{
 "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.open_catalog('/g/data/ua8/Working/packages/aus2200-intake/catalogue.yaml')"
   ]
  },
  {
   "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": [
       "['ashwed80', 'ashwed83', 'canberra03', 'combined']"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(catalog)"
   ]
  },
  {
   "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": 4,
   "id": "815c99b5-4974-4187-9d59-c50ca80fa837",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'A limited area model study of the entire Australian continent at 2.2 km resolution, using the UM atmospheric model. ERA5+ERA5Land reanalysis data was used to provide initial and boundary conditions. The study covers the time period of 2003-01-16 to 2003-01-19, including the 2003 Canberra bushfires.\\nThis dataset is part of the AUS2200 simulations collection at NCI.\\n'"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "experiment = catalog['canberra03']\n",
    "experiment.description"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cb6372c3-bcc6-43d9-835c-6d47f22d79fe",
   "metadata": {},
   "source": [
    "What are the available variables?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "d3ed0523-003b-4993-a65f-362bf2f65b67",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['amdry',\n",
       " 'amwet',\n",
       " 'clhigh',\n",
       " 'cllow',\n",
       " 'clmed',\n",
       " 'clmxro',\n",
       " 'hus',\n",
       " 'huss',\n",
       " 'nflash',\n",
       " 'pralsns',\n",
       " 'pralsprof',\n",
       " 'ps',\n",
       " 'psl',\n",
       " 'reflmax',\n",
       " 'storm',\n",
       " 'tas',\n",
       " 'tdps',\n",
       " 'ts',\n",
       " 'uas',\n",
       " 'vas',\n",
       " 'wsgmax10m',\n",
       " 'cl',\n",
       " 'cli',\n",
       " 'clw',\n",
       " 'eow',\n",
       " 'estot',\n",
       " 'evspsbl',\n",
       " 'grplmxrat',\n",
       " 'hfls',\n",
       " 'hfss',\n",
       " 'mrso',\n",
       " 'mrsol',\n",
       " 'pfull',\n",
       " 'phalf',\n",
       " 'refl',\n",
       " 'ta',\n",
       " 'ua',\n",
       " 'va',\n",
       " 'wa',\n",
       " 'rainmxrat',\n",
       " 'rlds',\n",
       " 'rls',\n",
       " 'rlut',\n",
       " 'rsds',\n",
       " 'rsdsdiff',\n",
       " 'rsdsdir',\n",
       " 'rsdt',\n",
       " 'rss',\n",
       " 'rsut',\n",
       " 'theta',\n",
       " 'tke',\n",
       " 'z0',\n",
       " 'zmla',\n",
       " 'lmask',\n",
       " 'orog']"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "experiment.unique()['variable']"
   ]
  },
  {
   "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": 6,
   "id": "1640f093-d260-484e-88b9-11b2e60273ad",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
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       "</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=(1, 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=(1, 1060, 1300), meta=np.ndarray&gt;\n",
       "Attributes: (12/55)\n",
       "    Conventions:                     CF-1.7 ACDD1.3\n",
       "    contact:                         dsroberts@unimelb.edu.au\n",
       "    contributor_email:               paola.petrelli@utas.edu.au, sam.green@un...\n",
       "    contributor_name:                Paola Petrelli, Samuel Green\n",
       "    contributor_role:                data_curator, data_curator\n",
       "    contributor_url:                 https://orcid.org/0000-0002-0164-5105, h...\n",
       "    ...                              ...\n",
       "    intake_esm_attrs:variable:       tas\n",
       "    intake_esm_attrs:experiment_id:  canberra03\n",
       "    intake_esm_attrs:frequency:      1hr\n",
       "    intake_esm_attrs:date_range:     200301160030-200301192330\n",
       "    intake_esm_attrs:_data_format_:  netcdf\n",
       "    intake_esm_dataset_key:          v1-0.1hr.tas</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-a4f762ca-6c16-4ca5-9f0f-d4d63bf11ea8' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a4f762ca-6c16-4ca5-9f0f-d4d63bf11ea8' 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>: 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><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-9b820b93-55a5-41db-aafc-90927f8b981e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9b820b93-55a5-41db-aafc-90927f8b981e' 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 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-4dc60fea-f3aa-40ce-a46b-c08fc71958da' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4dc60fea-f3aa-40ce-a46b-c08fc71958da' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-44c3701a-c2ef-44c2-8c98-e7268cf51cc8' class='xr-var-data-in' type='checkbox'><label for='data-44c3701a-c2ef-44c2-8c98-e7268cf51cc8' 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-b96a9ad1-e6be-450f-902c-d253843ba055' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b96a9ad1-e6be-450f-902c-d253843ba055' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aa25028d-e5ba-4daf-bc28-a05b886a5c83' class='xr-var-data-in' type='checkbox'><label for='data-aa25028d-e5ba-4daf-bc28-a05b886a5c83' 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])</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-b05d3e28-7706-4709-85c8-457620c02045' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b05d3e28-7706-4709-85c8-457620c02045' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0f006b34-7a33-4c4d-b5c0-0bcc59f3f0a9' class='xr-var-data-in' type='checkbox'><label for='data-0f006b34-7a33-4c4d-b5c0-0bcc59f3f0a9' 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])</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-4bbfdb4d-a522-4f02-86b3-429a28cbe23f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4bbfdb4d-a522-4f02-86b3-429a28cbe23f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d59419e1-1333-4151-8efb-43a1b8001676' class='xr-var-data-in' type='checkbox'><label for='data-d59419e1-1333-4151-8efb-43a1b8001676' 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-fe7db9b7-ed91-4cdd-bd10-7666e57efc9a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-fe7db9b7-ed91-4cdd-bd10-7666e57efc9a' class='xr-section-summary' >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=(1, 2), meta=np.ndarray&gt;</div><input id='attrs-748e102b-b2a2-4012-8399-21d1f405f3d1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-748e102b-b2a2-4012-8399-21d1f405f3d1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-df825917-92ff-4c13-8bf1-d9f3873f4bd4' class='xr-var-data-in' type='checkbox'><label for='data-df825917-92ff-4c13-8bf1-d9f3873f4bd4' 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> 16 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (96, 2) </td>\n",
       "                        <td> (1, 2) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 96 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",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"79\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
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       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</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-60ab4714-d0e3-43ae-9c10-af5791e83084' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-60ab4714-d0e3-43ae-9c10-af5791e83084' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ac8c3678-f4f9-4d18-949b-350143cd4471' class='xr-var-data-in' type='checkbox'><label for='data-ac8c3678-f4f9-4d18-949b-350143cd4471' 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> 33.12 kiB </td>\n",
       "                        <td> 33.12 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (2120, 2) </td>\n",
       "                        <td> (2120, 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\"> float64 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
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       "        </td>\n",
       "    </tr>\n",
       "</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-3ce1243a-e032-492b-a8cd-b7adba2b2ab3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3ce1243a-e032-492b-a8cd-b7adba2b2ab3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7c95a893-5e04-4f3e-9e75-f834f24814b7' class='xr-var-data-in' type='checkbox'><label for='data-7c95a893-5e04-4f3e-9e75-f834f24814b7' 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",
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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",
       "                    </tr>\n",
       "                    \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",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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       "        </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=(1, 1060, 1300), meta=np.ndarray&gt;</div><input id='attrs-9bf1f9d4-c442-400d-aaae-b33b3a2807a2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9bf1f9d4-c442-400d-aaae-b33b3a2807a2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5e272800-7555-4080-929e-4597b5334b96' class='xr-var-data-in' type='checkbox'><label for='data-5e272800-7555-4080-929e-4597b5334b96' 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></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 1.97 GiB </td>\n",
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       "                         &#x27;2003-01-16 01:30:00&#x27;,\n",
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       "               &#x27;2003-01-19 21:29:59.999999872&#x27;,\n",
       "                         &#x27;2003-01-19 22:30:00&#x27;,\n",
       "               &#x27;2003-01-19 23:30:00.000000128&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, 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-2a182ceb-9cc5-4060-b676-e80eef9ee016' class='xr-index-data-in' type='checkbox'/><label for='index-2a182ceb-9cc5-4060-b676-e80eef9ee016' 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-45401011-9c45-43b4-b8f3-3534251ce053' class='xr-index-data-in' type='checkbox'/><label for='index-45401011-9c45-43b4-b8f3-3534251ce053' 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-ff40555b-43ae-40f5-9289-c065d478b180' class='xr-section-summary-in' type='checkbox'  ><label for='section-ff40555b-43ae-40f5-9289-c065d478b180' class='xr-section-summary' >Attributes: <span>(55)</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-1.7 ACDD1.3</dd><dt><span>contact :</span></dt><dd>dsroberts@unimelb.edu.au</dd><dt><span>contributor_email :</span></dt><dd>paola.petrelli@utas.edu.au, sam.green@unsw.edu.au</dd><dt><span>contributor_name :</span></dt><dd>Paola Petrelli, Samuel Green</dd><dt><span>contributor_role :</span></dt><dd>data_curator, data_curator</dd><dt><span>contributor_url :</span></dt><dd>https://orcid.org/0000-0002-0164-5105, https://orcid.org/0000-0003-1129-4676</dd><dt><span>creation_date :</span></dt><dd>2023-10-19T06:04:51Z</dd><dt><span>creator_email :</span></dt><dd>dsroberts@unimelb.edu.au</dd><dt><span>creator_name :</span></dt><dd>Dale Roberts</dd><dt><span>creator_url :</span></dt><dd>https://orcid.org/0000-0003-3952-6344</dd><dt><span>data_specs_version :</span></dt><dd>01.00.00</dd><dt><span>date_created :</span></dt><dd>2023-06-05</dd><dt><span>exp_description :</span></dt><dd>A limited area model study of the entire Australian continent at 2.2 km resolution, using the UM atmospheric model. ERA5+ERA5Land reanalysis data was used to provide initial and boundary conditions. The study covers the time period of 2003-01-16 to 2003-01-19, including the 2003 Canberra bushfires.</dd><dt><span>experiment :</span></dt><dd>canberra03</dd><dt><span>experiment_id :</span></dt><dd>canberra03</dd><dt><span>external_variables :</span></dt><dd>areacella</dd><dt><span>forcing :</span></dt><dd>GHG, Oz, SA, Sl, Vl, BC, OC, (GHG = CO2, N2O, CH4, CFC11, CFC12, CFC113, HCFC22, HFC125, HFC134a)</dd><dt><span>frequency :</span></dt><dd>1hr</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/.institution_idAUS2200.canberra03.sub_experiment_idvariant_label</dd><dt><span>geospatial_lat_max :</span></dt><dd>-6.83</dd><dt><span>geospatial_lat_min :</span></dt><dd>-48.79</dd><dt><span>geospatial_lon_max :</span></dt><dd>158.98</dd><dt><span>geospatial_lon_min :</span></dt><dd>107.52</dd><dt><span>grid :</span></dt><dd>native atmosphere grid (2120x2600 latxlon)</dd><dt><span>history :</span></dt><dd>2023-10-19T06:04:51Z ; CMOR rewrote data to be consistent with , CF-1.7 ACDD1.3 and CF standards.</dd><dt><span>institution :</span></dt><dd>University of Melbourne</dd><dt><span>keywords :</span></dt><dd>Climate change processes, Adverse weather events, Cloud physics</dd><dt><span>nominal_resolution :</span></dt><dd>2.2 km</dd><dt><span>organisation :</span></dt><dd>Centre of Excellence for Climate Extremes</dd><dt><span>parent :</span></dt><dd>False</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>product_version :</span></dt><dd>v1.0</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>source :</span></dt><dd>UM v12.2 ECMWF ERA5 and ERA5-Land reanalysis fields used as forcings</dd><dt><span>source_id :</span></dt><dd>AUS2200</dd><dt><span>table_id :</span></dt><dd>A1hr</dd><dt><span>table_info :</span></dt><dd>Creation Date:(20 June 2023) MD5:71a4110ed3210ee3a5e9f7f71551dad2</dd><dt><span>time_coverage_end :</span></dt><dd>2003-01-20</dd><dt><span>time_coverage_start :</span></dt><dd>2003-01-16</dd><dt><span>title :</span></dt><dd>AUS2200 UM amip simulation of the 2003 Canberra bushfire.</dd><dt><span>tracking_id :</span></dt><dd>ddbb400b-b0a9-41f9-b88c-ecbccfeff5d3</dd><dt><span>variable_id :</span></dt><dd>tas</dd><dt><span>version :</span></dt><dd>v1.0</dd><dt><span>license :</span></dt><dd>https://creativecommons.org/licenses/by/4.0/</dd><dt><span>cmor_version :</span></dt><dd>3.7.1</dd><dt><span>intake_esm_vars :</span></dt><dd>[&#x27;tas&#x27;]</dd><dt><span>intake_esm_attrs:path :</span></dt><dd>/g/data/ua8/AUS2200/canberra03/v1-0/1hr/tas_AUS2200_canberra03_1hr_200301160030-200301192330.nc</dd><dt><span>intake_esm_attrs:version :</span></dt><dd>v1-0</dd><dt><span>intake_esm_attrs:table :</span></dt><dd>1hr</dd><dt><span>intake_esm_attrs:variable :</span></dt><dd>tas</dd><dt><span>intake_esm_attrs:experiment_id :</span></dt><dd>canberra03</dd><dt><span>intake_esm_attrs:frequency :</span></dt><dd>1hr</dd><dt><span>intake_esm_attrs:date_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>v1-0.1hr.tas</dd></dl></div></li></ul></div></div>"
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      "text/plain": [
       "<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=(1, 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",
       "    tas        (time, lat, lon) float32 2GB dask.array<chunksize=(1, 1060, 1300), meta=np.ndarray>\n",
       "Attributes: (12/55)\n",
       "    Conventions:                     CF-1.7 ACDD1.3\n",
       "    contact:                         dsroberts@unimelb.edu.au\n",
       "    contributor_email:               paola.petrelli@utas.edu.au, sam.green@un...\n",
       "    contributor_name:                Paola Petrelli, Samuel Green\n",
       "    contributor_role:                data_curator, data_curator\n",
       "    contributor_url:                 https://orcid.org/0000-0002-0164-5105, h...\n",
       "    ...                              ...\n",
       "    intake_esm_attrs:variable:       tas\n",
       "    intake_esm_attrs:experiment_id:  canberra03\n",
       "    intake_esm_attrs:frequency:      1hr\n",
       "    intake_esm_attrs:date_range:     200301160030-200301192330\n",
       "    intake_esm_attrs:_data_format_:  netcdf\n",
       "    intake_esm_dataset_key:          v1-0.1hr.tas"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds = experiment.search(variable='tas', frequency=\"1hr\").to_dask()\n",
    "ds"
   ]
  },
  {
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   "execution_count": 7,
   "id": "1a42e650-e76d-4108-ba00-e52007b62e2e",
   "metadata": {
    "tags": []
   },
   "outputs": [
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       ".xr-var-data,\n",
       ".xr-index-name div,\n",
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       ".xr-attrs {\n",
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       "}\n",
       "\n",
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       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
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       "  grid-column: 1 / -1;\n",
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       "  margin: 0;\n",
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       "\n",
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       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
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       "  width: auto;\n",
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       "\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",
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       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
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       "  vertical-align: middle;\n",
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       "</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=(1, 1060, 1300), 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 scalar dime...</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'>'tas'</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-161cbbab-a29c-41b3-83be-090da7029c3c' class='xr-array-in' type='checkbox' checked><label for='section-161cbbab-a29c-41b3-83be-090da7029c3c' 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> 1.97 GiB </td>\n",
       "                        <td> 5.26 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
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       "                        <td> (96, 2120, 2600) </td>\n",
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       "                    <tr>\n",
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       "                    <tr>\n",
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       "       &#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-6118ef3f-bf09-4202-8858-6ee43e36f205' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6118ef3f-bf09-4202-8858-6ee43e36f205' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b3931ca8-5dfe-4086-8bf5-990afb2517cd' class='xr-var-data-in' type='checkbox'><label for='data-b3931ca8-5dfe-4086-8bf5-990afb2517cd' 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])</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-b7267fa2-871e-43e9-ade4-cbb1556c7c5f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b7267fa2-871e-43e9-ade4-cbb1556c7c5f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7aa6209e-d6bb-4c09-9c30-ee5c58027995' class='xr-var-data-in' type='checkbox'><label for='data-7aa6209e-d6bb-4c09-9c30-ee5c58027995' 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])</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-22866615-02aa-4af8-aa12-e668a67cf315' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-22866615-02aa-4af8-aa12-e668a67cf315' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6e2a52b0-1b3b-40f2-9d9e-ebdf3392cc63' class='xr-var-data-in' type='checkbox'><label for='data-6e2a52b0-1b3b-40f2-9d9e-ebdf3392cc63' 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-ca32fa06-41ba-428e-9d64-2c87d0ef9cfe' class='xr-section-summary-in' type='checkbox'  ><label for='section-ca32fa06-41ba-428e-9d64-2c87d0ef9cfe' 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-cab22ac8-f276-4a5f-8235-abd1c3a2a74e' class='xr-index-data-in' type='checkbox'/><label for='index-cab22ac8-f276-4a5f-8235-abd1c3a2a74e' 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;2003-01-16 00:29:59.999999872&#x27;,\n",
       "                         &#x27;2003-01-16 01:30:00&#x27;,\n",
       "               &#x27;2003-01-16 02:30:00.000000128&#x27;,\n",
       "               &#x27;2003-01-16 03:29:59.999999872&#x27;,\n",
       "                         &#x27;2003-01-16 04:30:00&#x27;,\n",
       "               &#x27;2003-01-16 05:30:00.000000128&#x27;,\n",
       "               &#x27;2003-01-16 06:29:59.999999872&#x27;,\n",
       "                         &#x27;2003-01-16 07:30:00&#x27;,\n",
       "               &#x27;2003-01-16 08:30:00.000000128&#x27;,\n",
       "               &#x27;2003-01-16 09:29:59.999999872&#x27;,\n",
       "                         &#x27;2003-01-16 10:30:00&#x27;,\n",
       "               &#x27;2003-01-16 11:30:00.000000128&#x27;,\n",
       "               &#x27;2003-01-16 12:29:59.999999872&#x27;,\n",
       "                         &#x27;2003-01-16 13:30:00&#x27;,\n",
       "               &#x27;2003-01-16 14:30:00.000000128&#x27;,\n",
       "               &#x27;2003-01-16 15:29:59.999999872&#x27;,\n",
       "                         &#x27;2003-01-16 16:30:00&#x27;,\n",
       "               &#x27;2003-01-16 17:30:00.000000128&#x27;,\n",
       "               &#x27;2003-01-16 18:29:59.999999872&#x27;,\n",
       "                         &#x27;2003-01-16 19:30:00&#x27;,\n",
       "               &#x27;2003-01-16 20:30:00.000000128&#x27;,\n",
       "               &#x27;2003-01-16 21:29:59.999999872&#x27;,\n",
       "                         &#x27;2003-01-16 22:30:00&#x27;,\n",
       "               &#x27;2003-01-16 23:30:00.000000128&#x27;,\n",
       "               &#x27;2003-01-17 00:29:59.999999872&#x27;,\n",
       "                         &#x27;2003-01-17 01:30:00&#x27;,\n",
       "               &#x27;2003-01-17 02:30:00.000000128&#x27;,\n",
       "               &#x27;2003-01-17 03:29:59.999999872&#x27;,\n",
       "                         &#x27;2003-01-17 04:30:00&#x27;,\n",
       "               &#x27;2003-01-17 05:30:00.000000128&#x27;,\n",
       "               &#x27;2003-01-17 06:29:59.999999872&#x27;,\n",
       "                         &#x27;2003-01-17 07:30:00&#x27;,\n",
       "               &#x27;2003-01-17 08:30:00.000000128&#x27;,\n",
       "               &#x27;2003-01-17 09:29:59.999999872&#x27;,\n",
       "                         &#x27;2003-01-17 10:30:00&#x27;,\n",
       "               &#x27;2003-01-17 11:30:00.000000128&#x27;,\n",
       "               &#x27;2003-01-17 12:29:59.999999872&#x27;,\n",
       "                         &#x27;2003-01-17 13:30:00&#x27;,\n",
       "               &#x27;2003-01-17 14:30:00.000000128&#x27;,\n",
       "               &#x27;2003-01-17 15:29:59.999999872&#x27;,\n",
       "                         &#x27;2003-01-17 16:30:00&#x27;,\n",
       "               &#x27;2003-01-17 17:30:00.000000128&#x27;,\n",
       "               &#x27;2003-01-17 18:29:59.999999872&#x27;,\n",
       "                         &#x27;2003-01-17 19:30:00&#x27;,\n",
       "               &#x27;2003-01-17 20:30:00.000000128&#x27;,\n",
       "               &#x27;2003-01-17 21:29:59.999999872&#x27;,\n",
       "                         &#x27;2003-01-17 22:30:00&#x27;,\n",
       "               &#x27;2003-01-17 23:30:00.000000128&#x27;,\n",
       "               &#x27;2003-01-18 00:29:59.999999872&#x27;,\n",
       "                         &#x27;2003-01-18 01:30:00&#x27;,\n",
       "               &#x27;2003-01-18 02:30:00.000000128&#x27;,\n",
       "               &#x27;2003-01-18 03:29:59.999999872&#x27;,\n",
       "                         &#x27;2003-01-18 04:30:00&#x27;,\n",
       "               &#x27;2003-01-18 05:30:00.000000128&#x27;,\n",
       "               &#x27;2003-01-18 06:29:59.999999872&#x27;,\n",
       "                         &#x27;2003-01-18 07:30:00&#x27;,\n",
       "               &#x27;2003-01-18 08:30:00.000000128&#x27;,\n",
       "               &#x27;2003-01-18 09:29:59.999999872&#x27;,\n",
       "                         &#x27;2003-01-18 10:30:00&#x27;,\n",
       "               &#x27;2003-01-18 11:30:00.000000128&#x27;,\n",
       "               &#x27;2003-01-18 12:29:59.999999872&#x27;,\n",
       "                         &#x27;2003-01-18 13:30:00&#x27;,\n",
       "               &#x27;2003-01-18 14:30:00.000000128&#x27;,\n",
       "               &#x27;2003-01-18 15:29:59.999999872&#x27;,\n",
       "                         &#x27;2003-01-18 16:30:00&#x27;,\n",
       "               &#x27;2003-01-18 17:30:00.000000128&#x27;,\n",
       "               &#x27;2003-01-18 18:29:59.999999872&#x27;,\n",
       "                         &#x27;2003-01-18 19:30:00&#x27;,\n",
       "               &#x27;2003-01-18 20:30:00.000000128&#x27;,\n",
       "               &#x27;2003-01-18 21:29:59.999999872&#x27;,\n",
       "                         &#x27;2003-01-18 22:30:00&#x27;,\n",
       "               &#x27;2003-01-18 23:30:00.000000128&#x27;,\n",
       "               &#x27;2003-01-19 00:29:59.999999872&#x27;,\n",
       "                         &#x27;2003-01-19 01:30:00&#x27;,\n",
       "               &#x27;2003-01-19 02:30:00.000000128&#x27;,\n",
       "               &#x27;2003-01-19 03:29:59.999999872&#x27;,\n",
       "                         &#x27;2003-01-19 04:30:00&#x27;,\n",
       "               &#x27;2003-01-19 05:30:00.000000128&#x27;,\n",
       "               &#x27;2003-01-19 06:29:59.999999872&#x27;,\n",
       "                         &#x27;2003-01-19 07:30:00&#x27;,\n",
       "               &#x27;2003-01-19 08:30:00.000000128&#x27;,\n",
       "               &#x27;2003-01-19 09:29:59.999999872&#x27;,\n",
       "                         &#x27;2003-01-19 10:30:00&#x27;,\n",
       "               &#x27;2003-01-19 11:30:00.000000128&#x27;,\n",
       "               &#x27;2003-01-19 12:29:59.999999872&#x27;,\n",
       "                         &#x27;2003-01-19 13:30:00&#x27;,\n",
       "               &#x27;2003-01-19 14:30:00.000000128&#x27;,\n",
       "               &#x27;2003-01-19 15:29:59.999999872&#x27;,\n",
       "                         &#x27;2003-01-19 16:30:00&#x27;,\n",
       "               &#x27;2003-01-19 17:30:00.000000128&#x27;,\n",
       "               &#x27;2003-01-19 18:29:59.999999872&#x27;,\n",
       "                         &#x27;2003-01-19 19:30:00&#x27;,\n",
       "               &#x27;2003-01-19 20:30:00.000000128&#x27;,\n",
       "               &#x27;2003-01-19 21:29:59.999999872&#x27;,\n",
       "                         &#x27;2003-01-19 22:30:00&#x27;,\n",
       "               &#x27;2003-01-19 23:30:00.000000128&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, 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-b0f20f89-0bd0-48b4-87a8-2a6c7a15b021' class='xr-index-data-in' type='checkbox'/><label for='index-b0f20f89-0bd0-48b4-87a8-2a6c7a15b021' 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-976b98d3-8431-459f-a7e9-c6e6cd1214a7' class='xr-index-data-in' type='checkbox'/><label for='index-976b98d3-8431-459f-a7e9-c6e6cd1214a7' 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-3817f451-a34b-40d0-a601-9d28e6f73ca3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3817f451-a34b-40d0-a601-9d28e6f73ca3' class='xr-section-summary' >Attributes: <span>(7)</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></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=(1, 1060, 1300), 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 scalar dime..."
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tas = ds['tas']\n",
    "tas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "f3e12e59-97ee-49fc-bd6d-e5254ed5700a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x1515d0d2d9c0>"
      ]
     },
     "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": [
    "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": 9,
   "id": "19da85a0-a952-4acb-a679-04f3d318582f",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x1515a82d13f0>"
      ]
     },
     "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": [
    "tas.cf.sel(longitude = 130, method='nearest').plot()"
   ]
  }
 ],
 "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
}