diff --git a/README.md b/README.md
index 90a7ae73..e43b2abd 100644
--- a/README.md
+++ b/README.md
@@ -29,13 +29,13 @@ This Cookbook is a comprehensive showcase of workflows & techniques for visualiz
 
 ## Structure
 
-This cookbook is split up into three chapters that provide a comprehensive overview of how to use UXarray to work with and visualuze unstructured grid datasets.
+This cookbook is split up into three chapters that provide a detailed overview of how to use UXarray to work with and visualuze unstructured grid datasets:
 
-#### **1. Introduction to UXarray & Unstructured Grids**
+**1. Introduction to UXarray & Unstructured Grids**
 
-#### **2. Methods & Libraries for Unstructured Grid Visualization**
+**2. Methods & Libraries for Unstructured Grid Visualization**
 
-#### **3. UXarray Visualization**
+**3. UXarray Visualization**
 
 ## Running the Notebooks
 
diff --git a/notebooks/01-intro/01-unstructured-grid-overview.ipynb b/notebooks/01-intro/01-unstructured-grid-overview.ipynb
index e5f435e3..09cf875a 100644
--- a/notebooks/01-intro/01-unstructured-grid-overview.ipynb
+++ b/notebooks/01-intro/01-unstructured-grid-overview.ipynb
@@ -18,7 +18,8 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The goal of this notebook is to provide a brief overview of unstructured grids and provide a teaser of plotting with the UXarray package.\n",
+    "The goal of this notebook is to provide a brief overview of unstructured grids and provide a teaser of plotting with the [UXarray](https://uxarray.readthedocs.io/) package.\n",
+    "\n",
     "Contents:\n",
     "1. Structured vs. Unstructured Grids\n",
     "2. Structured Grids\n",
@@ -137,6 +138,13 @@
     "## Unstructured Grids"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Characteristic features of unstructured grids are:"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -232,7 +240,9 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "NOTE: This is a very basic example of an unstructured grid with triangles. There are very specialized libraries to create unstructured grids. Often the region of interest is meshed with a finer resolution. The mesh is then coarsened in areas where the resolution is not needed. This is done to reduce the number of elements and improve computational efficiency."
+    ":::{note}\n",
+    "This is a very basic example of an unstructured grid with triangles. There are very specialized libraries to create unstructured grids. Often the region of interest is meshed with a finer resolution. The mesh is then coarsened in areas where the resolution is not needed. This is done to reduce the number of elements and improve computational efficiency.\n",
+    ":::"
    ]
   },
   {
@@ -241,26 +251,28 @@
    "source": [
     "## Why UXarray for Unstructured Grids?\n",
     "\n",
-    "- It inherits from Xarray, providing simplified data using familiar (Xarray like) data structures and operations.\n",
-    "  \n",
-    "- Bring standardization to unstructured mesh support for climate data analysis and visualization.\n",
+    "UXarray, which stands for \"Unstructured-Xarray\", is a Python package that provides Xarray-styled functionality for working with unstructured grids built around the UGRID conventions. UXarray can simplify working with unstructured grids because it:\n",
     "\n",
-    "- Adherence to the UGRID specification for compatibility across a variety of mesh formats.\n",
+    "- Enables significant data analysis and visualization functionality to be executed dircetly on unstructured grids\n",
+    "\n",
+    "- Inherits from Xarray, providing simplified data using familiar (Xarray-like) data structures and operations\n",
+    "  \n",
+    "- Brings standardization to unstructured mesh support for climate data analysis and visualization\n",
     "\n",
-    "- Optimized data structures and algorithms for handling large and complex unstructured datasets. \n",
+    "- Adheres to the UGRID specification for compatibility across a variety of mesh formats\n",
     "\n",
-    "- Enhanced Interoperability and Community Collaboration.\n",
+    "- Builds on optimized data structures and algorithms for handling large and complex unstructured datasets\n",
     "\n",
-    "- One interface for a variety of unstructured grid formats.\n",
+    "- Supports enhanced interoperability and community collaboration\n",
     "\n",
-    "There are unstructured grid format such as Exodus, SCRIP, MPAS, UGRID etc. UXarray is a library that can read and write many such unstructured grid formats. The specific focus of UXarray is to provide a common interface to access and operate on unstructured grids in the climate science community."
+    "- Provides a single interface for supporting a variety of unstructured grid formats including UGRID, MPAS, SCRIP, and Exodus"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    ":::{info}\n",
+    ":::{note}\n",
     "This notebook serves as an introduction to unstructured grids and UXarray. For more information, please visit the UXarray documentation at https://uxarray.readthedocs.io/en/latest/ and specifically see the example section: https://uxarray.readthedocs.io/en/latest/examples.html\n",
     ":::"
    ]
diff --git a/notebooks/01-intro/02-data-structures.ipynb b/notebooks/01-intro/02-data-structures.ipynb
index 47d38d69..16fe91be 100644
--- a/notebooks/01-intro/02-data-structures.ipynb
+++ b/notebooks/01-intro/02-data-structures.ipynb
@@ -10,113 +10,139 @@
   },
   {
    "cell_type": "markdown",
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    }
+   },
    "source": [
-    "UXarray, which stands for \"Unstructured-Xarray\", extends upon Xarray's core data structures and provides functionality for operating on unstructured (a.k.a. non-regular) grids. \n",
+    "UXarray extends upon Xarray's core data structures (i.e. Dataset and DataArray) and provides functionality for operating on unstructured (a.k.a. non-regular) grids. \n",
     "\n",
     "This notebook will showcase the core UXarray data structures and how to interact with them"
-   ],
-   "metadata": {
-    "collapsed": false
-   }
+   ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    }
+   },
    "outputs": [],
    "source": [
     "import uxarray as ux"
-   ],
-   "metadata": {
-    "collapsed": false
-   }
+   ]
   },
   {
    "cell_type": "markdown",
-   "source": [],
    "metadata": {
-    "collapsed": false
-   }
-  },
-  {
-   "cell_type": "markdown",
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    }
+   },
    "source": [
     "First, lets specify the paths to our Grid and Data files. As mentioned in the previous notebook, unstructured grids are typically separated into two files: one containing the grid topology and one containing data variables that reside on that grid."
-   ],
-   "metadata": {
-    "collapsed": false
-   }
+   ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    }
+   },
    "outputs": [],
    "source": [
     "file_dir = \"../../meshfiles/\"\n",
     "grid_filename = file_dir + \"oQU480.grid.nc\"\n",
     "data_filename = file_dir + \"oQU480.data.nc\""
-   ],
-   "metadata": {
-    "collapsed": false
-   }
+   ]
   },
   {
    "cell_type": "markdown",
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    }
+   },
    "source": [
     "## `Grid` Data Structure\n",
     "\n",
-    "A grid file can be opened standalone using the `ux.open_grid` method, which is a catch-all method that parses the provided input and returns a `Grid` object with grid coordinate and connectivity variables represented in the UGRID conventions.\n",
+    "An unstructured grid file can be opened standalone using the `ux.open_grid` method, which is a catch-all method that parses the provided input and returns a `Grid` object with grid coordinate and connectivity variables represented in the UGRID conventions.\n",
     "\n",
     "Printing our `Grid` instance shows all available grid variables and original grid type.\n"
-   ],
-   "metadata": {
-    "collapsed": false
-   }
+   ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    }
+   },
    "outputs": [],
    "source": [
     "grid = ux.open_grid(grid_filename)\n",
     "grid"
-   ],
-   "metadata": {
-    "collapsed": false
-   }
+   ]
   },
   {
    "cell_type": "markdown",
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    }
+   },
    "source": [
     "We can access our coordinate, connectivity, and other descriptor variables as attributes through this `Grid` instance"
-   ],
-   "metadata": {
-    "collapsed": false
-   }
+   ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    }
+   },
    "outputs": [],
    "source": [
     "grid.node_lon"
-   ],
-   "metadata": {
-    "collapsed": false
-   }
+   ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    }
+   },
    "outputs": [],
    "source": [
     "grid.face_node_connectivity"
-   ],
-   "metadata": {
-    "collapsed": false
-   }
+   ]
   },
   {
    "cell_type": "markdown",
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    }
+   },
    "source": [
     "## `UxDataset` & `UxDataArray` Data Structures\n",
     "\n",
@@ -125,84 +151,102 @@
     "The major difference between them is that UXarray's implementation is paired with a `Grid` object, accessed through the `.uxgrid` property.\n",
     "\n",
     "UXarray also provides a overloaded `ux.open_dataset` method, which takes in both a Grid and Data file path to construct a `UxDataset`\n"
-   ],
-   "metadata": {
-    "collapsed": false
-   }
+   ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    }
+   },
    "outputs": [],
    "source": [
     "uxds = ux.open_dataset(grid_filename, data_filename)\n",
     "uxds"
-   ],
-   "metadata": {
-    "collapsed": false
-   }
+   ]
   },
   {
    "cell_type": "markdown",
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    }
+   },
    "source": [
     "We can see that our `UxDataset` has a single data variable \"bottomDepth\", which is mapped to each face (as specified by the \"n_face\" dimension).\n",
     "\n",
     "We can access this variable by indexing our `UxDataset` to obtain a `UxDataArray`"
-   ],
-   "metadata": {
-    "collapsed": false
-   }
+   ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    }
+   },
    "outputs": [],
    "source": [
     "uxds[\"bottomDepth\"]"
-   ],
-   "metadata": {
-    "collapsed": false
-   }
+   ]
   },
   {
    "cell_type": "markdown",
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    }
+   },
    "source": [
     "You can access the `Grid` instance using the `.uxgrid` attribute, which is linked to every `UxDataset` and `UxDataArray`"
-   ],
-   "metadata": {
-    "collapsed": false
-   }
+   ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    }
+   },
    "outputs": [],
    "source": [
     "uxds.uxgrid"
-   ],
-   "metadata": {
-    "collapsed": false
-   }
+   ]
   },
   {
    "cell_type": "markdown",
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    }
+   },
    "source": [
     "Each `UxDataArray` under a `UxDataset` is linked to the same `Grid` object"
-   ],
-   "metadata": {
-    "collapsed": false
-   }
+   ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    }
+   },
    "outputs": [],
    "source": [
     "uxds.uxgrid == uxds[\"bottomDepth\"].uxgrid"
-   ],
-   "metadata": {
-    "collapsed": false
-   }
+   ]
   }
  ],
  "metadata": {
@@ -221,7 +265,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.11"
+   "version": "3.11.6"
   },
   "nbdime-conflicts": {
    "local_diff": [