update approach paragraph

doc/source/example_notebooks/IS2_data_read-in.ipynb

@@ -22,10 +22,7 @@
     "Instead of needing to manually iterate through the beam pairs, you can provide a few options to the `Read` object and icepyx will do the heavy lifting for you (as detailed in this notebook).\n",
     "\n",
     "### Approach\n",
-    "If you're interested in what's happening under the hood: icepyx turns your instructions into something called a catalog, then uses the Intake library and the catalog to actually load the data into memory. Specifically, icepyx creates an [Intake](https://intake.readthedocs.io/en/latest/) data [catalog](https://intake.readthedocs.io/en/latest/catalog.html) for each requested variable and then merges the read-in data from each of the variables to create a single data object.\n",
-    "\n",
-    "Intake catalogs are powerful (and the tool we selected) because they can be saved, shared, modified, and reused to reproducibly read in a set of data files in a consistent way as part of an analysis workflow.\n",
-    "This approach streamlines the transition between data sources (local/downloaded files or, ultimately, cloud/bucket access) and data object types (e.g. [Xarray Dataset](http://xarray.pydata.org/en/stable/generated/xarray.Dataset.html) or [GeoPandas GeoDataFrame](https://geopandas.org/docs/reference/api/geopandas.GeoDataFrame.html))."
+    "If you're interested in what's happening under the hood: icepyx uses the [xarray](https://docs.xarray.dev/en/stable/) library to read in each of the requested variables of the dataset. icepyx formats each requested variable and then merges the read-in data from each of the variables to create a single data object. The use of xarray is powerful, because the returned data object can be used with relevant xarray processing tools."
    ]
   },
   {