diff --git a/notebooks/examp_easyms2022.ipynb b/notebooks/examp_easyms2022.ipynb
index d57f3a5e04b4a74194c0ba848863641b3f4eab83..1829d7a5ce5d8003e95c62cc3b02d3dea1a9376f 100644
--- a/notebooks/examp_easyms2022.ipynb
+++ b/notebooks/examp_easyms2022.ipynb
@@ -366,6 +366,29 @@
     "## Plotting meridional sections"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "bc2ba869-6b03-4fc7-a3c1-2d9c5b7c5237",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 751.967x480.314 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ds_3d.to.isel(time=-1).pyic.plot_sec(section='gzave',\n",
+    "                                     fpath_fx='/home/m/m300602/work/icon/grids/r2b4_oce_r0004/r2b4_oce_r0004_L40_fx.nc',\n",
+    "                                     res=2.0,)"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 12,
@@ -430,7 +453,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 27,
    "id": "54357aa3-b360-45e0-80fe-84d5f83a5324",
    "metadata": {},
    "outputs": [
@@ -446,11 +469,10 @@
     }
    ],
    "source": [
-    "pyic.plot_sec(ds_3d.to.isel(time=-1), \n",
-    "              section='gzave',\n",
-    "              fpath_fx='/home/m/m300602/work/icon/grids/r2b4_oce_r0004/r2b4_oce_r0004_L40_fx.nc',\n",
-    "              res=2.0, # choose something >= 1.0 to avoid \n",
-    "             )"
+    "ds_3d.to.isel(time=-1).pyic.plot_sec(section='gzave',\n",
+    "                                     fpath_fx='/home/m/m300602/work/icon/grids/r2b4_oce_r0004/r2b4_oce_r0004_L40_fx.nc',\n",
+    "                                     res=2.0, # choose something >= 1.0 to avoid overprecision\n",
+    "                                    )"
    ]
   },
   {
@@ -463,7 +485,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 28,
    "id": "5cc04bab-6fc0-48f5-8d6a-09dda45d14fb",
    "metadata": {},
    "outputs": [
@@ -479,11 +501,10 @@
     }
    ],
    "source": [
-    "pyic.plot_sec(ds_3d.to.isel(time=-1), \n",
-    "              section='azave',\n",
-    "              fpath_fx='/home/m/m300602/work/icon/grids/r2b4_oce_r0004/r2b4_oce_r0004_L40_fx.nc',\n",
-    "              res=2.0, # choose something >= 1.0 to avoid \n",
-    "             )"
+    "ds_3d.to.isel(time=-1).pyic.plot_sec(section='azave',\n",
+    "                                     fpath_fx='/home/m/m300602/work/icon/grids/r2b4_oce_r0004/r2b4_oce_r0004_L40_fx.nc',\n",
+    "                                     res=2.0, # choose something >= 1.0 to avoid overprecision\n",
+    "                                    )"
    ]
   },
   {
@@ -496,7 +517,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 29,
    "id": "01d4cbe3-c54c-4bf5-9696-19192382d459",
    "metadata": {},
    "outputs": [
@@ -512,11 +533,10 @@
     }
    ],
    "source": [
-    "pyic.plot_sec(ds_3d.to.isel(time=-1), \n",
-    "              section='ipzave',\n",
-    "              fpath_fx='/home/m/m300602/work/icon/grids/r2b4_oce_r0004/r2b4_oce_r0004_L40_fx.nc',\n",
-    "              res=2.0, # choose something >= 1.0 to avoid \n",
-    "             )"
+    "ds_3d.to.isel(time=-1).pyic.plot_sec(section='ipzave',\n",
+    "                                     fpath_fx='/home/m/m300602/work/icon/grids/r2b4_oce_r0004/r2b4_oce_r0004_L40_fx.nc',\n",
+    "                                     res=2.0, # choose something >= 1.0 to avoid overprecision\n",
+    "                                    )"
    ]
   },
   {