diff --git a/mlair/reference_data_handler/IntelliO3v1Reference.py b/mlair/reference_data_handler/IntelliO3v1Reference.py
new file mode 100644
index 0000000000000000000000000000000000000000..ca2f025cfe47e4bbdf7e81918ab86701f27a855e
--- /dev/null
+++ b/mlair/reference_data_handler/IntelliO3v1Reference.py
@@ -0,0 +1,127 @@
+"""
+Extract forecasts from intelliO3 and store them for MLAir
+
+"""
+
+__author__ = "Felix Kleinert"
+__date__ = "2021-01-29"
+
+import os
+import xarray as xr
+import wget
+import sys
+import shutil
+
+from mlair.configuration.path_config import check_path_and_create
+from mlair.reference_data_handler.abstract_reference_data_handler import AbstractReferenceModel
+
+
+class AbstractReferenceb2share(AbstractReferenceModel):
+ """
+ Abstract class for reference models located on b2share (eudat or fz-juelich)
+ See also https://github.com/EUDAT-Training/B2SHARE-Training/blob/master/api/01_Retrieve_existing_record.md
+
+ """
+ def __init__(self, b2share_hosturl: str, b2share_bucket: str, b2share_key: str):
+ super().__init__()
+ self.b2share_hosturl = b2share_hosturl
+ self.b2share_bucket = b2share_bucket
+ self.b2share_key = b2share_key
+
+ @property
+ def b2share_url(self):
+ return f"{self.b2share_hosturl}/api/files/{self.b2share_bucket}"
+
+ def bar_custom(self, current, total, width=80):
+ progress_message = f"Downloading {self.b2share_key}: {round(current / total * 100)}% [{current} / {total}] bytes"
+ sys.stdout.write("\r" + progress_message)
+ sys.stdout.flush()
+
+ def download_from_b2share(self, tmp_download_path: str):
+ check_path_and_create(tmp_download_path)
+ wget.download(f"{self.b2share_url}/{self.b2share_key}",
+ out=f"{tmp_download_path}{self.b2share_key}",
+ bar=self.bar_custom)
+
+
+class IntelliO3Reference(AbstractReferenceb2share):
+ """
+ Reference handler that extracts IntelliO3-ts v1.0 forecasts (Kleinert, 2021).
+
+ IntelliO3 forecasts can be used as a competitive model within MLAir. Downloads the IntelliO3 tar-ball and extracts
+ the forecasts.
+
+ Kleinert, F., Leufen, L. H., and Schultz, M. G.: IntelliO3-ts v1.0: a neural network approach to predict
+ near-surface ozone concentrations in Germany, Geosci. Model Dev., 14, 1–25,
+ https://doi.org/10.5194/gmd-14-1-2021, 2021.
+ """
+
+ def __init__(self, ref_name: str, ref_store_path: str = None):
+ """
+ :param ref_name: Desired Name of reference forecast
+ :type ref_name: str
+ :param ref_store_path: Path to store reference forecasts
+ :type ref_store_path: str
+ """
+ super().__init__(b2share_hosturl="https://b2share.eudat.eu",
+ b2share_bucket="0cae9db2-f388-4136-8d28-9d9c5665d641",
+ b2share_key="IntelliO3-ts.tar.gz",
+ )
+ self.ref_name = ref_name
+ if ref_store_path is None:
+ ref_store_path = f"{self.ref_name}/"
+ self.ref_store_path = ref_store_path
+ self.tmp_extract_path = "tmp_download/"
+ self.orig_forecast_path = "IntelliO3-ts/IntelliO3-ts_network/forecasts/"
+ self.file_pattern = "forecasts_DE?????_test.nc"
+
+ def untar_forecasts(self):
+ """
+ Extracts IntelliO3 forecasts from tar-ball.
+ """
+ cmd = f"tar -xf {self.tmp_extract_path}{self.b2share_key} --directory {self.tmp_extract_path} --wildcards --no-anchored '{self.orig_forecast_path}{self.file_pattern}'"
+ os.system(cmd)
+
+ def file_list(self):
+ """
+ :return: base dir of tmp path and list of forecast files
+ :rtype: tuple(str, list(str))
+ """
+ for root, dirs, file_names in os.walk(self.tmp_extract_path+self.orig_forecast_path):
+ pass
+ return root, file_names
+
+ def read_and_drop(self, sel_coords: dict = None):
+ """
+ Reads original forecast files, renames coord type and store forecasts as NetCdf4 files
+ :param sel_coords:
+ :type sel_coords:
+ """
+ if sel_coords is None:
+ sel_coords = {'type': 'CNN'}
+ in_path, files = self.file_list()
+ check_path_and_create(self.ref_store_path)
+ for infile in files:
+ data = xr.open_dataarray(f"{in_path}{infile}")
+ data = data.sel(**sel_coords)
+ data.coords['type'] = (self.ref_name)
+ data.to_netcdf(f"{self.ref_store_path}{infile}")
+
+ def make_reference_available_locally(self):
+ """
+
+ :return:
+ :rtype:
+ """
+ if not self.is_reference_available_locally(self.ref_store_path):
+ if not os.path.exists(self.tmp_extract_path+self.b2share_key):
+ self.download_from_b2share(tmp_download_path=self.tmp_extract_path)
+ self.untar_forecasts()
+ self.read_and_drop()
+ shutil.rmtree(self.tmp_extract_path)
+
+
+if __name__ == '__main__':
+ io3 = IntelliO3Reference('IntelliO3-ts')
+ io3.make_reference_available_locally()
+
diff --git a/mlair/reference_data_handler/__init__.py b/mlair/reference_data_handler/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/mlair/reference_data_handler/abstract_reference_data_handler.py b/mlair/reference_data_handler/abstract_reference_data_handler.py
new file mode 100644
index 0000000000000000000000000000000000000000..e9d129a722b1e90c07012d9c942f6f70e5d0d69a
--- /dev/null
+++ b/mlair/reference_data_handler/abstract_reference_data_handler.py
@@ -0,0 +1,32 @@
+__author__ = "Felix Kleinert"
+__date__ = "2021-01-29"
+
+import os
+from abc import ABC
+
+
+class AbstractReferenceModel(ABC):
+ """
+ Abstract reference model. All classes providing some reference or competitor models must inherent from this class.
+ """
+ def __init__(self, *args, **kwargs):
+ pass
+
+ def make_reference_available_locally(self):
+ raise NotImplementedError
+
+ @staticmethod
+ def is_reference_available_locally(reference_path) -> bool:
+ """
+ Checks if reference is available locally
+ """
+
+ try:
+ if os.listdir(reference_path):
+ res = True
+ else:
+ res = False
+ except FileNotFoundError:
+ res = False
+ return res
+