diff --git a/notebook/RomanDESCForwardModelLightcurves.ipynb b/notebook/RomanDESCForwardModelLightcurves.ipynb
index adadab5..80191bf 100644
--- a/notebook/RomanDESCForwardModelLightcurves.ipynb
+++ b/notebook/RomanDESCForwardModelLightcurves.ipynb
@@ -34,13 +34,20 @@
     "This Notebook was developed and tested within a conda environment.  You can create this environment with:\n",
     "\n",
     "```\n",
-    "conda create --name astrophot -c conda-forge python astropy cudatoolkit h5py ipykernel jupyter matplotlib numpy pandas pyyaml pyarrow scipy requests tqdm webbpsf\n",
+    "conda create --name astrophot -c conda-forge python astropy cudatoolkit h5py ipykernel jupyter matplotlib numpy pandas pyyaml pyarrow scipy requests tqdm \n",
     "conda activate astrophot\n",
-    "pip install astrophot pyro-ppl torch\n",
+    "pip install astrophot pyro-ppl torch webbpsf\n",
     "ipython kernel install --user --name=astrophot\n",
     "```\n",
     "\n",
     "And then download the `webbpsf` extra data files.\n",
+    "https://webbpsf.readthedocs.io/en/latest/installation.html#installing-the-required-data-files\n",
+    "\n",
+    "and set the `WEBBPSF_PATH` in the conda environment, e.g.,\n",
+    "\n",
+    "```\n",
+    "conda env config vars set WEBBPSF_PATH=/pscratch/sd/w/wmwv/RomanDESC/webbpsf-data\n",
+    "```\n",
     "\n",
     "This requires astrophot >= v0.15.2"
    ]
@@ -57,7 +64,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "DATASET = \"RomanDESC\"\n",
@@ -67,7 +76,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "import os\n",
@@ -87,6 +98,18 @@
     "import webbpsf\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Make sure we have WEBBPSF_PATH set to load the Roman WFI PSF model\n",
+    "print(os.environ[\"WEBBPSF_PATH\"])"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -97,7 +120,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "image_file_format = (\n",
@@ -122,7 +147,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "# 5 transient IDs of interest\n",
@@ -231,7 +258,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "# Persist the above in CSV files.\n",
@@ -248,7 +277,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "def get_visit_band_sca_for_object_id(object_id):\n",
@@ -326,7 +357,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "# transient_id = 30328322\n",
@@ -342,7 +375,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "transient_info = transient_info_table.loc[transient_id]\n",
@@ -368,7 +403,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "image_files = [os.path.join(DATADIR, bn) for bn in image_file_basenames]\n",
@@ -378,7 +415,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "def get_truth_table(truth_files, visits, transient_id):\n",
@@ -414,7 +453,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "scrolled": false
+    "tags": []
    },
    "outputs": [],
    "source": [
@@ -424,7 +463,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "print(lightcurve_truth)"
@@ -445,7 +486,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "def get_roman_psf(band, sca, x, y):\n",
@@ -490,7 +533,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "# These are 4k x 4k images\n",
@@ -518,7 +563,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "### Bad pixel mask values\n",
@@ -549,7 +596,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "zp_AB_to_nJy = 8.90 + 2.5 * 9"
@@ -567,7 +616,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "DEFAULT_ZP = 22.5  # Appropriate if the image was calibrated and scaled to nanomaggies\n",
@@ -664,7 +715,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "scrolled": false
+    "tags": []
    },
    "outputs": [],
    "source": [
@@ -674,7 +725,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "for i, target in enumerate(targets):\n",
@@ -691,7 +744,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "npix = 75\n",
@@ -724,9 +779,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "n = len(targets.image_list)\n",
@@ -1051,9 +1104,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "model_host_sn.initialize()"
@@ -1108,9 +1159,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "model_filename = f\"Transient_{transient_id}_AstroPhot_model.yaml\"\n",
@@ -1228,9 +1277,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "lightcurve_obs[\"mag\"] = lightcurve_obs[\"inst_mag\"] + lightcurve_obs[\"zp\"] \n",
@@ -1281,9 +1328,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "lightcurve_truth"
@@ -1292,9 +1337,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "from astropy.table import join\n",
@@ -1332,9 +1375,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "lightcurve"
@@ -1451,9 +1492,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "plot_target_model(\n",
@@ -1474,9 +1513,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "astrophot",
    "language": "python",
-   "name": "python3"
+   "name": "astrophot"
   },
   "language_info": {
    "codemirror_mode": {
@@ -1488,7 +1527,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.6"
+   "version": "3.11.9"
   }
  },
  "nbformat": 4,