diff --git a/fbfmaproom/data-conversion-scripts/ethiopia/southern-oromia-bad-years-v3-3season.py b/fbfmaproom/data-conversion-scripts/ethiopia/southern-oromia-bad-years-v3-3season.py
new file mode 100644
index 00000000..17e8b5f4
--- /dev/null
+++ b/fbfmaproom/data-conversion-scripts/ethiopia/southern-oromia-bad-years-v3-3season.py
@@ -0,0 +1,136 @@
+import cftime
+import datetime
+import pandas as pd
+import xarray as xr
+import sys
+import os
+import numpy as np
+import shutil
+
+
+def convert_zarr_to_dataset(zarr_path):
+    # Zarr file exist
+    if os.path.exists(zarr_path) and os.path.isdir(zarr_path):
+        try:
+            ds = xr.open_zarr(zarr_path)
+            for var_name, variable in ds.data_vars.items():
+                print(var_name)
+                print(ds[var_name].values)
+            print("Zarr file successfully converted to Xarray Dataset.")
+            return ds
+        except Exception as e:
+            print(f"An error occurred while opening the Zarr file: {e}")
+    else:
+        print("Zarr directory does not exist.")
+        return None
+
+dirout='/data/aaron/fbf-candidate/'
+regionsdic = {
+    "ethiopia/southern-oromia": {"file": "/data/aaron/fbf-candidate/original-data/ethiopia/oromia_bad_years.csv",
+                                 "time-span":'2000-2023',
+                                 "version":'v3'
+                                 },
+  "djibouti": {"file": "/data/aaron/fbf-candidate/original-data/djibouti/bad_years.csv",
+               "time-span":None,
+               "version":'v2'
+               }
+    
+}
+
+vars=['rank','hum_bady','nma_bady']
+
+seasons = {"djf":1, 
+           "jfm":2, 
+           "fma":3, 
+           "mam":4, 
+           "amj":5, 
+           "mjj":6, 
+           "jja":7, 
+           "jas":8, 
+           "aso":9, 
+           "son":10, 
+           "ond":11, 
+           "ndj":12}
+
+
+
+if  len(sys.argv) < 3:
+    print("\033[91m"+"Two arguments is expected. (season, region)"+"\033[0m")
+    print("\033[1m"+"Example: python bad-years-v3-3season.py ond djibouti"+"\033[0m")
+    sys.exit()
+elif not sys.argv[1] in seasons: 
+    print("\033[91m"+"The season is not allowed."+"\033[0m")
+    print("\033[1m"+"Example: "+", ".join(seasons.keys()) +"\033[0m")
+    sys.exit()
+elif not sys.argv[2].lower() in regionsdic: 
+    print("\033[91m"+"The region is not defined."+"\033[0m")
+    print("\033[1m"+"regions available: "+ (", ".join(regionsdic.keys())) +"\033[0m")
+    sys.exit()
+elif len(sys.argv) ==4:
+    if not sys.argv[3] in vars:
+        print("\033[91m"+"The var is not allowed."+"\033[0m")
+        print("\033[1m"+"Example: "+", ".join(vars) +"\033[0m")
+        sys.exit()
+
+    season = f"{sys.argv[1].lower()}"
+    region = f"{sys.argv[2]}".lower()
+    var = f"{sys.argv[3]}"
+    column_file=season+'-'+var
+    
+else:
+    season = f"{sys.argv[1].lower()}"
+    region = f"{sys.argv[2]}".lower()
+    var = ''
+    column_file=season
+    
+
+bad=pd.read_csv(regionsdic[region]['file'], skiprows=1)
+if not regionsdic[region]['time-span'] == None:
+    year_ini, year_end = map(int, regionsdic[region]['time-span'].split('-'))
+    for year in range(year_ini, year_end + 1):
+        if not year in bad['year'].values:
+            new_row = {bad.columns[0]: year, bad.columns[1]: 8}
+            new_row_df = pd.DataFrame(new_row, index=[0])
+            bad=pd.concat([bad, new_row_df], ignore_index=True)
+    bad = bad.sort_values(by='year').reset_index(drop=True)
+    del year, new_row, new_row_df,year_ini,year_end
+
+years = [cftime.Datetime360Day(y, seasons[season], 16) for y in bad['year'].tolist()]
+
+if column_file in bad.columns:
+    ranks = bad[column_file].to_list()
+    if var=='nma_bady':
+        ranks=[2 if rank == 'High Impact' else 
+               1 if rank == 'Moderate Impact' else 
+               0 if rank ==  'Normal' else 
+               rank for rank in ranks]
+else:
+    print("\033[91m"+"The season "+column_file+" is not available in the file "+regionsdic[region]['file']+"."+"\033[0m")
+    sys.exit()
+
+if not var =='':
+    ds = xr.Dataset(data_vars={var: xr.DataArray(ranks, coords={"T": years})})
+else:  
+    ds = xr.Dataset(data_vars={"rank": xr.DataArray(ranks, coords={"T": years})})
+
+if "/" in region:
+    file=os.path.join(dirout,region+'-bad-years-'+regionsdic[region]['version']+'-'+season+'.zarr')
+else:
+    file=os.path.join(dirout,region,'bad-years-'+regionsdic[region]['version']+'-'+season+'.zarr')
+
+ds_aux = convert_zarr_to_dataset(file)
+if ds_aux is not None:
+    # Zarr file exist
+    if np.array_equal(ds_aux['T'].values, ds['T'].values): 
+        shutil.move(file, file.replace('.zarr','OLD.zarr'))
+        ds_aux[var] = (('T'), ranks)
+        ds_aux.to_zarr(file)
+
+    else:
+        print("\033[91m"+"The T coordinate has different sizes."+"\033[0m")
+        sys.exit()
+    print(ds_aux)
+else:
+    ds.to_zarr(file)
+sys.exit()
+
diff --git a/fbfmaproom/fbfmaproom-sample.yaml b/fbfmaproom/fbfmaproom-sample.yaml
index fd4c1dda..e8ba8b66 100644
--- a/fbfmaproom/fbfmaproom-sample.yaml
+++ b/fbfmaproom/fbfmaproom-sample.yaml
@@ -1175,7 +1175,7 @@ countries:
                 predictors:
                     - pnep
                     - rain
-                predictand: bad-years
+                predictand: bad-years-v2
             observations:
                 rain:
                     label: Rain
@@ -1292,6 +1292,17 @@ countries:
                     colormap: precip
                     lower_is_worse: no
                     format: bad
+                bad-years-v2:
+                    label: Drought humanitarian ranking v2
+                    description: Drought ranking of expert committee humanitarian data review (v2)
+                    path: ethiopia/southern-oromia-bad-years-v2-ond.zarr
+                    var_names:
+                        value: rank
+                        time: T
+                    colormap: precip
+                    lower_is_worse: yes
+                    format: number0
+                    units: rank
             forecasts:
                 pnep:
                     label: Forecast prob non-exc
@@ -1877,7 +1888,7 @@ countries:
                 predictors:
                     - pnep-v2
                     - rain
-                predictand: bad-years
+                predictand: bad-years-rank-v2
             observations:
                 rain:
                     label: Rain
@@ -1934,6 +1945,27 @@ countries:
                     colormap: precip
                     lower_is_worse: yes
                     format: number0
+                bad-years-rank-v2:
+                    label: Reported bad years v2
+                    description: Adjusted rank from NMA's Bad Year Classification (AA Workshop 2024)
+                    path: djibouti/bad-years-v2-jas.zarr
+                    var_names:
+                        value: rank
+                        time: T
+                    colormap: precip
+                    lower_is_worse: yes
+                    format: number0
+                    units: rank
+                bad-years-hum_bady-v2:
+                    label: Bad Years for Humanitarian Sector 2024
+                    description: Bad years identified by the Humanitarian Sector (AA Workshop 2024)
+                    path: djibouti/bad-years-v2-jas.zarr
+                    var_names:
+                        value: hum_bady
+                        time: T
+                    colormap: precip
+                    lower_is_worse: no
+                    format: bad
             forecasts:
                 pnep:
                     label: Forecast prob non-exc
@@ -2006,7 +2038,7 @@ countries:
                 predictors:
                     - pnep-v2
                     - rain
-                predictand: bad-years
+                predictand: bad-years-rank-v2
             observations:
                 rain:
                     label: Rain
@@ -2051,6 +2083,27 @@ countries:
                     colormap: precip
                     lower_is_worse: yes
                     format: number0
+                bad-years-rank-v2:
+                    label: Reported bad years v2
+                    description: Adjusted rank from NMA's Bad Year Classification (AA Workshop 2024)
+                    path: djibouti/bad-years-v2-mam.zarr
+                    var_names:
+                        value: rank
+                        time: T
+                    colormap: precip
+                    lower_is_worse: yes
+                    format: number0
+                    units: rank
+                bad-years-hum_bady-v2:
+                    label: Bad Years for Humanitarian Sector 2024
+                    description: Bad years identified by the Humanitarian Sector (AA Workshop 2024)
+                    path: djibouti/bad-years-v2-mam.zarr
+                    var_names:
+                        value: hum_bady
+                        time: T
+                    colormap: precip
+                    lower_is_worse: no
+                    format: bad
                 spi:
                     label: SPI
                     description: SPI calculated from CHIRPS
@@ -2136,7 +2189,7 @@ countries:
                 predictors:
                     - pnep-v2
                     - rain
-                predictand: bad-years
+                predictand: bad-years-rank-v2
             observations:
                 rain:
                     label: Rain
@@ -2181,6 +2234,27 @@ countries:
                     colormap: precip
                     lower_is_worse: yes
                     format: number0
+                bad-years-rank-v2:
+                    label: Reported bad years v2
+                    description: Adjusted rank from NMA's Bad Year Classification (AA Workshop 2024)
+                    path: djibouti/bad-years-v2-ond.zarr
+                    var_names:
+                        value: rank
+                        time: T
+                    colormap: precip
+                    lower_is_worse: yes
+                    format: number0
+                    units: rank
+                bad-years-hum_bady-v2:
+                    label: Bad Years for Humanitarian Sector 2024
+                    description: Bad years identified by the Humanitarian Sector (AA Workshop 2024)
+                    path: djibouti/bad-years-v2-ond.zarr
+                    var_names:
+                        value: hum_bady
+                        time: T
+                    colormap: precip
+                    lower_is_worse: no
+                    format: bad
                 spi:
                     label: SPI
                     description: SPI calculated from CHIRPS