diff --git a/notebooks/wp5/satellite_esacci_gmpe_trends.ipynb b/notebooks/wp5/satellite_esacci_gmpe_trends.ipynb
index 57a801e..5cf37a3 100644
--- a/notebooks/wp5/satellite_esacci_gmpe_trends.ipynb
+++ b/notebooks/wp5/satellite_esacci_gmpe_trends.ipynb
@@ -217,7 +217,7 @@
     "            chunks=chunks,\n",
     "            transform_chunks=False,\n",
     "            transform_func=compute_low_resolution,\n",
-    "            transform_func_kwargs={\"freq\": \"Q-DEC\" if seasonal else \"MS\"},\n",
+    "            transform_func_kwargs={\"freq\": \"QE-DEC\" if seasonal else \"MS\"},\n",
     "            **open_mfdataset_kwargs,\n",
     "        )\n",
     "        dataarrays.append(rechunk(ds[\"analysed_sst\"]))\n",
@@ -227,8 +227,8 @@
     "        ds = da.groupby(\"time.season\").map(_mann_kendall, **mann_kendall_kwargs)\n",
     "        ds[\"trend\"].attrs[\"units\"] = f\"{da.attrs['units']}/year\"\n",
     "    else:\n",
-    "        ds = _mann_kendall(da, **mann_kendall_kwargs)\n",
-    "        ds[\"trend\"].attrs[\"units\"] = f\"{da.attrs['units']}/month\"\n",
+    "        ds = da.groupby(\"time.year\").map(_mann_kendall, **mann_kendall_kwargs)\n",
+    "        ds[\"trend\"].attrs[\"units\"] = f\"{da.attrs['units']}/year\"\n",
     "    return rechunk(ds)"
    ]
   },
@@ -264,6 +264,8 @@
     "        )\n",
     "        for coord in (\"longitude\", \"latitude\"):\n",
     "            ds[coord] = ds[coord].round(3)\n",
+    "        if not seasonal:\n",
+    "            ds = ds.mean(\"year\", keep_attrs=True)\n",
     "        ds = ds.expand_dims(product=[product])\n",
     "        datasets.append(rechunk(ds))\n",
     "    maps_datasets[f\"{seasonal=}\"] = xr.concat(datasets, \"product\")\n",
@@ -330,7 +332,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.12"
+   "version": "3.11.9"
   }
  },
  "nbformat": 4,