diff --git a/examples/nblibrary/rof/month_annual_flow.ipynb b/examples/nblibrary/rof/month_annual_flow.ipynb
index 1c910ba..fea0c60 100644
--- a/examples/nblibrary/rof/month_annual_flow.ipynb
+++ b/examples/nblibrary/rof/month_annual_flow.ipynb
@@ -59,6 +59,7 @@
     "%matplotlib inline\n",
     "\n",
     "import os, sys\n",
+    "import glob\n",
     "import matplotlib.pyplot as plt\n",
     "import matplotlib as mpl\n",
     "from matplotlib.ticker import FormatStrFormatter\n",
@@ -160,7 +161,11 @@
     "grid_list = [grid for grid in [grid_name, base_grid_name] if grid is not None]\n",
     "time_period = slice(f\"{rof_start_date}\", f\"{rof_end_date}\")  # analysis time period\n",
     "nyrs = int(rof_end_date[:4]) - int(rof_start_date[:4]) + 1  # number of years\n",
-    "nmons = nyrs * 12  # number of months"
+    "nmons = nyrs * 12  # number of months\n",
+    "year_list = [\n",
+    "    \"{:04d}\".format(yr)\n",
+    "    for yr in np.arange(int(rof_start_date[0:4]), int(rof_end_date[0:4]) + 1)\n",
+    "]"
    ]
   },
   {
@@ -231,9 +236,15 @@
     "        return ds[var_list]\n",
     "\n",
     "    # monthly\n",
+    "    nc_list = []\n",
+    "    for nc_path in sorted(glob.glob(f\"{in_dire}/{case}.{model}.h*.????-*.nc\")):\n",
+    "        for yr in year_list:\n",
+    "            if yr in os.path.basename(nc_path):\n",
+    "                nc_list.append(nc_path)\n",
+    "\n",
     "    month_data[case] = (\n",
     "        xr.open_mfdataset(\n",
-    "            f\"{in_dire}/{case}.{model}.h*.????-*.nc\",\n",
+    "            nc_list,\n",
     "            data_vars=\"minimal\",\n",
     "            parallel=True,\n",
     "            preprocess=preprocess,\n",
diff --git a/examples/nblibrary/rof/ocean_discharge.ipynb b/examples/nblibrary/rof/ocean_discharge.ipynb
index 299d0c6..4c7a8d6 100644
--- a/examples/nblibrary/rof/ocean_discharge.ipynb
+++ b/examples/nblibrary/rof/ocean_discharge.ipynb
@@ -48,6 +48,7 @@
     "%matplotlib inline\n",
     "\n",
     "import os, sys\n",
+    "import glob\n",
     "import matplotlib.pyplot as plt\n",
     "import numpy as np\n",
     "import pandas as pd\n",
@@ -163,7 +164,11 @@
     "grid_list = [grid for grid in [grid_name, base_grid_name] if grid is not None]\n",
     "time_period = slice(f\"{rof_start_date}\", f\"{rof_end_date}\")  # analysis time period\n",
     "nyrs = int(rof_end_date[:4]) - int(rof_start_date[:4]) + 1  # number of years\n",
-    "nmons = nyrs * 12  # number of months"
+    "nmons = nyrs * 12  # number of months\n",
+    "year_list = [\n",
+    "    \"{:04d}\".format(yr)\n",
+    "    for yr in np.arange(int(rof_start_date[0:4]), int(rof_end_date[0:4]) + 1)\n",
+    "]"
    ]
   },
   {
@@ -234,9 +239,14 @@
     "        return ds[var_list]\n",
     "\n",
     "    # monthly\n",
+    "    nc_list = []\n",
+    "    for nc_path in sorted(glob.glob(f\"{in_dire}/{case}.{model}.h*.????-*.nc\")):\n",
+    "        for yr in year_list:\n",
+    "            if yr in os.path.basename(nc_path):\n",
+    "                nc_list.append(nc_path)\n",
     "    month_data[case] = (\n",
     "        xr.open_mfdataset(\n",
-    "            f\"{in_dire}/{case}.{model}.h*.????-*.nc\",\n",
+    "            nc_list,\n",
     "            data_vars=\"minimal\",\n",
     "            parallel=True,\n",
     "            preprocess=preprocess,\n",