProjDiags::Subset(as.Date(data_cube$Dates$start), 'syear', 1)
+  dates <- as.PCICt(ClimProjDiags::Subset(data_cube$Dates$start, 'syear', 1),
+		    cal = calendar)
   if (fcst.horizon == 'decadal') {
     # Method 1: Use the first date as init_date. But it may be better to use the real initialized date (ask users)
 #    init_date <- as.Date(data_cube$Dates$start[1], format = '%Y%m%d')
     # Method 2: use initial month
     init_month <- archive$System[[recipe$Analysis$Datasets$System$name]]$initial_month
-    init_date <- as.Date(paste0(recipe$Analysis$Time$hcst_start, '-', 
-                                sprintf('%02d', init_month), '-01'))
+    init_date <- as.PCICt(paste0(recipe$Analysis$Time$hcst_start, '-', 
+                                 sprintf('%02d', init_month), '-01'),
+			  cal = calendar)
 
   } else {
-    init_date <- as.Date(paste0(recipe$Analysis$Time$hcst_start,
-                         recipe$Analysis$Time$sdate),
-	                 format = '%Y%m%d')
+    init_date <- as.PCICt(paste0(recipe$Analysis$Time$hcst_start,
+                          recipe$Analysis$Time$sdate),
+	                  format = '%Y%m%d', cal = calendar)
   }
-  # Get time difference in months
-  leadtimes <- interval(init_date, dates) %/% hours(1)
+  # Get time difference in hours
+  leadtimes <- as.numeric(dates - init_date)/3600
 
   syears <- seq(1:dim(data_cube$data)['syear'][[1]])
   syears_val <- lubridate::year(data_cube$Dates$start[1, 1, , 1]) # expect dim = [sday = 1, sweek = 1, syear, time]
@@ -329,7 +353,6 @@ save_observations <- function(data_cube,
     attr(fcst[[1]], 'variables') <- metadata
     names(dim(fcst[[1]])) <- dims
     # Add global attributes
-    global_attributes <- get_global_attributes(recipe)
     attr(fcst[[1]], 'global_attrs') <- global_attributes
     
     # Select start date. The date is computed for each year, and adapted for
@@ -339,6 +362,7 @@ save_observations <- function(data_cube,
     ## cases, different approaches are necessary.
     if (fcst.horizon == 'decadal') {
       # init_date is like "1990-11-01"
+      init_date <- as.POSIXct(init_date)
       fcst.sdate <- init_date + lubridate::years(syears_val[i] - lubridate::year(init_date))
     } else {
 
@@ -351,6 +375,7 @@ save_observations <- function(data_cube,
     }
 
     # Ensure the year is correct if the first leadtime goes to the next year
+    init_date <- as.POSIXct(init_date)
     if (lubridate::month(fcst.sdate) < lubridate::month(init_date)) {
       lubridate::year(fcst.sdate) <- lubridate::year(fcst.sdate) + 1
     }
@@ -359,7 +384,7 @@ save_observations <- function(data_cube,
     fcst.sdate <- format(fcst.sdate, format = '%Y%m%d')
 
     # Get time dimension values and metadata
-    times <- get_times(store.freq, fcst.horizon, leadtimes, fcst.sdate)
+    times <- get_times(store.freq, fcst.horizon, leadtimes, fcst.sdate, calendar)
     time <- times$time
 
     # Generate name of output file
@@ -438,20 +463,25 @@ save_metrics <- function(skill,
   # Time indices and metadata
   fcst.horizon <- tolower(recipe$Analysis$Horizon)
   store.freq <- recipe$Analysis$Variables$freq
+  calendar <- archive$System[[global_attributes$system]]$calendar
+
   # Generate vector containing leadtimes
-  dates <- ClimProjDiags::Subset(as.Date(data_cube$Dates$start), 'syear', 1)
+  dates <- as.PCICt(ClimProjDiags::Subset(data_cube$Dates$start, 'syear', 1),
+		    cal = calendar)
+
   if (fcst.horizon == 'decadal') {
     init_month <- archive$System[[recipe$Analysis$Datasets$System$name]]$initial_month
-    init_date <- as.Date(paste0(recipe$Analysis$Time$hcst_start, '-',
-                                sprintf('%02d', init_month), '-01'))
+    init_date <- as.PCICt(paste0(recipe$Analysis$Time$hcst_start, '-',
+                                 sprintf('%02d', init_month), '-01'),
+			  cal = calendar)
   } else {
-    init_date <- as.Date(paste0(recipe$Analysis$Time$hcst_start,
-                         recipe$Analysis$Time$sdate),
-                         format = '%Y%m%d')
+    init_date <- as.PCICt(paste0(recipe$Analysis$Time$hcst_start,
+                          recipe$Analysis$Time$sdate),
+                          format = '%Y%m%d', cal = calendar)
   }
 
-  # Get time difference in months
-  leadtimes <- interval(init_date, dates) %/% hours(1)
+  # Get time difference in hours
+  leadtimes <- as.numeric(dates - init_date)/3600
 
   # Select start date
   # If a fcst is provided, use that as the ref. year. Otherwise use 1970.
@@ -472,7 +502,7 @@ save_metrics <- function(skill,
     }
   }
 
-  times <- get_times(store.freq, fcst.horizon, leadtimes, fcst.sdate)
+  times <- get_times(store.freq, fcst.horizon, leadtimes, fcst.sdate, calendar)
   time <- times$time
 
   # Generate name of output file
@@ -541,20 +571,24 @@ save_corr <- function(skill,
   # Time indices and metadata
   fcst.horizon <- tolower(recipe$Analysis$Horizon)
   store.freq <- recipe$Analysis$Variables$freq
+  calendar <- archive$System[[global_attributes$system]]$calendar
+  
   # Generate vector containing leadtimes
-  dates <- ClimProjDiags::Subset(as.Date(data_cube$Dates$start), 'syear', 1)
+  dates <- as.PCICt(ClimProjDiags::Subset(data_cube$Dates$start, 'syear', 1),
+		    cal = calendar)
   if (fcst.horizon == 'decadal') {
     init_month <- archive$System[[recipe$Analysis$Datasets$System$name]]$initial_month
-    init_date <- as.Date(paste0(recipe$Analysis$Time$hcst_start, '-',
-                                sprintf('%02d', init_month), '-01'))
+    init_date <- as.PCICt(paste0(recipe$Analysis$Time$hcst_start, '-',
+                                 sprintf('%02d', init_month), '-01'),
+			  cal = calendar)
   } else {
-    init_date <- as.Date(paste0(recipe$Analysis$Time$hcst_start,
-                         recipe$Analysis$Time$sdate),
-                         format = '%Y%m%d')
+    init_date <- as.PCICt(paste0(recipe$Analysis$Time$hcst_start,
+                          recipe$Analysis$Time$sdate),
+                          format = '%Y%m%d', cal = calendar)
   }
 
-  # Get time difference in months
-  leadtimes <- interval(init_date, dates) %/% hours(1)
+  # Get time difference in hours
+  leadtimes <- as.numeric(dates - init_date)/3600
 
   # Select start date
   # If a fcst is provided, use that as the ref. year. Otherwise use 1970.
@@ -575,7 +609,7 @@ save_corr <- function(skill,
     }
   }
 
-  times <- get_times(store.freq, fcst.horizon, leadtimes, fcst.sdate)
+  times <- get_times(store.freq, fcst.horizon, leadtimes, fcst.sdate, calendar)
   time <- times$time
 
   # Generate name of output file
@@ -637,20 +671,23 @@ save_percentiles <- function(percentiles,
   # Time indices and metadata
   fcst.horizon <- tolower(recipe$Analysis$Horizon)
   store.freq <- recipe$Analysis$Variables$freq
+  calendar <- archive$System[[global_attributes$system]]$calendar
   # Generate vector containing leadtimes
-  dates <- ClimProjDiags::Subset(as.Date(data_cube$Dates$start), 'syear', 1)
+  dates <- as.PCICt(ClimProjDiags::Subset(data_cube$Dates$start, 'syear', 1),
+		    cal = calendar)
   if (fcst.horizon == 'decadal') {
     init_month <- archive$System[[recipe$Analysis$Datasets$System$name]]$initial_month
-    init_date <- as.Date(paste0(recipe$Analysis$Time$hcst_start, '-',
-                                sprintf('%02d', init_month), '-01'))
+    init_date <- as.PCICt(paste0(recipe$Analysis$Time$hcst_start, '-',
+                                 sprintf('%02d', init_month), '-01'),
+			  cal = calendar)
   } else {
-    init_date <- as.Date(paste0(recipe$Analysis$Time$hcst_start,
-                         recipe$Analysis$Time$sdate),
-                         format = '%Y%m%d')
+    init_date <- as.PCICt(paste0(recipe$Analysis$Time$hcst_start,
+                          recipe$Analysis$Time$sdate),
+                          format = '%Y%m%d', cal = calendar)
   }
 
   # Get time difference in hours
-  leadtimes <- interval(init_date, dates) %/% hours(1)
+  leadtimes <- as.numeric(dates - init_date)/3600
 
   # Select start date
   # If a fcst is provided, use that as the ref. year. Otherwise use 1970.
@@ -671,7 +708,7 @@ save_percentiles <- function(percentiles,
     }
   }
 
-  times <- get_times(store.freq, fcst.horizon, leadtimes, fcst.sdate)
+  times <- get_times(store.freq, fcst.horizon, leadtimes, fcst.sdate, calendar)
   time <- times$time
 
   # Generate name of output file
@@ -717,22 +754,25 @@ save_probabilities <- function(probs,
   global_attributes <- get_global_attributes(recipe)
   fcst.horizon <- tolower(recipe$Analysis$Horizon)
   store.freq <- recipe$Analysis$Variables$freq
-  
+  calendar <- archive$System[[global_attributes$system]]$calendar
+
   # Generate vector containing leadtimes
   ## TODO: Move to a separate function?
-  dates <- ClimProjDiags::Subset(as.Date(data_cube$Dates$start), 'syear', 1)
+  dates <- as.PCICt(ClimProjDiags::Subset(data_cube$Dates$start, 'syear', 1),
+		    cal = calendar)
   if (fcst.horizon == 'decadal') {
     init_month <- archive$System[[recipe$Analysis$Datasets$System$name]]$initial_month
-    init_date <- as.Date(paste0(recipe$Analysis$Time$hcst_start, '-',
-                                sprintf('%02d', init_month), '-01'))
+    init_date <- as.PCICt(paste0(recipe$Analysis$Time$hcst_start, '-',
+                                 sprintf('%02d', init_month), '-01'),
+			  cal = calendar)
   } else {
-    init_date <- as.Date(paste0(recipe$Analysis$Time$hcst_start,
-                         recipe$Analysis$Time$sdate),
-                         format = '%Y%m%d')
+    init_date <- as.PCICt(paste0(recipe$Analysis$Time$hcst_start,
+                          recipe$Analysis$Time$sdate),
+                          format = '%Y%m%d', cal = calendar)
   }
 
   # Get time difference in hours
-  leadtimes <- interval(init_date, dates) %/% hours(1)
+  leadtimes <- as.numeric(dates - init_date)/3600
 
   syears <- seq(1:dim(data_cube$data)['syear'][[1]])
   syears_val <- lubridate::year(data_cube$Dates$start[1, 1, , 1]) # expect dim = [sday = 1, sweek = 1, syear, time]
@@ -762,12 +802,12 @@ save_probabilities <- function(probs,
     }
 
     # Add global attributes
-    global_attributes <- get_global_attributes(recipe)
     attr(probs_syear[[1]], 'global_attrs') <- global_attributes
     
     # Select start date
     if (fcst.horizon == 'decadal') {
       # init_date is like "1990-11-01"
+      init_date <- as.POSIXct(init_date)
       fcst.sdate <- init_date + lubridate::years(syears_val[i] - lubridate::year(init_date))
       fcst.sdate <- format(fcst.sdate, '%Y%m%d')
     } else {
@@ -775,7 +815,7 @@ save_probabilities <- function(probs,
     }
 
     # Get time dimension values and metadata
-    times <- get_times(store.freq, fcst.horizon, leadtimes, fcst.sdate)
+    times <- get_times(store.freq, fcst.horizon, leadtimes, fcst.sdate, calendar)
     time <- times$time
 
     # Generate name of output file
diff --git a/modules/test_decadal.R b/modules/test_decadal.R
index 7923c0286a91a26f6fcc7fca6bcd8f2d3a489550..8077b7e200142a638568e5e30ff60ac71d209407 100644
--- a/modules/test_decadal.R
+++ b/modules/test_decadal.R
@@ -17,4 +17,4 @@ skill_metrics <- compute_skill_metrics(calibrated_data$hcst, data$obs, recipe)
 # Compute percentiles and probability bins
 probabilities <- compute_probabilities(calibrated_data$hcst, recipe)
 # Export all data to netCDF
-save_data(recipe, data, calibrated_data, skill_metrics, probabilities, archive = archive)
+save_data(recipe, archive, data, calibrated_data, skill_metrics, probabilities)
diff --git a/modules/test_victoria.R b/modules/test_victoria.R
index df425659132de063cf2403537253932cdac29d76..eb5933b3547a7d7e2ff10e8d251aee0bed0a538f 100644
--- a/modules/test_victoria.R
+++ b/modules/test_victoria.R
@@ -4,8 +4,9 @@ source("modules/Calibration/Calibration.R")
 source("modules/Skill/Skill.R")
 source("modules/Saving/Saving.R")
 
-recipe_file <- "modules/Loading/testing_recipes/recipe_era5land.yml"
+recipe_file <- "modules/Loading/testing_recipes/recipe_4.yml"
 recipe <- read_yaml(recipe_file)
+archive <- read_yaml(paste0(recipe$Run$code_dir, "conf/archive.yml"))$archive
 
 # Load datasets
 data <- load_datasets(recipe_file)
@@ -16,4 +17,4 @@ skill_metrics <- compute_skill_metrics(calibrated_data$hcst, data$obs, recipe)
 # Compute percentiles and probability bins
 probabilities <- compute_probabilities(calibrated_data$hcst, recipe)
 # Export all data to netCDF
-save_data(recipe, data, calibrated_data, skill_metrics, probabilities)
+save_data(recipe, archive, data, calibrated_data, skill_metrics, probabilities)
diff --git a/tools/libs.R b/tools/libs.R
index 248ada450574cfbcaf6615068989e6884b0d0e46..2b29835927f2443e7f5e8f67cacc345db0436633 100644
--- a/tools/libs.R
+++ b/tools/libs.R
@@ -11,6 +11,7 @@ library(abind)
 library(easyNCDF)
 library(CSTools)
 library(lubridate)
+library(PCICt)
 #
 #  library(parallel)
 #  library(pryr) # To check mem usage.