diff --git a/regional_mom6/regridding.py b/regional_mom6/regridding.py
index b4026e3f..e794d041 100644
--- a/regional_mom6/regridding.py
+++ b/regional_mom6/regridding.py
@@ -379,3 +379,82 @@ def generate_encoding(
             }
 
     return encoding_dict
+
+
+
+def modulo_around_point(x, xc, Lx):
+    """
+    This function calculates the modulo around a point. Return the modulo value of x in an interval [xc-(Lx/2) xc+(Lx/2)]. If Lx<=0, then it returns x without applying modulo arithmetic.
+    Parameters
+    ----------
+    x: float
+        Value to which to apply modulo arithmetic
+    xc: float
+        Center of modulo range
+    Lx: float
+        Modulo range width
+    Returns
+    -------
+    float
+        x shifted by an integer multiple of Lx to be close to xc, 
+    """
+    if Lx <= 0:
+        return x
+    else:
+        return ((x - (xc - 0.5*Lx)) % Lx )- Lx/2 + xc
+    
+
+def initialize_grid_rotation_angle(hgrid: xr.Dataset) -> xr.Dataset:
+    """
+    Calculate the angle_dx in degrees from the true x (east?) direction counterclockwise) and save as angle_dx_mom6
+    Parameters
+    ----------
+    hgrid: xr.Dataset
+        The hgrid dataset
+    Returns
+    -------
+    xr.Dataset
+        The dataset with the mom6_angle_dx variable added
+    """
+    regridding_logger.info("Initializing grid rotation angle")
+    # Direct Translation
+    pi_720deg = np.arctan(1)/180 # One quarter the conversion factor from degrees to radians
+    
+    ## Check length of longitude
+    len_lon = 360.0
+    G_len_lon = hgrid.x.max() - hgrid.x.min()
+    if G_len_lon != 360:
+        regridding_logger.info("This is a regional case")
+        len_lon = G_len_lon
+
+    angles_arr = np.zeros((len(hgrid.nyp), len(hgrid.nxp)))
+
+    # Compute lonB for all points
+    lonB = np.zeros((2, 2, len(hgrid.nyp)-2, len(hgrid.nxp)-2))
+
+    # Vectorized Compute lonB - Fortran is 1-indexed, so we need to subtract 1 from the indices in lonB[m-1,n-1]
+    for n in np.arange(1,3):
+        for m in np.arange(1,3):
+            lonB[m-1, n-1] = modulo_around_point(hgrid.x[np.arange((m-2+1),(m-2+len(hgrid.nyp)-1)), np.arange((n-2+1),(n-2+len(hgrid.nxp)-1))], hgrid.x[1:-1,1:-1], len_lon)
+
+    # Vectorized Compute lon_scale
+    lon_scale = np.cos(pi_720deg* ((hgrid.y[0:-2, 0:-2] + hgrid.y[1:-1, 1:-1]) + (hgrid.y[1:-1, 0:-2] + hgrid.y[0:-2, 1:-1])))
+
+    # Vectorized Compute angle
+    angle = np.arctan2(
+        lon_scale * ((lonB[0, 1] - lonB[1, 0]) + (lonB[1, 1] - lonB[0, 0])),
+        (hgrid.y[0:-2, 1:-1] - hgrid.y[1:-1, 0:-2]) + (hgrid.y[1:-1, 1:-1] - hgrid.y[0:-2, 0:-2])
+    )
+
+    # Assign angle to angles_arr
+    angles_arr[1:-1,1:-1] = 90 - np.rad2deg(angle)
+
+
+    # Assign angles_arr to hgrid
+    hgrid["angle_dx_mom6"] = (("nyp", "nxp"), angles_arr)
+    hgrid["angle_dx_mom6"].attrs["_FillValue"] = np.nan
+    hgrid["angle_dx_mom6"].attrs["units"] = "deg"
+    hgrid["angle_dx_mom6"].attrs["description"] = "MOM6 calculates angles internally, this field replicates that for rotating boundary conditions. Use this over other angle fields for MOM6 applications"
+
+    return hgrid
+    
diff --git a/regional_mom6/testing_to_be_deleted/angle_calc.md b/regional_mom6/testing_to_be_deleted/angle_calc.md
new file mode 100644
index 00000000..4f40e8e9
--- /dev/null
+++ b/regional_mom6/testing_to_be_deleted/angle_calc.md
@@ -0,0 +1,11 @@
+# MOM6 Angle Calculation Steps
+
+1. Calculate pi/4rads / 180 degress  = Gives a 1/4 conversion of degrees to radians. I.E. multiplying an angle in degrees by this gives the conversion to radians at 1/4 the value. 
+2. Figure out the longitudunal extent of our domain, or periodic range of longitudes. For global cases it is len_lon = 360, for our regional cases it is given by the hgrid.
+3. At each point on our hgrid, we find the point to the left, bottom left diag, bottom, and itself. We adjust each of these longitudes to be in the range of len_lon around the point itself. (module_around_point)
+4. We then find the lon_scale, which is the "trigonometric scaling factor converting changes in longitude to equivalent distances in latitudes". Whatever that actually means is we add the latitude of all four of these points from part 3 and basically average it and convert to radians. We then take the cosine of it. 
+5. Then we calculate the angle. This is a simple arctan2 so y/x. 
+    1. The "y" component is the addition of the difference between the diagonals in longitude of lonB multiplied by the lon_scale, which is our conversion to latitude.
+    2. The "x" component is the same addition of differences in latitude.
+    3. Thus, given the same units, we can call arctan to get the angle in degrees
+6. Challenge: Because this takes the left & bottom points, we can't calculate the angle at the left and bottom edges. Therefore, we can always calculate it the other way by using the right and top points. 
diff --git a/regional_mom6/testing_to_be_deleted/angle_calc_mom6.ipynb b/regional_mom6/testing_to_be_deleted/angle_calc_mom6.ipynb
new file mode 100755
index 00000000..921aedf6
--- /dev/null
+++ b/regional_mom6/testing_to_be_deleted/angle_calc_mom6.ipynb
@@ -0,0 +1,755 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import xarray as xr\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<xarray.Dataset> Size: 111MB\n",
+      "Dimensions:   (nyp: 1561, nxp: 1481, ny: 1560, nx: 1480)\n",
+      "Dimensions without coordinates: nyp, nxp, ny, nx\n",
+      "Data variables:\n",
+      "    tile      |S255 255B ...\n",
+      "    y         (nyp, nxp) float64 18MB ...\n",
+      "    x         (nyp, nxp) float64 18MB ...\n",
+      "    dy        (ny, nxp) float64 18MB ...\n",
+      "    dx        (nyp, nx) float64 18MB ...\n",
+      "    area      (ny, nx) float64 18MB ...\n",
+      "    angle_dx  (nyp, nxp) float64 18MB ...\n",
+      "Attributes:\n",
+      "    file_name:    ocean_hgrid.nc\n",
+      "    Description:  MOM6 NCAR NWA12\n",
+      "    Author:       Fred Castruccio (fredc@ucar.edu)\n",
+      "    Created:      2024-04-18T08:39:49.607481\n",
+      "    type:         MOM6 supergrid file\n"
+     ]
+    }
+   ],
+   "source": [
+    "\n",
+    "hgrid = xr.open_dataset(\"/glade/u/home/manishrv/documents/nwa12_0.1/mom_input/n3b.clean/hgrid.nc\")\n",
+    "print(hgrid)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x7f3d803534d0>"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "hgrid[\"angle_dx\"].plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "    pi_720deg = atan(1.0) / 180.0\n",
+    "    len_lon = 360.0 ; if (G%len_lon > 0.0) len_lon = G%len_lon\n",
+    "    do j=G%jsc,G%jec ; do i=G%isc,G%iec\n",
+    "      do n=1,2 ; do m=1,2\n",
+    "        lonB(m,n) = modulo_around_point(G%geoLonBu(I+m-2,J+n-2), G%geoLonT(i,j), len_lon)\n",
+    "      enddo ; enddo\n",
+    "      lon_scale = cos(pi_720deg*((G%geoLatBu(I-1,J-1) + G%geoLatBu(I,J)) + &\n",
+    "                                 (G%geoLatBu(I,J-1) + G%geoLatBu(I-1,J)) ) )\n",
+    "      angle = atan2(lon_scale*((lonB(1,2) - lonB(2,1)) + (lonB(2,2) - lonB(1,1))), &\n",
+    "                    (G%geoLatBu(I-1,J) - G%geoLatBu(I,J-1)) + &\n",
+    "                    (G%geoLatBu(I,J) - G%geoLatBu(I-1,J-1)) )\n",
+    "      G%sin_rot(i,j) = sin(angle) ! angle is the clockwise angle from lat/lon to ocean\n",
+    "      G%cos_rot(i,j) = cos(angle) ! grid (e.g. angle of ocean \"north\" from true north)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "function modulo_around_point(x, xc, Lx) result(x_mod)\n",
+    "  real, intent(in) :: x  !< Value to which to apply modulo arithmetic [A]\n",
+    "  real, intent(in) :: xc !< Center of modulo range [A]\n",
+    "  real, intent(in) :: Lx !< Modulo range width [A]\n",
+    "  real :: x_mod          !< x shifted by an integer multiple of Lx to be close to xc [A].\n",
+    "\n",
+    "  if (Lx > 0.0) then\n",
+    "    x_mod = modulo(x - (xc - 0.5*Lx), Lx) + (xc - 0.5*Lx)\n",
+    "  else\n",
+    "    x_mod = x\n",
+    "  endif\n",
+    "end function modulo_around_point"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "This is a regional case\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Direct Translation\n",
+    "pi_720deg = np.arctan(1)/180 # One quarter the conversion factor from degrees to radians\n",
+    " \n",
+    "## Check length of longitude\n",
+    "len_lon = 360.0\n",
+    "G_len_lon = hgrid.x.max() - hgrid.x.min()\n",
+    "if G_len_lon != 360:\n",
+    "    print(\"This is a regional case\")\n",
+    "    len_lon = G_len_lon\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "## Iterate it, j=G%jsc,G%jec ; do i=G%isc,G%iec mean we iterate from jsc to jec and isc to iec\n",
+    "## Then you iterate around it, 1,2 and 1,2\n",
+    "\n",
+    "# In this way we wrap each longitude in the correct way even if we are at the seam like 360, I still don't understand it as much\n",
+    "\n",
+    "\n",
+    "def modulo_around_point(x, xc, Lx):\n",
+    "    \"\"\"\n",
+    "    This function calculates the modulo around a point, for use in cases where we are wrapping around the globe at the seam. Return the modulo value of x in an interval [xc-(Lx/2) xc+(Lx/2)]. If Lx<=0, then it returns x without applying modulo arithmetic.\n",
+    "    Parameters\n",
+    "    ----------\n",
+    "    x: float\n",
+    "        Value to which to apply modulo arithmetic\n",
+    "    xc: float\n",
+    "        Center of modulo range\n",
+    "    Lx: float\n",
+    "        Modulo range width\n",
+    "    Returns\n",
+    "    -------\n",
+    "    float\n",
+    "        x shifted by an integer multiple of Lx to be close to xc, \n",
+    "    \"\"\"\n",
+    "    if Lx <= 0:\n",
+    "        return x\n",
+    "    else:\n",
+    "        return ((x - (xc - 0.5*Lx)) % Lx )- Lx/2 + xc\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[[0.         0.         0.         ... 0.         0.         0.        ]\n",
+      " [0.         0.         0.         ... 0.         0.         0.        ]\n",
+      " [0.         0.         0.         ... 0.         0.         0.        ]\n",
+      " ...\n",
+      " [0.         4.45305106 4.47236786 ... 4.39342157 4.3767402  4.36004645]\n",
+      " [0.         4.46353797 4.48289919 ... 4.40354537 4.38683191 4.37010606]\n",
+      " [0.         4.4740426  4.49344831 ... 4.41368567 4.3969401  4.3801821 ]]\n"
+     ]
+    }
+   ],
+   "source": [
+    "\n",
+    "angles_arr_v2 = np.zeros((len(hgrid.nyp), len(hgrid.nxp)))\n",
+    "\n",
+    "# Compute lonB for all points\n",
+    "lonB = np.zeros((2, 2, len(hgrid.nyp)-1, len(hgrid.nxp)-1))\n",
+    "\n",
+    "# Vectorized computation of lonB\n",
+    "for n in np.arange(1,3):\n",
+    "    for m in np.arange(1,3):\n",
+    "        lonB[m-1, n-1] = modulo_around_point(hgrid.x[np.arange((m-2+1),(m-2+len(hgrid.nyp))), np.arange((n-2+1),(n-2+len(hgrid.nxp)))], hgrid.x[1:,1:], len_lon)\n",
+    "\n",
+    "# Compute lon_scale\n",
+    "lon_scale = np.cos(pi_720deg* ((hgrid.y[0:-1, 0:-1] + hgrid.y[1:, 1:]) + (hgrid.y[1:, 0:-1] + hgrid.y[0:-1, 1:])))\n",
+    "\n",
+    "# Compute angle\n",
+    "angle = np.arctan2(\n",
+    "    lon_scale * ((lonB[0, 1] - lonB[1, 0]) + (lonB[1, 1] - lonB[0, 0])),\n",
+    "    (hgrid.y[0:-1, 1:] - hgrid.y[1:, 0:-1]) + (hgrid.y[1:, 1:] - hgrid.y[0:-1, 0:-1])\n",
+    ")\n",
+    "# Assign angle to angles_arr\n",
+    "angles_arr_v2[1:,1:] = 90 - np.rad2deg(angle)\n",
+    "# Print the result\n",
+    "print(angles_arr_v2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "hgrid[\"angle_dx_mom6\"] = ((\"nyp\", \"nxp\"), angles_arr_v2)\n",
+    "hgrid[\"angle_dx_mom6\"].attrs[\"_FillValue\"] = np.nan\n",
+    "hgrid[\"angle_dx_mom6\"].attrs[\"units\"] = \"rad\"\n",
+    "hgrid[\"angle_dx_mom6\"].attrs[\"description\"] = \"MOM6 calculates angles internally, this field replicates that for rotating boundary conditions. Use this over other angle fields for MOM6 applications\"\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x7f3db0148bf0>"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "hgrid[\"angle_dx_mom6\"].plot(vmin = 0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x600 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "angle_diff = hgrid[\"angle_dx\"][1:,1:] - hgrid[\"angle_dx_mom6\"][1:,1:]\n",
+    "plt.figure(figsize=(8, 6))\n",
+    "angle_diff.plot(cmap='coolwarm')\n",
+    "plt.title(\"Difference between caluculated MOM6 angle and angle_dx from Hgrid angle_dx\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
+       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
+       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
+       " *\n",
+       " */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
+       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
+       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
+       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
+       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
+       "  --xr-background-color: var(--jp-layout-color0, white);\n",
+       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
+       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
+       "}\n",
+       "\n",
+       "html[theme=dark],\n",
+       "html[data-theme=dark],\n",
+       "body[data-theme=dark],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
+       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
+       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
+       "  --xr-border-color: #1F1F1F;\n",
+       "  --xr-disabled-color: #515151;\n",
+       "  --xr-background-color: #111111;\n",
+       "  --xr-background-color-row-even: #111111;\n",
+       "  --xr-background-color-row-odd: #313131;\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: '►';\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: '▼';\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: '(';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: ')';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: ',';\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 129MB\n",
+       "Dimensions:        (nyp: 1561, nxp: 1481, ny: 1560, nx: 1480)\n",
+       "Dimensions without coordinates: nyp, nxp, ny, nx\n",
+       "Data variables:\n",
+       "    tile           |S255 255B ...\n",
+       "    y              (nyp, nxp) float64 18MB ...\n",
+       "    x              (nyp, nxp) float64 18MB -98.0 -97.96 -97.92 ... -37.49 -37.45\n",
+       "    dy             (ny, nxp) float64 18MB ...\n",
+       "    dx             (nyp, nx) float64 18MB ...\n",
+       "    area           (ny, nx) float64 18MB ...\n",
+       "    angle_dx       (nyp, nxp) float64 18MB ...\n",
+       "    angle_dx_mom6  (nyp, nxp) float64 18MB 0.0 0.0 0.0 0.0 ... 4.414 4.397 4.38\n",
+       "Attributes:\n",
+       "    file_name:    ocean_hgrid.nc\n",
+       "    Description:  MOM6 NCAR NWA12\n",
+       "    Author:       Fred Castruccio (fredc@ucar.edu)\n",
+       "    Created:      2024-04-18T08:39:49.607481\n",
+       "    type:         MOM6 supergrid file</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-94bc956a-6a3a-43d8-8eb0-76f896cbc372' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-94bc956a-6a3a-43d8-8eb0-76f896cbc372' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span>nyp</span>: 1561</li><li><span>nxp</span>: 1481</li><li><span>ny</span>: 1560</li><li><span>nx</span>: 1480</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-1a1db89e-8ae4-45cb-b209-083aefdffb1a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-1a1db89e-8ae4-45cb-b209-083aefdffb1a' class='xr-section-summary'  title='Expand/collapse section'>Coordinates: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-5900999f-cfec-4f6a-9775-77ab7c66e4e9' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5900999f-cfec-4f6a-9775-77ab7c66e4e9' class='xr-section-summary' >Data variables: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>tile</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>|S255</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8f9246f0-a701-493c-8d41-b0262b4cd36a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8f9246f0-a701-493c-8d41-b0262b4cd36a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-411e4b53-4a4e-4fad-8a43-5e5238abfdd7' class='xr-var-data-in' type='checkbox'><label for='data-411e4b53-4a4e-4fad-8a43-5e5238abfdd7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>[1 values with dtype=|S255]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>y</span></div><div class='xr-var-dims'>(nyp, nxp)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1bbe4e85-861b-435d-b7aa-ed06da67b1cf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1bbe4e85-861b-435d-b7aa-ed06da67b1cf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9cbabada-af21-4304-bb9f-d2e76759cd3a' class='xr-var-data-in' type='checkbox'><label for='data-9cbabada-af21-4304-bb9f-d2e76759cd3a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees</dd></dl></div><div class='xr-var-data'><pre>[2311841 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x</span></div><div class='xr-var-dims'>(nyp, nxp)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-98.0 -97.96 ... -37.49 -37.45</div><input id='attrs-0cac3ec7-6943-443d-8317-1c43413149a9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0cac3ec7-6943-443d-8317-1c43413149a9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ea2efa6b-00b6-4cd3-be8b-b11401dbe0e3' class='xr-var-data-in' type='checkbox'><label for='data-ea2efa6b-00b6-4cd3-be8b-b11401dbe0e3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees</dd></dl></div><div class='xr-var-data'><pre>array([[-98.      , -97.958333, -97.916667, ..., -36.416667, -36.375   ,\n",
+       "        -36.333333],\n",
+       "       [-98.      , -97.958333, -97.916667, ..., -36.416667, -36.375   ,\n",
+       "        -36.333333],\n",
+       "       [-98.      , -97.958333, -97.916667, ..., -36.416667, -36.375   ,\n",
+       "        -36.333333],\n",
+       "       ...,\n",
+       "       [-98.745792, -98.70752 , -98.669246, ..., -37.533511, -37.487349,\n",
+       "        -37.441182],\n",
+       "       [-98.747878, -98.709615, -98.671351, ..., -37.537222, -37.491047,\n",
+       "        -37.444866],\n",
+       "       [-98.749968, -98.711715, -98.67346 , ..., -37.540943, -37.494754,\n",
+       "        -37.44856 ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dy</span></div><div class='xr-var-dims'>(ny, nxp)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5f8eebe7-00cc-45cb-999d-b61cf8ee56b4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5f8eebe7-00cc-45cb-999d-b61cf8ee56b4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9ba5c6a1-9e9e-4e21-9197-5ef32ebe97f9' class='xr-var-data-in' type='checkbox'><label for='data-9ba5c6a1-9e9e-4e21-9197-5ef32ebe97f9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>meters</dd></dl></div><div class='xr-var-data'><pre>[2310360 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dx</span></div><div class='xr-var-dims'>(nyp, nx)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-771015c2-dfae-4c2b-a63b-e0a93d41c6ad' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-771015c2-dfae-4c2b-a63b-e0a93d41c6ad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1ff0f0e2-fc1c-4e47-a422-20a5395ae300' class='xr-var-data-in' type='checkbox'><label for='data-1ff0f0e2-fc1c-4e47-a422-20a5395ae300' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>meters</dd></dl></div><div class='xr-var-data'><pre>[2310280 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>area</span></div><div class='xr-var-dims'>(ny, nx)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4c52e765-d7c1-4bfc-a5eb-1b1961ddd1d3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4c52e765-d7c1-4bfc-a5eb-1b1961ddd1d3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1d6f5db4-cc9a-414c-999b-498622d24233' class='xr-var-data-in' type='checkbox'><label for='data-1d6f5db4-cc9a-414c-999b-498622d24233' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m2</dd></dl></div><div class='xr-var-data'><pre>[2308800 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_dx</span></div><div class='xr-var-dims'>(nyp, nxp)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-bf220ed3-f49e-48d0-990d-4a08df4d6caf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bf220ed3-f49e-48d0-990d-4a08df4d6caf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c1a676cc-73a9-4ce4-bc3a-dd6919f5d369' class='xr-var-data-in' type='checkbox'><label for='data-c1a676cc-73a9-4ce4-bc3a-dd6919f5d369' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>meters</dd></dl></div><div class='xr-var-data'><pre>[2311841 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_dx_mom6</span></div><div class='xr-var-dims'>(nyp, nxp)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 ... 4.414 4.397 4.38</div><input id='attrs-437a35be-a454-4446-887f-ff2c18b83a88' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-437a35be-a454-4446-887f-ff2c18b83a88' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-db6f1b1b-383e-45da-985c-740f393961e1' class='xr-var-data-in' type='checkbox'><label for='data-db6f1b1b-383e-45da-985c-740f393961e1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_FillValue :</span></dt><dd>nan</dd><dt><span>units :</span></dt><dd>rad</dd><dt><span>description :</span></dt><dd>MOM6 calculates angles internally, this field replicates that for rotating boundary conditions. Use this over other angle fields for MOM6 applications</dd></dl></div><div class='xr-var-data'><pre>array([[0.        , 0.        , 0.        , ..., 0.        , 0.        ,\n",
+       "        0.        ],\n",
+       "       [0.        , 0.        , 0.        , ..., 0.        , 0.        ,\n",
+       "        0.        ],\n",
+       "       [0.        , 0.        , 0.        , ..., 0.        , 0.        ,\n",
+       "        0.        ],\n",
+       "       ...,\n",
+       "       [0.        , 4.45305106, 4.47236786, ..., 4.39342157, 4.3767402 ,\n",
+       "        4.36004645],\n",
+       "       [0.        , 4.46353797, 4.48289919, ..., 4.40354537, 4.38683191,\n",
+       "        4.37010606],\n",
+       "       [0.        , 4.4740426 , 4.49344831, ..., 4.41368567, 4.3969401 ,\n",
+       "        4.3801821 ]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-43859d70-65b8-4eea-954c-ad3f2ee9c90a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-43859d70-65b8-4eea-954c-ad3f2ee9c90a' class='xr-section-summary'  title='Expand/collapse section'>Indexes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-ec86e2e6-2e69-466a-8c73-c024943f339c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ec86e2e6-2e69-466a-8c73-c024943f339c' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>file_name :</span></dt><dd>ocean_hgrid.nc</dd><dt><span>Description :</span></dt><dd>MOM6 NCAR NWA12</dd><dt><span>Author :</span></dt><dd>Fred Castruccio (fredc@ucar.edu)</dd><dt><span>Created :</span></dt><dd>2024-04-18T08:39:49.607481</dd><dt><span>type :</span></dt><dd>MOM6 supergrid file</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 129MB\n",
+       "Dimensions:        (nyp: 1561, nxp: 1481, ny: 1560, nx: 1480)\n",
+       "Dimensions without coordinates: nyp, nxp, ny, nx\n",
+       "Data variables:\n",
+       "    tile           |S255 255B ...\n",
+       "    y              (nyp, nxp) float64 18MB ...\n",
+       "    x              (nyp, nxp) float64 18MB -98.0 -97.96 -97.92 ... -37.49 -37.45\n",
+       "    dy             (ny, nxp) float64 18MB ...\n",
+       "    dx             (nyp, nx) float64 18MB ...\n",
+       "    area           (ny, nx) float64 18MB ...\n",
+       "    angle_dx       (nyp, nxp) float64 18MB ...\n",
+       "    angle_dx_mom6  (nyp, nxp) float64 18MB 0.0 0.0 0.0 0.0 ... 4.414 4.397 4.38\n",
+       "Attributes:\n",
+       "    file_name:    ocean_hgrid.nc\n",
+       "    Description:  MOM6 NCAR NWA12\n",
+       "    Author:       Fred Castruccio (fredc@ucar.edu)\n",
+       "    Created:      2024-04-18T08:39:49.607481\n",
+       "    type:         MOM6 supergrid file"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "hgrid"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "crr_dev",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}