added-value.ipynb

{
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  {
   "cell_type": "markdown",
   "id": "7bcd125e-438e-466e-9773-d154209cb21f",
   "metadata": {},
   "source": [
    "# Notebook on Added Value\n",
    "This notebook will be used to show an example on how added value is calculated."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "14438d66-c9f7-49c2-8f74-06993ed59a97",
   "metadata": {},
   "outputs": [],
   "source": [
    "import lib\n",
    "from dask.distributed import Client,Scheduler,LocalCluster\n",
    "import xarray as xr\n",
    "import pandas as pd\n",
    "import cartopy.crs as ccrs\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "6ae6ecee-c244-4b54-9c45-87a08fbd64ed",
   "metadata": {},
   "outputs": [
    {
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       "    <div style=\"margin-left: 48px;\">\n",
       "        <h3 style=\"margin-bottom: 0px;\">Client</h3>\n",
       "        <p style=\"color: #9D9D9D; margin-bottom: 0px;\">Client-8f1c8db2-ed12-11ec-9354-0000070bfe80</p>\n",
       "        <table style=\"width: 100%; text-align: left;\">\n",
       "\n",
       "        <tr>\n",
       "        \n",
       "            <td style=\"text-align: left;\"><strong>Connection method:</strong> Cluster object</td>\n",
       "            <td style=\"text-align: left;\"><strong>Cluster type:</strong> distributed.LocalCluster</td>\n",
       "        \n",
       "        </tr>\n",
       "\n",
       "        \n",
       "            <tr>\n",
       "                <td style=\"text-align: left;\">\n",
       "                    <strong>Dashboard: </strong> <a href=\"/proxy/8787/status\" target=\"_blank\">/proxy/8787/status</a>\n",
       "                </td>\n",
       "                <td style=\"text-align: left;\"></td>\n",
       "            </tr>\n",
       "        \n",
       "\n",
       "        </table>\n",
       "\n",
       "        \n",
       "            <details>\n",
       "            <summary style=\"margin-bottom: 20px;\"><h3 style=\"display: inline;\">Cluster Info</h3></summary>\n",
       "            <div class=\"jp-RenderedHTMLCommon jp-RenderedHTML jp-mod-trusted jp-OutputArea-output\">\n",
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       "    </div>\n",
       "    <div style=\"margin-left: 48px;\">\n",
       "        <h3 style=\"margin-bottom: 0px; margin-top: 0px;\">LocalCluster</h3>\n",
       "        <p style=\"color: #9D9D9D; margin-bottom: 0px;\">d614753d</p>\n",
       "        <table style=\"width: 100%; text-align: left;\">\n",
       "            <tr>\n",
       "                <td style=\"text-align: left;\">\n",
       "                    <strong>Dashboard:</strong> <a href=\"/proxy/8787/status\" target=\"_blank\">/proxy/8787/status</a>\n",
       "                </td>\n",
       "                <td style=\"text-align: left;\">\n",
       "                    <strong>Workers:</strong> 4\n",
       "                </td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                <td style=\"text-align: left;\">\n",
       "                    <strong>Total threads:</strong> 8\n",
       "                </td>\n",
       "                <td style=\"text-align: left;\">\n",
       "                    <strong>Total memory:</strong> 64.00 GiB\n",
       "                </td>\n",
       "            </tr>\n",
       "            \n",
       "            <tr>\n",
       "    <td style=\"text-align: left;\"><strong>Status:</strong> running</td>\n",
       "    <td style=\"text-align: left;\"><strong>Using processes:</strong> True</td>\n",
       "</tr>\n",
       "\n",
       "            \n",
       "        </table>\n",
       "\n",
       "        <details>\n",
       "            <summary style=\"margin-bottom: 20px;\">\n",
       "                <h3 style=\"display: inline;\">Scheduler Info</h3>\n",
       "            </summary>\n",
       "\n",
       "            <div style=\"\">\n",
       "    <div>\n",
       "        <div style=\"width: 24px; height: 24px; background-color: #FFF7E5; border: 3px solid #FF6132; border-radius: 5px; position: absolute;\"> </div>\n",
       "        <div style=\"margin-left: 48px;\">\n",
       "            <h3 style=\"margin-bottom: 0px;\">Scheduler</h3>\n",
       "            <p style=\"color: #9D9D9D; margin-bottom: 0px;\">Scheduler-a5accc8a-198c-4cc8-9e77-a20f0eeb234f</p>\n",
       "            <table style=\"width: 100%; text-align: left;\">\n",
       "                <tr>\n",
       "                    <td style=\"text-align: left;\">\n",
       "                        <strong>Comm:</strong> tcp://127.0.0.1:37667\n",
       "                    </td>\n",
       "                    <td style=\"text-align: left;\">\n",
       "                        <strong>Workers:</strong> 4\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td style=\"text-align: left;\">\n",
       "                        <strong>Dashboard:</strong> <a href=\"/proxy/8787/status\" target=\"_blank\">/proxy/8787/status</a>\n",
       "                    </td>\n",
       "                    <td style=\"text-align: left;\">\n",
       "                        <strong>Total threads:</strong> 8\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td style=\"text-align: left;\">\n",
       "                        <strong>Started:</strong> Just now\n",
       "                    </td>\n",
       "                    <td style=\"text-align: left;\">\n",
       "                        <strong>Total memory:</strong> 64.00 GiB\n",
       "                    </td>\n",
       "                </tr>\n",
       "            </table>\n",
       "        </div>\n",
       "    </div>\n",
       "\n",
       "    <details style=\"margin-left: 48px;\">\n",
       "        <summary style=\"margin-bottom: 20px;\">\n",
       "            <h3 style=\"display: inline;\">Workers</h3>\n",
       "        </summary>\n",
       "\n",
       "        \n",
       "        <div style=\"margin-bottom: 20px;\">\n",
       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
       "            <div style=\"margin-left: 48px;\">\n",
       "            <details>\n",
       "                <summary>\n",
       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 0</h4>\n",
       "                </summary>\n",
       "                <table style=\"width: 100%; text-align: left;\">\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Comm: </strong> tcp://127.0.0.1:43705\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Total threads: </strong> 2\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Dashboard: </strong> <a href=\"/proxy/41591/status\" target=\"_blank\">/proxy/41591/status</a>\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Memory: </strong> 16.00 GiB\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Nanny: </strong> tcp://127.0.0.1:35247\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/44227604.gadi-pbs/dask-worker-space/worker-zv991wmo\n",
       "                        </td>\n",
       "                    </tr>\n",
       "\n",
       "                    \n",
       "\n",
       "                    \n",
       "\n",
       "                </table>\n",
       "            </details>\n",
       "            </div>\n",
       "        </div>\n",
       "        \n",
       "        <div style=\"margin-bottom: 20px;\">\n",
       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
       "            <div style=\"margin-left: 48px;\">\n",
       "            <details>\n",
       "                <summary>\n",
       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 1</h4>\n",
       "                </summary>\n",
       "                <table style=\"width: 100%; text-align: left;\">\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Comm: </strong> tcp://127.0.0.1:40251\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Total threads: </strong> 2\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Dashboard: </strong> <a href=\"/proxy/42245/status\" target=\"_blank\">/proxy/42245/status</a>\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Memory: </strong> 16.00 GiB\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Nanny: </strong> tcp://127.0.0.1:45407\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/44227604.gadi-pbs/dask-worker-space/worker-vscq1ayp\n",
       "                        </td>\n",
       "                    </tr>\n",
       "\n",
       "                    \n",
       "\n",
       "                    \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: 2</h4>\n",
       "                </summary>\n",
       "                <table style=\"width: 100%; text-align: left;\">\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Comm: </strong> tcp://127.0.0.1:37751\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Total threads: </strong> 2\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Dashboard: </strong> <a href=\"/proxy/33233/status\" target=\"_blank\">/proxy/33233/status</a>\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Memory: </strong> 16.00 GiB\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Nanny: </strong> tcp://127.0.0.1:42599\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/44227604.gadi-pbs/dask-worker-space/worker-gq2lvwvu\n",
       "                        </td>\n",
       "                    </tr>\n",
       "\n",
       "                    \n",
       "\n",
       "                    \n",
       "\n",
       "                </table>\n",
       "            </details>\n",
       "            </div>\n",
       "        </div>\n",
       "        \n",
       "        <div style=\"margin-bottom: 20px;\">\n",
       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
       "            <div style=\"margin-left: 48px;\">\n",
       "            <details>\n",
       "                <summary>\n",
       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 3</h4>\n",
       "                </summary>\n",
       "                <table style=\"width: 100%; text-align: left;\">\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Comm: </strong> tcp://127.0.0.1:39923\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Total threads: </strong> 2\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Dashboard: </strong> <a href=\"/proxy/37323/status\" target=\"_blank\">/proxy/37323/status</a>\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Memory: </strong> 16.00 GiB\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Nanny: </strong> tcp://127.0.0.1:39557\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/44227604.gadi-pbs/dask-worker-space/worker-zfynec34\n",
       "                        </td>\n",
       "                    </tr>\n",
       "\n",
       "                    \n",
       "\n",
       "                    \n",
       "\n",
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       "        \n",
       "\n",
       "    </details>\n",
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       "\n",
       "        </details>\n",
       "    </div>\n",
       "</div>\n",
       "            </details>\n",
       "        \n",
       "\n",
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      ],
      "text/plain": [
       "<Client: 'tcp://127.0.0.1:37667' processes=4 threads=8, memory=64.00 GiB>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cluster = LocalCluster()\n",
    "client = Client(cluster)\n",
    "client"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "026d78ae-28a8-4509-87b8-ac63a91245b7",
   "metadata": {},
   "source": [
    "Open the global driving model (gcm) data, the regional climate model (rcm) data, and reference data (observations)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "42adb30f-7f7d-4a5e-9861-2511b18a2089",
   "metadata": {},
   "outputs": [],
   "source": [
    "# ds_gcm = lib.open_dataset(\"/g/data/fs38/publications/CMIP6/CMIP/CSIRO-ARCCSS/ACCESS-CM2/historical/r4i1p1f1/day/tasmax/gn/v20210607/tasmax_day_ACCESS-CM2_historical_r4i1p1f1_gn_*-*.nc\")\n",
    "# ds_rcm = lib.open_dataset(\"/g/data/ia39/australian-climate-service/test-data/CORDEX-CMIP6/output/AUS-17i/BOM/CSIRO-BOM-ACCESS-CM2/historical/r4i1p1f1/BOM-BARPA-R/v1/day/tasmax/*.nc\")\n",
    "# ds_obs = lib.open_dataset(\"/g/data/xv83/agcd-csiro/tmax/daily/tmax_AGCD-CSIRO_r005_*-*_daily.nc\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "6b9adb8c-57ed-4e9a-a31b-7615a38ca9bf",
   "metadata": {},
   "outputs": [],
   "source": [
    "# ds_gcm = lib.open_dataset(\"/g/data/fs38/publications/CMIP6/CMIP/CSIRO-ARCCSS/ACCESS-CM2/historical/r4i1p1f1/day/tasmin/gn/v20210607/tasmin_day_ACCESS-CM2_historical_r4i1p1f1_gn_*-*.nc\")\n",
    "# ds_rcm = lib.open_dataset(\"/g/data/ia39/australian-climate-service/test-data/CORDEX-CMIP6/output/AUS-17i/BOM/CSIRO-BOM-ACCESS-CM2/historical/r4i1p1f1/BOM-BARPA-R/v1/day/tasmin/*.nc\")\n",
    "# ds_obs = lib.open_dataset(\"/g/data/xv83/agcd-csiro/tmin/daily/tmin_AGCD-CSIRO_r005_*-*_daily.nc\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "de43da64-9d9f-49b2-8b82-d35cd7f267dc",
   "metadata": {},
   "outputs": [],
   "source": [
    "ds_gcm = lib.open_dataset(\"/g/data/fs38/publications/CMIP6/CMIP/CSIRO-ARCCSS/ACCESS-CM2/historical/r4i1p1f1/day/pr/gn/latest/pr_day_ACCESS-CM2_historical_r4i1p1f1_gn_*-*.nc\")\n",
    "ds_rcm = lib.open_dataset(\"/g/data/ia39/australian-climate-service/test-data/CORDEX-CMIP6/output/AUS-17i/BOM/CSIRO-BOM-ACCESS-CM2/historical/r4i1p1f1/BOM-BARPA-R/v1/day/pr/*.nc\")\n",
    "ds_obs = lib.open_dataset(\"/g/data/xv83/agcd-csiro/precip/daily/precip-total_AGCD-CSIRO_r005_*-*_daily.nc\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a32bbe2f-1c00-4778-9ec3-8c43deb7ff71",
   "metadata": {},
   "source": [
    "Let's have a look at the files that were opened.\n",
    "\n",
    "The gcm data looks like:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "fae2c7b4-a493-4558-8964-191bac0404d1",
   "metadata": {},
   "outputs": [
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       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:    (time: 60265, bnds: 2, lat: 144, lon: 192)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1850-01-01T12:00:00 ... 2014-12-31T12:00:00\n",
       "  * lat        (lat) float64 -89.38 -88.12 -86.88 -85.62 ... 86.88 88.12 89.38\n",
       "  * lon        (lon) float64 0.9375 2.812 4.688 6.562 ... 355.3 357.2 359.1\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) datetime64[ns] dask.array&lt;chunksize=(18262, 2), meta=np.ndarray&gt;\n",
       "    lat_bnds   (lat, bnds) float64 dask.array&lt;chunksize=(144, 2), meta=np.ndarray&gt;\n",
       "    lon_bnds   (lon, bnds) float64 dask.array&lt;chunksize=(192, 2), meta=np.ndarray&gt;\n",
       "    pr         (time, lat, lon) float32 dask.array&lt;chunksize=(18262, 144, 192), meta=np.ndarray&gt;\n",
       "Attributes: (12/47)\n",
       "    Conventions:            CF-1.7 CMIP-6.2\n",
       "    activity_id:            CMIP\n",
       "    branch_method:          standard\n",
       "    branch_time_in_child:   0.0\n",
       "    branch_time_in_parent:  54786.0\n",
       "    creation_date:          2021-06-07T05:50:06Z\n",
       "    ...                     ...\n",
       "    variable_id:            pr\n",
       "    variant_label:          r4i1p1f1\n",
       "    version:                v20210607\n",
       "    license:                CMIP6 model data produced by CSIRO is licensed un...\n",
       "    cmor_version:           3.4.0\n",
       "    tracking_id:            hdl:21.14100/fc9b337e-2ee3-407a-a222-f1ee62caeda6</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-728f27ab-6d30-4163-bf01-abdf8291e4a1' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-728f27ab-6d30-4163-bf01-abdf8291e4a1' 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>: 60265</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lat</span>: 144</li><li><span class='xr-has-index'>lon</span>: 192</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-973fb5ea-f403-4fc5-a023-4ebcdff8ae81' class='xr-section-summary-in' type='checkbox'  checked><label for='section-973fb5ea-f403-4fc5-a023-4ebcdff8ae81' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>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'>1850-01-01T12:00:00 ... 2014-12-...</div><input id='attrs-d5a2d419-ee02-430f-add6-f908b4c728e0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d5a2d419-ee02-430f-add6-f908b4c728e0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fbe10a95-ce59-4de8-963e-57f85f79793f' class='xr-var-data-in' type='checkbox'><label for='data-fbe10a95-ce59-4de8-963e-57f85f79793f' 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;1850-01-01T12:00:00.000000000&#x27;, &#x27;1850-01-02T12:00:00.000000000&#x27;,\n",
       "       &#x27;1850-01-03T12:00:00.000000000&#x27;, ..., &#x27;2014-12-29T12:00:00.000000000&#x27;,\n",
       "       &#x27;2014-12-30T12:00:00.000000000&#x27;, &#x27;2014-12-31T12:00:00.000000000&#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'>-89.38 -88.12 ... 88.12 89.38</div><input id='attrs-b1193e94-2f7e-437d-88c7-8f34af994076' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b1193e94-2f7e-437d-88c7-8f34af994076' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a4d540e7-7be1-4968-ab91-309d41443819' class='xr-var-data-in' type='checkbox'><label for='data-a4d540e7-7be1-4968-ab91-309d41443819' 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([-89.375, -88.125, -86.875, -85.625, -84.375, -83.125, -81.875, -80.625,\n",
       "       -79.375, -78.125, -76.875, -75.625, -74.375, -73.125, -71.875, -70.625,\n",
       "       -69.375, -68.125, -66.875, -65.625, -64.375, -63.125, -61.875, -60.625,\n",
       "       -59.375, -58.125, -56.875, -55.625, -54.375, -53.125, -51.875, -50.625,\n",
       "       -49.375, -48.125, -46.875, -45.625, -44.375, -43.125, -41.875, -40.625,\n",
       "       -39.375, -38.125, -36.875, -35.625, -34.375, -33.125, -31.875, -30.625,\n",
       "       -29.375, -28.125, -26.875, -25.625, -24.375, -23.125, -21.875, -20.625,\n",
       "       -19.375, -18.125, -16.875, -15.625, -14.375, -13.125, -11.875, -10.625,\n",
       "        -9.375,  -8.125,  -6.875,  -5.625,  -4.375,  -3.125,  -1.875,  -0.625,\n",
       "         0.625,   1.875,   3.125,   4.375,   5.625,   6.875,   8.125,   9.375,\n",
       "        10.625,  11.875,  13.125,  14.375,  15.625,  16.875,  18.125,  19.375,\n",
       "        20.625,  21.875,  23.125,  24.375,  25.625,  26.875,  28.125,  29.375,\n",
       "        30.625,  31.875,  33.125,  34.375,  35.625,  36.875,  38.125,  39.375,\n",
       "        40.625,  41.875,  43.125,  44.375,  45.625,  46.875,  48.125,  49.375,\n",
       "        50.625,  51.875,  53.125,  54.375,  55.625,  56.875,  58.125,  59.375,\n",
       "        60.625,  61.875,  63.125,  64.375,  65.625,  66.875,  68.125,  69.375,\n",
       "        70.625,  71.875,  73.125,  74.375,  75.625,  76.875,  78.125,  79.375,\n",
       "        80.625,  81.875,  83.125,  84.375,  85.625,  86.875,  88.125,  89.375])</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'>0.9375 2.812 4.688 ... 357.2 359.1</div><input id='attrs-6374d34c-de31-4025-b29b-782262eda0c9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6374d34c-de31-4025-b29b-782262eda0c9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c8803437-72e4-49c3-aa8a-7ec050e3ddd9' class='xr-var-data-in' type='checkbox'><label for='data-c8803437-72e4-49c3-aa8a-7ec050e3ddd9' 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([  0.9375,   2.8125,   4.6875,   6.5625,   8.4375,  10.3125,  12.1875,\n",
       "        14.0625,  15.9375,  17.8125,  19.6875,  21.5625,  23.4375,  25.3125,\n",
       "        27.1875,  29.0625,  30.9375,  32.8125,  34.6875,  36.5625,  38.4375,\n",
       "        40.3125,  42.1875,  44.0625,  45.9375,  47.8125,  49.6875,  51.5625,\n",
       "        53.4375,  55.3125,  57.1875,  59.0625,  60.9375,  62.8125,  64.6875,\n",
       "        66.5625,  68.4375,  70.3125,  72.1875,  74.0625,  75.9375,  77.8125,\n",
       "        79.6875,  81.5625,  83.4375,  85.3125,  87.1875,  89.0625,  90.9375,\n",
       "        92.8125,  94.6875,  96.5625,  98.4375, 100.3125, 102.1875, 104.0625,\n",
       "       105.9375, 107.8125, 109.6875, 111.5625, 113.4375, 115.3125, 117.1875,\n",
       "       119.0625, 120.9375, 122.8125, 124.6875, 126.5625, 128.4375, 130.3125,\n",
       "       132.1875, 134.0625, 135.9375, 137.8125, 139.6875, 141.5625, 143.4375,\n",
       "       145.3125, 147.1875, 149.0625, 150.9375, 152.8125, 154.6875, 156.5625,\n",
       "       158.4375, 160.3125, 162.1875, 164.0625, 165.9375, 167.8125, 169.6875,\n",
       "       171.5625, 173.4375, 175.3125, 177.1875, 179.0625, 180.9375, 182.8125,\n",
       "       184.6875, 186.5625, 188.4375, 190.3125, 192.1875, 194.0625, 195.9375,\n",
       "       197.8125, 199.6875, 201.5625, 203.4375, 205.3125, 207.1875, 209.0625,\n",
       "       210.9375, 212.8125, 214.6875, 216.5625, 218.4375, 220.3125, 222.1875,\n",
       "       224.0625, 225.9375, 227.8125, 229.6875, 231.5625, 233.4375, 235.3125,\n",
       "       237.1875, 239.0625, 240.9375, 242.8125, 244.6875, 246.5625, 248.4375,\n",
       "       250.3125, 252.1875, 254.0625, 255.9375, 257.8125, 259.6875, 261.5625,\n",
       "       263.4375, 265.3125, 267.1875, 269.0625, 270.9375, 272.8125, 274.6875,\n",
       "       276.5625, 278.4375, 280.3125, 282.1875, 284.0625, 285.9375, 287.8125,\n",
       "       289.6875, 291.5625, 293.4375, 295.3125, 297.1875, 299.0625, 300.9375,\n",
       "       302.8125, 304.6875, 306.5625, 308.4375, 310.3125, 312.1875, 314.0625,\n",
       "       315.9375, 317.8125, 319.6875, 321.5625, 323.4375, 325.3125, 327.1875,\n",
       "       329.0625, 330.9375, 332.8125, 334.6875, 336.5625, 338.4375, 340.3125,\n",
       "       342.1875, 344.0625, 345.9375, 347.8125, 349.6875, 351.5625, 353.4375,\n",
       "       355.3125, 357.1875, 359.0625])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-13b60cc2-e7b5-4c73-bde3-78537a18deee' class='xr-section-summary-in' type='checkbox'  checked><label for='section-13b60cc2-e7b5-4c73-bde3-78537a18deee' 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=(18262, 2), meta=np.ndarray&gt;</div><input id='attrs-047bbfa5-144b-45e9-96f5-81ac8b56fcd7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-047bbfa5-144b-45e9-96f5-81ac8b56fcd7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f9928ccd-0700-4ceb-aa99-b31f85daf6a5' class='xr-var-data-in' type='checkbox'><label for='data-f9928ccd-0700-4ceb-aa99-b31f85daf6a5' 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>\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> 0.92 MiB </td>\n",
       "                        <td> 285.34 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (60265, 2) </td>\n",
       "                        <td> (18262, 2) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 12 Tasks </td>\n",
       "                        <td> 4 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> datetime64[ns] </td>\n",
       "                    <td> numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
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       "        </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=(144, 2), meta=np.ndarray&gt;</div><input id='attrs-4f79a8c3-cb96-43ce-beee-787b1e3a4362' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4f79a8c3-cb96-43ce-beee-787b1e3a4362' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-903abf74-0d0f-4722-8f86-41af27dd3cdf' class='xr-var-data-in' type='checkbox'><label for='data-903abf74-0d0f-4722-8f86-41af27dd3cdf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
       "            <table>\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> 2.25 kiB </td>\n",
       "                        <td> 2.25 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (144, 2) </td>\n",
       "                        <td> (144, 2) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 2 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float64 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
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       "    </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=(192, 2), meta=np.ndarray&gt;</div><input id='attrs-3587ac43-859d-4dfa-8f46-a8e9d181e2a8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3587ac43-859d-4dfa-8f46-a8e9d181e2a8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dc23ae7b-38e0-4046-9ed5-5f2bbe48cbdc' class='xr-var-data-in' type='checkbox'><label for='data-dc23ae7b-38e0-4046-9ed5-5f2bbe48cbdc' 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>\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> 3.00 kiB </td>\n",
       "                        <td> 3.00 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (192, 2) </td>\n",
       "                        <td> (192, 2) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 2 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float64 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pr</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=(18262, 144, 192), meta=np.ndarray&gt;</div><input id='attrs-9d2335e0-5ab2-4258-8a08-24ef16ad5be3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9d2335e0-5ab2-4258-8a08-24ef16ad5be3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-10cc4230-33da-4f61-8158-921d45c93ce4' class='xr-var-data-in' type='checkbox'><label for='data-10cc4230-33da-4f61-8158-921d45c93ce4' 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>precipitation_flux</dd><dt><span>long_name :</span></dt><dd>Precipitation</dd><dt><span>comment :</span></dt><dd>includes both liquid and solid phases</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>cell_measures :</span></dt><dd>area: areacella</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 6.21 GiB </td>\n",
       "                        <td> 1.88 GiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (60265, 144, 192) </td>\n",
       "                        <td> (18262, 144, 192) </td>\n",
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       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 12 Tasks </td>\n",
       "                        <td> 4 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float32 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
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       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-1bfcc335-4130-4719-acf4-1c7b6752f867' class='xr-section-summary-in' type='checkbox'  ><label for='section-1bfcc335-4130-4719-acf4-1c7b6752f867' class='xr-section-summary' >Attributes: <span>(47)</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 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>branch_time_in_child :</span></dt><dd>0.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>54786.0</dd><dt><span>creation_date :</span></dt><dd>2021-06-07T05:50:06Z</dd><dt><span>data_specs_version :</span></dt><dd>01.00.30</dd><dt><span>experiment :</span></dt><dd>all-forcing simulation of the recent past</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>external_variables :</span></dt><dd>areacella</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>day</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.CSIRO-ARCCSS.ACCESS-CM2.historical.none.r4i1p1f1</dd><dt><span>grid :</span></dt><dd>native atmosphere N96 grid (144x192 latxlon)</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>history :</span></dt><dd>2021-06-07T05:50:06Z ; CMOR rewrote data to be consistent with CMIP6, CF-1.7 CMIP-6.2 and CF standards.</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>CSIRO (Commonwealth Scientific and Industrial Research Organisation, Aspendale, Victoria 3195, Australia), ARCCSS (Australian Research Council Centre of Excellence for Climate System Science)</dd><dt><span>institution_id :</span></dt><dd>CSIRO-ARCCSS</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>nominal_resolution :</span></dt><dd>250 km</dd><dt><span>notes :</span></dt><dd>Exp: CM2-historical; Local ID: cd659; Variable: pr ([&#x27;fld_s05i216&#x27;])</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>ACCESS-CM2</dd><dt><span>parent_time_units :</span></dt><dd>days since 0950-01-01</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>4</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>run_variant :</span></dt><dd>forcing: GHG, Oz, SA, Sl, Vl, BC, OC, (GHG = CO2, N2O, CH4, CFC11, CFC12, CFC113, HCFC22, HFC125, HFC134a)</dd><dt><span>source :</span></dt><dd>ACCESS-CM2 (2019): \n",
       "aerosol: UKCA-GLOMAP-mode\n",
       "atmos: MetUM-HadGEM3-GA7.1 (N96; 192 x 144 longitude/latitude; 85 levels; top level 85 km)\n",
       "atmosChem: none\n",
       "land: CABLE2.5\n",
       "landIce: none\n",
       "ocean: ACCESS-OM2 (GFDL-MOM5, tripolar primarily 1deg; 360 x 300 longitude/latitude; 50 levels; top grid cell 0-10 m)\n",
       "ocnBgchem: none\n",
       "seaIce: CICE5.1.2 (same grid as ocean)</dd><dt><span>source_id :</span></dt><dd>ACCESS-CM2</dd><dt><span>source_type :</span></dt><dd>AOGCM</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>table_id :</span></dt><dd>day</dd><dt><span>table_info :</span></dt><dd>Creation Date:(30 April 2019) MD5:12ec21eb48eb992c2e353382c1c903b1</dd><dt><span>title :</span></dt><dd>ACCESS-CM2 output prepared for CMIP6</dd><dt><span>variable_id :</span></dt><dd>pr</dd><dt><span>variant_label :</span></dt><dd>r4i1p1f1</dd><dt><span>version :</span></dt><dd>v20210607</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by CSIRO is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License (https://creativecommons.org/licenses/). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment.  Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file). The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>cmor_version :</span></dt><dd>3.4.0</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/fc9b337e-2ee3-407a-a222-f1ee62caeda6</dd></dl></div></li></ul></div></div>"
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       "<xarray.Dataset>\n",
       "Dimensions:    (time: 60265, bnds: 2, lat: 144, lon: 192)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1850-01-01T12:00:00 ... 2014-12-31T12:00:00\n",
       "  * lat        (lat) float64 -89.38 -88.12 -86.88 -85.62 ... 86.88 88.12 89.38\n",
       "  * lon        (lon) float64 0.9375 2.812 4.688 6.562 ... 355.3 357.2 359.1\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) datetime64[ns] dask.array<chunksize=(18262, 2), meta=np.ndarray>\n",
       "    lat_bnds   (lat, bnds) float64 dask.array<chunksize=(144, 2), meta=np.ndarray>\n",
       "    lon_bnds   (lon, bnds) float64 dask.array<chunksize=(192, 2), meta=np.ndarray>\n",
       "    pr         (time, lat, lon) float32 dask.array<chunksize=(18262, 144, 192), meta=np.ndarray>\n",
       "Attributes: (12/47)\n",
       "    Conventions:            CF-1.7 CMIP-6.2\n",
       "    activity_id:            CMIP\n",
       "    branch_method:          standard\n",
       "    branch_time_in_child:   0.0\n",
       "    branch_time_in_parent:  54786.0\n",
       "    creation_date:          2021-06-07T05:50:06Z\n",
       "    ...                     ...\n",
       "    variable_id:            pr\n",
       "    variant_label:          r4i1p1f1\n",
       "    version:                v20210607\n",
       "    license:                CMIP6 model data produced by CSIRO is licensed un...\n",
       "    cmor_version:           3.4.0\n",
       "    tracking_id:            hdl:21.14100/fc9b337e-2ee3-407a-a222-f1ee62caeda6"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_gcm"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "273b300c-e58e-4203-a865-812e6dc101b0",
   "metadata": {},
   "source": [
    "The rcm data looks like:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "09fb46f0-02e2-4415-bbba-54aee27e5973",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:    (time: 6575, lat: 427, lon: 767, bnds: 2)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1960-01-01 1960-01-02 ... 1977-12-31\n",
       "  * lat        (lat) float64 -53.11 -52.96 -52.8 -52.65 ... 12.4 12.55 12.7\n",
       "  * lon        (lon) float64 88.81 88.96 89.12 89.27 ... 206.7 206.8 207.0 207.2\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    pr         (time, lat, lon) float32 dask.array&lt;chunksize=(366, 427, 767), meta=np.ndarray&gt;\n",
       "    time_bnds  (time, bnds) datetime64[ns] dask.array&lt;chunksize=(366, 2), meta=np.ndarray&gt;\n",
       "Attributes: (12/56)\n",
       "    axiom_version:                  0.1.0\n",
       "    axiom_schemas_version:          0.1.0\n",
       "    axiom_schema:                   cordex-1D.json\n",
       "    productive_version:             v1\n",
       "    Conventions:                    CF-1.9, ACDD-1.3\n",
       "    title:                          Bureau of Meteorology Atmospheric Regiona...\n",
       "    ...                             ...\n",
       "    frequency:                      day\n",
       "    tracking_id:                    6e0a37b5-e965-4e49-a419-21e9f572a813\n",
       "    date_created:                   2022-06-15T06:50:13Z\n",
       "    date_modified:                  2022-06-15T06:50:13Z\n",
       "    date_metadata_modified:         2022-06-15T06:50:13Z\n",
       "    history:                        Wed Jun 15 16:49:47 2022: /g/data/access/...</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-92b18c19-a14f-4f35-aab3-584e0e3cfcb3' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-92b18c19-a14f-4f35-aab3-584e0e3cfcb3' 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>: 6575</li><li><span class='xr-has-index'>lat</span>: 427</li><li><span class='xr-has-index'>lon</span>: 767</li><li><span>bnds</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-00b13f95-14fc-4b63-8d51-0d6ca34fc2c9' class='xr-section-summary-in' type='checkbox'  checked><label for='section-00b13f95-14fc-4b63-8d51-0d6ca34fc2c9' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>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'>1960-01-01 ... 1977-12-31</div><input id='attrs-31e4697b-ba49-412b-8c7e-a771daa0c74d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-31e4697b-ba49-412b-8c7e-a771daa0c74d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c17760cc-284a-4ce0-9143-6f64d04d8604' class='xr-var-data-in' type='checkbox'><label for='data-c17760cc-284a-4ce0-9143-6f64d04d8604' 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><dt><span>long_name :</span></dt><dd>time</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1960-01-01T00:00:00.000000000&#x27;, &#x27;1960-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;1960-01-03T00:00:00.000000000&#x27;, ..., &#x27;1977-12-29T00:00:00.000000000&#x27;,\n",
       "       &#x27;1977-12-30T00:00:00.000000000&#x27;, &#x27;1977-12-31T00:00:00.000000000&#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'>-53.11 -52.96 -52.8 ... 12.55 12.7</div><input id='attrs-6cfe9330-1ae9-47a8-819c-05a727fd6730' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6cfe9330-1ae9-47a8-819c-05a727fd6730' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-012b37c9-5453-4a21-8adf-39f271dad4bb' class='xr-var-data-in' type='checkbox'><label for='data-012b37c9-5453-4a21-8adf-39f271dad4bb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-53.112  , -52.9575 , -52.803  , ...,  12.396  ,  12.5505 ,  12.70499])</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'>88.81 88.96 89.12 ... 207.0 207.2</div><input id='attrs-020190c7-4764-4880-a3e2-5dd631d2b468' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-020190c7-4764-4880-a3e2-5dd631d2b468' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6873a8e3-302d-4a6c-8666-dbcb7bc40547' class='xr-var-data-in' type='checkbox'><label for='data-6873a8e3-302d-4a6c-8666-dbcb7bc40547' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([ 88.808  ,  88.9625 ,  89.117  , ..., 206.84599, 207.00049, 207.155  ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0b3f5087-4990-407e-b00d-78e31d339399' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0b3f5087-4990-407e-b00d-78e31d339399' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>pr</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=(366, 427, 767), meta=np.ndarray&gt;</div><input id='attrs-26494d83-0d7a-4820-a79e-89fae8d4cc04' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-26494d83-0d7a-4820-a79e-89fae8d4cc04' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-172bbb8f-67ae-4537-b703-47c1df25ff90' class='xr-var-data-in' type='checkbox'><label for='data-172bbb8f-67ae-4537-b703-47c1df25ff90' 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>Precipitation</dd><dt><span>standard_name :</span></dt><dd>precipitation_flux</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>cell_methods :</span></dt><dd>time: mean (interval: 1 hour) time: mean (interval: 1D)</dd></dl></div><div class='xr-var-data'><table>\n",
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GCMD Keywords, Version 13.6 Greenbelt, MD: Earth Science Data and Information System, Earth Science Projects Division, Goddard Space Flight Center (GSFC) National Aeronautics and Space Administration (NASA). URL (GCMD Keyword Forum Page): https://forum.earthdata.nasa.gov/app.php/tag/GCMD+Keywords</dd><dt><span>frequency :</span></dt><dd>day</dd><dt><span>tracking_id :</span></dt><dd>6e0a37b5-e965-4e49-a419-21e9f572a813</dd><dt><span>date_created :</span></dt><dd>2022-06-15T06:50:13Z</dd><dt><span>date_modified :</span></dt><dd>2022-06-15T06:50:13Z</dd><dt><span>date_metadata_modified :</span></dt><dd>2022-06-15T06:50:13Z</dd><dt><span>history :</span></dt><dd>Wed Jun 15 16:49:47 2022: /g/data/access/ngm/miniconda3/envs/analysis3-21.10/bin/python /home/565/cst565/cylc-run/pp_BARPA-R_ACCESS-CM2_historical/run1/bin/master_postproc.py --start_year 1960 --end_year 1960 --config_files /home/565/cst565/cylc-run/pp_BARPA-R_ACCESS-CM2_historical/run1/share/config_files/config_file_BARPA-R.json /home/565/cst565/cylc-run/pp_BARPA-R_ACCESS-CM2_historical/run1/share/config_files/config_file_historical.json /home/565/cst565/cylc-run/pp_BARPA-R_ACCESS-CM2_historical/run1/share/config_files/config_file_ACCESS-CM2.json /home/565/cst565/cylc-run/pp_BARPA-R_ACCESS-CM2_historical/run1/share/config_files/config_file_pr_1Dm.json /home/565/cst565/cylc-run/pp_BARPA-R_ACCESS-CM2_historical/run1/share/config_files/config_file_publisher_info.json /home/565/cst565/cylc-run/pp_BARPA-R_ACCESS-CM2_historical/run1/share/config_files/config_file_misc.json /home/565/cst565/cylc-run/pp_BARPA-R_ACCESS-CM2_historical/run1/share/config_files/config_file_license.json --kwargs {} --cleanup True --n_workers 9 --n_threads 1\n",
       "Tue May 31 02:06:53 2022: /g/data3/hh5/public/apps/miniconda3/envs/analysis3-22.01/bin/python /home/548/eh6215/cylc-run/cg282_ACCESS-CM2_historical_1960_sciB/bin/convert2nc.py --ifiles_template /home/548/eh6215/cylc-run/cg282_ACCESS-CM2_historical_1960_sciB/share/cycle/19601101T0000Z/um/barpara_slv1h_{:%Y%m%d_%H} --current_cycle 19601101T0000Z --cycle_freq P1M --stream_freq 6H --stashcodes --n_threads 1 --n_workers 16 --suite_name u-cg282 --suite_version_number 227458 --suite_url https://code.metoffice.gov.uk/svn/roses-u/c/g/2/8/2/trunk --ofile_template /home/548/eh6215/cylc-run/cg282_ACCESS-CM2_historical_1960_sciB/share/cycle/19601101T0000Z/nc/SLV1H/{bom_name}-CMIP6-ACCESS-CM2-historical-r4i1p1f1-barpa_r-v1-{date1:%Y%m%d%H%M}-{date2:%Y%m%d%H%M}.nc --ofile_freq 1D --realization r4i1p1f1 --engine netcdf4 --output_format netcdf --version latest --rcm_model barpa_r</dd></dl></div></li></ul></div></div>"
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       "  * lon        (lon) float64 88.81 88.96 89.12 89.27 ... 206.7 206.8 207.0 207.2\n",
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       "    time_bnds  (time, bnds) datetime64[ns] dask.array<chunksize=(366, 2), meta=np.ndarray>\n",
       "Attributes: (12/56)\n",
       "    axiom_version:                  0.1.0\n",
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       "    Conventions:                    CF-1.9, ACDD-1.3\n",
       "    title:                          Bureau of Meteorology Atmospheric Regiona...\n",
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       "    history:                        Wed Jun 15 16:49:47 2022: /g/data/access/..."
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     "execution_count": 48,
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    "And finally the observations look like:"
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       "\n",
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       "\n",
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       "\n",
       ".xr-icon-database,\n",
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       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:    (lon: 886, bnds: 2, lat: 691, time: 44655)\n",
       "Coordinates:\n",
       "  * lon        (lon) float32 112.0 112.1 112.1 112.2 ... 156.1 156.1 156.2 156.2\n",
       "  * lat        (lat) float32 -44.5 -44.45 -44.4 -44.35 ... -10.1 -10.05 -10.0\n",
       "  * time       (time) datetime64[ns] 1900-01-01T09:00:00 ... 2022-04-05T09:00:00\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    lon_bnds   (lon, bnds) float32 dask.array&lt;chunksize=(886, 2), meta=np.ndarray&gt;\n",
       "    lat_bnds   (lat, bnds) float32 dask.array&lt;chunksize=(691, 2), meta=np.ndarray&gt;\n",
       "    time_bnds  (time, bnds) datetime64[ns] dask.array&lt;chunksize=(365, 2), meta=np.ndarray&gt;\n",
       "    precip     (time, lat, lon) float32 dask.array&lt;chunksize=(365, 691, 886), meta=np.ndarray&gt;\n",
       "Attributes: (12/33)\n",
       "    CDI:                           Climate Data Interface version ?? (http://...\n",
       "    history:                       Tue Sep 03 14:23:23 2019: cdo -O -z zip_4 ...\n",
       "    institution:                   Australian Bureau of Meteorology, GPO Box ...\n",
       "    Conventions:                   CF-1.6\n",
       "    geospatial_lat_min:            -44.525\n",
       "    geospatial_lat_max:            -9.975\n",
       "    ...                            ...\n",
       "    url:                           http://www.bom.gov.au/climate/\n",
       "    licence:                       Copyright for any data supplied by the Bur...\n",
       "    id:                            Australian Gridded Climate Data (AGCD)\n",
       "    summary:                       The daily and monthly rainfall data repres...\n",
       "    naming_authority:              au.gov.bom\n",
       "    CDO:                           Climate Data Operators version 1.7.0 (http...</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-4cf9ecfe-d89d-44c5-9bde-2ff22a0919b0' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-4cf9ecfe-d89d-44c5-9bde-2ff22a0919b0' 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'>lon</span>: 886</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lat</span>: 691</li><li><span class='xr-has-index'>time</span>: 44655</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-7ea0b940-713d-4487-972b-a71840ed6e99' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7ea0b940-713d-4487-972b-a71840ed6e99' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>112.0 112.1 112.1 ... 156.2 156.2</div><input id='attrs-6785600a-f7b5-40e0-9eea-e62e752f3149' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6785600a-f7b5-40e0-9eea-e62e752f3149' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d5464964-c544-4192-97d4-b2f9026b65b0' class='xr-var-data-in' type='checkbox'><label for='data-d5464964-c544-4192-97d4-b2f9026b65b0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd></dl></div><div class='xr-var-data'><pre>array([112.  , 112.05, 112.1 , ..., 156.15, 156.2 , 156.25], dtype=float32)</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'>float32</div><div class='xr-var-preview xr-preview'>-44.5 -44.45 -44.4 ... -10.05 -10.0</div><input id='attrs-073778b6-e93c-43ca-9206-ad088fd71d3e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-073778b6-e93c-43ca-9206-ad088fd71d3e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7fdc8c12-582d-48b1-bf57-fd804b9e2bc7' class='xr-var-data-in' type='checkbox'><label for='data-7fdc8c12-582d-48b1-bf57-fd804b9e2bc7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd></dl></div><div class='xr-var-data'><pre>array([-44.5 , -44.45, -44.4 , ..., -10.1 , -10.05, -10.  ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1900-01-01T09:00:00 ... 2022-04-...</div><input id='attrs-eb9ff15d-de83-4b57-97d4-31b501b7b9f6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eb9ff15d-de83-4b57-97d4-31b501b7b9f6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-82fd8d9d-7bb0-47b2-ab4b-44d5243f42b1' class='xr-var-data-in' type='checkbox'><label for='data-82fd8d9d-7bb0-47b2-ab4b-44d5243f42b1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1900-01-01T09:00:00.000000000&#x27;, &#x27;1900-01-02T09:00:00.000000000&#x27;,\n",
       "       &#x27;1900-01-03T09:00:00.000000000&#x27;, ..., &#x27;2022-04-03T09:00:00.000000000&#x27;,\n",
       "       &#x27;2022-04-04T09:00:00.000000000&#x27;, &#x27;2022-04-05T09:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2c9f62b8-8bd5-42a3-97c9-360f3c4b79a2' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2c9f62b8-8bd5-42a3-97c9-360f3c4b79a2' 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>lon_bnds</span></div><div class='xr-var-dims'>(lon, bnds)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(886, 2), meta=np.ndarray&gt;</div><input id='attrs-95a87e3f-f0dd-465d-a767-a4a97ccd7d4e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-95a87e3f-f0dd-465d-a767-a4a97ccd7d4e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8ed60ab8-b223-46f4-961b-f5667e306406' class='xr-var-data-in' type='checkbox'><label for='data-8ed60ab8-b223-46f4-961b-f5667e306406' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>precip</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=(365, 691, 886), meta=np.ndarray&gt;</div><input id='attrs-3f7d1eb6-e698-445c-8f5d-23df9a998469' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3f7d1eb6-e698-445c-8f5d-23df9a998469' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0f75f40e-99fe-401a-bd81-e2d26ac9f801' class='xr-var-data-in' type='checkbox'><label for='data-0f75f40e-99fe-401a-bd81-e2d26ac9f801' 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>lwe_thickness_of_precipitation_amount</dd><dt><span>long_name :</span></dt><dd>Daily precipitation</dd><dt><span>units :</span></dt><dd>mm</dd><dt><span>cell_methods :</span></dt><dd>time: sum</dd><dt><span>analysis_version_number :</span></dt><dd>3.01</dd><dt><span>number_of_stations_reporting :</span></dt><dd>2757</dd><dt><span>source :</span></dt><dd>Interpolated surface observations</dd><dt><span>frequency :</span></dt><dd>daily</dd><dt><span>length_scale_for_analysis :</span></dt><dd>80.0</dd><dt><span>analysis_time :</span></dt><dd>2010-10-23 14:49:46 UTC</dd></dl></div><div class='xr-var-data'><table>\n",
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       "Tue Jan 17 22:25:12 2017: conversion to netCDF, /cmap/script/utilities/aifs2nc/convert_aifs_binary.py /cmap/data/awap/rr.dir/daily_means_0.05.dir/1900/rr.1900123119001231.grid.un.gz /tmp/tmp.y1hsR4hgz3_precip_total_r005_19001231_19001231.nc --check-rpms --base-config-file /cmap/config/agcd/metadata/agcd_base.json --config-file /cmap/config/agcd/metadata/precip_total.json --overwrite --missval 99999.9</dd><dt><span>institution :</span></dt><dd>Australian Bureau of Meteorology, GPO Box 1289, Melbourne VIC 3001, Australia</dd><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>geospatial_lat_min :</span></dt><dd>-44.525</dd><dt><span>geospatial_lat_max :</span></dt><dd>-9.975</dd><dt><span>geospatial_lon_min :</span></dt><dd>111.975</dd><dt><span>geospatial_lon_max :</span></dt><dd>156.275</dd><dt><span>time_coverage_start :</span></dt><dd>1899-12-31T09:00:00</dd><dt><span>time_coverage_end :</span></dt><dd>1900-01-01T09:00:00</dd><dt><span>original_AIFS_header :</span></dt><dd>SOUTHWEST_LATITUDE: 44.5, SOUTHWEST_LONGITUDE: 112.0, NUMBER_OF_LONGITUDES_IN_GRID: 886, RAINFALL_ANALYSIS: 1900010119000101, LENGTH_SCALE_FOR_ANALYSIS: 80.0, BUREAU_OF_METEOROLOGY, NUMBER_OF_LATITUDES_IN_GRID: 691, GRID_INCREMENT_OF_LONGITUDE: 0.05, GRID_INCREMENT_OF_LATITUDE: 0.05, ROW_CHANGES_WITH_LONGITUDE, NUMBER_OF_STATIONS_REPORTING: 2757, ANALYSIS_TIME: 2010-10-23 14:49:46 UTC, COLUMN_NUMBER_AT_SOUTHWEST_CORNER: 1, ROW_NUMBER_AT_SOUTHWEST_CORNER: 1, ANALYSIS_VERSION_NUMBER: 3.01, LATITUDE_-_LONGITUDE_GRID</dd><dt><span>date_created :</span></dt><dd>2017-01-17T22:13:51.976225</dd><dt><span>bom-cmp-awap_version :</span></dt><dd>bom-cmp-awap-1.00-89.0.x86_64</dd><dt><span>bom-cmp-util_aifs2nc_version :</span></dt><dd>bom-cmp-util_aifs2nc-v1.1.0-2.x86_64</dd><dt><span>netcdf_version :</span></dt><dd>4.3.0 of Jul 16 2013 05:46:56 $</dd><dt><span>uuid :</span></dt><dd>14333ae2-28fe-4cb6-9f00-677adc94f25e</dd><dt><span>keywords_reference :</span></dt><dd>Global Change Master Directory (GCMD). 2015. GCMD Keywords, Version 8.1. Greenbelt, MD: Global Change Data Center, Science and Exploration Directorate, Goddard Space Flight Center (GSFC) National Aeronautics and Space Administration (NASA). URL:http://gcmd.nasa.gov/learn/keywords.html</dd><dt><span>acknowledgment :</span></dt><dd>The Australian Government, Bureau of Meteorology; The Australian Water Availability Project; The AusCover facility of the Terrestrial Ecosystem Research Network (TERN)</dd><dt><span>copyright :</span></dt><dd>(C) Copyright Commonwealth of Australia 2017, Bureau of Meteorology (ABN 92637 533532), see http://www.bom.gov.au/other/copyright.shtml for terms and conditions of reuse.</dd><dt><span>title :</span></dt><dd>Interpolated Rain Gauge Precipitation</dd><dt><span>keywords_vocabulary :</span></dt><dd>GCMD Science Keywords, Version 8.1</dd><dt><span>standard_name_vocabulary :</span></dt><dd>CF Standard Names, v28</dd><dt><span>keywords :</span></dt><dd>Earth Science, Atmosphere, Precipitation, Precipitation Amount, Liquid Water Equivalent</dd><dt><span>data_format :</span></dt><dd>netCDF4 with zlib compression</dd><dt><span>cdm_data_type :</span></dt><dd>Grid</dd><dt><span>analysis_components :</span></dt><dd>total: the gridded accumulation of rainfall.</dd><dt><span>references :</span></dt><dd>http://www.bom.gov.au/amm/docs/2009/jones_hres.pdf; http://www.csiro.au/awap; http://www.cawcr.gov.au/technical-reports/CTR_013.pdf</dd><dt><span>url :</span></dt><dd>http://www.bom.gov.au/climate/</dd><dt><span>licence :</span></dt><dd>Copyright for any data supplied by the Bureau of Meteorology is held in the Commonwealth of Australia and the purchaser shall give acknowledgement of the source in reference to the data. Apart from dealings under the Copyright Act 1968, the purchaser shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) these data without written permission from the supplier.</dd><dt><span>id :</span></dt><dd>Australian Gridded Climate Data (AGCD)</dd><dt><span>summary :</span></dt><dd>The daily and monthly rainfall data represents the amount of precipitation of any type (including the liquid equivalent of frozen hydrometeors such as hail and snow) observed by means of rain gauges stationed across Australia. These gauges measure millimetres of liquid water depth over a 24-hour period running from 9am local clock time the previous day to 9am on the observed day. Rainfall data from up to 6500 sites across the country are analysed, with limited quality control, onto 0.05x0.05 degree grids using the technique described in Jones et al. (2009). Monthly rainfall totals are calculated from the accumulation of the contributing daily rainfall totals, and may incorporate multi-day rainfall totals if observations were missing on any one day. Weekly rainfall totals are calculated from the sum of the daily grids. Multi-month rainfall totals are calculated from the sum of monthly grids. Month-to-date and Year-to-date rainfall grids are calculated from the sum of the contributing monthly and daily grids. </dd><dt><span>naming_authority :</span></dt><dd>au.gov.bom</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 1.7.0 (http://mpimet.mpg.de/cdo)</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:    (lon: 886, bnds: 2, lat: 691, time: 44655)\n",
       "Coordinates:\n",
       "  * lon        (lon) float32 112.0 112.1 112.1 112.2 ... 156.1 156.1 156.2 156.2\n",
       "  * lat        (lat) float32 -44.5 -44.45 -44.4 -44.35 ... -10.1 -10.05 -10.0\n",
       "  * time       (time) datetime64[ns] 1900-01-01T09:00:00 ... 2022-04-05T09:00:00\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    lon_bnds   (lon, bnds) float32 dask.array<chunksize=(886, 2), meta=np.ndarray>\n",
       "    lat_bnds   (lat, bnds) float32 dask.array<chunksize=(691, 2), meta=np.ndarray>\n",
       "    time_bnds  (time, bnds) datetime64[ns] dask.array<chunksize=(365, 2), meta=np.ndarray>\n",
       "    precip     (time, lat, lon) float32 dask.array<chunksize=(365, 691, 886), meta=np.ndarray>\n",
       "Attributes: (12/33)\n",
       "    CDI:                           Climate Data Interface version ?? (http://...\n",
       "    history:                       Tue Sep 03 14:23:23 2019: cdo -O -z zip_4 ...\n",
       "    institution:                   Australian Bureau of Meteorology, GPO Box ...\n",
       "    Conventions:                   CF-1.6\n",
       "    geospatial_lat_min:            -44.525\n",
       "    geospatial_lat_max:            -9.975\n",
       "    ...                            ...\n",
       "    url:                           http://www.bom.gov.au/climate/\n",
       "    licence:                       Copyright for any data supplied by the Bur...\n",
       "    id:                            Australian Gridded Climate Data (AGCD)\n",
       "    summary:                       The daily and monthly rainfall data repres...\n",
       "    naming_authority:              au.gov.bom\n",
       "    CDO:                           Climate Data Operators version 1.7.0 (http..."
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_obs"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "734a30f6-2da6-4a80-b06d-4dbf5038eeb1",
   "metadata": {},
   "source": [
    "## Prepare data for added value analysis\n",
    "This involves cutting all datasets to the same extend in time, latitude and longitude extension, which for now is the time period between 1960 and 1977,"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "3de29b6d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# da_gcm = ds_gcm[\"tasmax\"]\n",
    "# da_rcm = ds_rcm[\"tasmax\"]\n",
    "# da_obs = ds_obs[\"tmax\"] + 273.15 # Convert Celsius to Kelvin"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "0ed7f47f-a387-46eb-a210-1c8e576f2c8c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# da_gcm = ds_gcm[\"tasmin\"]\n",
    "# da_rcm = ds_rcm[\"tasmin\"]\n",
    "# da_obs = ds_obs[\"tmin\"] + 273.15 # Convert Celsius to Kelvin"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "852fd870-94c1-4ed1-9da9-46c00ab2d577",
   "metadata": {},
   "outputs": [],
   "source": [
    "da_gcm = ds_gcm[\"pr\"]*86400 # Convert kg/m2/s too mm/day\n",
    "da_rcm = ds_rcm[\"pr\"]*86400 # Convert kg/m2/s too mm/day\n",
    "da_obs = ds_obs[\"precip\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "4dceed99-f655-42dd-b0a2-e13b7ea538ee",
   "metadata": {},
   "outputs": [],
   "source": [
    "da_gcm = da_gcm.sel(time=slice(\"1960-01-01\",\"1977-12-31\"))\n",
    "da_rcm = da_rcm.sel(time=slice(\"1960-01-01\",\"1977-12-31\"))\n",
    "da_obs = da_obs.sel(time=slice(\"1960-01-01\",\"1977-12-31\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f30f1924-152b-4030-b501-a9e7a8658320",
   "metadata": {},
   "source": [
    "latitude between -44.5 to -9.8 and longitude between 111.5625 to 156.5625. For the gcm and obs data we keep a bit more to allow for the regridding to work properly."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "26132bbf-7add-4f3f-a478-a2568cb53bf1",
   "metadata": {},
   "outputs": [],
   "source": [
    "da_gcm = da_gcm.sel(lat=slice(-45.625,-9.375), lon=slice(111.5625,156.5625))\n",
    "da_rcm = da_rcm.sel(lat=slice(-44.5,-9.8), lon=slice(111.5625,156.5625))\n",
    "da_obs = da_obs.sel(lat=slice(-45.625,-9.375), lon=slice(111.5625,156.5625))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "375adcc0-9ff7-4127-948d-b823c3060f13",
   "metadata": {},
   "source": [
    "## Quantile calculations\n",
    "Now that we have the data in the correct shape lets calculate the quantiles. In this example we have chosen the 90th percentile. Because xarray cannot calculate quantiles over chunked dimensions we also have to re-chunk the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "7204307f-468a-4c46-8272-3bbf6a2e528a",
   "metadata": {},
   "outputs": [],
   "source": [
    "da_gcm = da_gcm.chunk({\"time\":None, \"lat\":\"auto\"})\n",
    "da_rcm = da_rcm.chunk({\"time\":None, \"lat\":\"auto\"})\n",
    "da_obs = da_obs.chunk({\"time\":None, \"lat\":\"auto\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "2e5211f2-da31-4152-831b-f8360b2d8e37",
   "metadata": {},
   "outputs": [],
   "source": [
    "q = 0.9\n",
    "X_gcm = da_gcm.quantile(q,\"time\", skipna=True).load()\n",
    "X_rcm = da_rcm.quantile(q,\"time\", skipna=True).load()\n",
    "X_obs = da_obs.quantile(q,\"time\", skipna=True).load()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "76901ca5-220f-4ce1-aea4-d54a7d5672ca",
   "metadata": {},
   "source": [
    "## Regridding and masking\n",
    "Before we can calculate added value we have to bring all data to the same grid. For now we will do this by bilinear interpolation of the global model data to the resolution of the regional model and conservative interpolation of the observation data to the regional model resolution."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "4256b99b-4eeb-4734-b03f-a9c82d720ba5",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/g/data/hh5/public/apps/miniconda3/envs/analysis3-22.01/lib/python3.9/site-packages/xesmf/frontend.py:594: UserWarning: Using dimensions ('lat', 'lon') from data variable pr as the horizontal dimensions for the regridding.\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "X_gcm = lib.regrid(X_gcm, X_rcm, method=\"bilinear\")\n",
    "X_gcm = X_gcm.rename({\"latitude\":\"lat\", \"longitude\":\"lon\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "39e99aac-32e5-4ac8-9129-8c34a21911f3",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/g/data/hh5/public/apps/miniconda3/envs/analysis3-22.01/lib/python3.9/site-packages/xesmf/frontend.py:594: UserWarning: Using dimensions ('lat', 'lon') from data variable precip as the horizontal dimensions for the regridding.\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "X_obs = lib.regrid(X_obs, X_rcm, method=\"conservative_normed\")\n",
    "X_obs = X_obs.rename({\"latitude\":\"lat\", \"longitude\":\"lon\"})"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dcf20a9a-64dc-43ed-8d0b-703c38f067ae",
   "metadata": {},
   "source": [
    "Round the coordinates to 4 digits before masking otherwise the coordinates are picked up as being different and xarray drops many grid-points."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "946baa7d-8a3d-4dd8-9c9b-bc30400c93c3",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_gcm[\"lat\"] = np.round(X_gcm[\"lat\"],4)\n",
    "X_gcm[\"lon\"] = np.round(X_gcm[\"lon\"],4)\n",
    "\n",
    "X_rcm[\"lat\"] = np.round(X_rcm[\"lat\"],4)\n",
    "X_rcm[\"lon\"] = np.round(X_rcm[\"lon\"],4)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d3be4d19-5f1d-4bab-81a7-001c66107eb2",
   "metadata": {},
   "source": [
    "We also have to mask the ocean. We do this after interpolating to GCM to the RCM grid to avoid a patchy coastline. This will favour the RCM along the coastline because the GCM \"land\" values will be a mix of ocean and land points."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "340d3a70-ad09-4a8d-ad40-c6afaed240e7",
   "metadata": {},
   "outputs": [],
   "source": [
    "#< Load the land sea mask from BARPA ancilary\n",
    "lsmask_rcm = xr.open_dataset(\"/g/data/tp28/dev/barpa/ancils/barpa-r/land_sea_mask/cci/qrparm.mask.nc\")[\"land_area_fraction\"]\n",
    "lsmask_rcm = lsmask_rcm.rename({\"latitude\":\"lat\", \"longitude\":\"lon\"})\n",
    "lsmask_rcm = lsmask_rcm.sel(lat=slice(-44.5,-9.8), lon=slice(111.5625,156.5625))\n",
    "\n",
    "#< Round coordinates to 4 digits\n",
    "lsmask_rcm[\"lat\"] = np.round(lsmask_rcm[\"lat\"],4)\n",
    "lsmask_rcm[\"lon\"] = np.round(lsmask_rcm[\"lon\"],4)\n",
    "\n",
    "#< Mask \n",
    "X_rcm = X_rcm.where(lsmask_rcm>0)\n",
    "X_gcm = X_gcm.where(lsmask_rcm>0)\n",
    "X_obs = X_obs.where(lsmask_rcm>0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "71d870a1-1b6a-46e2-919a-8330311774ea",
   "metadata": {},
   "source": [
    "Let's plot those three quantiles we have just calculate on a map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "235c31ae-dd6c-4133-b6c8-c54cbafb4617",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ds_plot = xr.concat([X_obs, X_gcm, X_rcm], dim=pd.Index([\"obs\",\"gcm\",\"rcm\"], name=\"model\"))\n",
    "p = ds_plot.plot.pcolormesh(col=\"model\", robust=True, transform=ccrs.PlateCarree(), subplot_kws={\"projection\": ccrs.PlateCarree()})\n",
    "plt.suptitle(f\"Tasmax - {q*100}th percentile\")\n",
    "for ax in p.axes.flat:\n",
    "    ax.coastlines()\n",
    "    ax.gridlines()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c465fb56-f410-43e8-baab-2116112e0dbf",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Added value"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c66a64f9-15a0-4e34-b51c-c0cd1f8de7dd",
   "metadata": {},
   "source": [
    "Now we can calculate the added value, measured as reduction in squared error, between the global and regional model data compared to observations. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "51abae24-c7eb-4577-ac41-9bfa3a4f55d0",
   "metadata": {},
   "outputs": [],
   "source": [
    "av = np.sqrt((X_gcm-X_obs)**2) - np.sqrt((X_rcm-X_obs)**2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1b5dd729-34c6-4b51-867b-b09c81ef785f",
   "metadata": {},
   "source": [
    "Let's plot the added value on a map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "a80dd943-4da3-4aca-943a-1656fc67ce98",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<cartopy.mpl.gridliner.Gridliner at 0x151b2fc44280>"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "p = av.plot.pcolormesh(robust=True, transform=ccrs.PlateCarree(), subplot_kws={\"projection\": ccrs.PlateCarree()})\n",
    "ax = p.axes\n",
    "ax.set_title(f\"added value - tasmax - {q*100}th percentile\")\n",
    "ax.coastlines()\n",
    "ax.gridlines()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "8999db47-66e5-4fe9-aad0-63fdb3c59371",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<cartopy.mpl.gridliner.Gridliner at 0x151b48564820>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "p = av.plot.pcolormesh(robust=True, transform=ccrs.PlateCarree(), subplot_kws={\"projection\": ccrs.PlateCarree()})\n",
    "ax = p.axes\n",
    "ax.set_title(f\"added value - tasmin - {q*100}th percentile\")\n",
    "ax.coastlines()\n",
    "ax.gridlines()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "3e7ac6f7-7d4a-4ff3-940e-022234333101",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<cartopy.mpl.gridliner.Gridliner at 0x151b2e9bf880>"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "p = av.plot.pcolormesh(robust=True, transform=ccrs.PlateCarree(), subplot_kws={\"projection\": ccrs.PlateCarree()})\n",
    "ax = p.axes\n",
    "ax.set_title(f\"added value - precip - {q*100}th percentile\")\n",
    "ax.coastlines()\n",
    "ax.gridlines()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "84dfc30e-506d-43d8-934a-030babe3535b",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:analysis3-22.01]",
   "language": "python",
   "name": "conda-env-analysis3-22.01-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}