Take home messages

Author: wplouvie

precipitation-girafe.ipynb

@@ -72,14 +72,7 @@
     "\n",
     "![banner](./img/girafe-banner.png)\n",
     "\n",
-    "Anthropogenic activities and natural variations from years to decades shape the Earth's climate. Water and energy cycles are central to the physics of climate change. Within the hydrological cycle, precipitation has been recognised as an Essential Climate Variable (ECV) as it is the main component of water transport from the atmosphere to the Earth’s surface. Precipitation varies strongly, depending on geographical location, season, synopsis, and other meteorological factors. The supply with freshwater through precipitation is vital for many subsystems of the climate and the environment, but there are also hazards related to extensive precipitation (floods) or to the lack of precipitation (droughts).\n",
-    "\n",
-    "In the Copernicus Climate Data Store (CDS), the EUMETSAT Satellite Application Facility on Climate Monitoring has brokered the Global Interpolated RAinFall Estimation (GIRAFE) product. It merges microwave (MW) sounder- and imager-based estimations of instantaneous surface precipitation (over land and ocean) with infrared (IR) observations from geostationary platforms along the equator. GIRAFE is a global 1° x 1° latitude-longitude data record that is produced at a daily temporal resolution, as well as on a monthly mean basis. It covers the time period January 2002 to December 2022.\n",
-    "\n",
-    "In this Jupyter notebook tutorial, we present examples, based on monthly mean Precipitation products, to illustrate the philosophy on the usage, visualisation, and analysis of the dataset. First you get to sort out data access and retrieval, and get all the right libraries in place for the computations. Then we take you through a short process of inspecting the retrieved data to see if it's all ok for analysis. You then have a chance to visualise your data, before we take you through some climatology analyses that you could use in your work.\n",
-    "\n",
-    "You will find further information about the dataset (Algorithm Theoretical Basis Document, Product User Guide and Specification, etc.) as well as the data in the Climate Data Store catalogue entry ***Monthly and daily global interpolated rainfall estimation data from 2002 to 2022 derived from satellite measurements*** (see the link to the entry below), sections \"[Overview](https://cds.climate.copernicus.eu/datasets/satellite-precipitation-microwave-infrared?tab=overview)\", \"[Download data](https://cds.climate.copernicus.eu/datasets/satellite-precipitation-microwave-infrared?tab=download)\" and \"[Documentation](https://cds.climate.copernicus.eu/datasets/satellite-precipitation-microwave-infrared?tab=documentation)\":\n",
-    "- [Monthly and daily global interpolated rainfall estimation data from 2002 to 2022 derived from satellite measurements](https://cds.climate.copernicus.eu/datasets/satellite-precipitation-microwave-infrared?tab=overview)"
+    "Anthropogenic activities and natural variations from years to decades shape the Earth's climate. Water and energy cycles are central to the physics of climate change. Within the hydrological cycle, precipitation has been recognised as an Essential Climate Variable (ECV) as it is the main component of water transport from the atmosphere to the Earth’s surface. Precipitation varies strongly, depending on geographical location, season, synopsis, and other meteorological factors. The supply with freshwater through precipitation is vital for many subsystems of the climate and the environment, but there are also hazards related to extensive precipitation (floods) or to the lack of precipitation (droughts)."
    ]
   },
   {
@@ -123,12 +116,7 @@
    },
    "outputs": [],
    "source": [
-    "!pip install -q earthkit\n",
-    "\n",
-    "!pip install -q cdsapi\n",
-    "# If you have already setup your .cdsapirc file you can leave this as None\n",
-    "cdsapi_key = None\n",
-    "cdsapi_url = None"
+    "!pip install -q earthkit"
    ]
   },
   {
@@ -194,7 +182,14 @@
     "tags": []
    },
    "source": [
-    "## Explore the data"
+    "## Explore the data\n",
+    "\n",
+    "In the Copernicus Climate Data Store (CDS), the EUMETSAT Satellite Application Facility on Climate Monitoring has brokered the Global Interpolated RAinFall Estimation (GIRAFE) product. It merges microwave (MW) sounder- and imager-based estimations of instantaneous surface precipitation (over land and ocean) with infrared (IR) observations from geostationary platforms along the equator. GIRAFE is a global 1° x 1° latitude-longitude data record that is produced at a daily temporal resolution, as well as on a monthly mean basis. It covers the time period January 2002 to December 2022.\n",
+    "\n",
+    "In this Jupyter notebook tutorial, we present examples, based on monthly mean Precipitation products, to illustrate the philosophy on the usage, visualisation, and analysis of the dataset. First you get to sort out data access and retrieval, and get all the right libraries in place for the computations. Then we take you through a short process of inspecting the retrieved data to see if it's all ok for analysis. You then have a chance to visualise your data, before we take you through some climatology analyses that you could use in your work.\n",
+    "\n",
+    "You will find further information about the dataset (Algorithm Theoretical Basis Document, Product User Guide and Specification, etc.) as well as the data in the Climate Data Store catalogue entry ***Monthly and daily global interpolated rainfall estimation data from 2002 to 2022 derived from satellite measurements*** (see the link to the entry below), sections \"[Overview](https://cds.climate.copernicus.eu/datasets/satellite-precipitation-microwave-infrared?tab=overview)\", \"[Download data](https://cds.climate.copernicus.eu/datasets/satellite-precipitation-microwave-infrared?tab=download)\" and \"[Documentation](https://cds.climate.copernicus.eu/datasets/satellite-precipitation-microwave-infrared?tab=documentation)\":\n",
+    "- [Monthly and daily global interpolated rainfall estimation data from 2002 to 2022 derived from satellite measurements](https://cds.climate.copernicus.eu/datasets/satellite-precipitation-microwave-infrared?tab=overview)"
    ]
   },
   {
@@ -6459,9 +6454,12 @@
     ]
    },
    "source": [
-    "## Conclusion\n",
+    "## Take home messages 📌\n",
     "\n",
-    "In this notebook we have provided some use cases, based on the global interpolated rainfall estimation (GIRAFE) Precipitation product to illustrate the way this dataset can be used to study, analyse and visualise this essential climate variable. The high values found along the equator can be explained by the Inter-Tropical Convergence Zone and the moderately high values observed in the region of the Gulf Stream extension and Kurushio are associated to the storm track regions. Comparisons with other independent datasets can be made to further investigate trends (like more frequent episodes of floods and droughts) that can be attributed to global climate change, El-Niño events, etc."
+    "- Use cases to illustrate how the global interpolated rainfall estimation (GIRAFE) Precipitation product can be used to study, analyse and visualise this essential climate variable.\n",
+    "- The high values found along the equator can be explained by the Inter-Tropical Convergence Zone\n",
+    "- The moderately high values observed in the region of the Gulf Stream extension and Kurushio are associated to the storm track regions. \n",
+    "- Comparisons with other independent datasets to further investigate trends (like more frequent episodes of floods and droughts) that can be attributed to global climate change, El-Niño events, etc."
    ]
   }
  ],