diff --git a/tests/produce_data.ipynb b/tests/produce_data.ipynb
index 14d00e9942a2257bcbc428890b3f25050520f4a1..c604debdeb9a911ea9292f43e892c2517b47b4ca 100644
--- a/tests/produce_data.ipynb
+++ b/tests/produce_data.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -18,41 +18,62 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
     "#creation of request.\n",
     "\n",
-    "Config = namedtuple(\"Config\", [\"grid\", \"time\", \"variables\", \"stats\"])\n",
+    "Config = namedtuple(\"Config\", [\"grid\", \"time\", \"variables\", \"stats\",\"moreOptions\"])\n",
+    "\n",
+    "#moreOptions is implemented as a dict to add additional arguments to the query to the REST API\n",
+    "#For example the field toar1_category with its possible values Urban, RuralLowElevation, RuralHighElevation and Unclassified can be added.\n",
+    "#see page 18 in  https://toar-data.fz-juelich.de/sphinx/TOAR_UG_Vol03_Database/build/latex/toardatabase--userguide.pdf\n",
     "\n",
     "valid_data = Config(\n",
     "    RegularGrid( lat_resolution=1.9, lon_resolution=2.5, ),\n",
     "    TimeSample( start=dt(2014,1,1), end=dt(2019,12,31), sampling=\"daily\"),\n",
     "    [\"mole_fraction_of_ozone_in_air\"],#variable name\n",
-    "    [\"mean\"]# [\"dma8epax\"], # enable when finished\n",
+    "    [\"mean\"],# [\"dma8epax\"], # enable when finished\n",
+    "    {}\n",
     ")\n",
     "missing_data = Config(\n",
     "    RegularGrid( lat_resolution=1.9, lon_resolution=2.5),\n",
     "    TimeSample( start=dt(2000,1,1), end=dt(2013,12,31), sampling=\"daily\"),\n",
     "    [\"mole_fraction_of_ozone_in_air\"],\n",
-    "    [\"dma8epax\"],\n",
+    "    [\"mean\"],\n",
+    "    #[\"dma8epax\"],\n",
+    "    {}\n",
     ")\n",
     "\n",
     "configs = {\n",
-    "    \"test_ta\": valid_data\n",
+    "    #\"test_ta\"  : valid_data\n",
+    "    \"test_ta2\" : missing_data\n",
     "}\n",
     "\n",
     "#testing access:\n",
-    "config = configs[\"test_ta\"]\n",
-    "config.grid"
+    "#config = configs[\"test_ta\"]\n",
+    "#config.grid"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "load status endpoint from cache\n",
+      "try: 1, wait_time: 300\n",
+      "try: 2, wait_time: 300\n",
+      "try: 3, wait_time: 300\n",
+      "try: 4, wait_time: 300\n",
+      "try: 5, wait_time: 300\n"
+     ]
+    }
+   ],
    "source": [
     "#CAVE: this cell runs about 30minutes per requested year\n",
     "#the processing is done on the server of the TOAR database.\n",
@@ -71,6 +92,7 @@
     "        time=config.time,\n",
     "        variables=config.variables,\n",
     "        stats=config.stats\n",
+    "        #**config.moreOptions\n",
     "    )\n",
     "\n",
     "    for dataset, metadata in zip(datasets, metadatas):\n",
diff --git a/toargridding/toar_rest_client.py b/toargridding/toar_rest_client.py
index 554960f25de4b457efbf69f4517a42cefb5e6b9f..2e5e54c5553f58af3d3d3de327350edbafe86574 100644
--- a/toargridding/toar_rest_client.py
+++ b/toargridding/toar_rest_client.py
@@ -339,15 +339,13 @@ class AnalysisService:
         # remove data where utc -> sun/local ? time conversion leads to dateshift
         newDates = metadata.time.as_datetime_index()
         if len(timeseries.columns) == len(newDates)+2:
+            print(f"Info: removed columns {timeseries.columns[0]} and {timeseries.columns[-1]} to match data range of {newDates[0]} to {newDates[-1]}")
             timeseries.drop(columns=[first, last], inplace=True)
-            print("Info: removed first and last column from retrieved timeseries")
         elif len(timeseries.columns) == len(newDates)+1:
+            print(f"Info: removed columns {timeseries.columns[-1]} to match data range of {newDates[0]} to {newDates[-1]}")
             timeseries.drop(columns=[last], inplace=True)
-            print("Info: removed last column from retrieved timeseries")
         else:
             raise RuntimeError(f"There is a mismatch in the timestamps...\nDownloaded:{timeseries.columns}\nFrom Metadata: {newDates}")
-        print(timeseries.columns)
-        print(newDates)
         timeseries.columns = newDates 
 
         all_na = timeseries.isna().all(axis=1)