{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "791acb4d-46bb-4ea4-a44d-28c1a2c5c785",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Demo for the AUS2200 intake catalogue"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1cc14a25-271e-458e-b6d0-1ea2a1cfe1c5",
   "metadata": {},
   "source": [
    "### How to load output for an experiment without knowledge where the output lives on NCI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "5e07cd11-e7c2-42b2-ae03-486402444db0",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import intake\n",
    "import cf_xarray"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "f1d4a27d-19df-4559-b597-b06475fec789",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "catalog = intake.cat.access_nri['AUS2200']\n",
    "\n",
    "# Until https://github.com/ACCESS-NRI/access-nri-intake-catalog/pull/621 is merged\n",
    "catalog = catalog.unwrap()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "309f1051-77ce-48de-ba01-54d1a2c0ff49",
   "metadata": {},
   "source": [
    "#### You can also explore datasets in the intake catalog via https://access-nri.github.io/interactive-data-catalogue/#/, which will give you an interactive way to explore them in a browser"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1e597611-1285-4727-97d2-47fb9fb7cb9e",
   "metadata": {},
   "source": [
    "List all the datasets available."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "69a1e6fd-9071-4ec1-8898-1e84a656db70",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['f.AUS2200.6hrPlev.zg.v1-0',\n",
       " 'f.AUS2200.1hr.pfull.v1-0',\n",
       " 'f.AUS2200.1hr.rsdsdiff.v1-0',\n",
       " 'f.AUS2200.1hr.hus.v1-0',\n",
       " 'f.AUS2200.1hr.va.v1-0']"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(catalog)[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "69010826-c3bc-4dc3-a83a-c0a1ef22e6d5",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<p><strong>AUS2200 catalog with 61 dataset(s) from 21471 asset(s)</strong>:</p> <div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>unique</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>path</th>\n",
       "      <td>21471</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>file_type</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>realm</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>model_id</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>experiment_id</th>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>frequency</th>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>variable_id</th>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>version</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>time_range</th>\n",
       "      <td>2054</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>derived_variable_id</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
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      ]
     },
     "metadata": {},
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    }
   ],
   "source": [
    "# This is not very helpful - so lets figure out what is in the datastore\n",
    "\n",
    "catalog"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "4425daf7-6823-419e-bcfe-119644668983",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['mjo-lanina2018',\n",
       " 'mjo-elnino2016',\n",
       " 'coralsea-sstreduced',\n",
       " 'ashwed1983',\n",
       " 'mjo-neutral2013',\n",
       " 'canberra2003',\n",
       " 'flood2022',\n",
       " 'ashwed1980',\n",
       " 'ecoastlow-corclimsst',\n",
       " 'blacksat2009',\n",
       " 'ecoastlow-smooth',\n",
       " 'ecoastlow-evolvsst',\n",
       " 'ecoastlow-climsst',\n",
       " 'ecoastlow-tasclimsst',\n",
       " 'coralsea-sstobs',\n",
       " 'ecoastlow-fixsst']"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# experiment_id looks like it might be helpful!\n",
    "catalog.unique().experiment_id"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "e1dad44b-6f98-4c4b-85dc-97679be09d8d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Lets pick the Canberra 2003 experiment\n",
    "experiment = catalog.search(experiment_id='canberra2003')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "615a3dcd-92e3-4743-90f4-574b874e41cf",
   "metadata": {},
   "source": [
    "At the moment we have one dataset for each separate simulation and a combined dataset which includes all simulations."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8d71bdf0-c154-4bb4-954d-499bf2625494",
   "metadata": {},
   "source": [
    "## Example of dataset for a single simulation: canberra03"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "815c99b5-4974-4187-9d59-c50ca80fa837",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
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       "<p><strong>AUS2200 catalog with 56 dataset(s) from 341 asset(s)</strong>:</p> <div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>unique</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>path</th>\n",
       "      <td>341</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>file_type</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>realm</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>model_id</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>experiment_id</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>frequency</th>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>variable_id</th>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>version</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
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   "source": [
    "# Lets pick the Canberra 2003 experiment\n",
    "experiment = catalog.search(experiment_id='canberra2003')\n",
    "experiment"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cb6372c3-bcc6-43d9-835c-6d47f22d79fe",
   "metadata": {},
   "source": [
    "What are the available variables?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "d3ed0523-003b-4993-a65f-362bf2f65b67",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['rainmxrat',\n",
       " 'vas',\n",
       " 'refl',\n",
       " 'cl',\n",
       " 'wa',\n",
       " 'clmed',\n",
       " 'clw',\n",
       " 'ta',\n",
       " 'cli',\n",
       " 'grplmxrat',\n",
       " 'hus',\n",
       " 'pralsns',\n",
       " 'eow',\n",
       " 'theta',\n",
       " 'tke',\n",
       " 'uas',\n",
       " 'hfss',\n",
       " 'va',\n",
       " 'pralsprof',\n",
       " 'hfls',\n",
       " 'ua',\n",
       " 'pfull',\n",
       " 'huss',\n",
       " 'clmxro',\n",
       " 'rsds',\n",
       " 'mrsol',\n",
       " 'psl',\n",
       " 'rsdt',\n",
       " 'reflmax',\n",
       " 'estot',\n",
       " 'wsgmax10m',\n",
       " 'evspsbl',\n",
       " 'lmask',\n",
       " 'z0',\n",
       " 'clhigh',\n",
       " 'cllow',\n",
       " 'rsut',\n",
       " 'rss',\n",
       " 'rsdsdir',\n",
       " 'orog',\n",
       " 'mrso',\n",
       " 'tas',\n",
       " 'zmla',\n",
       " 'rlds',\n",
       " 'rls',\n",
       " 'rsdsdiff',\n",
       " 'rlut']"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "experiment.unique()['variable_id']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f796f2ef-6e89-49a9-a93d-aa64f205118b",
   "metadata": {},
   "source": [
    "Let's get one (e.g., the temperature) and do some super-duper analysis!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "1640f093-d260-484e-88b9-11b2e60273ad",
   "metadata": {
    "tags": []
   },
   "outputs": [
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       ".xr-section-item > input:enabled + label,\n",
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       ".xr-group-box-contents > input:enabled + label {\n",
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       ".xr-array-wrap > input:enabled + label:hover,\n",
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       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.3em;\n",
       "}\n",
       "\n",
       ".xr-group-box-contents > input:checked + label > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.6em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: \"►\";\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: \"▼\";\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details,\n",
       ".xr-group-box-contents > label {\n",
       "  padding-top: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  grid-column: 1 / -1;\n",
       "  margin-top: 4px;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in ~ .xr-section-details {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-children {\n",
       "  display: inline-grid;\n",
       "  grid-template-columns: 100%;\n",
       "  grid-column: 1 / -1;\n",
       "  padding-top: 4px;\n",
       "}\n",
       "\n",
       ".xr-group-box {\n",
       "  display: inline-grid;\n",
       "  grid-template-columns: 0px 30px auto;\n",
       "}\n",
       "\n",
       ".xr-group-box-vline {\n",
       "  grid-column-start: 1;\n",
       "  border-right: 0.2em solid;\n",
       "  border-color: var(--xr-border-color);\n",
       "  width: 0px;\n",
       "}\n",
       "\n",
       ".xr-group-box-hline {\n",
       "  grid-column-start: 2;\n",
       "  grid-row-start: 1;\n",
       "  height: 1em;\n",
       "  width: 26px;\n",
       "  border-bottom: 0.2em solid;\n",
       "  border-color: var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-group-box-contents {\n",
       "  grid-column-start: 3;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-group-box-contents > label::before {\n",
       "  content: \"📂\";\n",
       "  padding-right: 0.3em;\n",
       "}\n",
       "\n",
       ".xr-group-box-contents > input:checked + label::before {\n",
       "  content: \"📁\";\n",
       "}\n",
       "\n",
       ".xr-group-box-contents > input:checked + label {\n",
       "  padding-bottom: 0px;\n",
       "}\n",
       "\n",
       ".xr-group-box-contents > input:checked ~ .xr-sections {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-group-box-contents > input + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-group-box-ellipsis {\n",
       "  font-size: 1.4em;\n",
       "  font-weight: 900;\n",
       "  color: var(--xr-font-color2);\n",
       "  letter-spacing: 0.15em;\n",
       "  cursor: default;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: \"(\";\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: \")\";\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: \",\";\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  border-color: var(--xr-background-color-row-odd);\n",
       "  margin-bottom: 0;\n",
       "  padding-top: 2px;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "  border-color: var(--xr-background-color-row-even);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  border-top: 2px dotted var(--xr-background-color);\n",
       "  padding-bottom: 20px !important;\n",
       "  padding-top: 10px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in + label,\n",
       ".xr-var-data-in + label,\n",
       ".xr-index-data-in + label {\n",
       "  padding: 0 1px;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-data > pre,\n",
       ".xr-index-data > pre,\n",
       ".xr-var-data > table > tbody > tr {\n",
       "  background-color: transparent !important;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
       "  color: var(--xr-font-color0);\n",
       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
       "  stroke-width: 0.8px;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 2GB\n",
       "Dimensions:    (time: 96, bnds: 2, lat: 2120, lon: 2600)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 768B 2003-01-16T00:29:59.999999872 ... 2...\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",
       "    height     float64 8B ...\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) datetime64[ns] 2kB dask.array&lt;chunksize=(96, 2), meta=np.ndarray&gt;\n",
       "    lat_bnds   (lat, bnds) float64 34kB dask.array&lt;chunksize=(2120, 2), meta=np.ndarray&gt;\n",
       "    lon_bnds   (lon, bnds) float64 42kB dask.array&lt;chunksize=(2600, 2), meta=np.ndarray&gt;\n",
       "    tas        (time, lat, lon) float32 2GB dask.array&lt;chunksize=(6, 2120, 2600), meta=np.ndarray&gt;\n",
       "Attributes: (12/57)\n",
       "    Conventions:                     CF-1.7 ACDD1.3\n",
       "    creation_date:                   2023-10-19T06:04:51Z\n",
       "    data_specs_version:              01.00.00\n",
       "    date_created:                    2023-06-05\n",
       "    exp_description:                 A limited area model study of the entire...\n",
       "    external_variables:              areacella\n",
       "    ...                              ...\n",
       "    intake_esm_attrs:frequency:      1hr\n",
       "    intake_esm_attrs:variable_id:    tas\n",
       "    intake_esm_attrs:version:        v1-0\n",
       "    intake_esm_attrs:time_range:     200301160030-200301192330\n",
       "    intake_esm_attrs:_data_format_:  netcdf\n",
       "    intake_esm_dataset_key:          f.AUS2200.1hr.tas.v1-0</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-c1607b7f-ceae-4bdf-bc8a-b130dea88307' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-c1607b7f-ceae-4bdf-bc8a-b130dea88307' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 96</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lat</span>: 2120</li><li><span class='xr-has-index'>lon</span>: 2600</li></ul></div></li><li class='xr-section-item'><input id='section-a8d9fbde-e1be-4297-abab-4fa1eb97c1c9' class='xr-section-summary-in' type='checkbox' checked /><label for='section-a8d9fbde-e1be-4297-abab-4fa1eb97c1c9' class='xr-section-summary' title='Expand/collapse section'>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 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'>2003-01-16T00:29:59.999999872 .....</div><input id='attrs-94ce04a7-6b2f-41a7-8e7a-ea309b5ca600' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-94ce04a7-6b2f-41a7-8e7a-ea309b5ca600' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f792552b-eb1c-48b4-a340-669a88c6c512' class='xr-var-data-in' type='checkbox'><label for='data-f792552b-eb1c-48b4-a340-669a88c6c512' 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>time_bnds</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2003-01-16T00:29:59.999999872&#x27;, &#x27;2003-01-16T01:30:00.000000000&#x27;,\n",
       "       &#x27;2003-01-16T02:30:00.000000128&#x27;, &#x27;2003-01-16T03:29:59.999999872&#x27;,\n",
       "       &#x27;2003-01-16T04:30:00.000000000&#x27;, &#x27;2003-01-16T05:30:00.000000128&#x27;,\n",
       "       &#x27;2003-01-16T06:29:59.999999872&#x27;, &#x27;2003-01-16T07:30:00.000000000&#x27;,\n",
       "       &#x27;2003-01-16T08:30:00.000000128&#x27;, &#x27;2003-01-16T09:29:59.999999872&#x27;,\n",
       "       &#x27;2003-01-16T10:30:00.000000000&#x27;, &#x27;2003-01-16T11:30:00.000000128&#x27;,\n",
       "       &#x27;2003-01-16T12:29:59.999999872&#x27;, &#x27;2003-01-16T13:30:00.000000000&#x27;,\n",
       "       &#x27;2003-01-16T14:30:00.000000128&#x27;, &#x27;2003-01-16T15:29:59.999999872&#x27;,\n",
       "       &#x27;2003-01-16T16:30:00.000000000&#x27;, &#x27;2003-01-16T17:30:00.000000128&#x27;,\n",
       "       &#x27;2003-01-16T18:29:59.999999872&#x27;, &#x27;2003-01-16T19:30:00.000000000&#x27;,\n",
       "       &#x27;2003-01-16T20:30:00.000000128&#x27;, &#x27;2003-01-16T21:29:59.999999872&#x27;,\n",
       "       &#x27;2003-01-16T22:30:00.000000000&#x27;, &#x27;2003-01-16T23:30:00.000000128&#x27;,\n",
       "       &#x27;2003-01-17T00:29:59.999999872&#x27;, &#x27;2003-01-17T01:30:00.000000000&#x27;,\n",
       "       &#x27;2003-01-17T02:30:00.000000128&#x27;, &#x27;2003-01-17T03:29:59.999999872&#x27;,\n",
       "       &#x27;2003-01-17T04:30:00.000000000&#x27;, &#x27;2003-01-17T05:30:00.000000128&#x27;,\n",
       "       &#x27;2003-01-17T06:29:59.999999872&#x27;, &#x27;2003-01-17T07:30:00.000000000&#x27;,\n",
       "       &#x27;2003-01-17T08:30:00.000000128&#x27;, &#x27;2003-01-17T09:29:59.999999872&#x27;,\n",
       "       &#x27;2003-01-17T10:30:00.000000000&#x27;, &#x27;2003-01-17T11:30:00.000000128&#x27;,\n",
       "       &#x27;2003-01-17T12:29:59.999999872&#x27;, &#x27;2003-01-17T13:30:00.000000000&#x27;,\n",
       "       &#x27;2003-01-17T14:30:00.000000128&#x27;, &#x27;2003-01-17T15:29:59.999999872&#x27;,\n",
       "       &#x27;2003-01-17T16:30:00.000000000&#x27;, &#x27;2003-01-17T17:30:00.000000128&#x27;,\n",
       "       &#x27;2003-01-17T18:29:59.999999872&#x27;, &#x27;2003-01-17T19:30:00.000000000&#x27;,\n",
       "       &#x27;2003-01-17T20:30:00.000000128&#x27;, &#x27;2003-01-17T21:29:59.999999872&#x27;,\n",
       "       &#x27;2003-01-17T22:30:00.000000000&#x27;, &#x27;2003-01-17T23:30:00.000000128&#x27;,\n",
       "       &#x27;2003-01-18T00:29:59.999999872&#x27;, &#x27;2003-01-18T01:30:00.000000000&#x27;,\n",
       "       &#x27;2003-01-18T02:30:00.000000128&#x27;, &#x27;2003-01-18T03:29:59.999999872&#x27;,\n",
       "       &#x27;2003-01-18T04:30:00.000000000&#x27;, &#x27;2003-01-18T05:30:00.000000128&#x27;,\n",
       "       &#x27;2003-01-18T06:29:59.999999872&#x27;, &#x27;2003-01-18T07:30:00.000000000&#x27;,\n",
       "       &#x27;2003-01-18T08:30:00.000000128&#x27;, &#x27;2003-01-18T09:29:59.999999872&#x27;,\n",
       "       &#x27;2003-01-18T10:30:00.000000000&#x27;, &#x27;2003-01-18T11:30:00.000000128&#x27;,\n",
       "       &#x27;2003-01-18T12:29:59.999999872&#x27;, &#x27;2003-01-18T13:30:00.000000000&#x27;,\n",
       "       &#x27;2003-01-18T14:30:00.000000128&#x27;, &#x27;2003-01-18T15:29:59.999999872&#x27;,\n",
       "       &#x27;2003-01-18T16:30:00.000000000&#x27;, &#x27;2003-01-18T17:30:00.000000128&#x27;,\n",
       "       &#x27;2003-01-18T18:29:59.999999872&#x27;, &#x27;2003-01-18T19:30:00.000000000&#x27;,\n",
       "       &#x27;2003-01-18T20:30:00.000000128&#x27;, &#x27;2003-01-18T21:29:59.999999872&#x27;,\n",
       "       &#x27;2003-01-18T22:30:00.000000000&#x27;, &#x27;2003-01-18T23:30:00.000000128&#x27;,\n",
       "       &#x27;2003-01-19T00:29:59.999999872&#x27;, &#x27;2003-01-19T01:30:00.000000000&#x27;,\n",
       "       &#x27;2003-01-19T02:30:00.000000128&#x27;, &#x27;2003-01-19T03:29:59.999999872&#x27;,\n",
       "       &#x27;2003-01-19T04:30:00.000000000&#x27;, &#x27;2003-01-19T05:30:00.000000128&#x27;,\n",
       "       &#x27;2003-01-19T06:29:59.999999872&#x27;, &#x27;2003-01-19T07:30:00.000000000&#x27;,\n",
       "       &#x27;2003-01-19T08:30:00.000000128&#x27;, &#x27;2003-01-19T09:29:59.999999872&#x27;,\n",
       "       &#x27;2003-01-19T10:30:00.000000000&#x27;, &#x27;2003-01-19T11:30:00.000000128&#x27;,\n",
       "       &#x27;2003-01-19T12:29:59.999999872&#x27;, &#x27;2003-01-19T13:30:00.000000000&#x27;,\n",
       "       &#x27;2003-01-19T14:30:00.000000128&#x27;, &#x27;2003-01-19T15:29:59.999999872&#x27;,\n",
       "       &#x27;2003-01-19T16:30:00.000000000&#x27;, &#x27;2003-01-19T17:30:00.000000128&#x27;,\n",
       "       &#x27;2003-01-19T18:29:59.999999872&#x27;, &#x27;2003-01-19T19:30:00.000000000&#x27;,\n",
       "       &#x27;2003-01-19T20:30:00.000000128&#x27;, &#x27;2003-01-19T21:29:59.999999872&#x27;,\n",
       "       &#x27;2003-01-19T22:30:00.000000000&#x27;, &#x27;2003-01-19T23:30:00.000000128&#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-0bcfc6c4-3251-455b-9a92-cb5b8910fd0e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0bcfc6c4-3251-455b-9a92-cb5b8910fd0e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aeaec9d6-6295-4fa8-ad6a-aabd648fdf8a' class='xr-var-data-in' type='checkbox'><label for='data-aeaec9d6-6295-4fa8-ad6a-aabd648fdf8a' 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>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>Latitude</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], shape=(2120,))</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-708fad33-61ad-4fa5-b3d0-df2051e1ce02' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-708fad33-61ad-4fa5-b3d0-df2051e1ce02' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1d94b0d8-be86-4466-8ff6-6b517d5ecb04' class='xr-var-data-in' type='checkbox'><label for='data-1d94b0d8-be86-4466-8ff6-6b517d5ecb04' 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>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>Longitude</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], shape=(2600,))</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-84284a0f-1223-48b2-b3d7-03b5edc93175' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-84284a0f-1223-48b2-b3d7-03b5edc93175' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-388bb70b-27c9-44d2-8ffd-6acf1ba9eb36' class='xr-var-data-in' type='checkbox'><label for='data-388bb70b-27c9-44d2-8ffd-6acf1ba9eb36' 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>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>standard_name :</span></dt><dd>height</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-510aaf75-d3d9-445d-8af6-2fbfaf93fc72' class='xr-section-summary-in' type='checkbox' checked /><label for='section-510aaf75-d3d9-445d-8af6-2fbfaf93fc72' class='xr-section-summary' title='Expand/collapse section'>Data variables: <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_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(96, 2), meta=np.ndarray&gt;</div><input id='attrs-4971a00a-6afd-4eb2-8f9d-cbf628d23137' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4971a00a-6afd-4eb2-8f9d-cbf628d23137' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1eeb9218-53b6-4fc3-ae0b-5328e7294fc3' class='xr-var-data-in' type='checkbox'><label for='data-1eeb9218-53b6-4fc3-ae0b-5328e7294fc3' 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'><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> 1.50 kiB </td>\n",
       "                        <td> 1.50 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (96, 2) </td>\n",
       "                        <td> (96, 2) </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\"> datetime64[ns] numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_bnds</span></div><div class='xr-var-dims'>(lat, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2120, 2), meta=np.ndarray&gt;</div><input id='attrs-b98c374e-b457-417d-9e19-4464030df356' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b98c374e-b457-417d-9e19-4464030df356' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7a2bf739-f258-4697-a802-e5bfcb984816' class='xr-var-data-in' type='checkbox'><label for='data-7a2bf739-f258-4697-a802-e5bfcb984816' 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'><table>\n",
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       "                        <th> Array </th>\n",
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       "                <tbody>\n",
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       "                        <td> 33.12 kiB </td>\n",
       "                        <td> 33.12 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (2120, 2) </td>\n",
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       "                    <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",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2600, 2), meta=np.ndarray&gt;</div><input id='attrs-db9916ce-6d6d-47f7-bb75-d0691233ff47' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-db9916ce-6d6d-47f7-bb75-d0691233ff47' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-48eda668-a90a-42e7-855f-5fc5f2e5cd4d' class='xr-var-data-in' type='checkbox'><label for='data-48eda668-a90a-42e7-855f-5fc5f2e5cd4d' 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'><table>\n",
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       "        <td>\n",
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       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
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       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 40.62 kiB </td>\n",
       "                        <td> 40.62 kiB </td>\n",
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       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (2600, 2) </td>\n",
       "                        <td> (2600, 2) </td>\n",
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       "                    <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",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tas</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=(6, 2120, 2600), meta=np.ndarray&gt;</div><input id='attrs-22cb3a91-8005-4272-9450-8b155e02d802' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-22cb3a91-8005-4272-9450-8b155e02d802' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-97ae730a-cfce-431c-a4d4-a23fc70600f1' class='xr-var-data-in' type='checkbox'><label for='data-97ae730a-cfce-431c-a4d4-a23fc70600f1' 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>air_temperature</dd><dt><span>long_name :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>comment :</span></dt><dd>near-surface (for access 1.5 meters) air temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>cell_methods :</span></dt><dd>area: mean time: mean</dd><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>history :</span></dt><dd>2023-10-19T06:04:25Z altered by CMOR: Treated scalar dimension: &#x27;height&#x27;. 2023-10-19T06:04:25Z altered by CMOR: replaced missing value flag (9.96921e+36) and corresponding data with standard missing value (1e+20).</dd><dt><span>coverage_content_type :</span></dt><dd>modelResult</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 16 chunks in 2 graph layers </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "https://orcid.org/0000-0001-9499-5894</dd><dt><span>contact :</span></dt><dd>hooman.ayat@unimelb.edu.au</dd><dt><span>comment :</span></dt><dd>post-processed using ACCESS-MOPPeR v0.6.0 https://doi.org/10.5281/zenodo.10976467</dd><dt><span>publisher_name :</span></dt><dd>NCI</dd><dt><span>publisher_email :</span></dt><dd>help@nci.org.au</dd><dt><span>creator_name :</span></dt><dd>Dale Roberts, Paola Petrelli, Hooman Ayat</dd><dt><span>creator_email :</span></dt><dd>dale.roberts1@anu.edu.au, paola.petrelli@utas.edu.au, hooman.ayat@unimelb.edu.au</dd><dt><span>time_coverage_end :</span></dt><dd>2003-01-19</dd><dt><span>id :</span></dt><dd>https://doi.org/10.25194/vhs6-ja29</dd><dt><span>citation :</span></dt><dd>Roberts, Dale, Petrelli, Paola, Ayat, Hooman. AUS2200 Unified Model atmospheric simulation of the 2003 Canberra bushfire, over Australia at 2.2km resolution. v1.0 (2024). NCI Australia. (Dataset) https://doi.org/10.25914/vhs6-ja29</dd><dt><span>intake_esm_vars :</span></dt><dd>[&#x27;tas&#x27;]</dd><dt><span>intake_esm_attrs:path :</span></dt><dd>/g/data/bs94/AUS2200/canberra2003/v1-0/1hr/tas/tas_AUS2200_canberra03_1hr_200301160030-200301192330.nc</dd><dt><span>intake_esm_attrs:file_type :</span></dt><dd>f</dd><dt><span>intake_esm_attrs:realm :</span></dt><dd>atmos</dd><dt><span>intake_esm_attrs:model_id :</span></dt><dd>AUS2200</dd><dt><span>intake_esm_attrs:experiment_id :</span></dt><dd>canberra2003</dd><dt><span>intake_esm_attrs:frequency :</span></dt><dd>1hr</dd><dt><span>intake_esm_attrs:variable_id :</span></dt><dd>tas</dd><dt><span>intake_esm_attrs:version :</span></dt><dd>v1-0</dd><dt><span>intake_esm_attrs:time_range :</span></dt><dd>200301160030-200301192330</dd><dt><span>intake_esm_attrs:_data_format_ :</span></dt><dd>netcdf</dd><dt><span>intake_esm_dataset_key :</span></dt><dd>f.AUS2200.1hr.tas.v1-0</dd></dl></div></li></ul></div></div>"
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       "<xarray.Dataset> Size: 2GB\n",
       "Dimensions:    (time: 96, bnds: 2, lat: 2120, lon: 2600)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 768B 2003-01-16T00:29:59.999999872 ... 2...\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",
       "    height     float64 8B ...\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) datetime64[ns] 2kB dask.array<chunksize=(96, 2), meta=np.ndarray>\n",
       "    lat_bnds   (lat, bnds) float64 34kB dask.array<chunksize=(2120, 2), meta=np.ndarray>\n",
       "    lon_bnds   (lon, bnds) float64 42kB dask.array<chunksize=(2600, 2), meta=np.ndarray>\n",
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       "Attributes: (12/57)\n",
       "    Conventions:                     CF-1.7 ACDD1.3\n",
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       "    data_specs_version:              01.00.00\n",
       "    date_created:                    2023-06-05\n",
       "    exp_description:                 A limited area model study of the entire...\n",
       "    external_variables:              areacella\n",
       "    ...                              ...\n",
       "    intake_esm_attrs:frequency:      1hr\n",
       "    intake_esm_attrs:variable_id:    tas\n",
       "    intake_esm_attrs:version:        v1-0\n",
       "    intake_esm_attrs:time_range:     200301160030-200301192330\n",
       "    intake_esm_attrs:_data_format_:  netcdf\n",
       "    intake_esm_dataset_key:          f.AUS2200.1hr.tas.v1-0"
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     },
     "execution_count": 9,
     "metadata": {},
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   "source": [
    "ds = experiment.search(variable_id='tas', frequency=\"1hr\").to_dask()\n",
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  {
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       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  grid-column: 1 / -1;\n",
       "  margin-top: 4px;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in ~ .xr-section-details {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-children {\n",
       "  display: inline-grid;\n",
       "  grid-template-columns: 100%;\n",
       "  grid-column: 1 / -1;\n",
       "  padding-top: 4px;\n",
       "}\n",
       "\n",
       ".xr-group-box {\n",
       "  display: inline-grid;\n",
       "  grid-template-columns: 0px 30px auto;\n",
       "}\n",
       "\n",
       ".xr-group-box-vline {\n",
       "  grid-column-start: 1;\n",
       "  border-right: 0.2em solid;\n",
       "  border-color: var(--xr-border-color);\n",
       "  width: 0px;\n",
       "}\n",
       "\n",
       ".xr-group-box-hline {\n",
       "  grid-column-start: 2;\n",
       "  grid-row-start: 1;\n",
       "  height: 1em;\n",
       "  width: 26px;\n",
       "  border-bottom: 0.2em solid;\n",
       "  border-color: var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-group-box-contents {\n",
       "  grid-column-start: 3;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-group-box-contents > label::before {\n",
       "  content: \"📂\";\n",
       "  padding-right: 0.3em;\n",
       "}\n",
       "\n",
       ".xr-group-box-contents > input:checked + label::before {\n",
       "  content: \"📁\";\n",
       "}\n",
       "\n",
       ".xr-group-box-contents > input:checked + label {\n",
       "  padding-bottom: 0px;\n",
       "}\n",
       "\n",
       ".xr-group-box-contents > input:checked ~ .xr-sections {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-group-box-contents > input + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-group-box-ellipsis {\n",
       "  font-size: 1.4em;\n",
       "  font-weight: 900;\n",
       "  color: var(--xr-font-color2);\n",
       "  letter-spacing: 0.15em;\n",
       "  cursor: default;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: \"(\";\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: \")\";\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: \",\";\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  border-color: var(--xr-background-color-row-odd);\n",
       "  margin-bottom: 0;\n",
       "  padding-top: 2px;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "  border-color: var(--xr-background-color-row-even);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  border-top: 2px dotted var(--xr-background-color);\n",
       "  padding-bottom: 20px !important;\n",
       "  padding-top: 10px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in + label,\n",
       ".xr-var-data-in + label,\n",
       ".xr-index-data-in + label {\n",
       "  padding: 0 1px;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-data > pre,\n",
       ".xr-index-data > pre,\n",
       ".xr-var-data > table > tbody > tr {\n",
       "  background-color: transparent !important;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
       "  color: var(--xr-font-color0);\n",
       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
       "  stroke-width: 0.8px;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;tas&#x27; (time: 96, lat: 2120, lon: 2600)&gt; Size: 2GB\n",
       "dask.array&lt;open_dataset-tas, shape=(96, 2120, 2600), dtype=float32, chunksize=(6, 2120, 2600), chunktype=numpy.ndarray&gt;\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 768B 2003-01-16T00:29:59.999999872 ... 200...\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",
       "    height   float64 8B ...\n",
       "Attributes:\n",
       "    standard_name:          air_temperature\n",
       "    long_name:              Near-Surface Air Temperature\n",
       "    comment:                near-surface (for access 1.5 meters) air temperature\n",
       "    units:                  K\n",
       "    cell_methods:           area: mean time: mean\n",
       "    cell_measures:          area: areacella\n",
       "    history:                2023-10-19T06:04:25Z altered by CMOR: Treated sca...\n",
       "    coverage_content_type:  modelResult</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-obj-name'>&#x27;tas&#x27;</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 96</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-1becd94a-8c08-4aef-b8fb-f945fbbab9e1' class='xr-array-in' type='checkbox' checked><label for='section-1becd94a-8c08-4aef-b8fb-f945fbbab9e1' 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=(6, 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> 1.97 GiB </td>\n",
       "                        <td> 126.16 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (96, 2120, 2600) </td>\n",
       "                        <td> (6, 2120, 2600) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 16 chunks in 2 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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       "</table></div></div></li><li class='xr-section-item'><input id='section-a16c71f9-fe1c-42bb-8ec9-b11d2e1cce7d' class='xr-section-summary-in' type='checkbox' checked /><label for='section-a16c71f9-fe1c-42bb-8ec9-b11d2e1cce7d' class='xr-section-summary' title='Expand/collapse section'>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 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'>2003-01-16T00:29:59.999999872 .....</div><input id='attrs-48ea53b8-0b77-450c-a259-eb98ec820d7a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-48ea53b8-0b77-450c-a259-eb98ec820d7a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fbb73d09-6536-422b-b0ea-4f835cb8fc09' class='xr-var-data-in' type='checkbox'><label for='data-fbb73d09-6536-422b-b0ea-4f835cb8fc09' 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>time_bnds</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2003-01-16T00:29:59.999999872&#x27;, &#x27;2003-01-16T01:30:00.000000000&#x27;,\n",
       "       &#x27;2003-01-16T02:30:00.000000128&#x27;, &#x27;2003-01-16T03:29:59.999999872&#x27;,\n",
       "       &#x27;2003-01-16T04:30:00.000000000&#x27;, &#x27;2003-01-16T05:30:00.000000128&#x27;,\n",
       "       &#x27;2003-01-16T06:29:59.999999872&#x27;, &#x27;2003-01-16T07:30:00.000000000&#x27;,\n",
       "       &#x27;2003-01-16T08:30:00.000000128&#x27;, &#x27;2003-01-16T09:29:59.999999872&#x27;,\n",
       "       &#x27;2003-01-16T10:30:00.000000000&#x27;, &#x27;2003-01-16T11:30:00.000000128&#x27;,\n",
       "       &#x27;2003-01-16T12:29:59.999999872&#x27;, &#x27;2003-01-16T13:30:00.000000000&#x27;,\n",
       "       &#x27;2003-01-16T14:30:00.000000128&#x27;, &#x27;2003-01-16T15:29:59.999999872&#x27;,\n",
       "       &#x27;2003-01-16T16:30:00.000000000&#x27;, &#x27;2003-01-16T17:30:00.000000128&#x27;,\n",
       "       &#x27;2003-01-16T18:29:59.999999872&#x27;, &#x27;2003-01-16T19:30:00.000000000&#x27;,\n",
       "       &#x27;2003-01-16T20:30:00.000000128&#x27;, &#x27;2003-01-16T21:29:59.999999872&#x27;,\n",
       "       &#x27;2003-01-16T22:30:00.000000000&#x27;, &#x27;2003-01-16T23:30:00.000000128&#x27;,\n",
       "       &#x27;2003-01-17T00:29:59.999999872&#x27;, &#x27;2003-01-17T01:30:00.000000000&#x27;,\n",
       "       &#x27;2003-01-17T02:30:00.000000128&#x27;, &#x27;2003-01-17T03:29:59.999999872&#x27;,\n",
       "       &#x27;2003-01-17T04:30:00.000000000&#x27;, &#x27;2003-01-17T05:30:00.000000128&#x27;,\n",
       "       &#x27;2003-01-17T06:29:59.999999872&#x27;, &#x27;2003-01-17T07:30:00.000000000&#x27;,\n",
       "       &#x27;2003-01-17T08:30:00.000000128&#x27;, &#x27;2003-01-17T09:29:59.999999872&#x27;,\n",
       "       &#x27;2003-01-17T10:30:00.000000000&#x27;, &#x27;2003-01-17T11:30:00.000000128&#x27;,\n",
       "       &#x27;2003-01-17T12:29:59.999999872&#x27;, &#x27;2003-01-17T13:30:00.000000000&#x27;,\n",
       "       &#x27;2003-01-17T14:30:00.000000128&#x27;, &#x27;2003-01-17T15:29:59.999999872&#x27;,\n",
       "       &#x27;2003-01-17T16:30:00.000000000&#x27;, &#x27;2003-01-17T17:30:00.000000128&#x27;,\n",
       "       &#x27;2003-01-17T18:29:59.999999872&#x27;, &#x27;2003-01-17T19:30:00.000000000&#x27;,\n",
       "       &#x27;2003-01-17T20:30:00.000000128&#x27;, &#x27;2003-01-17T21:29:59.999999872&#x27;,\n",
       "       &#x27;2003-01-17T22:30:00.000000000&#x27;, &#x27;2003-01-17T23:30:00.000000128&#x27;,\n",
       "       &#x27;2003-01-18T00:29:59.999999872&#x27;, &#x27;2003-01-18T01:30:00.000000000&#x27;,\n",
       "       &#x27;2003-01-18T02:30:00.000000128&#x27;, &#x27;2003-01-18T03:29:59.999999872&#x27;,\n",
       "       &#x27;2003-01-18T04:30:00.000000000&#x27;, &#x27;2003-01-18T05:30:00.000000128&#x27;,\n",
       "       &#x27;2003-01-18T06:29:59.999999872&#x27;, &#x27;2003-01-18T07:30:00.000000000&#x27;,\n",
       "       &#x27;2003-01-18T08:30:00.000000128&#x27;, &#x27;2003-01-18T09:29:59.999999872&#x27;,\n",
       "       &#x27;2003-01-18T10:30:00.000000000&#x27;, &#x27;2003-01-18T11:30:00.000000128&#x27;,\n",
       "       &#x27;2003-01-18T12:29:59.999999872&#x27;, &#x27;2003-01-18T13:30:00.000000000&#x27;,\n",
       "       &#x27;2003-01-18T14:30:00.000000128&#x27;, &#x27;2003-01-18T15:29:59.999999872&#x27;,\n",
       "       &#x27;2003-01-18T16:30:00.000000000&#x27;, &#x27;2003-01-18T17:30:00.000000128&#x27;,\n",
       "       &#x27;2003-01-18T18:29:59.999999872&#x27;, &#x27;2003-01-18T19:30:00.000000000&#x27;,\n",
       "       &#x27;2003-01-18T20:30:00.000000128&#x27;, &#x27;2003-01-18T21:29:59.999999872&#x27;,\n",
       "       &#x27;2003-01-18T22:30:00.000000000&#x27;, &#x27;2003-01-18T23:30:00.000000128&#x27;,\n",
       "       &#x27;2003-01-19T00:29:59.999999872&#x27;, &#x27;2003-01-19T01:30:00.000000000&#x27;,\n",
       "       &#x27;2003-01-19T02:30:00.000000128&#x27;, &#x27;2003-01-19T03:29:59.999999872&#x27;,\n",
       "       &#x27;2003-01-19T04:30:00.000000000&#x27;, &#x27;2003-01-19T05:30:00.000000128&#x27;,\n",
       "       &#x27;2003-01-19T06:29:59.999999872&#x27;, &#x27;2003-01-19T07:30:00.000000000&#x27;,\n",
       "       &#x27;2003-01-19T08:30:00.000000128&#x27;, &#x27;2003-01-19T09:29:59.999999872&#x27;,\n",
       "       &#x27;2003-01-19T10:30:00.000000000&#x27;, &#x27;2003-01-19T11:30:00.000000128&#x27;,\n",
       "       &#x27;2003-01-19T12:29:59.999999872&#x27;, &#x27;2003-01-19T13:30:00.000000000&#x27;,\n",
       "       &#x27;2003-01-19T14:30:00.000000128&#x27;, &#x27;2003-01-19T15:29:59.999999872&#x27;,\n",
       "       &#x27;2003-01-19T16:30:00.000000000&#x27;, &#x27;2003-01-19T17:30:00.000000128&#x27;,\n",
       "       &#x27;2003-01-19T18:29:59.999999872&#x27;, &#x27;2003-01-19T19:30:00.000000000&#x27;,\n",
       "       &#x27;2003-01-19T20:30:00.000000128&#x27;, &#x27;2003-01-19T21:29:59.999999872&#x27;,\n",
       "       &#x27;2003-01-19T22:30:00.000000000&#x27;, &#x27;2003-01-19T23:30:00.000000128&#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-875e2a82-93d5-48ca-8a14-f60123ed499a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-875e2a82-93d5-48ca-8a14-f60123ed499a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6e7bc8df-d543-4e01-9a6d-2f167b342b23' class='xr-var-data-in' type='checkbox'><label for='data-6e7bc8df-d543-4e01-9a6d-2f167b342b23' 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>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>Latitude</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], shape=(2120,))</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-f09ff9ae-b84b-4e87-987a-6fd08fde4df4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f09ff9ae-b84b-4e87-987a-6fd08fde4df4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ad6d8584-ed44-45a9-abf4-2fa07a656ee8' class='xr-var-data-in' type='checkbox'><label for='data-ad6d8584-ed44-45a9-abf4-2fa07a656ee8' 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>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>Longitude</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], shape=(2600,))</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-0b6eb131-2c72-48fe-8610-a42eed70fd7d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0b6eb131-2c72-48fe-8610-a42eed70fd7d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6e8e9c4a-4027-49c3-aed4-4de9aedce67c' class='xr-var-data-in' type='checkbox'><label for='data-6e8e9c4a-4027-49c3-aed4-4de9aedce67c' 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>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>standard_name :</span></dt><dd>height</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-4740078a-feac-4908-a43b-272fce7ce6a8' class='xr-section-summary-in' type='checkbox' checked /><label for='section-4740078a-feac-4908-a43b-272fce7ce6a8' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(8)</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>air_temperature</dd><dt><span>long_name :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>comment :</span></dt><dd>near-surface (for access 1.5 meters) air temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>cell_methods :</span></dt><dd>area: mean time: mean</dd><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>history :</span></dt><dd>2023-10-19T06:04:25Z altered by CMOR: Treated scalar dimension: &#x27;height&#x27;. 2023-10-19T06:04:25Z altered by CMOR: replaced missing value flag (9.96921e+36) and corresponding data with standard missing value (1e+20).</dd><dt><span>coverage_content_type :</span></dt><dd>modelResult</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'tas' (time: 96, lat: 2120, lon: 2600)> Size: 2GB\n",
       "dask.array<open_dataset-tas, shape=(96, 2120, 2600), dtype=float32, chunksize=(6, 2120, 2600), chunktype=numpy.ndarray>\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 768B 2003-01-16T00:29:59.999999872 ... 200...\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",
       "    height   float64 8B ...\n",
       "Attributes:\n",
       "    standard_name:          air_temperature\n",
       "    long_name:              Near-Surface Air Temperature\n",
       "    comment:                near-surface (for access 1.5 meters) air temperature\n",
       "    units:                  K\n",
       "    cell_methods:           area: mean time: mean\n",
       "    cell_measures:          area: areacella\n",
       "    history:                2023-10-19T06:04:25Z altered by CMOR: Treated sca...\n",
       "    coverage_content_type:  modelResult"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tas = ds['tas']\n",
    "tas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "f3e12e59-97ee-49fc-bd6d-e5254ed5700a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x15278ab032c0>"
      ]
     },
     "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": [
    "tas.cf.sel(time = '2003-01-16T02:30:00').plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1ff5f769-a35a-4061-a0c4-b032536bd839",
   "metadata": {},
   "source": [
    "Plot a Hovmoller"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "19da85a0-a952-4acb-a679-04f3d318582f",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x15271aea5310>"
      ]
     },
     "execution_count": 12,
     "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": [
    "tas.cf.sel(longitude = 130, method='nearest').plot()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:analysis3-26.05]",
   "language": "python",
   "name": "conda-env-analysis3-26.05-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": "3.12.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}