fix satellite

bopen · Jul 9, 2024 · 4f1db87 · 4f1db87
1 parent b4d6b19
commit 4f1db87
Showing 1 changed file with 18 additions and 28 deletions.
diff --git a/notebooks/wp5/satellite_surface_radiation_budget.ipynb b/notebooks/wp5/satellite_surface_radiation_budget.ipynb
@@ -75,8 +75,7 @@
     "        \"climate_data_record_type\": \"thematic_climate_data_record\",\n",
     "        \"format\": \"zip\",\n",
     "        \"origin\": \"c3s\",\n",
-    "        \"product_family\": \"clara\",\n",
-    "        \"sensor_on_satellite\": \"avhrr_on_multiple_satellites\",\n",
+    "        \"product_family\": \"clara_a2\",\n",
     "        \"time_aggregation\": \"monthly_mean\",\n",
     "        \"variable\": \"surface_upwelling_shortwave_flux\",\n",
     "        \"version\": \"v2_0_1\",\n",
@@ -87,8 +86,7 @@
     "        \"climate_data_record_type\": \"thematic_climate_data_record\",\n",
     "        \"format\": \"zip\",\n",
     "        \"origin\": \"eumetsat\",\n",
-    "        \"product_family\": \"clara\",\n",
-    "        \"sensor_on_satellite\": \"avhrr_on_multiple_satellites\",\n",
+    "        \"product_family\": \"clara_a2\",\n",
     "        \"time_aggregation\": \"monthly_mean\",\n",
     "        \"variable\": [\n",
     "            \"surface_downwelling_longwave_flux\",\n",
@@ -126,7 +124,7 @@
     "        \"format\": \"zip\",\n",
     "        \"origin\": \"c3s\",\n",
     "        \"product_family\": \"cci\",\n",
-    "        \"sensor_on_satellite\": \"slstr_on_sentinel_3a_is_under_investigation\",\n",
+    "        \"sensor_on_satellite\": \"slstr_on_sentinel_3a\",\n",
     "        \"time_aggregation\": \"monthly_mean\",\n",
     "        \"variable\": \"all_variables\",\n",
     "    },\n",
@@ -137,7 +135,7 @@
     "        \"format\": \"zip\",\n",
     "        \"origin\": \"c3s\",\n",
     "        \"product_family\": \"cci\",\n",
-    "        \"sensor_on_satellite\": \"slstr_on_sentinel_3b_is_under_investigation\",\n",
+    "        \"sensor_on_satellite\": \"slstr_on_sentinel_3b\",\n",
     "        \"time_aggregation\": \"monthly_mean\",\n",
     "        \"variable\": \"all_variables\",\n",
     "    },\n",
@@ -159,29 +157,19 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "def convert_source_to_time(ds):\n",
-    "    if \"source\" in ds.dims:\n",
-    "        ds[\"time\"] = (\n",
-    "            \"source\",\n",
-    "            pd.to_datetime(\n",
-    "                [source.split(\"_\")[-2] + \"15\" for source in ds[\"source\"].values],\n",
-    "                format=\"%Y%m%d\",\n",
-    "            ),\n",
-    "        )\n",
-    "        ds[\"time\"].attrs[\"standard_name\"] = \"time\"\n",
-    "        ds = ds.swap_dims(source=\"time\").drop(\"source\")\n",
+    "def preprocess_time(ds):\n",
+    "    if \"time\" in ds and \"units\" in ds[\"time\"].attrs:\n",
+    "        # Could not decode\n",
+    "        ds = ds.squeeze(\"time\", drop=True)\n",
+    "    if \"time\" not in ds:\n",
+    "        time = pd.to_datetime(ds.attrs[\"time_coverage_start\"])\n",
+    "        ds = ds.assign_coords(time=time)\n",
     "    return ds\n",
     "\n",
     "\n",
     "def spatial_weighted_mean(ds, lon_slice, lat_slice):\n",
-    "    ds = convert_source_to_time(ds)\n",
     "    ds = utils.regionalise(ds, lon_slice=lon_slice, lat_slice=lat_slice)\n",
-    "    return diagnostics.spatial_weighted_mean(ds)\n",
-    "\n",
-    "\n",
-    "def time_weighted_mean(ds):\n",
-    "    ds = convert_source_to_time(ds)\n",
-    "    return diagnostics.time_weighted_mean(ds)"
+    "    return diagnostics.spatial_weighted_mean(ds)"
    ]
   },
   {
@@ -199,6 +187,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "xarray_kwargs = {\"drop_variables\": \"time_bounds\", \"preprocess\": preprocess_time}\n",
+    "\n",
     "ds_maps = {}\n",
     "ds_timeseries = {}\n",
     "for product, request in request_dict.items():\n",
@@ -213,10 +203,10 @@
     "    ds = download.download_and_transform(\n",
     "        collection_id,\n",
     "        requests,\n",
-    "        transform_func=time_weighted_mean,\n",
+    "        transform_func=diagnostics.time_weighted_mean,\n",
     "        chunks=chunks,\n",
     "        transform_chunks=False,\n",
-    "        drop_variables=\"time_bounds\",\n",
+    "        **xarray_kwargs,\n",
     "    )\n",
     "    ds.attrs.update({\"start\": start, \"stop\": stop})\n",
     "    ds_maps[product] = ds.rename({var: var.lower() for var in ds.data_vars})\n",
@@ -231,7 +221,7 @@
     "            \"lat_slice\": slice(-90, 90),\n",
     "        },\n",
     "        chunks=chunks,\n",
-    "        drop_variables=\"time_bounds\",\n",
+    "        **xarray_kwargs,\n",
     "    )\n",
     "    ds_timeseries[product] = ds.rename({var: var.lower() for var in ds.data_vars})"
    ]
@@ -337,7 +327,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.12"
+   "version": "3.11.9"
   }
  },
  "nbformat": 4,