diff --git a/quartz_solar_forecast/dataset/make_test_set.py b/quartz_solar_forecast/dataset/make_test_set.py
index a52e9648..eb4cf0b3 100644
--- a/quartz_solar_forecast/dataset/make_test_set.py
+++ b/quartz_solar_forecast/dataset/make_test_set.py
@@ -2,6 +2,9 @@
 Make a random test set
 
 This takes a random subset of times and for various pv ids and makes a test set
+
+There is an option to odmit timestamps that don't exsits in the ICON dataset:
+https://huggingface.co/datasets/openclimatefix/dwd-icon-eu/tree/main/data
 """
 import os
 from typing import Optional
@@ -9,6 +12,9 @@
 import numpy as np
 import pandas as pd
 
+from quartz_solar_forecast.eval.utils import make_hf_filename
+from huggingface_hub import HfFileSystem
+
 test_start_date = pd.Timestamp("2021-01-01")
 test_end_date = pd.Timestamp("2022-01-01")
 
@@ -69,7 +75,7 @@
 np.random.seed(42)
 
 
-def make_test_set(output_file_name: Optional[str] = None, number_of_samples_per_system: int = 50):
+def make_test_set(output_file_name: Optional[str] = None, number_of_samples_per_system: int = 50, check_hf_files: bool = False):
     """
     Make a test set of random times and pv ids
 
@@ -81,16 +87,47 @@ def make_test_set(output_file_name: Optional[str] = None, number_of_samples_per_
         # get the folder where this file is
         output_file_name = os.path.dirname(os.path.abspath(__file__)) + "/testset.csv"
 
+    ts = pd.date_range(start=test_start_date, end=test_end_date, freq="15min")
+
+    # check that the files are in HF for ICON
+    if check_hf_files:
+        ts = filter_timestamps_if_hf_files_exists(ts)
+
     test_set = []
     for pv_id in pv_ids:
-        ts = pd.date_range(start=test_start_date, end=test_end_date, freq="15min")
-        ts = ts[np.random.choice(len(ts), size=number_of_samples_per_system, replace=False)]
-        test_set.append(pd.DataFrame({"pv_id": pv_id, "timestamp": ts}))
+        ts_choice = ts[np.random.choice(len(ts), size=number_of_samples_per_system, replace=False)]
+        test_set.append(pd.DataFrame({"pv_id": pv_id, "timestamp": ts_choice}))
     test_set = pd.concat(test_set)
     test_set.to_csv(output_file_name, index=False)
 
     return test_set
 
 
+def filter_timestamps_if_hf_files_exists(timestamps_full: pd.DatetimeIndex):
+    """
+    Filter the timestamps if the huggingface files exist
+
+    We are checking if the teimstamps, rounded down to the nearest 6 hours,
+    exist in
+    https://huggingface.co/datasets/openclimatefix/dwd-icon-eu/tree/main/data
+
+    """
+    timestamps = []
+    fs = HfFileSystem()
+    # print(fs.ls("datasets/openclimatefix/dwd-icon-eu/data/2022/4/11/", detail=False))
+    for timestamp in timestamps_full:
+        timestamp_floor = timestamp.floor("6H")
+        _, huggingface_file = make_hf_filename(timestamp_floor)
+        huggingface_file = huggingface_file[14:]
+
+        if fs.exists(huggingface_file):
+            timestamps.append(timestamp)
+        else:
+            print(f"Skipping {timestamp} because {huggingface_file} does not exist")
+
+    timestamps = pd.DatetimeIndex(timestamps)
+    return timestamps
+
+
 # To run the script, un comment the following line and run this file
-# make_test_set()
+# make_test_set(check_hf_files=True)
diff --git a/quartz_solar_forecast/dataset/testset.csv b/quartz_solar_forecast/dataset/testset.csv
index 5f47aaab..96a40e79 100644
--- a/quartz_solar_forecast/dataset/testset.csv
+++ b/quartz_solar_forecast/dataset/testset.csv
@@ -1,2501 +1,2501 @@
 pv_id,timestamp
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diff --git a/quartz_solar_forecast/eval/nwp.py b/quartz_solar_forecast/eval/nwp.py
index a8030394..2f530a2d 100644
--- a/quartz_solar_forecast/eval/nwp.py
+++ b/quartz_solar_forecast/eval/nwp.py
@@ -1,14 +1,16 @@
 """ Get nwp data from HF"""
 import os
+import sys
 import pandas as pd
 import numpy as np
 
 import ocf_blosc2  # noqa
 import xarray as xr
-from huggingface_hub import HfFileSystem
 
 import multiprocessing
 
+from quartz_solar_forecast.eval.utils import make_hf_filename
+
 multiprocessing.set_start_method("spawn", force=True)
 
 
@@ -38,7 +40,6 @@ def get_nwp(time_locations: pd.DataFrame):
                 "progress": np.round(i / len(time_locations), 3),
             }
 
-
             # collect together args for pool.starmap
             task_arg = list(kwargs.values())
             tasks_args.append(task_arg)
@@ -81,16 +82,7 @@ def get_nwp_for_one_timestamp_one_location(
 
     # round timestamp to 6 hours floor
     timestamp_floor = timestamp.floor("6H")
-    year = timestamp_floor.year
-    month = timestamp_floor.month
-    day = timestamp_floor.day
-    date_and_hour = timestamp_floor.strftime("%Y%m%d_%H")
-
-    date = f"{year}/{month}/{day}"
-    file_location = f"{date}/{date_and_hour}"
-    huggingface_route = "zip:///::hf://datasets/openclimatefix/dwd-icon-eu/data"
-    # huggingface_route = "datasets/openclimatefix/dwd-icon-eu/data"
-    huggingface_file = f"{huggingface_route}/{file_location}.zarr.zip"
+    date_and_hour, huggingface_file = make_hf_filename(timestamp_floor)
 
     # dataset variables
     variables = ["t_2m", "tot_prec", "clch", "clcm", "clcl", "u", "v", "aswdir_s", "aswdifd_s"]
@@ -100,6 +92,7 @@ def get_nwp_for_one_timestamp_one_location(
     if not os.path.exists(cache_file):
         # use fsspec to copy file
         print(f"Opening file {huggingface_file} from HF to local")
+        sys.stdout.flush()
 
         data = xr.open_zarr(
             f"{huggingface_file}",
@@ -177,3 +170,5 @@ def get_nwp_for_one_timestamp_one_location(
         print(f"Getting NWP for {timestamp} {pv_id}. Progress: {100*progress}%")
 
     return df
+
+
diff --git a/quartz_solar_forecast/eval/utils.py b/quartz_solar_forecast/eval/utils.py
index 3cfa115a..8c216a6e 100644
--- a/quartz_solar_forecast/eval/utils.py
+++ b/quartz_solar_forecast/eval/utils.py
@@ -41,3 +41,23 @@ def combine_forecast_ground_truth(forecast_df: pd.DataFrame, ground_truth_df: pd
     combined_df = pd.merge(forecast_df, ground_truth_df, on=["timestamp", "pv_id", "horizon_hour"])
 
     return combined_df
+
+
+def make_hf_filename(timestamp_floor):
+    """
+    Make ICON filename from timestamp_floor
+
+    '2021-01-01 00:00:00' ->
+    'zip:///::hf://datasets/openclimatefix/dwd-icon-eu/data/2021/1/1/20210101_00.zarr.zip'
+
+    """
+    year = timestamp_floor.year
+    month = timestamp_floor.month
+    day = timestamp_floor.day
+    date_and_hour = timestamp_floor.strftime("%Y%m%d_%H")
+    date = f"{year}/{month}/{day}"
+    file_location = f"{date}/{date_and_hour}"
+    huggingface_route = "zip:///::hf://datasets/openclimatefix/dwd-icon-eu/data"
+    # huggingface_route = "datasets/openclimatefix/dwd-icon-eu/data"
+    huggingface_file = f"{huggingface_route}/{file_location}.zarr.zip"
+    return date_and_hour, huggingface_file