diff --git a/Recipes/AUS2200_1day_rain.ipynb b/Recipes/AUS2200_1day_rain.ipynb
new file mode 100644
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--- /dev/null
+++ b/Recipes/AUS2200_1day_rain.ipynb
@@ -0,0 +1,1735 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "467e28a0-cd24-4c62-a1e6-f00ca41b1b28",
+   "metadata": {},
+   "source": [
+    "### 1-day rain plots\n",
+    "\n",
+    "Plots daily rainfall over 5 days of the East Coast Low AUS2200 simulation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "45afb41b-0618-4d2c-9e0b-e4e27e0464d1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from dask.distributed import Client\n",
+    "from glob import glob\n",
+    "import xarray as xr\n",
+    "import pandas"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "53924b17-f77b-4ebc-a589-06df5ca94e8c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "flist=sorted(glob('/g/data/v45/cc6171/experiments/ECL-2016_smallshift/netcdf/u-cs142/2016060*T*Z/aus2200/d0198/RA3/um/umnsa_spec_*.nc'))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "c18fcf31-9189-4237-8242-8d36845321ae",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/g/data/hh5/public/apps/cms_conda/envs/analysis3-24.04/lib/python3.10/site-packages/distributed/node.py:182: UserWarning: Port 8787 is already in use.\n",
+      "Perhaps you already have a cluster running?\n",
+      "Hosting the HTTP server on port 37389 instead\n",
+      "  warnings.warn(\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Modifying workers\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/g/data/hh5/public/apps/dask-optimiser/schedplugin.py:160: UserWarning: Attempted illegal binding: []\n",
+      "  warn(f\"Attempted illegal binding: {(sorted(list(self.slots_available - taken_slots))[:self.worker.state.nthreads])}\")\n",
+      "/g/data/hh5/public/apps/dask-optimiser/schedplugin.py:160: UserWarning: Attempted illegal binding: []\n",
+      "  warn(f\"Attempted illegal binding: {(sorted(list(self.slots_available - taken_slots))[:self.worker.state.nthreads])}\")\n",
+      "/g/data/hh5/public/apps/dask-optimiser/schedplugin.py:160: UserWarning: Attempted illegal binding: []\n",
+      "  warn(f\"Attempted illegal binding: {(sorted(list(self.slots_available - taken_slots))[:self.worker.state.nthreads])}\")\n",
+      "/g/data/hh5/public/apps/dask-optimiser/schedplugin.py:160: UserWarning: Attempted illegal binding: []\n",
+      "  warn(f\"Attempted illegal binding: {(sorted(list(self.slots_available - taken_slots))[:self.worker.state.nthreads])}\")\n"
+     ]
+    }
+   ],
+   "source": [
+    "client=Client()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "95f27779-0807-44f8-9807-61305c3f98b3",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "    <div style=\"width: 24px; height: 24px; background-color: #e1e1e1; border: 3px solid #9D9D9D; border-radius: 5px; position: absolute;\"> </div>\n",
+       "    <div style=\"margin-left: 48px;\">\n",
+       "        <h3 style=\"margin-bottom: 0px;\">Client</h3>\n",
+       "        <p style=\"color: #9D9D9D; margin-bottom: 0px;\">Client-967d2a8d-216a-11ef-b858-000007affe80</p>\n",
+       "        <table style=\"width: 100%; text-align: left;\">\n",
+       "\n",
+       "        <tr>\n",
+       "        \n",
+       "            <td style=\"text-align: left;\"><strong>Connection method:</strong> Cluster object</td>\n",
+       "            <td style=\"text-align: left;\"><strong>Cluster type:</strong> distributed.LocalCluster</td>\n",
+       "        \n",
+       "        </tr>\n",
+       "\n",
+       "        \n",
+       "            <tr>\n",
+       "                <td style=\"text-align: left;\">\n",
+       "                    <strong>Dashboard: </strong> <a href=\"/node/gadi-cpu-spr-0218.gadi.nci.org.au/13627/proxy/37389/status\" target=\"_blank\">/node/gadi-cpu-spr-0218.gadi.nci.org.au/13627/proxy/37389/status</a>\n",
+       "                </td>\n",
+       "                <td style=\"text-align: left;\"></td>\n",
+       "            </tr>\n",
+       "        \n",
+       "\n",
+       "        </table>\n",
+       "\n",
+       "        \n",
+       "            <button style=\"margin-bottom: 12px;\" data-commandlinker-command=\"dask:populate-and-launch-layout\" data-commandlinker-args='{\"url\": \"/node/gadi-cpu-spr-0218.gadi.nci.org.au/13627/proxy/37389/status\" }'>\n",
+       "                Launch dashboard in JupyterLab\n",
+       "            </button>\n",
+       "        \n",
+       "\n",
+       "        \n",
+       "            <details>\n",
+       "            <summary style=\"margin-bottom: 20px;\"><h3 style=\"display: inline;\">Cluster Info</h3></summary>\n",
+       "            <div class=\"jp-RenderedHTMLCommon jp-RenderedHTML jp-mod-trusted jp-OutputArea-output\">\n",
+       "    <div style=\"width: 24px; height: 24px; background-color: #e1e1e1; border: 3px solid #9D9D9D; border-radius: 5px; position: absolute;\">\n",
+       "    </div>\n",
+       "    <div style=\"margin-left: 48px;\">\n",
+       "        <h3 style=\"margin-bottom: 0px; margin-top: 0px;\">LocalCluster</h3>\n",
+       "        <p style=\"color: #9D9D9D; margin-bottom: 0px;\">b6cb1c90</p>\n",
+       "        <table style=\"width: 100%; text-align: left;\">\n",
+       "            <tr>\n",
+       "                <td style=\"text-align: left;\">\n",
+       "                    <strong>Dashboard:</strong> <a href=\"/node/gadi-cpu-spr-0218.gadi.nci.org.au/13627/proxy/37389/status\" target=\"_blank\">/node/gadi-cpu-spr-0218.gadi.nci.org.au/13627/proxy/37389/status</a>\n",
+       "                </td>\n",
+       "                <td style=\"text-align: left;\">\n",
+       "                    <strong>Workers:</strong> 4\n",
+       "                </td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                <td style=\"text-align: left;\">\n",
+       "                    <strong>Total threads:</strong> 4\n",
+       "                </td>\n",
+       "                <td style=\"text-align: left;\">\n",
+       "                    <strong>Total memory:</strong> 0 B\n",
+       "                </td>\n",
+       "            </tr>\n",
+       "            \n",
+       "            <tr>\n",
+       "    <td style=\"text-align: left;\"><strong>Status:</strong> running</td>\n",
+       "    <td style=\"text-align: left;\"><strong>Using processes:</strong> True</td>\n",
+       "</tr>\n",
+       "\n",
+       "            \n",
+       "        </table>\n",
+       "\n",
+       "        <details>\n",
+       "            <summary style=\"margin-bottom: 20px;\">\n",
+       "                <h3 style=\"display: inline;\">Scheduler Info</h3>\n",
+       "            </summary>\n",
+       "\n",
+       "            <div style=\"\">\n",
+       "    <div>\n",
+       "        <div style=\"width: 24px; height: 24px; background-color: #FFF7E5; border: 3px solid #FF6132; border-radius: 5px; position: absolute;\"> </div>\n",
+       "        <div style=\"margin-left: 48px;\">\n",
+       "            <h3 style=\"margin-bottom: 0px;\">Scheduler</h3>\n",
+       "            <p style=\"color: #9D9D9D; margin-bottom: 0px;\">Scheduler-121cf7f7-38f5-4b1f-9e25-ba7c2f564c34</p>\n",
+       "            <table style=\"width: 100%; text-align: left;\">\n",
+       "                <tr>\n",
+       "                    <td style=\"text-align: left;\">\n",
+       "                        <strong>Comm:</strong> tcp://127.0.0.1:42913\n",
+       "                    </td>\n",
+       "                    <td style=\"text-align: left;\">\n",
+       "                        <strong>Workers:</strong> 4\n",
+       "                    </td>\n",
+       "                </tr>\n",
+       "                <tr>\n",
+       "                    <td style=\"text-align: left;\">\n",
+       "                        <strong>Dashboard:</strong> <a href=\"/node/gadi-cpu-spr-0218.gadi.nci.org.au/13627/proxy/37389/status\" target=\"_blank\">/node/gadi-cpu-spr-0218.gadi.nci.org.au/13627/proxy/37389/status</a>\n",
+       "                    </td>\n",
+       "                    <td style=\"text-align: left;\">\n",
+       "                        <strong>Total threads:</strong> 4\n",
+       "                    </td>\n",
+       "                </tr>\n",
+       "                <tr>\n",
+       "                    <td style=\"text-align: left;\">\n",
+       "                        <strong>Started:</strong> Just now\n",
+       "                    </td>\n",
+       "                    <td style=\"text-align: left;\">\n",
+       "                        <strong>Total memory:</strong> 0 B\n",
+       "                    </td>\n",
+       "                </tr>\n",
+       "            </table>\n",
+       "        </div>\n",
+       "    </div>\n",
+       "\n",
+       "    <details style=\"margin-left: 48px;\">\n",
+       "        <summary style=\"margin-bottom: 20px;\">\n",
+       "            <h3 style=\"display: inline;\">Workers</h3>\n",
+       "        </summary>\n",
+       "\n",
+       "        \n",
+       "        <div style=\"margin-bottom: 20px;\">\n",
+       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
+       "            <div style=\"margin-left: 48px;\">\n",
+       "            <details>\n",
+       "                <summary>\n",
+       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 0</h4>\n",
+       "                </summary>\n",
+       "                <table style=\"width: 100%; text-align: left;\">\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Comm: </strong> tcp://127.0.0.1:41847\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Total threads: </strong> 1\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Dashboard: </strong> <a href=\"/node/gadi-cpu-spr-0218.gadi.nci.org.au/13627/proxy/33621/status\" target=\"_blank\">/node/gadi-cpu-spr-0218.gadi.nci.org.au/13627/proxy/33621/status</a>\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Memory: </strong> 0 B\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Nanny: </strong> tcp://127.0.0.1:40577\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\"></td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
+       "                            <strong>Local directory: </strong> /jobfs/117041814.gadi-pbs/dask-scratch-space/worker-51zs6anx\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                </table>\n",
+       "            </details>\n",
+       "            </div>\n",
+       "        </div>\n",
+       "        \n",
+       "        <div style=\"margin-bottom: 20px;\">\n",
+       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
+       "            <div style=\"margin-left: 48px;\">\n",
+       "            <details>\n",
+       "                <summary>\n",
+       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 1</h4>\n",
+       "                </summary>\n",
+       "                <table style=\"width: 100%; text-align: left;\">\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Comm: </strong> tcp://127.0.0.1:36723\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Total threads: </strong> 1\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Dashboard: </strong> <a href=\"/node/gadi-cpu-spr-0218.gadi.nci.org.au/13627/proxy/33947/status\" target=\"_blank\">/node/gadi-cpu-spr-0218.gadi.nci.org.au/13627/proxy/33947/status</a>\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Memory: </strong> 0 B\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Nanny: </strong> tcp://127.0.0.1:37665\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\"></td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
+       "                            <strong>Local directory: </strong> /jobfs/117041814.gadi-pbs/dask-scratch-space/worker-i6bhti7j\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                </table>\n",
+       "            </details>\n",
+       "            </div>\n",
+       "        </div>\n",
+       "        \n",
+       "        <div style=\"margin-bottom: 20px;\">\n",
+       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
+       "            <div style=\"margin-left: 48px;\">\n",
+       "            <details>\n",
+       "                <summary>\n",
+       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 2</h4>\n",
+       "                </summary>\n",
+       "                <table style=\"width: 100%; text-align: left;\">\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Comm: </strong> tcp://127.0.0.1:45801\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Total threads: </strong> 1\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Dashboard: </strong> <a href=\"/node/gadi-cpu-spr-0218.gadi.nci.org.au/13627/proxy/33645/status\" target=\"_blank\">/node/gadi-cpu-spr-0218.gadi.nci.org.au/13627/proxy/33645/status</a>\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Memory: </strong> 0 B\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Nanny: </strong> tcp://127.0.0.1:35097\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\"></td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
+       "                            <strong>Local directory: </strong> /jobfs/117041814.gadi-pbs/dask-scratch-space/worker-aabzzg64\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                </table>\n",
+       "            </details>\n",
+       "            </div>\n",
+       "        </div>\n",
+       "        \n",
+       "        <div style=\"margin-bottom: 20px;\">\n",
+       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
+       "            <div style=\"margin-left: 48px;\">\n",
+       "            <details>\n",
+       "                <summary>\n",
+       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 3</h4>\n",
+       "                </summary>\n",
+       "                <table style=\"width: 100%; text-align: left;\">\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Comm: </strong> tcp://127.0.0.1:39321\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Total threads: </strong> 1\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Dashboard: </strong> <a href=\"/node/gadi-cpu-spr-0218.gadi.nci.org.au/13627/proxy/46389/status\" target=\"_blank\">/node/gadi-cpu-spr-0218.gadi.nci.org.au/13627/proxy/46389/status</a>\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Memory: </strong> 0 B\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Nanny: </strong> tcp://127.0.0.1:35941\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\"></td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
+       "                            <strong>Local directory: </strong> /jobfs/117041814.gadi-pbs/dask-scratch-space/worker-ursgrl9a\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                </table>\n",
+       "            </details>\n",
+       "            </div>\n",
+       "        </div>\n",
+       "        \n",
+       "\n",
+       "    </details>\n",
+       "</div>\n",
+       "\n",
+       "        </details>\n",
+       "    </div>\n",
+       "</div>\n",
+       "            </details>\n",
+       "        \n",
+       "\n",
+       "    </div>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "<Client: 'tcp://127.0.0.1:42913' processes=4 threads=4, memory=19.00 GiB>"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "client"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "742dd8bd-4200-4388-8a0a-8c88e07337c5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ds = xr.open_mfdataset(flist,parallel=True,preprocess=lambda x: x['fld_s04i201'] + x['fld_s04i202'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "id": "dcd5c938-3833-4cd6-b40c-18ed2796aa84",
+   "metadata": {},
+   "outputs": [
+    {
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+       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
+       " *\n",
+       " */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
+       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
+       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
+       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
+       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
+       "  --xr-background-color: var(--jp-layout-color0, white);\n",
+       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
+       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
+       "}\n",
+       "\n",
+       "html[theme=dark],\n",
+       "body[data-theme=dark],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
+       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
+       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
+       "  --xr-border-color: #1F1F1F;\n",
+       "  --xr-disabled-color: #515151;\n",
+       "  --xr-background-color: #111111;\n",
+       "  --xr-background-color-row-even: #111111;\n",
+       "  --xr-background-color-row-odd: #313131;\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: '►';\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: '▼';\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: '(';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: ')';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: ',';\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (time_0: 720, lat: 2120, lon: 2600)&gt; Size: 16GB\n",
+       "dask.array&lt;concatenate, shape=(720, 2120, 2600), dtype=float32, chunksize=(2, 1060, 1300), chunktype=numpy.ndarray&gt;\n",
+       "Coordinates:\n",
+       "  * lat                       (lat) float64 17kB -48.79 -48.77 ... -6.852 -6.832\n",
+       "  * lon                       (lon) float64 21kB 114.3 114.3 ... 165.7 165.7\n",
+       "    theta_level_height        float64 8B 5.0\n",
+       "    model_theta_level_number  int32 4B 1\n",
+       "    sigma_theta               float64 8B 0.9994\n",
+       "    height                    float64 8B 10.0\n",
+       "    height_0                  float64 8B 1.5\n",
+       "  * time_0                    (time_0) datetime64[ns] 6kB 2016-06-03T00:05:00...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>time_0</span>: 720</li><li><span class='xr-has-index'>lat</span>: 2120</li><li><span class='xr-has-index'>lon</span>: 2600</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-cf665875-a905-43b1-b6d7-1d30d50d49db' class='xr-array-in' type='checkbox' checked><label for='section-cf665875-a905-43b1-b6d7-1d30d50d49db' 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>dask.array&lt;chunksize=(2, 1060, 1300), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 14.78 GiB </td>\n",
+       "                        <td> 10.51 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (720, 2120, 2600) </td>\n",
+       "                        <td> (2, 1060, 1300) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1440 chunks in 601 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"205\" height=\"173\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
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+       "  <line x1=\"10\" y1=\"0\" x2=\"35\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"70\" y1=\"0\" x2=\"95\" y2=\"25\" />\n",
+       "  <line x1=\"130\" y1=\"0\" x2=\"155\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"10.0,0.0 130.0,0.0 155.45295131656394,25.45295131656395 35.452951316563954,25.45295131656395\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"35\" y1=\"25\" x2=\"155\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"35\" y1=\"74\" x2=\"155\" y2=\"74\" />\n",
+       "  <line x1=\"35\" y1=\"123\" x2=\"155\" y2=\"123\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"35\" y1=\"25\" x2=\"35\" y2=\"123\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"95\" y1=\"25\" x2=\"95\" y2=\"123\" />\n",
+       "  <line x1=\"155\" y1=\"25\" x2=\"155\" y2=\"123\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"35.452951316563954,25.45295131656395 155.45295131656394,25.45295131656395 155.45295131656394,123.29910516271781 35.452951316563954,123.29910516271781\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"95.452951\" y=\"143.299105\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2600</text>\n",
+       "  <text x=\"175.452951\" y=\"74.376028\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,175.452951,74.376028)\">2120</text>\n",
+       "  <text x=\"12.726476\" y=\"130.572630\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,12.726476,130.572630)\">720</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></div></li><li class='xr-section-item'><input id='section-c92ba684-02bd-4224-a835-ab4e19b74b5a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c92ba684-02bd-4224-a835-ab4e19b74b5a' class='xr-section-summary' >Coordinates: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-48.79 -48.77 ... -6.852 -6.832</div><input id='attrs-153420fb-57ca-4531-b0a8-07c42951286a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-153420fb-57ca-4531-b0a8-07c42951286a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-835ed24c-ff38-4cf6-9be7-db4ed86df730' class='xr-var-data-in' type='checkbox'><label for='data-835ed24c-ff38-4cf6-9be7-db4ed86df730' 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>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-48.787998, -48.7682  , -48.748398, ...,  -6.871399,  -6.851597,\n",
+       "        -6.831799])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>114.3 114.3 114.3 ... 165.7 165.7</div><input id='attrs-06bac205-10cc-4a27-bb88-2bebaef8faa7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-06bac205-10cc-4a27-bb88-2bebaef8faa7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-93ff4b94-f58f-431c-b1eb-137149c83f66' class='xr-var-data-in' type='checkbox'><label for='data-93ff4b94-f58f-431c-b1eb-137149c83f66' 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>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([114.260002, 114.2798  , 114.299599, ..., 165.680603, 165.700409,\n",
+       "       165.7202  ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>theta_level_height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.0</div><input id='attrs-b6aad06d-8e19-4511-b3fd-60884a28a96b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b6aad06d-8e19-4511-b3fd-60884a28a96b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5a506328-d983-402f-9197-42a99efca02f' class='xr-var-data-in' type='checkbox'><label for='data-5a506328-d983-402f-9197-42a99efca02f' 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>bounds :</span></dt><dd>theta_level_height_bnds</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>level_height</dd><dt><span>positive :</span></dt><dd>up</dd></dl></div><div class='xr-var-data'><pre>array(5.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>model_theta_level_number</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1</div><input id='attrs-76abe524-1216-43b7-a19c-959b90bfa712' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-76abe524-1216-43b7-a19c-959b90bfa712' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d5c4eabe-d042-44cd-a2dc-b88ea1b025fb' class='xr-var-data-in' type='checkbox'><label for='data-d5c4eabe-d042-44cd-a2dc-b88ea1b025fb' 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>1</dd><dt><span>standard_name :</span></dt><dd>model_level_number</dd><dt><span>positive :</span></dt><dd>up</dd></dl></div><div class='xr-var-data'><pre>array(1, dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sigma_theta</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.9994</div><input id='attrs-21e2b470-9b06-4e7b-88bf-b7b6d53aef70' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-21e2b470-9b06-4e7b-88bf-b7b6d53aef70' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-87b30340-bd7b-490e-b15f-7f14a468808e' class='xr-var-data-in' type='checkbox'><label for='data-87b30340-bd7b-490e-b15f-7f14a468808e' 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>bounds :</span></dt><dd>sigma_theta_bnds</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>sigma</dd></dl></div><div class='xr-var-data'><pre>array(0.99942381)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>10.0</div><input id='attrs-b3664949-2d8a-467c-8ddc-d9a9d9e9e2b4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b3664949-2d8a-467c-8ddc-d9a9d9e9e2b4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2731c8b2-aa87-4486-9894-6f0c54177157' class='xr-var-data-in' type='checkbox'><label for='data-2731c8b2-aa87-4486-9894-6f0c54177157' 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>m</dd><dt><span>standard_name :</span></dt><dd>height</dd><dt><span>positive :</span></dt><dd>up</dd></dl></div><div class='xr-var-data'><pre>array(10.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>height_0</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.5</div><input id='attrs-e448c972-3e9d-47e4-b9f0-448ab9dab4c5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e448c972-3e9d-47e4-b9f0-448ab9dab4c5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-12d11685-0bfa-4961-a7c9-534b934f3620' class='xr-var-data-in' type='checkbox'><label for='data-12d11685-0bfa-4961-a7c9-534b934f3620' 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>m</dd><dt><span>standard_name :</span></dt><dd>height</dd><dt><span>positive :</span></dt><dd>up</dd></dl></div><div class='xr-var-data'><pre>array(1.5)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time_0</span></div><div class='xr-var-dims'>(time_0)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2016-06-03T00:05:00 ... 2016-06-...</div><input id='attrs-b7877815-d8cf-4c12-b6b5-8b4f6dc8a146' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b7877815-d8cf-4c12-b6b5-8b4f6dc8a146' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f8126190-aa25-46c0-bf01-47ef72c7e2a2' class='xr-var-data-in' type='checkbox'><label for='data-f8126190-aa25-46c0-bf01-47ef72c7e2a2' 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>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_0_bnds</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2016-06-03T00:05:00.000000000&#x27;, &#x27;2016-06-03T00:15:00.000000000&#x27;,\n",
+       "       &#x27;2016-06-03T00:24:59.999999744&#x27;, ..., &#x27;2016-06-07T23:35:00.000000256&#x27;,\n",
+       "       &#x27;2016-06-07T23:45:00.000000000&#x27;, &#x27;2016-06-07T23:55:00.000000000&#x27;],\n",
+       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-02184cb9-000b-4367-92d1-81d72e0456d3' class='xr-section-summary-in' type='checkbox'  ><label for='section-02184cb9-000b-4367-92d1-81d72e0456d3' class='xr-section-summary' >Indexes: <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-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-61ad30a0-f622-4753-bd43-732c13319de2' class='xr-index-data-in' type='checkbox'/><label for='index-61ad30a0-f622-4753-bd43-732c13319de2' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ -48.78799819946289,   -48.7681999206543,  -48.74839782714844,\n",
+       "       -48.728599548339844, -48.708797454833984,  -48.68899917602539,\n",
+       "        -48.66919708251953,  -48.64939880371094,  -48.62959671020508,\n",
+       "       -48.609798431396484,\n",
+       "       ...\n",
+       "        -7.009998321533203,  -6.990200042724609,   -6.97039794921875,\n",
+       "        -6.950599670410156,  -6.930797576904297,  -6.910999298095703,\n",
+       "        -6.891197204589844,   -6.87139892578125,  -6.851596832275391,\n",
+       "        -6.831798553466797],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=2120))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-813ae206-c50d-444d-8051-051f38bfc886' class='xr-index-data-in' type='checkbox'/><label for='index-813ae206-c50d-444d-8051-051f38bfc886' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([114.26000213623047, 114.27980041503906, 114.29959869384766,\n",
+       "       114.31940460205078, 114.33920288085938, 114.35900115966797,\n",
+       "       114.37879943847656, 114.39860534667969, 114.41840362548828,\n",
+       "       114.43820190429688,\n",
+       "       ...\n",
+       "       165.54200744628906, 165.56179809570312, 165.58160400390625,\n",
+       "       165.60140991210938, 165.62120056152344, 165.64100646972656,\n",
+       "       165.66079711914062, 165.68060302734375, 165.70040893554688,\n",
+       "       165.72019958496094],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=2600))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time_0</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-fa31f7cf-c4a6-4c8e-837a-503bb44f0959' class='xr-index-data-in' type='checkbox'/><label for='index-fa31f7cf-c4a6-4c8e-837a-503bb44f0959' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([          &#x27;2016-06-03 00:05:00&#x27;,\n",
+       "                         &#x27;2016-06-03 00:15:00&#x27;,\n",
+       "               &#x27;2016-06-03 00:24:59.999999744&#x27;,\n",
+       "               &#x27;2016-06-03 00:35:00.000000256&#x27;,\n",
+       "                         &#x27;2016-06-03 00:45:00&#x27;,\n",
+       "               &#x27;2016-06-03 00:54:59.999999744&#x27;,\n",
+       "               &#x27;2016-06-03 01:05:00.000000256&#x27;,\n",
+       "                         &#x27;2016-06-03 01:15:00&#x27;,\n",
+       "                         &#x27;2016-06-03 01:25:00&#x27;,\n",
+       "                         &#x27;2016-06-03 01:35:00&#x27;,\n",
+       "               ...\n",
+       "                         &#x27;2016-06-07 22:25:00&#x27;,\n",
+       "                         &#x27;2016-06-07 22:35:00&#x27;,\n",
+       "                         &#x27;2016-06-07 22:45:00&#x27;,\n",
+       "               &#x27;2016-06-07 22:54:59.999999744&#x27;,\n",
+       "               &#x27;2016-06-07 23:05:00.000000256&#x27;,\n",
+       "                         &#x27;2016-06-07 23:15:00&#x27;,\n",
+       "               &#x27;2016-06-07 23:24:59.999999744&#x27;,\n",
+       "               &#x27;2016-06-07 23:35:00.000000256&#x27;,\n",
+       "                         &#x27;2016-06-07 23:45:00&#x27;,\n",
+       "                         &#x27;2016-06-07 23:55:00&#x27;],\n",
+       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time_0&#x27;, length=720, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6e529e8a-3832-4209-bc72-4a51f1b13161' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6e529e8a-3832-4209-bc72-4a51f1b13161' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.DataArray (time_0: 720, lat: 2120, lon: 2600)> Size: 16GB\n",
+       "dask.array<concatenate, shape=(720, 2120, 2600), dtype=float32, chunksize=(2, 1060, 1300), chunktype=numpy.ndarray>\n",
+       "Coordinates:\n",
+       "  * lat                       (lat) float64 17kB -48.79 -48.77 ... -6.852 -6.832\n",
+       "  * lon                       (lon) float64 21kB 114.3 114.3 ... 165.7 165.7\n",
+       "    theta_level_height        float64 8B 5.0\n",
+       "    model_theta_level_number  int32 4B 1\n",
+       "    sigma_theta               float64 8B 0.9994\n",
+       "    height                    float64 8B 10.0\n",
+       "    height_0                  float64 8B 1.5\n",
+       "  * time_0                    (time_0) datetime64[ns] 6kB 2016-06-03T00:05:00..."
+      ]
+     },
+     "execution_count": 36,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "be638e58-904f-46a4-9dc6-e4d7e2628af1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "da_fin=ds.resample(time_0='1D',offset='9h').sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "id": "7efe72d6-f1f7-4143-ad5f-b375a5a7a97a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x14f0440f26e0>"
+      ]
+     },
+     "execution_count": 35,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "(ds.sel(time_0=slice(pandas.Timestamp('2016-06-03T09:00:00'),pandas.Timestamp('2016-06-04T09:00:00'))).sum(dim='time_0') - da_fin[1]).plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "ad0d86f7-17f6-43f6-b4e8-a9c0d5b71ebc",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x14f04382d2a0>"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "da_fin[0].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "72a3f353-9e54-4aad-b15a-0f6e03bbe4ea",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x14f00818b760>"
+      ]
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "da_fin[1].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "3a770abc-5d26-44a6-a652-31c118552b47",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x14f0a0847b50>"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "da_fin[2].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "aafed708-7fa7-48ee-b39d-1c4c04f4b7fc",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x14f0490af880>"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "da_fin[3].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "4c717e6f-f783-4b4b-8be6-f55919398d08",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x14f0440855a0>"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "da_fin[4].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "fdbc19ed-71e7-44e7-af6c-887c67c001f5",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "<defs>\n",
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+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
+       " *\n",
+       " */\n",
+       "\n",
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+       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
+       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
+       "  --xr-background-color: var(--jp-layout-color0, white);\n",
+       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
+       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
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+       "\n",
+       "html[theme=dark],\n",
+       "body[data-theme=dark],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
+       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
+       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
+       "  --xr-border-color: #1F1F1F;\n",
+       "  --xr-disabled-color: #515151;\n",
+       "  --xr-background-color: #111111;\n",
+       "  --xr-background-color-row-even: #111111;\n",
+       "  --xr-background-color-row-odd: #313131;\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
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+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: '►';\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: '▼';\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: '(';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: ')';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: ',';\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (time_0: 6, lat: 2120, lon: 2600)&gt; Size: 132MB\n",
+       "dask.array&lt;transpose, shape=(6, 2120, 2600), dtype=float32, chunksize=(1, 1060, 1300), chunktype=numpy.ndarray&gt;\n",
+       "Coordinates:\n",
+       "  * lat                       (lat) float64 17kB -48.79 -48.77 ... -6.852 -6.832\n",
+       "  * lon                       (lon) float64 21kB 114.3 114.3 ... 165.7 165.7\n",
+       "    theta_level_height        float64 8B 5.0\n",
+       "    model_theta_level_number  int32 4B 1\n",
+       "    sigma_theta               float64 8B 0.9994\n",
+       "    height                    float64 8B 10.0\n",
+       "    height_0                  float64 8B 1.5\n",
+       "  * time_0                    (time_0) datetime64[ns] 48B 2016-06-02T09:00:00...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>time_0</span>: 6</li><li><span class='xr-has-index'>lat</span>: 2120</li><li><span class='xr-has-index'>lon</span>: 2600</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-4e63b67f-eea8-4a4c-891b-1716c2f825ff' class='xr-array-in' type='checkbox' checked><label for='section-4e63b67f-eea8-4a4c-891b-1716c2f825ff' 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>dask.array&lt;chunksize=(1, 1060, 1300), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 126.16 MiB </td>\n",
+       "                        <td> 5.26 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (6, 2120, 2600) </td>\n",
+       "                        <td> (1, 1060, 1300) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 24 chunks in 635 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"194\" height=\"162\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"24\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"10\" y1=\"48\" x2=\"24\" y2=\"63\" />\n",
+       "  <line x1=\"10\" y1=\"97\" x2=\"24\" y2=\"112\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"97\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"12\" y1=\"2\" x2=\"12\" y2=\"100\" />\n",
+       "  <line x1=\"14\" y1=\"4\" x2=\"14\" y2=\"102\" />\n",
+       "  <line x1=\"17\" y1=\"7\" x2=\"17\" y2=\"105\" />\n",
+       "  <line x1=\"19\" y1=\"9\" x2=\"19\" y2=\"107\" />\n",
+       "  <line x1=\"22\" y1=\"12\" x2=\"22\" y2=\"110\" />\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"112\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"10.0,0.0 24.9485979497544,14.948597949754403 24.9485979497544,112.79475179590825 10.0,97.84615384615385\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"130\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"12\" y1=\"2\" x2=\"132\" y2=\"2\" />\n",
+       "  <line x1=\"14\" y1=\"4\" x2=\"134\" y2=\"4\" />\n",
+       "  <line x1=\"17\" y1=\"7\" x2=\"137\" y2=\"7\" />\n",
+       "  <line x1=\"19\" y1=\"9\" x2=\"139\" y2=\"9\" />\n",
+       "  <line x1=\"22\" y1=\"12\" x2=\"142\" y2=\"12\" />\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"144\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"24\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"70\" y1=\"0\" x2=\"84\" y2=\"14\" />\n",
+       "  <line x1=\"130\" y1=\"0\" x2=\"144\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"10.0,0.0 130.0,0.0 144.9485979497544,14.948597949754403 24.9485979497544,14.948597949754403\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"144\" y2=\"14\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"24\" y1=\"63\" x2=\"144\" y2=\"63\" />\n",
+       "  <line x1=\"24\" y1=\"112\" x2=\"144\" y2=\"112\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"112\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"84\" y1=\"14\" x2=\"84\" y2=\"112\" />\n",
+       "  <line x1=\"144\" y1=\"14\" x2=\"144\" y2=\"112\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"24.9485979497544,14.948597949754403 144.9485979497544,14.948597949754403 144.9485979497544,112.79475179590825 24.9485979497544,112.79475179590825\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"84.948598\" y=\"132.794752\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2600</text>\n",
+       "  <text x=\"164.948598\" y=\"63.871675\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,164.948598,63.871675)\">2120</text>\n",
+       "  <text x=\"7.474299\" y=\"125.320453\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,7.474299,125.320453)\">6</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></div></li><li class='xr-section-item'><input id='section-1e906b48-1a37-4fa8-bfe7-a63cc2b9e2ed' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1e906b48-1a37-4fa8-bfe7-a63cc2b9e2ed' class='xr-section-summary' >Coordinates: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-48.79 -48.77 ... -6.852 -6.832</div><input id='attrs-a982f179-90ba-4b5c-aef1-dac7fa593e4f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a982f179-90ba-4b5c-aef1-dac7fa593e4f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0054881f-2f69-4b85-b81d-9f62ae7e22e5' class='xr-var-data-in' type='checkbox'><label for='data-0054881f-2f69-4b85-b81d-9f62ae7e22e5' 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>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-48.787998, -48.7682  , -48.748398, ...,  -6.871399,  -6.851597,\n",
+       "        -6.831799])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>114.3 114.3 114.3 ... 165.7 165.7</div><input id='attrs-848bc66a-c2b5-4130-b518-aa837b80ab6d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-848bc66a-c2b5-4130-b518-aa837b80ab6d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eaab0649-eb91-4210-acf1-98fade5909b0' class='xr-var-data-in' type='checkbox'><label for='data-eaab0649-eb91-4210-acf1-98fade5909b0' 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>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([114.260002, 114.2798  , 114.299599, ..., 165.680603, 165.700409,\n",
+       "       165.7202  ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>theta_level_height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.0</div><input id='attrs-45a5b80a-4a8b-4146-bbab-6df46b00350b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-45a5b80a-4a8b-4146-bbab-6df46b00350b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-49237484-23e2-4393-91f2-2c24ea2a6351' class='xr-var-data-in' type='checkbox'><label for='data-49237484-23e2-4393-91f2-2c24ea2a6351' 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>bounds :</span></dt><dd>theta_level_height_bnds</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>level_height</dd><dt><span>positive :</span></dt><dd>up</dd></dl></div><div class='xr-var-data'><pre>array(5.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>model_theta_level_number</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1</div><input id='attrs-a7832881-d662-4fed-96fc-9802a2770ac2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a7832881-d662-4fed-96fc-9802a2770ac2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dea19c82-f31c-4db2-832c-646dc288e5cb' class='xr-var-data-in' type='checkbox'><label for='data-dea19c82-f31c-4db2-832c-646dc288e5cb' 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>1</dd><dt><span>standard_name :</span></dt><dd>model_level_number</dd><dt><span>positive :</span></dt><dd>up</dd></dl></div><div class='xr-var-data'><pre>array(1, dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sigma_theta</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.9994</div><input id='attrs-cf504213-287b-4668-befa-8845b5707426' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cf504213-287b-4668-befa-8845b5707426' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7a7928ad-291a-4b48-9faf-cd6203a12d23' class='xr-var-data-in' type='checkbox'><label for='data-7a7928ad-291a-4b48-9faf-cd6203a12d23' 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>bounds :</span></dt><dd>sigma_theta_bnds</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>sigma</dd></dl></div><div class='xr-var-data'><pre>array(0.99942381)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>10.0</div><input id='attrs-ab364083-9dd3-491c-bd5e-80c58219d7e9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ab364083-9dd3-491c-bd5e-80c58219d7e9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eedbbc23-496d-4c7f-8b8e-2a13cf576636' class='xr-var-data-in' type='checkbox'><label for='data-eedbbc23-496d-4c7f-8b8e-2a13cf576636' 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>m</dd><dt><span>standard_name :</span></dt><dd>height</dd><dt><span>positive :</span></dt><dd>up</dd></dl></div><div class='xr-var-data'><pre>array(10.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>height_0</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.5</div><input id='attrs-837739ff-10c9-4f38-93cc-5c2bfbca083f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-837739ff-10c9-4f38-93cc-5c2bfbca083f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-13f6ae6d-44c1-4e68-afd1-1d13227d94f9' class='xr-var-data-in' type='checkbox'><label for='data-13f6ae6d-44c1-4e68-afd1-1d13227d94f9' 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>m</dd><dt><span>standard_name :</span></dt><dd>height</dd><dt><span>positive :</span></dt><dd>up</dd></dl></div><div class='xr-var-data'><pre>array(1.5)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time_0</span></div><div class='xr-var-dims'>(time_0)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2016-06-02T09:00:00 ... 2016-06-...</div><input id='attrs-3fd18f50-d850-448c-a4d4-59869ac061e8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3fd18f50-d850-448c-a4d4-59869ac061e8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ad1390ba-c235-42ac-a854-26826fbc3cf8' class='xr-var-data-in' type='checkbox'><label for='data-ad1390ba-c235-42ac-a854-26826fbc3cf8' 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([&#x27;2016-06-02T09:00:00.000000000&#x27;, &#x27;2016-06-03T09:00:00.000000000&#x27;,\n",
+       "       &#x27;2016-06-04T09:00:00.000000000&#x27;, &#x27;2016-06-05T09:00:00.000000000&#x27;,\n",
+       "       &#x27;2016-06-06T09:00:00.000000000&#x27;, &#x27;2016-06-07T09:00:00.000000000&#x27;],\n",
+       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fea31217-8191-48b9-a5fb-1475637aa229' class='xr-section-summary-in' type='checkbox'  ><label for='section-fea31217-8191-48b9-a5fb-1475637aa229' class='xr-section-summary' >Indexes: <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-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-2388c901-1df9-4fec-b7db-e5a15ecee3e0' class='xr-index-data-in' type='checkbox'/><label for='index-2388c901-1df9-4fec-b7db-e5a15ecee3e0' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ -48.78799819946289,   -48.7681999206543,  -48.74839782714844,\n",
+       "       -48.728599548339844, -48.708797454833984,  -48.68899917602539,\n",
+       "        -48.66919708251953,  -48.64939880371094,  -48.62959671020508,\n",
+       "       -48.609798431396484,\n",
+       "       ...\n",
+       "        -7.009998321533203,  -6.990200042724609,   -6.97039794921875,\n",
+       "        -6.950599670410156,  -6.930797576904297,  -6.910999298095703,\n",
+       "        -6.891197204589844,   -6.87139892578125,  -6.851596832275391,\n",
+       "        -6.831798553466797],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=2120))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-26ecd1ad-4b68-429e-ad3f-5b733d157d3f' class='xr-index-data-in' type='checkbox'/><label for='index-26ecd1ad-4b68-429e-ad3f-5b733d157d3f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([114.26000213623047, 114.27980041503906, 114.29959869384766,\n",
+       "       114.31940460205078, 114.33920288085938, 114.35900115966797,\n",
+       "       114.37879943847656, 114.39860534667969, 114.41840362548828,\n",
+       "       114.43820190429688,\n",
+       "       ...\n",
+       "       165.54200744628906, 165.56179809570312, 165.58160400390625,\n",
+       "       165.60140991210938, 165.62120056152344, 165.64100646972656,\n",
+       "       165.66079711914062, 165.68060302734375, 165.70040893554688,\n",
+       "       165.72019958496094],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=2600))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time_0</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-87d1de0a-fb3b-4fa6-9518-aa4c28eb812a' class='xr-index-data-in' type='checkbox'/><label for='index-87d1de0a-fb3b-4fa6-9518-aa4c28eb812a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2016-06-02 09:00:00&#x27;, &#x27;2016-06-03 09:00:00&#x27;,\n",
+       "               &#x27;2016-06-04 09:00:00&#x27;, &#x27;2016-06-05 09:00:00&#x27;,\n",
+       "               &#x27;2016-06-06 09:00:00&#x27;, &#x27;2016-06-07 09:00:00&#x27;],\n",
+       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time_0&#x27;, freq=&#x27;D&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-bc48a251-9225-4791-9d8e-3def783f0606' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-bc48a251-9225-4791-9d8e-3def783f0606' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.DataArray (time_0: 6, lat: 2120, lon: 2600)> Size: 132MB\n",
+       "dask.array<transpose, shape=(6, 2120, 2600), dtype=float32, chunksize=(1, 1060, 1300), chunktype=numpy.ndarray>\n",
+       "Coordinates:\n",
+       "  * lat                       (lat) float64 17kB -48.79 -48.77 ... -6.852 -6.832\n",
+       "  * lon                       (lon) float64 21kB 114.3 114.3 ... 165.7 165.7\n",
+       "    theta_level_height        float64 8B 5.0\n",
+       "    model_theta_level_number  int32 4B 1\n",
+       "    sigma_theta               float64 8B 0.9994\n",
+       "    height                    float64 8B 10.0\n",
+       "    height_0                  float64 8B 1.5\n",
+       "  * time_0                    (time_0) datetime64[ns] 48B 2016-06-02T09:00:00..."
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "da_fin"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e8d389ab-8564-464c-ab6a-506b06e996a1",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python [conda env:analysis3-24.04]",
+   "language": "python",
+   "name": "conda-env-analysis3-24.04-py"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.14"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/Recipes/AUS2200_diagnotics.ipynb b/Recipes/AUS2200_diagnotics.ipynb
new file mode 100644
index 0000000..32263c4
--- /dev/null
+++ b/Recipes/AUS2200_diagnotics.ipynb
@@ -0,0 +1,170 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "d03a2ac1-54bc-428f-aa2e-45d4a7368262",
+   "metadata": {},
+   "source": [
+    "### Plot diagnostic quantities\n",
+    "\n",
+    "Uses the Unified Model's .pe0 files to plot diagnostic quantities on a per-timestep basis. Note that the UM's print level must be set to 'debug'."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "229befe2-5147-4d58-8118-6384151552d0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from matplotlib import pyplot as plt\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "1ebb58ee-6930-45a9-ae60-f392eed6c700",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "with open('/scratch/w40/dr4292/aus2200-instability-analysis/75sec/20220222T0000Z/aus2200_d0198_RA3_um_fcst_000/pe_output/umnsa.fort6.pe0000','r') as f:\n",
+    "    lines=[ i.strip() for i in f.readlines() ]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "cd74527b-8cf2-454a-8bc3-f865aea7a675",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "vals_avg=dict.fromkeys([l.split()[0] for l in lines if l.startswith('s_')])\n",
+    "vals_max=dict.fromkeys([l.split()[0] for l in lines if l.startswith('s_')])\n",
+    "vals_min=dict.fromkeys([l.split()[0] for l in lines if l.startswith('s_')])\n",
+    "for k in vals_avg:\n",
+    "    vals_avg[k]=[]\n",
+    "    vals_max[k]=[]\n",
+    "    vals_min[k]=[]\n",
+    "del(vals_avg['s_pdm'])\n",
+    "del(vals_min['s_pdm'])\n",
+    "del(vals_max['s_pdm'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "6940084e-971d-4547-a359-d8199391b175",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for l in lines:\n",
+    "    if l.startswith('s_'):\n",
+    "        l_arr=l.split()\n",
+    "        for k in vals_avg:\n",
+    "            if l_arr[0] == k:\n",
+    "                vals_min[k].append(float(l_arr[2]))\n",
+    "                vals_max[k].append(float(l_arr[3]))\n",
+    "                vals_avg[k].append(float(l_arr[4]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "cc730be9-ba63-4516-ad1b-3fa85597f798",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.legend.Legend at 0x14a32a415b20>"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig,ax=plt.subplots()\n",
+    "x=[ i for i,_ in enumerate(vals_min['s_u']) ]\n",
+    "for k,v in vals_max.items():\n",
+    "    ax.plot(x,v/np.average(v),label=k)\n",
+    "ax.legend()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "346bea9c-b31f-4a04-8c3d-1fa77fdd7235",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.legend.Legend at 0x14a32a45a760>"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig,ax=plt.subplots()\n",
+    "for k,v in vals_max.items():\n",
+    "    ax.plot(x,v,label=k)\n",
+    "ax.legend()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ae60b35c-799f-4e54-afba-c3f7ab6e7fb4",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python [conda env:analysis3-22.10]",
+   "language": "python",
+   "name": "conda-env-analysis3-22.10-py"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.15"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/Recipes/UpdateSST.ipynb b/Recipes/UpdateSST.ipynb
new file mode 100644
index 0000000..b314801
--- /dev/null
+++ b/Recipes/UpdateSST.ipynb
@@ -0,0 +1,1879 @@
+{
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+   "cell_type": "markdown",
+   "id": "032b441f-3c1f-47c4-aa3e-9604f3f9604f",
+   "metadata": {},
+   "source": [
+    "### Sea Surface Temperature Update\n",
+    "\n",
+    "Updates SSTs in model dump files during an AUS2200 run. Useful for creating runs in which SST evolves over time according to known historical data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "536e05d0-caab-42dc-be02-25dd5f1ca5e2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import iris\n",
+    "import mule\n",
+    "import xarray as xr\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "5dbb0ae7-2685-45e3-baf7-56817b2cae68",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dump_fn  = '/scratch/ly62/dr4292/cylc-run/u-cs142-20160603T0000-continuous-140E-evolvingSST/share/cycle/20160606T1800Z/aus2200/d0198/RA3/ics/umnsaa_da006'\n",
+    "dump_out = '/scratch/ly62/dr4292/cylc-run/u-cs142-20160603T0000-continuous-140E-evolvingSST/share/cycle/20160606T1800Z/aus2200/d0198/RA3/ics/umnsaa_da006_newsst'\n",
+    "era5_fn  = '/scratch/ly62/dr4292/cylc-run/u-cs142-20160603T0000-continuous-140E-evolvingSST/share/cycle/20160606T1800Z/ec/um/ec_cb006'"
+   ]
+  },
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+   "execution_count": 3,
+   "id": "4550de27-01d1-4b97-b171-f2397126dfb1",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/g/data/hh5/public/apps/cms_conda/envs/analysis3-24.01/lib/python3.10/site-packages/iris/fileformats/_ff.py:722: _WarnComboLoadingDefaulting: The stash code m01s00i060 is on a grid 22 which has not been explicitly handled by the fieldsfile loader. Assuming the data is on a P grid.\n",
+      "  warnings.warn(\n"
+     ]
+    }
+   ],
+   "source": [
+    "cubes = iris.load(dump_fn)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "e3270e2f-bc23-4ee4-9ea9-e3416809c008",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/g/data/hh5/public/apps/cms_conda/envs/analysis3-24.01/lib/python3.10/site-packages/iris/fileformats/_ff.py:722: _WarnComboLoadingDefaulting: The stash code m01s00i060 is on a grid 22 which has not been explicitly handled by the fieldsfile loader. Assuming the data is on a P grid.\n",
+      "  warnings.warn(\n"
+     ]
+    }
+   ],
+   "source": [
+    "era5 = iris.load(era5_fn)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "d2233fb7-da18-4507-afdb-70e3ce974465",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for f in cubes:\n",
+    "    s=f.attributes['STASH']\n",
+    "    if s.model==1 and s.section==0 and s.item == 24:\n",
+    "        um_sst = xr.DataArray.from_iris(f)\n",
+    "        break"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "908a171e-5ab5-479d-be31-f80ebd318aee",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for f in era5:\n",
+    "    s=f.attributes['STASH']\n",
+    "    if s.model==1 and s.section==0 and s.item == 24:\n",
+    "        era5_sst = xr.DataArray.from_iris(f)\n",
+    "        break"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "e93fe638-e98d-4e98-8a24-7a2a4f975a81",
+   "metadata": {},
+   "outputs": [
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+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;surface_temperature&#x27; (latitude: 2170, longitude: 2650)&gt; Size: 23MB\n",
+       "dask.array&lt;filled, shape=(2170, 2650), dtype=float32, chunksize=(2170, 2650), chunktype=numpy.ndarray&gt;\n",
+       "Coordinates:\n",
+       "  * latitude      (latitude) float32 9kB -49.28 -49.26 -49.24 ... -6.357 -6.337\n",
+       "  * longitude     (longitude) float32 11kB 113.8 113.8 113.8 ... 166.2 166.2\n",
+       "    pseudo_level  int64 8B ...\n",
+       "    realization   int64 8B ...\n",
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+       "Attributes:\n",
+       "    standard_name:  surface_temperature\n",
+       "    units:          K\n",
+       "    source:         Data from Met Office Unified Model\n",
+       "    um_version:     12.2\n",
+       "    STASH:          m01s00i024</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'surface_temperature'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>latitude</span>: 2170</li><li><span class='xr-has-index'>longitude</span>: 2650</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-e219efcb-fa81-49ef-b11b-2c2c7bfb8b02' class='xr-array-in' type='checkbox' checked><label for='section-e219efcb-fa81-49ef-b11b-2c2c7bfb8b02' 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>dask.array&lt;chunksize=(2170, 2650), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
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+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 21.94 MiB </td>\n",
+       "                        <td> 21.94 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (2170, 2650) </td>\n",
+       "                        <td> (2170, 2650) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 3 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"148\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"98\" x2=\"120\" y2=\"98\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"98\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"98\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,98.26415094339623 0.0,98.26415094339623\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"118.264151\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2650</text>\n",
+       "  <text x=\"140.000000\" y=\"49.132075\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,49.132075)\">2170</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></div></li><li class='xr-section-item'><input id='section-710aec52-7bb8-46b6-b58b-4ce847f0cf0c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-710aec52-7bb8-46b6-b58b-4ce847f0cf0c' class='xr-section-summary' >Coordinates: <span>(5)</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'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-49.28 -49.26 ... -6.357 -6.337</div><input id='attrs-abce6acf-6650-42ba-8d68-e82e2aaf0096' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-abce6acf-6650-42ba-8d68-e82e2aaf0096' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ac0e11ab-5643-4419-9bc5-893395a3ac1b' class='xr-var-data-in' type='checkbox'><label for='data-ac0e11ab-5643-4419-9bc5-893395a3ac1b' 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>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees</dd></dl></div><div class='xr-var-data'><pre>array([-49.283   , -49.263203, -49.2434  , ...,  -6.3764  ,  -6.356602,\n",
+       "        -6.3368  ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>113.8 113.8 113.8 ... 166.2 166.2</div><input id='attrs-e645cccc-2397-4886-8007-dac115749d90' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e645cccc-2397-4886-8007-dac115749d90' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f9fb14f2-1c7d-4c29-8823-b73dc83929df' class='xr-var-data-in' type='checkbox'><label for='data-f9fb14f2-1c7d-4c29-8823-b73dc83929df' 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>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees</dd></dl></div><div class='xr-var-data'><pre>array([113.765   , 113.7848  , 113.804596, ..., 166.1756  , 166.1954  ,\n",
+       "       166.2152  ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pseudo_level</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-feb707af-a666-4655-815f-1a0334fdbfdb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-feb707af-a666-4655-815f-1a0334fdbfdb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6ca8168c-2ac0-4a9a-8db0-a4c1b64f3d76' class='xr-var-data-in' type='checkbox'><label for='data-6ca8168c-2ac0-4a9a-8db0-a4c1b64f3d76' 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>pseudo_level</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=int64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>realization</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9ab89171-7adf-4de3-bc80-7c9541395eb1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9ab89171-7adf-4de3-bc80-7c9541395eb1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-177cfd18-6706-4b6a-8a78-483fe1235897' class='xr-var-data-in' type='checkbox'><label for='data-177cfd18-6706-4b6a-8a78-483fe1235897' 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>standard_name :</span></dt><dd>realization</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=int64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-44ef8316-d098-4619-98a7-811ef7de9afb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-44ef8316-d098-4619-98a7-811ef7de9afb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-de0ad9a0-c87b-4ccc-91a9-ce3bcca24cb6' class='xr-var-data-in' type='checkbox'><label for='data-de0ad9a0-c87b-4ccc-91a9-ce3bcca24cb6' 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>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=datetime64[ns]]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c90f6ab3-1218-490b-a21c-af1f62273bd8' class='xr-section-summary-in' type='checkbox'  ><label for='section-c90f6ab3-1218-490b-a21c-af1f62273bd8' class='xr-section-summary' >Indexes: <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-index-name'><div>latitude</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b8cc8a4b-69a6-467d-b0cd-fd5538b3de6a' class='xr-index-data-in' type='checkbox'/><label for='index-b8cc8a4b-69a6-467d-b0cd-fd5538b3de6a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ -49.28300094604492,  -49.26320266723633,  -49.24340057373047,\n",
+       "       -49.223602294921875, -49.203800201416016,  -49.18400192260742,\n",
+       "        -49.16419982910156,  -49.14440155029297,  -49.12459945678711,\n",
+       "       -49.104801177978516,\n",
+       "       ...\n",
+       "       -6.5149993896484375,  -6.495201110839844,   -6.47540283203125,\n",
+       "        -6.455600738525391,  -6.435802459716797, -6.4160003662109375,\n",
+       "        -6.396202087402344,  -6.376399993896484,  -6.356601715087891,\n",
+       "        -6.336799621582031],\n",
+       "      dtype=&#x27;float32&#x27;, name=&#x27;latitude&#x27;, length=2170))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>longitude</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-117c29b5-3b93-4663-b159-6cc3fd8dac65' class='xr-index-data-in' type='checkbox'/><label for='index-117c29b5-3b93-4663-b159-6cc3fd8dac65' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([113.76499938964844, 113.78479766845703, 113.80459594726562,\n",
+       "       113.82440185546875, 113.84420013427734, 113.86399841308594,\n",
+       "       113.88379669189453, 113.90360260009766, 113.92340087890625,\n",
+       "       113.94319915771484,\n",
+       "       ...\n",
+       "       166.03700256347656, 166.05679321289062, 166.07659912109375,\n",
+       "       166.09640502929688, 166.11619567871094, 166.13600158691406,\n",
+       "       166.15579223632812, 166.17559814453125, 166.19540405273438,\n",
+       "       166.21519470214844],\n",
+       "      dtype=&#x27;float32&#x27;, name=&#x27;longitude&#x27;, length=2650))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6deefa0b-b58f-4262-a6d8-ee24f7b4329d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6deefa0b-b58f-4262-a6d8-ee24f7b4329d' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>surface_temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>source :</span></dt><dd>Data from Met Office Unified Model</dd><dt><span>um_version :</span></dt><dd>12.2</dd><dt><span>STASH :</span></dt><dd>m01s00i024</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.DataArray 'surface_temperature' (latitude: 2170, longitude: 2650)> Size: 23MB\n",
+       "dask.array<filled, shape=(2170, 2650), dtype=float32, chunksize=(2170, 2650), chunktype=numpy.ndarray>\n",
+       "Coordinates:\n",
+       "  * latitude      (latitude) float32 9kB -49.28 -49.26 -49.24 ... -6.357 -6.337\n",
+       "  * longitude     (longitude) float32 11kB 113.8 113.8 113.8 ... 166.2 166.2\n",
+       "    pseudo_level  int64 8B ...\n",
+       "    realization   int64 8B ...\n",
+       "    time          datetime64[ns] 8B ...\n",
+       "Attributes:\n",
+       "    standard_name:  surface_temperature\n",
+       "    units:          K\n",
+       "    source:         Data from Met Office Unified Model\n",
+       "    um_version:     12.2\n",
+       "    STASH:          m01s00i024"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "era5_sst"
+   ]
+  },
+  {
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+   "execution_count": 8,
+   "id": "c44782db-ee43-47bf-9554-95b7c9bbb7da",
+   "metadata": {},
+   "outputs": [
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+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: '(';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: ')';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: ',';\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;surface_temperature&#x27; (latitude: 2120, longitude: 2600)&gt; Size: 22MB\n",
+       "dask.array&lt;filled, shape=(2120, 2600), dtype=float32, chunksize=(2120, 2600), chunktype=numpy.ndarray&gt;\n",
+       "Coordinates:\n",
+       "  * latitude      (latitude) float32 8kB -48.79 -48.77 -48.75 ... -6.852 -6.832\n",
+       "  * longitude     (longitude) float32 10kB 114.3 114.3 114.3 ... 165.7 165.7\n",
+       "    pseudo_level  int64 8B ...\n",
+       "    realization   int64 8B ...\n",
+       "    time          datetime64[ns] 8B ...\n",
+       "Attributes:\n",
+       "    standard_name:  surface_temperature\n",
+       "    units:          K\n",
+       "    source:         Data from Met Office Unified Model\n",
+       "    um_version:     12.2\n",
+       "    STASH:          m01s00i024</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'surface_temperature'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>latitude</span>: 2120</li><li><span class='xr-has-index'>longitude</span>: 2600</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-87b90dd9-6c93-4907-b1e3-1acf386a347d' class='xr-array-in' type='checkbox' checked><label for='section-87b90dd9-6c93-4907-b1e3-1acf386a347d' 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>dask.array&lt;chunksize=(2120, 2600), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 21.03 MiB </td>\n",
+       "                        <td> 21.03 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (2120, 2600) </td>\n",
+       "                        <td> (2120, 2600) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 3 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"147\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"97\" x2=\"120\" y2=\"97\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"97\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"97\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,97.84615384615385 0.0,97.84615384615385\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"117.846154\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2600</text>\n",
+       "  <text x=\"140.000000\" y=\"48.923077\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,48.923077)\">2120</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></div></li><li class='xr-section-item'><input id='section-aaddc79f-a84d-4d4d-9e20-418b35c2751e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-aaddc79f-a84d-4d4d-9e20-418b35c2751e' class='xr-section-summary' >Coordinates: <span>(5)</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'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-48.79 -48.77 ... -6.852 -6.832</div><input id='attrs-a198c564-1def-41cb-9ab3-9ed27dcdcc9d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a198c564-1def-41cb-9ab3-9ed27dcdcc9d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d5c0ccaf-9106-4d1d-8177-2114665ec61f' class='xr-var-data-in' type='checkbox'><label for='data-d5c0ccaf-9106-4d1d-8177-2114665ec61f' 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>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees</dd></dl></div><div class='xr-var-data'><pre>array([-48.788   , -48.7682  , -48.748398, ...,  -6.871399,  -6.851597,\n",
+       "        -6.831799], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>114.3 114.3 114.3 ... 165.7 165.7</div><input id='attrs-39cd243e-5dcf-482f-9220-759a02b38cb7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-39cd243e-5dcf-482f-9220-759a02b38cb7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6d7e0e3e-c00a-478c-b918-a9872403fe78' class='xr-var-data-in' type='checkbox'><label for='data-6d7e0e3e-c00a-478c-b918-a9872403fe78' 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>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees</dd></dl></div><div class='xr-var-data'><pre>array([114.26   , 114.2798 , 114.2996 , ..., 165.6806 , 165.70041, 165.7202 ],\n",
+       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pseudo_level</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5c40dd2b-aab7-4f38-8cd7-20e4ef286bac' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5c40dd2b-aab7-4f38-8cd7-20e4ef286bac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-46500b56-ee47-426a-a094-3ae2652dce16' class='xr-var-data-in' type='checkbox'><label for='data-46500b56-ee47-426a-a094-3ae2652dce16' 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>pseudo_level</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=int64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>realization</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-766eb036-fcf8-4e6e-b4d9-417166cbcddd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-766eb036-fcf8-4e6e-b4d9-417166cbcddd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fe762e69-d9a5-40f0-9944-c0b4fd2167ff' class='xr-var-data-in' type='checkbox'><label for='data-fe762e69-d9a5-40f0-9944-c0b4fd2167ff' 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>standard_name :</span></dt><dd>realization</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=int64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0975eb65-5e04-480a-85ee-48fa565a77df' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0975eb65-5e04-480a-85ee-48fa565a77df' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5dfb121f-4c97-4ed7-951c-6f1eda848010' class='xr-var-data-in' type='checkbox'><label for='data-5dfb121f-4c97-4ed7-951c-6f1eda848010' 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>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=datetime64[ns]]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8178b124-525c-45a9-b86c-f8653dd4473c' class='xr-section-summary-in' type='checkbox'  ><label for='section-8178b124-525c-45a9-b86c-f8653dd4473c' class='xr-section-summary' >Indexes: <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-index-name'><div>latitude</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-386a8247-9058-4ac4-826c-a88ee9913459' class='xr-index-data-in' type='checkbox'/><label for='index-386a8247-9058-4ac4-826c-a88ee9913459' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ -48.78799819946289,   -48.7681999206543,  -48.74839782714844,\n",
+       "       -48.728599548339844, -48.708797454833984,  -48.68899917602539,\n",
+       "        -48.66919708251953,  -48.64939880371094,  -48.62959671020508,\n",
+       "       -48.609798431396484,\n",
+       "       ...\n",
+       "        -7.009998321533203,  -6.990200042724609,   -6.97039794921875,\n",
+       "        -6.950599670410156,  -6.930797576904297,  -6.910999298095703,\n",
+       "        -6.891197204589844,   -6.87139892578125,  -6.851596832275391,\n",
+       "        -6.831798553466797],\n",
+       "      dtype=&#x27;float32&#x27;, name=&#x27;latitude&#x27;, length=2120))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>longitude</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-1d992650-d1c8-4207-86d7-8300627f6fb6' class='xr-index-data-in' type='checkbox'/><label for='index-1d992650-d1c8-4207-86d7-8300627f6fb6' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([114.26000213623047, 114.27980041503906, 114.29959869384766,\n",
+       "       114.31940460205078, 114.33920288085938, 114.35900115966797,\n",
+       "       114.37879943847656, 114.39860534667969, 114.41840362548828,\n",
+       "       114.43820190429688,\n",
+       "       ...\n",
+       "       165.54200744628906, 165.56179809570312, 165.58160400390625,\n",
+       "       165.60140991210938, 165.62120056152344, 165.64100646972656,\n",
+       "       165.66079711914062, 165.68060302734375, 165.70040893554688,\n",
+       "       165.72019958496094],\n",
+       "      dtype=&#x27;float32&#x27;, name=&#x27;longitude&#x27;, length=2600))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-96dcae2f-0875-4182-8e50-40c122b0fb2d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-96dcae2f-0875-4182-8e50-40c122b0fb2d' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>surface_temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>source :</span></dt><dd>Data from Met Office Unified Model</dd><dt><span>um_version :</span></dt><dd>12.2</dd><dt><span>STASH :</span></dt><dd>m01s00i024</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.DataArray 'surface_temperature' (latitude: 2120, longitude: 2600)> Size: 22MB\n",
+       "dask.array<filled, shape=(2120, 2600), dtype=float32, chunksize=(2120, 2600), chunktype=numpy.ndarray>\n",
+       "Coordinates:\n",
+       "  * latitude      (latitude) float32 8kB -48.79 -48.77 -48.75 ... -6.852 -6.832\n",
+       "  * longitude     (longitude) float32 10kB 114.3 114.3 114.3 ... 165.7 165.7\n",
+       "    pseudo_level  int64 8B ...\n",
+       "    realization   int64 8B ...\n",
+       "    time          datetime64[ns] 8B ...\n",
+       "Attributes:\n",
+       "    standard_name:  surface_temperature\n",
+       "    units:          K\n",
+       "    source:         Data from Met Office Unified Model\n",
+       "    um_version:     12.2\n",
+       "    STASH:          m01s00i024"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "um_sst"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "221a003b-c005-4fa0-9c2b-6e18b5f1ec85",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "era5_sst_on_um = era5_sst.isel(longitude=slice(25,-25),latitude=slice(25,-25))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "38e148fa-275d-447c-b263-ef659af20db4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "era5_sst_on_um = era5_sst_on_um.assign_coords(latitude=um_sst.latitude,longitude=um_sst.longitude)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "d6e9f5ff-ba38-4a6c-a154-0a1dbf86fa19",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for f in cubes:\n",
+    "    s=f.attributes['STASH']\n",
+    "    if s.model==1 and s.section==0 and s.item == 30:\n",
+    "        um_lsm = xr.DataArray.from_iris(f)\n",
+    "        break"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "7cb260af-ecf1-42fc-ac37-86ed0c37e6fc",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;land_binary_mask&#x27; (latitude: 2120, longitude: 2600)&gt; Size: 44MB\n",
+       "dask.array&lt;filled, shape=(2120, 2600), dtype=int64, chunksize=(2120, 2600), chunktype=numpy.ndarray&gt;\n",
+       "Coordinates:\n",
+       "  * latitude      (latitude) float32 8kB -48.79 -48.77 -48.75 ... -6.852 -6.832\n",
+       "  * longitude     (longitude) float32 10kB 114.3 114.3 114.3 ... 165.7 165.7\n",
+       "    pseudo_level  int64 8B ...\n",
+       "    realization   int64 8B ...\n",
+       "    time          datetime64[ns] 8B ...\n",
+       "Attributes:\n",
+       "    standard_name:  land_binary_mask\n",
+       "    source:         Data from Met Office Unified Model\n",
+       "    um_version:     12.2\n",
+       "    STASH:          m01s00i030</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'land_binary_mask'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>latitude</span>: 2120</li><li><span class='xr-has-index'>longitude</span>: 2600</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-2b0fd927-b770-4e18-b9b8-2955cb6b9581' class='xr-array-in' type='checkbox' checked><label for='section-2b0fd927-b770-4e18-b9b8-2955cb6b9581' 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>dask.array&lt;chunksize=(2120, 2600), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 42.05 MiB </td>\n",
+       "                        <td> 42.05 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (2120, 2600) </td>\n",
+       "                        <td> (2120, 2600) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 3 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> int64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"147\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"97\" x2=\"120\" y2=\"97\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
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+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"97\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,97.84615384615385 0.0,97.84615384615385\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"117.846154\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2600</text>\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></div></li><li class='xr-section-item'><input id='section-1082afcb-685e-4cdf-af90-e9cbfd44b11b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1082afcb-685e-4cdf-af90-e9cbfd44b11b' class='xr-section-summary' >Coordinates: <span>(5)</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'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-48.79 -48.77 ... -6.852 -6.832</div><input id='attrs-553a204d-4f9c-4e21-9124-90393f96f490' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-553a204d-4f9c-4e21-9124-90393f96f490' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-16fdecc5-5cc9-46a9-b670-5e6c317b573a' class='xr-var-data-in' type='checkbox'><label for='data-16fdecc5-5cc9-46a9-b670-5e6c317b573a' 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>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees</dd></dl></div><div class='xr-var-data'><pre>array([-48.788   , -48.7682  , -48.748398, ...,  -6.871399,  -6.851597,\n",
+       "        -6.831799], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>114.3 114.3 114.3 ... 165.7 165.7</div><input id='attrs-f1aa3056-0400-4bb8-807f-62d74fe42d4e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f1aa3056-0400-4bb8-807f-62d74fe42d4e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-00cf4d64-5410-436c-bffd-6b5400fac74c' class='xr-var-data-in' type='checkbox'><label for='data-00cf4d64-5410-436c-bffd-6b5400fac74c' 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>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees</dd></dl></div><div class='xr-var-data'><pre>array([114.26   , 114.2798 , 114.2996 , ..., 165.6806 , 165.70041, 165.7202 ],\n",
+       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pseudo_level</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f60fb1ca-a9e4-4b7b-8514-d862ece2a4ed' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f60fb1ca-a9e4-4b7b-8514-d862ece2a4ed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1c6beb94-40c7-4196-a291-10722a8cb1f2' class='xr-var-data-in' type='checkbox'><label for='data-1c6beb94-40c7-4196-a291-10722a8cb1f2' 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>pseudo_level</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=int64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>realization</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-22cf348b-738b-4a95-bb8c-93fc37d4ebec' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-22cf348b-738b-4a95-bb8c-93fc37d4ebec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-af44544d-562a-4158-99e5-963f2d831928' class='xr-var-data-in' type='checkbox'><label for='data-af44544d-562a-4158-99e5-963f2d831928' 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>standard_name :</span></dt><dd>realization</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=int64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-04ed5b1c-89ca-4e24-b6f2-226eaa83331a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-04ed5b1c-89ca-4e24-b6f2-226eaa83331a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-615ff5f4-070b-4e72-97ab-ed4cf0231ed3' class='xr-var-data-in' type='checkbox'><label for='data-615ff5f4-070b-4e72-97ab-ed4cf0231ed3' 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>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=datetime64[ns]]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d5645959-5a26-48c4-b4c1-861329313296' class='xr-section-summary-in' type='checkbox'  ><label for='section-d5645959-5a26-48c4-b4c1-861329313296' class='xr-section-summary' >Indexes: <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-index-name'><div>latitude</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-8c658a97-fd91-4387-8953-dabcfcbe31a8' class='xr-index-data-in' type='checkbox'/><label for='index-8c658a97-fd91-4387-8953-dabcfcbe31a8' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ -48.78799819946289,   -48.7681999206543,  -48.74839782714844,\n",
+       "       -48.728599548339844, -48.708797454833984,  -48.68899917602539,\n",
+       "        -48.66919708251953,  -48.64939880371094,  -48.62959671020508,\n",
+       "       -48.609798431396484,\n",
+       "       ...\n",
+       "        -7.009998321533203,  -6.990200042724609,   -6.97039794921875,\n",
+       "        -6.950599670410156,  -6.930797576904297,  -6.910999298095703,\n",
+       "        -6.891197204589844,   -6.87139892578125,  -6.851596832275391,\n",
+       "        -6.831798553466797],\n",
+       "      dtype=&#x27;float32&#x27;, name=&#x27;latitude&#x27;, length=2120))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>longitude</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-0fc9a94a-e4ca-4091-bd59-09f61345fc7b' class='xr-index-data-in' type='checkbox'/><label for='index-0fc9a94a-e4ca-4091-bd59-09f61345fc7b' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([114.26000213623047, 114.27980041503906, 114.29959869384766,\n",
+       "       114.31940460205078, 114.33920288085938, 114.35900115966797,\n",
+       "       114.37879943847656, 114.39860534667969, 114.41840362548828,\n",
+       "       114.43820190429688,\n",
+       "       ...\n",
+       "       165.54200744628906, 165.56179809570312, 165.58160400390625,\n",
+       "       165.60140991210938, 165.62120056152344, 165.64100646972656,\n",
+       "       165.66079711914062, 165.68060302734375, 165.70040893554688,\n",
+       "       165.72019958496094],\n",
+       "      dtype=&#x27;float32&#x27;, name=&#x27;longitude&#x27;, length=2600))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0992b48f-6f12-4264-b9f3-bb615374b279' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0992b48f-6f12-4264-b9f3-bb615374b279' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>land_binary_mask</dd><dt><span>source :</span></dt><dd>Data from Met Office Unified Model</dd><dt><span>um_version :</span></dt><dd>12.2</dd><dt><span>STASH :</span></dt><dd>m01s00i030</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.DataArray 'land_binary_mask' (latitude: 2120, longitude: 2600)> Size: 44MB\n",
+       "dask.array<filled, shape=(2120, 2600), dtype=int64, chunksize=(2120, 2600), chunktype=numpy.ndarray>\n",
+       "Coordinates:\n",
+       "  * latitude      (latitude) float32 8kB -48.79 -48.77 -48.75 ... -6.852 -6.832\n",
+       "  * longitude     (longitude) float32 10kB 114.3 114.3 114.3 ... 165.7 165.7\n",
+       "    pseudo_level  int64 8B ...\n",
+       "    realization   int64 8B ...\n",
+       "    time          datetime64[ns] 8B ...\n",
+       "Attributes:\n",
+       "    standard_name:  land_binary_mask\n",
+       "    source:         Data from Met Office Unified Model\n",
+       "    um_version:     12.2\n",
+       "    STASH:          m01s00i030"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "um_lsm"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "5be87ec6-8445-4a2f-9a74-89ee119639c3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "updated_sst=(((1-um_lsm)*era5_sst_on_um) + um_lsm*um_sst)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "e06891fc-f6cd-47b3-a39e-21defbe21851",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x1534a9516f20>"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "### Sanity check - identical over land\n",
+    "(um_lsm*(um_sst-updated_sst)).plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "09c78602-7dfe-499c-be5a-3736d47aa46e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x1534a48cd5d0>"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "### Sanity check - different over ocean\n",
+    "((1-um_lsm)*(um_sst-updated_sst)).plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "2c1f2869-c36d-4305-93e9-e702ec11d5cc",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "d=updated_sst.data.compute()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "74097729-ab10-499b-a4a0-314d7e8c8e20",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/g/data/hh5/public/apps/cms_conda/envs/analysis3-24.01/lib/python3.10/site-packages/mule/stashmaster.py:259: UserWarning: \n",
+      "Unable to load STASHmaster from version string, path does not exist\n",
+      "Path: $UMDIR/vn12.2/ctldata/STASHmaster/STASHmaster_A\n",
+      "Please check that the value of mule.stashmaster.STASHMASTER_PATH_PATTERN is correct for your site/configuration\n",
+      "  warnings.warn(msg)\n"
+     ]
+    }
+   ],
+   "source": [
+    "dump_mule = mule.load_umfile(dump_fn)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "53613a18-a0c4-4d7b-961f-8702aff35ff7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "mf_out = dump_mule.copy()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "ac43fa72-5208-443c-932b-9525f123a9c6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "array_provider = mule.ArrayDataProvider(d)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "808d78fb-84e0-4176-b8d4-cc3406a1887f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for f in dump_mule.fields:\n",
+    "    if f.lbuser4 != 24:\n",
+    "        mf_out.fields.append(f)\n",
+    "    else:\n",
+    "        new_field = f.copy()\n",
+    "        new_field.set_data_provider(array_provider)\n",
+    "        mf_out.fields.append(new_field)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "abf27d00-ce2f-4ab0-a7db-0c8fa402d886",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "mf_out.to_file(dump_out)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "42bd15cc-ec07-4bee-9a4a-7e8c78b4c014",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/g/data/hh5/public/apps/cms_conda/envs/analysis3-24.01/lib/python3.10/site-packages/iris/fileformats/_ff.py:722: _WarnComboLoadingDefaulting: The stash code m01s00i060 is on a grid 22 which has not been explicitly handled by the fieldsfile loader. Assuming the data is on a P grid.\n",
+      "  warnings.warn(\n"
+     ]
+    }
+   ],
+   "source": [
+    "new_cubes = iris.load(dump_out)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "f5dba4e1-a69a-4c5b-afc7-dde05db127a1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for f in new_cubes:\n",
+    "    s=f.attributes['STASH']\n",
+    "    if s.model==1 and s.section==0 and s.item == 24:\n",
+    "        new_um_sst = xr.DataArray.from_iris(f)\n",
+    "        break"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "05ebff8f-7bd2-405b-8031-69f172347144",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x1534a8f61de0>"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "### Sanity check - identical over land\n",
+    "(um_lsm*(um_sst-new_um_sst)).plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "24c7e5ba-f980-4810-8b25-70f0649369d3",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x1534a8d5ecb0>"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "### Sanity check - different over ocean\n",
+    "((1-um_lsm)*(um_sst-new_um_sst)).plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b16f1ce5-2349-49e3-82c4-f72b1664242e",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python [conda env:analysis3-24.01]",
+   "language": "python",
+   "name": "conda-env-analysis3-24.01-py"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.14"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/Recipes/XarrayMovieMaker.ipynb b/Recipes/XarrayMovieMaker.ipynb
new file mode 100644
index 0000000..7c998eb
--- /dev/null
+++ b/Recipes/XarrayMovieMaker.ipynb
@@ -0,0 +1,1055 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "43c330a3-ef0d-4328-8b27-edee620031bb",
+   "metadata": {},
+   "source": [
+    "### Temperature Animation\n",
+    "\n",
+    "Create an animation of the surface temperature across the entire AUS2200 domain for a complete simulation in parallel using Xarray."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9a7d4353-bcdb-4311-82da-32092fe13683",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import xarray as xr\n",
+    "from glob import glob\n",
+    "from dask.distributed import Client\n",
+    "import matplotlib.pyplot as plt\n",
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "88786b5a-1b8a-48a6-ac4b-cb5551257743",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "file_list = sorted(glob('/g/data/gx60/dr4292/experiments/ECL-shifted-evolvingSST/netcdf/u-cs142-20160603T0000-continuous-140E-evolvingSST/*/aus2200/d0198/RA3/um/umnsa_spec*'))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "8d43d79a-2965-43aa-b44f-db287a3df162",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-11 12:23:33,952 - distributed.preloading - INFO - Creating preload: /g/data/hh5/public/apps/dask-optimiser/schedplugin.py\n",
+      "2024-06-11 12:23:33,984 - distributed.utils - INFO - Reload module schedplugin from .py file\n",
+      "2024-06-11 12:23:34,048 - distributed.preloading - INFO - Import preload module: /g/data/hh5/public/apps/dask-optimiser/schedplugin.py\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Modifying workers\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "    <div style=\"width: 24px; height: 24px; background-color: #e1e1e1; border: 3px solid #9D9D9D; border-radius: 5px; position: absolute;\"> </div>\n",
+       "    <div style=\"margin-left: 48px;\">\n",
+       "        <h3 style=\"margin-bottom: 0px;\">Client</h3>\n",
+       "        <p style=\"color: #9D9D9D; margin-bottom: 0px;\">Client-9a08e09b-2799-11ef-a20f-00000813fe80</p>\n",
+       "        <table style=\"width: 100%; text-align: left;\">\n",
+       "\n",
+       "        <tr>\n",
+       "        \n",
+       "            <td style=\"text-align: left;\"><strong>Connection method:</strong> Cluster object</td>\n",
+       "            <td style=\"text-align: left;\"><strong>Cluster type:</strong> distributed.LocalCluster</td>\n",
+       "        \n",
+       "        </tr>\n",
+       "\n",
+       "        \n",
+       "            <tr>\n",
+       "                <td style=\"text-align: left;\">\n",
+       "                    <strong>Dashboard: </strong> <a href=\"/node/gadi-cpu-spr-0098.gadi.nci.org.au/52617/proxy/8787/status\" target=\"_blank\">/node/gadi-cpu-spr-0098.gadi.nci.org.au/52617/proxy/8787/status</a>\n",
+       "                </td>\n",
+       "                <td style=\"text-align: left;\"></td>\n",
+       "            </tr>\n",
+       "        \n",
+       "\n",
+       "        </table>\n",
+       "\n",
+       "        \n",
+       "            <button style=\"margin-bottom: 12px;\" data-commandlinker-command=\"dask:populate-and-launch-layout\" data-commandlinker-args='{\"url\": \"/node/gadi-cpu-spr-0098.gadi.nci.org.au/52617/proxy/8787/status\" }'>\n",
+       "                Launch dashboard in JupyterLab\n",
+       "            </button>\n",
+       "        \n",
+       "\n",
+       "        \n",
+       "            <details>\n",
+       "            <summary style=\"margin-bottom: 20px;\"><h3 style=\"display: inline;\">Cluster Info</h3></summary>\n",
+       "            <div class=\"jp-RenderedHTMLCommon jp-RenderedHTML jp-mod-trusted jp-OutputArea-output\">\n",
+       "    <div style=\"width: 24px; height: 24px; background-color: #e1e1e1; border: 3px solid #9D9D9D; border-radius: 5px; position: absolute;\">\n",
+       "    </div>\n",
+       "    <div style=\"margin-left: 48px;\">\n",
+       "        <h3 style=\"margin-bottom: 0px; margin-top: 0px;\">LocalCluster</h3>\n",
+       "        <p style=\"color: #9D9D9D; margin-bottom: 0px;\">95fafa1a</p>\n",
+       "        <table style=\"width: 100%; text-align: left;\">\n",
+       "            <tr>\n",
+       "                <td style=\"text-align: left;\">\n",
+       "                    <strong>Dashboard:</strong> <a href=\"/node/gadi-cpu-spr-0098.gadi.nci.org.au/52617/proxy/8787/status\" target=\"_blank\">/node/gadi-cpu-spr-0098.gadi.nci.org.au/52617/proxy/8787/status</a>\n",
+       "                </td>\n",
+       "                <td style=\"text-align: left;\">\n",
+       "                    <strong>Workers:</strong> 4\n",
+       "                </td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                <td style=\"text-align: left;\">\n",
+       "                    <strong>Total threads:</strong> 4\n",
+       "                </td>\n",
+       "                <td style=\"text-align: left;\">\n",
+       "                    <strong>Total memory:</strong> 0 B\n",
+       "                </td>\n",
+       "            </tr>\n",
+       "            \n",
+       "            <tr>\n",
+       "    <td style=\"text-align: left;\"><strong>Status:</strong> running</td>\n",
+       "    <td style=\"text-align: left;\"><strong>Using processes:</strong> True</td>\n",
+       "</tr>\n",
+       "\n",
+       "            \n",
+       "        </table>\n",
+       "\n",
+       "        <details>\n",
+       "            <summary style=\"margin-bottom: 20px;\">\n",
+       "                <h3 style=\"display: inline;\">Scheduler Info</h3>\n",
+       "            </summary>\n",
+       "\n",
+       "            <div style=\"\">\n",
+       "    <div>\n",
+       "        <div style=\"width: 24px; height: 24px; background-color: #FFF7E5; border: 3px solid #FF6132; border-radius: 5px; position: absolute;\"> </div>\n",
+       "        <div style=\"margin-left: 48px;\">\n",
+       "            <h3 style=\"margin-bottom: 0px;\">Scheduler</h3>\n",
+       "            <p style=\"color: #9D9D9D; margin-bottom: 0px;\">Scheduler-0f745ce2-8ff3-47d4-82bb-54d95d456290</p>\n",
+       "            <table style=\"width: 100%; text-align: left;\">\n",
+       "                <tr>\n",
+       "                    <td style=\"text-align: left;\">\n",
+       "                        <strong>Comm:</strong> tcp://127.0.0.1:35419\n",
+       "                    </td>\n",
+       "                    <td style=\"text-align: left;\">\n",
+       "                        <strong>Workers:</strong> 4\n",
+       "                    </td>\n",
+       "                </tr>\n",
+       "                <tr>\n",
+       "                    <td style=\"text-align: left;\">\n",
+       "                        <strong>Dashboard:</strong> <a href=\"/node/gadi-cpu-spr-0098.gadi.nci.org.au/52617/proxy/8787/status\" target=\"_blank\">/node/gadi-cpu-spr-0098.gadi.nci.org.au/52617/proxy/8787/status</a>\n",
+       "                    </td>\n",
+       "                    <td style=\"text-align: left;\">\n",
+       "                        <strong>Total threads:</strong> 4\n",
+       "                    </td>\n",
+       "                </tr>\n",
+       "                <tr>\n",
+       "                    <td style=\"text-align: left;\">\n",
+       "                        <strong>Started:</strong> Just now\n",
+       "                    </td>\n",
+       "                    <td style=\"text-align: left;\">\n",
+       "                        <strong>Total memory:</strong> 0 B\n",
+       "                    </td>\n",
+       "                </tr>\n",
+       "            </table>\n",
+       "        </div>\n",
+       "    </div>\n",
+       "\n",
+       "    <details style=\"margin-left: 48px;\">\n",
+       "        <summary style=\"margin-bottom: 20px;\">\n",
+       "            <h3 style=\"display: inline;\">Workers</h3>\n",
+       "        </summary>\n",
+       "\n",
+       "        \n",
+       "        <div style=\"margin-bottom: 20px;\">\n",
+       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
+       "            <div style=\"margin-left: 48px;\">\n",
+       "            <details>\n",
+       "                <summary>\n",
+       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 0</h4>\n",
+       "                </summary>\n",
+       "                <table style=\"width: 100%; text-align: left;\">\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Comm: </strong> tcp://127.0.0.1:39799\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Total threads: </strong> 1\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Dashboard: </strong> <a href=\"/node/gadi-cpu-spr-0098.gadi.nci.org.au/52617/proxy/35585/status\" target=\"_blank\">/node/gadi-cpu-spr-0098.gadi.nci.org.au/52617/proxy/35585/status</a>\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Memory: </strong> 0 B\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Nanny: </strong> tcp://127.0.0.1:45567\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\"></td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
+       "                            <strong>Local directory: </strong> /jobfs/117857481.gadi-pbs/dask-scratch-space/worker-svqrc4hr\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                </table>\n",
+       "            </details>\n",
+       "            </div>\n",
+       "        </div>\n",
+       "        \n",
+       "        <div style=\"margin-bottom: 20px;\">\n",
+       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
+       "            <div style=\"margin-left: 48px;\">\n",
+       "            <details>\n",
+       "                <summary>\n",
+       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 1</h4>\n",
+       "                </summary>\n",
+       "                <table style=\"width: 100%; text-align: left;\">\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Comm: </strong> tcp://127.0.0.1:40109\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Total threads: </strong> 1\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Dashboard: </strong> <a href=\"/node/gadi-cpu-spr-0098.gadi.nci.org.au/52617/proxy/41377/status\" target=\"_blank\">/node/gadi-cpu-spr-0098.gadi.nci.org.au/52617/proxy/41377/status</a>\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Memory: </strong> 0 B\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Nanny: </strong> tcp://127.0.0.1:32889\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\"></td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
+       "                            <strong>Local directory: </strong> /jobfs/117857481.gadi-pbs/dask-scratch-space/worker-1vri8v2j\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                </table>\n",
+       "            </details>\n",
+       "            </div>\n",
+       "        </div>\n",
+       "        \n",
+       "        <div style=\"margin-bottom: 20px;\">\n",
+       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
+       "            <div style=\"margin-left: 48px;\">\n",
+       "            <details>\n",
+       "                <summary>\n",
+       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 2</h4>\n",
+       "                </summary>\n",
+       "                <table style=\"width: 100%; text-align: left;\">\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Comm: </strong> tcp://127.0.0.1:43757\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Total threads: </strong> 1\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Dashboard: </strong> <a href=\"/node/gadi-cpu-spr-0098.gadi.nci.org.au/52617/proxy/33443/status\" target=\"_blank\">/node/gadi-cpu-spr-0098.gadi.nci.org.au/52617/proxy/33443/status</a>\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Memory: </strong> 0 B\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Nanny: </strong> tcp://127.0.0.1:34421\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\"></td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
+       "                            <strong>Local directory: </strong> /jobfs/117857481.gadi-pbs/dask-scratch-space/worker-8kub71ir\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                </table>\n",
+       "            </details>\n",
+       "            </div>\n",
+       "        </div>\n",
+       "        \n",
+       "        <div style=\"margin-bottom: 20px;\">\n",
+       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
+       "            <div style=\"margin-left: 48px;\">\n",
+       "            <details>\n",
+       "                <summary>\n",
+       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 3</h4>\n",
+       "                </summary>\n",
+       "                <table style=\"width: 100%; text-align: left;\">\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Comm: </strong> tcp://127.0.0.1:46723\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Total threads: </strong> 1\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Dashboard: </strong> <a href=\"/node/gadi-cpu-spr-0098.gadi.nci.org.au/52617/proxy/41219/status\" target=\"_blank\">/node/gadi-cpu-spr-0098.gadi.nci.org.au/52617/proxy/41219/status</a>\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Memory: </strong> 0 B\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Nanny: </strong> tcp://127.0.0.1:41795\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\"></td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
+       "                            <strong>Local directory: </strong> /jobfs/117857481.gadi-pbs/dask-scratch-space/worker-bp1yuo9k\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                </table>\n",
+       "            </details>\n",
+       "            </div>\n",
+       "        </div>\n",
+       "        \n",
+       "\n",
+       "    </details>\n",
+       "</div>\n",
+       "\n",
+       "        </details>\n",
+       "    </div>\n",
+       "</div>\n",
+       "            </details>\n",
+       "        \n",
+       "\n",
+       "    </div>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "<Client: 'tcp://127.0.0.1:35419' processes=4 threads=4, memory=19.00 GiB>"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "client=Client()\n",
+    "client"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "beb713cd-5f9f-4fd2-8b01-7649de2a1e3b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "mf_ds = xr.open_mfdataset(file_list,preprocess=lambda x: x['fld_s00i024'],parallel=True,chunks={'lat':-1,'lon':-1})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "de381673-e463-4685-ae84-a1c2aa54606d",
+   "metadata": {},
+   "outputs": [
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+       "body[data-theme=dark],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
+       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
+       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
+       "  --xr-border-color: #1F1F1F;\n",
+       "  --xr-disabled-color: #515151;\n",
+       "  --xr-background-color: #111111;\n",
+       "  --xr-background-color-row-even: #111111;\n",
+       "  --xr-background-color-row-odd: #313131;\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: '►';\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: '▼';\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: '(';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: ')';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: ',';\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 16GB\n",
+       "Dimensions:                   (time: 720, lat: 2120, lon: 2600)\n",
+       "Coordinates:\n",
+       "  * time                      (time) datetime64[ns] 6kB 2016-06-03T00:10:00 ....\n",
+       "  * lat                       (lat) float64 17kB -48.79 -48.77 ... -6.852 -6.832\n",
+       "  * lon                       (lon) float64 21kB 114.3 114.3 ... 165.7 165.7\n",
+       "    theta_level_height        float64 8B 5.0\n",
+       "    model_theta_level_number  int32 4B 1\n",
+       "    sigma_theta               float64 8B 0.9994\n",
+       "    height                    float64 8B 10.0\n",
+       "    height_0                  float64 8B 1.5\n",
+       "Data variables:\n",
+       "    fld_s00i024               (time, lat, lon) float32 16GB dask.array&lt;chunksize=(1, 2120, 2600), meta=np.ndarray&gt;</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-8bca0ed8-9350-4bf1-aa97-6cab65a3fcfb' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-8bca0ed8-9350-4bf1-aa97-6cab65a3fcfb' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 720</li><li><span class='xr-has-index'>lat</span>: 2120</li><li><span class='xr-has-index'>lon</span>: 2600</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-01bf9699-f11c-49e1-baca-3ac50191fcf4' class='xr-section-summary-in' type='checkbox'  checked><label for='section-01bf9699-f11c-49e1-baca-3ac50191fcf4' class='xr-section-summary' >Coordinates: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2016-06-03T00:10:00 ... 2016-06-08</div><input id='attrs-8dc8cdb1-4c49-4832-98a7-ea4fe051681c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8dc8cdb1-4c49-4832-98a7-ea4fe051681c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-832e24f6-713c-4943-add3-d328e3223701' class='xr-var-data-in' type='checkbox'><label for='data-832e24f6-713c-4943-add3-d328e3223701' 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>axis :</span></dt><dd>T</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2016-06-03T00:10:00.000000000&#x27;, &#x27;2016-06-03T00:19:59.999999744&#x27;,\n",
+       "       &#x27;2016-06-03T00:30:00.000000000&#x27;, ..., &#x27;2016-06-07T23:40:00.000000256&#x27;,\n",
+       "       &#x27;2016-06-07T23:50:00.000000000&#x27;, &#x27;2016-06-08T00:00:00.000000000&#x27;],\n",
+       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-48.79 -48.77 ... -6.852 -6.832</div><input id='attrs-2731f4c5-6027-45f0-a1fc-44fb43d0a73e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2731f4c5-6027-45f0-a1fc-44fb43d0a73e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d0cac94b-9c72-4b3e-ae86-ee1b9a23a3bd' class='xr-var-data-in' type='checkbox'><label for='data-d0cac94b-9c72-4b3e-ae86-ee1b9a23a3bd' 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>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-48.787998, -48.7682  , -48.748398, ...,  -6.871399,  -6.851597,\n",
+       "        -6.831799])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>114.3 114.3 114.3 ... 165.7 165.7</div><input id='attrs-88757c40-6ac6-4c70-acf5-a6689593a7c3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-88757c40-6ac6-4c70-acf5-a6689593a7c3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eef44fb8-5037-4a5d-af41-a146060c3d55' class='xr-var-data-in' type='checkbox'><label for='data-eef44fb8-5037-4a5d-af41-a146060c3d55' 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>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([114.260002, 114.2798  , 114.299599, ..., 165.680603, 165.700409,\n",
+       "       165.7202  ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>theta_level_height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.0</div><input id='attrs-68f897d2-3ca5-4393-a70d-30016265e12c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-68f897d2-3ca5-4393-a70d-30016265e12c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d859f172-0ee4-4a31-8e8f-dfd1ed77bfaa' class='xr-var-data-in' type='checkbox'><label for='data-d859f172-0ee4-4a31-8e8f-dfd1ed77bfaa' 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>bounds :</span></dt><dd>theta_level_height_bnds</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>level_height</dd><dt><span>positive :</span></dt><dd>up</dd></dl></div><div class='xr-var-data'><pre>array(5.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>model_theta_level_number</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1</div><input id='attrs-14d6362d-3f70-4137-acef-a1d93779d1e6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-14d6362d-3f70-4137-acef-a1d93779d1e6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3fe8695f-b026-4935-98bd-ea66811cc690' class='xr-var-data-in' type='checkbox'><label for='data-3fe8695f-b026-4935-98bd-ea66811cc690' 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>1</dd><dt><span>standard_name :</span></dt><dd>model_level_number</dd><dt><span>positive :</span></dt><dd>up</dd></dl></div><div class='xr-var-data'><pre>array(1, dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sigma_theta</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.9994</div><input id='attrs-ac80ca2b-8aa7-4236-87db-ce2f29799729' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ac80ca2b-8aa7-4236-87db-ce2f29799729' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-254fd2f6-d6fe-4813-b3d7-00628cda54ad' class='xr-var-data-in' type='checkbox'><label for='data-254fd2f6-d6fe-4813-b3d7-00628cda54ad' 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>bounds :</span></dt><dd>sigma_theta_bnds</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>sigma</dd></dl></div><div class='xr-var-data'><pre>array(0.99942381)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>10.0</div><input id='attrs-99c044c6-1b03-43c9-821e-530460a60024' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-99c044c6-1b03-43c9-821e-530460a60024' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a1a95dff-fede-406b-bf7c-7156296bf3f2' class='xr-var-data-in' type='checkbox'><label for='data-a1a95dff-fede-406b-bf7c-7156296bf3f2' 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>m</dd><dt><span>standard_name :</span></dt><dd>height</dd><dt><span>positive :</span></dt><dd>up</dd></dl></div><div class='xr-var-data'><pre>array(10.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>height_0</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.5</div><input id='attrs-9dd4d5aa-3766-4a67-ab30-1f728b030fe7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9dd4d5aa-3766-4a67-ab30-1f728b030fe7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c31cdd62-a719-4d99-b71c-34a0e60cf72e' class='xr-var-data-in' type='checkbox'><label for='data-c31cdd62-a719-4d99-b71c-34a0e60cf72e' 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>m</dd><dt><span>standard_name :</span></dt><dd>height</dd><dt><span>positive :</span></dt><dd>up</dd></dl></div><div class='xr-var-data'><pre>array(1.5)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ff79b7a6-9165-4100-8011-fd6f37104c4f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ff79b7a6-9165-4100-8011-fd6f37104c4f' class='xr-section-summary' >Data variables: <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>fld_s00i024</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 2120, 2600), meta=np.ndarray&gt;</div><input id='attrs-8949df93-611b-4458-b832-c0ab4c198c57' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8949df93-611b-4458-b832-c0ab4c198c57' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e721f00f-8be9-4b29-a5ac-497463ad05d5' class='xr-var-data-in' type='checkbox'><label for='data-e721f00f-8be9-4b29-a5ac-497463ad05d5' 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>standard_name :</span></dt><dd>surface_temperature</dd><dt><span>long_name :</span></dt><dd>SURFACE TEMPERATURE AFTER TIMESTEP</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>um_stash_source :</span></dt><dd>m01s00i024</dd><dt><span>grid_mapping :</span></dt><dd>latitude_longitude</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 14.78 GiB </td>\n",
+       "                        <td> 21.03 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (720, 2120, 2600) </td>\n",
+       "                        <td> (1, 2120, 2600) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 720 chunks in 241 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-8e9087e2-24e3-4b18-8faf-b60040e97d2e' class='xr-section-summary-in' type='checkbox'  ><label for='section-8e9087e2-24e3-4b18-8faf-b60040e97d2e' class='xr-section-summary' >Indexes: <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-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-44107242-0778-41ac-9c16-d5387bad5398' class='xr-index-data-in' type='checkbox'/><label for='index-44107242-0778-41ac-9c16-d5387bad5398' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([          &#x27;2016-06-03 00:10:00&#x27;,\n",
+       "               &#x27;2016-06-03 00:19:59.999999744&#x27;,\n",
+       "                         &#x27;2016-06-03 00:30:00&#x27;,\n",
+       "                         &#x27;2016-06-03 00:40:00&#x27;,\n",
+       "                         &#x27;2016-06-03 00:50:00&#x27;,\n",
+       "                         &#x27;2016-06-03 01:00:00&#x27;,\n",
+       "               &#x27;2016-06-03 01:10:00.000000256&#x27;,\n",
+       "                         &#x27;2016-06-03 01:20:00&#x27;,\n",
+       "                         &#x27;2016-06-03 01:30:00&#x27;,\n",
+       "                         &#x27;2016-06-03 01:40:00&#x27;,\n",
+       "               ...\n",
+       "                         &#x27;2016-06-07 22:30:00&#x27;,\n",
+       "                         &#x27;2016-06-07 22:40:00&#x27;,\n",
+       "               &#x27;2016-06-07 22:49:59.999999744&#x27;,\n",
+       "                         &#x27;2016-06-07 23:00:00&#x27;,\n",
+       "                         &#x27;2016-06-07 23:10:00&#x27;,\n",
+       "                         &#x27;2016-06-07 23:20:00&#x27;,\n",
+       "                         &#x27;2016-06-07 23:30:00&#x27;,\n",
+       "               &#x27;2016-06-07 23:40:00.000000256&#x27;,\n",
+       "                         &#x27;2016-06-07 23:50:00&#x27;,\n",
+       "                         &#x27;2016-06-08 00:00:00&#x27;],\n",
+       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=720, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b46d22d7-4a23-4eca-9593-e9a2f776ca7c' class='xr-index-data-in' type='checkbox'/><label for='index-b46d22d7-4a23-4eca-9593-e9a2f776ca7c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ -48.78799819946289,   -48.7681999206543,  -48.74839782714844,\n",
+       "       -48.728599548339844, -48.708797454833984,  -48.68899917602539,\n",
+       "        -48.66919708251953,  -48.64939880371094,  -48.62959671020508,\n",
+       "       -48.609798431396484,\n",
+       "       ...\n",
+       "        -7.009998321533203,  -6.990200042724609,   -6.97039794921875,\n",
+       "        -6.950599670410156,  -6.930797576904297,  -6.910999298095703,\n",
+       "        -6.891197204589844,   -6.87139892578125,  -6.851596832275391,\n",
+       "        -6.831798553466797],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=2120))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-cebe1e6a-03ac-4d1f-9adf-cbc4cbf4ce27' class='xr-index-data-in' type='checkbox'/><label for='index-cebe1e6a-03ac-4d1f-9adf-cbc4cbf4ce27' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([114.26000213623047, 114.27980041503906, 114.29959869384766,\n",
+       "       114.31940460205078, 114.33920288085938, 114.35900115966797,\n",
+       "       114.37879943847656, 114.39860534667969, 114.41840362548828,\n",
+       "       114.43820190429688,\n",
+       "       ...\n",
+       "       165.54200744628906, 165.56179809570312, 165.58160400390625,\n",
+       "       165.60140991210938, 165.62120056152344, 165.64100646972656,\n",
+       "       165.66079711914062, 165.68060302734375, 165.70040893554688,\n",
+       "       165.72019958496094],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=2600))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-814a96cd-2ce3-4efd-9e4b-449897fd0d27' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-814a96cd-2ce3-4efd-9e4b-449897fd0d27' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 16GB\n",
+       "Dimensions:                   (time: 720, lat: 2120, lon: 2600)\n",
+       "Coordinates:\n",
+       "  * time                      (time) datetime64[ns] 6kB 2016-06-03T00:10:00 ....\n",
+       "  * lat                       (lat) float64 17kB -48.79 -48.77 ... -6.852 -6.832\n",
+       "  * lon                       (lon) float64 21kB 114.3 114.3 ... 165.7 165.7\n",
+       "    theta_level_height        float64 8B 5.0\n",
+       "    model_theta_level_number  int32 4B 1\n",
+       "    sigma_theta               float64 8B 0.9994\n",
+       "    height                    float64 8B 10.0\n",
+       "    height_0                  float64 8B 1.5\n",
+       "Data variables:\n",
+       "    fld_s00i024               (time, lat, lon) float32 16GB dask.array<chunksize=(1, 2120, 2600), meta=np.ndarray>"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "mf_ds"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "bc74d6d0-b163-4f47-8625-31c3b01525c8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def make_frame(f,ts,i,lat,lon):\n",
+    "    fig = plt.figure()\n",
+    "    ax=fig.add_subplot(111)\n",
+    "    pc = ax.pcolormesh(lon,lat,f - 273.15,shading='nearest',vmin=-5,vmax=45)\n",
+    "    fig.colorbar(pc,label=\"Surface Temperature (°C)\")\n",
+    "    t = pd.to_datetime(ts)\n",
+    "    plt.title(str(ts))\n",
+    "    plt.savefig(f'/home/563/dr4292/animation/frame{i:04}.png')\n",
+    "    return i"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "a09947ac-fd5d-4091-9e22-e7e142e5bc5a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "out = xr.apply_ufunc(make_frame,\n",
+    "    mf_ds['fld_s00i024'],\n",
+    "    mf_ds['fld_s00i024'].time,\n",
+    "    xr.DataArray([i for i in range(720)],{'time':mf_ds.time}),\n",
+    "    mf_ds['fld_s00i024'].lat,\n",
+    "    mf_ds['fld_s00i024'].lon,\n",
+    "    input_core_dims=[['lat','lon'],[],[],['lat',],['lon',]],\n",
+    "    exclude_dims=set((\"lat\",\"lon\")),\n",
+    "    vectorize=True,\n",
+    "    dask=\"parallelized\"\n",
+    ")\n",
+    "#for i,f in enumerate(mf_ds['fld_s00i024']):\n",
+    "#    f.plot(vmin=260, vmax=350)\n",
+    "#    plt.savefig(f'/home/563/dr4292/animation/frame{i:04}.png')\n",
+    "#    plt.close()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "822038d3-438e-4c51-944d-9ede546d4443",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "out.compute()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e7534694-e579-4d97-90eb-1b485da7594d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!ffmpeg -framerate 10 -pattern_type glob -i '/home/563/dr4292/animation/frame*.png' -c:v libx264 -r 30 -pix_fmt yuv420p output.mp4"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python [conda env:analysis3-unstable]",
+   "language": "python",
+   "name": "conda-env-analysis3-unstable-py"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.14"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/Recipes/geopotential.ipynb b/Recipes/geopotential.ipynb
new file mode 100644
index 0000000..b5b2639
--- /dev/null
+++ b/Recipes/geopotential.ipynb
@@ -0,0 +1,3348 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "0437be3c-b72e-452f-afc8-a54b3a8c6408",
+   "metadata": {},
+   "source": [
+    "### Calculate geopotential from pressure & temperature data\n",
+    "\n",
+    "Calculates geopotential from pressure and temperature data for a single timestep over the entire AUS2200 domain. Can be used to provide geopotential more frequently that is output by the model. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "9a6fdf17-da72-4043-8c69-d2d63473c49d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import xarray as xr\n",
+    "from scipy.interpolate import interp1d\n",
+    "from scipy.integrate import trapezoid\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "from dask.distributed import Client"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "9bd6f7e2-3326-4ce3-82e6-2525665d5821",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "Rd = 287.1\n",
+    "g0 = 9.81\n",
+    "\n",
+    "specific_humidity_at_level = 'fld_s00i010'\n",
+    "pressure_at_level = 'fld_s00i408'\n",
+    "temperature_at_level = 'fld_s16i004'\n",
+    "\n",
+    "surface_pressure = 'fld_s00i409'\n",
+    "surface_temperature = 'fld_s00i024'\n",
+    "specific_humidity = 'fld_s03i237'\n",
+    "\n",
+    "plev19=np.array([100000, 92500, 85000, 70000,\n",
+    "        60000, 50000, 40000, 30000,\n",
+    "        25000, 20000, 15000, 10000,\n",
+    "        7000, 5000, 3000, 2000,\n",
+    "        1000, 500, 100],dtype=np.float32)\n",
+    "\n",
+    "def interp_and_integrate_over_pressure_with_surf(pres, var, surf_pres, surf_var, plev):\n",
+    "\n",
+    "    pres_with_surf = np.insert(pres,0,surf_pres)\n",
+    "    var_with_surf = np.insert(var,0,surf_var)\n",
+    "\n",
+    "    vint = interp1d(pres_with_surf,var_with_surf,kind=\"linear\",fill_value=\"extrapolate\")\n",
+    "    interped = vint(plev)\n",
+    "\n",
+    "    all_pres = np.zeros(len(pres_with_surf)+len(plev))\n",
+    "    all_fld  = np.zeros(len(pres_with_surf)+len(plev))\n",
+    "    plev_idx = np.zeros(len(plev),dtype=int)\n",
+    "    surf_idx = -1\n",
+    "    ### Now intersperse with original var\n",
+    "    i = 0\n",
+    "    j = 0\n",
+    "\n",
+    "    for _ in range(len(all_pres)):\n",
+    "        if j >= len(pres_with_surf):\n",
+    "            pres_test = -1\n",
+    "        else:\n",
+    "            pres_test = pres_with_surf[j]\n",
+    "        if i >= len(plev):\n",
+    "            plev_test = -1\n",
+    "        else:\n",
+    "            plev_test = plev[i]\n",
+    "        \n",
+    "        if plev_test > pres_test:\n",
+    "            if j == 0:\n",
+    "                all_pres[i+j] = 0\n",
+    "            else:\n",
+    "                all_pres[i+j] = plev_test\n",
+    "            all_fld[i+j] = interped[i]\n",
+    "            plev_idx[i] = i+j\n",
+    "            i+=1\n",
+    "        else:\n",
+    "            all_pres[i+j] = pres_test\n",
+    "            all_fld[i+j] = var_with_surf[j]\n",
+    "            if j == 0:\n",
+    "                surf_idx = i+j\n",
+    "            j+=1\n",
+    "    \n",
+    "    out_fld = np.zeros(len(plev_idx))\n",
+    "    for out_i,idx in enumerate(plev_idx):\n",
+    "        if idx < surf_idx:\n",
+    "            continue\n",
+    "        out_fld[out_i] = trapezoid(all_fld[surf_idx:idx+1],all_pres[surf_idx:idx+1]) * Rd * np.log(all_pres[idx]/all_pres[surf_idx]) / g0 / ( all_pres[surf_idx] - all_pres[idx] )\n",
+    "    return out_fld\n",
+    "\n",
+    "def interp_and_integrate_over_pressure(pres, var, plev):\n",
+    "\n",
+    "    vint = interp1d(pres,var,kind=\"linear\",fill_value=\"extrapolate\")\n",
+    "    interped = vint(plev)\n",
+    "\n",
+    "    all_pres = np.zeros(len(pres)+len(plev))\n",
+    "    all_fld  = np.zeros(len(pres)+len(plev))\n",
+    "    plev_idx = np.zeros(len(plev),dtype=int)\n",
+    "    surf_idx = -1\n",
+    "    ### Now intersperse with original var\n",
+    "    i = 0\n",
+    "    j = 0\n",
+    "\n",
+    "    for _ in range(len(all_pres)):\n",
+    "        if j >= len(pres):\n",
+    "            pres_test = -1\n",
+    "        else:\n",
+    "            pres_test = pres[j]\n",
+    "        if i >= len(plev):\n",
+    "            plev_test = -1\n",
+    "        else:\n",
+    "            plev_test = plev[i]\n",
+    "        \n",
+    "        if plev_test > pres_test:\n",
+    "            if j == 0:\n",
+    "                all_pres[i+j] = 0\n",
+    "            else:\n",
+    "                all_pres[i+j] = plev_test\n",
+    "            all_fld[i+j] = interped[i]\n",
+    "            plev_idx[i] = i+j\n",
+    "            i+=1\n",
+    "        else:\n",
+    "            all_pres[i+j] = pres_test\n",
+    "            all_fld[i+j] = var[j]\n",
+    "            if j == 0:\n",
+    "                surf_idx = i+j\n",
+    "            j+=1\n",
+    "    \n",
+    "    out_fld = np.zeros(len(plev_idx))\n",
+    "    for out_i,idx in enumerate(plev_idx):\n",
+    "        if idx < surf_idx:\n",
+    "            continue\n",
+    "        out_fld[out_i] = trapezoid(all_fld[surf_idx:idx+1],all_pres[surf_idx:idx+1]) * Rd * np.log(all_pres[idx]/all_pres[surf_idx]) / g0 / ( all_pres[surf_idx] - all_pres[idx] )\n",
+    "    return out_fld\n",
+    "### Tv = (1 + 0.618*specific_humidity)*temperature\n",
+    "\n",
+    "### delta_Z = Rd * Tv / g0 * ln(p1/p2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "9f34332e-48d4-4a81-8b0b-c57b18a3a152",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-08-22 12:18:47,923 - distributed.preloading - INFO - Creating preload: /g/data/hh5/public/apps/dask-optimiser/schedplugin.py\n",
+      "2024-08-22 12:18:47,925 - distributed.utils - INFO - Reload module schedplugin from .py file\n",
+      "2024-08-22 12:18:47,932 - distributed.preloading - INFO - Import preload module: /g/data/hh5/public/apps/dask-optimiser/schedplugin.py\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Modifying workers\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "    <div style=\"width: 24px; height: 24px; background-color: #e1e1e1; border: 3px solid #9D9D9D; border-radius: 5px; position: absolute;\"> </div>\n",
+       "    <div style=\"margin-left: 48px;\">\n",
+       "        <h3 style=\"margin-bottom: 0px;\">Client</h3>\n",
+       "        <p style=\"color: #9D9D9D; margin-bottom: 0px;\">Client-dd4a53fb-602c-11ef-ba3f-000007cafe80</p>\n",
+       "        <table style=\"width: 100%; text-align: left;\">\n",
+       "\n",
+       "        <tr>\n",
+       "        \n",
+       "            <td style=\"text-align: left;\"><strong>Connection method:</strong> Cluster object</td>\n",
+       "            <td style=\"text-align: left;\"><strong>Cluster type:</strong> distributed.LocalCluster</td>\n",
+       "        \n",
+       "        </tr>\n",
+       "\n",
+       "        \n",
+       "            <tr>\n",
+       "                <td style=\"text-align: left;\">\n",
+       "                    <strong>Dashboard: </strong> <a href=\"/node/gadi-cpu-spr-0693.gadi.nci.org.au/59916/proxy/8787/status\" target=\"_blank\">/node/gadi-cpu-spr-0693.gadi.nci.org.au/59916/proxy/8787/status</a>\n",
+       "                </td>\n",
+       "                <td style=\"text-align: left;\"></td>\n",
+       "            </tr>\n",
+       "        \n",
+       "\n",
+       "        </table>\n",
+       "\n",
+       "        \n",
+       "            <button style=\"margin-bottom: 12px;\" data-commandlinker-command=\"dask:populate-and-launch-layout\" data-commandlinker-args='{\"url\": \"/node/gadi-cpu-spr-0693.gadi.nci.org.au/59916/proxy/8787/status\" }'>\n",
+       "                Launch dashboard in JupyterLab\n",
+       "            </button>\n",
+       "        \n",
+       "\n",
+       "        \n",
+       "            <details>\n",
+       "            <summary style=\"margin-bottom: 20px;\"><h3 style=\"display: inline;\">Cluster Info</h3></summary>\n",
+       "            <div class=\"jp-RenderedHTMLCommon jp-RenderedHTML jp-mod-trusted jp-OutputArea-output\">\n",
+       "    <div style=\"width: 24px; height: 24px; background-color: #e1e1e1; border: 3px solid #9D9D9D; border-radius: 5px; position: absolute;\">\n",
+       "    </div>\n",
+       "    <div style=\"margin-left: 48px;\">\n",
+       "        <h3 style=\"margin-bottom: 0px; margin-top: 0px;\">LocalCluster</h3>\n",
+       "        <p style=\"color: #9D9D9D; margin-bottom: 0px;\">81583452</p>\n",
+       "        <table style=\"width: 100%; text-align: left;\">\n",
+       "            <tr>\n",
+       "                <td style=\"text-align: left;\">\n",
+       "                    <strong>Dashboard:</strong> <a href=\"/node/gadi-cpu-spr-0693.gadi.nci.org.au/59916/proxy/8787/status\" target=\"_blank\">/node/gadi-cpu-spr-0693.gadi.nci.org.au/59916/proxy/8787/status</a>\n",
+       "                </td>\n",
+       "                <td style=\"text-align: left;\">\n",
+       "                    <strong>Workers:</strong> 4\n",
+       "                </td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                <td style=\"text-align: left;\">\n",
+       "                    <strong>Total threads:</strong> 4\n",
+       "                </td>\n",
+       "                <td style=\"text-align: left;\">\n",
+       "                    <strong>Total memory:</strong> 0 B\n",
+       "                </td>\n",
+       "            </tr>\n",
+       "            \n",
+       "            <tr>\n",
+       "    <td style=\"text-align: left;\"><strong>Status:</strong> running</td>\n",
+       "    <td style=\"text-align: left;\"><strong>Using processes:</strong> True</td>\n",
+       "</tr>\n",
+       "\n",
+       "            \n",
+       "        </table>\n",
+       "\n",
+       "        <details>\n",
+       "            <summary style=\"margin-bottom: 20px;\">\n",
+       "                <h3 style=\"display: inline;\">Scheduler Info</h3>\n",
+       "            </summary>\n",
+       "\n",
+       "            <div style=\"\">\n",
+       "    <div>\n",
+       "        <div style=\"width: 24px; height: 24px; background-color: #FFF7E5; border: 3px solid #FF6132; border-radius: 5px; position: absolute;\"> </div>\n",
+       "        <div style=\"margin-left: 48px;\">\n",
+       "            <h3 style=\"margin-bottom: 0px;\">Scheduler</h3>\n",
+       "            <p style=\"color: #9D9D9D; margin-bottom: 0px;\">Scheduler-22e93173-d96f-4e10-ac23-a7e3a1f42346</p>\n",
+       "            <table style=\"width: 100%; text-align: left;\">\n",
+       "                <tr>\n",
+       "                    <td style=\"text-align: left;\">\n",
+       "                        <strong>Comm:</strong> tcp://127.0.0.1:35999\n",
+       "                    </td>\n",
+       "                    <td style=\"text-align: left;\">\n",
+       "                        <strong>Workers:</strong> 4\n",
+       "                    </td>\n",
+       "                </tr>\n",
+       "                <tr>\n",
+       "                    <td style=\"text-align: left;\">\n",
+       "                        <strong>Dashboard:</strong> <a href=\"/node/gadi-cpu-spr-0693.gadi.nci.org.au/59916/proxy/8787/status\" target=\"_blank\">/node/gadi-cpu-spr-0693.gadi.nci.org.au/59916/proxy/8787/status</a>\n",
+       "                    </td>\n",
+       "                    <td style=\"text-align: left;\">\n",
+       "                        <strong>Total threads:</strong> 4\n",
+       "                    </td>\n",
+       "                </tr>\n",
+       "                <tr>\n",
+       "                    <td style=\"text-align: left;\">\n",
+       "                        <strong>Started:</strong> Just now\n",
+       "                    </td>\n",
+       "                    <td style=\"text-align: left;\">\n",
+       "                        <strong>Total memory:</strong> 0 B\n",
+       "                    </td>\n",
+       "                </tr>\n",
+       "            </table>\n",
+       "        </div>\n",
+       "    </div>\n",
+       "\n",
+       "    <details style=\"margin-left: 48px;\">\n",
+       "        <summary style=\"margin-bottom: 20px;\">\n",
+       "            <h3 style=\"display: inline;\">Workers</h3>\n",
+       "        </summary>\n",
+       "\n",
+       "        \n",
+       "        <div style=\"margin-bottom: 20px;\">\n",
+       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
+       "            <div style=\"margin-left: 48px;\">\n",
+       "            <details>\n",
+       "                <summary>\n",
+       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 0</h4>\n",
+       "                </summary>\n",
+       "                <table style=\"width: 100%; text-align: left;\">\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Comm: </strong> tcp://127.0.0.1:45301\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Total threads: </strong> 1\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Dashboard: </strong> <a href=\"/node/gadi-cpu-spr-0693.gadi.nci.org.au/59916/proxy/42307/status\" target=\"_blank\">/node/gadi-cpu-spr-0693.gadi.nci.org.au/59916/proxy/42307/status</a>\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Memory: </strong> 0 B\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Nanny: </strong> tcp://127.0.0.1:35929\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\"></td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
+       "                            <strong>Local directory: </strong> /jobfs/123409378.gadi-pbs/dask-scratch-space/worker-eutv4y9o\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                </table>\n",
+       "            </details>\n",
+       "            </div>\n",
+       "        </div>\n",
+       "        \n",
+       "        <div style=\"margin-bottom: 20px;\">\n",
+       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
+       "            <div style=\"margin-left: 48px;\">\n",
+       "            <details>\n",
+       "                <summary>\n",
+       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 1</h4>\n",
+       "                </summary>\n",
+       "                <table style=\"width: 100%; text-align: left;\">\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Comm: </strong> tcp://127.0.0.1:39291\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Total threads: </strong> 1\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Dashboard: </strong> <a href=\"/node/gadi-cpu-spr-0693.gadi.nci.org.au/59916/proxy/41861/status\" target=\"_blank\">/node/gadi-cpu-spr-0693.gadi.nci.org.au/59916/proxy/41861/status</a>\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Memory: </strong> 0 B\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Nanny: </strong> tcp://127.0.0.1:39599\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\"></td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
+       "                            <strong>Local directory: </strong> /jobfs/123409378.gadi-pbs/dask-scratch-space/worker-32zpu3qv\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                </table>\n",
+       "            </details>\n",
+       "            </div>\n",
+       "        </div>\n",
+       "        \n",
+       "        <div style=\"margin-bottom: 20px;\">\n",
+       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
+       "            <div style=\"margin-left: 48px;\">\n",
+       "            <details>\n",
+       "                <summary>\n",
+       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 2</h4>\n",
+       "                </summary>\n",
+       "                <table style=\"width: 100%; text-align: left;\">\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Comm: </strong> tcp://127.0.0.1:39735\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Total threads: </strong> 1\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Dashboard: </strong> <a href=\"/node/gadi-cpu-spr-0693.gadi.nci.org.au/59916/proxy/36159/status\" target=\"_blank\">/node/gadi-cpu-spr-0693.gadi.nci.org.au/59916/proxy/36159/status</a>\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Memory: </strong> 0 B\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Nanny: </strong> tcp://127.0.0.1:46873\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\"></td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
+       "                            <strong>Local directory: </strong> /jobfs/123409378.gadi-pbs/dask-scratch-space/worker-j9beyj2d\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                </table>\n",
+       "            </details>\n",
+       "            </div>\n",
+       "        </div>\n",
+       "        \n",
+       "        <div style=\"margin-bottom: 20px;\">\n",
+       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
+       "            <div style=\"margin-left: 48px;\">\n",
+       "            <details>\n",
+       "                <summary>\n",
+       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 3</h4>\n",
+       "                </summary>\n",
+       "                <table style=\"width: 100%; text-align: left;\">\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Comm: </strong> tcp://127.0.0.1:37021\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Total threads: </strong> 1\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Dashboard: </strong> <a href=\"/node/gadi-cpu-spr-0693.gadi.nci.org.au/59916/proxy/45007/status\" target=\"_blank\">/node/gadi-cpu-spr-0693.gadi.nci.org.au/59916/proxy/45007/status</a>\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Memory: </strong> 0 B\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Nanny: </strong> tcp://127.0.0.1:35939\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\"></td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
+       "                            <strong>Local directory: </strong> /jobfs/123409378.gadi-pbs/dask-scratch-space/worker-h38ugnzm\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                </table>\n",
+       "            </details>\n",
+       "            </div>\n",
+       "        </div>\n",
+       "        \n",
+       "\n",
+       "    </details>\n",
+       "</div>\n",
+       "\n",
+       "        </details>\n",
+       "    </div>\n",
+       "</div>\n",
+       "            </details>\n",
+       "        \n",
+       "\n",
+       "    </div>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "<Client: 'tcp://127.0.0.1:35999' processes=4 threads=4, memory=19.00 GiB>"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "client=Client()\n",
+    "client"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "da0d1408-2891-4bae-9672-76699ce82118",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/g/data/hh5/public/apps/cms_conda/envs/analysis3-24.07/lib/python3.10/site-packages/xarray/core/dataset.py:277: UserWarning: The specified chunks separate the stored chunks along dimension \"lat\" starting at index 212. This could degrade performance. Instead, consider rechunking after loading.\n",
+      "  warnings.warn(\n",
+      "/g/data/hh5/public/apps/cms_conda/envs/analysis3-24.07/lib/python3.10/site-packages/xarray/core/dataset.py:277: UserWarning: The specified chunks separate the stored chunks along dimension \"lon_0\" starting at index 260. This could degrade performance. Instead, consider rechunking after loading.\n",
+      "  warnings.warn(\n"
+     ]
+    }
+   ],
+   "source": [
+    "#ds = xr.open_dataset(\"/g/data/hh5/tmp/AUS2200/flood22-continuous/atmos/umnsa_mdl_20220221T1400_1hr.nc\").sel(lat=-37.81, lon_0=144.96, method='nearest').isel(time=0)\n",
+    "#ds = xr.open_dataset(\"/g/data/hh5/tmp/AUS2200/flood22-continuous/atmos/umnsa_mdl_20220221T1400_1hr.nc\").sel(lat=-7, lon_0=146, method='nearest').isel(time=0)\n",
+    "ds = xr.open_dataset(\"/g/data/hh5/tmp/AUS2200/flood22-continuous/atmos/umnsa_mdl_20220221T1400_1hr.nc\",chunks={\"model_theta_level_number\":-1,\"lat\":212,\"lon_0\":260}).isel(time=0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "bd49d816-10e5-408a-b863-08e901d9c6ad",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/g/data/hh5/public/apps/cms_conda/envs/analysis3-24.07/lib/python3.10/site-packages/xarray/core/dataset.py:277: UserWarning: The specified chunks separate the stored chunks along dimension \"lat\" starting at index 212. This could degrade performance. Instead, consider rechunking after loading.\n",
+      "  warnings.warn(\n",
+      "/g/data/hh5/public/apps/cms_conda/envs/analysis3-24.07/lib/python3.10/site-packages/xarray/core/dataset.py:277: UserWarning: The specified chunks separate the stored chunks along dimension \"lon\" starting at index 260. This could degrade performance. Instead, consider rechunking after loading.\n",
+      "  warnings.warn(\n"
+     ]
+    }
+   ],
+   "source": [
+    "#ds3 = xr.open_dataset(\"/g/data/hh5/tmp/AUS2200/flood22-continuous/atmos/umnsa_spec_20220221T1400_10min.nc\").sel(lat=-37.81, lon=144.96, method='nearest').isel(time=5)\n",
+    "#ds3 = xr.open_dataset(\"/g/data/hh5/tmp/AUS2200/flood22-continuous/atmos/umnsa_spec_20220221T1400_10min.nc\").sel(lat=-7, lon=146, method='nearest').isel(time=5)\n",
+    "ds3 = xr.open_dataset(\"/g/data/hh5/tmp/AUS2200/flood22-continuous/atmos/umnsa_spec_20220221T1400_10min.nc\",chunks={\"lat\":212,\"lon\":260}).isel(time=5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "2c165f43-abec-4294-99f5-0199f97faa8b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (model_theta_level_number: 70, lat: 2120, lon: 2600)&gt; Size: 2GB\n",
+       "dask.array&lt;mul, shape=(70, 2120, 2600), dtype=float32, chunksize=(70, 212, 260), chunktype=numpy.ndarray&gt;\n",
+       "Coordinates:\n",
+       "    time                      datetime64[ns] 8B 2022-02-21T15:00:00\n",
+       "  * lat                       (lat) float64 17kB -48.79 -48.77 ... -6.852 -6.832\n",
+       "  * lon                       (lon) float64 21kB 107.5 107.5 ... 159.0 159.0\n",
+       "  * model_theta_level_number  (model_theta_level_number) int32 280B 1 2 ... 70\n",
+       "    theta_level_height        (model_theta_level_number) float64 560B dask.array&lt;chunksize=(70,), meta=np.ndarray&gt;\n",
+       "    sigma_theta               (model_theta_level_number) float64 560B dask.array&lt;chunksize=(70,), meta=np.ndarray&gt;</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>model_theta_level_number</span>: 70</li><li><span class='xr-has-index'>lat</span>: 2120</li><li><span class='xr-has-index'>lon</span>: 2600</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-8233223f-4cba-449d-8aeb-2cbe0a993c16' class='xr-array-in' type='checkbox' checked><label for='section-8233223f-4cba-449d-8aeb-2cbe0a993c16' 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>dask.array&lt;chunksize=(70, 212, 260), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 1.44 GiB </td>\n",
+       "                        <td> 14.72 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (70, 2120, 2600) </td>\n",
+       "                        <td> (70, 212, 260) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 100 chunks in 9 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"198\" height=\"165\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
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+       "\n",
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+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"88.086386\" y=\"135.932540\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2600</text>\n",
+       "  <text x=\"168.086386\" y=\"67.009463\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,168.086386,67.009463)\">2120</text>\n",
+       "  <text x=\"9.043193\" y=\"126.889347\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,9.043193,126.889347)\">70</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></div></li><li class='xr-section-item'><input id='section-e5827d75-75e9-4540-8afd-049256510f76' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e5827d75-75e9-4540-8afd-049256510f76' class='xr-section-summary' >Coordinates: <span>(6)</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>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-02-21T15:00:00</div><input id='attrs-9549a85a-e6e1-4f91-80be-6203329a67f9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9549a85a-e6e1-4f91-80be-6203329a67f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-20811872-3a63-4044-9ff1-6e474817516c' class='xr-var-data-in' type='checkbox'><label for='data-20811872-3a63-4044-9ff1-6e474817516c' 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>axis :</span></dt><dd>T</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array(&#x27;2022-02-21T15:00:00.000000000&#x27;, dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-48.79 -48.77 ... -6.852 -6.832</div><input id='attrs-6852817d-6a0c-4865-a8ec-68664efd2c88' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6852817d-6a0c-4865-a8ec-68664efd2c88' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0e5343fa-8f0f-4448-ba38-f8ad8d2bb73b' class='xr-var-data-in' type='checkbox'><label for='data-0e5343fa-8f0f-4448-ba38-f8ad8d2bb73b' 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>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-48.787998, -48.7682  , -48.748398, ...,  -6.871399,  -6.851597,\n",
+       "        -6.831799])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>107.5 107.5 107.6 ... 159.0 159.0</div><input id='attrs-535faac0-1717-413d-9e5a-339c1be8c859' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-535faac0-1717-413d-9e5a-339c1be8c859' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6033127c-e175-4784-8697-a47bc8e79683' class='xr-var-data-in' type='checkbox'><label for='data-6033127c-e175-4784-8697-a47bc8e79683' 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>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_0_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([107.519997, 107.539795, 107.559593, ..., 158.940598, 158.960388,\n",
+       "       158.980194])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>model_theta_level_number</span></div><div class='xr-var-dims'>(model_theta_level_number)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4 5 6 7 ... 65 66 67 68 69 70</div><input id='attrs-0346bcea-5b11-46fa-9c46-e4a1037ea990' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0346bcea-5b11-46fa-9c46-e4a1037ea990' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-472e4ba7-82e6-4930-8cd7-08e61d3a8ed5' class='xr-var-data-in' type='checkbox'><label for='data-472e4ba7-82e6-4930-8cd7-08e61d3a8ed5' 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>axis :</span></dt><dd>Z</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>standard_name :</span></dt><dd>model_level_number</dd><dt><span>positive :</span></dt><dd>up</dd></dl></div><div class='xr-var-data'><pre>array([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17, 18,\n",
+       "       19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36,\n",
+       "       37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54,\n",
+       "       55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70],\n",
+       "      dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>theta_level_height</span></div><div class='xr-var-dims'>(model_theta_level_number)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(70,), meta=np.ndarray&gt;</div><input id='attrs-2bc2584b-d1c1-4010-b8d7-d4f1219c4790' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2bc2584b-d1c1-4010-b8d7-d4f1219c4790' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3c2606a6-913f-4b8d-8181-bd09942124d9' class='xr-var-data-in' type='checkbox'><label for='data-3c2606a6-913f-4b8d-8181-bd09942124d9' 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>bounds :</span></dt><dd>theta_level_height_bnds</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>level_height</dd><dt><span>positive :</span></dt><dd>up</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 560 B </td>\n",
+       "                        <td> 560 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (70,) </td>\n",
+       "                        <td> (70,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"77\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"27\" x2=\"120\" y2=\"27\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"27\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"27\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,27.20110529785043 0.0,27.20110529785043\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"47.201105\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >70</text>\n",
+       "  <text x=\"140.000000\" y=\"13.600553\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,13.600553)\">1</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sigma_theta</span></div><div class='xr-var-dims'>(model_theta_level_number)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(70,), meta=np.ndarray&gt;</div><input id='attrs-c5f19cad-4f13-4b52-bb64-582f8728bded' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c5f19cad-4f13-4b52-bb64-582f8728bded' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-550d9c16-2b8a-4089-984f-3723f86b0d4a' class='xr-var-data-in' type='checkbox'><label for='data-550d9c16-2b8a-4089-984f-3723f86b0d4a' 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>bounds :</span></dt><dd>sigma_theta_bnds</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>sigma</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 560 B </td>\n",
+       "                        <td> 560 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (70,) </td>\n",
+       "                        <td> (70,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"77\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"27\" x2=\"120\" y2=\"27\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"27\" style=\"stroke-width:2\" />\n",
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+       "\n",
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+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"47.201105\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >70</text>\n",
+       "  <text x=\"140.000000\" y=\"13.600553\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,13.600553)\">1</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-419cbb47-88a4-4def-a430-62c7f4339fd4' class='xr-section-summary-in' type='checkbox'  ><label for='section-419cbb47-88a4-4def-a430-62c7f4339fd4' class='xr-section-summary' >Indexes: <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-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ad90eca0-4336-43c5-b863-e658d0a45d77' class='xr-index-data-in' type='checkbox'/><label for='index-ad90eca0-4336-43c5-b863-e658d0a45d77' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ -48.78799819946289,   -48.7681999206543,  -48.74839782714844,\n",
+       "       -48.728599548339844, -48.708797454833984,  -48.68899917602539,\n",
+       "        -48.66919708251953,  -48.64939880371094,  -48.62959671020508,\n",
+       "       -48.609798431396484,\n",
+       "       ...\n",
+       "        -7.009998321533203,  -6.990200042724609,   -6.97039794921875,\n",
+       "        -6.950599670410156,  -6.930797576904297,  -6.910999298095703,\n",
+       "        -6.891197204589844,   -6.87139892578125,  -6.851596832275391,\n",
+       "        -6.831798553466797],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=2120))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4af22f43-959b-4efb-8e43-7f5fb1b235f4' class='xr-index-data-in' type='checkbox'/><label for='index-4af22f43-959b-4efb-8e43-7f5fb1b235f4' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 107.5199966430664,   107.539794921875,  107.5595932006836,\n",
+       "       107.57939910888672, 107.59919738769531,  107.6189956665039,\n",
+       "        107.6387939453125, 107.65859985351562, 107.67839813232422,\n",
+       "       107.69819641113281,\n",
+       "       ...\n",
+       "         158.802001953125, 158.82179260253906,  158.8415985107422,\n",
+       "       158.86138916015625, 158.88119506835938,  158.9010009765625,\n",
+       "       158.92079162597656,  158.9405975341797, 158.96038818359375,\n",
+       "       158.98019409179688],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=2600))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>model_theta_level_number</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-465ee324-f4b2-4154-9540-ee3df5e31956' class='xr-index-data-in' type='checkbox'/><label for='index-465ee324-f4b2-4154-9540-ee3df5e31956' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17, 18,\n",
+       "       19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36,\n",
+       "       37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54,\n",
+       "       55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70],\n",
+       "      dtype=&#x27;int32&#x27;, name=&#x27;model_theta_level_number&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-74a68e11-7093-4c88-9265-2e0378fa700d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-74a68e11-7093-4c88-9265-2e0378fa700d' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.DataArray (model_theta_level_number: 70, lat: 2120, lon: 2600)> Size: 2GB\n",
+       "dask.array<mul, shape=(70, 2120, 2600), dtype=float32, chunksize=(70, 212, 260), chunktype=numpy.ndarray>\n",
+       "Coordinates:\n",
+       "    time                      datetime64[ns] 8B 2022-02-21T15:00:00\n",
+       "  * lat                       (lat) float64 17kB -48.79 -48.77 ... -6.852 -6.832\n",
+       "  * lon                       (lon) float64 21kB 107.5 107.5 ... 159.0 159.0\n",
+       "  * model_theta_level_number  (model_theta_level_number) int32 280B 1 2 ... 70\n",
+       "    theta_level_height        (model_theta_level_number) float64 560B dask.array<chunksize=(70,), meta=np.ndarray>\n",
+       "    sigma_theta               (model_theta_level_number) float64 560B dask.array<chunksize=(70,), meta=np.ndarray>"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_tv = (1 + 0.618 * ds[specific_humidity_at_level])*ds[temperature_at_level]\n",
+    "ds_tv = ds_tv.rename({'lon_0':'lon'})\n",
+    "ds_tv"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "9f916e51-c49a-40bb-b29f-c8521696243f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (lat: 2120, lon: 2600)&gt; Size: 22MB\n",
+       "dask.array&lt;mul, shape=(2120, 2600), dtype=float32, chunksize=(212, 260), chunktype=numpy.ndarray&gt;\n",
+       "Coordinates:\n",
+       "    time                      datetime64[ns] 8B 2022-02-21T15:00:00\n",
+       "  * lat                       (lat) float64 17kB -48.79 -48.77 ... -6.852 -6.832\n",
+       "  * lon                       (lon) float64 21kB 107.5 107.5 ... 159.0 159.0\n",
+       "    theta_level_height        float64 8B 5.0\n",
+       "    model_theta_level_number  int32 4B 1\n",
+       "    sigma_theta               float64 8B 0.9994\n",
+       "    height                    float64 8B 10.0\n",
+       "    height_0                  float64 8B 1.5</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 2120</li><li><span class='xr-has-index'>lon</span>: 2600</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-039912f2-f7a7-4d26-a5ba-890768822deb' class='xr-array-in' type='checkbox' checked><label for='section-039912f2-f7a7-4d26-a5ba-890768822deb' 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>dask.array&lt;chunksize=(212, 260), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 21.03 MiB </td>\n",
+       "                        <td> 215.31 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (2120, 2600) </td>\n",
+       "                        <td> (212, 260) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 100 chunks in 9 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"147\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"29\" x2=\"120\" y2=\"29\" />\n",
+       "  <line x1=\"0\" y1=\"39\" x2=\"120\" y2=\"39\" />\n",
+       "  <line x1=\"0\" y1=\"48\" x2=\"120\" y2=\"48\" />\n",
+       "  <line x1=\"0\" y1=\"58\" x2=\"120\" y2=\"58\" />\n",
+       "  <line x1=\"0\" y1=\"68\" x2=\"120\" y2=\"68\" />\n",
+       "  <line x1=\"0\" y1=\"78\" x2=\"120\" y2=\"78\" />\n",
+       "  <line x1=\"0\" y1=\"88\" x2=\"120\" y2=\"88\" />\n",
+       "  <line x1=\"0\" y1=\"97\" x2=\"120\" y2=\"97\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"97\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"12\" y1=\"0\" x2=\"12\" y2=\"97\" />\n",
+       "  <line x1=\"24\" y1=\"0\" x2=\"24\" y2=\"97\" />\n",
+       "  <line x1=\"36\" y1=\"0\" x2=\"36\" y2=\"97\" />\n",
+       "  <line x1=\"48\" y1=\"0\" x2=\"48\" y2=\"97\" />\n",
+       "  <line x1=\"60\" y1=\"0\" x2=\"60\" y2=\"97\" />\n",
+       "  <line x1=\"72\" y1=\"0\" x2=\"72\" y2=\"97\" />\n",
+       "  <line x1=\"84\" y1=\"0\" x2=\"84\" y2=\"97\" />\n",
+       "  <line x1=\"96\" y1=\"0\" x2=\"96\" y2=\"97\" />\n",
+       "  <line x1=\"108\" y1=\"0\" x2=\"108\" y2=\"97\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"97\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,97.84615384615385 0.0,97.84615384615385\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"117.846154\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2600</text>\n",
+       "  <text x=\"140.000000\" y=\"48.923077\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,48.923077)\">2120</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></div></li><li class='xr-section-item'><input id='section-fbb2bf05-0aec-4c45-ad59-c8d7aa983014' class='xr-section-summary-in' type='checkbox'  checked><label for='section-fbb2bf05-0aec-4c45-ad59-c8d7aa983014' class='xr-section-summary' >Coordinates: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-02-21T15:00:00</div><input id='attrs-72eafbb7-b8bc-430a-a9b3-92459515b08e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-72eafbb7-b8bc-430a-a9b3-92459515b08e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8b1411c1-7ada-434b-9992-69d1deda080e' class='xr-var-data-in' type='checkbox'><label for='data-8b1411c1-7ada-434b-9992-69d1deda080e' 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>axis :</span></dt><dd>T</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array(&#x27;2022-02-21T15:00:00.000000000&#x27;, dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-48.79 -48.77 ... -6.852 -6.832</div><input id='attrs-82d3b32d-0c47-4cfd-a739-6c34435fe28e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-82d3b32d-0c47-4cfd-a739-6c34435fe28e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-35f4a2c7-b611-4b7b-a653-9d65e3b51eed' class='xr-var-data-in' type='checkbox'><label for='data-35f4a2c7-b611-4b7b-a653-9d65e3b51eed' 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>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-48.787998, -48.7682  , -48.748398, ...,  -6.871399,  -6.851597,\n",
+       "        -6.831799])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>107.5 107.5 107.6 ... 159.0 159.0</div><input id='attrs-7d3b3b26-c72e-4f17-89f2-d7370338865d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7d3b3b26-c72e-4f17-89f2-d7370338865d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ece7d1fe-6772-40a9-a6a7-f65c174e66fb' class='xr-var-data-in' type='checkbox'><label for='data-ece7d1fe-6772-40a9-a6a7-f65c174e66fb' 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>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([107.519997, 107.539795, 107.559593, ..., 158.940598, 158.960388,\n",
+       "       158.980194])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>theta_level_height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.0</div><input id='attrs-82fdf9ad-9306-42e6-a58d-72fc49bb4bed' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-82fdf9ad-9306-42e6-a58d-72fc49bb4bed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-73b72a52-071d-4d2e-a9f2-4ba8a721fd90' class='xr-var-data-in' type='checkbox'><label for='data-73b72a52-071d-4d2e-a9f2-4ba8a721fd90' 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>bounds :</span></dt><dd>theta_level_height_bnds</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>level_height</dd><dt><span>positive :</span></dt><dd>up</dd></dl></div><div class='xr-var-data'><pre>array(5.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>model_theta_level_number</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1</div><input id='attrs-248be8d9-7947-48df-b812-1e904afbe605' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-248be8d9-7947-48df-b812-1e904afbe605' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fe7cf067-b8af-49eb-975f-91b397b473a3' class='xr-var-data-in' type='checkbox'><label for='data-fe7cf067-b8af-49eb-975f-91b397b473a3' 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>1</dd><dt><span>standard_name :</span></dt><dd>model_level_number</dd><dt><span>positive :</span></dt><dd>up</dd></dl></div><div class='xr-var-data'><pre>array(1, dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sigma_theta</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.9994</div><input id='attrs-38eb9731-c2cb-412a-b2f7-dbb81e4c9598' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-38eb9731-c2cb-412a-b2f7-dbb81e4c9598' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-803a2a8b-8b14-4ea9-98be-b488efdbf91c' class='xr-var-data-in' type='checkbox'><label for='data-803a2a8b-8b14-4ea9-98be-b488efdbf91c' 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>bounds :</span></dt><dd>sigma_theta_bnds</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>sigma</dd></dl></div><div class='xr-var-data'><pre>array(0.99942381)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>10.0</div><input id='attrs-10ad1814-5b78-487e-8647-f0da70947e2e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-10ad1814-5b78-487e-8647-f0da70947e2e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-17b1552a-a3b1-48fd-9c7f-502b691b5836' class='xr-var-data-in' type='checkbox'><label for='data-17b1552a-a3b1-48fd-9c7f-502b691b5836' 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>m</dd><dt><span>standard_name :</span></dt><dd>height</dd><dt><span>positive :</span></dt><dd>up</dd></dl></div><div class='xr-var-data'><pre>array(10.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>height_0</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.5</div><input id='attrs-77c15506-982c-4677-8eb1-fd66f6eee5a5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-77c15506-982c-4677-8eb1-fd66f6eee5a5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d2a96afa-ffef-47ba-b3a6-ec5d8fef1e68' class='xr-var-data-in' type='checkbox'><label for='data-d2a96afa-ffef-47ba-b3a6-ec5d8fef1e68' 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>m</dd><dt><span>standard_name :</span></dt><dd>height</dd><dt><span>positive :</span></dt><dd>up</dd></dl></div><div class='xr-var-data'><pre>array(1.5)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ecd873c7-d6d2-4b4b-8afe-0b386c5684a2' class='xr-section-summary-in' type='checkbox'  ><label for='section-ecd873c7-d6d2-4b4b-8afe-0b386c5684a2' class='xr-section-summary' >Indexes: <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-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-da4dde19-6671-4422-acfd-7c0f1ad61364' class='xr-index-data-in' type='checkbox'/><label for='index-da4dde19-6671-4422-acfd-7c0f1ad61364' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ -48.78799819946289,   -48.7681999206543,  -48.74839782714844,\n",
+       "       -48.728599548339844, -48.708797454833984,  -48.68899917602539,\n",
+       "        -48.66919708251953,  -48.64939880371094,  -48.62959671020508,\n",
+       "       -48.609798431396484,\n",
+       "       ...\n",
+       "        -7.009998321533203,  -6.990200042724609,   -6.97039794921875,\n",
+       "        -6.950599670410156,  -6.930797576904297,  -6.910999298095703,\n",
+       "        -6.891197204589844,   -6.87139892578125,  -6.851596832275391,\n",
+       "        -6.831798553466797],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=2120))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-643cb7fb-5419-4ec2-a17f-ae9552a5ed3b' class='xr-index-data-in' type='checkbox'/><label for='index-643cb7fb-5419-4ec2-a17f-ae9552a5ed3b' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 107.5199966430664,   107.539794921875,  107.5595932006836,\n",
+       "       107.57939910888672, 107.59919738769531,  107.6189956665039,\n",
+       "        107.6387939453125, 107.65859985351562, 107.67839813232422,\n",
+       "       107.69819641113281,\n",
+       "       ...\n",
+       "         158.802001953125, 158.82179260253906,  158.8415985107422,\n",
+       "       158.86138916015625, 158.88119506835938,  158.9010009765625,\n",
+       "       158.92079162597656,  158.9405975341797, 158.96038818359375,\n",
+       "       158.98019409179688],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=2600))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8512e8ae-d82e-4614-9199-0ce2cdf34a29' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-8512e8ae-d82e-4614-9199-0ce2cdf34a29' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.DataArray (lat: 2120, lon: 2600)> Size: 22MB\n",
+       "dask.array<mul, shape=(2120, 2600), dtype=float32, chunksize=(212, 260), chunktype=numpy.ndarray>\n",
+       "Coordinates:\n",
+       "    time                      datetime64[ns] 8B 2022-02-21T15:00:00\n",
+       "  * lat                       (lat) float64 17kB -48.79 -48.77 ... -6.852 -6.832\n",
+       "  * lon                       (lon) float64 21kB 107.5 107.5 ... 159.0 159.0\n",
+       "    theta_level_height        float64 8B 5.0\n",
+       "    model_theta_level_number  int32 4B 1\n",
+       "    sigma_theta               float64 8B 0.9994\n",
+       "    height                    float64 8B 10.0\n",
+       "    height_0                  float64 8B 1.5"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tv_surf = (1 + 0.618 * ds3[specific_humidity]) * ds3[surface_temperature]\n",
+    "tv_surf"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "f64e1a05-969a-4fd8-ace1-fcd5d3a6a79b",
+   "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",
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+       "</defs>\n",
+       "</svg>\n",
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+       " */\n",
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+       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
+       "  --xr-background-color: var(--jp-layout-color0, white);\n",
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+       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
+       "}\n",
+       "\n",
+       "html[theme=dark],\n",
+       "html[data-theme=dark],\n",
+       "body[data-theme=dark],\n",
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+       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
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+       "  --xr-background-color: #111111;\n",
+       "  --xr-background-color-row-even: #111111;\n",
+       "  --xr-background-color-row-odd: #313131;\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: '►';\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: '▼';\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: '(';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: ')';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: ',';\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;fld_s00i409&#x27; (lat: 2120, lon: 2600)&gt; Size: 22MB\n",
+       "dask.array&lt;getitem, shape=(2120, 2600), dtype=float32, chunksize=(212, 260), chunktype=numpy.ndarray&gt;\n",
+       "Coordinates:\n",
+       "    time                      datetime64[ns] 8B 2022-02-21T15:00:00\n",
+       "  * lat                       (lat) float64 17kB -48.79 -48.77 ... -6.852 -6.832\n",
+       "  * lon                       (lon) float64 21kB 107.5 107.5 ... 159.0 159.0\n",
+       "    theta_level_height        float64 8B ...\n",
+       "    model_theta_level_number  int32 4B ...\n",
+       "    sigma_theta               float64 8B ...\n",
+       "    height                    float64 8B ...\n",
+       "    height_0                  float64 8B ...\n",
+       "Attributes:\n",
+       "    standard_name:    surface_air_pressure\n",
+       "    long_name:        SURFACE PRESSURE AFTER TIMESTEP\n",
+       "    units:            Pa\n",
+       "    um_stash_source:  m01s00i409\n",
+       "    grid_mapping:     latitude_longitude</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'fld_s00i409'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 2120</li><li><span class='xr-has-index'>lon</span>: 2600</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-040b301b-6fc2-4acd-a127-c253b60dc022' class='xr-array-in' type='checkbox' checked><label for='section-040b301b-6fc2-4acd-a127-c253b60dc022' 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>dask.array&lt;chunksize=(212, 260), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 21.03 MiB </td>\n",
+       "                        <td> 215.31 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (2120, 2600) </td>\n",
+       "                        <td> (212, 260) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 100 chunks in 3 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
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+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></div></li><li class='xr-section-item'><input id='section-4862528a-2468-43c4-96c8-8bde82a523d8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4862528a-2468-43c4-96c8-8bde82a523d8' class='xr-section-summary' >Coordinates: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-02-21T15:00:00</div><input id='attrs-8692aa92-b9e7-40f0-945d-f266a32ae0c8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8692aa92-b9e7-40f0-945d-f266a32ae0c8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eaad7e88-5d96-4fb9-b48b-df1ba6ff7d10' class='xr-var-data-in' type='checkbox'><label for='data-eaad7e88-5d96-4fb9-b48b-df1ba6ff7d10' 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>axis :</span></dt><dd>T</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array(&#x27;2022-02-21T15:00:00.000000000&#x27;, dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-48.79 -48.77 ... -6.852 -6.832</div><input id='attrs-97429d9d-c1ec-448b-8c87-73b625bc7f07' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-97429d9d-c1ec-448b-8c87-73b625bc7f07' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5c366032-a544-4c82-853d-3a9b61f73783' class='xr-var-data-in' type='checkbox'><label for='data-5c366032-a544-4c82-853d-3a9b61f73783' 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>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-48.787998, -48.7682  , -48.748398, ...,  -6.871399,  -6.851597,\n",
+       "        -6.831799])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>107.5 107.5 107.6 ... 159.0 159.0</div><input id='attrs-f6181137-7f3a-43a1-b027-2b6497d34d1e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f6181137-7f3a-43a1-b027-2b6497d34d1e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dbe263c6-a8a3-431d-b42e-37c4ee6f7759' class='xr-var-data-in' type='checkbox'><label for='data-dbe263c6-a8a3-431d-b42e-37c4ee6f7759' 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>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([107.519997, 107.539795, 107.559593, ..., 158.940598, 158.960388,\n",
+       "       158.980194])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>theta_level_height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-eec2f439-0b8a-4aa3-a603-59938d78f78c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eec2f439-0b8a-4aa3-a603-59938d78f78c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fce9e13f-1403-46cf-a3a9-c96c88e41b03' class='xr-var-data-in' type='checkbox'><label for='data-fce9e13f-1403-46cf-a3a9-c96c88e41b03' 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>bounds :</span></dt><dd>theta_level_height_bnds</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>level_height</dd><dt><span>positive :</span></dt><dd>up</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>model_theta_level_number</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-815161a9-9666-406b-84e6-455685f4bebf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-815161a9-9666-406b-84e6-455685f4bebf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ab41623c-aa69-4b98-b8c6-196c22c271f9' class='xr-var-data-in' type='checkbox'><label for='data-ab41623c-aa69-4b98-b8c6-196c22c271f9' 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>1</dd><dt><span>standard_name :</span></dt><dd>model_level_number</dd><dt><span>positive :</span></dt><dd>up</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=int32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sigma_theta</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-64428e9c-6af6-4417-8a97-a7f77621eeec' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-64428e9c-6af6-4417-8a97-a7f77621eeec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3d340e89-5fe9-410e-892d-fa55b9b8e4f0' class='xr-var-data-in' type='checkbox'><label for='data-3d340e89-5fe9-410e-892d-fa55b9b8e4f0' 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>bounds :</span></dt><dd>sigma_theta_bnds</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>sigma</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-55ccda3b-4d3e-4770-84ce-a3ca8db91f20' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-55ccda3b-4d3e-4770-84ce-a3ca8db91f20' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-556888d0-50b9-4532-af33-09cd0d21fe06' class='xr-var-data-in' type='checkbox'><label for='data-556888d0-50b9-4532-af33-09cd0d21fe06' 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>m</dd><dt><span>standard_name :</span></dt><dd>height</dd><dt><span>positive :</span></dt><dd>up</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>height_0</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-2aad447b-d9f3-4385-8d1f-7dda6beb8081' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2aad447b-d9f3-4385-8d1f-7dda6beb8081' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3a6a8de1-6122-4c68-861a-c55e1c2b473c' class='xr-var-data-in' type='checkbox'><label for='data-3a6a8de1-6122-4c68-861a-c55e1c2b473c' 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>m</dd><dt><span>standard_name :</span></dt><dd>height</dd><dt><span>positive :</span></dt><dd>up</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b0f33c23-08da-4168-92a2-b355f66d975f' class='xr-section-summary-in' type='checkbox'  ><label for='section-b0f33c23-08da-4168-92a2-b355f66d975f' class='xr-section-summary' >Indexes: <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-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-1d95d933-f385-43c2-a47d-450fe6d0d37c' class='xr-index-data-in' type='checkbox'/><label for='index-1d95d933-f385-43c2-a47d-450fe6d0d37c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ -48.78799819946289,   -48.7681999206543,  -48.74839782714844,\n",
+       "       -48.728599548339844, -48.708797454833984,  -48.68899917602539,\n",
+       "        -48.66919708251953,  -48.64939880371094,  -48.62959671020508,\n",
+       "       -48.609798431396484,\n",
+       "       ...\n",
+       "        -7.009998321533203,  -6.990200042724609,   -6.97039794921875,\n",
+       "        -6.950599670410156,  -6.930797576904297,  -6.910999298095703,\n",
+       "        -6.891197204589844,   -6.87139892578125,  -6.851596832275391,\n",
+       "        -6.831798553466797],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=2120))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-42305a5b-85b7-4950-bde0-6b471cf2e1e8' class='xr-index-data-in' type='checkbox'/><label for='index-42305a5b-85b7-4950-bde0-6b471cf2e1e8' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 107.5199966430664,   107.539794921875,  107.5595932006836,\n",
+       "       107.57939910888672, 107.59919738769531,  107.6189956665039,\n",
+       "        107.6387939453125, 107.65859985351562, 107.67839813232422,\n",
+       "       107.69819641113281,\n",
+       "       ...\n",
+       "         158.802001953125, 158.82179260253906,  158.8415985107422,\n",
+       "       158.86138916015625, 158.88119506835938,  158.9010009765625,\n",
+       "       158.92079162597656,  158.9405975341797, 158.96038818359375,\n",
+       "       158.98019409179688],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=2600))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-02c33eb8-e9a1-4e4d-a097-2e9b0d9b71f6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-02c33eb8-e9a1-4e4d-a097-2e9b0d9b71f6' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>surface_air_pressure</dd><dt><span>long_name :</span></dt><dd>SURFACE PRESSURE AFTER TIMESTEP</dd><dt><span>units :</span></dt><dd>Pa</dd><dt><span>um_stash_source :</span></dt><dd>m01s00i409</dd><dt><span>grid_mapping :</span></dt><dd>latitude_longitude</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.DataArray 'fld_s00i409' (lat: 2120, lon: 2600)> Size: 22MB\n",
+       "dask.array<getitem, shape=(2120, 2600), dtype=float32, chunksize=(212, 260), chunktype=numpy.ndarray>\n",
+       "Coordinates:\n",
+       "    time                      datetime64[ns] 8B 2022-02-21T15:00:00\n",
+       "  * lat                       (lat) float64 17kB -48.79 -48.77 ... -6.852 -6.832\n",
+       "  * lon                       (lon) float64 21kB 107.5 107.5 ... 159.0 159.0\n",
+       "    theta_level_height        float64 8B ...\n",
+       "    model_theta_level_number  int32 4B ...\n",
+       "    sigma_theta               float64 8B ...\n",
+       "    height                    float64 8B ...\n",
+       "    height_0                  float64 8B ...\n",
+       "Attributes:\n",
+       "    standard_name:    surface_air_pressure\n",
+       "    long_name:        SURFACE PRESSURE AFTER TIMESTEP\n",
+       "    units:            Pa\n",
+       "    um_stash_source:  m01s00i409\n",
+       "    grid_mapping:     latitude_longitude"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "surf_pres = ds3[surface_pressure]\n",
+    "surf_pres"
+   ]
+  },
+  {
+   "cell_type": "raw",
+   "id": "9af18a44-ff23-4236-8fc3-30aa9d4cfda5",
+   "metadata": {},
+   "source": [
+    "ds_tv_pl = xr.apply_ufunc(\n",
+    "    interp_and_integrate_over_pressure_with_surf,\n",
+    "    ds[pressure_at_level].rename({'lon_0':'lon'}),\n",
+    "    ds_tv,\n",
+    "    surf_pres,\n",
+    "    tv_surf,\n",
+    "    plev19,\n",
+    "    input_core_dims=[[\"model_theta_level_number\"],[\"model_theta_level_number\"],[],[],[\"pressure_level\"]],\n",
+    "    output_core_dims=[ [\"pressure_level\"] ],\n",
+    "    exclude_dims=set((\"model_theta_level_number\",)),\n",
+    "    vectorize=True,\n",
+    "    dask=\"parallelized\"\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "20363ba2-6ea7-4882-82dd-d171d70b2930",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ds_tv_pl = xr.apply_ufunc(\n",
+    "    interp_and_integrate_over_pressure,\n",
+    "    ds[pressure_at_level].rename({'lon_0':'lon'}),\n",
+    "    ds_tv,\n",
+    "    plev19,\n",
+    "    input_core_dims=[[\"model_theta_level_number\"],[\"model_theta_level_number\"],[\"pressure_level\"]],\n",
+    "    output_core_dims=[ [\"pressure_level\"] ],\n",
+    "    exclude_dims=set((\"model_theta_level_number\",)),\n",
+    "    vectorize=True,\n",
+    "    dask=\"parallelized\"\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "017bc49a-f70d-461e-a354-836e4fbc20e1",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "html[theme=dark],\n",
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+       "body[data-theme=dark],\n",
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+       "  --xr-background-color-row-even: #111111;\n",
+       "  --xr-background-color-row-odd: #313131;\n",
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+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
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+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: '►';\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: '▼';\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: '(';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: ')';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: ',';\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (lat: 2120, lon: 2600, pressure_level: 19)&gt; Size: 838MB\n",
+       "dask.array&lt;transpose, shape=(2120, 2600, 19), dtype=float64, chunksize=(212, 260, 19), chunktype=numpy.ndarray&gt;\n",
+       "Coordinates:\n",
+       "    time     datetime64[ns] 8B 2022-02-21T15:00:00\n",
+       "  * lat      (lat) float64 17kB -48.79 -48.77 -48.75 ... -6.871 -6.852 -6.832\n",
+       "  * lon      (lon) float64 21kB 107.5 107.5 107.6 107.6 ... 158.9 159.0 159.0\n",
+       "Dimensions without coordinates: pressure_level</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 2120</li><li><span class='xr-has-index'>lon</span>: 2600</li><li><span>pressure_level</span>: 19</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-3e0529e9-c822-41b3-98e4-292966b7d691' class='xr-array-in' type='checkbox' checked><label for='section-3e0529e9-c822-41b3-98e4-292966b7d691' 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>dask.array&lt;chunksize=(212, 260, 19), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 799.01 MiB </td>\n",
+       "                        <td> 7.99 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (2120, 2600, 19) </td>\n",
+       "                        <td> (212, 260, 19) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 100 chunks in 18 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
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+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></div></li><li class='xr-section-item'><input id='section-b9933240-b4ad-4488-a1c4-ad7197322ee4' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b9933240-b4ad-4488-a1c4-ad7197322ee4' class='xr-section-summary' >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>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-02-21T15:00:00</div><input id='attrs-181d204d-d813-4556-b93f-55135fda04cc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-181d204d-d813-4556-b93f-55135fda04cc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-77afa9ef-5a60-4132-83f1-adf8e6e9bba5' class='xr-var-data-in' type='checkbox'><label for='data-77afa9ef-5a60-4132-83f1-adf8e6e9bba5' 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(&#x27;2022-02-21T15:00:00.000000000&#x27;, dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-48.79 -48.77 ... -6.852 -6.832</div><input id='attrs-cd3f769d-e91d-45e2-8769-15bc099233d4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cd3f769d-e91d-45e2-8769-15bc099233d4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a5140ac4-cc98-4239-8247-c505e179231b' class='xr-var-data-in' type='checkbox'><label for='data-a5140ac4-cc98-4239-8247-c505e179231b' 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([-48.787998, -48.7682  , -48.748398, ...,  -6.871399,  -6.851597,\n",
+       "        -6.831799])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>107.5 107.5 107.6 ... 159.0 159.0</div><input id='attrs-ea49ef68-5ae8-4419-9ec8-148c9b4702f9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ea49ef68-5ae8-4419-9ec8-148c9b4702f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-da3cbafd-49d4-460e-b584-abdcd75428ed' class='xr-var-data-in' type='checkbox'><label for='data-da3cbafd-49d4-460e-b584-abdcd75428ed' 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([107.519997, 107.539795, 107.559593, ..., 158.940598, 158.960388,\n",
+       "       158.980194])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2668cc07-45e0-4394-ac76-c85f33a799b6' class='xr-section-summary-in' type='checkbox'  ><label for='section-2668cc07-45e0-4394-ac76-c85f33a799b6' class='xr-section-summary' >Indexes: <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-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-36214025-ae0e-413c-a048-0ebd4d7d7a2b' class='xr-index-data-in' type='checkbox'/><label for='index-36214025-ae0e-413c-a048-0ebd4d7d7a2b' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ -48.78799819946289,   -48.7681999206543,  -48.74839782714844,\n",
+       "       -48.728599548339844, -48.708797454833984,  -48.68899917602539,\n",
+       "        -48.66919708251953,  -48.64939880371094,  -48.62959671020508,\n",
+       "       -48.609798431396484,\n",
+       "       ...\n",
+       "        -7.009998321533203,  -6.990200042724609,   -6.97039794921875,\n",
+       "        -6.950599670410156,  -6.930797576904297,  -6.910999298095703,\n",
+       "        -6.891197204589844,   -6.87139892578125,  -6.851596832275391,\n",
+       "        -6.831798553466797],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=2120))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-bf2834d1-2fe7-4ff8-a6a3-300c69569546' class='xr-index-data-in' type='checkbox'/><label for='index-bf2834d1-2fe7-4ff8-a6a3-300c69569546' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 107.5199966430664,   107.539794921875,  107.5595932006836,\n",
+       "       107.57939910888672, 107.59919738769531,  107.6189956665039,\n",
+       "        107.6387939453125, 107.65859985351562, 107.67839813232422,\n",
+       "       107.69819641113281,\n",
+       "       ...\n",
+       "         158.802001953125, 158.82179260253906,  158.8415985107422,\n",
+       "       158.86138916015625, 158.88119506835938,  158.9010009765625,\n",
+       "       158.92079162597656,  158.9405975341797, 158.96038818359375,\n",
+       "       158.98019409179688],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=2600))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8d573483-6b7d-4571-96f6-aa901c9a3bad' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-8d573483-6b7d-4571-96f6-aa901c9a3bad' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.DataArray (lat: 2120, lon: 2600, pressure_level: 19)> Size: 838MB\n",
+       "dask.array<transpose, shape=(2120, 2600, 19), dtype=float64, chunksize=(212, 260, 19), chunktype=numpy.ndarray>\n",
+       "Coordinates:\n",
+       "    time     datetime64[ns] 8B 2022-02-21T15:00:00\n",
+       "  * lat      (lat) float64 17kB -48.79 -48.77 -48.75 ... -6.871 -6.852 -6.832\n",
+       "  * lon      (lon) float64 21kB 107.5 107.5 107.6 107.6 ... 158.9 159.0 159.0\n",
+       "Dimensions without coordinates: pressure_level"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_tv_pl"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "3671df36-cc7a-431c-b6f8-0e6c7af4654a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/jobfs/123409378.gadi-pbs/ipykernel_2374207/3741949889.py:108: RuntimeWarning: invalid value encountered in scalar divide\n",
+      "/jobfs/123409378.gadi-pbs/ipykernel_2374207/3741949889.py:108: RuntimeWarning: invalid value encountered in scalar divide\n"
+     ]
+    }
+   ],
+   "source": [
+    "ds_tv_pl = ds_tv_pl.compute()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "c332eefc-4cd2-4815-909b-6a6f57e4e0a6",
+   "metadata": {},
+   "outputs": [
+    {
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+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;fld_s16i202&#x27; (pressure: 16)&gt; Size: 64B\n",
+       "array([  151.,   583.,   805.,  1499.,  1999.,  2533.,  3098.,  3698.,\n",
+       "        4336.,  5750.,  7406.,  9418., 10630., 12064., 13882., 16402.],\n",
+       "      dtype=float32)\n",
+       "Coordinates:\n",
+       "    time      datetime64[ns] 8B 2022-02-21T15:00:00\n",
+       "  * pressure  (pressure) float64 128B 1e+05 9.5e+04 9.25e+04 ... 1.5e+04 1e+04\n",
+       "    lat       float64 8B -37.82\n",
+       "    lon       float64 8B 145.0\n",
+       "Attributes:\n",
+       "    standard_name:    geopotential_height\n",
+       "    long_name:        GEOPOTENTIAL HEIGHT ON P LEV/P GRID\n",
+       "    units:            m\n",
+       "    um_stash_source:  m01s16i202\n",
+       "    grid_mapping:     latitude_longitude</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'fld_s16i202'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>pressure</span>: 16</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-ac248fe5-0991-4c64-bff2-abcd20e8dd20' class='xr-array-in' type='checkbox' checked><label for='section-ac248fe5-0991-4c64-bff2-abcd20e8dd20' 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>151.0 583.0 805.0 1.499e+03 ... 1.063e+04 1.206e+04 1.388e+04 1.64e+04</span></div><div class='xr-array-data'><pre>array([  151.,   583.,   805.,  1499.,  1999.,  2533.,  3098.,  3698.,\n",
+       "        4336.,  5750.,  7406.,  9418., 10630., 12064., 13882., 16402.],\n",
+       "      dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-3a34b96a-38eb-47be-aba7-526638f4e892' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3a34b96a-38eb-47be-aba7-526638f4e892' class='xr-section-summary' >Coordinates: <span>(4)</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>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-02-21T15:00:00</div><input id='attrs-7cbdec14-58a5-4dbc-8c23-c364cdfc3647' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7cbdec14-58a5-4dbc-8c23-c364cdfc3647' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fb2e2dbc-46f4-49aa-97ea-8113eae9997c' class='xr-var-data-in' type='checkbox'><label for='data-fb2e2dbc-46f4-49aa-97ea-8113eae9997c' 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>axis :</span></dt><dd>T</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array(&#x27;2022-02-21T15:00:00.000000000&#x27;, dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>pressure</span></div><div class='xr-var-dims'>(pressure)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1e+05 9.5e+04 ... 1.5e+04 1e+04</div><input id='attrs-069f435f-2c87-4a98-9fb4-47986cfb48c5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-069f435f-2c87-4a98-9fb4-47986cfb48c5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-71fdaf4e-d989-4832-b4d6-02675872b859' class='xr-var-data-in' type='checkbox'><label for='data-71fdaf4e-d989-4832-b4d6-02675872b859' 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>axis :</span></dt><dd>Z</dd><dt><span>units :</span></dt><dd>Pa</dd><dt><span>long_name :</span></dt><dd>pressure</dd><dt><span>positive :</span></dt><dd>down</dd></dl></div><div class='xr-var-data'><pre>array([100000.,  95000.,  92500.,  85000.,  80000.,  75000.,  70000.,  65000.,\n",
+       "        60000.,  50000.,  40000.,  30000.,  25000.,  20000.,  15000.,  10000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-37.82</div><input id='attrs-06149d14-8a27-49fd-9221-db0d90eea5d0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-06149d14-8a27-49fd-9221-db0d90eea5d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-99048959-97dc-4a73-a17f-a857749d3997' class='xr-var-data-in' type='checkbox'><label for='data-99048959-97dc-4a73-a17f-a857749d3997' 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>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array(-37.81879807)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>145.0</div><input id='attrs-ebe4f10c-0350-42df-9f48-bfedd8ffc60c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ebe4f10c-0350-42df-9f48-bfedd8ffc60c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-be24a94b-8f01-417f-ab94-5f7272516fd3' class='xr-var-data-in' type='checkbox'><label for='data-be24a94b-8f01-417f-ab94-5f7272516fd3' 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>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array(144.96179199)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-aeb07169-c1af-441d-96fd-9a095b6f8bd2' class='xr-section-summary-in' type='checkbox'  ><label for='section-aeb07169-c1af-441d-96fd-9a095b6f8bd2' class='xr-section-summary' >Indexes: <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-index-name'><div>pressure</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-d0bd51f3-c6a7-4da8-a53d-cdf4aeb1749e' class='xr-index-data-in' type='checkbox'/><label for='index-d0bd51f3-c6a7-4da8-a53d-cdf4aeb1749e' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([100000.0,  95000.0,  92500.0,  85000.0,  80000.0,  75000.0,  70000.0,\n",
+       "        65000.0,  60000.0,  50000.0,  40000.0,  30000.0,  25000.0,  20000.0,\n",
+       "        15000.0,  10000.0],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;pressure&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-957486c0-a441-49d7-b5da-73fd35cde8d2' class='xr-section-summary-in' type='checkbox'  checked><label for='section-957486c0-a441-49d7-b5da-73fd35cde8d2' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>geopotential_height</dd><dt><span>long_name :</span></dt><dd>GEOPOTENTIAL HEIGHT ON P LEV/P GRID</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>um_stash_source :</span></dt><dd>m01s16i202</dd><dt><span>grid_mapping :</span></dt><dd>latitude_longitude</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.DataArray 'fld_s16i202' (pressure: 16)> Size: 64B\n",
+       "array([  151.,   583.,   805.,  1499.,  1999.,  2533.,  3098.,  3698.,\n",
+       "        4336.,  5750.,  7406.,  9418., 10630., 12064., 13882., 16402.],\n",
+       "      dtype=float32)\n",
+       "Coordinates:\n",
+       "    time      datetime64[ns] 8B 2022-02-21T15:00:00\n",
+       "  * pressure  (pressure) float64 128B 1e+05 9.5e+04 9.25e+04 ... 1.5e+04 1e+04\n",
+       "    lat       float64 8B -37.82\n",
+       "    lon       float64 8B 145.0\n",
+       "Attributes:\n",
+       "    standard_name:    geopotential_height\n",
+       "    long_name:        GEOPOTENTIAL HEIGHT ON P LEV/P GRID\n",
+       "    units:            m\n",
+       "    um_stash_source:  m01s16i202\n",
+       "    grid_mapping:     latitude_longitude"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds2 = xr.open_dataset(\"/g/data/hh5/tmp/AUS2200/flood22-continuous/atmos/umnsaa_pverd000_20220221T1200_6hr.nc\")\n",
+    "gph = ds2['fld_s16i202'].sel(lat=-37.81, lon=144.96, method='nearest').isel(time=1).load()\n",
+    "gph"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "e21979ed-7636-49b5-a485-109a4ed9668b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.PathCollection at 0x14b7d3625690>"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.scatter(gph.data,gph.pressure.data)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "2ac114a8-9d7c-4236-a93d-0e865c9fc8ce",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure()\n",
+    "ax1 = fig.add_subplot(111)\n",
+    "\n",
+    "\n",
+    "ax1.scatter(gph.data, gph.pressure.data, c='b', marker=\"s\", label='From model')\n",
+    "ax1.scatter(ds_tv_pl.sel(lat=-37.81, lon=144.96, method='nearest')[:12],plev19[:12], c='r', marker=\"o\", label='calculated')\n",
+    "plt.legend(loc='upper left')\n",
+    "plt.gca().invert_yaxis()\n",
+    "plt.xlabel(\"Geopotential Height (m)\")\n",
+    "plt.ylabel(\"Pressure (Pa)\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "e2d9b49f-86c4-4733-baca-d8ba062c34d5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model_indices=[0,2,3,6,8,9,10,11,12,13,14,15]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "d273c68c-7c91-49b4-a0ec-a30e94e3ad01",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "(( gph.data[model_indices] - ds_tv_pl.sel(lat=-37.81, lon=144.96, method='nearest')[:12])/gph.data[model_indices]).plot()\n",
+    "plt.xlabel(\"Pressure Level\")\n",
+    "plt.ylabel(\"Relative error\")\n",
+    "plt.show()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python [conda env:analysis3-24.07]",
+   "language": "python",
+   "name": "conda-env-analysis3-24.07-py"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.14"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/Recipes/geopotential_cross_section.ipynb b/Recipes/geopotential_cross_section.ipynb
new file mode 100644
index 0000000..8f5a803
--- /dev/null
+++ b/Recipes/geopotential_cross_section.ipynb
@@ -0,0 +1,3638 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "96c0947f-53f6-41bc-85d1-47b0b64b2f46",
+   "metadata": {},
+   "source": [
+    "### Create a cross-section of geopotiential height for a specific region\n",
+    "\n",
+    "Uses iris to open raw UM model data - predates automatic netCDF conversion in the AUS2200 suite. Useful for diagnosing model instabilities."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "53401880-6932-4d31-bf46-6384c620e65e",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import xarray as xr\n",
+    "import datetime\n",
+    "import cartopy.crs as ccrs\n",
+    "from matplotlib import pyplot as plt, animation\n",
+    "from glob import glob\n",
+    "import iris"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "f2e08b15-f75b-48c4-9b09-55c81f227a51",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "ts1=30\n",
+    "starttime=datetime.datetime(year=2022,month=2,day=21,hour=18)\n",
+    "td1=datetime.timedelta(seconds=ts1)\n",
+    "\n",
+    "ts2=75\n",
+    "td2=datetime.timedelta(seconds=ts2)\n",
+    "\n",
+    "tdg=datetime.timedelta(seconds=15)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "b49b8ff7-6560-4143-b8b9-2d5b3ab7d899",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "ds=xr.open_dataset(f\"/g/data/hh5/tmp/WACI-Hackathon-2023/AUS2200/data/surf/1hr/orog_1hr_{(starttime + datetime.timedelta(hours=7)).strftime('%Y%m%d')}_20220307.nc\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "dc567e73-c048-4b2e-95fc-8dbf3d39f61b",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "x_min=min(ds.longitude)\n",
+    "x_max=max(ds.longitude)\n",
+    "y_min=min(ds.latitude)\n",
+    "y_max=max(ds.latitude)\n",
+    "ex=(x_min,x_max,y_min,y_max)\n",
+    "x_minf=x_min.data.item()\n",
+    "x_maxf=x_max.data.item()\n",
+    "y_minf=y_min.data.item()\n",
+    "y_maxf=y_max.data.item()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "7315e1b7-14b1-49a4-96ec-eb3479a991ce",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
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+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
+       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
+       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
+       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
+       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
+       "  --xr-background-color: var(--jp-layout-color0, white);\n",
+       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
+       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
+       "}\n",
+       "\n",
+       "html[theme=dark],\n",
+       "body[data-theme=dark],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
+       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
+       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
+       "  --xr-border-color: #1F1F1F;\n",
+       "  --xr-disabled-color: #515151;\n",
+       "  --xr-background-color: #111111;\n",
+       "  --xr-background-color-row-even: #111111;\n",
+       "  --xr-background-color-row-odd: #313131;\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: '►';\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: '▼';\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: '(';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: ')';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: ',';\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
+       "Dimensions:    (latitude: 2120, longitude: 2600, time: 336)\n",
+       "Coordinates:\n",
+       "  * latitude   (latitude) float32 -48.79 -48.77 -48.75 ... -6.871 -6.852 -6.832\n",
+       "  * longitude  (longitude) float32 107.5 107.5 107.6 107.6 ... 158.9 159.0 159.0\n",
+       "  * time       (time) datetime64[ns] 2022-02-22T00:00:30 ... 2022-03-08\n",
+       "Data variables:\n",
+       "    orog       (time, latitude, longitude) float32 ...\n",
+       "Attributes: (12/25)\n",
+       "    Conventions:          CF-1.6, ACDD-1.3\n",
+       "    title:                AUS2200 UM amip simulation over Australian region f...\n",
+       "    summary:              A limited area model study of the entire Australian...\n",
+       "    source:               UM v12.2 ECMWF ERA5 forecast fields used as forcings\n",
+       "    license:              http://creativecommons.org/licenses/by/4.0/\n",
+       "    product_version:      0.1\n",
+       "    ...                   ...\n",
+       "    geospatial_lon_min:   107.5101\n",
+       "    geospatial_lon_max:   0.0198\n",
+       "    contributor_name:     Sam Green, Paola Petrelli\n",
+       "    contributor_email:    sam.green@unsw.edu.au, paola.petrelli@utas.edu.au\n",
+       "    contributor_url:      https://orcid.org/0000-0003-1129-4676, https://orci...\n",
+       "    contributor_role:     post-processing, post-processing</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-3d075873-c32c-4b87-898c-67be261d102b' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3d075873-c32c-4b87-898c-67be261d102b' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>latitude</span>: 2120</li><li><span class='xr-has-index'>longitude</span>: 2600</li><li><span class='xr-has-index'>time</span>: 336</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-399196e5-7153-4eb9-98a0-b04e15c1bb1f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-399196e5-7153-4eb9-98a0-b04e15c1bb1f' class='xr-section-summary' >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'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-48.79 -48.77 ... -6.852 -6.832</div><input id='attrs-675a0b44-b222-4a27-b354-20f5c96cd4d5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-675a0b44-b222-4a27-b354-20f5c96cd4d5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8cf1b14f-ccdf-4ddb-9a8d-77499325e709' class='xr-var-data-in' type='checkbox'><label for='data-8cf1b14f-ccdf-4ddb-9a8d-77499325e709' 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>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees</dd></dl></div><div class='xr-var-data'><pre>array([-48.788   , -48.7682  , -48.748398, ...,  -6.871399,  -6.851597,\n",
+       "        -6.831799], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>107.5 107.5 107.6 ... 159.0 159.0</div><input id='attrs-0912b26a-6bff-4519-b53c-2cb466884a77' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0912b26a-6bff-4519-b53c-2cb466884a77' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6c35326e-afea-4144-a825-a4d579cf0d95' class='xr-var-data-in' type='checkbox'><label for='data-6c35326e-afea-4144-a825-a4d579cf0d95' 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>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees</dd></dl></div><div class='xr-var-data'><pre>array([107.52    , 107.539795, 107.55959 , ..., 158.9406  , 158.96039 ,\n",
+       "       158.9802  ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-02-22T00:00:30 ... 2022-03-08</div><input id='attrs-eb9448af-8da8-47bc-a68c-54c0c5203f7d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eb9448af-8da8-47bc-a68c-54c0c5203f7d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f21d8baa-9b32-4492-a73d-6326237b342b' class='xr-var-data-in' type='checkbox'><label for='data-f21d8baa-9b32-4492-a73d-6326237b342b' 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>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-02-22T00:00:30.000000000&#x27;, &#x27;2022-02-22T02:00:00.000000000&#x27;,\n",
+       "       &#x27;2022-02-22T03:00:00.000000000&#x27;, ..., &#x27;2022-03-07T22:00:00.000000000&#x27;,\n",
+       "       &#x27;2022-03-07T23:00:00.000000000&#x27;, &#x27;2022-03-08T00:00:00.000000000&#x27;],\n",
+       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f2c10a33-e9b6-411e-af28-2ab222fb9bff' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f2c10a33-e9b6-411e-af28-2ab222fb9bff' class='xr-section-summary' >Data variables: <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>orog</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7201ab10-c823-4cbd-86d1-02af83e152d7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7201ab10-c823-4cbd-86d1-02af83e152d7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b8b78e01-2357-4fdb-93ff-ea99d2f7e882' class='xr-var-data-in' type='checkbox'><label for='data-b8b78e01-2357-4fdb-93ff-ea99d2f7e882' 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>standard_name :</span></dt><dd>surface_altitude</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>source :</span></dt><dd>Data from Met Office Unified Model</dd><dt><span>um_version :</span></dt><dd>12.2</dd><dt><span>STASH :</span></dt><dd>[ 1  0 33]</dd></dl></div><div class='xr-var-data'><pre>[1852032000 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0a10885b-80f0-4142-a432-a692b8295564' class='xr-section-summary-in' type='checkbox'  ><label for='section-0a10885b-80f0-4142-a432-a692b8295564' class='xr-section-summary' >Indexes: <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-index-name'><div>latitude</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-f0560026-0c9f-42ff-a84b-ac5ffddaa249' class='xr-index-data-in' type='checkbox'/><label for='index-f0560026-0c9f-42ff-a84b-ac5ffddaa249' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([ -48.78799819946289,   -48.7681999206543,  -48.74839782714844,\n",
+       "              -48.728599548339844, -48.708797454833984,  -48.68899917602539,\n",
+       "               -48.66919708251953,  -48.64939880371094,  -48.62959671020508,\n",
+       "              -48.609798431396484,\n",
+       "              ...\n",
+       "               -7.009998321533203,  -6.990200042724609,   -6.97039794921875,\n",
+       "               -6.950599670410156,  -6.930797576904297,  -6.910999298095703,\n",
+       "               -6.891197204589844,   -6.87139892578125,  -6.851596832275391,\n",
+       "               -6.831798553466797],\n",
+       "             dtype=&#x27;float64&#x27;, name=&#x27;latitude&#x27;, length=2120))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>longitude</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c2cdaa15-f779-4e1c-8cbe-3aebb060c62e' class='xr-index-data-in' type='checkbox'/><label for='index-c2cdaa15-f779-4e1c-8cbe-3aebb060c62e' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([ 107.5199966430664,   107.539794921875,  107.5595932006836,\n",
+       "              107.57939910888672, 107.59919738769531,  107.6189956665039,\n",
+       "               107.6387939453125, 107.65859985351562, 107.67839813232422,\n",
+       "              107.69819641113281,\n",
+       "              ...\n",
+       "                158.802001953125, 158.82179260253906,  158.8415985107422,\n",
+       "              158.86138916015625, 158.88119506835938,  158.9010009765625,\n",
+       "              158.92079162597656,  158.9405975341797, 158.96038818359375,\n",
+       "              158.98019409179688],\n",
+       "             dtype=&#x27;float64&#x27;, name=&#x27;longitude&#x27;, length=2600))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-5fe165a9-5c98-42ec-bfc4-275e8f35b54e' class='xr-index-data-in' type='checkbox'/><label for='index-5fe165a9-5c98-42ec-bfc4-275e8f35b54e' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2022-02-22 00:00:30&#x27;, &#x27;2022-02-22 02:00:00&#x27;,\n",
+       "               &#x27;2022-02-22 03:00:00&#x27;, &#x27;2022-02-22 04:00:00&#x27;,\n",
+       "               &#x27;2022-02-22 05:00:00&#x27;, &#x27;2022-02-22 06:00:00&#x27;,\n",
+       "               &#x27;2022-02-22 06:00:30&#x27;, &#x27;2022-02-22 08:00:00&#x27;,\n",
+       "               &#x27;2022-02-22 09:00:00&#x27;, &#x27;2022-02-22 10:00:00&#x27;,\n",
+       "               ...\n",
+       "               &#x27;2022-03-07 15:00:00&#x27;, &#x27;2022-03-07 16:00:00&#x27;,\n",
+       "               &#x27;2022-03-07 17:00:00&#x27;, &#x27;2022-03-07 18:00:00&#x27;,\n",
+       "               &#x27;2022-03-07 18:00:30&#x27;, &#x27;2022-03-07 20:00:00&#x27;,\n",
+       "               &#x27;2022-03-07 21:00:00&#x27;, &#x27;2022-03-07 22:00:00&#x27;,\n",
+       "               &#x27;2022-03-07 23:00:00&#x27;, &#x27;2022-03-08 00:00:00&#x27;],\n",
+       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=336, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-aeb1cad0-6fd7-47bb-b63c-dcdc78ea5518' class='xr-section-summary-in' type='checkbox'  ><label for='section-aeb1cad0-6fd7-47bb-b63c-dcdc78ea5518' class='xr-section-summary' >Attributes: <span>(25)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6, ACDD-1.3</dd><dt><span>title :</span></dt><dd>AUS2200 UM amip simulation over Australian region for the 22 Feb to 07 Mar 2022</dd><dt><span>summary :</span></dt><dd>A limited area model study of the entire Australian continent at 2.2 km resolution, using the UM atmospheric model. ERA5 and ERA5 land reanalysis datasets were used to provide intial and boundary conditions. The study covers the time period of 2022-02-22 to 2022-03-7 including high rainfall events</dd><dt><span>source :</span></dt><dd>UM v12.2 ECMWF ERA5 forecast fields used as forcings</dd><dt><span>license :</span></dt><dd>http://creativecommons.org/licenses/by/4.0/</dd><dt><span>product_version :</span></dt><dd>0.1</dd><dt><span>contact :</span></dt><dd>dsroberts@unimelb.edu.au</dd><dt><span>institution :</span></dt><dd>Melbourne University</dd><dt><span>organisation :</span></dt><dd>ARC Centre of Excellence for Climate Extremes</dd><dt><span>keywords :</span></dt><dd>Cloud Physics, Meteorology, Atmospheric Dynamics</dd><dt><span>date_created :</span></dt><dd>2023-02-13</dd><dt><span>creator_name :</span></dt><dd>Dale Roberts</dd><dt><span>creator_email :</span></dt><dd>dsroberts@unimelb.edu.au</dd><dt><span>creator_url :</span></dt><dd>https://orcid.org/0000-0003-3952-6344</dd><dt><span>creator_role :</span></dt><dd>running model, post-processing</dd><dt><span>time_coverage_start :</span></dt><dd>2022-02-22</dd><dt><span>time_coverage_end :</span></dt><dd>2022-03-07</dd><dt><span>geospatial_lat_min :</span></dt><dd>-48.788</dd><dt><span>geospatial_lat_max :</span></dt><dd>-6.831799</dd><dt><span>geospatial_lon_min :</span></dt><dd>107.5101</dd><dt><span>geospatial_lon_max :</span></dt><dd>0.0198</dd><dt><span>contributor_name :</span></dt><dd>Sam Green, Paola Petrelli</dd><dt><span>contributor_email :</span></dt><dd>sam.green@unsw.edu.au, paola.petrelli@utas.edu.au</dd><dt><span>contributor_url :</span></dt><dd>https://orcid.org/0000-0003-1129-4676, https://orcid.org/0000-0002-0164-5105</dd><dt><span>contributor_role :</span></dt><dd>post-processing, post-processing</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset>\n",
+       "Dimensions:    (latitude: 2120, longitude: 2600, time: 336)\n",
+       "Coordinates:\n",
+       "  * latitude   (latitude) float32 -48.79 -48.77 -48.75 ... -6.871 -6.852 -6.832\n",
+       "  * longitude  (longitude) float32 107.5 107.5 107.6 107.6 ... 158.9 159.0 159.0\n",
+       "  * time       (time) datetime64[ns] 2022-02-22T00:00:30 ... 2022-03-08\n",
+       "Data variables:\n",
+       "    orog       (time, latitude, longitude) float32 ...\n",
+       "Attributes: (12/25)\n",
+       "    Conventions:          CF-1.6, ACDD-1.3\n",
+       "    title:                AUS2200 UM amip simulation over Australian region f...\n",
+       "    summary:              A limited area model study of the entire Australian...\n",
+       "    source:               UM v12.2 ECMWF ERA5 forecast fields used as forcings\n",
+       "    license:              http://creativecommons.org/licenses/by/4.0/\n",
+       "    product_version:      0.1\n",
+       "    ...                   ...\n",
+       "    geospatial_lon_min:   107.5101\n",
+       "    geospatial_lon_max:   0.0198\n",
+       "    contributor_name:     Sam Green, Paola Petrelli\n",
+       "    contributor_email:    sam.green@unsw.edu.au, paola.petrelli@utas.edu.au\n",
+       "    contributor_url:      https://orcid.org/0000-0003-1129-4676, https://orci...\n",
+       "    contributor_role:     post-processing, post-processing"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "7e58d82f-c2a3-4d20-86c9-c46502ebc7e1",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
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+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;orog&#x27; ()&gt;\n",
+       "array(2)\n",
+       "Coordinates:\n",
+       "    time     datetime64[ns] 2022-02-22T00:00:30</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'orog'</div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-b963564b-6600-479d-8520-01e0976614c2' class='xr-array-in' type='checkbox' checked><label for='section-b963564b-6600-479d-8520-01e0976614c2' 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>2</span></div><div class='xr-array-data'><pre>array(2)</pre></div></div></li><li class='xr-section-item'><input id='section-1eef99df-bd69-44d1-a8cd-8cfc036e75b0' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1eef99df-bd69-44d1-a8cd-8cfc036e75b0' class='xr-section-summary' >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>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-02-22T00:00:30</div><input id='attrs-3151e1d3-0e9f-4160-ab10-8232cb7b526f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3151e1d3-0e9f-4160-ab10-8232cb7b526f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ca4c7d4d-791d-4aea-8034-d39bd406b665' class='xr-var-data-in' type='checkbox'><label for='data-ca4c7d4d-791d-4aea-8034-d39bd406b665' 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>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array(&#x27;2022-02-22T00:00:30.000000000&#x27;, dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-189d2cc6-7b07-4aca-8b79-af286ca5d83a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-189d2cc6-7b07-4aca-8b79-af286ca5d83a' class='xr-section-summary'  title='Expand/collapse section'>Indexes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-09c85c2d-3302-4054-a0c6-fb436d0cc877' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-09c85c2d-3302-4054-a0c6-fb436d0cc877' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.DataArray 'orog' ()>\n",
+       "array(2)\n",
+       "Coordinates:\n",
+       "    time     datetime64[ns] 2022-02-22T00:00:30"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "xr.where(ds.orog[0] < -10,True,False).sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "1086c3b4-e341-49cb-921c-015fb0d58374",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax1 = plt.subplots()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "658d1b0f-059b-4a00-9c94-7e7054411af3",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x146b29188a60>]"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds.orog[0].sel(latitude=-6.851597,longitude=slice(143.1,143.5)).plot(ax=ax1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "7825033c-5b89-48d2-9e9f-18f176990b3a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/g/data/hh5/public/apps/cms_conda/envs/analysis3-23.01/lib/python3.9/site-packages/iris/fileformats/rules.py:353: UserWarning: Unable to create instance of HybridHeightFactory. The source data contains no field(s) for 'orography'.\n",
+      "  warnings.warn(msg.format(factory=factory_name))\n"
+     ]
+    }
+   ],
+   "source": [
+    "cubes=iris.load(\"/scratch/w40/dr4292/aus2200-instability-analysis/30sec/20220222T0000Z/aus2200/d0198/RA3/um/umnsa_mdl_20220222T0000\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "2189fd70-a36f-4975-86c4-3ddceaca1bc7",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "<style>\n",
+       "    .accordion-22450476936384 {\n",
+       "        color: var(--jp-ui-font-color2);\n",
+       "        background: var(--jp-layout-color2);\n",
+       "        cursor: pointer;\n",
+       "        padding: 10px;\n",
+       "        border: 1px solid var(--jp-border-color0);\n",
+       "        width: 100%;\n",
+       "        text-align: left;\n",
+       "        font-size: 14px;\n",
+       "        font-family: var(--jp-code-font-family);\n",
+       "        font-weight: normal;\n",
+       "        outline: none;\n",
+       "        transition: 0.4s;\n",
+       "    }\n",
+       "    .active {\n",
+       "        background: var(--jp-layout-color1);\n",
+       "        font-weight: 900;\n",
+       "    }\n",
+       "    .accordion-22450476936384.active {\n",
+       "        border: 1px solid var(--jp-brand-color1) !important;\n",
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+       "        box-shadow: var(--jp-input-box-shadow);\n",
+       "        border: 2px solid var(--jp-brand-color1);\n",
+       "    }\n",
+       "    .panel-22450476936384 {\n",
+       "        padding: 0 18px;\n",
+       "        margin-bottom: 5px;\n",
+       "        background-color: var(--jp-layout-color1);\n",
+       "        display: none;\n",
+       "        overflow: hidden;\n",
+       "        border: 1px solid var(--jp-brand-color2);\n",
+       "    }\n",
+       "</style>\n",
+       "<script type=\"text/javascript\">\n",
+       "    var accordion = document.getElementsByClassName(\"accordion-22450476936384\");\n",
+       "    var i;\n",
+       "\n",
+       "    for (i = 0; i < accordion.length; i++) {\n",
+       "        accordion[i].addEventListener(\"click\", function() {\n",
+       "            this.classList.toggle(\"active\");\n",
+       "\n",
+       "            var panel = this.nextElementSibling;\n",
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+       "            }\n",
+       "        });\n",
+       "    }\n",
+       "</script>\n",
+       "\n",
+       "<button class=\"accordion-22450476936384\">0: m01s03i468 / (unknown)              (model_level_number: 45; latitude: 2120; longitude: 2600)</button>\n",
+       "<div class=\"panel-22450476936384\">\n",
+       "    <p>\n",
+       "<style>\n",
+       "  a.iris {\n",
+       "      text-decoration: none !important;\n",
+       "  }\n",
+       "  table.iris {\n",
+       "      white-space: pre;\n",
+       "      border: 1px solid;\n",
+       "      border-color: #9c9c9c;\n",
+       "      font-family: monaco, monospace;\n",
+       "  }\n",
+       "  th.iris {\n",
+       "      background: #303f3f;\n",
+       "      color: #e0e0e0;\n",
+       "      border-left: 1px solid;\n",
+       "      border-color: #9c9c9c;\n",
+       "      font-size: 1.05em;\n",
+       "      min-width: 50px;\n",
+       "      max-width: 125px;\n",
+       "  }\n",
+       "  tr.iris :first-child {\n",
+       "      border-right: 1px solid #9c9c9c !important;\n",
+       "  }\n",
+       "  td.iris-title {\n",
+       "      background: #d5dcdf;\n",
+       "      border-top: 1px solid #9c9c9c;\n",
+       "      font-weight: bold;\n",
+       "  }\n",
+       "  .iris-word-cell {\n",
+       "      text-align: left !important;\n",
+       "      white-space: pre;\n",
+       "  }\n",
+       "  .iris-subheading-cell {\n",
+       "      padding-left: 2em !important;\n",
+       "  }\n",
+       "  .iris-inclusion-cell {\n",
+       "      padding-right: 1em !important;\n",
+       "  }\n",
+       "  .iris-panel-body {\n",
+       "      padding-top: 0px;\n",
+       "  }\n",
+       "  .iris-panel-title {\n",
+       "      padding-left: 3em;\n",
+       "  }\n",
+       "  .iris-panel-title {\n",
+       "      margin-top: 7px;\n",
+       "  }\n",
+       "</style>\n",
+       "<table class=\"iris\" id=\"22450477095376\">\n",
+       "    <tr class=\"iris\">\n",
+       "<th class=\"iris iris-word-cell\">M01S03I468 (unknown)</th>\n",
+       "<th class=\"iris iris-word-cell\">model_level_number</th>\n",
+       "<th class=\"iris iris-word-cell\">latitude</th>\n",
+       "<th class=\"iris iris-word-cell\">longitude</th>\n",
+       "</tr>\n",
+       "    <tr class=\"iris\">\n",
+       "<td class=\"iris-word-cell iris-subheading-cell\">Shape</td>\n",
+       "<td class=\"iris iris-inclusion-cell\">45</td>\n",
+       "<td class=\"iris iris-inclusion-cell\">2120</td>\n",
+       "<td class=\"iris iris-inclusion-cell\">2600</td>\n",
+       "</tr>\n",
+       "    <tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Dimension coordinates</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tmodel_level_number</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tlatitude</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tlongitude</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Auxiliary coordinates</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tlevel_height</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tsigma</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Scalar coordinates</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tforecast_period</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">13.0 hours</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tforecast_reference_time</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">2022-02-21 12:00:00</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\ttime</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">2022-02-22 01:00:00</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Attributes</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tSTASH</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">m01s03i468</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tsource</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">&#x27;Data from Met Office Unified Model&#x27;</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tum_version</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">&#x27;12.2&#x27;</td>\n",
+       "</tr>\n",
+       "</table>\n",
+       "        </p>\n",
+       "</div>\n",
+       "    \n",
+       "\n",
+       "<button class=\"accordion-22450476936384\">1: m01s03i473 / (unknown)              (model_level_number: 45; latitude: 2120; longitude: 2600)</button>\n",
+       "<div class=\"panel-22450476936384\">\n",
+       "    <p>\n",
+       "<style>\n",
+       "  a.iris {\n",
+       "      text-decoration: none !important;\n",
+       "  }\n",
+       "  table.iris {\n",
+       "      white-space: pre;\n",
+       "      border: 1px solid;\n",
+       "      border-color: #9c9c9c;\n",
+       "      font-family: monaco, monospace;\n",
+       "  }\n",
+       "  th.iris {\n",
+       "      background: #303f3f;\n",
+       "      color: #e0e0e0;\n",
+       "      border-left: 1px solid;\n",
+       "      border-color: #9c9c9c;\n",
+       "      font-size: 1.05em;\n",
+       "      min-width: 50px;\n",
+       "      max-width: 125px;\n",
+       "  }\n",
+       "  tr.iris :first-child {\n",
+       "      border-right: 1px solid #9c9c9c !important;\n",
+       "  }\n",
+       "  td.iris-title {\n",
+       "      background: #d5dcdf;\n",
+       "      border-top: 1px solid #9c9c9c;\n",
+       "      font-weight: bold;\n",
+       "  }\n",
+       "  .iris-word-cell {\n",
+       "      text-align: left !important;\n",
+       "      white-space: pre;\n",
+       "  }\n",
+       "  .iris-subheading-cell {\n",
+       "      padding-left: 2em !important;\n",
+       "  }\n",
+       "  .iris-inclusion-cell {\n",
+       "      padding-right: 1em !important;\n",
+       "  }\n",
+       "  .iris-panel-body {\n",
+       "      padding-top: 0px;\n",
+       "  }\n",
+       "  .iris-panel-title {\n",
+       "      padding-left: 3em;\n",
+       "  }\n",
+       "  .iris-panel-title {\n",
+       "      margin-top: 7px;\n",
+       "  }\n",
+       "</style>\n",
+       "<table class=\"iris\" id=\"22450475823008\">\n",
+       "    <tr class=\"iris\">\n",
+       "<th class=\"iris iris-word-cell\">M01S03I473 (unknown)</th>\n",
+       "<th class=\"iris iris-word-cell\">model_level_number</th>\n",
+       "<th class=\"iris iris-word-cell\">latitude</th>\n",
+       "<th class=\"iris iris-word-cell\">longitude</th>\n",
+       "</tr>\n",
+       "    <tr class=\"iris\">\n",
+       "<td class=\"iris-word-cell iris-subheading-cell\">Shape</td>\n",
+       "<td class=\"iris iris-inclusion-cell\">45</td>\n",
+       "<td class=\"iris iris-inclusion-cell\">2120</td>\n",
+       "<td class=\"iris iris-inclusion-cell\">2600</td>\n",
+       "</tr>\n",
+       "    <tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Dimension coordinates</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tmodel_level_number</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tlatitude</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tlongitude</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Auxiliary coordinates</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tlevel_height</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tsigma</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Scalar coordinates</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tforecast_period</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">13.0 hours</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tforecast_reference_time</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">2022-02-21 12:00:00</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\ttime</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">2022-02-22 01:00:00</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Attributes</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tSTASH</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">m01s03i473</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tsource</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">&#x27;Data from Met Office Unified Model&#x27;</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tum_version</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">&#x27;12.2&#x27;</td>\n",
+       "</tr>\n",
+       "</table>\n",
+       "        </p>\n",
+       "</div>\n",
+       "    \n",
+       "\n",
+       "<button class=\"accordion-22450476936384\">2: air_potential_temperature / (K)     (model_level_number: 70; latitude: 2120; longitude: 2600)</button>\n",
+       "<div class=\"panel-22450476936384\">\n",
+       "    <p>\n",
+       "<style>\n",
+       "  a.iris {\n",
+       "      text-decoration: none !important;\n",
+       "  }\n",
+       "  table.iris {\n",
+       "      white-space: pre;\n",
+       "      border: 1px solid;\n",
+       "      border-color: #9c9c9c;\n",
+       "      font-family: monaco, monospace;\n",
+       "  }\n",
+       "  th.iris {\n",
+       "      background: #303f3f;\n",
+       "      color: #e0e0e0;\n",
+       "      border-left: 1px solid;\n",
+       "      border-color: #9c9c9c;\n",
+       "      font-size: 1.05em;\n",
+       "      min-width: 50px;\n",
+       "      max-width: 125px;\n",
+       "  }\n",
+       "  tr.iris :first-child {\n",
+       "      border-right: 1px solid #9c9c9c !important;\n",
+       "  }\n",
+       "  td.iris-title {\n",
+       "      background: #d5dcdf;\n",
+       "      border-top: 1px solid #9c9c9c;\n",
+       "      font-weight: bold;\n",
+       "  }\n",
+       "  .iris-word-cell {\n",
+       "      text-align: left !important;\n",
+       "      white-space: pre;\n",
+       "  }\n",
+       "  .iris-subheading-cell {\n",
+       "      padding-left: 2em !important;\n",
+       "  }\n",
+       "  .iris-inclusion-cell {\n",
+       "      padding-right: 1em !important;\n",
+       "  }\n",
+       "  .iris-panel-body {\n",
+       "      padding-top: 0px;\n",
+       "  }\n",
+       "  .iris-panel-title {\n",
+       "      padding-left: 3em;\n",
+       "  }\n",
+       "  .iris-panel-title {\n",
+       "      margin-top: 7px;\n",
+       "  }\n",
+       "</style>\n",
+       "<table class=\"iris\" id=\"22450474020480\">\n",
+       "    <tr class=\"iris\">\n",
+       "<th class=\"iris iris-word-cell\">Air Potential Temperature (K)</th>\n",
+       "<th class=\"iris iris-word-cell\">model_level_number</th>\n",
+       "<th class=\"iris iris-word-cell\">latitude</th>\n",
+       "<th class=\"iris iris-word-cell\">longitude</th>\n",
+       "</tr>\n",
+       "    <tr class=\"iris\">\n",
+       "<td class=\"iris-word-cell iris-subheading-cell\">Shape</td>\n",
+       "<td class=\"iris iris-inclusion-cell\">70</td>\n",
+       "<td class=\"iris iris-inclusion-cell\">2120</td>\n",
+       "<td class=\"iris iris-inclusion-cell\">2600</td>\n",
+       "</tr>\n",
+       "    <tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Dimension coordinates</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tmodel_level_number</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tlatitude</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tlongitude</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Auxiliary coordinates</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tlevel_height</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tsigma</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Scalar coordinates</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tforecast_period</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">13.0 hours</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tforecast_reference_time</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">2022-02-21 12:00:00</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\ttime</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">2022-02-22 01:00:00</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Attributes</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tSTASH</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">m01s00i004</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tsource</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">&#x27;Data from Met Office Unified Model&#x27;</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tum_version</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">&#x27;12.2&#x27;</td>\n",
+       "</tr>\n",
+       "</table>\n",
+       "        </p>\n",
+       "</div>\n",
+       "    \n",
+       "\n",
+       "<button class=\"accordion-22450476936384\">3: air_pressure / (Pa)                 (model_level_number: 71; latitude: 2120; longitude: 2600)</button>\n",
+       "<div class=\"panel-22450476936384\">\n",
+       "    <p>\n",
+       "<style>\n",
+       "  a.iris {\n",
+       "      text-decoration: none !important;\n",
+       "  }\n",
+       "  table.iris {\n",
+       "      white-space: pre;\n",
+       "      border: 1px solid;\n",
+       "      border-color: #9c9c9c;\n",
+       "      font-family: monaco, monospace;\n",
+       "  }\n",
+       "  th.iris {\n",
+       "      background: #303f3f;\n",
+       "      color: #e0e0e0;\n",
+       "      border-left: 1px solid;\n",
+       "      border-color: #9c9c9c;\n",
+       "      font-size: 1.05em;\n",
+       "      min-width: 50px;\n",
+       "      max-width: 125px;\n",
+       "  }\n",
+       "  tr.iris :first-child {\n",
+       "      border-right: 1px solid #9c9c9c !important;\n",
+       "  }\n",
+       "  td.iris-title {\n",
+       "      background: #d5dcdf;\n",
+       "      border-top: 1px solid #9c9c9c;\n",
+       "      font-weight: bold;\n",
+       "  }\n",
+       "  .iris-word-cell {\n",
+       "      text-align: left !important;\n",
+       "      white-space: pre;\n",
+       "  }\n",
+       "  .iris-subheading-cell {\n",
+       "      padding-left: 2em !important;\n",
+       "  }\n",
+       "  .iris-inclusion-cell {\n",
+       "      padding-right: 1em !important;\n",
+       "  }\n",
+       "  .iris-panel-body {\n",
+       "      padding-top: 0px;\n",
+       "  }\n",
+       "  .iris-panel-title {\n",
+       "      padding-left: 3em;\n",
+       "  }\n",
+       "  .iris-panel-title {\n",
+       "      margin-top: 7px;\n",
+       "  }\n",
+       "</style>\n",
+       "<table class=\"iris\" id=\"22450472475568\">\n",
+       "    <tr class=\"iris\">\n",
+       "<th class=\"iris iris-word-cell\">Air Pressure (Pa)</th>\n",
+       "<th class=\"iris iris-word-cell\">model_level_number</th>\n",
+       "<th class=\"iris iris-word-cell\">latitude</th>\n",
+       "<th class=\"iris iris-word-cell\">longitude</th>\n",
+       "</tr>\n",
+       "    <tr class=\"iris\">\n",
+       "<td class=\"iris-word-cell iris-subheading-cell\">Shape</td>\n",
+       "<td class=\"iris iris-inclusion-cell\">71</td>\n",
+       "<td class=\"iris iris-inclusion-cell\">2120</td>\n",
+       "<td class=\"iris iris-inclusion-cell\">2600</td>\n",
+       "</tr>\n",
+       "    <tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Dimension coordinates</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tmodel_level_number</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tlatitude</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tlongitude</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Auxiliary coordinates</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tlevel_height</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tsigma</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Scalar coordinates</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tforecast_period</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">13.0 hours</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tforecast_reference_time</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">2022-02-21 12:00:00</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\ttime</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">2022-02-22 01:00:00</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Attributes</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tSTASH</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">m01s00i407</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tsource</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">&#x27;Data from Met Office Unified Model&#x27;</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tum_version</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">&#x27;12.2&#x27;</td>\n",
+       "</tr>\n",
+       "</table>\n",
+       "        </p>\n",
+       "</div>\n",
+       "    \n",
+       "\n",
+       "<button class=\"accordion-22450476936384\">4: air_pressure / (Pa)                 (model_level_number: 70; latitude: 2120; longitude: 2600)</button>\n",
+       "<div class=\"panel-22450476936384\">\n",
+       "    <p>\n",
+       "<style>\n",
+       "  a.iris {\n",
+       "      text-decoration: none !important;\n",
+       "  }\n",
+       "  table.iris {\n",
+       "      white-space: pre;\n",
+       "      border: 1px solid;\n",
+       "      border-color: #9c9c9c;\n",
+       "      font-family: monaco, monospace;\n",
+       "  }\n",
+       "  th.iris {\n",
+       "      background: #303f3f;\n",
+       "      color: #e0e0e0;\n",
+       "      border-left: 1px solid;\n",
+       "      border-color: #9c9c9c;\n",
+       "      font-size: 1.05em;\n",
+       "      min-width: 50px;\n",
+       "      max-width: 125px;\n",
+       "  }\n",
+       "  tr.iris :first-child {\n",
+       "      border-right: 1px solid #9c9c9c !important;\n",
+       "  }\n",
+       "  td.iris-title {\n",
+       "      background: #d5dcdf;\n",
+       "      border-top: 1px solid #9c9c9c;\n",
+       "      font-weight: bold;\n",
+       "  }\n",
+       "  .iris-word-cell {\n",
+       "      text-align: left !important;\n",
+       "      white-space: pre;\n",
+       "  }\n",
+       "  .iris-subheading-cell {\n",
+       "      padding-left: 2em !important;\n",
+       "  }\n",
+       "  .iris-inclusion-cell {\n",
+       "      padding-right: 1em !important;\n",
+       "  }\n",
+       "  .iris-panel-body {\n",
+       "      padding-top: 0px;\n",
+       "  }\n",
+       "  .iris-panel-title {\n",
+       "      padding-left: 3em;\n",
+       "  }\n",
+       "  .iris-panel-title {\n",
+       "      margin-top: 7px;\n",
+       "  }\n",
+       "</style>\n",
+       "<table class=\"iris\" id=\"22450471579952\">\n",
+       "    <tr class=\"iris\">\n",
+       "<th class=\"iris iris-word-cell\">Air Pressure (Pa)</th>\n",
+       "<th class=\"iris iris-word-cell\">model_level_number</th>\n",
+       "<th class=\"iris iris-word-cell\">latitude</th>\n",
+       "<th class=\"iris iris-word-cell\">longitude</th>\n",
+       "</tr>\n",
+       "    <tr class=\"iris\">\n",
+       "<td class=\"iris-word-cell iris-subheading-cell\">Shape</td>\n",
+       "<td class=\"iris iris-inclusion-cell\">70</td>\n",
+       "<td class=\"iris iris-inclusion-cell\">2120</td>\n",
+       "<td class=\"iris iris-inclusion-cell\">2600</td>\n",
+       "</tr>\n",
+       "    <tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Dimension coordinates</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tmodel_level_number</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tlatitude</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tlongitude</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Auxiliary coordinates</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tlevel_height</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tsigma</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Scalar coordinates</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tforecast_period</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">13.0 hours</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tforecast_reference_time</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">2022-02-21 12:00:00</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\ttime</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">2022-02-22 01:00:00</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Attributes</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tSTASH</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">m01s00i408</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tsource</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">&#x27;Data from Met Office Unified Model&#x27;</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tum_version</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">&#x27;12.2&#x27;</td>\n",
+       "</tr>\n",
+       "</table>\n",
+       "        </p>\n",
+       "</div>\n",
+       "    \n",
+       "\n",
+       "<button class=\"accordion-22450476936384\">5: air_temperature / (K)               (model_level_number: 70; latitude: 2120; longitude: 2600)</button>\n",
+       "<div class=\"panel-22450476936384\">\n",
+       "    <p>\n",
+       "<style>\n",
+       "  a.iris {\n",
+       "      text-decoration: none !important;\n",
+       "  }\n",
+       "  table.iris {\n",
+       "      white-space: pre;\n",
+       "      border: 1px solid;\n",
+       "      border-color: #9c9c9c;\n",
+       "      font-family: monaco, monospace;\n",
+       "  }\n",
+       "  th.iris {\n",
+       "      background: #303f3f;\n",
+       "      color: #e0e0e0;\n",
+       "      border-left: 1px solid;\n",
+       "      border-color: #9c9c9c;\n",
+       "      font-size: 1.05em;\n",
+       "      min-width: 50px;\n",
+       "      max-width: 125px;\n",
+       "  }\n",
+       "  tr.iris :first-child {\n",
+       "      border-right: 1px solid #9c9c9c !important;\n",
+       "  }\n",
+       "  td.iris-title {\n",
+       "      background: #d5dcdf;\n",
+       "      border-top: 1px solid #9c9c9c;\n",
+       "      font-weight: bold;\n",
+       "  }\n",
+       "  .iris-word-cell {\n",
+       "      text-align: left !important;\n",
+       "      white-space: pre;\n",
+       "  }\n",
+       "  .iris-subheading-cell {\n",
+       "      padding-left: 2em !important;\n",
+       "  }\n",
+       "  .iris-inclusion-cell {\n",
+       "      padding-right: 1em !important;\n",
+       "  }\n",
+       "  .iris-panel-body {\n",
+       "      padding-top: 0px;\n",
+       "  }\n",
+       "  .iris-panel-title {\n",
+       "      padding-left: 3em;\n",
+       "  }\n",
+       "  .iris-panel-title {\n",
+       "      margin-top: 7px;\n",
+       "  }\n",
+       "</style>\n",
+       "<table class=\"iris\" id=\"22450470737760\">\n",
+       "    <tr class=\"iris\">\n",
+       "<th class=\"iris iris-word-cell\">Air Temperature (K)</th>\n",
+       "<th class=\"iris iris-word-cell\">model_level_number</th>\n",
+       "<th class=\"iris iris-word-cell\">latitude</th>\n",
+       "<th class=\"iris iris-word-cell\">longitude</th>\n",
+       "</tr>\n",
+       "    <tr class=\"iris\">\n",
+       "<td class=\"iris-word-cell iris-subheading-cell\">Shape</td>\n",
+       "<td class=\"iris iris-inclusion-cell\">70</td>\n",
+       "<td class=\"iris iris-inclusion-cell\">2120</td>\n",
+       "<td class=\"iris iris-inclusion-cell\">2600</td>\n",
+       "</tr>\n",
+       "    <tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Dimension coordinates</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tmodel_level_number</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tlatitude</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tlongitude</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Auxiliary coordinates</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tlevel_height</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tsigma</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Scalar coordinates</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tforecast_period</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">13.0 hours</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tforecast_reference_time</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">2022-02-21 12:00:00</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\ttime</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">2022-02-22 01:00:00</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Attributes</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tSTASH</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">m01s16i004</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tsource</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">&#x27;Data from Met Office Unified Model&#x27;</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tum_version</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">&#x27;12.2&#x27;</td>\n",
+       "</tr>\n",
+       "</table>\n",
+       "        </p>\n",
+       "</div>\n",
+       "    \n",
+       "\n",
+       "<button class=\"accordion-22450476936384\">6: height_above_reference_ellipsoid / (m) (model_level_number: 70; latitude: 2120; longitude: 2600)</button>\n",
+       "<div class=\"panel-22450476936384\">\n",
+       "    <p>\n",
+       "<style>\n",
+       "  a.iris {\n",
+       "      text-decoration: none !important;\n",
+       "  }\n",
+       "  table.iris {\n",
+       "      white-space: pre;\n",
+       "      border: 1px solid;\n",
+       "      border-color: #9c9c9c;\n",
+       "      font-family: monaco, monospace;\n",
+       "  }\n",
+       "  th.iris {\n",
+       "      background: #303f3f;\n",
+       "      color: #e0e0e0;\n",
+       "      border-left: 1px solid;\n",
+       "      border-color: #9c9c9c;\n",
+       "      font-size: 1.05em;\n",
+       "      min-width: 50px;\n",
+       "      max-width: 125px;\n",
+       "  }\n",
+       "  tr.iris :first-child {\n",
+       "      border-right: 1px solid #9c9c9c !important;\n",
+       "  }\n",
+       "  td.iris-title {\n",
+       "      background: #d5dcdf;\n",
+       "      border-top: 1px solid #9c9c9c;\n",
+       "      font-weight: bold;\n",
+       "  }\n",
+       "  .iris-word-cell {\n",
+       "      text-align: left !important;\n",
+       "      white-space: pre;\n",
+       "  }\n",
+       "  .iris-subheading-cell {\n",
+       "      padding-left: 2em !important;\n",
+       "  }\n",
+       "  .iris-inclusion-cell {\n",
+       "      padding-right: 1em !important;\n",
+       "  }\n",
+       "  .iris-panel-body {\n",
+       "      padding-top: 0px;\n",
+       "  }\n",
+       "  .iris-panel-title {\n",
+       "      padding-left: 3em;\n",
+       "  }\n",
+       "  .iris-panel-title {\n",
+       "      margin-top: 7px;\n",
+       "  }\n",
+       "</style>\n",
+       "<table class=\"iris\" id=\"22450468693616\">\n",
+       "    <tr class=\"iris\">\n",
+       "<th class=\"iris iris-word-cell\">Height Above Reference Ellipsoid (m)</th>\n",
+       "<th class=\"iris iris-word-cell\">model_level_number</th>\n",
+       "<th class=\"iris iris-word-cell\">latitude</th>\n",
+       "<th class=\"iris iris-word-cell\">longitude</th>\n",
+       "</tr>\n",
+       "    <tr class=\"iris\">\n",
+       "<td class=\"iris-word-cell iris-subheading-cell\">Shape</td>\n",
+       "<td class=\"iris iris-inclusion-cell\">70</td>\n",
+       "<td class=\"iris iris-inclusion-cell\">2120</td>\n",
+       "<td class=\"iris iris-inclusion-cell\">2600</td>\n",
+       "</tr>\n",
+       "    <tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Dimension coordinates</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tmodel_level_number</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tlatitude</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tlongitude</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Auxiliary coordinates</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tlevel_height</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tsigma</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Scalar coordinates</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tforecast_period</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">12.008333333360497 hours</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tforecast_reference_time</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">2022-02-21 12:00:00</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\ttime</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">2022-02-22 00:00:30</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Attributes</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tSTASH</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">m01s15i101</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tsource</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">&#x27;Data from Met Office Unified Model&#x27;</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tum_version</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">&#x27;12.2&#x27;</td>\n",
+       "</tr>\n",
+       "</table>\n",
+       "        </p>\n",
+       "</div>\n",
+       "    \n",
+       "\n",
+       "<button class=\"accordion-22450476936384\">7: height_above_reference_ellipsoid / (m) (model_level_number: 70; latitude: 2120; longitude: 2600)</button>\n",
+       "<div class=\"panel-22450476936384\">\n",
+       "    <p>\n",
+       "<style>\n",
+       "  a.iris {\n",
+       "      text-decoration: none !important;\n",
+       "  }\n",
+       "  table.iris {\n",
+       "      white-space: pre;\n",
+       "      border: 1px solid;\n",
+       "      border-color: #9c9c9c;\n",
+       "      font-family: monaco, monospace;\n",
+       "  }\n",
+       "  th.iris {\n",
+       "      background: #303f3f;\n",
+       "      color: #e0e0e0;\n",
+       "      border-left: 1px solid;\n",
+       "      border-color: #9c9c9c;\n",
+       "      font-size: 1.05em;\n",
+       "      min-width: 50px;\n",
+       "      max-width: 125px;\n",
+       "  }\n",
+       "  tr.iris :first-child {\n",
+       "      border-right: 1px solid #9c9c9c !important;\n",
+       "  }\n",
+       "  td.iris-title {\n",
+       "      background: #d5dcdf;\n",
+       "      border-top: 1px solid #9c9c9c;\n",
+       "      font-weight: bold;\n",
+       "  }\n",
+       "  .iris-word-cell {\n",
+       "      text-align: left !important;\n",
+       "      white-space: pre;\n",
+       "  }\n",
+       "  .iris-subheading-cell {\n",
+       "      padding-left: 2em !important;\n",
+       "  }\n",
+       "  .iris-inclusion-cell {\n",
+       "      padding-right: 1em !important;\n",
+       "  }\n",
+       "  .iris-panel-body {\n",
+       "      padding-top: 0px;\n",
+       "  }\n",
+       "  .iris-panel-title {\n",
+       "      padding-left: 3em;\n",
+       "  }\n",
+       "  .iris-panel-title {\n",
+       "      margin-top: 7px;\n",
+       "  }\n",
+       "</style>\n",
+       "<table class=\"iris\" id=\"22450469461584\">\n",
+       "    <tr class=\"iris\">\n",
+       "<th class=\"iris iris-word-cell\">Height Above Reference Ellipsoid (m)</th>\n",
+       "<th class=\"iris iris-word-cell\">model_level_number</th>\n",
+       "<th class=\"iris iris-word-cell\">latitude</th>\n",
+       "<th class=\"iris iris-word-cell\">longitude</th>\n",
+       "</tr>\n",
+       "    <tr class=\"iris\">\n",
+       "<td class=\"iris-word-cell iris-subheading-cell\">Shape</td>\n",
+       "<td class=\"iris iris-inclusion-cell\">70</td>\n",
+       "<td class=\"iris iris-inclusion-cell\">2120</td>\n",
+       "<td class=\"iris iris-inclusion-cell\">2600</td>\n",
+       "</tr>\n",
+       "    <tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Dimension coordinates</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tmodel_level_number</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tlatitude</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tlongitude</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Auxiliary coordinates</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tlevel_height</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tsigma</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Scalar coordinates</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tforecast_period</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">12.008333333360497 hours</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tforecast_reference_time</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">2022-02-21 12:00:00</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\ttime</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">2022-02-22 00:00:30</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Attributes</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tSTASH</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">m01s15i102</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tsource</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">&#x27;Data from Met Office Unified Model&#x27;</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tum_version</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">&#x27;12.2&#x27;</td>\n",
+       "</tr>\n",
+       "</table>\n",
+       "        </p>\n",
+       "</div>\n",
+       "    \n",
+       "\n",
+       "<button class=\"accordion-22450476936384\">8: specific_humidity / (kg kg-1)       (model_level_number: 70; latitude: 2120; longitude: 2600)</button>\n",
+       "<div class=\"panel-22450476936384\">\n",
+       "    <p>\n",
+       "<style>\n",
+       "  a.iris {\n",
+       "      text-decoration: none !important;\n",
+       "  }\n",
+       "  table.iris {\n",
+       "      white-space: pre;\n",
+       "      border: 1px solid;\n",
+       "      border-color: #9c9c9c;\n",
+       "      font-family: monaco, monospace;\n",
+       "  }\n",
+       "  th.iris {\n",
+       "      background: #303f3f;\n",
+       "      color: #e0e0e0;\n",
+       "      border-left: 1px solid;\n",
+       "      border-color: #9c9c9c;\n",
+       "      font-size: 1.05em;\n",
+       "      min-width: 50px;\n",
+       "      max-width: 125px;\n",
+       "  }\n",
+       "  tr.iris :first-child {\n",
+       "      border-right: 1px solid #9c9c9c !important;\n",
+       "  }\n",
+       "  td.iris-title {\n",
+       "      background: #d5dcdf;\n",
+       "      border-top: 1px solid #9c9c9c;\n",
+       "      font-weight: bold;\n",
+       "  }\n",
+       "  .iris-word-cell {\n",
+       "      text-align: left !important;\n",
+       "      white-space: pre;\n",
+       "  }\n",
+       "  .iris-subheading-cell {\n",
+       "      padding-left: 2em !important;\n",
+       "  }\n",
+       "  .iris-inclusion-cell {\n",
+       "      padding-right: 1em !important;\n",
+       "  }\n",
+       "  .iris-panel-body {\n",
+       "      padding-top: 0px;\n",
+       "  }\n",
+       "  .iris-panel-title {\n",
+       "      padding-left: 3em;\n",
+       "  }\n",
+       "  .iris-panel-title {\n",
+       "      margin-top: 7px;\n",
+       "  }\n",
+       "</style>\n",
+       "<table class=\"iris\" id=\"22450468526016\">\n",
+       "    <tr class=\"iris\">\n",
+       "<th class=\"iris iris-word-cell\">Specific Humidity (kg kg-1)</th>\n",
+       "<th class=\"iris iris-word-cell\">model_level_number</th>\n",
+       "<th class=\"iris iris-word-cell\">latitude</th>\n",
+       "<th class=\"iris iris-word-cell\">longitude</th>\n",
+       "</tr>\n",
+       "    <tr class=\"iris\">\n",
+       "<td class=\"iris-word-cell iris-subheading-cell\">Shape</td>\n",
+       "<td class=\"iris iris-inclusion-cell\">70</td>\n",
+       "<td class=\"iris iris-inclusion-cell\">2120</td>\n",
+       "<td class=\"iris iris-inclusion-cell\">2600</td>\n",
+       "</tr>\n",
+       "    <tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Dimension coordinates</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tmodel_level_number</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tlatitude</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tlongitude</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Auxiliary coordinates</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tlevel_height</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tsigma</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Scalar coordinates</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tforecast_period</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">13.0 hours</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tforecast_reference_time</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">2022-02-21 12:00:00</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\ttime</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">2022-02-22 01:00:00</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Attributes</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tSTASH</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">m01s00i010</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tsource</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">&#x27;Data from Met Office Unified Model&#x27;</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tum_version</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">&#x27;12.2&#x27;</td>\n",
+       "</tr>\n",
+       "</table>\n",
+       "        </p>\n",
+       "</div>\n",
+       "    \n",
+       "\n",
+       "<button class=\"accordion-22450476936384\">9: upward_air_velocity / (m s-1)       (model_level_number: 70; latitude: 2120; longitude: 2600)</button>\n",
+       "<div class=\"panel-22450476936384\">\n",
+       "    <p>\n",
+       "<style>\n",
+       "  a.iris {\n",
+       "      text-decoration: none !important;\n",
+       "  }\n",
+       "  table.iris {\n",
+       "      white-space: pre;\n",
+       "      border: 1px solid;\n",
+       "      border-color: #9c9c9c;\n",
+       "      font-family: monaco, monospace;\n",
+       "  }\n",
+       "  th.iris {\n",
+       "      background: #303f3f;\n",
+       "      color: #e0e0e0;\n",
+       "      border-left: 1px solid;\n",
+       "      border-color: #9c9c9c;\n",
+       "      font-size: 1.05em;\n",
+       "      min-width: 50px;\n",
+       "      max-width: 125px;\n",
+       "  }\n",
+       "  tr.iris :first-child {\n",
+       "      border-right: 1px solid #9c9c9c !important;\n",
+       "  }\n",
+       "  td.iris-title {\n",
+       "      background: #d5dcdf;\n",
+       "      border-top: 1px solid #9c9c9c;\n",
+       "      font-weight: bold;\n",
+       "  }\n",
+       "  .iris-word-cell {\n",
+       "      text-align: left !important;\n",
+       "      white-space: pre;\n",
+       "  }\n",
+       "  .iris-subheading-cell {\n",
+       "      padding-left: 2em !important;\n",
+       "  }\n",
+       "  .iris-inclusion-cell {\n",
+       "      padding-right: 1em !important;\n",
+       "  }\n",
+       "  .iris-panel-body {\n",
+       "      padding-top: 0px;\n",
+       "  }\n",
+       "  .iris-panel-title {\n",
+       "      padding-left: 3em;\n",
+       "  }\n",
+       "  .iris-panel-title {\n",
+       "      margin-top: 7px;\n",
+       "  }\n",
+       "</style>\n",
+       "<table class=\"iris\" id=\"22450468109184\">\n",
+       "    <tr class=\"iris\">\n",
+       "<th class=\"iris iris-word-cell\">Upward Air Velocity (m s-1)</th>\n",
+       "<th class=\"iris iris-word-cell\">model_level_number</th>\n",
+       "<th class=\"iris iris-word-cell\">latitude</th>\n",
+       "<th class=\"iris iris-word-cell\">longitude</th>\n",
+       "</tr>\n",
+       "    <tr class=\"iris\">\n",
+       "<td class=\"iris-word-cell iris-subheading-cell\">Shape</td>\n",
+       "<td class=\"iris iris-inclusion-cell\">70</td>\n",
+       "<td class=\"iris iris-inclusion-cell\">2120</td>\n",
+       "<td class=\"iris iris-inclusion-cell\">2600</td>\n",
+       "</tr>\n",
+       "    <tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Dimension coordinates</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tmodel_level_number</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tlatitude</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tlongitude</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Auxiliary coordinates</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tlevel_height</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tsigma</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Scalar coordinates</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tforecast_period</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">13.0 hours</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tforecast_reference_time</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">2022-02-21 12:00:00</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\ttime</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">2022-02-22 01:00:00</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Attributes</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tSTASH</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">m01s00i150</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tsource</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">&#x27;Data from Met Office Unified Model&#x27;</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tum_version</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">&#x27;12.2&#x27;</td>\n",
+       "</tr>\n",
+       "</table>\n",
+       "        </p>\n",
+       "</div>\n",
+       "    \n",
+       "\n",
+       "<button class=\"accordion-22450476936384\">10: x_wind / (m s-1)                    (model_level_number: 70; latitude: 2120; longitude: 2600)</button>\n",
+       "<div class=\"panel-22450476936384\">\n",
+       "    <p>\n",
+       "<style>\n",
+       "  a.iris {\n",
+       "      text-decoration: none !important;\n",
+       "  }\n",
+       "  table.iris {\n",
+       "      white-space: pre;\n",
+       "      border: 1px solid;\n",
+       "      border-color: #9c9c9c;\n",
+       "      font-family: monaco, monospace;\n",
+       "  }\n",
+       "  th.iris {\n",
+       "      background: #303f3f;\n",
+       "      color: #e0e0e0;\n",
+       "      border-left: 1px solid;\n",
+       "      border-color: #9c9c9c;\n",
+       "      font-size: 1.05em;\n",
+       "      min-width: 50px;\n",
+       "      max-width: 125px;\n",
+       "  }\n",
+       "  tr.iris :first-child {\n",
+       "      border-right: 1px solid #9c9c9c !important;\n",
+       "  }\n",
+       "  td.iris-title {\n",
+       "      background: #d5dcdf;\n",
+       "      border-top: 1px solid #9c9c9c;\n",
+       "      font-weight: bold;\n",
+       "  }\n",
+       "  .iris-word-cell {\n",
+       "      text-align: left !important;\n",
+       "      white-space: pre;\n",
+       "  }\n",
+       "  .iris-subheading-cell {\n",
+       "      padding-left: 2em !important;\n",
+       "  }\n",
+       "  .iris-inclusion-cell {\n",
+       "      padding-right: 1em !important;\n",
+       "  }\n",
+       "  .iris-panel-body {\n",
+       "      padding-top: 0px;\n",
+       "  }\n",
+       "  .iris-panel-title {\n",
+       "      padding-left: 3em;\n",
+       "  }\n",
+       "  .iris-panel-title {\n",
+       "      margin-top: 7px;\n",
+       "  }\n",
+       "</style>\n",
+       "<table class=\"iris\" id=\"22450467646144\">\n",
+       "    <tr class=\"iris\">\n",
+       "<th class=\"iris iris-word-cell\">X Wind (m s-1)</th>\n",
+       "<th class=\"iris iris-word-cell\">model_level_number</th>\n",
+       "<th class=\"iris iris-word-cell\">latitude</th>\n",
+       "<th class=\"iris iris-word-cell\">longitude</th>\n",
+       "</tr>\n",
+       "    <tr class=\"iris\">\n",
+       "<td class=\"iris-word-cell iris-subheading-cell\">Shape</td>\n",
+       "<td class=\"iris iris-inclusion-cell\">70</td>\n",
+       "<td class=\"iris iris-inclusion-cell\">2120</td>\n",
+       "<td class=\"iris iris-inclusion-cell\">2600</td>\n",
+       "</tr>\n",
+       "    <tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Dimension coordinates</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tmodel_level_number</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tlatitude</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tlongitude</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Auxiliary coordinates</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tlevel_height</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tsigma</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Scalar coordinates</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tforecast_period</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">13.0 hours</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tforecast_reference_time</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">2022-02-21 12:00:00</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\ttime</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">2022-02-22 01:00:00</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Attributes</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tSTASH</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">m01s00i002</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tsource</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">&#x27;Data from Met Office Unified Model&#x27;</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tum_version</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">&#x27;12.2&#x27;</td>\n",
+       "</tr>\n",
+       "</table>\n",
+       "        </p>\n",
+       "</div>\n",
+       "    \n",
+       "\n",
+       "<button class=\"accordion-22450476936384\">11: y_wind / (m s-1)                    (model_level_number: 70; latitude: 2121; longitude: 2600)</button>\n",
+       "<div class=\"panel-22450476936384\">\n",
+       "    <p>\n",
+       "<style>\n",
+       "  a.iris {\n",
+       "      text-decoration: none !important;\n",
+       "  }\n",
+       "  table.iris {\n",
+       "      white-space: pre;\n",
+       "      border: 1px solid;\n",
+       "      border-color: #9c9c9c;\n",
+       "      font-family: monaco, monospace;\n",
+       "  }\n",
+       "  th.iris {\n",
+       "      background: #303f3f;\n",
+       "      color: #e0e0e0;\n",
+       "      border-left: 1px solid;\n",
+       "      border-color: #9c9c9c;\n",
+       "      font-size: 1.05em;\n",
+       "      min-width: 50px;\n",
+       "      max-width: 125px;\n",
+       "  }\n",
+       "  tr.iris :first-child {\n",
+       "      border-right: 1px solid #9c9c9c !important;\n",
+       "  }\n",
+       "  td.iris-title {\n",
+       "      background: #d5dcdf;\n",
+       "      border-top: 1px solid #9c9c9c;\n",
+       "      font-weight: bold;\n",
+       "  }\n",
+       "  .iris-word-cell {\n",
+       "      text-align: left !important;\n",
+       "      white-space: pre;\n",
+       "  }\n",
+       "  .iris-subheading-cell {\n",
+       "      padding-left: 2em !important;\n",
+       "  }\n",
+       "  .iris-inclusion-cell {\n",
+       "      padding-right: 1em !important;\n",
+       "  }\n",
+       "  .iris-panel-body {\n",
+       "      padding-top: 0px;\n",
+       "  }\n",
+       "  .iris-panel-title {\n",
+       "      padding-left: 3em;\n",
+       "  }\n",
+       "  .iris-panel-title {\n",
+       "      margin-top: 7px;\n",
+       "  }\n",
+       "</style>\n",
+       "<table class=\"iris\" id=\"22450466726144\">\n",
+       "    <tr class=\"iris\">\n",
+       "<th class=\"iris iris-word-cell\">Y Wind (m s-1)</th>\n",
+       "<th class=\"iris iris-word-cell\">model_level_number</th>\n",
+       "<th class=\"iris iris-word-cell\">latitude</th>\n",
+       "<th class=\"iris iris-word-cell\">longitude</th>\n",
+       "</tr>\n",
+       "    <tr class=\"iris\">\n",
+       "<td class=\"iris-word-cell iris-subheading-cell\">Shape</td>\n",
+       "<td class=\"iris iris-inclusion-cell\">70</td>\n",
+       "<td class=\"iris iris-inclusion-cell\">2121</td>\n",
+       "<td class=\"iris iris-inclusion-cell\">2600</td>\n",
+       "</tr>\n",
+       "    <tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Dimension coordinates</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tmodel_level_number</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tlatitude</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tlongitude</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Auxiliary coordinates</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tlevel_height</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tsigma</td>\n",
+       "    <td class=\"iris-inclusion-cell\">x</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "    <td class=\"iris-inclusion-cell\">-</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Scalar coordinates</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tforecast_period</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">13.0 hours</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tforecast_reference_time</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">2022-02-21 12:00:00</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\ttime</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">2022-02-22 01:00:00</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-title iris-word-cell\">Attributes</td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "    <td class=\"iris-title\"></td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tSTASH</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">m01s00i003</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tsource</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">&#x27;Data from Met Office Unified Model&#x27;</td>\n",
+       "</tr>\n",
+       "<tr class=\"iris\">\n",
+       "    <td class=\"iris-word-cell iris-subheading-cell\">\tum_version</td>\n",
+       "    <td class=\"iris-word-cell\" colspan=\"3\">&#x27;12.2&#x27;</td>\n",
+       "</tr>\n",
+       "</table>\n",
+       "        </p>\n",
+       "</div>\n",
+       "    \n",
+       "    "
+      ],
+      "text/plain": [
+       "[<iris 'Cube' of m01s03i468 / (unknown) (model_level_number: 45; latitude: 2120; longitude: 2600)>,\n",
+       "<iris 'Cube' of m01s03i473 / (unknown) (model_level_number: 45; latitude: 2120; longitude: 2600)>,\n",
+       "<iris 'Cube' of air_potential_temperature / (K) (model_level_number: 70; latitude: 2120; longitude: 2600)>,\n",
+       "<iris 'Cube' of air_pressure / (Pa) (model_level_number: 71; latitude: 2120; longitude: 2600)>,\n",
+       "<iris 'Cube' of air_pressure / (Pa) (model_level_number: 70; latitude: 2120; longitude: 2600)>,\n",
+       "<iris 'Cube' of air_temperature / (K) (model_level_number: 70; latitude: 2120; longitude: 2600)>,\n",
+       "<iris 'Cube' of height_above_reference_ellipsoid / (m) (model_level_number: 70; latitude: 2120; longitude: 2600)>,\n",
+       "<iris 'Cube' of height_above_reference_ellipsoid / (m) (model_level_number: 70; latitude: 2120; longitude: 2600)>,\n",
+       "<iris 'Cube' of specific_humidity / (kg kg-1) (model_level_number: 70; latitude: 2120; longitude: 2600)>,\n",
+       "<iris 'Cube' of upward_air_velocity / (m s-1) (model_level_number: 70; latitude: 2120; longitude: 2600)>,\n",
+       "<iris 'Cube' of x_wind / (m s-1) (model_level_number: 70; latitude: 2120; longitude: 2600)>,\n",
+       "<iris 'Cube' of y_wind / (m s-1) (model_level_number: 70; latitude: 2121; longitude: 2600)>]"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cubes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "1c768908-839b-48f5-8964-c9972301a2a1",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "theta_da=xr.DataArray.from_iris(cubes[6]).chunk({\"model_level_number\":-1,\"latitude\":106,\"longitude\":130})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "cfda931c-33a8-4484-aea7-8def58ec1cb6",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "#small_da=theta_da.sel(latitude=-6.851597,longitude=slice(143.1,143.5))\n",
+    "small_da=theta_da.sel(latitude=-6.851597,method='nearest').sel(longitude=slice(143.09,143.5))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "878ed7ac-c81f-4047-88ce-6866d2c79243",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
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+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;height_above_reference_ellipsoid&#x27; (model_level_number: 70,\n",
+       "                                                      longitude: 21)&gt;\n",
+       "dask.array&lt;getitem, shape=(70, 21), dtype=float64, chunksize=(70, 21), chunktype=numpy.ndarray&gt;\n",
+       "Coordinates:\n",
+       "  * model_level_number       (model_level_number) int64 1 2 3 4 ... 67 68 69 70\n",
+       "    latitude                 float32 -6.852\n",
+       "  * longitude                (longitude) float32 143.1 143.1 ... 143.5 143.5\n",
+       "    forecast_period          timedelta64[ns] ...\n",
+       "    forecast_reference_time  datetime64[ns] ...\n",
+       "    time                     datetime64[ns] ...\n",
+       "    level_height             (model_level_number) float64 dask.array&lt;chunksize=(70,), meta=np.ndarray&gt;\n",
+       "    sigma                    (model_level_number) float64 dask.array&lt;chunksize=(70,), meta=np.ndarray&gt;\n",
+       "Attributes:\n",
+       "    standard_name:  height_above_reference_ellipsoid\n",
+       "    units:          m\n",
+       "    source:         Data from Met Office Unified Model\n",
+       "    um_version:     12.2\n",
+       "    STASH:          m01s15i101</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'height_above_reference_ellipsoid'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>model_level_number</span>: 70</li><li><span class='xr-has-index'>longitude</span>: 21</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-722f8f11-5116-473c-8240-ed2fe40df72f' class='xr-array-in' type='checkbox' checked><label for='section-722f8f11-5116-473c-8240-ed2fe40df72f' 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>dask.array&lt;chunksize=(70, 21), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 11.48 kiB </td>\n",
+       "                        <td> 11.48 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (70, 21) </td>\n",
+       "                        <td> (70, 21) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 147 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"93\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"43\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"43\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"43\" y1=\"0\" x2=\"43\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 43.54481495527667,0.0 43.54481495527667,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"21.772407\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >21</text>\n",
+       "  <text x=\"63.544815\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,63.544815,60.000000)\">70</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></div></li><li class='xr-section-item'><input id='section-ab88e1eb-4221-4905-b83b-5ab0da761c39' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ab88e1eb-4221-4905-b83b-5ab0da761c39' class='xr-section-summary' >Coordinates: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>model_level_number</span></div><div class='xr-var-dims'>(model_level_number)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 2 3 4 5 6 7 ... 65 66 67 68 69 70</div><input id='attrs-ca5c3f2f-6a30-49fd-bb09-c9c6394f79ac' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ca5c3f2f-6a30-49fd-bb09-c9c6394f79ac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2381dbf7-2061-4628-bf09-25b6d40fe305' class='xr-var-data-in' type='checkbox'><label for='data-2381dbf7-2061-4628-bf09-25b6d40fe305' 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>standard_name :</span></dt><dd>model_level_number</dd><dt><span>positive :</span></dt><dd>up</dd></dl></div><div class='xr-var-data'><pre>array([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17, 18,\n",
+       "       19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36,\n",
+       "       37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54,\n",
+       "       55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-6.852</div><input id='attrs-63082394-c846-48f3-b593-af41d01abadd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-63082394-c846-48f3-b593-af41d01abadd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c2b9c763-f467-4737-be17-33d3a4b2a1b2' class='xr-var-data-in' type='checkbox'><label for='data-c2b9c763-f467-4737-be17-33d3a4b2a1b2' 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>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees</dd></dl></div><div class='xr-var-data'><pre>array(-6.851597, dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>143.1 143.1 143.1 ... 143.5 143.5</div><input id='attrs-d2398666-be0d-4d4a-a4c3-2ee57d01144e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d2398666-be0d-4d4a-a4c3-2ee57d01144e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-622fb437-fea6-4137-b8f9-93a7df0aa9b2' class='xr-var-data-in' type='checkbox'><label for='data-622fb437-fea6-4137-b8f9-93a7df0aa9b2' 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>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees</dd></dl></div><div class='xr-var-data'><pre>array([143.1006 , 143.12039, 143.1402 , 143.16   , 143.1798 , 143.1996 ,\n",
+       "       143.21939, 143.2392 , 143.259  , 143.2788 , 143.2986 , 143.31839,\n",
+       "       143.3382 , 143.358  , 143.37779, 143.3976 , 143.41739, 143.4372 ,\n",
+       "       143.457  , 143.47679, 143.4966 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>forecast_period</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e351e4a2-9d11-40cd-b9f6-071e9831a8c7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e351e4a2-9d11-40cd-b9f6-071e9831a8c7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0c8fb467-003c-44dd-85fa-a828946c8eea' class='xr-var-data-in' type='checkbox'><label for='data-0c8fb467-003c-44dd-85fa-a828946c8eea' 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>standard_name :</span></dt><dd>forecast_period</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=timedelta64[ns]]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>forecast_reference_time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9a99b6d2-1e16-4bb8-930b-7705cda4beae' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9a99b6d2-1e16-4bb8-930b-7705cda4beae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b46cc25a-5c61-4382-b4a0-6198837ea663' class='xr-var-data-in' type='checkbox'><label for='data-b46cc25a-5c61-4382-b4a0-6198837ea663' 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>standard_name :</span></dt><dd>forecast_reference_time</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>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0058a1f7-3892-463f-b971-a8d62f6b1545' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0058a1f7-3892-463f-b971-a8d62f6b1545' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b940c8ea-ff9c-43f5-84fe-99bea3fed040' class='xr-var-data-in' type='checkbox'><label for='data-b940c8ea-ff9c-43f5-84fe-99bea3fed040' 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>standard_name :</span></dt><dd>time</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>level_height</span></div><div class='xr-var-dims'>(model_level_number)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(70,), meta=np.ndarray&gt;</div><input id='attrs-95db26ad-d911-4c1f-96db-0092c80fb780' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-95db26ad-d911-4c1f-96db-0092c80fb780' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f8e9536e-1279-4dee-94fc-1ea84d392678' class='xr-var-data-in' type='checkbox'><label for='data-f8e9536e-1279-4dee-94fc-1ea84d392678' 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>level_height</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>positive :</span></dt><dd>up</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 560 B </td>\n",
+       "                        <td> 560 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (70,) </td>\n",
+       "                        <td> (70,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"77\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"27\" x2=\"120\" y2=\"27\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"27\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"27\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,27.20110529785043 0.0,27.20110529785043\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"47.201105\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >70</text>\n",
+       "  <text x=\"140.000000\" y=\"13.600553\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,13.600553)\">1</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sigma</span></div><div class='xr-var-dims'>(model_level_number)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(70,), meta=np.ndarray&gt;</div><input id='attrs-a481a28e-1faf-4250-8c70-b392834b9175' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a481a28e-1faf-4250-8c70-b392834b9175' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-63185bd5-0bff-43a5-850d-a522ae0dbe8f' class='xr-var-data-in' type='checkbox'><label for='data-63185bd5-0bff-43a5-850d-a522ae0dbe8f' 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>sigma</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 560 B </td>\n",
+       "                        <td> 560 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (70,) </td>\n",
+       "                        <td> (70,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"77\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"27\" x2=\"120\" y2=\"27\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"27\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"27\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,27.20110529785043 0.0,27.20110529785043\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"47.201105\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >70</text>\n",
+       "  <text x=\"140.000000\" y=\"13.600553\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,13.600553)\">1</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-a7334780-cc58-4046-99ee-f75c8866f12c' class='xr-section-summary-in' type='checkbox'  ><label for='section-a7334780-cc58-4046-99ee-f75c8866f12c' class='xr-section-summary' >Indexes: <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-index-name'><div>model_level_number</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b8681e0d-08a5-4759-84a0-9efe03021e23' class='xr-index-data-in' type='checkbox'/><label for='index-b8681e0d-08a5-4759-84a0-9efe03021e23' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Int64Index([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
+       "            18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34,\n",
+       "            35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51,\n",
+       "            52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68,\n",
+       "            69, 70],\n",
+       "           dtype=&#x27;int64&#x27;, name=&#x27;model_level_number&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>longitude</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ac5a64c6-c642-47ba-aa61-acc48d9cb3f1' class='xr-index-data-in' type='checkbox'/><label for='index-ac5a64c6-c642-47ba-aa61-acc48d9cb3f1' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([143.10060119628906, 143.12039184570312, 143.14019775390625,\n",
+       "              143.16000366210938, 143.17979431152344, 143.19960021972656,\n",
+       "              143.21939086914062, 143.23919677734375, 143.25900268554688,\n",
+       "              143.27879333496094, 143.29859924316406, 143.31838989257812,\n",
+       "              143.33819580078125, 143.35800170898438, 143.37779235839844,\n",
+       "              143.39759826660156, 143.41738891601562, 143.43719482421875,\n",
+       "              143.45700073242188, 143.47679138183594, 143.49659729003906],\n",
+       "             dtype=&#x27;float64&#x27;, name=&#x27;longitude&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-eb7f3253-1ec8-4a38-9693-1cbb310de857' class='xr-section-summary-in' type='checkbox'  checked><label for='section-eb7f3253-1ec8-4a38-9693-1cbb310de857' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>height_above_reference_ellipsoid</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>source :</span></dt><dd>Data from Met Office Unified Model</dd><dt><span>um_version :</span></dt><dd>12.2</dd><dt><span>STASH :</span></dt><dd>m01s15i101</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.DataArray 'height_above_reference_ellipsoid' (model_level_number: 70,\n",
+       "                                                      longitude: 21)>\n",
+       "dask.array<getitem, shape=(70, 21), dtype=float64, chunksize=(70, 21), chunktype=numpy.ndarray>\n",
+       "Coordinates:\n",
+       "  * model_level_number       (model_level_number) int64 1 2 3 4 ... 67 68 69 70\n",
+       "    latitude                 float32 -6.852\n",
+       "  * longitude                (longitude) float32 143.1 143.1 ... 143.5 143.5\n",
+       "    forecast_period          timedelta64[ns] ...\n",
+       "    forecast_reference_time  datetime64[ns] ...\n",
+       "    time                     datetime64[ns] ...\n",
+       "    level_height             (model_level_number) float64 dask.array<chunksize=(70,), meta=np.ndarray>\n",
+       "    sigma                    (model_level_number) float64 dask.array<chunksize=(70,), meta=np.ndarray>\n",
+       "Attributes:\n",
+       "    standard_name:  height_above_reference_ellipsoid\n",
+       "    units:          m\n",
+       "    source:         Data from Met Office Unified Model\n",
+       "    um_version:     12.2\n",
+       "    STASH:          m01s15i101"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "small_da"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "dea78d57-7268-4022-a485-3ded27317d50",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x146b312281f0>,\n",
+       " <matplotlib.lines.Line2D at 0x146b312c90d0>,\n",
+       " <matplotlib.lines.Line2D at 0x146b2857cf40>,\n",
+       " <matplotlib.lines.Line2D at 0x146b28ae0640>,\n",
+       " <matplotlib.lines.Line2D at 0x146b28a948b0>,\n",
+       " <matplotlib.lines.Line2D at 0x146b287dac10>,\n",
+       " <matplotlib.lines.Line2D at 0x146b287da1f0>,\n",
+       " <matplotlib.lines.Line2D at 0x146b287dadf0>,\n",
+       " <matplotlib.lines.Line2D at 0x146b28777430>,\n",
+       " <matplotlib.lines.Line2D at 0x146b28777190>,\n",
+       " <matplotlib.lines.Line2D at 0x146b28777220>,\n",
+       " <matplotlib.lines.Line2D at 0x146b28777340>,\n",
+       " <matplotlib.lines.Line2D at 0x146b287774c0>,\n",
+       " <matplotlib.lines.Line2D at 0x146b287776a0>,\n",
+       " <matplotlib.lines.Line2D at 0x146b28777820>,\n",
+       " <matplotlib.lines.Line2D at 0x146b287778b0>,\n",
+       " <matplotlib.lines.Line2D at 0x146b28777e80>,\n",
+       " <matplotlib.lines.Line2D at 0x146b28777910>,\n",
+       " <matplotlib.lines.Line2D at 0x146b28777d30>,\n",
+       " <matplotlib.lines.Line2D at 0x146b28777a00>,\n",
+       " <matplotlib.lines.Line2D at 0x146b28777b20>,\n",
+       " <matplotlib.lines.Line2D at 0x146b2870e190>,\n",
+       " <matplotlib.lines.Line2D at 0x146b2870e310>,\n",
+       " <matplotlib.lines.Line2D at 0x146b2870e3d0>,\n",
+       " <matplotlib.lines.Line2D at 0x146b2870e490>,\n",
+       " <matplotlib.lines.Line2D at 0x146b2870eaf0>,\n",
+       " <matplotlib.lines.Line2D at 0x146b2870ec10>,\n",
+       " <matplotlib.lines.Line2D at 0x146b2870ec70>,\n",
+       " <matplotlib.lines.Line2D at 0x146b2870ed90>,\n",
+       " <matplotlib.lines.Line2D at 0x146b2870eee0>,\n",
+       " <matplotlib.lines.Line2D at 0x146b2870efd0>,\n",
+       " <matplotlib.lines.Line2D at 0x146b2870e730>,\n",
+       " <matplotlib.lines.Line2D at 0x146b2870ea60>,\n",
+       " <matplotlib.lines.Line2D at 0x146b28715070>,\n",
+       " <matplotlib.lines.Line2D at 0x146b28715100>,\n",
+       " <matplotlib.lines.Line2D at 0x146b28715340>,\n",
+       " <matplotlib.lines.Line2D at 0x146b28715eb0>,\n",
+       " <matplotlib.lines.Line2D at 0x146b28715940>,\n",
+       " <matplotlib.lines.Line2D at 0x146b28715970>,\n",
+       " <matplotlib.lines.Line2D at 0x146b28715be0>,\n",
+       " <matplotlib.lines.Line2D at 0x146b28715b80>,\n",
+       " <matplotlib.lines.Line2D at 0x146b28715d60>,\n",
+       " <matplotlib.lines.Line2D at 0x146b28715f70>,\n",
+       " <matplotlib.lines.Line2D at 0x146b287157f0>,\n",
+       " <matplotlib.lines.Line2D at 0x146b28715610>,\n",
+       " <matplotlib.lines.Line2D at 0x146b287240d0>,\n",
+       " <matplotlib.lines.Line2D at 0x146b28724190>,\n",
+       " <matplotlib.lines.Line2D at 0x146b287247f0>,\n",
+       " <matplotlib.lines.Line2D at 0x146b28724910>,\n",
+       " <matplotlib.lines.Line2D at 0x146b28724970>]"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "small_da[:50].plot.line(hue=\"model_level_number\",ax=ax1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "id": "92bfcec3-7d38-4b22-8587-b280067be0f8",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.contour.QuadContourSet at 0x1530d24c7250>"
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ds.orog[0].sel(longitude=slice(143,143.5),latitude=slice(-7.33,-6.83)).plot.contour()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "e275c5ee-9a17-4bef-8d65-26b31f7d8a38",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "fig"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1171e59f-08ec-4341-be16-bde5ca0b4eed",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python [conda env:analysis3-23.01]",
+   "language": "python",
+   "name": "conda-env-analysis3-23.01-py"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.15"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/Recipes/maxverticalwindmap.ipynb b/Recipes/maxverticalwindmap.ipynb
new file mode 100644
index 0000000..df75fd3
--- /dev/null
+++ b/Recipes/maxverticalwindmap.ipynb
@@ -0,0 +1,1302 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "645bc418-a8d8-4ea2-9fa0-890e29bcca48",
+   "metadata": {},
+   "source": [
+    "## Maximum vertial wind map\n",
+    "\n",
+    "Use data provided by the Unified Model's .pe0 file to geographically locate the site of the largest vertial winds within a model domain. Animate this data as the model progresses. Useful for diagnosing model instabilities."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "691460e8-3f7f-4ead-abd7-6aaefe11144c",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import xarray as xr\n",
+    "import datetime\n",
+    "import cartopy.crs as ccrs\n",
+    "from matplotlib import pyplot as plt, animation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "6cfd36d7-e5b2-402c-90af-ffc63086ad14",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "ts1=30\n",
+    "starttime=datetime.datetime(year=2022,month=2,day=21,hour=18)\n",
+    "td1=datetime.timedelta(seconds=ts1)\n",
+    "\n",
+    "ts2=75\n",
+    "td2=datetime.timedelta(seconds=ts2)\n",
+    "\n",
+    "tdg=datetime.timedelta(seconds=15)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "0847e72c-f217-4667-b901-c865c8f58522",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "ds=xr.open_dataset(f\"/g/data/hh5/tmp/WACI-Hackathon-2023/AUS2200/data/surf/orog_1hr_{(starttime + datetime.timedelta(hours=7)).strftime('%Y%m%d')}_20220307.nc\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "f66e93c6-7fbc-42d4-b990-b35a02ccdb44",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
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+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: '►';\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: '▼';\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: '(';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: ')';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: ',';\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
+       "Dimensions:    (latitude: 2120, longitude: 2600, time: 336)\n",
+       "Coordinates:\n",
+       "  * latitude   (latitude) float32 -48.79 -48.77 -48.75 ... -6.871 -6.852 -6.832\n",
+       "  * longitude  (longitude) float32 107.5 107.5 107.6 107.6 ... 158.9 159.0 159.0\n",
+       "  * time       (time) datetime64[ns] 2022-02-22T00:00:30 ... 2022-03-08\n",
+       "Data variables:\n",
+       "    orog       (time, latitude, longitude) float32 ...\n",
+       "Attributes: (12/25)\n",
+       "    Conventions:          CF-1.6, ACDD-1.3\n",
+       "    title:                AUS2200 UM amip simulation over Australian region f...\n",
+       "    summary:              A limited area model study of the entire Australian...\n",
+       "    source:               UM v12.2 ECMWF ERA5 forecast fields used as forcings\n",
+       "    license:              http://creativecommons.org/licenses/by/4.0/\n",
+       "    product_version:      0.1\n",
+       "    ...                   ...\n",
+       "    geospatial_lon_min:   107.5101\n",
+       "    geospatial_lon_max:   0.0198\n",
+       "    contributor_name:     Sam Green, Paola Petrelli\n",
+       "    contributor_email:    sam.green@unsw.edu.au, paola.petrelli@utas.edu.au\n",
+       "    contributor_url:      https://orcid.org/0000-0003-1129-4676, https://orci...\n",
+       "    contributor_role:     post-processing, post-processing</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-f20e9268-b56d-40bd-ab66-5a5f315f2d50' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f20e9268-b56d-40bd-ab66-5a5f315f2d50' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>latitude</span>: 2120</li><li><span class='xr-has-index'>longitude</span>: 2600</li><li><span class='xr-has-index'>time</span>: 336</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-c2427f26-f7f2-45d4-ab5d-20156afed01d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c2427f26-f7f2-45d4-ab5d-20156afed01d' class='xr-section-summary' >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'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-48.79 -48.77 ... -6.852 -6.832</div><input id='attrs-48871bc2-e629-4e69-b70d-deeb99a21a2d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-48871bc2-e629-4e69-b70d-deeb99a21a2d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-36792302-da28-4da4-ad47-be52727c68db' class='xr-var-data-in' type='checkbox'><label for='data-36792302-da28-4da4-ad47-be52727c68db' 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>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees</dd></dl></div><div class='xr-var-data'><pre>array([-48.788   , -48.7682  , -48.748398, ...,  -6.871399,  -6.851597,\n",
+       "        -6.831799], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>107.5 107.5 107.6 ... 159.0 159.0</div><input id='attrs-5702233d-f280-4577-9156-dcf99708779d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5702233d-f280-4577-9156-dcf99708779d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bbabdb07-f086-4dfa-aa3c-62aef5557356' class='xr-var-data-in' type='checkbox'><label for='data-bbabdb07-f086-4dfa-aa3c-62aef5557356' 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>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees</dd></dl></div><div class='xr-var-data'><pre>array([107.52    , 107.539795, 107.55959 , ..., 158.9406  , 158.96039 ,\n",
+       "       158.9802  ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-02-22T00:00:30 ... 2022-03-08</div><input id='attrs-223be4db-6e97-45fb-97a1-a71c39cfd0f4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-223be4db-6e97-45fb-97a1-a71c39cfd0f4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3667dde2-832e-4370-ab31-285da751348c' class='xr-var-data-in' type='checkbox'><label for='data-3667dde2-832e-4370-ab31-285da751348c' 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>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-02-22T00:00:30.000000000&#x27;, &#x27;2022-02-22T02:00:00.000000000&#x27;,\n",
+       "       &#x27;2022-02-22T03:00:00.000000000&#x27;, ..., &#x27;2022-03-07T22:00:00.000000000&#x27;,\n",
+       "       &#x27;2022-03-07T23:00:00.000000000&#x27;, &#x27;2022-03-08T00:00:00.000000000&#x27;],\n",
+       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f30ebcea-d9ef-40cd-af19-db7d0ad896e1' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f30ebcea-d9ef-40cd-af19-db7d0ad896e1' class='xr-section-summary' >Data variables: <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>orog</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-2db6d44d-8414-4d4b-ab24-fb17fe63686d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2db6d44d-8414-4d4b-ab24-fb17fe63686d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cd76d5fa-1d15-4a2d-89dc-945979f1534d' class='xr-var-data-in' type='checkbox'><label for='data-cd76d5fa-1d15-4a2d-89dc-945979f1534d' 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>standard_name :</span></dt><dd>surface_altitude</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>source :</span></dt><dd>Data from Met Office Unified Model</dd><dt><span>um_version :</span></dt><dd>12.2</dd><dt><span>STASH :</span></dt><dd>[ 1  0 33]</dd></dl></div><div class='xr-var-data'><pre>[1852032000 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8dc4d7d8-f05e-4db8-9e75-21efbf200cc6' class='xr-section-summary-in' type='checkbox'  ><label for='section-8dc4d7d8-f05e-4db8-9e75-21efbf200cc6' class='xr-section-summary' >Indexes: <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-index-name'><div>latitude</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-a2a6b19b-4d70-45e0-a89b-16fd8173114f' class='xr-index-data-in' type='checkbox'/><label for='index-a2a6b19b-4d70-45e0-a89b-16fd8173114f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([ -48.78799819946289,   -48.7681999206543,  -48.74839782714844,\n",
+       "              -48.728599548339844, -48.708797454833984,  -48.68899917602539,\n",
+       "               -48.66919708251953,  -48.64939880371094,  -48.62959671020508,\n",
+       "              -48.609798431396484,\n",
+       "              ...\n",
+       "               -7.009998321533203,  -6.990200042724609,   -6.97039794921875,\n",
+       "               -6.950599670410156,  -6.930797576904297,  -6.910999298095703,\n",
+       "               -6.891197204589844,   -6.87139892578125,  -6.851596832275391,\n",
+       "               -6.831798553466797],\n",
+       "             dtype=&#x27;float64&#x27;, name=&#x27;latitude&#x27;, length=2120))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>longitude</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-9f3e7501-e606-4a51-b2bf-3496482a320d' class='xr-index-data-in' type='checkbox'/><label for='index-9f3e7501-e606-4a51-b2bf-3496482a320d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([ 107.5199966430664,   107.539794921875,  107.5595932006836,\n",
+       "              107.57939910888672, 107.59919738769531,  107.6189956665039,\n",
+       "               107.6387939453125, 107.65859985351562, 107.67839813232422,\n",
+       "              107.69819641113281,\n",
+       "              ...\n",
+       "                158.802001953125, 158.82179260253906,  158.8415985107422,\n",
+       "              158.86138916015625, 158.88119506835938,  158.9010009765625,\n",
+       "              158.92079162597656,  158.9405975341797, 158.96038818359375,\n",
+       "              158.98019409179688],\n",
+       "             dtype=&#x27;float64&#x27;, name=&#x27;longitude&#x27;, length=2600))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-aaf762d4-4310-4e2d-90c4-56634325d84f' class='xr-index-data-in' type='checkbox'/><label for='index-aaf762d4-4310-4e2d-90c4-56634325d84f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2022-02-22 00:00:30&#x27;, &#x27;2022-02-22 02:00:00&#x27;,\n",
+       "               &#x27;2022-02-22 03:00:00&#x27;, &#x27;2022-02-22 04:00:00&#x27;,\n",
+       "               &#x27;2022-02-22 05:00:00&#x27;, &#x27;2022-02-22 06:00:00&#x27;,\n",
+       "               &#x27;2022-02-22 06:00:30&#x27;, &#x27;2022-02-22 08:00:00&#x27;,\n",
+       "               &#x27;2022-02-22 09:00:00&#x27;, &#x27;2022-02-22 10:00:00&#x27;,\n",
+       "               ...\n",
+       "               &#x27;2022-03-07 15:00:00&#x27;, &#x27;2022-03-07 16:00:00&#x27;,\n",
+       "               &#x27;2022-03-07 17:00:00&#x27;, &#x27;2022-03-07 18:00:00&#x27;,\n",
+       "               &#x27;2022-03-07 18:00:30&#x27;, &#x27;2022-03-07 20:00:00&#x27;,\n",
+       "               &#x27;2022-03-07 21:00:00&#x27;, &#x27;2022-03-07 22:00:00&#x27;,\n",
+       "               &#x27;2022-03-07 23:00:00&#x27;, &#x27;2022-03-08 00:00:00&#x27;],\n",
+       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=336, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6267978e-2a12-4546-96c4-86dc12f40f4f' class='xr-section-summary-in' type='checkbox'  ><label for='section-6267978e-2a12-4546-96c4-86dc12f40f4f' class='xr-section-summary' >Attributes: <span>(25)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6, ACDD-1.3</dd><dt><span>title :</span></dt><dd>AUS2200 UM amip simulation over Australian region for the 22 Feb to 07 Mar 2022</dd><dt><span>summary :</span></dt><dd>A limited area model study of the entire Australian continent at 2.2 km resolution, using the UM atmospheric model. ERA5 and ERA5 land reanalysis datasets were used to provide intial and boundary conditions. The study covers the time period of 2022-02-22 to 2022-03-7 including high rainfall events</dd><dt><span>source :</span></dt><dd>UM v12.2 ECMWF ERA5 forecast fields used as forcings</dd><dt><span>license :</span></dt><dd>http://creativecommons.org/licenses/by/4.0/</dd><dt><span>product_version :</span></dt><dd>0.1</dd><dt><span>contact :</span></dt><dd>dsroberts@unimelb.edu.au</dd><dt><span>institution :</span></dt><dd>Melbourne University</dd><dt><span>organisation :</span></dt><dd>ARC Centre of Excellence for Climate Extremes</dd><dt><span>keywords :</span></dt><dd>Cloud Physics, Meteorology, Atmospheric Dynamics</dd><dt><span>date_created :</span></dt><dd>2023-02-13</dd><dt><span>creator_name :</span></dt><dd>Dale Roberts</dd><dt><span>creator_email :</span></dt><dd>dsroberts@unimelb.edu.au</dd><dt><span>creator_url :</span></dt><dd>https://orcid.org/0000-0003-3952-6344</dd><dt><span>creator_role :</span></dt><dd>running model, post-processing</dd><dt><span>time_coverage_start :</span></dt><dd>2022-02-22</dd><dt><span>time_coverage_end :</span></dt><dd>2022-03-07</dd><dt><span>geospatial_lat_min :</span></dt><dd>-48.788</dd><dt><span>geospatial_lat_max :</span></dt><dd>-6.831799</dd><dt><span>geospatial_lon_min :</span></dt><dd>107.5101</dd><dt><span>geospatial_lon_max :</span></dt><dd>0.0198</dd><dt><span>contributor_name :</span></dt><dd>Sam Green, Paola Petrelli</dd><dt><span>contributor_email :</span></dt><dd>sam.green@unsw.edu.au, paola.petrelli@utas.edu.au</dd><dt><span>contributor_url :</span></dt><dd>https://orcid.org/0000-0003-1129-4676, https://orcid.org/0000-0002-0164-5105</dd><dt><span>contributor_role :</span></dt><dd>post-processing, post-processing</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset>\n",
+       "Dimensions:    (latitude: 2120, longitude: 2600, time: 336)\n",
+       "Coordinates:\n",
+       "  * latitude   (latitude) float32 -48.79 -48.77 -48.75 ... -6.871 -6.852 -6.832\n",
+       "  * longitude  (longitude) float32 107.5 107.5 107.6 107.6 ... 158.9 159.0 159.0\n",
+       "  * time       (time) datetime64[ns] 2022-02-22T00:00:30 ... 2022-03-08\n",
+       "Data variables:\n",
+       "    orog       (time, latitude, longitude) float32 ...\n",
+       "Attributes: (12/25)\n",
+       "    Conventions:          CF-1.6, ACDD-1.3\n",
+       "    title:                AUS2200 UM amip simulation over Australian region f...\n",
+       "    summary:              A limited area model study of the entire Australian...\n",
+       "    source:               UM v12.2 ECMWF ERA5 forecast fields used as forcings\n",
+       "    license:              http://creativecommons.org/licenses/by/4.0/\n",
+       "    product_version:      0.1\n",
+       "    ...                   ...\n",
+       "    geospatial_lon_min:   107.5101\n",
+       "    geospatial_lon_max:   0.0198\n",
+       "    contributor_name:     Sam Green, Paola Petrelli\n",
+       "    contributor_email:    sam.green@unsw.edu.au, paola.petrelli@utas.edu.au\n",
+       "    contributor_url:      https://orcid.org/0000-0003-1129-4676, https://orci...\n",
+       "    contributor_role:     post-processing, post-processing"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "d15410bc-a14c-4769-866c-aba7013f7381",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "x_min=min(ds.longitude)\n",
+    "x_max=max(ds.longitude)\n",
+    "y_min=min(ds.latitude)\n",
+    "y_max=max(ds.latitude)\n",
+    "ex=(x_min,x_max,y_min,y_max)\n",
+    "x_minf=x_min.data.item()\n",
+    "x_maxf=x_max.data.item()\n",
+    "y_minf=y_min.data.item()\n",
+    "y_maxf=y_max.data.item()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "c00cb7db-1f68-49b6-90c7-2e15377ddfe0",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
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+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;longitude&#x27; ()&gt;\n",
+       "array(158.9802, dtype=float32)\n",
+       "Coordinates:\n",
+       "    longitude  float32 159.0\n",
+       "Attributes:\n",
+       "    standard_name:  longitude\n",
+       "    units:          degrees</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'longitude'</div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-fc884690-e37f-42b5-938a-6824b52173dd' class='xr-array-in' type='checkbox' checked><label for='section-fc884690-e37f-42b5-938a-6824b52173dd' 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>159.0</span></div><div class='xr-array-data'><pre>array(158.9802, dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-3236d65c-6e55-4c98-b31a-0071b9d26b44' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3236d65c-6e55-4c98-b31a-0071b9d26b44' class='xr-section-summary' >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>longitude</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>159.0</div><input id='attrs-984eec8d-0bb2-4c55-94e0-c8b5b9a4dc60' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-984eec8d-0bb2-4c55-94e0-c8b5b9a4dc60' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c5fc6621-353c-4542-98ba-6b98d6496d50' class='xr-var-data-in' type='checkbox'><label for='data-c5fc6621-353c-4542-98ba-6b98d6496d50' 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>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees</dd></dl></div><div class='xr-var-data'><pre>array(158.9802, dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6baa7649-666d-4d5e-b1a7-4a6f4aedeb3d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6baa7649-666d-4d5e-b1a7-4a6f4aedeb3d' class='xr-section-summary'  title='Expand/collapse section'>Indexes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-b90dbb07-ba44-4e64-9c48-a2a2667317a5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b90dbb07-ba44-4e64-9c48-a2a2667317a5' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.DataArray 'longitude' ()>\n",
+       "array(158.9802, dtype=float32)\n",
+       "Coordinates:\n",
+       "    longitude  float32 159.0\n",
+       "Attributes:\n",
+       "    standard_name:  longitude\n",
+       "    units:          degrees"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "x_max"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "1bd310a8-3cd8-4179-98dd-fa21b1e87b64",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ax=plt.axes(projection=ccrs.PlateCarree())\n",
+    "ax.coastlines('50m',linewidth=1)\n",
+    "ax.set_extent(ex)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "50b9c447-4045-408d-91d4-c1232ae76a7d",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x150109905400>"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ds.orog[0].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "cf56362e-c7f7-4219-a804-5644b50b9904",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "prefix=f'/scratch/w40/dr4292/aus2200-instability-analysis/{ts1}sec/'\n",
+    "suffix='Z/aus2200_d0198_RA3_um_fcst_000/pe_output/umnsa.fort6.pe0000'\n",
+    "lines30=[]\n",
+    "for f in ( f'{prefix}20220221T1800{suffix}', f'{prefix}20220222T0000{suffix}' ):\n",
+    "    with open(f,'r') as f:\n",
+    "        lines30.extend([ i.strip() for i in f.readlines() ])\n",
+    "prefix=f'/scratch/w40/dr4292/aus2200-instability-analysis/{ts2}sec/'\n",
+    "lines75=[]\n",
+    "for f in ( f'{prefix}20220221T1800{suffix}', f'{prefix}20220222T0000{suffix}' ):\n",
+    "    with open(f,'r') as f:\n",
+    "        lines75.extend([ i.strip() for i in f.readlines() ])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "a54bf3ef-b453-4dd9-afad-d2b5b31215d1",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "winddat30_lines=[]\n",
+    "countdown=-1\n",
+    "for l in lines30:\n",
+    "    countdown=countdown-1\n",
+    "    if l.startswith('Maximum vertical velocity'): countdown=2\n",
+    "    if countdown==0:\n",
+    "        winddat30_lines.append(l)\n",
+    "        \n",
+    "winddat75_lines=[]\n",
+    "countdown=-1\n",
+    "for l in lines75:\n",
+    "    countdown=countdown-1\n",
+    "    if l.startswith('Maximum vertical velocity'): countdown=2\n",
+    "    if countdown==0:\n",
+    "        winddat75_lines.append(l)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "efc9f882-734d-4853-a5cf-e5bbb1abe0e0",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "winddat30=[ ( starttime+it*td1,float(i.split()[0]),int(i.split()[1]),x_minf+(float(i.split()[3].strip('%'))/100.0)*(x_maxf-x_minf),y_minf+(float(i.split()[5].strip('%'))/100.0)*(y_maxf-y_minf))  for it,i in enumerate(winddat30_lines) ]\n",
+    "winddat75=[ ( starttime+it*td2,float(i.split()[0]),int(i.split()[1]),x_minf+(float(i.split()[3].strip('%'))/100.0)*(x_maxf-x_minf),y_minf+(float(i.split()[5].strip('%'))/100.0)*(y_maxf-y_minf))  for it,i in enumerate(winddat75_lines) ]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "0acdd0e1-4dc5-4991-9599-419c577100fd",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "time=starttime\n",
+    "i30=0\n",
+    "i75=0\n",
+    "while True:\n",
+    "    _,_,lev30,x30,y30=winddat30[i30]\n",
+    "    _,_,lev75,x75,y75=winddat75[i75]\n",
+    "    ax=plt.axes(projection=ccrs.PlateCarree())\n",
+    "    ax.coastlines('10m',linewidth=1)\n",
+    "    ax.set_extent(ex)\n",
+    "    ax.contourf(ds.longitude,ds.latitude,ds.orog[0],cmap='gist_earth')\n",
+    "    plt.title(time)\n",
+    "    a=plt.plot(x30,y30,marker=\"o\",markersize=7.5,markerfacecolor='red')\n",
+    "    b=plt.plot(x75,y75,marker=\"o\",markersize=7.5,markerfacecolor='lightgreen')\n",
+    "    c=plt.text(x30+1,y30,f\"Level {lev30}\",color='white')\n",
+    "    d=plt.text(x75+1,y75,f\"Level {lev75}\",color='white')\n",
+    "    plt.show()\n",
+    "    time=time+tdg\n",
+    "    if winddat30[i30+1][0] == time:\n",
+    "        i30 = i30+1\n",
+    "    if winddat75[i75+1][0] == time:\n",
+    "        i75 = i75+1\n",
+    "    break"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "940f27d2-d150-4bfa-b624-8c20a6442187",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 2000x1500 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure(layout=None,figsize=(20,15))\n",
+    "gs = fig.add_gridspec(ncols=1,nrows=20)\n",
+    "ax0 = fig.add_subplot(gs[:-5],projection=ccrs.PlateCarree())\n",
+    "\n",
+    "#fig,axs = plt.subplots(nrows=3,figsize=(13, 10.6),gridspec_kw={'height_ratios': [4, 1, 1]},subplot_kw={'projection':ccrs.PlateCarree()})\n",
+    "#ax = plt.axes(projection=ccrs.PlateCarree())\n",
+    "ax0.coastlines('10m',linewidth=1)\n",
+    "ax0.set_extent(ex)\n",
+    "ax0.contourf(ds.longitude,ds.latitude,ds.orog[0],cmap='gist_earth')\n",
+    "ax0.set_title(starttime)\n",
+    "_,vel30,lev30,x30,y30=winddat30[0]\n",
+    "a = ax0.plot(x30,y30,marker=\"o\",markersize=7.5,markerfacecolor='red')\n",
+    "#b = ax[0].text(x30+1,y30,f\"Level {lev30}\")\n",
+    "_,vel75,lev75,x75,y75=winddat75[0]\n",
+    "b = ax0.plot(x75,y75,marker=\"o\",markersize=7.5,markerfacecolor='lightgreen')\n",
+    "#d = ax.text(x75+1,y75,f\"Level {lev75}\")\n",
+    "\n",
+    "ax1 = fig.add_subplot(gs[-4])\n",
+    "line1, = ax1.step([], [], color='red')\n",
+    "line2, = ax1.step([], [], color='lightgreen')\n",
+    "ax1.set_ylim((0,70))\n",
+    "ax1.set_xlim((starttime,starttime+2880*tdg))\n",
+    "ax1.set_title(\"Vertical level\")\n",
+    "times=[starttime,]\n",
+    "levs30=[lev30,]\n",
+    "levs75=[lev75,]\n",
+    "line1.set_data(times,levs30)\n",
+    "line2.set_data(times,levs75)\n",
+    "\n",
+    "ax2 = fig.add_subplot(gs[-2])\n",
+    "line3, = ax2.step([],[], color='red')\n",
+    "line4, = ax2.step([],[], color='lightgreen')\n",
+    "ax2.set_title(\"Vertical velocity\")\n",
+    "ax2.set_ylim((0,70))\n",
+    "ax2.set_xlim((starttime,starttime+2880*tdg))\n",
+    "vels30=[vel30,]\n",
+    "vels75=[vel75,]\n",
+    "line3.set_data(times,vels30)\n",
+    "line4.set_data(times,vels75)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "9ab832e3-eb08-4dce-babc-9124f2410adb",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "def animate(frame):\n",
+    "    i30 = frame//2\n",
+    "    i75 = frame//5\n",
+    "    ax0.set_title(starttime + frame * tdg)\n",
+    "    times.append(starttime + frame * tdg)\n",
+    "    try:\n",
+    "        _,vel30,lev30,x30,y30=winddat30[i30]\n",
+    "        a[0].set_data((x30,y30))\n",
+    "        levs30.append(lev30)\n",
+    "        vels30.append(vel30)\n",
+    "        line1.set_data(times,levs30)\n",
+    "        line3.set_data(times,vels30)\n",
+    "    except:\n",
+    "        pass\n",
+    "    \n",
+    "    try:\n",
+    "        _,vel75,lev75,x75,y75=winddat75[i75]\n",
+    "        b[0].set_data((x75,y75))#,marker=\"o\",markersize=7.5,markerfacecolor='blue')\n",
+    "        levs75.append(lev75)\n",
+    "        vels75.append(vel75)\n",
+    "        line2.set_data(times,levs75)\n",
+    "        line4.set_data(times,vels75)\n",
+    "    except:\n",
+    "        b[0].set_data((0,0))\n",
+    "    if frame%100 == 0:\n",
+    "        print(f\"{frame} {i30} {i75} {x30} {y30}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "c1a80146-56de-4cc7-bca8-1e938f3058ab",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "ani = animation.FuncAnimation(\n",
+    "    fig,             # figure\n",
+    "    animate,         # name of the function above\n",
+    "    frames=2880,       # Could also be iterable or list\n",
+    "    interval=33     # ms between frames\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "077e051d-60d2-4e6b-8ed8-091f2200188c",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0 0 0 143.69651544952393 -13.838483894348144\n",
+      "0 0 0 143.69651544952393 -13.838483894348144\n",
+      "100 50 20 122.49491410064698 -10.188294525146482\n",
+      "200 100 40 122.28907331085205 -10.146338325500494\n",
+      "300 150 60 122.44345390319825 -10.398075523376463\n",
+      "400 200 80 122.34053350830078 -10.314163124084473\n",
+      "500 250 100 122.44345390319825 -10.69176892089844\n",
+      "600 300 120 126.30296871185303 -10.146338325500494\n",
+      "700 350 140 122.80367528533935 -11.0693747177124\n",
+      "800 400 160 122.75221508789063 -11.0693747177124\n",
+      "900 450 180 121.41424995422364 -10.272206924438478\n",
+      "1000 500 200 121.25986936187743 -10.356119323730475\n",
+      "1100 550 220 122.5463742980957 -11.027418518066405\n",
+      "1200 600 240 122.44345390319825 -11.027418518066405\n",
+      "1300 650 260 122.34053350830078 -11.0693747177124\n",
+      "1400 700 280 123.00951607513427 -11.111330917358394\n",
+      "1500 750 300 124.65624239349364 -11.446980514526366\n",
+      "1600 800 320 154.9662986907959 -15.390863281250006\n",
+      "1700 850 340 127.84677463531494 -12.537841705322265\n",
+      "1800 900 360 143.59359505462646 -28.103591773986818\n",
+      "1900 950 380 123.11243647003174 -11.405024314880372\n",
+      "2000 1000 400 122.5463742980957 -11.363068115234377\n",
+      "2100 1050 420 149.5629779586792 -10.104382125854492\n",
+      "2200 1100 440 150.95240328979492 -16.271943473815917\n",
+      "2300 1150 460 142.71877169799805 -28.98467196655273\n",
+      "2400 1200 480 126.04566772460937 -12.076323509216309\n",
+      "2500 1250 500 123.31827725982666 -11.740673912048337\n",
+      "2600 1300 520 118.58393909454345 -9.68482012939453\n",
+      "2700 1350 540 119.35584205627441 -10.272206924438478\n",
+      "2800 1400 560 122.95805587768555 -16.90128646850586\n"
+     ]
+    }
+   ],
+   "source": [
+    "ani.save(f\"/home/563/dr4292/aus2200_instability_analysis/multiplot.mp4\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a2c0de17-432b-4c82-ac03-a7bba728c1ca",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python [conda env:analysis3-23.01]",
+   "language": "python",
+   "name": "conda-env-analysis3-23.01-py"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.15"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}