Add markdown narrative cells to GRIB example

doc/examples/ERA5-GRIB-example.ipynb

@@ -1,5 +1,19 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# GRIB Data Example "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "GRIB format is commonly used to disemminate atmospheric model data. With Xarray and the cfgrib engine, GRIB data can easily be analyzed and visualized."
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -10,6 +24,13 @@
     "import matplotlib.pyplot as plt"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To read GRIB data, you can use `xarray.load_dataset`. The only extra code you need is to specify the engine as `cfgrib`."
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -19,6 +40,13 @@
     "ds = xr.load_dataset('data/era5-2mt-2019-03-uk.grib', engine='cfgrib')"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Let's create a simple plot of 2-m air temperature in degrees Celsius:"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -29,6 +57,13 @@
     "ds.t2m[0].plot(cmap=plt.cm.coolwarm)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "With CartoPy, we can create a more detailed plot, using built-in shapefiles to help provide geographic context:"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -45,21 +80,21 @@
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
+   "cell_type": "markdown",
    "metadata": {},
-   "outputs": [],
    "source": [
-    "ds.t2m.sel(longitude=0,latitude=51.5).plot()\n",
-    "plt.title('ERA5 - London 2m temperature March 2019')"
+    "Finally, we can also pull out a time series for a given location easily:"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "ds.t2m.sel(longitude=0,latitude=51.5).plot()\n",
+    "plt.title('ERA5 - London 2m temperature March 2019')"
+   ]
   }
  ],
  "metadata": {