diff --git a/docs/examples/regridding-vertical.ipynb b/docs/examples/regridding-vertical.ipynb
index 40d89767..c6e95976 100644
--- a/docs/examples/regridding-vertical.ipynb
+++ b/docs/examples/regridding-vertical.ipynb
@@ -11,15 +11,15 @@
     "\n",
     "Authors: [Jason Boutte](https://github.com/jasonb5) and [Jill Zhang](https://github.com/chengzhuzhang)\n",
     "\n",
-    "Updated: 04/15/24 [xcdat v0.7.0]\n",
+    "Updated: 11/07/24 [xcdat v0.7.3]\n",
     "\n",
     "Related APIs:\n",
     "\n",
     "- [xarray.Dataset.regridder.vertical](../generated/xarray.Dataset.regridder.vertical.rst)\n",
     "\n",
-    "The data used in this example can be found through the [Earth System Grid Federation (ESGF) search portal](https://aims2.llnl.gov/search). We are using xarray's OPeNDAP support to read a netCDF4 dataset file directly from its source. The data is not loaded over the network until we perform operations on it (e.g., temperature unit adjustment). More information on the xarray's OPeNDAP support can be found [here](https://docs.xarray.dev/en/stable/user-guide/io.html#opendap).\n",
+    "We'll cover vertical regridding using `xgcm`. Two examples are outlined here to apply vertical regridding/remapping using ocean variables and atmosphere variables, respectively.\n",
     "\n",
-    "We'll cover vertical regridding using `xgcm`. Two examples are outlined here to apply vertical regridding/remapping using ocean variables and atmosphere variables, respectively.\n"
+    "In the example below, we will be working with the `\"ersstv5\"` dataset (NOAA’s Extended Reconstructed Sea Surface Temperature monthly averages). The data used in this example can be found in the [xarray-data repository](https://github.com/pydata/xarray-data).\n"
    ]
   },
   {
@@ -34,16 +34,16 @@
     "First, create the conda environment:\n",
     "\n",
     "```bash\n",
-    "conda create -n xcdat_notebook_0.7.0 -c conda-forge xcdat=0.7.0 xesmf matplotlib ipython ipykernel cartopy nc-time-axis gsw-xarray jupyter\n",
+    "conda create -n xcdat_notebook -c conda-forge xcdat xesmf matplotlib ipython ipykernel cartopy nc-time-axis gsw-xarray jupyter pooch\n",
     "```\n",
     "\n",
-    "Then install the kernel from the `xcdat_notebook_0.7.0` environment using `ipykernel` and name the kernel with the display name (e.g., `xcdat_notebook_0.7.0`):\n",
+    "Then install the kernel from the `xcdat_notebook` environment using `ipykernel` and name the kernel with the display name (e.g., `xcdat_notebook`):\n",
     "\n",
     "```bash\n",
-    "python -m ipykernel install --user --name xcdat_notebook_0.7.0 --display-name xcdat_notebook_0.7.0\n",
+    "python -m ipykernel install --user --name xcdat_notebook --display-name xcdat_notebook\n",
     "```\n",
     "\n",
-    "Then to select the kernel `xcdat_notebook_0.7.0` in Jupyter to use this kernel.\n"
+    "Then to select the kernel `xcdat_notebook` in Jupyter to use this kernel.\n"
    ]
   },
   {
@@ -63,13 +63,11 @@
    "source": [
     "%matplotlib inline\n",
     "\n",
+    "import gsw_xarray as gsw\n",
     "import matplotlib.pyplot as plt\n",
-    "import xarray as xr\n",
-    "import xcdat\n",
     "import numpy as np\n",
-    "# gsw-xarray is a wrapper for GSW-Python:\n",
-    "# the Python implementation of the Gibbs SeaWater (GSW) Oceanographic Toolbox of TEOS-10\n",
-    "import gsw_xarray as gsw\n",
+    "import xarray as xr\n",
+    "import xcdat as xc\n",
     "\n",
     "import warnings\n",
     "\n",
@@ -3149,9 +3147,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "xc070_vertical",
+   "display_name": "xcdat_notebook_0.7.3",
    "language": "python",
-   "name": "xcdat_notebook_vertical"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -3163,7 +3161,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.3"
+   "version": "3.12.7"
   }
  },
  "nbformat": 4,