diff --git a/RELEASE_NOTES.rst b/RELEASE_NOTES.rst
index acbb91bd..0e040e4b 100644
--- a/RELEASE_NOTES.rst
+++ b/RELEASE_NOTES.rst
@@ -17,6 +17,13 @@ Upcoming Release
    To use the features already you have to install the ``master`` branch, e.g.
    ``pip install git+https://github.com/pypsa/atlite``.
 
+**Bug fixes**
+
+* Fill missing irradiation data with zero for ``trigon_model="other"``, as for
+  ``trigon_model="simple"``. Before, cells without data, e.g. north of 65° N in SARAH
+  cutouts, returned NaN and made aggregated time series NaN
+  (https://github.com/PyPSA/atlite/pull/528).
+
 `v0.7.0 <https://github.com/PyPSA/atlite/releases/tag/v0.7.0>`__ (3rd October 2026)
 =======================================================================================
 
diff --git a/atlite/pv/irradiation.py b/atlite/pv/irradiation.py
index 3cf9f526..b84d6432 100644
--- a/atlite/pv/irradiation.py
+++ b/atlite/pv/irradiation.py
@@ -362,7 +362,7 @@ def clip(influx: xr.DataArray, influx_max: xr.DataArray) -> xr.DataArray:
             ds, solar_position, surface_orientation, direct + diffuse
         )
 
-        total_t = direct_t + diffuse_t + ground_t
+        total_t = direct_t.fillna(0.0) + diffuse_t.fillna(0.0) + ground_t.fillna(0.0)
 
     result: xr.DataArray
     if irradiation == "total":
diff --git a/test/test_irradiation.py b/test/test_irradiation.py
new file mode 100644
index 00000000..6d895bc1
--- /dev/null
+++ b/test/test_irradiation.py
@@ -0,0 +1,42 @@
+# SPDX-FileCopyrightText: Contributors to atlite <https://github.com/pypsa/atlite>
+#
+# SPDX-License-Identifier: MIT
+
+"""Tests for the irradiation on tilted surfaces."""
+
+import numpy as np
+import pandas as pd
+import pytest
+import xarray as xr
+
+from atlite.convert import convert_irradiation
+from atlite.pv.orientation import get_orientation
+
+
+@pytest.mark.parametrize("trigon_model", ["simple", "other"])
+def test_total_irradiation_is_zero_where_data_is_missing(trigon_model):
+    time = pd.date_range("2013-06-01 10:00", periods=3, freq="h")
+    coords = {"time": time, "y": [50.0, 70.0], "x": [5.0]}
+
+    def var(values):
+        return (("time", "y", "x"), np.broadcast_to(values, (3, 2, 1)).copy())
+
+    missing = np.array([[1.0], [np.nan]])
+    ds = xr.Dataset(
+        {
+            "influx_toa": var(1000.0),
+            "influx_direct": var(300.0 * missing),
+            "influx_diffuse": var(100.0 * missing),
+            "albedo": var(0.2),
+            "solar_altitude": var(0.8 * missing),
+            "solar_azimuth": var(3.0 * missing),
+        },
+        coords=coords,
+    )
+    ds = ds.assign_coords(lon=("x", coords["x"]), lat=("y", coords["y"]))
+    orientation = get_orientation({"slope": 30.0, "azimuth": 180.0})
+
+    res = convert_irradiation(ds, orientation, trigon_model=trigon_model)
+
+    assert (res.sel(y=50.0) > 0).all()
+    assert (res.sel(y=70.0) == 0).all()