diff --git a/ESDC/README.md b/ESDC/README.md
index 0084c74..934d81e 100644
--- a/ESDC/README.md
+++ b/ESDC/README.md
@@ -188,8 +188,8 @@ inputs-preprocess/FLUXCOM/fluxcom-data-cube-8d-0.25deg.py # Resample to 0.25 deg
 # GOSIF: Preprocessing
 inputs-preprocess/SIF/GOSIF/sif-gosif-data-cube-part1.py # Convert .tif to .zarr
 inputs-preprocess/SIF/GOSIF/sif-gosif-data-cube-part2.py # Concatenate .zarr files
-inputs-preprocess/SIF/GOSIF/sif-gosif-data-cube-0.25deg.py # Resample to 0.25 degrees
 inputs-preprocess/SIF/GOSIF/sif-gosif-metadata.py # Add initial metadata
+inputs-preprocess/SIF/GOSIF/sif-gosif-data-cube-0.25deg.py # Resample to 0.25 degrees
 
 # GOME-2 JJ Method: Preprocessing
 inputs-preprocess/SIF/GOME2/sif-gome2-JJ-data-cube.py # Concatenate .nc files
diff --git a/ESDC/inputs-collect/download-GOME2-SIF.py b/ESDC/inputs-collect/download-GOME2-SIF.py
index 65328c5..6ff0d1c 100644
--- a/ESDC/inputs-collect/download-GOME2-SIF.py
+++ b/ESDC/inputs-collect/download-GOME2-SIF.py
@@ -1,5 +1,6 @@
 import requests
 import numpy as np
+import os
 
 URL = "http://jeodpp.jrc.ec.europa.eu/ftp/jrc-opendata/ECOCLIM/Downscaled-GOME2-SIF/v2.0/"
 # pathOut = "/net/projects/deep_esdl/data/GOME2-SIF/data/"
@@ -18,4 +19,5 @@
         file_to_download = f"GOME_{rm}_dcSIF_005deg_8day_{year}.nc"
         print(f"Downloading {file_to_download}")
         response = requests.get(URL + file_to_download)
-        open(pathOut + file_to_download, "wb").write(response.content)
\ No newline at end of file
+        file_path = os.path.join(pathOut, file_to_download)
+        open(file_path, "wb").write(response.content)
diff --git a/ESDC/inputs-collect/download-GOSIF.py b/ESDC/inputs-collect/download-GOSIF.py
index 0df6434..b629405 100644
--- a/ESDC/inputs-collect/download-GOSIF.py
+++ b/ESDC/inputs-collect/download-GOSIF.py
@@ -2,6 +2,7 @@
 import requests
 from urllib.request import Request, urlopen
 import re
+import os
 from os.path import exists
 
 URL = "http://data.globalecology.unh.edu/data/GOSIF_v2/8day/"
@@ -24,9 +25,10 @@
     link = link.get('href')
     if link.endswith(".tif.gz"):
         file_to_download = link.split("/")[-1]
-        if not exists(pathOut + file_to_download):
+        file_path = os.path.join(pathOut, file_to_download)
+        if not exists(file_path):
             print(f"Downloading {file_to_download}")
             response = requests.get(URL + file_to_download)
-            open(pathOut + file_to_download, "wb").write(response.content)
+            open(file_path, "wb").write(response.content)
         else:
-            pass
\ No newline at end of file
+            pass
diff --git a/ESDC/inputs-collect/extract-gz-gosif.py b/ESDC/inputs-collect/extract-gz-gosif.py
index afe94a9..85871ff 100644
--- a/ESDC/inputs-collect/extract-gz-gosif.py
+++ b/ESDC/inputs-collect/extract-gz-gosif.py
@@ -1,16 +1,15 @@
 import gzip
 import shutil
 import glob
+import os
 
 from tqdm import tqdm
 
 pathOut = "~/data/SIF/GOSIF/source"
 pathOut = os.path.expanduser(pathOut)
-
 files = glob.glob(f"{pathOut}/*")
 files.sort()
-
 for file in tqdm(files):
     with gzip.open(file, 'rb') as f_in:
         with open(file.replace(".gz",""), 'wb') as f_out:
-            shutil.copyfileobj(f_in, f_out)
\ No newline at end of file
+            shutil.copyfileobj(f_in, f_out)
diff --git a/ESDC/inputs-preprocess/CCI/aerosol/cci-aod550-8d-0.083deg.py b/ESDC/inputs-preprocess/CCI/aerosol/cci-aod550-8d-0.083deg.py
index 2c5663e..9ebb0a4 100644
--- a/ESDC/inputs-preprocess/CCI/aerosol/cci-aod550-8d-0.083deg.py
+++ b/ESDC/inputs-preprocess/CCI/aerosol/cci-aod550-8d-0.083deg.py
@@ -1,49 +1,53 @@
-from xcube.core.store import find_data_store_extensions
-from xcube.core.store import get_data_store_params_schema
-from xcube.core.store import new_data_store
+import os
 
-import shapely.geometry
-from IPython.display import JSON
-import matplotlib.pyplot as plt
 import numpy as np
-from tqdm import tqdm
 import xarray as xr
+from tqdm import tqdm
+from xcube.core.store import new_data_store
+
+pathOut = "~/data/CCI/aerosol/preprocess"
+pathOut = os.path.expanduser(pathOut)
 
 print("Reading")
 store = new_data_store('cciodp')
 
 dataset = store.open_data(
-    'esacci.AEROSOL.day.L3C.AER_PRODUCTS.AATSR.Envisat.SU.4-3.r1', 
+    'esacci.AEROSOL.day.L3C.AER_PRODUCTS.AATSR.Envisat.SU.4-3.r1',
     variable_names=['AOD550_mean'],
-    time_range=['2002-05-20','2012-04-08']
+    time_range=['2002-05-20', '2012-04-08']
 )
 
-dates_2002 = np.arange(np.datetime64("2002-05-21"), np.datetime64("2003-01-01"), np.timedelta64(8, "D")).astype("datetime64[ns]")
+dates_2002 = np.arange(np.datetime64("2002-05-21"), np.datetime64("2003-01-01"),
+                       np.timedelta64(8, "D")).astype("datetime64[ns]")
 
 last_year = 2012
 first_year = 2002
 
-years = np.arange(first_year,last_year + 1)
+years = np.arange(first_year, last_year + 1)
+
 
-def resample_weekly(ds,year):
+def resample_weekly(ds, year):
     keep_attrs = ds.time.attrs
-    ds = ds.sel(time=slice(f"{year}-01-01",f"{year}-12-31")).resample(time="8D").mean()    
-    ds['time'] = ds.time + np.timedelta64(4,"D")
+    ds = ds.sel(time=slice(f"{year}-01-01", f"{year}-12-31")).resample(
+        time="8D").mean()
+    ds['time'] = ds.time + np.timedelta64(4, "D")
     ds.time.attrs = keep_attrs
-    if year==2002:
+    if year == 2002:
         ds = ds.interp(coords=dict(time=dates_2002))
     return ds
 
+
 print("Resampling in time")
-dataset_8d = [resample_weekly(dataset,year) for year in tqdm(years)]
-dataset_8d = xr.concat(dataset_8d,dim="time")
+dataset_8d = [resample_weekly(dataset, year) for year in tqdm(years)]
+dataset_8d = xr.concat(dataset_8d, dim="time")
 
 new_lats = np.load("lat.npy")
 new_lons = np.load("lon.npy")
 
 print("Resampling in space")
-dataset_8d = dataset_8d.interp(coords=dict(lat=new_lats,lon=new_lons),method="nearest")
-dataset_8d = dataset_8d.chunk(dict(time=512,lat=128,lon=128))
+dataset_8d = dataset_8d.interp(coords=dict(lat=new_lats, lon=new_lons),
+                               method="nearest")
+dataset_8d = dataset_8d.chunk(dict(time=512, lat=128, lon=128))
 
 print("Saving")
-dataset_8d.to_zarr("~/data/cci-aod550-8d-0.083deg-512x128x128.zarr")
+dataset_8d.to_zarr(f"{pathOut}/cci-aod550-8d-0.083deg-512x128x128.zarr")
diff --git a/ESDC/inputs-preprocess/CCI/aerosol/cci-aod550-8d-0.25deg.py b/ESDC/inputs-preprocess/CCI/aerosol/cci-aod550-8d-0.25deg.py
index f860cc3..2fb3574 100644
--- a/ESDC/inputs-preprocess/CCI/aerosol/cci-aod550-8d-0.25deg.py
+++ b/ESDC/inputs-preprocess/CCI/aerosol/cci-aod550-8d-0.25deg.py
@@ -1,13 +1,9 @@
-from xcube.core.store import find_data_store_extensions
-from xcube.core.store import get_data_store_params_schema
-from xcube.core.store import new_data_store
+import os
 
-import shapely.geometry
-from IPython.display import JSON
-import matplotlib.pyplot as plt
 import numpy as np
-from tqdm import tqdm
 import xarray as xr
+from tqdm import tqdm
+from xcube.core.store import new_data_store
 
 pathOut = "~/data/CCI/aerosol/preprocess"
 pathOut = os.path.expanduser(pathOut)
@@ -19,37 +15,42 @@
 store = new_data_store('cciodp')
 
 dataset = store.open_data(
-    'esacci.AEROSOL.day.L3C.AER_PRODUCTS.AATSR.Envisat.SU.4-3.r1', 
+    'esacci.AEROSOL.day.L3C.AER_PRODUCTS.AATSR.Envisat.SU.4-3.r1',
     variable_names=['AOD550_mean'],
-    time_range=['2002-05-20','2012-04-08']
+    time_range=['2002-05-20', '2012-04-08']
 )
 
-dates_2002 = np.arange(np.datetime64("2002-05-21"), np.datetime64("2003-01-01"), np.timedelta64(8, "D")).astype("datetime64[ns]")
+dates_2002 = np.arange(np.datetime64("2002-05-21"), np.datetime64("2003-01-01"),
+                       np.timedelta64(8, "D")).astype("datetime64[ns]")
 
 last_year = 2012
 first_year = 2002
 
-years = np.arange(first_year,last_year + 1)
+years = np.arange(first_year, last_year + 1)
+
 
-def resample_weekly(ds,year):
+def resample_weekly(ds, year):
     keep_attrs = ds.time.attrs
-    ds = ds.sel(time=slice(f"{year}-01-01",f"{year}-12-31")).resample(time="8D").mean()    
-    ds['time'] = ds.time + np.timedelta64(4,"D")
+    ds = ds.sel(time=slice(f"{year}-01-01", f"{year}-12-31")).resample(
+        time="8D").mean()
+    ds['time'] = ds.time + np.timedelta64(4, "D")
     ds.time.attrs = keep_attrs
-    if year==2002:
+    if year == 2002:
         ds = ds.interp(coords=dict(time=dates_2002))
     return ds
 
+
 print("Resampling in time")
-dataset_8d = [resample_weekly(dataset,year) for year in tqdm(years)]
-dataset_8d = xr.concat(dataset_8d,dim="time")
+dataset_8d = [resample_weekly(dataset, year) for year in tqdm(years)]
+dataset_8d = xr.concat(dataset_8d, dim="time")
 
-new_lats = np.arange(-89.875,90,0.25)
-new_lons = np.arange(-179.875,180,0.25)
+new_lats = np.arange(-89.875, 90, 0.25)
+new_lons = np.arange(-179.875, 180, 0.25)
 
 print("Resampling in space")
-dataset_8d = dataset_8d.interp(coords=dict(lat=new_lats,lon=new_lons),method="nearest")
-dataset_8d = dataset_8d.chunk(dict(time=256,lat=128,lon=128))
+dataset_8d = dataset_8d.interp(coords=dict(lat=new_lats, lon=new_lons),
+                               method="nearest")
+dataset_8d = dataset_8d.chunk(dict(time=256, lat=128, lon=128))
 
 print("Saving")
-dataset_8d.to_zarr(f"{pathOut}/cci-aod550-8d-0.25deg-256x128x128.zarr")
\ No newline at end of file
+dataset_8d.to_zarr(f"{pathOut}/cci-aod550-8d-0.25deg-256x128x128.zarr")
diff --git a/ESDC/inputs-preprocess/CCI/aerosol/cci-aod550-metadata-0.0833deg.py b/ESDC/inputs-preprocess/CCI/aerosol/cci-aod550-metadata-0.0833deg.py
index 3d20a5c..9f72486 100644
--- a/ESDC/inputs-preprocess/CCI/aerosol/cci-aod550-metadata-0.0833deg.py
+++ b/ESDC/inputs-preprocess/CCI/aerosol/cci-aod550-metadata-0.0833deg.py
@@ -1,22 +1,30 @@
-from tqdm import tqdm
+import os
 from datetime import datetime
-import yaml
-import rioxarray
+
 import xarray as xr
-import numpy as np
+import yaml
+
+pathIn = "~/data/CCI/aerosol/preprocess"
+pathIn = os.path.expanduser(pathIn)
+
+pathOut = "~/data/CCI/aerosol/output"
+pathOut = os.path.expanduser(pathOut)
 
+if not os.path.exists(pathOut):
+    os.makedirs(pathOut)
 
-with open("cci-aod550-metadata-0.0833deg.yaml", "r") as stream:
+with open("inputs-preprocess/CCI/aerosol/cci-aod550-metadata-0.0833deg.yaml",
+          "r") as stream:
     try:
         metadata = yaml.safe_load(stream)
     except yaml.YAMLError as exc:
         print(exc)
 
-datacube = xr.open_zarr("/home/davemlz/data/cci-aod550-8d-0.083deg-512x128x128.zarr")
+datacube = xr.open_zarr(f"{pathIn}/cci-aod550-8d-0.083deg-512x128x128.zarr")
 
 datacube = datacube.rio.write_crs(
     "epsg:4326", grid_mapping_name="crs"
-).reset_coords()    
+).reset_coords()
 del datacube.crs.attrs["spatial_ref"]
 
 datacube.attrs = metadata["global"]
@@ -44,4 +52,4 @@
     sorted({**datacube.attrs, **additional_attrs}.items())
 )
 
-datacube.to_zarr("/home/davemlz/data/metadata/cci-aod550-8d-0.083deg-512x128x128.zarr")
+datacube.to_zarr(f"{pathOut}/cci-aod550-8d-0.083deg-512x128x128.zarr")
diff --git a/ESDC/inputs-preprocess/CCI/aerosol/cci-aod550-metadata.py b/ESDC/inputs-preprocess/CCI/aerosol/cci-aod550-metadata.py
index e3b0567..2425ea8 100644
--- a/ESDC/inputs-preprocess/CCI/aerosol/cci-aod550-metadata.py
+++ b/ESDC/inputs-preprocess/CCI/aerosol/cci-aod550-metadata.py
@@ -1,10 +1,8 @@
-from tqdm import tqdm
+import os
 from datetime import datetime
-import yaml
-import rioxarray
-import xarray as xr
-import numpy as np
 
+import xarray as xr
+import yaml
 
 pathIn = "~/data/CCI/aerosol/preprocess"
 pathIn = os.path.expanduser(pathIn)
@@ -15,7 +13,8 @@
 if not os.path.exists(pathOut):
     os.makedirs(pathOut)
 
-with open("cci-aod550-metadata.yaml", "r") as stream:
+with open("inputs-preprocess/CCI/aerosol/cci-aod550-metadata.yaml",
+          "r") as stream:
     try:
         metadata = yaml.safe_load(stream)
     except yaml.YAMLError as exc:
@@ -25,7 +24,7 @@
 
 datacube = datacube.rio.write_crs(
     "epsg:4326", grid_mapping_name="crs"
-).reset_coords()    
+).reset_coords()
 del datacube.crs.attrs["spatial_ref"]
 
 datacube.attrs = metadata["global"]
diff --git a/ESDC/inputs-preprocess/CCI/cloud/cci-cloud-8d-0.083deg.py b/ESDC/inputs-preprocess/CCI/cloud/cci-cloud-8d-0.083deg.py
index 6799f29..113f1bc 100644
--- a/ESDC/inputs-preprocess/CCI/cloud/cci-cloud-8d-0.083deg.py
+++ b/ESDC/inputs-preprocess/CCI/cloud/cci-cloud-8d-0.083deg.py
@@ -1,42 +1,49 @@
-from xcube.core.store import find_data_store_extensions
-from xcube.core.store import get_data_store_params_schema
-from xcube.core.store import new_data_store
+import os
 
-import shapely.geometry
-from IPython.display import JSON
-import matplotlib.pyplot as plt
 import numpy as np
-from tqdm import tqdm
-import xarray as xr
+from xcube.core.store import new_data_store
+
+pathOut = "~/data/CCI/cloud/preprocess"
+pathOut = os.path.expanduser(pathOut)
+
+if not os.path.exists(pathOut):
+    os.makedirs(pathOut)
 
 print("Reading")
 store = new_data_store('cciodp')
 
 dataset = store.open_data(
-    'esacci.CLOUD.mon.L3C.CLD_PRODUCTS.MODIS.Terra.MODIS_TERRA.2-0.r1', 
-    variable_names=['cot','cth','ctt'],
-    time_range=["2000-02-01","2014-12-31"]
+    'esacci.CLOUD.mon.L3C.CLD_PRODUCTS.MODIS.Terra.MODIS_TERRA.2-0.r1',
+    variable_names=['cot', 'cth', 'ctt'],
+    time_range=["2000-02-01", "2014-12-31"]
 )
 
-dataset = dataset.drop([x for x in list(dataset.variables) if x not in ['time','lat','lon','cot','cth','ctt']])
+dataset = dataset.drop([x for x in list(dataset.variables) if
+                        x not in ['time', 'lat', 'lon', 'cot', 'cth', 'ctt']])
+
+dataset = dataset.chunk(dict(time=-1, lat=64, lon=64))
 
-dataset = dataset.chunk(dict(time=-1,lat=64,lon=64))
 
 def get_dates_8d(year):
-    return np.arange(np.datetime64(f"{year}-01-05"), np.datetime64(f"{year+1}-01-01"), np.timedelta64(8, "D")).astype("datetime64[ns]")
+    return np.arange(np.datetime64(f"{year}-01-05"),
+                     np.datetime64(f"{year + 1}-01-01"),
+                     np.timedelta64(8, "D")).astype("datetime64[ns]")
+
 
-dates = np.concatenate([get_dates_8d(year) for year in np.arange(2000,2015)])
-dates = dates[(dates >= np.datetime64("2000-02-15")) & (dates <= np.datetime64("2014-12-16"))]
+dates = np.concatenate([get_dates_8d(year) for year in np.arange(2000, 2015)])
+dates = dates[(dates >= np.datetime64("2000-02-15")) & (
+            dates <= np.datetime64("2014-12-16"))]
 
 print("Resampling in time")
-dataset_8d = dataset.interp(coords=dict(time=dates),method="nearest")
+dataset_8d = dataset.interp(coords=dict(time=dates), method="nearest")
 
 new_lats = np.load("lat.npy")
 new_lons = np.load("lon.npy")
 
 print("Resampling in space")
-dataset_8d = dataset_8d.interp(coords=dict(lat=new_lats,lon=new_lons),method="nearest")
-dataset_8d = dataset_8d.chunk(dict(time=256,lat=128,lon=128))
+dataset_8d = dataset_8d.interp(coords=dict(lat=new_lats, lon=new_lons),
+                               method="nearest")
+dataset_8d = dataset_8d.chunk(dict(time=256, lat=128, lon=128))
 
 print("Saving")
-dataset_8d.to_zarr("/net/scratch/dmontero/CCI/cci-cloud-8d-0.083deg-256x128x128.zarr")
+dataset_8d.to_zarr(f"{pathOut}/cci-cloud-8d-0.083deg-256x128x128.zarr")
diff --git a/ESDC/inputs-preprocess/CCI/cloud/cci-cloud-8d-0.25deg.py b/ESDC/inputs-preprocess/CCI/cloud/cci-cloud-8d-0.25deg.py
index 2fc0eae..653c23f 100644
--- a/ESDC/inputs-preprocess/CCI/cloud/cci-cloud-8d-0.25deg.py
+++ b/ESDC/inputs-preprocess/CCI/cloud/cci-cloud-8d-0.25deg.py
@@ -1,14 +1,7 @@
-from xcube.core.store import find_data_store_extensions
-from xcube.core.store import get_data_store_params_schema
-from xcube.core.store import new_data_store
+import os
 
-import shapely.geometry
-from IPython.display import JSON
-import matplotlib.pyplot as plt
 import numpy as np
-from tqdm import tqdm
-import xarray as xr
-import os
+from xcube.core.store import new_data_store
 
 pathOut = "~/data/CCI/cloud/preprocess"
 pathOut = os.path.expanduser(pathOut)
@@ -20,30 +13,38 @@
 store = new_data_store('cciodp')
 
 dataset = store.open_data(
-    'esacci.CLOUD.mon.L3C.CLD_PRODUCTS.MODIS.Terra.MODIS_TERRA.2-0.r1', 
-    variable_names=['cot','cth','ctt'],
-    time_range=["2000-02-01","2014-12-31"]
+    'esacci.CLOUD.mon.L3C.CLD_PRODUCTS.MODIS.Terra.MODIS_TERRA.2-0.r1',
+    variable_names=['cot', 'cth', 'ctt'],
+    time_range=["2000-02-01", "2014-12-31"]
 )
 
-dataset = dataset.drop([x for x in list(dataset.variables) if x not in ['time','lat','lon','cot','cth','ctt']])
+dataset = dataset.drop([x for x in list(dataset.variables) if
+                        x not in ['time', 'lat', 'lon', 'cot', 'cth', 'ctt']])
+
+dataset = dataset.chunk(dict(time=-1, lat=64, lon=64))
 
-dataset = dataset.chunk(dict(time=-1,lat=64,lon=64))
 
 def get_dates_8d(year):
-    return np.arange(np.datetime64(f"{year}-01-05"), np.datetime64(f"{year+1}-01-01"), np.timedelta64(8, "D")).astype("datetime64[ns]")
+    return np.arange(np.datetime64(f"{year}-01-05"),
+                     np.datetime64(f"{year + 1}-01-01"),
+                     np.timedelta64(8, "D")).astype("datetime64[ns]")
+
 
-dates = np.concatenate([get_dates_8d(year) for year in np.arange(2000,2015)])
-dates = dates[(dates >= np.datetime64("2000-02-15")) & (dates <= np.datetime64("2014-12-16"))]
+dates = np.concatenate([get_dates_8d(year) for year in np.arange(2000, 2015)])
+dates = dates[(dates >= np.datetime64("2000-02-15")) & (
+            dates <= np.datetime64("2014-12-16"))]
 
 print("Resampling in time")
-dataset_8d = dataset.interp(coords=dict(time=dates),method="nearest")
+dataset_8d = dataset.interp(coords=dict(time=dates), method="nearest")
 
-new_lats = np.arange(-89.875,90,0.25)
-new_lons = np.arange(-179.875,180,0.25)
+new_lats = np.arange(-89.875, 90, 0.25)
+new_lons = np.arange(-179.875, 180, 0.25)
 
 print("Resampling in space")
-dataset_8d = dataset_8d.interp(coords=dict(lat=new_lats,lon=new_lons),method="nearest",kwargs={"fill_value": "extrapolate"})
-dataset_8d = dataset_8d.chunk(dict(time=256,lat=128,lon=128))
+dataset_8d = dataset_8d.interp(coords=dict(lat=new_lats, lon=new_lons),
+                               method="nearest",
+                               kwargs={"fill_value": "extrapolate"})
+dataset_8d = dataset_8d.chunk(dict(time=256, lat=128, lon=128))
 
 print("Saving")
-dataset_8d.to_zarr(f"{pathOut}/cci-cloud-8d-0.25deg-256x128x128.zarr")
\ No newline at end of file
+dataset_8d.to_zarr(f"{pathOut}/cci-cloud-8d-0.25deg-256x128x128.zarr")
diff --git a/ESDC/inputs-preprocess/CCI/cloud/cci-cloud-metadata-0.0833deg.py b/ESDC/inputs-preprocess/CCI/cloud/cci-cloud-metadata-0.0833deg.py
index 02d1fa5..fea92f3 100644
--- a/ESDC/inputs-preprocess/CCI/cloud/cci-cloud-metadata-0.0833deg.py
+++ b/ESDC/inputs-preprocess/CCI/cloud/cci-cloud-metadata-0.0833deg.py
@@ -1,22 +1,30 @@
-from tqdm import tqdm
+import os
 from datetime import datetime
-import yaml
-import rioxarray
+
 import xarray as xr
-import numpy as np
+import yaml
+
+pathIn = "~/data/CCI/cloud/preprocess"
+pathIn = os.path.expanduser(pathIn)
+
+pathOut = "~/data/CCI/cloud/output"
+pathOut = os.path.expanduser(pathOut)
 
+if not os.path.exists(pathOut):
+    os.makedirs(pathOut)
 
-with open("cci-cloud-metadata-0.0833deg.yaml", "r") as stream:
+with open("inputs-preprocess/CCI/cloud/cci-cloud-metadata-0.0833deg.yaml",
+          "r") as stream:
     try:
         metadata = yaml.safe_load(stream)
     except yaml.YAMLError as exc:
         print(exc)
 
-datacube = xr.open_zarr("/net/scratch/dmontero/CCI/cci-cloud-8d-0.083deg-256x128x128.zarr")
+datacube = xr.open_zarr(f"{pathIn}/cci-cloud-8d-0.083deg-256x128x128.zarr")
 
 datacube = datacube.rio.write_crs(
     "epsg:4326", grid_mapping_name="crs"
-).reset_coords()    
+).reset_coords()
 del datacube.crs.attrs["spatial_ref"]
 
 datacube.attrs = metadata["global"]
@@ -44,4 +52,4 @@
     sorted({**datacube.attrs, **additional_attrs}.items())
 )
 
-datacube.to_zarr("/net/scratch/dmontero/CCI/metadata/cci-cloud-8d-0.083deg-256x128x128.zarr")
+datacube.to_zarr(f"{pathOut}/cci-cloud-8d-0.083deg-256x128x128.zarr")
diff --git a/ESDC/inputs-preprocess/CCI/cloud/cci-cloud-metadata.py b/ESDC/inputs-preprocess/CCI/cloud/cci-cloud-metadata.py
index 84437e0..63f73ef 100644
--- a/ESDC/inputs-preprocess/CCI/cloud/cci-cloud-metadata.py
+++ b/ESDC/inputs-preprocess/CCI/cloud/cci-cloud-metadata.py
@@ -1,10 +1,8 @@
-from tqdm import tqdm
+import os
 from datetime import datetime
-import yaml
-import rioxarray
+
 import xarray as xr
-import numpy as np
-import os
+import yaml
 
 pathIn = "~/data/CCI/cloud/preprocess"
 pathIn = os.path.expanduser(pathIn)
@@ -14,8 +12,7 @@
 
 if not os.path.exists(pathOut):
     os.makedirs(pathOut)
-
-with open("cci-cloud-metadata.yaml", "r") as stream:
+with open("inputs-preprocess/CCI/cloud/cci-cloud-metadata.yaml", "r") as stream:
     try:
         metadata = yaml.safe_load(stream)
     except yaml.YAMLError as exc:
@@ -25,7 +22,7 @@
 
 datacube = datacube.rio.write_crs(
     "epsg:4326", grid_mapping_name="crs"
-).reset_coords()    
+).reset_coords()
 del datacube.crs.attrs["spatial_ref"]
 
 datacube.attrs = metadata["global"]
diff --git a/ESDC/inputs-preprocess/CCI/sm/cci-sm-8d-0.083deg.py b/ESDC/inputs-preprocess/CCI/sm/cci-sm-8d-0.083deg.py
index a3b89e2..816c714 100644
--- a/ESDC/inputs-preprocess/CCI/sm/cci-sm-8d-0.083deg.py
+++ b/ESDC/inputs-preprocess/CCI/sm/cci-sm-8d-0.083deg.py
@@ -1,23 +1,20 @@
-from xcube.core.store import find_data_store_extensions
-from xcube.core.store import get_data_store_params_schema
-from xcube.core.store import new_data_store
+import os
 
-import shapely.geometry
-from IPython.display import JSON
-import matplotlib.pyplot as plt
 import numpy as np
-from tqdm import tqdm
 import xarray as xr
 
-print("Reading")
-dataset_8d = xr.open_zarr("/net/scratch/dmontero/CCI/cci-sm-8d-0.25deg-256x128x128.zarr")
+pathOut = "~/data/CCI/sm/preprocess"
+pathOut = os.path.expanduser(pathOut)
 
+print("Reading")
+dataset_8d = xr.open_zarr(f"{pathOut}/cci-sm-8d-0.25deg-256x128x128.zarr")
 new_lats = np.load("lat.npy")
 new_lons = np.load("lon.npy")
 
 print("Resampling in space")
-dataset_8d = dataset_8d.interp(coords=dict(lat=new_lats,lon=new_lons),method="nearest")
-dataset_8d = dataset_8d.chunk(dict(time=256,lat=128,lon=128))
+dataset_8d = dataset_8d.interp(coords=dict(lat=new_lats, lon=new_lons),
+                               method="nearest")
+dataset_8d = dataset_8d.chunk(dict(time=256, lat=128, lon=128))
 
 print("Saving")
-dataset_8d.to_zarr("/net/scratch/dmontero/CCI/cci-sm-8d-0.083deg-256x128x128.zarr")
+dataset_8d.to_zarr(f"{pathOut}/cci-sm-8d-0.083deg-256x128x128.zarr")
diff --git a/ESDC/inputs-preprocess/CCI/sm/cci-sm-8d-0.25deg.py b/ESDC/inputs-preprocess/CCI/sm/cci-sm-8d-0.25deg.py
index c2c4208..7b2cc5b 100644
--- a/ESDC/inputs-preprocess/CCI/sm/cci-sm-8d-0.25deg.py
+++ b/ESDC/inputs-preprocess/CCI/sm/cci-sm-8d-0.25deg.py
@@ -1,7 +1,9 @@
+import glob
+import os
+
 import numpy as np
-from tqdm import tqdm
 import xarray as xr
-import glob
+from tqdm import tqdm
 
 pathOut = "~/data/CCI/sm/preprocess"
 pathOut = os.path.expanduser(pathOut)
@@ -17,25 +19,28 @@
 files.sort()
 
 dataset = [xr.open_zarr(file) for file in tqdm(files)]
-dataset = xr.concat(dataset,dim="time")
+dataset = xr.concat(dataset, dim="time")
 dataset = dataset.chunk(dict(time=256))
 
 last_year = 2020
 first_year = 1979
 
-years = np.arange(first_year,last_year + 1)
+years = np.arange(first_year, last_year + 1)
+
 
-def resample_weekly(ds,year):
+def resample_weekly(ds, year):
     keep_attrs = ds.time.attrs
-    ds = ds.sel(time=slice(f"{year}-01-01",f"{year+1}-01-01")).resample(time="8D").mean()    
-    ds['time'] = ds.time + np.timedelta64(4,"D")
+    ds = ds.sel(time=slice(f"{year}-01-01", f"{year + 1}-01-01")).resample(
+        time="8D").mean()
+    ds['time'] = ds.time + np.timedelta64(4, "D")
     ds.time.attrs = keep_attrs
     return ds
 
+
 print("Resampling in time")
-dataset_8d = [resample_weekly(dataset,year) for year in tqdm(years)]
-dataset_8d = xr.concat(dataset_8d,dim="time")
+dataset_8d = [resample_weekly(dataset, year) for year in tqdm(years)]
+dataset_8d = xr.concat(dataset_8d, dim="time")
 dataset_8d = dataset_8d.chunk(dict(time=256))
 
 print("Saving")
-dataset_8d.to_zarr(f"{pathOut}/cci-sm-8d-0.25deg-256x128x128.zarr")
\ No newline at end of file
+dataset_8d.to_zarr(f"{pathOut}/cci-sm-8d-0.25deg-256x128x128.zarr")
diff --git a/ESDC/inputs-preprocess/CCI/sm/cci-sm-metadata-0.0833deg.py b/ESDC/inputs-preprocess/CCI/sm/cci-sm-metadata-0.0833deg.py
index 297594f..0b09ddc 100644
--- a/ESDC/inputs-preprocess/CCI/sm/cci-sm-metadata-0.0833deg.py
+++ b/ESDC/inputs-preprocess/CCI/sm/cci-sm-metadata-0.0833deg.py
@@ -1,22 +1,24 @@
-from tqdm import tqdm
+import os
 from datetime import datetime
-import yaml
-import rioxarray
+
 import xarray as xr
-import numpy as np
+import yaml
 
+pathOut = "~/data/CCI/sm/output"
+pathOut = os.path.expanduser(pathOut)
 
-with open("cci-sm-metadata-0.0833deg.yaml", "r") as stream:
+with open("inputs-preprocess/CCI/sm/cci-sm-metadata-0.0833deg.yaml",
+          "r") as stream:
     try:
         metadata = yaml.safe_load(stream)
     except yaml.YAMLError as exc:
         print(exc)
 
-datacube = xr.open_zarr("/net/scratch/dmontero/CCI/cci-sm-8d-0.083deg-256x128x128.zarr")
+datacube = xr.open_zarr(f"{pathOut}/cci-sm-8d-0.083deg-256x128x128.zarr")
 
 datacube = datacube.rio.write_crs(
     "epsg:4326", grid_mapping_name="crs"
-).reset_coords()    
+).reset_coords()
 del datacube.crs.attrs["spatial_ref"]
 
 datacube.attrs = metadata["global"]
@@ -44,4 +46,4 @@
     sorted({**datacube.attrs, **additional_attrs}.items())
 )
 
-datacube.to_zarr("/net/scratch/dmontero/CCI/metadata/cci-sm-8d-0.083deg-256x128x128.zarr")
+datacube.to_zarr(f"{pathOut}/cci-sm-8d-0.083deg-256x128x128.zarr")
diff --git a/ESDC/inputs-preprocess/CCI/sm/cci-sm-metadata.py b/ESDC/inputs-preprocess/CCI/sm/cci-sm-metadata.py
index 752f111..c5ef7ef 100644
--- a/ESDC/inputs-preprocess/CCI/sm/cci-sm-metadata.py
+++ b/ESDC/inputs-preprocess/CCI/sm/cci-sm-metadata.py
@@ -1,10 +1,8 @@
-from tqdm import tqdm
+import os
 from datetime import datetime
-import yaml
-import rioxarray
-import xarray as xr
-import numpy as np
 
+import xarray as xr
+import yaml
 
 pathOut = "~/data/CCI/sm/output"
 pathOut = os.path.expanduser(pathOut)
@@ -14,8 +12,7 @@
 
 pathIn = "~/data/CCI/sm/preprocess"
 pathIn = os.path.expanduser(pathIn)
-
-with open("cci-sm-metadata.yaml", "r") as stream:
+with open("inputs-preprocess/CCI/sm/cci-sm-metadata.yaml", "r") as stream:
     try:
         metadata = yaml.safe_load(stream)
     except yaml.YAMLError as exc:
@@ -25,7 +22,7 @@
 
 datacube = datacube.rio.write_crs(
     "epsg:4326", grid_mapping_name="crs"
-).reset_coords()    
+).reset_coords()
 del datacube.crs.attrs["spatial_ref"]
 
 datacube.attrs = metadata["global"]
diff --git a/ESDC/inputs-preprocess/FLUXCOM/fluxcom-data-cube.py b/ESDC/inputs-preprocess/FLUXCOM/fluxcom-data-cube.py
index bb0ebbf..1999323 100644
--- a/ESDC/inputs-preprocess/FLUXCOM/fluxcom-data-cube.py
+++ b/ESDC/inputs-preprocess/FLUXCOM/fluxcom-data-cube.py
@@ -1,7 +1,7 @@
 import xarray as xr
 import numpy as np
 import glob
-
+import os
 from tqdm import tqdm
 
 pathOut = "~/data/FLUXCOM/preprocess"
@@ -49,4 +49,4 @@ def merge_datasets(i):
 fluxcom = fluxcom.chunk(dict(time=256,lat=256,lon=256))
 
 print("Saving")
-fluxcom.to_zarr(f"{pathOut}/fluxcom-8d-0.083deg-256x256x256.zarr")
\ No newline at end of file
+fluxcom.to_zarr(f"{pathOut}/fluxcom-8d-0.083deg-256x256x256.zarr")
diff --git a/ESDC/inputs-preprocess/SIF/GOME2/sif-gome2-JJ-data-cube-0.25deg.py b/ESDC/inputs-preprocess/SIF/GOME2/sif-gome2-JJ-data-cube-0.25deg.py
index e571e99..bc9f8db 100644
--- a/ESDC/inputs-preprocess/SIF/GOME2/sif-gome2-JJ-data-cube-0.25deg.py
+++ b/ESDC/inputs-preprocess/SIF/GOME2/sif-gome2-JJ-data-cube-0.25deg.py
@@ -1,9 +1,8 @@
-import xarray as xr
-import xesmf as xe
-import numpy as np
-from tqdm import tqdm
+import os
 from datetime import datetime
 
+import xarray as xr
+
 pathOut = "~/data/SIF/GOME2-SIF/output"
 pathOut = os.path.expanduser(pathOut)
 
@@ -11,16 +10,18 @@
 dataset = xr.open_zarr(f"{pathOut}/sif-gome2-JJ-8d-0.05deg-256x256x256.zarr")
 
 print("Interpolating")
-dataset = dataset.coarsen(lat=5,lon=5).mean()
-dataset = dataset.chunk(dict(time=-1,lat=64,lon=64))
-dataset = dataset.interpolate_na(dim="time",fill_value="extrapolate")
-dataset = dataset.chunk(dict(time=256,lat=128,lon=128))
+dataset = dataset.coarsen(lat=5, lon=5).mean()
+dataset = dataset.chunk(dict(time=-1, lat=64, lon=64))
+dataset = dataset.interpolate_na(dim="time", fill_value="extrapolate")
+dataset = dataset.chunk(dict(time=256, lat=128, lon=128))
 
 print("Adding attributes")
 dataset.attrs['date_modified'] = str(datetime.now())
 dataset.attrs['time_coverage_end'] = str(dataset.time[-1].values)
 dataset.attrs['time_coverage_start'] = str(dataset.time[0].values)
-dataset.attrs['processing_steps'] = dataset.attrs['processing_steps'] + ['Downsampling to 0.25 deg with mean','Interpolating NA with linear interpolation']
+dataset.attrs['processing_steps'] = dataset.attrs['processing_steps'] + [
+    'Downsampling to 0.25 deg with mean',
+    'Interpolating NA with linear interpolation']
 
 dataset.attrs['geospatial_lat_max'] = float(dataset.lat.max().values)
 dataset.attrs['geospatial_lat_min'] = float(dataset.lat.min().values)
@@ -31,4 +32,4 @@
 dataset.attrs['geospatial_lon_resolution'] = 0.25
 
 print("Saving")
-dataset.to_zarr(f"{pathOut}/sif-gome2-JJ-8d-0.25deg-256x128x128.zarr")
\ No newline at end of file
+dataset.to_zarr(f"{pathOut}/sif-gome2-JJ-8d-0.25deg-256x128x128.zarr")
diff --git a/ESDC/inputs-preprocess/SIF/GOME2/sif-gome2-JJ-data-cube.py b/ESDC/inputs-preprocess/SIF/GOME2/sif-gome2-JJ-data-cube.py
index 5faf440..e7d2f52 100644
--- a/ESDC/inputs-preprocess/SIF/GOME2/sif-gome2-JJ-data-cube.py
+++ b/ESDC/inputs-preprocess/SIF/GOME2/sif-gome2-JJ-data-cube.py
@@ -1,14 +1,7 @@
-import xarray as xr
-import numpy as np
 import glob
 import os
-import datetime
-from tqdm import tqdm
-
-# pathOut = "/net/projects/deep_esdl/data/GOME2-SIF/cubes/"
 
-# if not os.path.exists(pathOut):
-#    os.mkdir(pathOut)
+import xarray as xr
 
 pathIn = "~/data/SIF/GOME2-SIF/source"
 pathIn = os.path.expanduser(pathIn)
@@ -18,13 +11,14 @@
 
 if not os.path.exists(pathOut):
     os.makedirs(pathOut)
-    
+
 files = glob.glob(f"{pathIn}/*JJ*.nc")
 files.sort()
 
-datasets = [xr.open_dataset(file,chunks = {'lat':256, 'lon':256, 'time':256}) for file in files]
-datasets = xr.concat(datasets,dim = "time").drop("crs")
-datasets = datasets.transpose("time","lat","lon")
-datasets = datasets.chunk({'lat':256, 'lon':256, 'time':256})
+datasets = [xr.open_dataset(file, chunks={'lat': 256, 'lon': 256, 'time': 256})
+            for file in files]
+datasets = xr.concat(datasets, dim="time").drop("crs")
+datasets = datasets.transpose("time", "lat", "lon")
+datasets = datasets.chunk({'lat': 256, 'lon': 256, 'time': 256})
 
 datasets.to_zarr(f"{pathOut}/sif-gome2-JJ-256x256x256.zarr")
diff --git a/ESDC/inputs-preprocess/SIF/GOME2/sif-gome2-JJ-metadata.py b/ESDC/inputs-preprocess/SIF/GOME2/sif-gome2-JJ-metadata.py
index fc02ebe..86920c7 100644
--- a/ESDC/inputs-preprocess/SIF/GOME2/sif-gome2-JJ-metadata.py
+++ b/ESDC/inputs-preprocess/SIF/GOME2/sif-gome2-JJ-metadata.py
@@ -1,10 +1,8 @@
-from tqdm import tqdm
+import os
 from datetime import datetime
-import yaml
-import rioxarray
-import xarray as xr
-import numpy as np
 
+import xarray as xr
+import yaml
 
 pathIn = "~/data/SIF/GOME2-SIF/preprocess"
 pathIn = os.path.expanduser(pathIn)
@@ -15,7 +13,8 @@
 if not os.path.exists(pathOut):
     os.makedirs(pathOut)
 
-with open("sif-gome2-JJ-metadata.yaml", "r") as stream:
+with open("inputs-preprocess/SIF/GOME2/sif-gome2-JJ-metadata.yaml",
+          "r") as stream:
     try:
         metadata = yaml.safe_load(stream)
     except yaml.YAMLError as exc:
@@ -25,7 +24,7 @@
 
 datacube = datacube.rio.write_crs(
     "epsg:4326", grid_mapping_name="crs"
-).reset_coords()    
+).reset_coords()
 del datacube.crs.attrs["spatial_ref"]
 
 datacube.attrs = metadata["global"]
@@ -53,4 +52,5 @@
     sorted({**datacube.attrs, **additional_attrs}.items())
 )
 
-datacube.to_zarr(f"{pathOutput}/sif-gome2-JJ-8d-0.05deg-256x256x256.zarr",mode = "w")
\ No newline at end of file
+datacube.to_zarr(f"{pathOut}/sif-gome2-JJ-8d-0.05deg-256x256x256.zarr",
+                 mode="w")
diff --git a/ESDC/inputs-preprocess/SIF/GOME2/sif-gome2-PK-data-cube-0.25deg.py b/ESDC/inputs-preprocess/SIF/GOME2/sif-gome2-PK-data-cube-0.25deg.py
index d862901..31b06a9 100644
--- a/ESDC/inputs-preprocess/SIF/GOME2/sif-gome2-PK-data-cube-0.25deg.py
+++ b/ESDC/inputs-preprocess/SIF/GOME2/sif-gome2-PK-data-cube-0.25deg.py
@@ -1,9 +1,8 @@
-import xarray as xr
-import xesmf as xe
-import numpy as np
-from tqdm import tqdm
+import os
 from datetime import datetime
 
+import xarray as xr
+
 pathOut = "~/data/SIF/GOME2-SIF/output"
 pathOut = os.path.expanduser(pathOut)
 
@@ -11,16 +10,18 @@
 dataset = xr.open_zarr(f"{pathOut}/sif-gome2-PK-8d-0.05deg-256x256x256.zarr")
 
 print("Interpolating")
-dataset = dataset.coarsen(lat=5,lon=5).mean()
-dataset = dataset.chunk(dict(time=-1,lat=64,lon=64))
-dataset = dataset.interpolate_na(dim="time",fill_value="extrapolate")
-dataset = dataset.chunk(dict(time=256,lat=128,lon=128))
+dataset = dataset.coarsen(lat=5, lon=5).mean()
+dataset = dataset.chunk(dict(time=-1, lat=64, lon=64))
+dataset = dataset.interpolate_na(dim="time", fill_value="extrapolate")
+dataset = dataset.chunk(dict(time=256, lat=128, lon=128))
 
 print("Adding attributes")
 dataset.attrs['date_modified'] = str(datetime.now())
 dataset.attrs['time_coverage_end'] = str(dataset.time[-1].values)
 dataset.attrs['time_coverage_start'] = str(dataset.time[0].values)
-dataset.attrs['processing_steps'] = dataset.attrs['processing_steps'] + ['Downsampling to 0.25 deg with mean','Interpolating NA with linear interpolation']
+dataset.attrs['processing_steps'] = dataset.attrs['processing_steps'] + [
+    'Downsampling to 0.25 deg with mean',
+    'Interpolating NA with linear interpolation']
 
 dataset.attrs['geospatial_lat_max'] = float(dataset.lat.max().values)
 dataset.attrs['geospatial_lat_min'] = float(dataset.lat.min().values)
@@ -31,4 +32,4 @@
 dataset.attrs['geospatial_lon_resolution'] = 0.25
 
 print("Saving")
-dataset.to_zarr(f"{pathOut}/sif-gome2-PK-8d-0.25deg-256x128x128.zarr")
\ No newline at end of file
+dataset.to_zarr(f"{pathOut}/sif-gome2-PK-8d-0.25deg-256x128x128.zarr")
diff --git a/ESDC/inputs-preprocess/SIF/GOME2/sif-gome2-PK-data-cube.py b/ESDC/inputs-preprocess/SIF/GOME2/sif-gome2-PK-data-cube.py
index 619340f..862c4c4 100644
--- a/ESDC/inputs-preprocess/SIF/GOME2/sif-gome2-PK-data-cube.py
+++ b/ESDC/inputs-preprocess/SIF/GOME2/sif-gome2-PK-data-cube.py
@@ -1,14 +1,7 @@
-import xarray as xr
-import numpy as np
 import glob
 import os
-import datetime
-from tqdm import tqdm
-
-# pathOut = "/net/projects/deep_esdl/data/GOME2-SIF/cubes/"
 
-# if not os.path.exists(pathOut):
-#    os.mkdir(pathOut)
+import xarray as xr
 
 pathIn = "~/data/SIF/GOME2-SIF/source"
 pathIn = os.path.expanduser(pathIn)
@@ -18,13 +11,14 @@
 
 if not os.path.exists(pathOut):
     os.makedirs(pathOut)
-    
+
 files = glob.glob(f"{pathIn}/*PK*.nc")
 files.sort()
 
-datasets = [xr.open_dataset(file,chunks = {'lat':256, 'lon':256, 'time':256}) for file in files]
-datasets = xr.concat(datasets,dim = "time").drop("crs")
-datasets = datasets.transpose("time","lat","lon")
-datasets = datasets.chunk({'lat':256, 'lon':256, 'time':256})
+datasets = [xr.open_dataset(file, chunks={'lat': 256, 'lon': 256, 'time': 256})
+            for file in files]
+datasets = xr.concat(datasets, dim="time").drop("crs")
+datasets = datasets.transpose("time", "lat", "lon")
+datasets = datasets.chunk({'lat': 256, 'lon': 256, 'time': 256})
 
 datasets.to_zarr(f"{pathOut}/sif-gome2-PK-256x256x256.zarr")
diff --git a/ESDC/inputs-preprocess/SIF/GOME2/sif-gome2-PK-metadata.py b/ESDC/inputs-preprocess/SIF/GOME2/sif-gome2-PK-metadata.py
index 01f56b9..9135f28 100644
--- a/ESDC/inputs-preprocess/SIF/GOME2/sif-gome2-PK-metadata.py
+++ b/ESDC/inputs-preprocess/SIF/GOME2/sif-gome2-PK-metadata.py
@@ -1,9 +1,8 @@
-from tqdm import tqdm
+import os
 from datetime import datetime
-import yaml
-import rioxarray
+
 import xarray as xr
-import numpy as np
+import yaml
 
 pathIn = "~/data/SIF/GOME2-SIF/preprocess"
 pathIn = os.path.expanduser(pathIn)
@@ -14,7 +13,8 @@
 if not os.path.exists(pathOut):
     os.makedirs(pathOut)
 
-with open("sif-gome2-PK-metadata.yaml", "r") as stream:
+with open("inputs-preprocess/SIF/GOME2/sif-gome2-PK-metadata.yaml",
+          "r") as stream:
     try:
         metadata = yaml.safe_load(stream)
     except yaml.YAMLError as exc:
@@ -24,7 +24,7 @@
 
 datacube = datacube.rio.write_crs(
     "epsg:4326", grid_mapping_name="crs"
-).reset_coords()    
+).reset_coords()
 del datacube.crs.attrs["spatial_ref"]
 
 datacube.attrs = metadata["global"]
@@ -52,4 +52,4 @@
     sorted({**datacube.attrs, **additional_attrs}.items())
 )
 
-datacube.to_zarr(f"{pathOut}/sif-gome2-PK-8d-0.05deg-256x256x256.zarr")
\ No newline at end of file
+datacube.to_zarr(f"{pathOut}/sif-gome2-PK-8d-0.05deg-256x256x256.zarr")
diff --git a/ESDC/inputs-preprocess/SIF/GOSIF/sif-gosif-data-cube-0.25deg.py b/ESDC/inputs-preprocess/SIF/GOSIF/sif-gosif-data-cube-0.25deg.py
index 156c630..ca1fae5 100644
--- a/ESDC/inputs-preprocess/SIF/GOSIF/sif-gosif-data-cube-0.25deg.py
+++ b/ESDC/inputs-preprocess/SIF/GOSIF/sif-gosif-data-cube-0.25deg.py
@@ -1,9 +1,9 @@
-import xarray as xr
-import xesmf as xe
-import numpy as np
-from tqdm import tqdm
+import os
 from datetime import datetime
 
+import numpy as np
+import xarray as xr
+
 pathOut = "~/data/SIF/GOSIF/output"
 pathOut = os.path.expanduser(pathOut)
 
@@ -12,21 +12,22 @@
 
 print("Fixing time")
 keep_attrs = dataset.time.attrs
-dataset["time"] = dataset.time + np.timedelta64(4,"D")
+dataset["time"] = dataset.time + np.timedelta64(4, "D")
 dataset.time.attrs = keep_attrs
 
 print("Coarsing")
-dataset = dataset.coarsen(lat=5,lon=5).mean()
+dataset = dataset.coarsen(lat=5, lon=5).mean()
 
 print("Chunking")
-dataset = dataset.chunk(dict(time=256,lat=128,lon=128))
+dataset = dataset.chunk(dict(time=256, lat=128, lon=128))
 
 print("Adding attrs")
 dataset.attrs['date_modified'] = str(datetime.now())
 dataset.attrs['time_coverage_end'] = str(dataset.time[-1].values)
 dataset.attrs['time_coverage_start'] = str(dataset.time[0].values)
 dataset.attrs['reported_day'] = 5.0
-dataset.attrs['processing_steps'] = dataset.attrs['processing_steps'] + ['Downsampling to 0.25 deg with mean']
+dataset.attrs['processing_steps'] = dataset.attrs['processing_steps'] + [
+    'Downsampling to 0.25 deg with mean']
 
 dataset.attrs['geospatial_lat_max'] = float(dataset.lat.max().values)
 dataset.attrs['geospatial_lat_min'] = float(dataset.lat.min().values)
@@ -40,4 +41,4 @@
 del dataset['sif'].encoding['chunks']
 
 print("Saving")
-dataset.to_zarr(f"{pathOut}/sif-gosif-8d-0.25deg-256x128x128.zarr")
\ No newline at end of file
+dataset.to_zarr(f"{pathOut}/sif-gosif-8d-0.25deg-256x128x128.zarr")
diff --git a/ESDC/inputs-preprocess/SIF/GOSIF/sif-gosif-data-cube-part1.py b/ESDC/inputs-preprocess/SIF/GOSIF/sif-gosif-data-cube-part1.py
index a85e13c..f602c84 100644
--- a/ESDC/inputs-preprocess/SIF/GOSIF/sif-gosif-data-cube-part1.py
+++ b/ESDC/inputs-preprocess/SIF/GOSIF/sif-gosif-data-cube-part1.py
@@ -1,14 +1,10 @@
-import xarray as xr
-import numpy as np
+import datetime
 import glob
 import os
-import datetime
-from tqdm import tqdm
-
-# pathOut = "/net/projects/deep_esdl/data/GOSIF/cubes/"
 
-# if not os.path.exists(pathOut):
-#     os.mkdir(pathOut)
+import numpy as np
+import xarray as xr
+from tqdm import tqdm
 
 pathIn = "~/data/SIF/GOSIF/source"
 pathIn = os.path.expanduser(pathIn)
@@ -16,16 +12,22 @@
 files = glob.glob(f"{pathIn}/*.tif")
 files.sort()
 
+
 def to_xarray(file):
     filename = file.split("/")[-1]
-    date = np.datetime64(datetime.datetime.strptime(filename[6:13],'%Y%j'))
-    ds = xr.open_dataset(file,engine = "rasterio",chunks = {"x":1024,"y":1024}).where(lambda x: x < 32766,other = np.nan)
-    ds = ds.reset_coords().band_data.sel(band = 1).drop("band").rename({"y": "lat", "x":"lon"})
+    date_info = filename.split("_", 1)[1].split(".")[0]
+    date = np.datetime64(datetime.datetime.strptime(date_info, '%Y%j'))
+    ds = xr.open_dataset(file, engine="rasterio",
+                         chunks={"x": 1024, "y": 1024}).where(
+        lambda x: x < 32766, other=np.nan)
+    ds = ds.reset_coords().band_data.sel(band=1).drop("band").rename(
+        {"y": "lat", "x": "lon"})
     ds.name = "sif"
     ds = ds.to_dataset()
     ds = ds.assign_coords({"time": date}).expand_dims("time")
     ds = ds * 0.0001
-    ds = ds.transpose("time","lat","lon")
-    ds.to_zarr(f"{pathIn}/{filename.replace('.tif','.zarr')}")
+    ds = ds.transpose("time", "lat", "lon")
+    ds.to_zarr(f"{pathIn}/{filename.replace('.tif', '.zarr')}")
+
 
-[to_xarray(file) for file in tqdm(files)]
\ No newline at end of file
+[to_xarray(file) for file in tqdm(files)]
diff --git a/ESDC/inputs-preprocess/SIF/GOSIF/sif-gosif-data-cube-part2.py b/ESDC/inputs-preprocess/SIF/GOSIF/sif-gosif-data-cube-part2.py
index ae7f746..a3aac9c 100644
--- a/ESDC/inputs-preprocess/SIF/GOSIF/sif-gosif-data-cube-part2.py
+++ b/ESDC/inputs-preprocess/SIF/GOSIF/sif-gosif-data-cube-part2.py
@@ -1,14 +1,8 @@
-import xarray as xr
-import numpy as np
 import glob
 import os
-import datetime
-from tqdm import tqdm
 
-# pathOut = "/net/projects/deep_esdl/data/GOSIF/cubes/"
-
-# if not os.path.exists(pathOut):
-#     os.mkdir(pathOut)
+import xarray as xr
+from tqdm import tqdm
 
 pathIn = "~/data/SIF/GOSIF/source"
 pathIn = os.path.expanduser(pathIn)
@@ -18,7 +12,7 @@
 
 if not os.path.exists(pathOut):
     os.makedirs(pathOut)
-   
+
 files = glob.glob(f"{pathIn}/*.zarr")
 files.sort()
 
@@ -30,7 +24,7 @@
     ds = xr.open_zarr(file)
     ds["lon"] = ref.lon
     datasets.append(ds)
-    
-datasets = xr.concat(datasets,dim = "time")
 
-datasets.to_zarr(f"{pathOut}/sif-gosif-1x1024x1024.zarr")
\ No newline at end of file
+datasets = xr.concat(datasets, dim="time")
+
+datacube = xr.open_zarr(f"{pathIn}/sif-gosif-1x1024x1024.zarr")
diff --git a/ESDC/inputs-preprocess/SIF/GOSIF/sif-gosif-metadata.py b/ESDC/inputs-preprocess/SIF/GOSIF/sif-gosif-metadata.py
index 9633bd8..de6f0e6 100644
--- a/ESDC/inputs-preprocess/SIF/GOSIF/sif-gosif-metadata.py
+++ b/ESDC/inputs-preprocess/SIF/GOSIF/sif-gosif-metadata.py
@@ -1,9 +1,8 @@
-from tqdm import tqdm
+import os
 from datetime import datetime
-import yaml
-import rioxarray
+
 import xarray as xr
-import numpy as np
+import yaml
 
 pathIn = "~/data/SIF/GOSIF/preprocess"
 pathIn = os.path.expanduser(pathIn)
@@ -14,7 +13,7 @@
 if not os.path.exists(pathOut):
     os.makedirs(pathOut)
 
-with open("sif-gosif-metadata.yaml", "r") as stream:
+with open("inputs-preprocess/SIF/GOSIF/sif-gosif-metadata.yaml", "r") as stream:
     try:
         metadata = yaml.safe_load(stream)
     except yaml.YAMLError as exc:
@@ -24,7 +23,7 @@
 
 datacube = datacube.rio.write_crs(
     "epsg:4326", grid_mapping_name="crs"
-).reset_coords()    
+).reset_coords()
 del datacube.crs.attrs["spatial_ref"]
 
 datacube.attrs = metadata["global"]
@@ -52,4 +51,4 @@
     sorted({**datacube.attrs, **additional_attrs}.items())
 )
 
-datacube.to_zarr(f"{pathOut}/sif-gosif-8d-0.05deg-1x1024x1024.zarr")
\ No newline at end of file
+datacube.to_zarr(f"{pathOut}/sif-gosif-8d-0.05deg-1x1024x1024.zarr")
diff --git a/ESDC/inputs-preprocess/SIF/RTSIF/sif-rtsif-data-cube-0.25deg.py b/ESDC/inputs-preprocess/SIF/RTSIF/sif-rtsif-data-cube-0.25deg.py
index 4640ed6..3b7579a 100644
--- a/ESDC/inputs-preprocess/SIF/RTSIF/sif-rtsif-data-cube-0.25deg.py
+++ b/ESDC/inputs-preprocess/SIF/RTSIF/sif-rtsif-data-cube-0.25deg.py
@@ -3,6 +3,7 @@
 import numpy as np
 from tqdm import tqdm
 from datetime import datetime
+import os
 
 pathIn = "~/data/SIF/RTSIF/preprocess"
 pathIn = os.path.expanduser(pathIn)
diff --git a/ESDC/inputs-preprocess/SIF/RTSIF/sif-rtsif-metadata.py b/ESDC/inputs-preprocess/SIF/RTSIF/sif-rtsif-metadata.py
index a53a894..320dfa6 100644
--- a/ESDC/inputs-preprocess/SIF/RTSIF/sif-rtsif-metadata.py
+++ b/ESDC/inputs-preprocess/SIF/RTSIF/sif-rtsif-metadata.py
@@ -4,7 +4,7 @@
 import rioxarray
 import xarray as xr
 import numpy as np
-
+import os
 pathIn = "path-to-RTSIF-cube"
 
 pathOut = "~/data/SIF/RTSIF/preprocess"
@@ -13,7 +13,7 @@
 if not os.path.exists(pathOut):
     os.makedirs(pathOut)
 
-with open("sif-rtsif-metadata.yaml", "r") as stream:
+with open("inputs-preprocess/SIF/RTSIF/sif-rtsif-metadata.yaml", "r") as stream:
     try:
         metadata = yaml.safe_load(stream)
     except yaml.YAMLError as exc: