diff --git a/how-to-guides/select_points_from_grid.ipynb b/how-to-guides/select_points_from_grid.ipynb
new file mode 100644
index 0000000..1555de3
--- /dev/null
+++ b/how-to-guides/select_points_from_grid.ipynb
@@ -0,0 +1,2695 @@
+{
+ "cells": [
+  {
+   "cell_type": "raw",
+   "id": "5f5d62cc-6b4e-4f96-a969-df6631268638",
+   "metadata": {},
+   "source": [
+    "---\n",
+    "title: \"How-to select points from a grid using `xarray`\n",
+    "author: \"Andrew P. Barrett\"\n",
+    "date: last-modified\n",
+    "---"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "68dc0a1d-420f-4c3a-88e2-ba0b53ca4e9e",
+   "metadata": {},
+   "source": [
+    "## Problem\n",
+    "\n",
+    "You have a list of locations in geographic coordinates and want to get the closest values to those locations from a gridded data product"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "fd2780a9-c6c8-41bd-b8b3-aaca94c64532",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Generate dummy data\n",
+    "import numpy as np\n",
+    "import datetime as dt\n",
+    "# import pandas as pd\n",
+    "\n",
+    "n_points = 50\n",
+    "\n",
+    "# generate Arctic points (lat > 60)\n",
+    "points = []\n",
+    "while len(points) < n_points:\n",
+    "    batch = 500\n",
+    "    lat = np.degrees(np.arcsin(np.random.uniform(-1, 1, batch)))\n",
+    "    lon = np.random.uniform(-180, 180, batch)\n",
+    "\n",
+    "    mask = lat > 75\n",
+    "    for la, lo in zip(lat[mask], lon[mask]):\n",
+    "        points.append((la, lo))\n",
+    "        if len(points) >= n_points:\n",
+    "            break\n",
+    "\n",
+    "lat, lon = np.array(points).T\n",
+    "\n",
+    "# random dates after Oct 2018\n",
+    "\n",
+    "start_date = dt.datetime(2018, 10, 1)\n",
+    "end_date = dt.datetime.now()\n",
+    "ndays = (end_date - start_date).days\n",
+    "incr = np.random.choice(np.arange(0,ndays), 50)\n",
+    "days = [start_date + dt.timedelta(days=int(i)) for i in incr]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d2de2277-b738-4b5e-9519-3505b945b896",
+   "metadata": {},
+   "source": [
+    "## Solution\n",
+    "\n",
+    "We'll use `earthaccess` to select the data granules, and `geopandas` and `xarray` extract the points.\n",
+    "\n",
+    "We use a `geopandas.GeoDataFrame` to store the data points because it has a convenient method to transform coordinate systems.\n",
+    "\n",
+    "We use `xarray` [vectorized indexing](https://tutorial.xarray.dev/intermediate/indexing/advanced-indexing.html) to select the grid values corresponding to each point.\n",
+    "\n",
+    "_Standard \"orthogonal\" indexing returns a 2D grid rather than a 1D list of values._"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b72ee94d-5bf6-421b-93ff-b41281e16389",
+   "metadata": {},
+   "source": [
+    "### Get data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "id": "15f243e4-983b-4f8b-a7ec-9d4bd8f5a543",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "420"
+      ]
+     },
+     "execution_count": 64,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import earthaccess\n",
+    "\n",
+    "auth = earthaccess.login()\n",
+    "\n",
+    "results = earthaccess.search_data(\n",
+    "    short_name='ATL21',\n",
+    "    temporal=(min(days), max(days)),\n",
+    ")\n",
+    "\n",
+    "# Filter results on date\n",
+    "len(results)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 129,
+   "id": "7f28eed9-6301-4f8a-b45b-1fe1f8c7300d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'HorizontalSpatialDomain': {'Geometry': {'BoundingRectangles': [{'WestBoundingCoordinate': -179.999996,\n",
+       "     'EastBoundingCoordinate': 179.999996,\n",
+       "     'NorthBoundingCoordinate': 88.045543,\n",
+       "     'SouthBoundingCoordinate': 66.163953}]}}}"
+      ]
+     },
+     "execution_count": 129,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "results[0]['umm']['SpatialExtent']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 130,
+   "id": "552be9e0-1610-49c4-852f-9bb8be054ad5",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'RangeDateTime': {'BeginningDateTime': '2018-10-14T00:21:48.736Z',\n",
+       "  'EndingDateTime': '2018-10-31T23:05:09.137Z'}}"
+      ]
+     },
+     "execution_count": 130,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "results[0]['umm']['TemporalExtent']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2d303eac-3cdd-4567-94c2-8686d2d07d77",
+   "metadata": {},
+   "source": [
+    "Could use Luis's `virtualizarr` here to lazy-load data cube.  For now just download data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "id": "3fdab0ea-c588-419c-a1f9-6a7781cd6204",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "8f896afbb1c4438ea166cf7060d2b5f9",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "QUEUEING TASKS | :   0%|          | 0/1 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "3f7aa0e00f704ff491b79c06d96e96cc",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "PROCESSING TASKS | :   0%|          | 0/1 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "c95d6210b75948aeb9b4299743eba78d",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "COLLECTING RESULTS | :   0%|          | 0/1 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import xarray as xr\n",
+    "import rioxarray\n",
+    "\n",
+    "# files = earthaccess.open(results)\n",
+    "files = earthaccess.download(results[0], local_path='data')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 110,
+   "id": "de4473cf-91af-4ac9-8cf7-69524a4e1d69",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_464073/2602607402.py:1: UserWarning: Variable(s) referenced in grid_mapping not in variables: ['../../crs']\n",
+      "  ds = xr.open_datatree(\n",
+      "/tmp/ipykernel_464073/2602607402.py:1: UserWarning: Variable(s) referenced in grid_mapping not in variables: ['../../crs']\n",
+      "  ds = xr.open_datatree(\n",
+      "/tmp/ipykernel_464073/2602607402.py:1: UserWarning: Variable(s) referenced in grid_mapping not in variables: ['../../crs']\n",
+      "  ds = xr.open_datatree(\n",
+      "/tmp/ipykernel_464073/2602607402.py:1: UserWarning: Variable(s) referenced in grid_mapping not in variables: ['../../crs']\n",
+      "  ds = xr.open_datatree(\n",
+      "/tmp/ipykernel_464073/2602607402.py:1: UserWarning: Variable(s) referenced in grid_mapping not in variables: ['../../crs']\n",
+      "  ds = xr.open_datatree(\n",
+      "/tmp/ipykernel_464073/2602607402.py:1: UserWarning: Variable(s) referenced in grid_mapping not in variables: ['../../crs']\n",
+      "  ds = xr.open_datatree(\n",
+      "/tmp/ipykernel_464073/2602607402.py:1: UserWarning: Variable(s) referenced in grid_mapping not in variables: ['../../crs']\n",
+      "  ds = xr.open_datatree(\n",
+      "/tmp/ipykernel_464073/2602607402.py:1: UserWarning: Variable(s) referenced in grid_mapping not in variables: ['../../crs']\n",
+      "  ds = xr.open_datatree(\n",
+      "/tmp/ipykernel_464073/2602607402.py:1: UserWarning: Variable(s) referenced in grid_mapping not in variables: ['../../crs']\n",
+      "  ds = xr.open_datatree(\n",
+      "/tmp/ipykernel_464073/2602607402.py:1: UserWarning: Variable(s) referenced in grid_mapping not in variables: ['../../crs']\n",
+      "  ds = xr.open_datatree(\n",
+      "/tmp/ipykernel_464073/2602607402.py:1: UserWarning: Variable(s) referenced in grid_mapping not in variables: ['../../crs']\n",
+      "  ds = xr.open_datatree(\n",
+      "/tmp/ipykernel_464073/2602607402.py:1: UserWarning: Variable(s) referenced in grid_mapping not in variables: ['../../crs']\n",
+      "  ds = xr.open_datatree(\n",
+      "/tmp/ipykernel_464073/2602607402.py:1: UserWarning: Variable(s) referenced in grid_mapping not in variables: ['../../crs']\n",
+      "  ds = xr.open_datatree(\n",
+      "/tmp/ipykernel_464073/2602607402.py:1: UserWarning: Variable(s) referenced in grid_mapping not in variables: ['../../crs']\n",
+      "  ds = xr.open_datatree(\n",
+      "/tmp/ipykernel_464073/2602607402.py:1: UserWarning: Variable(s) referenced in grid_mapping not in variables: ['../../crs']\n",
+      "  ds = xr.open_datatree(\n",
+      "/tmp/ipykernel_464073/2602607402.py:1: UserWarning: Variable(s) referenced in grid_mapping not in variables: ['../../crs']\n",
+      "  ds = xr.open_datatree(\n",
+      "/tmp/ipykernel_464073/2602607402.py:1: UserWarning: Variable(s) referenced in grid_mapping not in variables: ['../../crs']\n",
+      "  ds = xr.open_datatree(\n",
+      "/tmp/ipykernel_464073/2602607402.py:1: UserWarning: Variable(s) referenced in grid_mapping not in variables: ['../../crs']\n",
+      "  ds = xr.open_datatree(\n",
+      "/tmp/ipykernel_464073/2602607402.py:1: UserWarning: Variable(s) referenced in grid_mapping not in variables: ['../crs']\n",
+      "  ds = xr.open_datatree(\n"
+     ]
+    },
+    {
+     "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 notebooks */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "  line-height: 1.6;\n",
+       "  padding-bottom: 4px;\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",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "  margin-bottom: 4px;\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-obj-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-group-box-contents > label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "  margin-block-start: 0;\n",
+       "  margin-block-end: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input,\n",
+       ".xr-group-box-contents > input,\n",
+       ".xr-array-wrap > input {\n",
+       "  display: block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input + label,\n",
+       ".xr-var-item > input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label,\n",
+       ".xr-var-item > input:enabled + label,\n",
+       ".xr-array-wrap > input:enabled + label,\n",
+       ".xr-group-box-contents > input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:focus-visible + label,\n",
+       ".xr-var-item > input:focus-visible + label,\n",
+       ".xr-array-wrap > input:focus-visible + label,\n",
+       ".xr-group-box-contents > input:focus-visible + label {\n",
+       "  outline: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label:hover,\n",
+       ".xr-var-item > input:enabled + label:hover,\n",
+       ".xr-array-wrap > input:enabled + label:hover,\n",
+       ".xr-group-box-contents > 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",
+       "  white-space: nowrap;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > em {\n",
+       "  font-weight: normal;\n",
+       "}\n",
+       "\n",
+       ".xr-span-grid {\n",
+       "  grid-column-end: -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.6em;\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",
+       ".xr-group-box-contents > label {\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-top: 4px;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in ~ .xr-section-details {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-children {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 100%;\n",
+       "  grid-column: 1 / -1;\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 0px 30px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-vline {\n",
+       "  grid-column-start: 1;\n",
+       "  border-right: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "  width: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-hline {\n",
+       "  grid-column-start: 2;\n",
+       "  grid-row-start: 1;\n",
+       "  height: 1em;\n",
+       "  width: 26px;\n",
+       "  border-bottom: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents {\n",
+       "  grid-column-start: 3;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > label::before {\n",
+       "  content: \"📂\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label::before {\n",
+       "  content: \"📁\";\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label {\n",
+       "  padding-bottom: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked ~ .xr-sections {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-ellipsis {\n",
+       "  font-size: 1.4em;\n",
+       "  font-weight: 900;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  letter-spacing: 0.15em;\n",
+       "  cursor: default;\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",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\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",
+       "  border-color: var(--xr-background-color-row-even);\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",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\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-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\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",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 4MB\n",
+       "Dimensions:                        (phony_dim_25: 1, y: 448, x: 304,\n",
+       "                                    phony_dim_27: 1)\n",
+       "Coordinates:\n",
+       "  * y                              (y) float64 4kB 5.838e+06 ... -5.338e+06\n",
+       "  * x                              (x) float64 2kB -3.838e+06 ... 3.738e+06\n",
+       "Dimensions without coordinates: phony_dim_25, phony_dim_27\n",
+       "Data variables:\n",
+       "    delta_time_beg                 (phony_dim_25) datetime64[ns] 8B ...\n",
+       "    delta_time_end                 (phony_dim_25) datetime64[ns] 8B ...\n",
+       "    mean_ssha                      (y, x) float32 545kB ...\n",
+       "    mean_weighted_earth_free2mean  (y, x) float32 545kB ...\n",
+       "    mean_weighted_geoid            (y, x) float32 545kB ...\n",
+       "    mean_weighted_geoid_free2mean  (y, x) float32 545kB ...\n",
+       "    mean_weighted_mss              (y, x) float32 545kB ...\n",
+       "    n_refsurfs                     (y, x) float64 1MB ...\n",
+       "    sigma                          (y, x) float32 545kB ...\n",
+       "    crs                            (phony_dim_27) int8 1B ...\n",
+       "Attributes:\n",
+       "    Description:  Gridded Monthly averages</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-f7c9a697-6894-4f0a-b7d3-fe6a85dab83d' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-f7c9a697-6894-4f0a-b7d3-fe6a85dab83d' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span>phony_dim_25</span>: 1</li><li><span class='xr-has-index'>y</span>: 448</li><li><span class='xr-has-index'>x</span>: 304</li><li><span>phony_dim_27</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-62e4b09b-cd27-41eb-99db-430c5de79982' class='xr-section-summary-in' type='checkbox' checked /><label for='section-62e4b09b-cd27-41eb-99db-430c5de79982' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(2)</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 class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.838e+06 5.812e+06 ... -5.338e+06</div><input id='attrs-051c1d07-db26-4430-834c-18a350836182' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-051c1d07-db26-4430-834c-18a350836182' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4419d603-df38-4f11-b04e-086b1ee3aa6a' class='xr-var-data-in' type='checkbox'><label for='data-4419d603-df38-4f11-b04e-086b1ee3aa6a' 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>long_name :</span></dt><dd>gridded y</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>units :</span></dt><dd>meters</dd><dt><span>source :</span></dt><dd>Sea Ice ATBD</dd><dt><span>contentType :</span></dt><dd>referenceInformation</dd><dt><span>description :</span></dt><dd>Grid cell center Y value in projection grid</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([ 5837500.,  5812500.,  5787500., ..., -5287500., -5312500., -5337500.],\n",
+       "      shape=(448,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-3.838e+06 -3.812e+06 ... 3.738e+06</div><input id='attrs-ccfa6b15-3b9e-40cb-b1ca-2cb6726ef3c4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ccfa6b15-3b9e-40cb-b1ca-2cb6726ef3c4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-922993ae-66d1-4e9d-a98b-b965d1681af0' class='xr-var-data-in' type='checkbox'><label for='data-922993ae-66d1-4e9d-a98b-b965d1681af0' 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>long_name :</span></dt><dd>gridded x</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>units :</span></dt><dd>meters</dd><dt><span>source :</span></dt><dd>Sea Ice ATBD</dd><dt><span>contentType :</span></dt><dd>referenceInformation</dd><dt><span>description :</span></dt><dd>Grid cell center X value in projection grid</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([-3837500., -3812500., -3787500., ...,  3687500.,  3712500.,  3737500.],\n",
+       "      shape=(304,))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e17ba555-15ee-4505-b710-625f4246686f' class='xr-section-summary-in' type='checkbox' checked /><label for='section-e17ba555-15ee-4505-b710-625f4246686f' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(10)</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>delta_time_beg</span></div><div class='xr-var-dims'>(phony_dim_25)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b2aa1f72-9667-4e5b-8d12-6f972dcba9d3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b2aa1f72-9667-4e5b-8d12-6f972dcba9d3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0664c02a-88ae-4e28-9c8f-236abe6f6966' class='xr-var-data-in' type='checkbox'><label for='data-0664c02a-88ae-4e28-9c8f-236abe6f6966' 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>long_name :</span></dt><dd>Elapsed GPS seconds</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>source :</span></dt><dd>Derived via Time Tagging</dd><dt><span>contentType :</span></dt><dd>modelResult</dd><dt><span>description :</span></dt><dd>Center time of the first reference surface used in this gridded composite in seconds since the ATLAS SDP GPS Epoch.  The ATLAS Standard Data Products (SDP) epoch offset is defined within /ancillary_data/atlas_sdp_gps_epoch as the number of GPS seconds between the GPS epoch (1980-01-06T00:00:00.000000Z UTC) and the ATLAS SDP epoch. By adding the offset contained within atlas_sdp_gps_epoch to delta time parameters, the time in gps_seconds relative to the GPS epoch can be computed.</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=datetime64[ns]]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>delta_time_end</span></div><div class='xr-var-dims'>(phony_dim_25)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-fa2175ec-0c16-4aa4-a410-5865513c7292' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fa2175ec-0c16-4aa4-a410-5865513c7292' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-52713d9a-e92d-4c07-8b0c-42063cb7fe9c' class='xr-var-data-in' type='checkbox'><label for='data-52713d9a-e92d-4c07-8b0c-42063cb7fe9c' 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>long_name :</span></dt><dd>Elapsed GPS seconds</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>source :</span></dt><dd>Derived via Time Tagging</dd><dt><span>contentType :</span></dt><dd>modelResult</dd><dt><span>description :</span></dt><dd>Center time of the last reference surface used in this gridded composite in seconds since the ATLAS SDP GPS Epoch.  The ATLAS Standard Data Products (SDP) epoch offset is defined within /ancillary_data/atlas_sdp_gps_epoch as the number of GPS seconds between the GPS epoch (1980-01-06T00:00:00.000000Z UTC) and the ATLAS SDP epoch. By adding the offset contained within atlas_sdp_gps_epoch to delta time parameters, the time in gps_seconds relative to the GPS epoch can be computed.</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=datetime64[ns]]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mean_ssha</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5a8b5541-423d-4e21-9c43-5743cfb9a6e1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5a8b5541-423d-4e21-9c43-5743cfb9a6e1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-96dde7f9-04ce-4287-a963-1f65b43c24f0' class='xr-var-data-in' type='checkbox'><label for='data-96dde7f9-04ce-4287-a963-1f65b43c24f0' 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>long_name :</span></dt><dd>Monthly mean sea surface height anomalies</dd><dt><span>units :</span></dt><dd>meters</dd><dt><span>source :</span></dt><dd>Sea Ice ATBD</dd><dt><span>contentType :</span></dt><dd>modelResult</dd><dt><span>description :</span></dt><dd>Monthly mean sea surface height anomalies (SSHA) for each monthly grid cell. Sea surface height anomalies expressed relative to the mean sea surface (other geophysical corrections also applied, as indicated in the ATBD) calculated as the mean of all available daily mean_ssha values.</dd></dl></div><div class='xr-var-data'><pre>[136192 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mean_weighted_earth_free2mean</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-733f867c-42fd-400f-b655-b7d4b09016c0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-733f867c-42fd-400f-b655-b7d4b09016c0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bacc077a-7fc0-4996-9e33-4ec642df14f0' class='xr-var-data-in' type='checkbox'><label for='data-bacc077a-7fc0-4996-9e33-4ec642df14f0' 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>long_name :</span></dt><dd>Monthly mean solid earth tide free-to-mean conversion</dd><dt><span>standard_name :</span></dt><dd>solid earth tide free2mean</dd><dt><span>units :</span></dt><dd>meters</dd><dt><span>source :</span></dt><dd>Sea Ice ATBD</dd><dt><span>contentType :</span></dt><dd>modelResult</dd><dt><span>description :</span></dt><dd>Mean monthly solid earth permanent tide correction calculated from all available daily mean_weighted_earth_free2mean values. Subtract from mean_ssha to remove the solid earth permanent tide.</dd></dl></div><div class='xr-var-data'><pre>[136192 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mean_weighted_geoid</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3c15b969-fa53-41c2-a880-79be1b2c39e8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3c15b969-fa53-41c2-a880-79be1b2c39e8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-57d3fe0e-0551-4f11-9979-2e3c93ca4535' class='xr-var-data-in' type='checkbox'><label for='data-57d3fe0e-0551-4f11-9979-2e3c93ca4535' 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>long_name :</span></dt><dd>Monthly mean geoid</dd><dt><span>units :</span></dt><dd>meters</dd><dt><span>source :</span></dt><dd>Sea Ice ATBD</dd><dt><span>contentType :</span></dt><dd>modelResult</dd><dt><span>description :</span></dt><dd>Mean monthly geoid calculated from all available daily mean_weighted_geoid values. Geoid is expressed relative to the WGS-84 reference ellipsoid from EGM2008 and is in a mean-tide system.</dd></dl></div><div class='xr-var-data'><pre>[136192 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mean_weighted_geoid_free2mean</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5053a4a3-cd7e-4474-ac96-2bedafe3baf7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5053a4a3-cd7e-4474-ac96-2bedafe3baf7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dbded6b3-8a14-4b55-b133-5f12766ac5e6' class='xr-var-data-in' type='checkbox'><label for='data-dbded6b3-8a14-4b55-b133-5f12766ac5e6' 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>long_name :</span></dt><dd>Monthly mean geoid free-to-mean conversion</dd><dt><span>standard_name :</span></dt><dd>geoid free2mean</dd><dt><span>units :</span></dt><dd>meters</dd><dt><span>source :</span></dt><dd>Sea Ice ATBD</dd><dt><span>contentType :</span></dt><dd>modelResult</dd><dt><span>description :</span></dt><dd>Mean monthly geoid free-to-mean correction calculated from all available daily mean_weighted_geoid values. Subtract from mean_weighted_mss or mean_weighted_geoid to covert to a tide-free system.</dd></dl></div><div class='xr-var-data'><pre>[136192 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mean_weighted_mss</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5a4286a2-045f-45f9-ad38-fbe417ec6b46' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5a4286a2-045f-45f9-ad38-fbe417ec6b46' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-be93bdcb-a348-40fb-9d9f-4a1d4e3e48a5' class='xr-var-data-in' type='checkbox'><label for='data-be93bdcb-a348-40fb-9d9f-4a1d4e3e48a5' 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>long_name :</span></dt><dd>Monthly mean MSS</dd><dt><span>units :</span></dt><dd>meters</dd><dt><span>source :</span></dt><dd>Sea Ice ATBD</dd><dt><span>contentType :</span></dt><dd>modelResult</dd><dt><span>description :</span></dt><dd>Mean monthly MSS calculated from all available daily mean_weighted_mss values. MSS is expressed relative to the WGS-84 reference ellipsoid from a DTU/CS-2 merged product (https://doi.org/10.5281/zenodo.4294047) and is in a mean-tide system.</dd></dl></div><div class='xr-var-data'><pre>[136192 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>n_refsurfs</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c7b77820-36b0-474f-8048-5b4bb0e7b15e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c7b77820-36b0-474f-8048-5b4bb0e7b15e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-065b19f5-ae36-4531-8b00-ecc07cfe2c58' class='xr-var-data-in' type='checkbox'><label for='data-065b19f5-ae36-4531-8b00-ecc07cfe2c58' 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>long_name :</span></dt><dd>Monthly population count</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>source :</span></dt><dd>Sea Ice ATBD</dd><dt><span>contentType :</span></dt><dd>modelResult</dd><dt><span>description :</span></dt><dd>Number of reference surface sections used in each monthly grid cell</dd></dl></div><div class='xr-var-data'><pre>[136192 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sigma</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6ba42763-debb-440b-aae5-620ec16b642a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6ba42763-debb-440b-aae5-620ec16b642a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-60be84cb-3b8c-4ce8-a657-cbc7b99268e9' class='xr-var-data-in' type='checkbox'><label for='data-60be84cb-3b8c-4ce8-a657-cbc7b99268e9' 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><dt><span>long_name :</span></dt><dd>Monthly standard deviation</dd><dt><span>source :</span></dt><dd>Sea Ice ATBD</dd><dt><span>contentType :</span></dt><dd>modelResult</dd><dt><span>description :</span></dt><dd>Standard deviation of monthly gridded mean sea surface height anomaly, computed following ATBD section 6.3.</dd></dl></div><div class='xr-var-data'><pre>[136192 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>crs</span></div><div class='xr-var-dims'>(phony_dim_27)</div><div class='xr-var-dtype'>int8</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f1754004-afef-433a-b252-ace7b0908747' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f1754004-afef-433a-b252-ace7b0908747' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a46af81a-7ac8-440d-a6d2-210853c2c7cd' class='xr-var-data-in' type='checkbox'><label for='data-a46af81a-7ac8-440d-a6d2-210853c2c7cd' 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>crs_wkt :</span></dt><dd>&quot;PROJCS[&quot;NSIDC Sea Ice Polar Stereographic North&quot;,GEOGCS[&quot;Unspecified datum based upon the Hughes 1980 ellipsoid&quot;,DATUM[&quot;Not_specified_based_on_Hughes_1980_ellipsoid&quot;,SPHEROID[&quot;Hughes 1980&quot;,6378273,298.279411123061,AUTHORITY[&quot;EPSG&quot;,&quot;7058&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6054&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4054&quot;]],PROJECTION[&quot;Polar_Stereographic&quot;],PARAMETER[&quot;latitude_of_origin&quot;,70],PARAMETER[&quot;central_meridian&quot;,-45],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,0],PARAMETER[&quot;false_northing&quot;,0],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;X&quot;,EAST],AXIS[&quot;Y&quot;,NORTH],AUTHORITY[&quot;EPSG&quot;,&quot;3411&quot;]]</dd><dt><span>proj4text :</span></dt><dd>+proj=stere +lat_0=90 +lat_ts=70 +lon_0=-45 +k=1 +x_0=0 +y_0=0 +a=6378273 +b=6356889.449 +units=m +no_defs</dd><dt><span>false_easting :</span></dt><dd>0.0</dd><dt><span>false_northing :</span></dt><dd>0.0</dd><dt><span>grid_mapping_name :</span></dt><dd>polar_stereographic</dd><dt><span>inverse_flattening :</span></dt><dd>298.279411123061</dd><dt><span>semi_major_axis :</span></dt><dd>6378273.0</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>90.0</dd><dt><span>longitude_of_projection_origin :</span></dt><dd>-45.0</dd><dt><span>standard_parallel :</span></dt><dd>70.0</dd><dt><span>srid :</span></dt><dd>urn:ogc:def:crs:EPSG::3411</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=int8]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fbb42977-98ef-42ca-9d50-d800da51be5a' class='xr-section-summary-in' type='checkbox' checked /><label for='section-fbb42977-98ef-42ca-9d50-d800da51be5a' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Description :</span></dt><dd>Gridded Monthly averages</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 4MB\n",
+       "Dimensions:                        (phony_dim_25: 1, y: 448, x: 304,\n",
+       "                                    phony_dim_27: 1)\n",
+       "Coordinates:\n",
+       "  * y                              (y) float64 4kB 5.838e+06 ... -5.338e+06\n",
+       "  * x                              (x) float64 2kB -3.838e+06 ... 3.738e+06\n",
+       "Dimensions without coordinates: phony_dim_25, phony_dim_27\n",
+       "Data variables:\n",
+       "    delta_time_beg                 (phony_dim_25) datetime64[ns] 8B ...\n",
+       "    delta_time_end                 (phony_dim_25) datetime64[ns] 8B ...\n",
+       "    mean_ssha                      (y, x) float32 545kB ...\n",
+       "    mean_weighted_earth_free2mean  (y, x) float32 545kB ...\n",
+       "    mean_weighted_geoid            (y, x) float32 545kB ...\n",
+       "    mean_weighted_geoid_free2mean  (y, x) float32 545kB ...\n",
+       "    mean_weighted_mss              (y, x) float32 545kB ...\n",
+       "    n_refsurfs                     (y, x) float64 1MB ...\n",
+       "    sigma                          (y, x) float32 545kB ...\n",
+       "    crs                            (phony_dim_27) int8 1B ...\n",
+       "Attributes:\n",
+       "    Description:  Gridded Monthly averages"
+      ]
+     },
+     "execution_count": 110,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds = xr.open_datatree(\n",
+    "    files[0], \n",
+    "    decode_timedelta=False, \n",
+    "    decode_coords='all',\n",
+    ")\n",
+    "crs = ds.crs\n",
+    "ds = ds[\"monthly\"].to_dataset(inherit='all_coordinates')  # Just get monthly grids\n",
+    "ds = ds.rename({'grid_x': 'x', 'grid_y': 'y', })\n",
+    "ds[\"crs\"] = crs\n",
+    "ds"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 125,
+   "id": "be65c7d1-77a3-4502-aed6-fb164174742e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array(['2018-10-14T00:21:49.440616236'], dtype='datetime64[ns]')"
+      ]
+     },
+     "execution_count": 125,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds.delta_time_beg.values"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b90d5f18-fbe8-468d-8737-b505c8ccb36d",
+   "metadata": {},
+   "source": [
+    "### Use `geopandas` to transform geographic coordinates to grid CRS\n",
+    "\n",
+    "We assume that the original geographic coordinates are in WGS84.  Geopandas offers a convenient way to transform the coordinates and also to export transformed coordinates to `xarray.DataArray` objects.\n",
+    "\n",
+    "_This could be done using `pyproj` as well, but `geopandas` is convenient._"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 111,
+   "id": "54c8f235-09e1-40e2-a924-0648a6c0722e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import geopandas as gpd\n",
+    "\n",
+    "# gdf = gpd.GeoDataFrame\n",
+    "df = pd.DataFrame({\n",
+    "    'latitude': lat, \n",
+    "    'longitude': lon, \n",
+    "    'date': days,\n",
+    "})\n",
+    "gdf = gpd.GeoDataFrame(df, geometry=gpd.points_from_xy(lon, lat), crs=\"EPSG:4326\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 112,
+   "id": "5276378b-6e9d-44c5-8a10-1606418913f3",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>latitude</th>\n",
+       "      <th>longitude</th>\n",
+       "      <th>date</th>\n",
+       "      <th>geometry</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>85.878887</td>\n",
+       "      <td>-99.876421</td>\n",
+       "      <td>2025-12-02</td>\n",
+       "      <td>POINT (-99.87642 85.87889)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>82.540094</td>\n",
+       "      <td>-110.356676</td>\n",
+       "      <td>2023-09-30</td>\n",
+       "      <td>POINT (-110.35668 82.54009)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>77.002147</td>\n",
+       "      <td>-106.509007</td>\n",
+       "      <td>2021-12-13</td>\n",
+       "      <td>POINT (-106.50901 77.00215)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>82.242096</td>\n",
+       "      <td>-166.134799</td>\n",
+       "      <td>2020-02-06</td>\n",
+       "      <td>POINT (-166.1348 82.2421)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>81.609988</td>\n",
+       "      <td>-84.541883</td>\n",
+       "      <td>2019-11-14</td>\n",
+       "      <td>POINT (-84.54188 81.60999)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>77.161087</td>\n",
+       "      <td>-32.784409</td>\n",
+       "      <td>2024-09-20</td>\n",
+       "      <td>POINT (-32.78441 77.16109)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>82.406983</td>\n",
+       "      <td>129.734214</td>\n",
+       "      <td>2024-03-30</td>\n",
+       "      <td>POINT (129.73421 82.40698)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>76.306542</td>\n",
+       "      <td>-98.611666</td>\n",
+       "      <td>2023-11-05</td>\n",
+       "      <td>POINT (-98.61167 76.30654)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>84.732205</td>\n",
+       "      <td>-84.142686</td>\n",
+       "      <td>2024-08-15</td>\n",
+       "      <td>POINT (-84.14269 84.7322)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>84.878425</td>\n",
+       "      <td>-25.139996</td>\n",
+       "      <td>2020-04-12</td>\n",
+       "      <td>POINT (-25.14 84.87843)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>77.115882</td>\n",
+       "      <td>-74.003359</td>\n",
+       "      <td>2020-01-08</td>\n",
+       "      <td>POINT (-74.00336 77.11588)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>75.897833</td>\n",
+       "      <td>-61.535530</td>\n",
+       "      <td>2024-11-18</td>\n",
+       "      <td>POINT (-61.53553 75.89783)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>75.775344</td>\n",
+       "      <td>157.765110</td>\n",
+       "      <td>2024-11-09</td>\n",
+       "      <td>POINT (157.76511 75.77534)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>77.473378</td>\n",
+       "      <td>126.977091</td>\n",
+       "      <td>2020-11-01</td>\n",
+       "      <td>POINT (126.97709 77.47338)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>76.416839</td>\n",
+       "      <td>119.536651</td>\n",
+       "      <td>2019-07-09</td>\n",
+       "      <td>POINT (119.53665 76.41684)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>81.939321</td>\n",
+       "      <td>-71.576727</td>\n",
+       "      <td>2024-09-17</td>\n",
+       "      <td>POINT (-71.57673 81.93932)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>81.715396</td>\n",
+       "      <td>-125.997012</td>\n",
+       "      <td>2022-07-27</td>\n",
+       "      <td>POINT (-125.99701 81.7154)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>75.483854</td>\n",
+       "      <td>-177.826086</td>\n",
+       "      <td>2019-01-25</td>\n",
+       "      <td>POINT (-177.82609 75.48385)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>77.509625</td>\n",
+       "      <td>133.533183</td>\n",
+       "      <td>2019-06-06</td>\n",
+       "      <td>POINT (133.53318 77.50963)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>83.110725</td>\n",
+       "      <td>-18.598783</td>\n",
+       "      <td>2024-01-24</td>\n",
+       "      <td>POINT (-18.59878 83.11072)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>75.314986</td>\n",
+       "      <td>81.438867</td>\n",
+       "      <td>2021-11-10</td>\n",
+       "      <td>POINT (81.43887 75.31499)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>75.045494</td>\n",
+       "      <td>50.543610</td>\n",
+       "      <td>2023-03-17</td>\n",
+       "      <td>POINT (50.54361 75.04549)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>87.200711</td>\n",
+       "      <td>-167.645250</td>\n",
+       "      <td>2021-08-21</td>\n",
+       "      <td>POINT (-167.64525 87.20071)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>76.570009</td>\n",
+       "      <td>-167.018120</td>\n",
+       "      <td>2020-07-14</td>\n",
+       "      <td>POINT (-167.01812 76.57001)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>87.304326</td>\n",
+       "      <td>-167.672523</td>\n",
+       "      <td>2025-08-17</td>\n",
+       "      <td>POINT (-167.67252 87.30433)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>78.498242</td>\n",
+       "      <td>-115.992638</td>\n",
+       "      <td>2020-04-05</td>\n",
+       "      <td>POINT (-115.99264 78.49824)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>79.750194</td>\n",
+       "      <td>-69.528437</td>\n",
+       "      <td>2025-03-24</td>\n",
+       "      <td>POINT (-69.52844 79.75019)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>82.942209</td>\n",
+       "      <td>-38.228897</td>\n",
+       "      <td>2025-09-19</td>\n",
+       "      <td>POINT (-38.2289 82.94221)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>77.519608</td>\n",
+       "      <td>154.299379</td>\n",
+       "      <td>2022-10-10</td>\n",
+       "      <td>POINT (154.29938 77.51961)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>78.800802</td>\n",
+       "      <td>-51.460561</td>\n",
+       "      <td>2025-05-07</td>\n",
+       "      <td>POINT (-51.46056 78.8008)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>76.305085</td>\n",
+       "      <td>-18.538357</td>\n",
+       "      <td>2023-07-26</td>\n",
+       "      <td>POINT (-18.53836 76.30508)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>31</th>\n",
+       "      <td>79.717717</td>\n",
+       "      <td>-81.551905</td>\n",
+       "      <td>2020-04-07</td>\n",
+       "      <td>POINT (-81.55191 79.71772)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>75.725559</td>\n",
+       "      <td>156.857665</td>\n",
+       "      <td>2019-05-11</td>\n",
+       "      <td>POINT (156.85766 75.72556)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33</th>\n",
+       "      <td>83.343715</td>\n",
+       "      <td>-5.885913</td>\n",
+       "      <td>2023-05-03</td>\n",
+       "      <td>POINT (-5.88591 83.34371)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>34</th>\n",
+       "      <td>77.821635</td>\n",
+       "      <td>-170.375585</td>\n",
+       "      <td>2021-11-20</td>\n",
+       "      <td>POINT (-170.37559 77.82163)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>35</th>\n",
+       "      <td>79.953148</td>\n",
+       "      <td>99.053349</td>\n",
+       "      <td>2022-03-13</td>\n",
+       "      <td>POINT (99.05335 79.95315)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>36</th>\n",
+       "      <td>86.778715</td>\n",
+       "      <td>52.245274</td>\n",
+       "      <td>2021-11-15</td>\n",
+       "      <td>POINT (52.24527 86.77871)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>37</th>\n",
+       "      <td>85.706323</td>\n",
+       "      <td>96.626796</td>\n",
+       "      <td>2018-10-21</td>\n",
+       "      <td>POINT (96.6268 85.70632)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>38</th>\n",
+       "      <td>76.027898</td>\n",
+       "      <td>43.899166</td>\n",
+       "      <td>2024-10-01</td>\n",
+       "      <td>POINT (43.89917 76.0279)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>39</th>\n",
+       "      <td>76.651494</td>\n",
+       "      <td>74.983431</td>\n",
+       "      <td>2020-04-06</td>\n",
+       "      <td>POINT (74.98343 76.65149)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>40</th>\n",
+       "      <td>82.240191</td>\n",
+       "      <td>160.385187</td>\n",
+       "      <td>2018-10-03</td>\n",
+       "      <td>POINT (160.38519 82.24019)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>41</th>\n",
+       "      <td>85.175929</td>\n",
+       "      <td>-41.117508</td>\n",
+       "      <td>2021-05-15</td>\n",
+       "      <td>POINT (-41.11751 85.17593)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>42</th>\n",
+       "      <td>86.382235</td>\n",
+       "      <td>160.283466</td>\n",
+       "      <td>2019-08-05</td>\n",
+       "      <td>POINT (160.28347 86.38224)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>43</th>\n",
+       "      <td>81.719557</td>\n",
+       "      <td>99.791987</td>\n",
+       "      <td>2022-05-12</td>\n",
+       "      <td>POINT (99.79199 81.71956)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>44</th>\n",
+       "      <td>86.230500</td>\n",
+       "      <td>19.334520</td>\n",
+       "      <td>2024-10-19</td>\n",
+       "      <td>POINT (19.33452 86.2305)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>45</th>\n",
+       "      <td>76.996289</td>\n",
+       "      <td>132.077269</td>\n",
+       "      <td>2025-05-28</td>\n",
+       "      <td>POINT (132.07727 76.99629)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46</th>\n",
+       "      <td>77.188230</td>\n",
+       "      <td>25.375442</td>\n",
+       "      <td>2023-11-28</td>\n",
+       "      <td>POINT (25.37544 77.18823)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>47</th>\n",
+       "      <td>84.702183</td>\n",
+       "      <td>136.170244</td>\n",
+       "      <td>2019-03-29</td>\n",
+       "      <td>POINT (136.17024 84.70218)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>76.579978</td>\n",
+       "      <td>-141.819271</td>\n",
+       "      <td>2020-11-25</td>\n",
+       "      <td>POINT (-141.81927 76.57998)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>86.053686</td>\n",
+       "      <td>-58.070912</td>\n",
+       "      <td>2021-06-16</td>\n",
+       "      <td>POINT (-58.07091 86.05369)</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     latitude   longitude       date                     geometry\n",
+       "0   85.878887  -99.876421 2025-12-02   POINT (-99.87642 85.87889)\n",
+       "1   82.540094 -110.356676 2023-09-30  POINT (-110.35668 82.54009)\n",
+       "2   77.002147 -106.509007 2021-12-13  POINT (-106.50901 77.00215)\n",
+       "3   82.242096 -166.134799 2020-02-06    POINT (-166.1348 82.2421)\n",
+       "4   81.609988  -84.541883 2019-11-14   POINT (-84.54188 81.60999)\n",
+       "5   77.161087  -32.784409 2024-09-20   POINT (-32.78441 77.16109)\n",
+       "6   82.406983  129.734214 2024-03-30   POINT (129.73421 82.40698)\n",
+       "7   76.306542  -98.611666 2023-11-05   POINT (-98.61167 76.30654)\n",
+       "8   84.732205  -84.142686 2024-08-15    POINT (-84.14269 84.7322)\n",
+       "9   84.878425  -25.139996 2020-04-12      POINT (-25.14 84.87843)\n",
+       "10  77.115882  -74.003359 2020-01-08   POINT (-74.00336 77.11588)\n",
+       "11  75.897833  -61.535530 2024-11-18   POINT (-61.53553 75.89783)\n",
+       "12  75.775344  157.765110 2024-11-09   POINT (157.76511 75.77534)\n",
+       "13  77.473378  126.977091 2020-11-01   POINT (126.97709 77.47338)\n",
+       "14  76.416839  119.536651 2019-07-09   POINT (119.53665 76.41684)\n",
+       "15  81.939321  -71.576727 2024-09-17   POINT (-71.57673 81.93932)\n",
+       "16  81.715396 -125.997012 2022-07-27   POINT (-125.99701 81.7154)\n",
+       "17  75.483854 -177.826086 2019-01-25  POINT (-177.82609 75.48385)\n",
+       "18  77.509625  133.533183 2019-06-06   POINT (133.53318 77.50963)\n",
+       "19  83.110725  -18.598783 2024-01-24   POINT (-18.59878 83.11072)\n",
+       "20  75.314986   81.438867 2021-11-10    POINT (81.43887 75.31499)\n",
+       "21  75.045494   50.543610 2023-03-17    POINT (50.54361 75.04549)\n",
+       "22  87.200711 -167.645250 2021-08-21  POINT (-167.64525 87.20071)\n",
+       "23  76.570009 -167.018120 2020-07-14  POINT (-167.01812 76.57001)\n",
+       "24  87.304326 -167.672523 2025-08-17  POINT (-167.67252 87.30433)\n",
+       "25  78.498242 -115.992638 2020-04-05  POINT (-115.99264 78.49824)\n",
+       "26  79.750194  -69.528437 2025-03-24   POINT (-69.52844 79.75019)\n",
+       "27  82.942209  -38.228897 2025-09-19    POINT (-38.2289 82.94221)\n",
+       "28  77.519608  154.299379 2022-10-10   POINT (154.29938 77.51961)\n",
+       "29  78.800802  -51.460561 2025-05-07    POINT (-51.46056 78.8008)\n",
+       "30  76.305085  -18.538357 2023-07-26   POINT (-18.53836 76.30508)\n",
+       "31  79.717717  -81.551905 2020-04-07   POINT (-81.55191 79.71772)\n",
+       "32  75.725559  156.857665 2019-05-11   POINT (156.85766 75.72556)\n",
+       "33  83.343715   -5.885913 2023-05-03    POINT (-5.88591 83.34371)\n",
+       "34  77.821635 -170.375585 2021-11-20  POINT (-170.37559 77.82163)\n",
+       "35  79.953148   99.053349 2022-03-13    POINT (99.05335 79.95315)\n",
+       "36  86.778715   52.245274 2021-11-15    POINT (52.24527 86.77871)\n",
+       "37  85.706323   96.626796 2018-10-21     POINT (96.6268 85.70632)\n",
+       "38  76.027898   43.899166 2024-10-01     POINT (43.89917 76.0279)\n",
+       "39  76.651494   74.983431 2020-04-06    POINT (74.98343 76.65149)\n",
+       "40  82.240191  160.385187 2018-10-03   POINT (160.38519 82.24019)\n",
+       "41  85.175929  -41.117508 2021-05-15   POINT (-41.11751 85.17593)\n",
+       "42  86.382235  160.283466 2019-08-05   POINT (160.28347 86.38224)\n",
+       "43  81.719557   99.791987 2022-05-12    POINT (99.79199 81.71956)\n",
+       "44  86.230500   19.334520 2024-10-19     POINT (19.33452 86.2305)\n",
+       "45  76.996289  132.077269 2025-05-28   POINT (132.07727 76.99629)\n",
+       "46  77.188230   25.375442 2023-11-28    POINT (25.37544 77.18823)\n",
+       "47  84.702183  136.170244 2019-03-29   POINT (136.17024 84.70218)\n",
+       "48  76.579978 -141.819271 2020-11-25  POINT (-141.81927 76.57998)\n",
+       "49  86.053686  -58.070912 2021-06-16   POINT (-58.07091 86.05369)"
+      ]
+     },
+     "execution_count": 112,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "gdf"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 114,
+   "id": "dc47c66a-ce6c-4aa3-89d1-6d8f06903dbb",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<GeoAxes: xlabel='gridded x [meters]', ylabel='gridded y [meters]'>"
+      ]
+     },
+     "execution_count": 114,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 1000x1000 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import cartopy.crs as ccrs\n",
+    "import cartopy.feature as cfeature\n",
+    "\n",
+    "globe = ccrs.Globe(\n",
+    "    ellipse=None, \n",
+    "    semimajor_axis=ds.crs.semi_major_axis, \n",
+    "    inverse_flattening=ds.crs.inverse_flattening\n",
+    ")\n",
+    "projection = ccrs.Stereographic(\n",
+    "    central_latitude=ds.crs.latitude_of_projection_origin, \n",
+    "    central_longitude=ds.crs.longitude_of_projection_origin,\n",
+    "    true_scale_latitude=ds.crs.standard_parallel,\n",
+    ")\n",
+    "\n",
+    "p = ds.mean_ssha.plot(\n",
+    "    subplot_kws=dict(projection=projection),\n",
+    "    figsize=(10,10)\n",
+    ")\n",
+    "p.axes.add_feature(cfeature.LAND, facecolor='lightgrey')\n",
+    "gdf.to_crs(3411).plot(ax=p.axes, markersize=3, color='black')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e6a7bcc4-05c5-44dd-9a46-dd1f5246869a",
+   "metadata": {},
+   "source": [
+    "### Create xarray containing points"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 99,
+   "id": "39f88018-dd37-4ab6-88af-e86819acdd8e",
+   "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 notebooks */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "  line-height: 1.6;\n",
+       "  padding-bottom: 4px;\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",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "  margin-bottom: 4px;\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-obj-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-group-box-contents > label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "  margin-block-start: 0;\n",
+       "  margin-block-end: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input,\n",
+       ".xr-group-box-contents > input,\n",
+       ".xr-array-wrap > input {\n",
+       "  display: block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input + label,\n",
+       ".xr-var-item > input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label,\n",
+       ".xr-var-item > input:enabled + label,\n",
+       ".xr-array-wrap > input:enabled + label,\n",
+       ".xr-group-box-contents > input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:focus-visible + label,\n",
+       ".xr-var-item > input:focus-visible + label,\n",
+       ".xr-array-wrap > input:focus-visible + label,\n",
+       ".xr-group-box-contents > input:focus-visible + label {\n",
+       "  outline: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label:hover,\n",
+       ".xr-var-item > input:enabled + label:hover,\n",
+       ".xr-array-wrap > input:enabled + label:hover,\n",
+       ".xr-group-box-contents > 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",
+       "  white-space: nowrap;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > em {\n",
+       "  font-weight: normal;\n",
+       "}\n",
+       "\n",
+       ".xr-span-grid {\n",
+       "  grid-column-end: -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.6em;\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",
+       ".xr-group-box-contents > label {\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-top: 4px;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in ~ .xr-section-details {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-children {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 100%;\n",
+       "  grid-column: 1 / -1;\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 0px 30px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-vline {\n",
+       "  grid-column-start: 1;\n",
+       "  border-right: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "  width: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-hline {\n",
+       "  grid-column-start: 2;\n",
+       "  grid-row-start: 1;\n",
+       "  height: 1em;\n",
+       "  width: 26px;\n",
+       "  border-bottom: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents {\n",
+       "  grid-column-start: 3;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > label::before {\n",
+       "  content: \"📂\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label::before {\n",
+       "  content: \"📁\";\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label {\n",
+       "  padding-bottom: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked ~ .xr-sections {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-ellipsis {\n",
+       "  font-size: 1.4em;\n",
+       "  font-weight: 900;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  letter-spacing: 0.15em;\n",
+       "  cursor: default;\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",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\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",
+       "  border-color: var(--xr-background-color-row-even);\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",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\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-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\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",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 1kB\n",
+       "Dimensions:  (index: 50)\n",
+       "Coordinates:\n",
+       "  * index    (index) int64 400B 0 1 2 3 4 5 6 7 8 ... 41 42 43 44 45 46 47 48 49\n",
+       "Data variables:\n",
+       "    x        (index) float64 400B -3.653e+05 -7.355e+05 ... -1.45e+06 -9.672e+04\n",
+       "    y        (index) float64 400B -2.57e+05 -3.374e+05 ... 1.734e+05 -4.166e+05</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-c4c40beb-879f-4005-b1b1-7a7e450071c6' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-c4c40beb-879f-4005-b1b1-7a7e450071c6' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>index</span>: 50</li></ul></div></li><li class='xr-section-item'><input id='section-09e70738-d96b-46ac-a90a-1fce37b9a2c0' class='xr-section-summary-in' type='checkbox' checked /><label for='section-09e70738-d96b-46ac-a90a-1fce37b9a2c0' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(1)</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 class='xr-has-index'>index</span></div><div class='xr-var-dims'>(index)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 6 ... 44 45 46 47 48 49</div><input id='attrs-4300ff1c-67cf-41fd-a546-ef78128965e8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4300ff1c-67cf-41fd-a546-ef78128965e8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4a118367-b49e-42d0-8a27-c2a2ecafa858' class='xr-var-data-in' type='checkbox'><label for='data-4a118367-b49e-42d0-8a27-c2a2ecafa858' 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>[50 values with dtype=int64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-53e9dc28-5ec3-4357-946e-1b5f67d16abb' class='xr-section-summary-in' type='checkbox' checked /><label for='section-53e9dc28-5ec3-4357-946e-1b5f67d16abb' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(2)</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>x</span></div><div class='xr-var-dims'>(index)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-3.653e+05 ... -9.672e+04</div><input id='attrs-d29b0141-2925-41f2-a3a7-074f3a33cb11' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d29b0141-2925-41f2-a3a7-074f3a33cb11' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fe496c85-c0da-4d43-9443-1d5a432c20d4' class='xr-var-data-in' type='checkbox'><label for='data-fe496c85-c0da-4d43-9443-1d5a432c20d4' 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>array([ -365299.06797732,  -735522.58444328, -1242646.26051312,\n",
+       "        -720408.78841714,  -579629.91232069,   295475.5406155 ,\n",
+       "          75596.4000421 , -1199651.22284826,  -360473.826807  ,\n",
+       "         188605.05807765,  -679486.46740781,  -436913.04620378,\n",
+       "        -599235.41290089,   190123.29737365,   394096.63723521,\n",
+       "        -391290.19174755,  -887896.36337841, -1159284.08844815,\n",
+       "          34768.337277  ,   332235.19072211,  1286570.88238173,\n",
+       "        1621285.378973  ,  -255389.83870769, -1239002.90885596,\n",
+       "        -245858.20944427, -1181858.07396654,  -462142.69055134,\n",
+       "          90254.48969583,  -448544.04448483,  -136927.63319649,\n",
+       "         664112.55676475,  -665083.64336137,  -578583.34833368,\n",
+       "         455392.32738732, -1079609.86831658,   640484.55295048,\n",
+       "         346261.72874639,   288875.11924985,  1520553.9881336 ,\n",
+       "        1257982.19615459,  -360903.44119328,    35404.84171889,\n",
+       "        -167437.39486236,   518037.76941438,   368187.4439591 ,\n",
+       "          72125.200322  ,  1312530.34429938,   -11729.10568348,\n",
+       "       -1449869.92251011,   -96719.31228942])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>y</span></div><div class='xr-var-dims'>(index)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-2.57e+05 -3.374e+05 ... -4.166e+05</div><input id='attrs-b1952db9-5c80-452b-b098-6f866127873b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b1952db9-5c80-452b-b098-6f866127873b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-09eeeecd-2447-4622-8531-6fb8df8b3aaf' class='xr-var-data-in' type='checkbox'><label for='data-09eeeecd-2447-4622-8531-6fb8df8b3aaf' 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>array([ -256961.13468225,  -337421.5001514 ,  -674448.94307329,\n",
+       "         435175.35875899,  -702100.98963618, -1364830.33080379,\n",
+       "         820229.47937924,  -884082.19513189,  -442888.3762996 ,\n",
+       "        -522154.29656827, -1225656.57014779, -1471641.94259745,\n",
+       "        1427958.19034898,  1348883.90012342,  1424604.6371626 ,\n",
+       "        -782181.85846592,  -140676.43410008,  1074489.64309649,\n",
+       "        1357799.80382398,  -669247.76607613,   949889.69651938,\n",
+       "         157357.57472342,   163612.9484833 ,   774759.87831518,\n",
+       "         157671.71825793,  -407116.24126791, -1012747.25338113,\n",
+       "        -760157.58273002,  1280885.27002432, -1209197.93073603,\n",
+       "       -1334239.80453487,  -897108.13835662,  1442349.91026356,\n",
+       "        -560078.72411194,   766546.63043906,   883279.71722924,\n",
+       "          44021.03509835,   364820.06072881,   -29218.26283812,\n",
+       "         725811.40385443,   760568.30996417,  -521686.09224342,\n",
+       "         354481.27035717,   734147.36089757,  -176923.51837769,\n",
+       "        1412680.45048556,  -468005.04175548,   574183.35360794,\n",
+       "         173381.11905944,  -416584.42342492])</pre></div></li></ul></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 1kB\n",
+       "Dimensions:  (index: 50)\n",
+       "Coordinates:\n",
+       "  * index    (index) int64 400B 0 1 2 3 4 5 6 7 8 ... 41 42 43 44 45 46 47 48 49\n",
+       "Data variables:\n",
+       "    x        (index) float64 400B -3.653e+05 -7.355e+05 ... -1.45e+06 -9.672e+04\n",
+       "    y        (index) float64 400B -2.57e+05 -3.374e+05 ... 1.734e+05 -4.166e+05"
+      ]
+     },
+     "execution_count": 99,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pts_xr = gdf.to_crs(3411).geometry.get_coordinates().to_xarray()\n",
+    "pts_xr"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 116,
+   "id": "a5d2266e-0b0e-44ab-a377-4414fd9be5cd",
+   "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 notebooks */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "  line-height: 1.6;\n",
+       "  padding-bottom: 4px;\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",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "  margin-bottom: 4px;\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-obj-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-group-box-contents > label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "  margin-block-start: 0;\n",
+       "  margin-block-end: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input,\n",
+       ".xr-group-box-contents > input,\n",
+       ".xr-array-wrap > input {\n",
+       "  display: block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input + label,\n",
+       ".xr-var-item > input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label,\n",
+       ".xr-var-item > input:enabled + label,\n",
+       ".xr-array-wrap > input:enabled + label,\n",
+       ".xr-group-box-contents > input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:focus-visible + label,\n",
+       ".xr-var-item > input:focus-visible + label,\n",
+       ".xr-array-wrap > input:focus-visible + label,\n",
+       ".xr-group-box-contents > input:focus-visible + label {\n",
+       "  outline: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label:hover,\n",
+       ".xr-var-item > input:enabled + label:hover,\n",
+       ".xr-array-wrap > input:enabled + label:hover,\n",
+       ".xr-group-box-contents > 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",
+       "  white-space: nowrap;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > em {\n",
+       "  font-weight: normal;\n",
+       "}\n",
+       "\n",
+       ".xr-span-grid {\n",
+       "  grid-column-end: -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.6em;\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",
+       ".xr-group-box-contents > label {\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-top: 4px;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in ~ .xr-section-details {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-children {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 100%;\n",
+       "  grid-column: 1 / -1;\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 0px 30px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-vline {\n",
+       "  grid-column-start: 1;\n",
+       "  border-right: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "  width: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-hline {\n",
+       "  grid-column-start: 2;\n",
+       "  grid-row-start: 1;\n",
+       "  height: 1em;\n",
+       "  width: 26px;\n",
+       "  border-bottom: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents {\n",
+       "  grid-column-start: 3;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > label::before {\n",
+       "  content: \"📂\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label::before {\n",
+       "  content: \"📁\";\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label {\n",
+       "  padding-bottom: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked ~ .xr-sections {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-ellipsis {\n",
+       "  font-size: 1.4em;\n",
+       "  font-weight: 900;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  letter-spacing: 0.15em;\n",
+       "  cursor: default;\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",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\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",
+       "  border-color: var(--xr-background-color-row-even);\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",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\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-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\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",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;mean_ssha&#x27; (index: 50)&gt; Size: 200B\n",
+       "[50 values with dtype=float32]\n",
+       "Coordinates:\n",
+       "  * index    (index) int64 400B 0 1 2 3 4 5 6 7 8 ... 41 42 43 44 45 46 47 48 49\n",
+       "    x        (index) float64 400B -3.625e+05 -7.375e+05 ... -1.438e+06 -8.75e+04\n",
+       "    y        (index) float64 400B -2.625e+05 -3.375e+05 ... 1.625e+05 -4.125e+05\n",
+       "Attributes:\n",
+       "    long_name:    Monthly mean sea surface height anomalies\n",
+       "    units:        meters\n",
+       "    source:       Sea Ice ATBD\n",
+       "    contentType:  modelResult\n",
+       "    description:  Monthly mean sea surface height anomalies (SSHA) for each m...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-obj-name'>&#x27;mean_ssha&#x27;</div><ul class='xr-dim-list'><li><span class='xr-has-index'>index</span>: 50</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-7370fc9e-709c-4db6-bb6b-06d1d7614cb4' class='xr-array-in' type='checkbox' checked><label for='section-7370fc9e-709c-4db6-bb6b-06d1d7614cb4' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[50 values with dtype=float32]</pre></div></div></li><li class='xr-section-item'><input id='section-497cd64b-3d13-40a4-b836-d5e33541de12' class='xr-section-summary-in' type='checkbox' checked /><label for='section-497cd64b-3d13-40a4-b836-d5e33541de12' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(3)</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 class='xr-has-index'>index</span></div><div class='xr-var-dims'>(index)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 6 ... 44 45 46 47 48 49</div><input id='attrs-edff74d2-8dfb-4663-af81-30cf507e6f74' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-edff74d2-8dfb-4663-af81-30cf507e6f74' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bebd0687-b659-43f0-93a7-9ec58cef7297' class='xr-var-data-in' type='checkbox'><label for='data-bebd0687-b659-43f0-93a7-9ec58cef7297' 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>[50 values with dtype=int64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x</span></div><div class='xr-var-dims'>(index)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-3.625e+05 -7.375e+05 ... -8.75e+04</div><input id='attrs-77be3ec3-3f12-46cb-8895-87325d0bdac0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-77be3ec3-3f12-46cb-8895-87325d0bdac0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8fa79f66-c293-48c7-9a5f-3867611a239f' class='xr-var-data-in' type='checkbox'><label for='data-8fa79f66-c293-48c7-9a5f-3867611a239f' 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>long_name :</span></dt><dd>gridded x</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>units :</span></dt><dd>meters</dd><dt><span>source :</span></dt><dd>Sea Ice ATBD</dd><dt><span>contentType :</span></dt><dd>referenceInformation</dd><dt><span>description :</span></dt><dd>Grid cell center X value in projection grid</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([ -362500.,  -737500., -1237500.,  -712500.,  -587500.,   287500.,\n",
+       "          87500., -1187500.,  -362500.,   187500.,  -687500.,  -437500.,\n",
+       "        -587500.,   187500.,   387500.,  -387500.,  -887500., -1162500.,\n",
+       "          37500.,   337500.,  1287500.,  1612500.,  -262500., -1237500.,\n",
+       "        -237500., -1187500.,  -462500.,    87500.,  -437500.,  -137500.,\n",
+       "         662500.,  -662500.,  -587500.,   462500., -1087500.,   637500.,\n",
+       "         337500.,   287500.,  1512500.,  1262500.,  -362500.,    37500.,\n",
+       "        -162500.,   512500.,   362500.,    62500.,  1312500.,   -12500.,\n",
+       "       -1437500.,   -87500.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>y</span></div><div class='xr-var-dims'>(index)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-2.625e+05 ... -4.125e+05</div><input id='attrs-38b38a2b-1064-4c0b-89e1-ea0f9e3eecb5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-38b38a2b-1064-4c0b-89e1-ea0f9e3eecb5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e8ccfded-ea6f-4ebb-a95c-5a0be56ce663' class='xr-var-data-in' type='checkbox'><label for='data-e8ccfded-ea6f-4ebb-a95c-5a0be56ce663' 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>long_name :</span></dt><dd>gridded y</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>units :</span></dt><dd>meters</dd><dt><span>source :</span></dt><dd>Sea Ice ATBD</dd><dt><span>contentType :</span></dt><dd>referenceInformation</dd><dt><span>description :</span></dt><dd>Grid cell center Y value in projection grid</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([ -262500.,  -337500.,  -662500.,   437500.,  -712500., -1362500.,\n",
+       "         812500.,  -887500.,  -437500.,  -512500., -1237500., -1462500.,\n",
+       "        1437500.,  1337500.,  1412500.,  -787500.,  -137500.,  1062500.,\n",
+       "        1362500.,  -662500.,   937500.,   162500.,   162500.,   762500.,\n",
+       "         162500.,  -412500., -1012500.,  -762500.,  1287500., -1212500.,\n",
+       "       -1337500.,  -887500.,  1437500.,  -562500.,   762500.,   887500.,\n",
+       "          37500.,   362500.,   -37500.,   737500.,   762500.,  -512500.,\n",
+       "         362500.,   737500.,  -187500.,  1412500.,  -462500.,   562500.,\n",
+       "         162500.,  -412500.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1ebf2945-77e4-4724-b0d6-146af7749207' class='xr-section-summary-in' type='checkbox' checked /><label for='section-1ebf2945-77e4-4724-b0d6-146af7749207' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Monthly mean sea surface height anomalies</dd><dt><span>units :</span></dt><dd>meters</dd><dt><span>source :</span></dt><dd>Sea Ice ATBD</dd><dt><span>contentType :</span></dt><dd>modelResult</dd><dt><span>description :</span></dt><dd>Monthly mean sea surface height anomalies (SSHA) for each monthly grid cell. Sea surface height anomalies expressed relative to the mean sea surface (other geophysical corrections also applied, as indicated in the ATBD) calculated as the mean of all available daily mean_ssha values.</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.DataArray 'mean_ssha' (index: 50)> Size: 200B\n",
+       "[50 values with dtype=float32]\n",
+       "Coordinates:\n",
+       "  * index    (index) int64 400B 0 1 2 3 4 5 6 7 8 ... 41 42 43 44 45 46 47 48 49\n",
+       "    x        (index) float64 400B -3.625e+05 -7.375e+05 ... -1.438e+06 -8.75e+04\n",
+       "    y        (index) float64 400B -2.625e+05 -3.375e+05 ... 1.625e+05 -4.125e+05\n",
+       "Attributes:\n",
+       "    long_name:    Monthly mean sea surface height anomalies\n",
+       "    units:        meters\n",
+       "    source:       Sea Ice ATBD\n",
+       "    contentType:  modelResult\n",
+       "    description:  Monthly mean sea surface height anomalies (SSHA) for each m..."
+      ]
+     },
+     "execution_count": 116,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds.mean_ssha.sel(x=pts_xr.x, y=pts_xr.y, method='nearest')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "0a0481a7-fb4a-4bb0-bd12-62a59ff9e491",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.14.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/tutorials/how_to_select_xarray_gridcells_using_vectorized_indexing.ipynb b/tutorials/how_to_select_xarray_gridcells_using_vectorized_indexing.ipynb
index cf590dc..5c0e94d 100755
--- a/tutorials/how_to_select_xarray_gridcells_using_vectorized_indexing.ipynb
+++ b/tutorials/how_to_select_xarray_gridcells_using_vectorized_indexing.ipynb
@@ -1572,7 +1572,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.0"
+   "version": "3.14.3"
   }
  },
  "nbformat": 4,