Mopper_Intake_demo.ipynb

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   "source": [
    "# Create an intake catalogue using ACCESS-MOPPeR"
   ]
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   "id": "3fd21958-9f8f-4483-baa9-dfdca810605d",
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   "source": [
    "In this tutorial we are showing how to create an intake-esm catalogue to access ACCESS raw model output. To do so we are using the ACCESS-MOPPeR command line tool. MOPPeR was developed to post-process raw model output to CMIP style variables. However, as part of the workflow is the mapping of raw output to well-described variables it can be used to create a curated list of the raw output to use as base for an intake catalogue. "
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       "                            <strong>Comm: </strong> tcp://127.0.0.1:33195\n",
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       "                            <strong>Total threads: </strong> 3\n",
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       "                            <strong>Dashboard: </strong> <a href=\"/proxy/41031/status\" target=\"_blank\">/proxy/41031/status</a>\n",
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       "                            <strong>Local directory: </strong> /jobfs/121532218.gadi-pbs/dask-scratch-space/worker-aot49f59\n",
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       "                            <strong>CPU usage:</strong> 2.0%\n",
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       "                            <strong>Last seen: </strong> Just now\n",
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       "                            <strong>Memory usage: </strong> 127.67 MiB\n",
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       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Comm: </strong> tcp://127.0.0.1:45763\n",
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       "                            <strong>Total threads: </strong> 3\n",
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       "                            <strong>Local directory: </strong> /jobfs/121532218.gadi-pbs/dask-scratch-space/worker-bwdtofca\n",
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       "                            <strong>CPU usage:</strong> 4.0%\n",
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       "                            <strong>Last seen: </strong> Just now\n",
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       "                            <strong>Memory usage: </strong> 127.18 MiB\n",
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       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Comm: </strong> tcp://127.0.0.1:42991\n",
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       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Total threads: </strong> 3\n",
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       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Dashboard: </strong> <a href=\"/proxy/43349/status\" target=\"_blank\">/proxy/43349/status</a>\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Memory: </strong> 11.50 GiB\n",
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       "                            <strong>Nanny: </strong> tcp://127.0.0.1:37777\n",
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       "                            <strong>Local directory: </strong> /jobfs/121532218.gadi-pbs/dask-scratch-space/worker-sxj6ffob\n",
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       "\n",
       "                    \n",
       "\n",
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       "                            <strong>Tasks executing: </strong> \n",
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       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Tasks in memory: </strong> \n",
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       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Tasks ready: </strong> \n",
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       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Tasks in flight: </strong>\n",
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       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>CPU usage:</strong> 0.0%\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Last seen: </strong> Just now\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Memory usage: </strong> 127.15 MiB\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Spilled bytes: </strong> 0 B\n",
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       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Read bytes: </strong> 358.50 kiB\n",
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       "                            <strong>Write bytes: </strong> 122.61 kiB\n",
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       "                    \n",
       "\n",
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       "        \n",
       "        <div style=\"margin-bottom: 20px;\">\n",
       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
       "            <div style=\"margin-left: 48px;\">\n",
       "            <details>\n",
       "                <summary>\n",
       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 3</h4>\n",
       "                </summary>\n",
       "                <table style=\"width: 100%; text-align: left;\">\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Comm: </strong> tcp://127.0.0.1:35013\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Total threads: </strong> 3\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Dashboard: </strong> <a href=\"/proxy/35681/status\" target=\"_blank\">/proxy/35681/status</a>\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Memory: </strong> 11.50 GiB\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Nanny: </strong> tcp://127.0.0.1:43581\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\"></td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
       "                            <strong>Local directory: </strong> /jobfs/121532218.gadi-pbs/dask-scratch-space/worker-9gwj63ft\n",
       "                        </td>\n",
       "                    </tr>\n",
       "\n",
       "                    \n",
       "\n",
       "                    \n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Tasks executing: </strong> \n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Tasks in memory: </strong> \n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Tasks ready: </strong> \n",
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       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Tasks in flight: </strong>\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>CPU usage:</strong> 2.0%\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Last seen: </strong> Just now\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Memory usage: </strong> 127.07 MiB\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Spilled bytes: </strong> 0 B\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Read bytes: </strong> 359.73 kiB\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Write bytes: </strong> 123.87 kiB\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    \n",
       "\n",
       "                </table>\n",
       "            </details>\n",
       "            </div>\n",
       "        </div>\n",
       "        \n",
       "\n",
       "    </details>\n",
       "</div>\n",
       "            </details>\n",
       "        \n",
       "\n",
       "    </div>\n",
       "</div>"
      ],
      "text/plain": [
       "<Client: 'tcp://127.0.0.1:41671' processes=4 threads=12, memory=46.00 GiB>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from dask.distributed import Client\n",
    "\n",
    "client = Client(\"tcp://127.0.0.1:41671\")\n",
    "client"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "a93e8d09-9d9f-4e80-8c61-cf8912647f07",
   "metadata": {},
   "outputs": [],
   "source": [
    "import intake\n",
    "import xarray as xr\n",
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "18d3f7c9-85d1-4075-b25a-b53fa3ce83d5",
   "metadata": {},
   "outputs": [],
   "source": [
    "mopenv = '/g/data/ua8/Working/packages/ACCESS-MOPPeR/mopper_env/bin'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "5cc4579e-09be-4a37-ae09-6b0209a8e613",
   "metadata": {},
   "outputs": [],
   "source": [
    "# MOPPeR will soon be available in the hh5 conda environment, in the meantime we installed it in a custom conda environment\n",
    "! source /g/data/ua8/Working/packages/ACCESS-MOPPeR/mopper_env/bin/activate"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bb82ee1c-3baf-43c3-a651-cdebbb1455ea",
   "metadata": {},
   "source": [
    "To run this tutorial we are using some raw model output from a AUS2200 run. NB the UM data output has been converted to netcdf but the files are still stored in the same directory structure as they were output by the model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "8a7a9155-0bdf-4a04-9748-31cc7753fade",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Opened database /g/data/ua8/Working/packages/ACCESS-MOPPeR/mopper_env/lib/python3.10/site-packages/mopdata/access.db successfully\n",
      "Variable list for umnsa_cldrad_ successfully written\n",
      "Variable list for umnsa_mdl_ successfully written\n",
      "Found more than 1 definition for fld_s08i225:\n",
      "[('tsl', 'CM2', 'CMIP6_Lmon', 'mon'), ('tsl', 'ESM1.5', 'CMIP6_Lmon', 'mon')]\n",
      " Using tsl from CMIP6_Lmon\n",
      "Variable list for umnsa_slv_ successfully written\n",
      "Variable list for umnsa_spec_ successfully written\n",
      "Derived variables: {'va24', 'prw', 'theta24', 'refl24', 'wa24', 'sifllatstop', 'ta24', 'ua24', 'hus24'}\n",
      "Changing cl-AUS2200_A1hr units from 1 to %\n",
      "Changing rainmxrat-AUS2200_A1hr units from kg kg-1 to 1\n",
      "Changing grplmxrat-AUS2200_A1hr units from kg kg-1 to 1\n",
      "Variable: rinum- has no associated cmor_table\n",
      "Variable: rho- has no associated cmor_table\n",
      "Changing lmask-AUS2200_fx units from 1 to %\n",
      "Changing siconca-AUS2200_A1hr units from 1 to %\n",
      "Changing evspsbl_Pt-AUS2200_A1hr realm from atmos to land\n",
      "Changing evspsbl-AUS2200_A1hr realm from atmos to land\n",
      "Changing cw-AUS2200_A1hr realm from atmos to land\n",
      "Variable: evspsblpot- has no associated cmor_table\n",
      "Changing flashrate-AUS2200_A10min units from s-1 to km-2 s-1\n",
      "Changing lwp-AUS2200_A10min realm from atmos to areosol\n",
      "Changing ta24-AUS2200_A1hrPlev units from Pa to K\n",
      "Changing sifllatstop-AUS2200_A1hr units from 1 to W m-2\n",
      "Intake-esm and intake catalogues written to\n",
      "    intake_testrun.json and intake_testrun.yaml. File list saved to catalogue.csv.xz\n",
      "\u001b[0m"
     ]
    }
   ],
   "source": [
    "! /g/data/ua8/Working/packages/ACCESS-MOPPeR/mopper_env/bin/mopdb intake -f /g/data/v45/cc6171/experiments/ECL-2016_smallshift/netcdf/u-cs142  -v AUS2200 -m 20160603 -a testrun"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ab7900e8-928f-4086-814a-604c42c7489a",
   "metadata": {},
   "source": [
    "This command will create 3 files:\n",
    "* the main intake catalogue intake_test.yaml, \n",
    "* the intake-esm catalogue for the selected source intake_test.json,\n",
    "* and finally a list of all the files path and attributes catalogue.csv.xz\n",
    "\n",
    "We can now open the catalogue."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "92607264-dd11-4984-9591-f1efe06e4b46",
   "metadata": {},
   "outputs": [],
   "source": [
    "cat = intake.open_catalog('/g/data/ua8/Working/packages/ACCESS-MOPPeR/intake_demo.yaml')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "acda8934-5abc-47d3-8094-e5cb191d08a2",
   "metadata": {},
   "source": [
    "Usually intake would assume that each file contains one variable, which is not the case for raw model output, this is while we also defined a \"yaml\" catalogue file veen if we are only delaing with one datasets. In the catalogue definition we let intake knows that some of the fields have multiple values:\n",
    "* variable: the roginal variable name\n",
    "* map_var: the cmip style variable name where available\n",
    "* standard_name: the variable standard_name where available\n",
    "\n",
    "NB only `variable` will have a complete list of all the variables available, but as the name in the raw model output can be obscured we added the other two lists to faciliate queries.\n",
    "\n",
    "As an alternative the intake-esm json catalogue can be accessed directly with a few adjustments."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "44ce37a6-7d62-430b-be05-7707872e87b1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['demo']\n"
     ]
    }
   ],
   "source": [
    "print(list(cat))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "fb0b340e-4258-48ec-a48f-2b84d44a0c5f",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "demo = cat['demo']\n",
    "#testrun = intake.open_esm_datastore(\n",
    "#    \"/g/data/ua8/Working/packages/ACCESS-MOPPeR/intake_testrun.json\",\n",
    "#    columns_with_iterables=[\"variable\", \"map_var\", \"standard_name\"],\n",
    "#)\n",
    "demo.esmcat.has_multiple_variable_assets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "4878fc41-1e43-484a-ad35-719c3112917b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['NAV',\n",
       " 'theta',\n",
       " 'huslev1',\n",
       " 'phalf',\n",
       " 'pslev1',\n",
       " 'zfull',\n",
       " 'snw',\n",
       " 'zmla',\n",
       " 'z0',\n",
       " 'siconca',\n",
       " 'rss',\n",
       " 'rsut',\n",
       " 'rsdt',\n",
       " 'rsdsdir',\n",
       " 'rsdsdiff',\n",
       " 'rsds',\n",
       " 'rls',\n",
       " 'rlut',\n",
       " 'rlds',\n",
       " 'uas',\n",
       " 'vas',\n",
       " 'hfss_Pt',\n",
       " 'hfss',\n",
       " 'evspsbl_Pt',\n",
       " 'evspsbl',\n",
       " 'estot',\n",
       " 'eow',\n",
       " 'hfls_Pt',\n",
       " 'hfls',\n",
       " 'tasmin',\n",
       " 'tas',\n",
       " 'tasmax',\n",
       " 'huss',\n",
       " 'tdps',\n",
       " 'tauu',\n",
       " 'tauv_Pt',\n",
       " 'tauv',\n",
       " 'wsgmax10m',\n",
       " 'mrso',\n",
       " 'cw',\n",
       " 'mrsol',\n",
       " 'tsl',\n",
       " 'clmxro',\n",
       " 'psl',\n",
       " 'ts',\n",
       " 'ps',\n",
       " 'evspsblpot',\n",
       " 'wsgmax10m_max',\n",
       " 'reflmax',\n",
       " 'pralsprof',\n",
       " 'pralsns',\n",
       " 'cllow',\n",
       " 'clmed',\n",
       " 'clhigh',\n",
       " 'flashrate',\n",
       " 'storm',\n",
       " 'nflash',\n",
       " 'amdry',\n",
       " 'amwet',\n",
       " 'lwp',\n",
       " 'clivi']"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "demo.unique()['mapvar']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "94181a4b-12cc-4ab9-8ebb-ea90536b10b3",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>path</th>\n",
       "      <th>experiment</th>\n",
       "      <th>realm</th>\n",
       "      <th>frequency</th>\n",
       "      <th>variable</th>\n",
       "      <th>mapvar</th>\n",
       "      <th>standard_name</th>\n",
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       "      <th>cell_methods</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>/g/data/v45/cc6171/experiments/ECL-2016_smalls...</td>\n",
       "      <td>demo2</td>\n",
       "      <td>atmos</td>\n",
       "      <td>1hr</td>\n",
       "      <td>[fld_s03i209]</td>\n",
       "      <td>uas</td>\n",
       "      <td>eastward_wind</td>\n",
       "      <td>201606030000</td>\n",
       "      <td>m s-1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>area: time: mean</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>/g/data/v45/cc6171/experiments/ECL-2016_smalls...</td>\n",
       "      <td>demo2</td>\n",
       "      <td>atmos</td>\n",
       "      <td>1hr</td>\n",
       "      <td>[fld_s03i209]</td>\n",
       "      <td>uas</td>\n",
       "      <td>eastward_wind</td>\n",
       "      <td>201606030101</td>\n",
       "      <td>m s-1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>area: time: mean</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>/g/data/v45/cc6171/experiments/ECL-2016_smalls...</td>\n",
       "      <td>demo2</td>\n",
       "      <td>atmos</td>\n",
       "      <td>1hr</td>\n",
       "      <td>[fld_s03i209]</td>\n",
       "      <td>uas</td>\n",
       "      <td>eastward_wind</td>\n",
       "      <td>201606030201</td>\n",
       "      <td>m s-1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>area: time: mean</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>/g/data/v45/cc6171/experiments/ECL-2016_smalls...</td>\n",
       "      <td>demo2</td>\n",
       "      <td>atmos</td>\n",
       "      <td>1hr</td>\n",
       "      <td>[fld_s03i209]</td>\n",
       "      <td>uas</td>\n",
       "      <td>eastward_wind</td>\n",
       "      <td>201606030301</td>\n",
       "      <td>m s-1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>area: time: mean</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>/g/data/v45/cc6171/experiments/ECL-2016_smalls...</td>\n",
       "      <td>demo2</td>\n",
       "      <td>atmos</td>\n",
       "      <td>1hr</td>\n",
       "      <td>[fld_s03i209]</td>\n",
       "      <td>uas</td>\n",
       "      <td>eastward_wind</td>\n",
       "      <td>201606030401</td>\n",
       "      <td>m s-1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>area: time: mean</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>/g/data/v45/cc6171/experiments/ECL-2016_smalls...</td>\n",
       "      <td>demo2</td>\n",
       "      <td>atmos</td>\n",
       "      <td>1hr</td>\n",
       "      <td>[fld_s03i209]</td>\n",
       "      <td>uas</td>\n",
       "      <td>eastward_wind</td>\n",
       "      <td>201606071901</td>\n",
       "      <td>m s-1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>area: time: mean</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>/g/data/v45/cc6171/experiments/ECL-2016_smalls...</td>\n",
       "      <td>demo2</td>\n",
       "      <td>atmos</td>\n",
       "      <td>1hr</td>\n",
       "      <td>[fld_s03i209]</td>\n",
       "      <td>uas</td>\n",
       "      <td>eastward_wind</td>\n",
       "      <td>201606072001</td>\n",
       "      <td>m s-1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>area: time: mean</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>/g/data/v45/cc6171/experiments/ECL-2016_smalls...</td>\n",
       "      <td>demo2</td>\n",
       "      <td>atmos</td>\n",
       "      <td>1hr</td>\n",
       "      <td>[fld_s03i209]</td>\n",
       "      <td>uas</td>\n",
       "      <td>eastward_wind</td>\n",
       "      <td>201606072101</td>\n",
       "      <td>m s-1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>area: time: mean</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>/g/data/v45/cc6171/experiments/ECL-2016_smalls...</td>\n",
       "      <td>demo2</td>\n",
       "      <td>atmos</td>\n",
       "      <td>1hr</td>\n",
       "      <td>[fld_s03i209]</td>\n",
       "      <td>uas</td>\n",
       "      <td>eastward_wind</td>\n",
       "      <td>201606072201</td>\n",
       "      <td>m s-1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>area: time: mean</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>/g/data/v45/cc6171/experiments/ECL-2016_smalls...</td>\n",
       "      <td>demo2</td>\n",
       "      <td>atmos</td>\n",
       "      <td>1hr</td>\n",
       "      <td>[fld_s03i209]</td>\n",
       "      <td>uas</td>\n",
       "      <td>eastward_wind</td>\n",
       "      <td>201606072301</td>\n",
       "      <td>m s-1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>area: time: mean</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>120 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                  path experiment  realm  \\\n",
       "0    /g/data/v45/cc6171/experiments/ECL-2016_smalls...      demo2  atmos   \n",
       "1    /g/data/v45/cc6171/experiments/ECL-2016_smalls...      demo2  atmos   \n",
       "2    /g/data/v45/cc6171/experiments/ECL-2016_smalls...      demo2  atmos   \n",
       "3    /g/data/v45/cc6171/experiments/ECL-2016_smalls...      demo2  atmos   \n",
       "4    /g/data/v45/cc6171/experiments/ECL-2016_smalls...      demo2  atmos   \n",
       "..                                                 ...        ...    ...   \n",
       "115  /g/data/v45/cc6171/experiments/ECL-2016_smalls...      demo2  atmos   \n",
       "116  /g/data/v45/cc6171/experiments/ECL-2016_smalls...      demo2  atmos   \n",
       "117  /g/data/v45/cc6171/experiments/ECL-2016_smalls...      demo2  atmos   \n",
       "118  /g/data/v45/cc6171/experiments/ECL-2016_smalls...      demo2  atmos   \n",
       "119  /g/data/v45/cc6171/experiments/ECL-2016_smalls...      demo2  atmos   \n",
       "\n",
       "    frequency       variable mapvar  standard_name          date  units  \\\n",
       "0         1hr  [fld_s03i209]    uas  eastward_wind  201606030000  m s-1   \n",
       "1         1hr  [fld_s03i209]    uas  eastward_wind  201606030101  m s-1   \n",
       "2         1hr  [fld_s03i209]    uas  eastward_wind  201606030201  m s-1   \n",
       "3         1hr  [fld_s03i209]    uas  eastward_wind  201606030301  m s-1   \n",
       "4         1hr  [fld_s03i209]    uas  eastward_wind  201606030401  m s-1   \n",
       "..        ...            ...    ...            ...           ...    ...   \n",
       "115       1hr  [fld_s03i209]    uas  eastward_wind  201606071901  m s-1   \n",
       "116       1hr  [fld_s03i209]    uas  eastward_wind  201606072001  m s-1   \n",
       "117       1hr  [fld_s03i209]    uas  eastward_wind  201606072101  m s-1   \n",
       "118       1hr  [fld_s03i209]    uas  eastward_wind  201606072201  m s-1   \n",
       "119       1hr  [fld_s03i209]    uas  eastward_wind  201606072301  m s-1   \n",
       "\n",
       "     calculation      cell_methods  \n",
       "0            NaN  area: time: mean  \n",
       "1            NaN  area: time: mean  \n",
       "2            NaN  area: time: mean  \n",
       "3            NaN  area: time: mean  \n",
       "4            NaN  area: time: mean  \n",
       "..           ...               ...  \n",
       "115          NaN  area: time: mean  \n",
       "116          NaN  area: time: mean  \n",
       "117          NaN  area: time: mean  \n",
       "118          NaN  area: time: mean  \n",
       "119          NaN  area: time: mean  \n",
       "\n",
       "[120 rows x 11 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "subset = demo.search(mapvar=['uas'], frequency='1hr')\n",
    "subset.df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "46605187-d5ca-4f4d-9745-014afe31ad8a",
   "metadata": {},
   "source": [
    "This includes the entire timeseries we want to get a smaller subset only the data for the 5th of June after 8pm. We can do this in two ways:\n",
    "* using a regex to select on date=r\"201606052.*\"\n",
    "* or by selecting all the files in between two dates.\n",
    "\n",
    "In this specific case using the first method it's esier but we will demo both."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "89402c48-abcc-4c37-9d47-14fe1957b479",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "      <th>1</th>\n",
       "      <td>/g/data/v45/cc6171/experiments/ECL-2016_smalls...</td>\n",
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       "      <th>2</th>\n",
       "      <td>/g/data/v45/cc6171/experiments/ECL-2016_smalls...</td>\n",
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       "      <td>m s-1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>area: time: mean</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>/g/data/v45/cc6171/experiments/ECL-2016_smalls...</td>\n",
       "      <td>demo2</td>\n",
       "      <td>atmos</td>\n",
       "      <td>1hr</td>\n",
       "      <td>[fld_s03i209]</td>\n",
       "      <td>uas</td>\n",
       "      <td>eastward_wind</td>\n",
       "      <td>201606052301</td>\n",
       "      <td>m s-1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>area: time: mean</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                path experiment  realm  \\\n",
       "0  /g/data/v45/cc6171/experiments/ECL-2016_smalls...      demo2  atmos   \n",
       "1  /g/data/v45/cc6171/experiments/ECL-2016_smalls...      demo2  atmos   \n",
       "2  /g/data/v45/cc6171/experiments/ECL-2016_smalls...      demo2  atmos   \n",
       "3  /g/data/v45/cc6171/experiments/ECL-2016_smalls...      demo2  atmos   \n",
       "\n",
       "  frequency       variable mapvar  standard_name          date  units  \\\n",
       "0       1hr  [fld_s03i209]    uas  eastward_wind  201606052001  m s-1   \n",
       "1       1hr  [fld_s03i209]    uas  eastward_wind  201606052101  m s-1   \n",
       "2       1hr  [fld_s03i209]    uas  eastward_wind  201606052201  m s-1   \n",
       "3       1hr  [fld_s03i209]    uas  eastward_wind  201606052301  m s-1   \n",
       "\n",
       "   calculation      cell_methods  \n",
       "0          NaN  area: time: mean  \n",
       "1          NaN  area: time: mean  \n",
       "2          NaN  area: time: mean  \n",
       "3          NaN  area: time: mean  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "subset = subset.search(date=r\"201606052.*\")\n",
    "subset.df"
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   "execution_count": 9,
   "id": "3af9f07a-e853-44fb-a443-9e138d870bde",
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "--> The keys in the returned dictionary of datasets are constructed as follows:\n",
      "\t'realm.frequency.mapvar'\n"
     ]
    },
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       "['atmos.1hr.uas']"
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   "cell_type": "code",
   "execution_count": 11,
   "id": "f7ab9656-580e-45c6-893e-3452bc744aae",
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   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 7GB\n",
       "Dimensions:             (time: 4, lat: 2120, lon: 2600, time_0: 4, lon_0: 2600,\n",
       "                         lat_0: 2121, depth: 4, time_1: 4, bnds: 2)\n",
       "Coordinates: (12/75)\n",
       "  * time                (time) datetime64[ns] 32B 2016-06-05T21:00:00 ... 201...\n",
       "  * lat                 (lat) float64 17kB -48.79 -48.77 ... -6.852 -6.832\n",
       "  * lon                 (lon) float64 21kB 114.3 114.3 114.3 ... 165.7 165.7\n",
       "  * time_0              (time_0) datetime64[ns] 32B 2016-06-05T20:30:00 ... 2...\n",
       "  * lon_0               (lon_0) float64 21kB 114.3 114.3 114.3 ... 165.7 165.7\n",
       "  * lat_0               (lat_0) float64 17kB -48.8 -48.78 ... -6.842 -6.822\n",
       "    ...                  ...\n",
       "    fld_s09i212         (time, lat, lon) float32 88MB dask.array&lt;chunksize=(4, 1060, 1300), meta=np.ndarray&gt;\n",
       "    fld_s09i213         (time, lat, lon) float32 88MB dask.array&lt;chunksize=(4, 1060, 1300), meta=np.ndarray&gt;\n",
       "    fld_s09i214         (time, lat, lon) float32 88MB dask.array&lt;chunksize=(4, 1060, 1300), meta=np.ndarray&gt;\n",
       "    fld_s09i215         (time, lat, lon) float32 88MB dask.array&lt;chunksize=(4, 1060, 1300), meta=np.ndarray&gt;\n",
       "    fld_s09i217         (time_0, lat, lon) float32 88MB dask.array&lt;chunksize=(4, 1060, 1300), meta=np.ndarray&gt;\n",
       "    fld_s16i222         (time_0, lat, lon) float32 88MB dask.array&lt;chunksize=(4, 1060, 1300), meta=np.ndarray&gt;\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    fld_s03i209         (time_1, time, time_0, lat, lon_0) float32 1GB dask.array&lt;chunksize=(1, 4, 4, 1060, 1300), meta=np.ndarray&gt;\n",
       "Attributes: (12/14)\n",
       "    Conventions:                     CF-1.6\n",
       "    source:                          Data from Met Office Unified Model\n",
       "    um_version:                      12.2\n",
       "    intake_esm_vars:                 [&#x27;fld_s03i209&#x27;]\n",
       "    intake_esm_attrs:experiment:     demo2\n",
       "    intake_esm_attrs:realm:          atmos\n",
       "    ...                              ...\n",
       "    intake_esm_attrs:mapvar:         uas\n",
       "    intake_esm_attrs:standard_name:  eastward_wind\n",
       "    intake_esm_attrs:units:          m s-1\n",
       "    intake_esm_attrs:cell_methods:   area: time: mean\n",
       "    intake_esm_attrs:_data_format_:  netcdf\n",
       "    intake_esm_dataset_key:          atmos.1hr.uas</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-33ffa670-a654-445d-bf64-2bea8eddafad' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-33ffa670-a654-445d-bf64-2bea8eddafad' 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>: 4</li><li><span class='xr-has-index'>lat</span>: 2120</li><li><span class='xr-has-index'>lon</span>: 2600</li><li><span class='xr-has-index'>time_0</span>: 4</li><li><span class='xr-has-index'>lon_0</span>: 2600</li><li><span class='xr-has-index'>lat_0</span>: 2121</li><li><span class='xr-has-index'>depth</span>: 4</li><li><span class='xr-has-index'>time_1</span>: 4</li><li><span>bnds</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-b37148c9-a927-489d-a4f2-27f8eed0e5dd' class='xr-section-summary-in' type='checkbox'  ><label for='section-b37148c9-a927-489d-a4f2-27f8eed0e5dd' class='xr-section-summary' >Coordinates: <span>(75)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2016-06-05T21:00:00 ... 2016-06-06</div><input id='attrs-6b06e528-8996-4d74-b53c-8f7d4e26b89b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6b06e528-8996-4d74-b53c-8f7d4e26b89b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0cff048b-84a0-4beb-91fd-5c88b445306a' class='xr-var-data-in' type='checkbox'><label for='data-0cff048b-84a0-4beb-91fd-5c88b445306a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2016-06-05T21:00:00.000000000&#x27;, &#x27;2016-06-05T22:00:00.000000000&#x27;,\n",
       "       &#x27;2016-06-05T23:00:00.000000000&#x27;, &#x27;2016-06-06T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-48.79 -48.77 ... -6.852 -6.832</div><input id='attrs-50f3a7ed-c02c-4bb0-8ba1-29809c23fc08' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-50f3a7ed-c02c-4bb0-8ba1-29809c23fc08' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e8ff7f03-56c0-4b65-b1b9-e305a6dd5003' class='xr-var-data-in' type='checkbox'><label for='data-e8ff7f03-56c0-4b65-b1b9-e305a6dd5003' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-48.787998, -48.7682  , -48.748398, ...,  -6.871399,  -6.851597,\n",
       "        -6.831799])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>114.3 114.3 114.3 ... 165.7 165.7</div><input id='attrs-57e07aa4-4445-46c3-b438-9d77163b2162' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-57e07aa4-4445-46c3-b438-9d77163b2162' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6b896e93-9e64-484b-8e3a-6d65666ba0c4' class='xr-var-data-in' type='checkbox'><label for='data-6b896e93-9e64-484b-8e3a-6d65666ba0c4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([114.260002, 114.2798  , 114.299599, ..., 165.680603, 165.700409,\n",
       "       165.7202  ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time_0</span></div><div class='xr-var-dims'>(time_0)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2016-06-05T20:30:00 ... 2016-06-...</div><input id='attrs-8d41c7d1-709e-4784-a058-de33dd9ae701' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8d41c7d1-709e-4784-a058-de33dd9ae701' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c438bfea-7caa-4d4e-b029-6ca6200c0e09' class='xr-var-data-in' type='checkbox'><label for='data-c438bfea-7caa-4d4e-b029-6ca6200c0e09' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_0_bnds</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2016-06-05T20:30:00.000000000&#x27;, &#x27;2016-06-05T21:30:00.000000000&#x27;,\n",
       "       &#x27;2016-06-05T22:30:00.000000000&#x27;, &#x27;2016-06-05T23:30:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon_0</span></div><div class='xr-var-dims'>(lon_0)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>114.3 114.3 114.3 ... 165.7 165.7</div><input id='attrs-e82a517a-72c7-4bd1-950a-9ebd23ce3036' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e82a517a-72c7-4bd1-950a-9ebd23ce3036' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7c079d2a-9c85-4a2a-9c41-d1e6aa2e7d69' class='xr-var-data-in' type='checkbox'><label for='data-7c079d2a-9c85-4a2a-9c41-d1e6aa2e7d69' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_0_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([114.250099, 114.269897, 114.289696, ..., 165.6707  , 165.690491,\n",
       "       165.710297])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat_0</span></div><div class='xr-var-dims'>(lat_0)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-48.8 -48.78 ... -6.842 -6.822</div><input id='attrs-77b15c7e-01a7-4ef9-8911-9647c9723684' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-77b15c7e-01a7-4ef9-8911-9647c9723684' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d5f078e4-cb80-4667-9790-dd766708a45b' class='xr-var-data-in' type='checkbox'><label for='data-d5f078e4-cb80-4667-9790-dd766708a45b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_0_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-48.797901, -48.778103, -48.758301, ...,  -6.8615  ,  -6.841702,\n",
       "        -6.821903])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>depth</span></div><div class='xr-var-dims'>(depth)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.05 0.225 0.675 2.0</div><input id='attrs-6c7b6924-db7b-4246-99cc-57ba874a2596' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6c7b6924-db7b-4246-99cc-57ba874a2596' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bd93872f-2f19-4c5c-98fa-223a9dc1ba9e' class='xr-var-data-in' type='checkbox'><label for='data-bd93872f-2f19-4c5c-98fa-223a9dc1ba9e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Z</dd><dt><span>bounds :</span></dt><dd>depth_bnds</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>standard_name :</span></dt><dd>depth</dd><dt><span>positive :</span></dt><dd>down</dd></dl></div><div class='xr-var-data'><pre>array([0.05 , 0.225, 0.675, 2.   ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time_1</span></div><div class='xr-var-dims'>(time_1)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2016-06-05T20:01:14.999999744 .....</div><input id='attrs-6a2d83d5-307b-4f3d-89f1-ce70fb004ff6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6a2d83d5-307b-4f3d-89f1-ce70fb004ff6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b6169f2b-b7ef-41e2-bfdd-e27444ed5bf3' class='xr-var-data-in' type='checkbox'><label for='data-b6169f2b-b7ef-41e2-bfdd-e27444ed5bf3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2016-06-05T20:01:14.999999744&#x27;, &#x27;2016-06-05T21:01:15.000000000&#x27;,\n",
       "       &#x27;2016-06-05T22:01:15.000000000&#x27;, &#x27;2016-06-05T23:01:14.999999744&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fld_s00i023</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=(4, 1060, 1300), meta=np.ndarray&gt;</div><input id='attrs-1042c996-4928-4ff0-a33a-a85a1fa4fd7b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1042c996-4928-4ff0-a33a-a85a1fa4fd7b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eb8040ee-7428-43f9-8983-d41d21679b24' class='xr-var-data-in' type='checkbox'><label for='data-eb8040ee-7428-43f9-8983-d41d21679b24' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>surface_snow_amount</dd><dt><span>long_name :</span></dt><dd>SNOW AMOUNT OVER LAND AFT TSTP KG/M2</dd><dt><span>units :</span></dt><dd>kg m-2</dd><dt><span>um_stash_source :</span></dt><dd>m01s00i023</dd><dt><span>grid_mapping :</span></dt><dd>latitude_longitude</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 84.11 MiB </td>\n",
       "                        <td> 21.03 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (4, 2120, 2600) </td>\n",
       "                        <td> (4, 1060, 1300) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 4 chunks in 42 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"194\" height=\"162\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
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       "\n",
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       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"84.948598\" y=\"132.794752\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2600</text>\n",
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       "  <text x=\"7.474299\" y=\"125.320453\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,7.474299,125.320453)\">4</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude_longitude</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>-2147483647</div><input id='attrs-efe22ca6-1c3a-4ded-a299-aa664fe4093e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-efe22ca6-1c3a-4ded-a299-aa664fe4093e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6c0e034e-b78c-42f6-88a5-cc65b45ae66e' class='xr-var-data-in' type='checkbox'><label for='data-6c0e034e-b78c-42f6-88a5-cc65b45ae66e' 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>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>earth_radius :</span></dt><dd>6371229.0</dd></dl></div><div class='xr-var-data'><pre>array(-2147483647, dtype=int32)</pre></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-51a8aa19-f71e-411f-96e6-a1b1c7c175be' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-51a8aa19-f71e-411f-96e6-a1b1c7c175be' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5a915c4f-821c-4eb3-9ad2-9554cc2fbaf0' class='xr-var-data-in' type='checkbox'><label for='data-5a915c4f-821c-4eb3-9ad2-9554cc2fbaf0' 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",
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       "                        <td> (2120, 2) </td>\n",
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       "                        <th> Data type </th>\n",
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       "                        <td> 40.62 kiB </td>\n",
       "                        <td> 40.62 kiB </td>\n",
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       "                        <td> (2600, 2) </td>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 84.11 MiB </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>10.0</div><input id='attrs-9460a618-d174-4a89-964d-ba6ae815d8bf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9460a618-d174-4a89-964d-ba6ae815d8bf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aa760aee-a137-4c7b-8ec0-759a3794680e' class='xr-var-data-in' type='checkbox'><label for='data-aa760aee-a137-4c7b-8ec0-759a3794680e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>standard_name :</span></dt><dd>height</dd><dt><span>positive :</span></dt><dd>up</dd></dl></div><div class='xr-var-data'><pre>array(10.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fld_s03i210</span></div><div class='xr-var-dims'>(time_0, lat_0, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(4, 1061, 1300), meta=np.ndarray&gt;</div><input id='attrs-62ec024e-245e-41a8-97d4-4eda90d442d6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-62ec024e-245e-41a8-97d4-4eda90d442d6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a8321fbc-19bc-4d9c-8a8c-b8fdf6cf4890' class='xr-var-data-in' type='checkbox'><label for='data-a8321fbc-19bc-4d9c-8a8c-b8fdf6cf4890' 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>northward_wind</dd><dt><span>long_name :</span></dt><dd>10 METRE WIND V-COMP</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>um_stash_source :</span></dt><dd>m01s03i210</dd><dt><span>cell_methods :</span></dt><dd>time_0: mean</dd><dt><span>grid_mapping :</span></dt><dd>latitude_longitude</dd></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fld_s03i217</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=(4, 1060, 1300), meta=np.ndarray&gt;</div><input id='attrs-9f40de58-058c-484d-b75e-1bf21c03c918' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9f40de58-058c-484d-b75e-1bf21c03c918' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c0797553-99f3-4961-80a2-4f9f51f1519f' class='xr-var-data-in' type='checkbox'><label for='data-c0797553-99f3-4961-80a2-4f9f51f1519f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>surface_upward_sensible_heat_flux</dd><dt><span>long_name :</span></dt><dd>SURFACE SENSIBLE HEAT FLUX     W/M2</dd><dt><span>units :</span></dt><dd>W m-2</dd><dt><span>um_stash_source :</span></dt><dd>m01s03i217</dd><dt><span>grid_mapping :</span></dt><dd>latitude_longitude</dd></dl></div><div class='xr-var-data'><table>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>height_0</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.5</div><input id='attrs-d809d292-a7a0-442f-ad91-c36fd14908f3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d809d292-a7a0-442f-ad91-c36fd14908f3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-db018464-a8c9-4ec4-a4b2-675d3c52106d' class='xr-var-data-in' type='checkbox'><label for='data-db018464-a8c9-4ec4-a4b2-675d3c52106d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>standard_name :</span></dt><dd>height</dd><dt><span>positive :</span></dt><dd>up</dd></dl></div><div class='xr-var-data'><pre>array(1.5)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fld_s03i236</span></div><div class='xr-var-dims'>(time_0, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(4, 1060, 1300), meta=np.ndarray&gt;</div><input id='attrs-94f70b3d-8a1c-4241-8e31-4f8ddd1e63f9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-94f70b3d-8a1c-4241-8e31-4f8ddd1e63f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-410ed14a-c7f7-4a26-a081-58db3253a854' class='xr-var-data-in' type='checkbox'><label for='data-410ed14a-c7f7-4a26-a081-58db3253a854' 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>TEMPERATURE AT 1.5M</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>um_stash_source :</span></dt><dd>m01s03i236</dd><dt><span>cell_methods :</span></dt><dd>time_0: mean</dd><dt><span>grid_mapping :</span></dt><dd>latitude_longitude</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 84.11 MiB </td>\n",
       "                        <td> 21.03 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (4, 1060, 1300) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 4 chunks in 42 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fld_s03i236_max</span></div><div class='xr-var-dims'>(time_0, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(4, 1060, 1300), meta=np.ndarray&gt;</div><input id='attrs-d81e8d0d-e475-4b1c-b73c-d64ae59a2259' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d81e8d0d-e475-4b1c-b73c-d64ae59a2259' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-941be735-d9c8-4079-aa4b-4f917b636484' class='xr-var-data-in' type='checkbox'><label for='data-941be735-d9c8-4079-aa4b-4f917b636484' 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>TEMPERATURE AT 1.5M</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>um_stash_source :</span></dt><dd>m01s03i236</dd><dt><span>cell_methods :</span></dt><dd>time_0: maximum</dd><dt><span>grid_mapping :</span></dt><dd>latitude_longitude</dd></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
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       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 84.11 MiB </td>\n",
       "                        <td> 21.03 MiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 4 chunks in 42 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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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fld_s03i237</span></div><div class='xr-var-dims'>(time_0, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(4, 1060, 1300), meta=np.ndarray&gt;</div><input id='attrs-ab6f6e7b-5ebf-4d42-845a-f07c342e2978' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ab6f6e7b-5ebf-4d42-845a-f07c342e2978' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dd34a195-cb60-40fa-8cc9-3b0551644631' class='xr-var-data-in' type='checkbox'><label for='data-dd34a195-cb60-40fa-8cc9-3b0551644631' 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>specific_humidity</dd><dt><span>long_name :</span></dt><dd>SPECIFIC HUMIDITY  AT 1.5M</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>um_stash_source :</span></dt><dd>m01s03i237</dd><dt><span>cell_methods :</span></dt><dd>time_0: mean</dd><dt><span>grid_mapping :</span></dt><dd>latitude_longitude</dd></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fld_s03i247</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=(4, 1060, 1300), meta=np.ndarray&gt;</div><input id='attrs-265c1fa9-5fc3-40b9-9e81-3e0c7a190a09' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-265c1fa9-5fc3-40b9-9e81-3e0c7a190a09' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c96498d9-e597-4abd-88ed-76d231b4bfc6' class='xr-var-data-in' type='checkbox'><label for='data-c96498d9-e597-4abd-88ed-76d231b4bfc6' 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>visibility_in_air</dd><dt><span>long_name :</span></dt><dd>VISIBILITY AT 1.5M                 M</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>um_stash_source :</span></dt><dd>m01s03i247</dd><dt><span>grid_mapping :</span></dt><dd>latitude_longitude</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                        <th> Bytes </th>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 84.11 MiB </td>\n",
       "                        <td> 21.03 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (4, 2120, 2600) </td>\n",
       "                        <td> (4, 1060, 1300) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 4 chunks in 42 graph layers </td>\n",
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       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "                        <th> Dask graph </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fld_s03i283</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=(4, 1060, 1300), meta=np.ndarray&gt;</div><input id='attrs-b55eb870-824e-4fbf-abf3-751f52ffaf79' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b55eb870-824e-4fbf-abf3-751f52ffaf79' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-16bc53de-dd47-454e-ae96-b9070cd032a4' class='xr-var-data-in' type='checkbox'><label for='data-16bc53de-dd47-454e-ae96-b9070cd032a4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>PROB OF VIS &lt; 5 KM (incl precip)</dd><dt><span>um_stash_source :</span></dt><dd>m01s03i283</dd><dt><span>grid_mapping :</span></dt><dd>latitude_longitude</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 84.11 MiB </td>\n",
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       "                        <th> Shape </th>\n",
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       "                        <td> (4, 1060, 1300) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "                        <th> Bytes </th>\n",
       "                        <td> 84.11 MiB </td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fld_s16i222</span></div><div class='xr-var-dims'>(time_0, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(4, 1060, 1300), meta=np.ndarray&gt;</div><input id='attrs-88f419d3-0f99-46a1-b0f7-aa3e934786f0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-88f419d3-0f99-46a1-b0f7-aa3e934786f0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-89f714e2-51f5-41eb-8ffb-281342fdab05' class='xr-var-data-in' type='checkbox'><label for='data-89f714e2-51f5-41eb-8ffb-281342fdab05' 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_pressure_at_sea_level</dd><dt><span>long_name :</span></dt><dd>PRESSURE AT MEAN SEA LEVEL</dd><dt><span>units :</span></dt><dd>Pa</dd><dt><span>um_stash_source :</span></dt><dd>m01s16i222</dd><dt><span>cell_methods :</span></dt><dd>time_0: mean</dd><dt><span>grid_mapping :</span></dt><dd>latitude_longitude</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 84.11 MiB </td>\n",
       "                        <td> 21.03 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (4, 1060, 1300) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 4 chunks in 42 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-f6283eb1-b9a5-49e4-a27c-b69392446f50' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f6283eb1-b9a5-49e4-a27c-b69392446f50' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>fld_s03i209</span></div><div class='xr-var-dims'>(time_1, time, time_0, lat, lon_0)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 4, 4, 1060, 1300), meta=np.ndarray&gt;</div><input id='attrs-ef625c16-4bc8-4ce7-abdc-9a40d9f764a4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ef625c16-4bc8-4ce7-abdc-9a40d9f764a4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-21ed7868-baee-42d7-86fb-589ea3464eed' class='xr-var-data-in' type='checkbox'><label for='data-21ed7868-baee-42d7-86fb-589ea3464eed' 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>eastward_wind</dd><dt><span>long_name :</span></dt><dd>10 METRE WIND U-COMP</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>um_stash_source :</span></dt><dd>m01s03i209</dd><dt><span>cell_methods :</span></dt><dd>time_0: mean</dd><dt><span>grid_mapping :</span></dt><dd>latitude_longitude</dd></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",
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       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 1.31 GiB </td>\n",
       "                        <td> 84.11 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (4, 4, 4, 2120, 2600) </td>\n",
       "                        <td> (1, 4, 4, 1060, 1300) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 16 chunks in 65 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-2406b2b5-6b03-4f3a-8972-5e604fe39373' class='xr-section-summary-in' type='checkbox'  ><label for='section-2406b2b5-6b03-4f3a-8972-5e604fe39373' class='xr-section-summary' >Indexes: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-39170fbb-f6ac-4dad-975a-a7023f0f73cf' class='xr-index-data-in' type='checkbox'/><label for='index-39170fbb-f6ac-4dad-975a-a7023f0f73cf' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2016-06-05 21:00:00&#x27;, &#x27;2016-06-05 22:00:00&#x27;,\n",
       "               &#x27;2016-06-05 23:00:00&#x27;, &#x27;2016-06-06 00:00:00&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=&#x27;h&#x27;))</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-b82e89a3-a86c-4f1d-b7a4-e2d64a51d678' class='xr-index-data-in' type='checkbox'/><label for='index-b82e89a3-a86c-4f1d-b7a4-e2d64a51d678' 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-087cb39b-87c0-4654-a917-6f25e841aaed' class='xr-index-data-in' type='checkbox'/><label for='index-087cb39b-87c0-4654-a917-6f25e841aaed' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([114.26000213623047, 114.27980041503906, 114.29959869384766,\n",
       "       114.31940460205078, 114.33920288085938, 114.35900115966797,\n",
       "       114.37879943847656, 114.39860534667969, 114.41840362548828,\n",
       "       114.43820190429688,\n",
       "       ...\n",
       "       165.54200744628906, 165.56179809570312, 165.58160400390625,\n",
       "       165.60140991210938, 165.62120056152344, 165.64100646972656,\n",
       "       165.66079711914062, 165.68060302734375, 165.70040893554688,\n",
       "       165.72019958496094],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=2600))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time_0</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-6cd9f51d-9bef-40c0-8b2e-2dd74483abfe' class='xr-index-data-in' type='checkbox'/><label for='index-6cd9f51d-9bef-40c0-8b2e-2dd74483abfe' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2016-06-05 20:30:00&#x27;, &#x27;2016-06-05 21:30:00&#x27;,\n",
       "               &#x27;2016-06-05 22:30:00&#x27;, &#x27;2016-06-05 23:30:00&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time_0&#x27;, freq=&#x27;h&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon_0</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4837d461-ae51-4951-a4e9-5c0e8a2e3a88' class='xr-index-data-in' type='checkbox'/><label for='index-4837d461-ae51-4951-a4e9-5c0e8a2e3a88' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 114.2500991821289,  114.2698974609375,  114.2896957397461,\n",
       "       114.30950164794922, 114.32929992675781,  114.3490982055664,\n",
       "         114.368896484375, 114.38870239257812, 114.40850067138672,\n",
       "       114.42829895019531,\n",
       "       ...\n",
       "        165.5321044921875, 165.55189514160156,  165.5717010498047,\n",
       "       165.59149169921875, 165.61129760742188,   165.631103515625,\n",
       "       165.65089416503906,  165.6707000732422, 165.69049072265625,\n",
       "       165.71029663085938],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;lon_0&#x27;, length=2600))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat_0</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c38f32d6-258c-4ea0-bff4-70c84afb274a' class='xr-index-data-in' type='checkbox'/><label for='index-c38f32d6-258c-4ea0-bff4-70c84afb274a' 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([ -48.79790115356445,  -48.77810287475586,     -48.75830078125,\n",
       "       -48.738502502441406,  -48.71870040893555,  -48.69890213012695,\n",
       "       -48.679100036621094,   -48.6593017578125,  -48.63949966430664,\n",
       "        -48.61970138549805,\n",
       "       ...\n",
       "        -7.000102996826172, -6.9803009033203125,  -6.960502624511719,\n",
       "        -6.940700531005859,  -6.920902252197266,  -6.901100158691406,\n",
       "       -6.8813018798828125,  -6.861499786376953,  -6.841701507568359,\n",
       "        -6.821903228759766],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;lat_0&#x27;, length=2121))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>depth</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-2675e614-4beb-4a4d-8bbe-59656a1902b8' class='xr-index-data-in' type='checkbox'/><label for='index-2675e614-4beb-4a4d-8bbe-59656a1902b8' 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([0.05, 0.225, 0.675, 2.0], dtype=&#x27;float64&#x27;, name=&#x27;depth&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time_1</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-a2e606bd-1e41-4c9a-add7-e2e4653efd72' class='xr-index-data-in' type='checkbox'/><label for='index-a2e606bd-1e41-4c9a-add7-e2e4653efd72' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2016-06-05 20:01:14.999999744&#x27;,\n",
       "                         &#x27;2016-06-05 21:01:15&#x27;,\n",
       "                         &#x27;2016-06-05 22:01:15&#x27;,\n",
       "               &#x27;2016-06-05 23:01:14.999999744&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time_1&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0a3a656e-6cb6-4f04-9bc0-2dbaefbe4938' class='xr-section-summary-in' type='checkbox'  ><label for='section-0a3a656e-6cb6-4f04-9bc0-2dbaefbe4938' class='xr-section-summary' >Attributes: <span>(14)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>source :</span></dt><dd>Data from Met Office Unified Model</dd><dt><span>um_version :</span></dt><dd>12.2</dd><dt><span>intake_esm_vars :</span></dt><dd>[&#x27;fld_s03i209&#x27;]</dd><dt><span>intake_esm_attrs:experiment :</span></dt><dd>demo2</dd><dt><span>intake_esm_attrs:realm :</span></dt><dd>atmos</dd><dt><span>intake_esm_attrs:frequency :</span></dt><dd>1hr</dd><dt><span>intake_esm_attrs:variable :</span></dt><dd>fld_s03i209</dd><dt><span>intake_esm_attrs:mapvar :</span></dt><dd>uas</dd><dt><span>intake_esm_attrs:standard_name :</span></dt><dd>eastward_wind</dd><dt><span>intake_esm_attrs:units :</span></dt><dd>m s-1</dd><dt><span>intake_esm_attrs:cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>intake_esm_attrs:_data_format_ :</span></dt><dd>netcdf</dd><dt><span>intake_esm_dataset_key :</span></dt><dd>atmos.1hr.uas</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset> Size: 7GB\n",
       "Dimensions:             (time: 4, lat: 2120, lon: 2600, time_0: 4, lon_0: 2600,\n",
       "                         lat_0: 2121, depth: 4, time_1: 4, bnds: 2)\n",
       "Coordinates: (12/75)\n",
       "  * time                (time) datetime64[ns] 32B 2016-06-05T21:00:00 ... 201...\n",
       "  * lat                 (lat) float64 17kB -48.79 -48.77 ... -6.852 -6.832\n",
       "  * lon                 (lon) float64 21kB 114.3 114.3 114.3 ... 165.7 165.7\n",
       "  * time_0              (time_0) datetime64[ns] 32B 2016-06-05T20:30:00 ... 2...\n",
       "  * lon_0               (lon_0) float64 21kB 114.3 114.3 114.3 ... 165.7 165.7\n",
       "  * lat_0               (lat_0) float64 17kB -48.8 -48.78 ... -6.842 -6.822\n",
       "    ...                  ...\n",
       "    fld_s09i212         (time, lat, lon) float32 88MB dask.array<chunksize=(4, 1060, 1300), meta=np.ndarray>\n",
       "    fld_s09i213         (time, lat, lon) float32 88MB dask.array<chunksize=(4, 1060, 1300), meta=np.ndarray>\n",
       "    fld_s09i214         (time, lat, lon) float32 88MB dask.array<chunksize=(4, 1060, 1300), meta=np.ndarray>\n",
       "    fld_s09i215         (time, lat, lon) float32 88MB dask.array<chunksize=(4, 1060, 1300), meta=np.ndarray>\n",
       "    fld_s09i217         (time_0, lat, lon) float32 88MB dask.array<chunksize=(4, 1060, 1300), meta=np.ndarray>\n",
       "    fld_s16i222         (time_0, lat, lon) float32 88MB dask.array<chunksize=(4, 1060, 1300), meta=np.ndarray>\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    fld_s03i209         (time_1, time, time_0, lat, lon_0) float32 1GB dask.array<chunksize=(1, 4, 4, 1060, 1300), meta=np.ndarray>\n",
       "Attributes: (12/14)\n",
       "    Conventions:                     CF-1.6\n",
       "    source:                          Data from Met Office Unified Model\n",
       "    um_version:                      12.2\n",
       "    intake_esm_vars:                 ['fld_s03i209']\n",
       "    intake_esm_attrs:experiment:     demo2\n",
       "    intake_esm_attrs:realm:          atmos\n",
       "    ...                              ...\n",
       "    intake_esm_attrs:mapvar:         uas\n",
       "    intake_esm_attrs:standard_name:  eastward_wind\n",
       "    intake_esm_attrs:units:          m s-1\n",
       "    intake_esm_attrs:cell_methods:   area: time: mean\n",
       "    intake_esm_attrs:_data_format_:  netcdf\n",
       "    intake_esm_dataset_key:          atmos.1hr.uas"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dsets['atmos.1hr.uas']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8a841681-149e-4741-9988-a490b4cf879a",
   "metadata": {},
   "outputs": [],
   "source": [
    "subset = testrun.search(variable=['fld_s03i209','fld_s03i210'], frequency='1hr', date=r\"201606052.*\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5fb6a692-971a-412a-af69-3742e48c6790",
   "metadata": {},
   "source": [
    "Please note that what we got so far is not a very good result, intake-esm will try to sleect only the variables we passed however these don't exists in the dataset as we passed the mapped variables not the original names. We still selected the correct files but we need to tell intake-esm the right names. We can check the names in the mapping that was saved as the same time as the intake catalogues."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "975ecaf3-d8bc-41fc-89b7-905ac8094d7e",
   "metadata": {},
   "outputs": [],
   "source": [
    "from functools import partial"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f85dc2f7-b137-4f43-a859-e8138de88939",
   "metadata": {},
   "outputs": [],
   "source": [
    "def _preprocess(ds,varlist):\n",
    "    return ds[varlist]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0048b94b-b9cc-4a70-ba2f-ae40e65950b7",
   "metadata": {},
   "outputs": [],
   "source": [
    "selvar = partial(_preprocess, varlist=['fld_s03i209', 'fld_s03i210'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "dd005ef1-d6a0-43c4-a923-1c1b7eeb96cf",
   "metadata": {},
   "outputs": [],
   "source": [
    "dsets = subset.to_dataset_dict(preprocess=selvar)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "75a8a428-a80a-4ae0-a7e1-ef2829d037f6",
   "metadata": {},
   "outputs": [],
   "source": [
    "dsets['atmos.1hr']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f0d4e274-8a38-49e8-85da-2234daf237c9",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "dsets['ocean.mon.uo']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cd69a1ab-98e9-4d2c-bd49-c453915fea86",
   "metadata": {},
   "source": [
    "## Calculating derived variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "dbf4c8a9-e249-473c-b1b3-c6911a1b69d8",
   "metadata": {},
   "outputs": [],
   "source": [
    "We will now show ..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "dd80df5d-b938-49f6-af91-b7c1f45075dd",
   "metadata": {},
   "outputs": [],
   "source": [
    "from intake_esm import DerivedVariableRegistry"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "faaf4cf5-69f8-4dec-8bb4-d0802fd3ed7d",
   "metadata": {},
   "source": [
    "Initiate the `derived variable registry`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "35089870-2110-44db-80f6-6deb76a35954",
   "metadata": {},
   "outputs": [],
   "source": [
    "dvr = DerivedVariableRegistry()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "16e3dfe4-9ac4-4871-aab6-2ba6468fc1eb",
   "metadata": {},
   "source": [
    "Then we define a function to calculate wind_speed and use the register to decorate it"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1b3617b4-c959-4361-8831-57d974907307",
   "metadata": {},
   "outputs": [],
   "source": [
    "@dvr.register(variable='wind_speed', query={'map_var': ['uas', 'vas']})\n",
    "def calc_wind_speed(ds, uasname, vasname):\n",
    "    ds['wind_speed'] = np.sqrt(ds[uaname] ** 2 + ds[vaname] ** 2)\n",
    "    ds['wind_speed'].attrs = {'units': \"m s-1\",\n",
    "                              'long_name': \"Surface wind speed'\",\n",
    "                              'standard_name': \"wind_speed\",\n",
    "                              'comment': \"Derived using intake-esm from testrun experiment\"}\n",
    "    return ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0f8ea09f-4673-449e-ba69-427549d25e1b",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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